{"meta":{"query_hash":"f756441951fd","filters":{"topic":"Advanced machining processes and optimization"},"cohort_total":1190,"direct_labels_cover":0,"predictions_cover":1190,"exported":1190,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/f756441951fd","api":"https://metacan.xera.ac/api/v1/cohort?topic=Advanced+machining+processes+and+optimization"},"results":[{"id":"W1033776241","doi":"10.1007/978-1-4020-6761-7_32","title":"Agility in High Speed Machining: Optimization between Tool and Holder","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Machining; Surface roughness; Torque; Surface finish; Mechanical engineering; Materials science; Engineering; Composite material; Physics","score_opus":0.021514012035879097,"score_gpt":0.2414786538715007,"score_spread":0.2199646418356216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1033776241","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020523308,0.004601004,0.918691,0.00026155196,0.0001898564,0.000036410733,0.000051981377,0.0005633973,0.055081476],"genre_scores_gemma":[0.6020822,0.006059378,0.27054211,0.00016155187,0.00034310526,0.0001856465,0.00025422973,0.0015930965,0.11877874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999666,0.000046105753,0.0000075719936,0.000054767763,0.00019284891,0.000032737647],"domain_scores_gemma":[0.9997274,0.00015159123,0.000030759675,0.000030275021,0.000048652746,0.000011283641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038342227,0.0011099962,0.00095653353,0.00046635015,0.00047478228,0.0010786204,0.0014081481,0.0011736299,0.006568775],"category_scores_gemma":[0.0006833363,0.0007931968,0.0006770119,0.00089690724,0.00077942654,0.0012518597,0.0007242617,0.0013521777,0.0017813662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081651495,0.00007131911,0.00035130366,0.0002651323,0.0000342618,0.0000611229,0.0000763043,0.71431303,0.023382885,0.048680816,0.005152592,0.20752963],"study_design_scores_gemma":[0.0000140762895,0.00015420781,0.0008602719,0.000047655,0.000030908046,0.00015524338,0.000034077537,0.9176716,0.011353489,0.053014893,0.0166309,0.00003264447],"about_ca_topic_score_codex":0.00065668416,"about_ca_topic_score_gemma":0.0011838238,"teacher_disagreement_score":0.006568775,"about_ca_system_score_codex":0.0005667671,"about_ca_system_score_gemma":0.00045738896,"threshold_uncertainty_score":0.021974802},"labels":[],"label_agreement":null},{"id":"W115214475","doi":"10.1007/978-3-662-43902-9_2","title":"Cutting Tool Materials and Tool Wear","year":2014,"lang":"en","type":"book-chapter","venue":"Materials forming, machining and tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Machining; Titanium alloy; Context (archaeology); Cutting tool; Titanium; Tool wear; Materials science; Mechanical engineering; Metallurgy; Computer science; Engineering; Manufacturing engineering; Alloy; Geology","score_opus":0.0070398735307123815,"score_gpt":0.20839803547257243,"score_spread":0.20135816194186004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W115214475","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18189824,0.35696307,0.071052745,0.0016242899,0.0025264123,0.000084822124,0.00048140742,0.00043049722,0.3849385],"genre_scores_gemma":[0.7025709,0.056326825,0.007472133,0.00028162688,0.00060501223,0.000044647342,0.00033084754,0.00023857388,0.23212942],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997063,0.00003112549,0.000010546376,0.000057723522,0.00015667299,0.00003762458],"domain_scores_gemma":[0.9997873,0.00012379323,0.00001941663,0.000027642032,0.0000345361,0.0000073502574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002299154,0.0005327683,0.0005075473,0.0008985295,0.00037172477,0.0016074582,0.0008159695,0.00093774655,0.008238556],"category_scores_gemma":[0.0007749695,0.00037539384,0.0002885162,0.00073275086,0.0007129714,0.0015084364,0.0006357133,0.0008582101,0.0010209413],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039376476,0.00018294003,0.0019241857,0.0016667214,0.000075063326,0.0008303743,0.00090147497,0.016679468,0.059294518,0.19316097,0.016079979,0.7088105],"study_design_scores_gemma":[0.00004535893,0.000642191,0.023346966,0.00069675833,0.00012636323,0.0046506207,0.0013762091,0.026413737,0.046022076,0.41517773,0.48133543,0.00016656966],"about_ca_topic_score_codex":0.00053534255,"about_ca_topic_score_gemma":0.00080044236,"teacher_disagreement_score":0.008238556,"about_ca_system_score_codex":0.00032196593,"about_ca_system_score_gemma":0.00019122826,"threshold_uncertainty_score":0.02756071},"labels":[],"label_agreement":null},{"id":"W121874510","doi":"10.1007/978-0-387-36594-7_2","title":"Tool Condition Monitoring in Machining - Neural Networks","year":2007,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Artificial neural network; Component (thermodynamics); Engineering; Manufacturing engineering; Condition monitoring; Computer science; Mechanical engineering; Artificial intelligence; Electrical engineering","score_opus":0.016558197164054028,"score_gpt":0.25424845635163507,"score_spread":0.23769025918758105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W121874510","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004563027,0.037501484,0.90150166,0.0004337284,0.0007461568,0.00004792059,0.00022072268,0.0011785228,0.053806778],"genre_scores_gemma":[0.20338055,0.053038877,0.501812,0.00050331734,0.0009994351,0.00017398054,0.0008295597,0.00057235203,0.23869003],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998215,0.000021594235,0.000010014832,0.00005087819,0.000084747786,0.000011271849],"domain_scores_gemma":[0.99986863,0.00007197985,0.000008032372,0.00001758901,0.00003109992,0.0000026711386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021325385,0.000617949,0.000503213,0.00031708225,0.00014035145,0.0008707041,0.0009049731,0.0011389316,0.0047947983],"category_scores_gemma":[0.0005290701,0.0003770485,0.00024158428,0.00089251774,0.00043645923,0.0016059552,0.0003683701,0.0008817124,0.002116504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004989744,0.0000456543,0.0002655562,0.0007218959,0.000032879667,0.0000950933,0.0000625764,0.088727295,0.01193494,0.058203455,0.016949879,0.8229108],"study_design_scores_gemma":[0.0000094532625,0.00007119849,0.0017775263,0.00036663478,0.000064160486,0.0005446931,0.000046686073,0.6429943,0.035661455,0.14602701,0.17236936,0.000067612695],"about_ca_topic_score_codex":0.0010109773,"about_ca_topic_score_gemma":0.0019282309,"teacher_disagreement_score":0.0047947983,"about_ca_system_score_codex":0.00045222038,"about_ca_system_score_gemma":0.00017491836,"threshold_uncertainty_score":0.016040206},"labels":[],"label_agreement":null},{"id":"W136368523","doi":"10.1007/978-1-4471-0777-4_40","title":"Closed Loop Dimensional Error Correction for 5 Axis Flexible Part Milling","year":2000,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Deflection (physics); Machine tool; Microcomputer; Computer science; Climb; Control theory (sociology); Process (computing); Control engineering; Simulation; Engineering; Mechanical engineering; Artificial intelligence; Optics; Control (management); Physics","score_opus":0.0197493615773424,"score_gpt":0.237389711505339,"score_spread":0.2176403499279966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W136368523","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005800576,0.00041705757,0.98919874,0.000032357995,0.00017172137,0.000014856391,0.000023775701,0.0010778415,0.0032631105],"genre_scores_gemma":[0.49003452,0.0008678082,0.46183988,0.00012775799,0.00014031095,0.00008990877,0.00027425622,0.00059259456,0.04603291],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999519,0.000039868486,0.000013012626,0.00006224398,0.0003449524,0.000020937969],"domain_scores_gemma":[0.99977237,0.000088019144,0.000023555313,0.000041037532,0.00007070945,0.0000042747615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026953878,0.0006327258,0.00041951291,0.0003017828,0.0003018982,0.00052841764,0.0009794972,0.0006088902,0.004165457],"category_scores_gemma":[0.0009071325,0.00031663818,0.00024834916,0.00035964287,0.0002991759,0.00059202116,0.00052615703,0.00072890293,0.0010010836],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022555701,0.000048625596,0.00023568729,0.00015353586,0.000030838088,0.00008336255,0.00013492562,0.09492923,0.06692945,0.008602013,0.0049691517,0.8236576],"study_design_scores_gemma":[0.000029990842,0.00021257841,0.0016675743,0.000059723534,0.000028473967,0.00026419127,0.00003876461,0.89486533,0.0697394,0.0067205485,0.026320055,0.00005330103],"about_ca_topic_score_codex":0.0013571255,"about_ca_topic_score_gemma":0.0021609736,"teacher_disagreement_score":0.004165457,"about_ca_system_score_codex":0.0002684754,"about_ca_system_score_gemma":0.00021376174,"threshold_uncertainty_score":0.01393491},"labels":[],"label_agreement":null},{"id":"W1482604268","doi":"10.4271/2005-01-3325","title":"Study of Positive Feed Drilling Parameters for Optimized Drilling in Stackups of Composite/Metallic Materials","year":2005,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell Helicopter Textron (Canada)","funders":"","keywords":"Drilling; Composite number; Materials science; Petroleum engineering; Geology; Composite material; Metallurgy","score_opus":0.013154718194336274,"score_gpt":0.25964543268438905,"score_spread":0.24649071449005278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1482604268","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9790692,0.0015193047,0.015506693,0.00006453353,0.000032150336,0.000060796177,0.00015624633,0.00016142902,0.0034298191],"genre_scores_gemma":[0.9921773,0.00022414052,0.007297696,0.000006246459,0.0000030484096,0.000018221843,0.000051565592,0.000027762559,0.00019401149],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997832,0.000043732383,0.000018086223,0.000037531787,0.000085623855,0.000031883086],"domain_scores_gemma":[0.99803156,0.0011992223,0.00034951066,0.00007229491,0.00031353981,0.00003384654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055692403,0.00037809883,0.00040792974,0.00064364943,0.00022053863,0.00048629576,0.00040557014,0.00050698087,0.0012448748],"category_scores_gemma":[0.0026908454,0.0002567243,0.00020344288,0.0004582515,0.00021230256,0.0005768921,0.00016982641,0.00019053483,0.00023817559],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035121792,0.00047147524,0.0072246906,0.0019028843,0.000057414985,0.00042217653,0.0005966068,0.106736846,0.7755584,0.001505869,0.0015917574,0.10041976],"study_design_scores_gemma":[0.000107850785,0.0033253415,0.011210571,0.00012279053,0.0001297425,0.00024843597,0.00042507937,0.13908987,0.8419544,0.00035979797,0.0029501643,0.00007594767],"about_ca_topic_score_codex":0.00062332326,"about_ca_topic_score_gemma":0.0012830506,"teacher_disagreement_score":0.0012448748,"about_ca_system_score_codex":0.00024483667,"about_ca_system_score_gemma":0.00027283165,"threshold_uncertainty_score":0.004164517},"labels":[],"label_agreement":null},{"id":"W1483455599","doi":"10.1007/978-3-540-39899-8_32","title":"Modelling and Optimization of Bone-Cutting Forces in Orthopaedic Surgery","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Machining; Computer science; Orientation (vector space); Mechanical engineering; Process (computing); Energy (signal processing); Geometry; Engineering; Mathematics; Artificial intelligence","score_opus":0.01252020869808821,"score_gpt":0.21423515530045684,"score_spread":0.20171494660236863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1483455599","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01826225,0.0045378073,0.959498,0.00027982387,0.00013069782,0.00004580545,0.00017093026,0.00039569533,0.016679084],"genre_scores_gemma":[0.582067,0.0071624136,0.36953795,0.00012377276,0.00014752922,0.00025232285,0.00041377018,0.0004982779,0.03979687],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997451,0.000042620035,0.000016282576,0.000033475953,0.00014055152,0.000022031189],"domain_scores_gemma":[0.9997837,0.00012137886,0.000028811204,0.00001692275,0.00003909619,0.000010068751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043102115,0.00074115413,0.0012445416,0.0005372111,0.0002880679,0.0011676206,0.0016748003,0.0017944974,0.0036173312],"category_scores_gemma":[0.00087735796,0.00095744076,0.00087478524,0.0009839779,0.0006715539,0.0008203298,0.00059236545,0.00076667045,0.0009398808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011078403,0.0000114564245,0.0000756432,0.000060560986,0.000008242936,0.000018848019,0.000016093974,0.9803665,0.0011343381,0.004443965,0.00033352504,0.013519756],"study_design_scores_gemma":[0.000004061385,0.000009735845,0.00009455759,0.000011372764,0.0000049182704,0.000023502678,0.000004770808,0.994093,0.00056299724,0.003750907,0.0014343648,0.000005841036],"about_ca_topic_score_codex":0.005482625,"about_ca_topic_score_gemma":0.0067716525,"teacher_disagreement_score":0.005482625,"about_ca_system_score_codex":0.0005888481,"about_ca_system_score_gemma":0.00081183924,"threshold_uncertainty_score":0.012101114},"labels":[],"label_agreement":null},{"id":"W1484694549","doi":"10.4271/2003-01-2915","title":"Adaptive Feedforward Chatter Suppression in Machining","year":2003,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Machining; Feed forward; Control theory (sociology); Computer science; Control engineering; Engineering; Mechanical engineering; Artificial intelligence; Control (management)","score_opus":0.009608132558143148,"score_gpt":0.2360962655031587,"score_spread":0.22648813294501557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1484694549","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09108444,0.0005511798,0.90148526,0.000103421335,0.00008657797,0.00006140493,0.000016581062,0.0009175789,0.005693612],"genre_scores_gemma":[0.96358943,0.00012328374,0.033072572,0.000044508324,0.000030193398,0.00003937706,0.000013923584,0.000019973524,0.00306681],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978584,0.000045221608,0.000010825761,0.00003732404,0.00009905134,0.000021768346],"domain_scores_gemma":[0.99960583,0.00017833973,0.00004656487,0.000027960978,0.00012685751,0.000014381964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036509146,0.0004279793,0.00037339318,0.00022745808,0.00025615218,0.0003449395,0.0007313152,0.0004975871,0.0011112129],"category_scores_gemma":[0.00093591976,0.0002073235,0.00019247876,0.00016115086,0.00034402125,0.00038103428,0.00036249898,0.0003636549,0.00021868135],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005086507,0.00020677727,0.0009111768,0.0003285969,0.000050379815,0.00029301958,0.00030918853,0.51790875,0.101488166,0.004595384,0.0012118984,0.37218797],"study_design_scores_gemma":[0.00002694563,0.00024358967,0.00047488033,0.000013283718,0.000013908252,0.000055984226,0.000009650719,0.984321,0.012718564,0.0012169214,0.0008964967,0.000008764491],"about_ca_topic_score_codex":0.0020680833,"about_ca_topic_score_gemma":0.0020524657,"teacher_disagreement_score":0.0020680833,"about_ca_system_score_codex":0.00028962965,"about_ca_system_score_gemma":0.00020864441,"threshold_uncertainty_score":0.0041121244},"labels":[],"label_agreement":null},{"id":"W1509230396","doi":"10.4271/2002-01-2568","title":"Optimization of CDCF Grinding of Turbine Blade","year":2002,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Pratt and Whitney Canada","keywords":"Blade (archaeology); Grinding; Turbine blade; Mechanical engineering; Computer science; Turbine; Engineering","score_opus":0.010464085574519404,"score_gpt":0.22476442057880217,"score_spread":0.21430033500428275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1509230396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8274048,0.0008012566,0.15779857,0.00014634221,0.000050096067,0.0001514777,0.00020198172,0.00045115798,0.012994297],"genre_scores_gemma":[0.9652385,0.000116702104,0.032846574,0.00001184178,0.0000025764614,0.00004062365,0.00012803511,0.00006284796,0.0015523648],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998493,0.000017943274,0.000004780013,0.000037196885,0.000058753045,0.00003195679],"domain_scores_gemma":[0.9997757,0.000079608464,0.000037087244,0.000015601416,0.00007697191,0.000015033326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036481014,0.00059779926,0.00051866006,0.0005022632,0.00028146728,0.0006105964,0.00038020554,0.00054665096,0.0012613353],"category_scores_gemma":[0.00094932195,0.0003736282,0.00035007577,0.00030470392,0.0002279233,0.00030530817,0.00021922623,0.00032024668,0.00023925691],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014384024,0.000115482915,0.0016976662,0.00013183382,0.000016878463,0.00008548936,0.000041958217,0.922366,0.03307609,0.00069685775,0.0006569838,0.04097098],"study_design_scores_gemma":[0.000029092478,0.0002684022,0.002349417,0.0000069171506,0.000010744147,0.000028152579,0.00003231482,0.9853093,0.010889495,0.00028937176,0.0007779228,0.0000089983105],"about_ca_topic_score_codex":0.006510364,"about_ca_topic_score_gemma":0.011560209,"teacher_disagreement_score":0.006510364,"about_ca_system_score_codex":0.0009440248,"about_ca_system_score_gemma":0.00090662757,"threshold_uncertainty_score":0.012944937},"labels":[],"label_agreement":null},{"id":"W1536322264","doi":"10.5772/51174","title":"Free Vibration Analysis of Spinning Spindles: A Calibrated Dynamic Stiffness Matrix Method","year":2012,"lang":"en","type":"book-chapter","venue":"InTech eBooks","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spinning; Vibration; Direct stiffness method; Stiffness; Materials science; Matrix (chemical analysis); Structural engineering; Stiffness matrix; Composite material; Physics; Acoustics; Engineering","score_opus":0.012375945826280352,"score_gpt":0.2770898628951549,"score_spread":0.26471391706887454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1536322264","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018970713,0.00041638268,0.9761955,0.00003922983,0.000039521565,0.000025427476,0.00010998575,0.0003661342,0.0038371468],"genre_scores_gemma":[0.5751846,0.0010099419,0.409708,0.00005089786,0.00006865273,0.00011898498,0.0005101636,0.0004045024,0.012944284],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997744,0.000035256533,0.000008313668,0.000045650322,0.0001250724,0.000011335448],"domain_scores_gemma":[0.9997056,0.00015672833,0.000023620862,0.000039788367,0.00006496583,0.0000092593655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022747695,0.0004708289,0.00043392362,0.00046513815,0.00021015543,0.00038256714,0.00093326444,0.00061045616,0.004985287],"category_scores_gemma":[0.0006691499,0.0002857674,0.0004471722,0.00036312573,0.0002817223,0.00077488576,0.00039360148,0.00050105155,0.000965283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021600936,0.0000976909,0.0006012298,0.00071238953,0.00006746225,0.00017530413,0.00025951175,0.29554978,0.23346496,0.017657368,0.0035603207,0.447638],"study_design_scores_gemma":[0.000011149547,0.00005543938,0.0012779764,0.000021930204,0.000010915777,0.00008856722,0.000033744484,0.98207736,0.011700768,0.002291052,0.0024126677,0.000018459934],"about_ca_topic_score_codex":0.0010903728,"about_ca_topic_score_gemma":0.001356175,"teacher_disagreement_score":0.004985287,"about_ca_system_score_codex":0.00015949058,"about_ca_system_score_gemma":0.00029001647,"threshold_uncertainty_score":0.01667738},"labels":[],"label_agreement":null},{"id":"W154627543","doi":"10.1007/1-84628-269-1_3","title":"Tool Condition Monitoring in Machining","year":2006,"lang":"en","type":"book-chapter","venue":"Springer series in advanced manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Transformation (genetics); Wavelet; Machine tool; Engineering; Drill; Computer science; Artificial neural network; Condition monitoring; Fuzzy logic; Vibration; Control engineering; Artificial intelligence; Mechanical engineering; Acoustics","score_opus":0.006215817889444398,"score_gpt":0.2165111827445651,"score_spread":0.2102953648551207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W154627543","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016934596,0.040369697,0.9058931,0.00023493354,0.0005738911,0.00009040201,0.00021949502,0.0029829154,0.03270093],"genre_scores_gemma":[0.51939327,0.032656062,0.35567823,0.00028531614,0.0007630862,0.00013304771,0.0005409889,0.0005287881,0.09002134],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995553,0.00005252282,0.000017644003,0.00010705973,0.00024151235,0.00002597991],"domain_scores_gemma":[0.99969685,0.0001612019,0.00002038155,0.00005149375,0.00006009789,0.000009996627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032861056,0.00053998997,0.00074968394,0.0007264481,0.00020823006,0.0010402753,0.0012602499,0.0011603871,0.005546139],"category_scores_gemma":[0.0007787447,0.00043762548,0.00023308652,0.0012441303,0.00056993857,0.001411678,0.0005576568,0.0005677187,0.0016235341],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001447839,0.0000631587,0.0006455505,0.00048119665,0.000020542893,0.000118485616,0.00011221844,0.0151409535,0.059179794,0.01129994,0.007017798,0.9057756],"study_design_scores_gemma":[0.000045930603,0.00071158493,0.01596651,0.00057340245,0.00014920354,0.0026588428,0.0002698668,0.4828052,0.19153613,0.073868304,0.2312189,0.00019606443],"about_ca_topic_score_codex":0.00052826887,"about_ca_topic_score_gemma":0.00078368257,"teacher_disagreement_score":0.005546139,"about_ca_system_score_codex":0.00029539445,"about_ca_system_score_gemma":0.00017061783,"threshold_uncertainty_score":0.018553734},"labels":[],"label_agreement":null},{"id":"W1575852113","doi":"10.1007/s00170-015-7869-5","title":"On tool–workpiece interactions during machining metal matrix composites: investigation of the effect of cutting speed","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"King Abdulaziz City for Science and Technology","keywords":"Machinability; Machining; Materials science; Mechanical engineering; Finite element method; Matrix (chemical analysis); Process (computing); Composite material; Metallurgy; Computer science; Structural engineering; Engineering","score_opus":0.006300091330984374,"score_gpt":0.25332130574162876,"score_spread":0.24702121441064437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1575852113","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99673456,0.0005409327,0.0020413557,0.000017268527,0.000014052179,0.0000074088207,0.000017193428,0.00002410384,0.00060315715],"genre_scores_gemma":[0.9986179,0.00014387391,0.00088524824,0.0000069109155,0.0000051595953,0.000002847207,0.00001901204,0.000016010265,0.00030307006],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99976367,0.000026865422,0.000008585755,0.000056609595,0.00008656086,0.000057730686],"domain_scores_gemma":[0.9987293,0.00085986534,0.00016850235,0.000056701043,0.0001471374,0.000038502083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027980414,0.0002941489,0.00043292853,0.0002556981,0.00046611638,0.00040341847,0.0003718733,0.0004341992,0.001854135],"category_scores_gemma":[0.00090167695,0.0003288281,0.00027331564,0.0002519524,0.00035816524,0.00045606194,0.00019453879,0.00033698315,0.0002200331],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012801493,0.00007931152,0.001784968,0.00017316407,0.000025493493,0.00020711648,0.00019227217,0.0046019913,0.98151726,0.000093429706,0.00009432507,0.009950426],"study_design_scores_gemma":[0.000041228323,0.0012821542,0.04841266,0.000020110869,0.000107399785,0.00034736472,0.00037868286,0.04805151,0.89982104,0.00011064037,0.0013739767,0.000053265256],"about_ca_topic_score_codex":0.00081658707,"about_ca_topic_score_gemma":0.0015356877,"teacher_disagreement_score":0.001854135,"about_ca_system_score_codex":0.00021055175,"about_ca_system_score_gemma":0.00022763359,"threshold_uncertainty_score":0.006202638},"labels":[],"label_agreement":null},{"id":"W1577263459","doi":"10.4271/2004-01-2826","title":"High Speed Machining of Helicopter Gearcases","year":2004,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell Helicopter Textron (Canada)","funders":"University of Florida","keywords":"Machining; Computer science; Mechanical engineering; Automotive engineering; Marine engineering; Engineering","score_opus":0.009204574509282842,"score_gpt":0.23778380892294979,"score_spread":0.22857923441366695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1577263459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9563119,0.0005495909,0.020916687,0.000070331924,0.000047464186,0.000057984984,0.00011631438,0.00028666964,0.021643147],"genre_scores_gemma":[0.9811141,0.00015281283,0.012344173,0.000014304306,0.000009677725,0.000012397989,0.00014686915,0.000019433885,0.0061862655],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997781,0.000025743331,0.000007891381,0.000031388565,0.00012314037,0.000033786444],"domain_scores_gemma":[0.99967754,0.00009172803,0.000050335817,0.00006282786,0.00009289385,0.000024670328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020586976,0.00024304855,0.00014298501,0.00035255574,0.000287478,0.0003881673,0.00023593035,0.00020980166,0.004705609],"category_scores_gemma":[0.00049477274,0.00013521487,0.00013137635,0.00025633958,0.00025359265,0.00026507027,0.00020018841,0.00016373582,0.000595874],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028059268,0.000076482596,0.0021477237,0.00024006683,0.000014792436,0.00043073785,0.00022201851,0.007519928,0.86718154,0.0017431639,0.0019283006,0.11821469],"study_design_scores_gemma":[0.000057065357,0.0011549384,0.022246748,0.000026718231,0.000014717824,0.0008296379,0.00020041826,0.027843062,0.9279838,0.00092068687,0.018692715,0.000029477464],"about_ca_topic_score_codex":0.0009267702,"about_ca_topic_score_gemma":0.0016900462,"teacher_disagreement_score":0.004705609,"about_ca_system_score_codex":0.00019209339,"about_ca_system_score_gemma":0.00013857098,"threshold_uncertainty_score":0.015741825},"labels":[],"label_agreement":null},{"id":"W1616414718","doi":"10.1016/j.surfcoat.2015.08.073","title":"Tribological behavior of Al–6.5%, –12%, –18.5% Si alloys during machining using CVD diamond and DLC coated tools","year":2015,"lang":"en","type":"article","venue":"Surface and Coatings Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Eutectic system; Materials science; Diamond; Metallurgy; Tribology; Drilling; Aluminium; Coating; Diamond-like carbon; Carbon fibers; Chemical vapor deposition; Machining; Composite material; Alloy; Thin film; Nanotechnology","score_opus":0.029446205809381083,"score_gpt":0.2681751157124918,"score_spread":0.23872890990311071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1616414718","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99855536,0.0002564865,0.00024506482,0.000016695778,0.000014609219,0.00000535109,0.00015063648,0.000017720604,0.0007380456],"genre_scores_gemma":[0.9984573,0.000071300594,0.00035495296,0.0000069886414,0.0000027118133,0.0000034584014,0.00011365347,0.000007470054,0.0009820279],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997161,0.000025022257,0.000023608183,0.000059305024,0.00012211534,0.000053755222],"domain_scores_gemma":[0.99965584,0.000087394474,0.00003154087,0.000037288057,0.00015981004,0.000028066197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023765817,0.00027423416,0.00038015717,0.00035113987,0.00038999124,0.0003819979,0.00043877316,0.00044627345,0.00203316],"category_scores_gemma":[0.00059546944,0.00023871848,0.00019630726,0.00033517563,0.00024408942,0.00023818194,0.00011197006,0.00034689324,0.00035064094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006951613,0.000040876384,0.002611897,0.00008810273,0.000020812191,0.00019771648,0.00026884847,0.0012076857,0.98902905,0.00010364716,0.00024402993,0.005492174],"study_design_scores_gemma":[0.000021149594,0.0006713698,0.037161227,0.000013067743,0.00003900154,0.0001397393,0.00036835877,0.009276657,0.9500838,0.000052389798,0.002148911,0.00002433245],"about_ca_topic_score_codex":0.0036206602,"about_ca_topic_score_gemma":0.00801395,"teacher_disagreement_score":0.0036206602,"about_ca_system_score_codex":0.0003725654,"about_ca_system_score_gemma":0.00026173374,"threshold_uncertainty_score":0.007199168},"labels":[],"label_agreement":null},{"id":"W1626243892","doi":"10.1109/imc.1990.687288","title":"Direct Adaptive Control of Milling Force","year":2005,"lang":"en","type":"article","venue":"Proceedings of the IEEE International Workshop on Intelligent Motion Control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control (management); Computer science; Artificial intelligence","score_opus":0.014022592634266163,"score_gpt":0.24519490889701587,"score_spread":0.2311723162627497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1626243892","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06548632,0.00064528093,0.91888773,0.00021968527,0.00036601906,0.00003912269,0.000035584366,0.0006851943,0.013634952],"genre_scores_gemma":[0.95416194,0.00020768965,0.03693292,0.000080511156,0.0000829694,0.00004809756,0.00002996905,0.000027475062,0.008428515],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99988794,0.000012161497,0.0000041142503,0.000030287101,0.000051917144,0.000013399455],"domain_scores_gemma":[0.9997336,0.00012766292,0.000025064419,0.000032386957,0.000069093105,0.000012132516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001555488,0.00030177302,0.00024715767,0.00019888347,0.00021264025,0.00048488975,0.00041007984,0.00030043328,0.0022530283],"category_scores_gemma":[0.00087960117,0.00017092444,0.00013671097,0.00013510583,0.00028383546,0.00024755957,0.00047527178,0.00046178148,0.00029037226],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006128351,0.00014520242,0.0009758098,0.00026589402,0.00006233689,0.00014453236,0.00018478815,0.20822637,0.16391253,0.015244147,0.0039577438,0.60626787],"study_design_scores_gemma":[0.000060665516,0.00010977775,0.0011897611,0.000009172086,0.000012627589,0.000054054937,0.000011804022,0.97557676,0.015954552,0.0030003628,0.004007519,0.000012959829],"about_ca_topic_score_codex":0.0016615078,"about_ca_topic_score_gemma":0.003323175,"teacher_disagreement_score":0.0022530283,"about_ca_system_score_codex":0.00017986278,"about_ca_system_score_gemma":0.0002277619,"threshold_uncertainty_score":0.0075371265},"labels":[],"label_agreement":null},{"id":"W1669088529","doi":"10.1007/s00170-015-7758-y","title":"Experimental investigation on 3D chip morphology properties of rotary surface during orthogonal turn-milling of aluminum alloy","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; University of British Columbia; National Natural Science Foundation of China","keywords":"Alloy; Aluminium; Materials science; Turn (biochemistry); Morphology (biology); Industrial and production engineering; Metallurgy; Chip; Surface (topology); Composite material; Mechanical engineering; Engineering; Geometry; Chemistry; Mathematics","score_opus":0.01901229918998861,"score_gpt":0.23180682726825153,"score_spread":0.2127945280782629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1669088529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972945,0.00012469794,0.0016012639,0.000016230122,0.000009975944,0.0000069853036,0.000081820246,0.000039314546,0.0008251598],"genre_scores_gemma":[0.99881494,0.00003917537,0.00071625103,0.0000065328654,0.0000023587722,0.0000040810573,0.000038952516,0.000010078161,0.00036755294],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981374,0.000012655647,0.000006546587,0.00004578274,0.00008620674,0.000035106263],"domain_scores_gemma":[0.9995883,0.00013766388,0.000073915195,0.000060791932,0.00012320497,0.00001612129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016825939,0.00018547423,0.00022780229,0.00015286145,0.0003231486,0.00030449047,0.00026490985,0.00032934826,0.0018784094],"category_scores_gemma":[0.00043473535,0.0002494584,0.00021279785,0.00021506831,0.00036319738,0.0002877421,0.00016245486,0.0002796148,0.00018414874],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002216532,0.000032941152,0.0016404856,0.00006909219,0.0000073083806,0.00012671668,0.00026216224,0.000752074,0.99124545,0.000094380826,0.00014477877,0.00540288],"study_design_scores_gemma":[0.000013752177,0.0004331006,0.038946614,0.0000051205657,0.000024024466,0.00014612288,0.00033484356,0.0072103003,0.9516836,0.000047437068,0.0011297539,0.000025380823],"about_ca_topic_score_codex":0.0010675025,"about_ca_topic_score_gemma":0.0021977925,"teacher_disagreement_score":0.0018784094,"about_ca_system_score_codex":0.00024032667,"about_ca_system_score_gemma":0.00019238776,"threshold_uncertainty_score":0.006283939},"labels":[],"label_agreement":null},{"id":"W17072261","doi":"10.1007/978-3-662-43902-9_1","title":"Machinability and Machining of Titanium Alloys: A Review","year":2014,"lang":"en","type":"review","venue":"Materials forming, machining and tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machinability; Machining; Metallurgy; Materials science; Titanium alloy; Titanium; Lubrication; Surface roughness; Surface integrity; Tool wear; Chip formation; Surface finish; Composite material; Alloy","score_opus":0.014333593118467111,"score_gpt":0.29451923601106195,"score_spread":0.28018564289259484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W17072261","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004744554,0.99858224,0.00022452074,0.00005367434,0.00008022676,0.0000047005606,0.000015373804,0.0000039925035,0.0005609859],"genre_scores_gemma":[0.0016496272,0.99713945,0.0003713559,0.00004848216,0.00011705799,0.0000055477853,0.00003229467,0.0000017493363,0.0006344108],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997074,0.000027582946,0.000049001144,0.000055288794,0.00013891306,0.000021720913],"domain_scores_gemma":[0.99962056,0.00018121426,0.000095470714,0.000011894849,0.00007679068,0.000014095568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005070657,0.00094115455,0.001236488,0.0023453562,0.00027309815,0.00098397,0.001304026,0.0011417223,0.0025450517],"category_scores_gemma":[0.0007559309,0.0004654282,0.0005666642,0.0027314993,0.00042335351,0.001141377,0.0005264826,0.0007876382,0.00096405187],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009016827,0.00012590822,0.0003963596,0.051830012,0.0001409035,0.00023752256,0.000089880916,0.0009695283,0.012922034,0.0022647385,0.008927337,0.92200553],"study_design_scores_gemma":[0.000024232679,0.00034508735,0.0025584733,0.004319234,0.00042795154,0.001983613,0.00013197395,0.00047037084,0.0076887025,0.0022427076,0.9797489,0.000058737485],"about_ca_topic_score_codex":0.0009255083,"about_ca_topic_score_gemma":0.001740204,"teacher_disagreement_score":0.0025450517,"about_ca_system_score_codex":0.00029103522,"about_ca_system_score_gemma":0.00088162004,"threshold_uncertainty_score":0.008514047},"labels":[],"label_agreement":null},{"id":"W1735023290","doi":"10.1115/1.4030305","title":"A Three-Dimensional Transient Thermal Model for Machining","year":2015,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Transient (computer programming); Discretization; Thermal; Chip formation; Mechanical engineering; Chip; Transient response; Finite element method; Drilling; Finite difference method; Materials science; Mechanics; Engineering; Computer science; Tool wear; Structural engineering; Mathematics; Mathematical analysis; Physics; Thermodynamics","score_opus":0.018241660886197945,"score_gpt":0.22968784582631488,"score_spread":0.21144618494011694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1735023290","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0069335448,0.00017907881,0.98389673,0.000101390964,0.000055442706,0.000045841,0.00014590222,0.00033125127,0.008310848],"genre_scores_gemma":[0.80794936,0.0010558306,0.15955412,0.00016144727,0.000087972374,0.0009102901,0.0007909808,0.00028358994,0.029206434],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997831,0.000041891737,0.000012148932,0.000048272486,0.000091291564,0.000023349217],"domain_scores_gemma":[0.99981576,0.000075176664,0.000025936839,0.000025201834,0.000047574256,0.0000103929615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029731318,0.00065505516,0.0006626801,0.0003331203,0.00036989295,0.0008332502,0.0014244614,0.0013686228,0.003584924],"category_scores_gemma":[0.000735522,0.00038050287,0.00095830095,0.0004530559,0.00062865455,0.0009011805,0.0005433775,0.0010727855,0.0008122037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001949897,0.000017361126,0.00012692706,0.00005380214,0.000008445997,0.000055984285,0.000039126255,0.9697918,0.0053006024,0.019594736,0.00040415945,0.0045875646],"study_design_scores_gemma":[0.0000032487928,0.00000787466,0.000041370946,0.0000026133382,0.0000026853293,0.00001466756,0.0000030831789,0.99654144,0.0005494794,0.0013576678,0.0014721978,0.000003698982],"about_ca_topic_score_codex":0.0037704292,"about_ca_topic_score_gemma":0.0018917666,"teacher_disagreement_score":0.0037704292,"about_ca_system_score_codex":0.00071554945,"about_ca_system_score_gemma":0.00084504526,"threshold_uncertainty_score":0.011992753},"labels":[],"label_agreement":null},{"id":"W1824513792","doi":"10.1007/s00170-015-7919-z","title":"Force model for impact cutting grinding with a flexible robotic tool holder","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hydro-Québec; École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Mechanical engineering; Chip; Energy consumption; Process (computing); Specific energy; Energy (signal processing); Grinding wheel; Computer science; Automotive engineering; Materials science; Engineering; Process engineering; Mathematics","score_opus":0.017545936033819532,"score_gpt":0.2784590027877211,"score_spread":0.2609130667539016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1824513792","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13544376,0.0008957374,0.790287,0.000720162,0.00027062898,0.0002921741,0.0006525453,0.0007264159,0.07071157],"genre_scores_gemma":[0.9432357,0.00046997174,0.022143092,0.000083034734,0.000044054184,0.00019520191,0.00022810731,0.00010590468,0.03349496],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975735,0.000025551895,0.00001039747,0.00005307974,0.00010833958,0.000045296198],"domain_scores_gemma":[0.99978465,0.000079375684,0.000039694034,0.00001994263,0.000054019984,0.000022342101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003570668,0.00075317046,0.0008227747,0.0006517824,0.0006792636,0.0008313393,0.0017702195,0.0030515927,0.006571735],"category_scores_gemma":[0.0006204699,0.00046220465,0.00080308085,0.0005168883,0.00080672256,0.0007826355,0.0006055295,0.000719937,0.0008817414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040666775,0.000048197795,0.0002590721,0.00005528756,0.000011925729,0.00017125008,0.000038866656,0.98303545,0.0053101806,0.0058872392,0.00032686474,0.004815043],"study_design_scores_gemma":[0.0000067703486,0.000013258342,0.00012617768,0.0000020343305,0.0000023529205,0.000014333416,0.000004650655,0.9990802,0.00024483286,0.0002919248,0.00020959586,0.0000037553693],"about_ca_topic_score_codex":0.021849703,"about_ca_topic_score_gemma":0.011367704,"teacher_disagreement_score":0.021849703,"about_ca_system_score_codex":0.0008248303,"about_ca_system_score_gemma":0.0011933879,"threshold_uncertainty_score":0.04344505},"labels":[],"label_agreement":null},{"id":"W1829588277","doi":"10.1007/s00170-015-7971-8","title":"On the machinability of die/mold D2 steel material","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Machinability; Mold; Machining; Surface roughness; Metallurgy; Materials science; Die (integrated circuit); Surface integrity; Surface finish; Tool wear; Composite material","score_opus":0.00974788020382589,"score_gpt":0.24214550409793267,"score_spread":0.2323976238941068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1829588277","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9873875,0.0010297514,0.0043371785,0.00006801471,0.000021923228,0.000014702426,0.00009471228,0.000038319846,0.0070079775],"genre_scores_gemma":[0.9967468,0.00018698393,0.001047485,0.000012918796,0.00000661554,0.00000467861,0.00009769589,0.000021263002,0.0018754472],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980026,0.0000214763,0.0000074122145,0.000044542856,0.00009409429,0.000032322343],"domain_scores_gemma":[0.99934906,0.00033375862,0.00009334164,0.000072139424,0.00013006611,0.0000215127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032880207,0.0003025139,0.00020416146,0.000461103,0.00033230096,0.000366143,0.000416702,0.00039916515,0.0030243536],"category_scores_gemma":[0.0011675428,0.00015509487,0.00022337952,0.00022002049,0.0003481763,0.00040925486,0.00024672566,0.00029008614,0.00032647065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00095235906,0.000061926956,0.0036680223,0.00032915754,0.000032753534,0.00031933346,0.000120112556,0.038842287,0.93070376,0.0027652509,0.0004002658,0.021804767],"study_design_scores_gemma":[0.00003703969,0.0012301062,0.03321657,0.000022740845,0.00004674305,0.0002533592,0.00010909747,0.11122519,0.8494966,0.00092414935,0.0034018166,0.000036481546],"about_ca_topic_score_codex":0.0010326653,"about_ca_topic_score_gemma":0.0017362896,"teacher_disagreement_score":0.0030243536,"about_ca_system_score_codex":0.00035156345,"about_ca_system_score_gemma":0.00015725322,"threshold_uncertainty_score":0.010117412},"labels":[],"label_agreement":null},{"id":"W1851214885","doi":"10.1007/s00158-015-1324-y","title":"Drilling optimization of woven CFRP laminates under different tool wear conditions: a multi-objective design of experiments approach","year":2015,"lang":"en","type":"article","venue":"Structural and Multidisciplinary Optimization","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Ministerio de Economía y Competitividad","keywords":"Drilling; Factorial experiment; Thrust; Design of experiments; Woven fabric; Abrasive; Materials science; Composite laminates; Response surface methodology; Delamination (geology); Carbon fiber reinforced polymer; Composite number; Engineering design process; Composite material; Structural engineering; Computer science; Mechanical engineering; Engineering; Geology; Mathematics","score_opus":0.03090484833856814,"score_gpt":0.28002693663409306,"score_spread":0.24912208829552493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1851214885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9041491,0.0004743514,0.09147512,0.00006430487,0.00003264084,0.000111344445,0.00010698684,0.00010598957,0.0034800817],"genre_scores_gemma":[0.9780041,0.00016233878,0.0210829,0.000009110171,0.0000033340643,0.00008564194,0.00004818802,0.000018379933,0.00058592437],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997328,0.00008717146,0.00001528742,0.00004058452,0.00006796038,0.00005630891],"domain_scores_gemma":[0.99866796,0.00086768036,0.00020233198,0.00007001434,0.00015623184,0.00003582868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012426357,0.00085818925,0.0012123106,0.0006150479,0.00033678804,0.00080386066,0.00047156887,0.0010978449,0.00094150304],"category_scores_gemma":[0.0017245954,0.0005372656,0.0009720969,0.00033570584,0.0005437308,0.00063954515,0.0003771862,0.0004641343,0.00008014309],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029153455,0.00015520418,0.00047608998,0.0002742051,0.00002965855,0.00006506528,0.000049608556,0.96515465,0.02663081,0.00071940525,0.000063076666,0.0060906694],"study_design_scores_gemma":[0.000046872374,0.000935386,0.00088468165,0.000019029978,0.000040543233,0.000021319373,0.00006690795,0.97692114,0.02050959,0.00028164385,0.0002556304,0.000017351398],"about_ca_topic_score_codex":0.0010996368,"about_ca_topic_score_gemma":0.0013639468,"teacher_disagreement_score":0.0012426357,"about_ca_system_score_codex":0.00034748294,"about_ca_system_score_gemma":0.00059069385,"threshold_uncertainty_score":0.0065717697},"labels":[],"label_agreement":null},{"id":"W1860386002","doi":"10.1080/10910344.2015.1018537","title":"Evaluation of Present Numerical Models for Predicting Metal Cutting Performance And Residual Stresses","year":2015,"lang":"en","type":"article","venue":"Machining Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"École Nationale d’Ingénieurs de Saint-Etienne; Politecnico di Torino; Bilkent Üniversitesi; McGill University; Karlsruhe Institute of Technology; National Institute of Standards and Technology; Eidgenössische Technische Hochschule Zürich; Università degli Studi di Brescia; Indian National Science Academy","keywords":"Machining; Finite element method; Benchmark (surveying); Residual; Predictive modelling; Range (aeronautics); Work (physics); Computer simulation; Computer science; Performance prediction; Numerical analysis; Mechanical engineering; Structural engineering; Engineering; Algorithm; Simulation; Mathematics; Machine learning; Geology","score_opus":0.036309545656923604,"score_gpt":0.29486998137863984,"score_spread":0.2585604357217162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1860386002","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5491771,0.0027355726,0.424407,0.0003363007,0.00012015691,0.00028399046,0.0008827012,0.0019362369,0.020120982],"genre_scores_gemma":[0.9413355,0.0009062369,0.05603613,0.000020171889,0.000016809747,0.00016715852,0.00046939374,0.00006740514,0.0009811539],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987494,0.00024836627,0.00008088796,0.00011326618,0.000758107,0.00005003678],"domain_scores_gemma":[0.9974854,0.001181894,0.00024443364,0.00049230113,0.00056313566,0.00003276458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024715248,0.000815296,0.0006981595,0.0012636068,0.00047717383,0.0009832263,0.001954611,0.00093727844,0.00094154384],"category_scores_gemma":[0.0057103615,0.00033755228,0.0006057512,0.001010737,0.0004986283,0.001079773,0.0004967606,0.00060919696,0.00035365936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011458827,0.00012935867,0.0040638554,0.00018881551,0.000026883417,0.000044601507,0.00006314679,0.9436668,0.0075891656,0.0031405857,0.00025588236,0.040716317],"study_design_scores_gemma":[0.000007179108,0.00014731464,0.0013648125,0.000022958076,0.000015473177,0.000024831295,0.000026635747,0.9887798,0.008493854,0.0004599879,0.00064386317,0.000013317511],"about_ca_topic_score_codex":0.0031059934,"about_ca_topic_score_gemma":0.00281188,"teacher_disagreement_score":0.0031059934,"about_ca_system_score_codex":0.0009089616,"about_ca_system_score_gemma":0.0007340291,"threshold_uncertainty_score":0.013070822},"labels":[],"label_agreement":null},{"id":"W1869606799","doi":"10.5539/mer.v5n2p45","title":"Enhancement of the Capabilities of CNC Machines via the Addition of a New Counter boring Cycle with a Milling Cutter","year":2015,"lang":"en","type":"article","venue":"Mechanical Engineering Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Subroutine; Numerical control; Transformation matrix; Mechanical engineering; Cnc milling; Drilling; Machining; Diagonal; Engineering drawing; Computer science; Engineering; Algorithm; Geometry; Mathematics; Programming language","score_opus":0.025819111849980605,"score_gpt":0.2778954249837654,"score_spread":0.2520763131337848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1869606799","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0636964,0.0005303396,0.8957244,0.00020255882,0.00020326747,0.00039915022,0.00030097246,0.0122885145,0.02665429],"genre_scores_gemma":[0.22314912,0.00023335137,0.7655747,0.00014102519,0.000052068026,0.00021911172,0.0004681995,0.0011800476,0.008982365],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984621,0.00011534279,0.00009223481,0.00030742094,0.00091584923,0.00010702027],"domain_scores_gemma":[0.99795306,0.00048369373,0.00017303502,0.0006759823,0.00064227433,0.00007188671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001059638,0.0008650033,0.0004878313,0.0014135372,0.00031762535,0.0009379587,0.0016879588,0.0004851947,0.0052266642],"category_scores_gemma":[0.0026555387,0.00048431562,0.00040327082,0.0010001513,0.0006418096,0.0012295241,0.0007836729,0.0010210031,0.0014613444],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047120883,0.00017052972,0.0046691825,0.000663792,0.000026360962,0.00020379199,0.0003486834,0.015535328,0.2260715,0.02219359,0.0070209806,0.722625],"study_design_scores_gemma":[0.00015193071,0.0013488444,0.018434582,0.00023044879,0.00014617947,0.002871794,0.00007806427,0.27650765,0.3345556,0.0058948826,0.35949677,0.0002832701],"about_ca_topic_score_codex":0.0021974507,"about_ca_topic_score_gemma":0.0033899813,"teacher_disagreement_score":0.0052266642,"about_ca_system_score_codex":0.0006658819,"about_ca_system_score_gemma":0.0016493864,"threshold_uncertainty_score":0.017484963},"labels":[],"label_agreement":null},{"id":"W1870235474","doi":"10.1007/s00170-015-7346-1","title":"Analysis of tool-particle interactions during cutting process of metal matrix composites","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Materials science; Machining; Particle (ecology); Matrix (chemical analysis); Process (computing); Finite element method; Composite material; Mechanical engineering; Fracture (geology); Computer science; Structural engineering; Engineering; Metallurgy","score_opus":0.008217649530549454,"score_gpt":0.28401377110105525,"score_spread":0.2757961215705058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1870235474","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964657,0.0002257715,0.0024783784,0.000012488831,0.000008708438,0.0000066428524,0.000037463225,0.000029895304,0.00073511305],"genre_scores_gemma":[0.99850094,0.000058880654,0.0009632003,0.0000041347603,0.0000021521428,0.0000031178681,0.000036301306,0.000009176649,0.00042212987],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99986553,0.000008493871,0.0000032705127,0.000028779921,0.000068925496,0.000025041276],"domain_scores_gemma":[0.9997371,0.00012201581,0.00004505256,0.000011959916,0.000066423294,0.000017544211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001243792,0.00016065637,0.00019914002,0.00031540653,0.00032739353,0.00025359436,0.00023846599,0.00031870793,0.00090594956],"category_scores_gemma":[0.00028572654,0.00017620432,0.0002485749,0.0002458064,0.00014645224,0.00025995806,0.00010552653,0.0003200413,0.00013347855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049731653,0.000053905977,0.0028722642,0.00007903439,0.000019791998,0.00020309901,0.00010277452,0.0028257738,0.98418,0.00013391164,0.00011936023,0.008912675],"study_design_scores_gemma":[0.000013331856,0.0004054092,0.052334268,0.000005626816,0.000057062512,0.00022589699,0.00017999501,0.05516078,0.89051425,0.00009517391,0.0009785361,0.000029529569],"about_ca_topic_score_codex":0.0016585294,"about_ca_topic_score_gemma":0.0025419912,"teacher_disagreement_score":0.0016585294,"about_ca_system_score_codex":0.00021098061,"about_ca_system_score_gemma":0.00019405082,"threshold_uncertainty_score":0.0032978058},"labels":[],"label_agreement":null},{"id":"W1944569693","doi":"10.5267/j.dsl.2015.7.003","title":"Selection of a suitable multiresponse optimization technique for turning operation","year":2015,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Mathematical optimization; Computer science; Engineering; Mathematics; Artificial intelligence","score_opus":0.019638916100195906,"score_gpt":0.2950470234788042,"score_spread":0.27540810737860827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1944569693","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.063013405,0.00033465523,0.93271774,0.00008988079,0.000030748375,0.00017994555,0.000058576363,0.00044238495,0.003132693],"genre_scores_gemma":[0.44600245,0.00029928156,0.55130816,0.000041014453,0.00001733868,0.0004848821,0.00012757952,0.00017906999,0.0015402198],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993956,0.00024729685,0.00003140721,0.00010020733,0.00017659439,0.000048838923],"domain_scores_gemma":[0.9994542,0.00030931906,0.000063746855,0.000040074676,0.00012259308,0.000010059157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012950944,0.00092077843,0.0007091472,0.00091371045,0.00023043793,0.0005676551,0.0005312212,0.00078301487,0.0018593211],"category_scores_gemma":[0.0019502745,0.00029601835,0.0010936981,0.0005951027,0.00023123599,0.0003861626,0.0002919529,0.0005390217,0.0004807702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043897712,0.00043801617,0.0020533663,0.0012442449,0.0001771042,0.00014543775,0.00031479335,0.3992645,0.22380224,0.004031603,0.0009141799,0.3671756],"study_design_scores_gemma":[0.000040214134,0.0005491679,0.004158507,0.000060394355,0.00008898052,0.00010646558,0.00012433597,0.9307755,0.060047958,0.0010028331,0.0030004194,0.000045112578],"about_ca_topic_score_codex":0.00071782246,"about_ca_topic_score_gemma":0.0010260219,"teacher_disagreement_score":0.0018593211,"about_ca_system_score_codex":0.00019473291,"about_ca_system_score_gemma":0.00045875346,"threshold_uncertainty_score":0.0068491697},"labels":[],"label_agreement":null},{"id":"W1962580649","doi":"10.5539/jmsr.v5n1p32","title":"Comparative Assessment of Wiper and Conventional Carbide Inserts on Surface Roughness in the Turning of High Strength Steel","year":2015,"lang":"en","type":"article","venue":"Journal of Materials Science Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Surface roughness; Materials science; Grinding; Machining; Response surface methodology; Roundness (object); Surface finish; Design of experiments; Mechanical engineering; Composite material; Metallurgy; Mathematics; Engineering; Statistics","score_opus":0.09319316763829236,"score_gpt":0.41668225121196223,"score_spread":0.3234890835736699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1962580649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983216,0.00058803556,0.00078326947,0.0000050994977,0.000009350698,0.000009511429,0.000025927337,0.0000130267945,0.0002441724],"genre_scores_gemma":[0.9980819,0.0002810472,0.001163445,0.000007941642,0.0000072581834,0.0000069676503,0.000056279172,0.000006608803,0.00038864842],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991322,0.00014696446,0.000053622884,0.00007865661,0.0005104554,0.0000781066],"domain_scores_gemma":[0.99852633,0.00055251026,0.0002678425,0.00010610114,0.00046408243,0.000083064064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053490367,0.00023349957,0.00031889728,0.0005012462,0.00011353138,0.00023956668,0.0001916415,0.00032009862,0.0006456677],"category_scores_gemma":[0.0011266125,0.00016817742,0.00030708715,0.00025448835,0.00019524213,0.00028879527,0.0001944466,0.00019531364,0.00014690525],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012086908,0.00014091643,0.004530294,0.00023501947,0.000030648443,0.00012961752,0.000120663426,0.00062249525,0.97795403,0.000020300473,0.000048008547,0.0149593195],"study_design_scores_gemma":[0.000026975584,0.013584509,0.21231925,0.000023573128,0.00019437802,0.00047865967,0.00055696693,0.0034557935,0.7683209,0.000020854144,0.0009767647,0.000041282387],"about_ca_topic_score_codex":0.00049111806,"about_ca_topic_score_gemma":0.0011925123,"teacher_disagreement_score":0.0006456677,"about_ca_system_score_codex":0.00010293699,"about_ca_system_score_gemma":0.00009827693,"threshold_uncertainty_score":0.002828896},"labels":[],"label_agreement":null},{"id":"W1963569189","doi":"10.1007/s00170-012-3948-z","title":"Variable heat flux in numerical simulation of grinding temperatures","year":2012,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Heat flux; Mechanics; Flux (metallurgy); Power (physics); Materials science; Mechanical engineering; Thermodynamics; Heat transfer; Metallurgy; Engineering; Physics","score_opus":0.006190051597836207,"score_gpt":0.25319109171273524,"score_spread":0.24700104011489904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963569189","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71514976,0.00093960995,0.26678655,0.0005646726,0.00035250682,0.00009502787,0.0001326285,0.0003678932,0.015611321],"genre_scores_gemma":[0.9841957,0.00012957603,0.013903892,0.000032676264,0.000022903087,0.00003449018,0.00003193375,0.000070249866,0.0015785854],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996815,0.00014406342,0.0000124797525,0.000034622866,0.00007501254,0.0000523588],"domain_scores_gemma":[0.9985306,0.0011141681,0.00010173744,0.000057400415,0.00014238425,0.000053637636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009022107,0.0004784409,0.00074674847,0.00068857917,0.00059115764,0.00095885166,0.00095361896,0.0016382445,0.0013177727],"category_scores_gemma":[0.004076167,0.0005652194,0.0005882319,0.000602655,0.001347744,0.0010508237,0.0004531341,0.00094400946,0.00016192054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051437204,0.0000342968,0.0005384518,0.000022423297,0.0000060738807,0.000027470533,0.000029815625,0.9924706,0.0020408032,0.0032738224,0.00006542903,0.0014393153],"study_design_scores_gemma":[0.000006714331,0.000009437577,0.000083814804,0.0000014620473,0.0000010152855,0.0000023840892,0.000002716097,0.99920124,0.00040221782,0.00022953357,0.00005739319,0.000002165509],"about_ca_topic_score_codex":0.010040655,"about_ca_topic_score_gemma":0.0054080207,"teacher_disagreement_score":0.010040655,"about_ca_system_score_codex":0.0011595108,"about_ca_system_score_gemma":0.00079677126,"threshold_uncertainty_score":0.019964397},"labels":[],"label_agreement":null},{"id":"W1964244119","doi":"10.1080/10940340008945697","title":"IMPROVEMENT OF TOOL LIFE THROUGH THE USE OF TWO DISCRETE FEED RATES DURING MACHINING OF 4140 STEEL","year":2000,"lang":"en","type":"article","venue":"Machining Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"Polytechnique Montréal","keywords":"Machining; Variable (mathematics); Discrete variable; Mechanical engineering; Tool wear; Engineering; Metallurgy; Manufacturing engineering; Computer science; Engineering drawing; Mathematics; Materials science; Mathematical optimization; Mathematical analysis","score_opus":0.01140396690552563,"score_gpt":0.25062277201257566,"score_spread":0.23921880510705001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964244119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950015,0.0005397667,0.004118791,0.000013493749,0.0000076966335,0.000012100333,0.000023667048,0.000047770878,0.00023519121],"genre_scores_gemma":[0.99581236,0.00012776827,0.0038018287,0.000005963356,0.000004005518,0.0000071498744,0.00002672581,0.000013204923,0.00020096189],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964404,0.000051268864,0.000029052479,0.000069135494,0.00015286084,0.000053620126],"domain_scores_gemma":[0.99918133,0.00036076247,0.00022508841,0.000089167326,0.00008374243,0.00005984071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033806948,0.00035853524,0.00041191993,0.0003480759,0.00014160863,0.00036762774,0.0004066012,0.00029409115,0.00057438586],"category_scores_gemma":[0.0010848143,0.0002461981,0.00018854254,0.00019680391,0.00022422303,0.0002467687,0.00021874162,0.0003001839,0.000088215806],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00091731676,0.000099287805,0.0013117889,0.00014588393,0.000015211037,0.00005949487,0.00009114968,0.0013218964,0.9778972,0.000047984613,0.00002822261,0.018064551],"study_design_scores_gemma":[0.00010128641,0.002684948,0.01108378,0.000010893168,0.00004274066,0.00020041097,0.00003935652,0.00437301,0.98000586,0.000026080987,0.001399728,0.00003190509],"about_ca_topic_score_codex":0.00038116655,"about_ca_topic_score_gemma":0.0006967673,"teacher_disagreement_score":0.00057438586,"about_ca_system_score_codex":0.00015731981,"about_ca_system_score_gemma":0.00013519038,"threshold_uncertainty_score":0.0019214749},"labels":[],"label_agreement":null},{"id":"W1965490343","doi":"10.1007/s12541-014-0554-z","title":"Tool wear patterns when turning of titanium alloy using sustainable lubrication strategies","year":2014,"lang":"en","type":"article","venue":"International Journal of Precision Engineering and Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Machining; Lubrication; Coolant; Lubricant; Metallurgy; Materials science; Titanium alloy; Tool wear; Vegetable oil; Titanium; Mechanical engineering; Alloy; Engineering; Composite material","score_opus":0.005410931350794701,"score_gpt":0.22402839574997827,"score_spread":0.21861746439918356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965490343","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988417,0.00008722118,0.0004447652,0.000011500318,0.000013948056,0.0000037379245,0.00006215104,0.000025820473,0.0005092916],"genre_scores_gemma":[0.99932194,0.000023170036,0.000154104,0.000003839346,0.0000015384159,0.0000017686332,0.00005885162,0.00000915723,0.00042568758],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996805,0.000023664597,0.000013949669,0.00004586938,0.0001209656,0.00011500918],"domain_scores_gemma":[0.9993357,0.000206299,0.0000937504,0.0000718246,0.00022750009,0.00006490631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019753842,0.00022791787,0.0004312408,0.00062659266,0.00039490112,0.00065470004,0.0005136874,0.00055701425,0.00295918],"category_scores_gemma":[0.0009870778,0.0001911003,0.00038258577,0.00041297683,0.00047637214,0.0002965087,0.0002293024,0.00028496995,0.0002685584],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0056262296,0.00017578992,0.019710302,0.00041056031,0.000117472686,0.002293684,0.0013770264,0.011829884,0.9223511,0.0005789997,0.001408444,0.03412061],"study_design_scores_gemma":[0.00008355169,0.0029236185,0.20371136,0.000072926945,0.00017626364,0.0013895355,0.0037726348,0.068290174,0.71487653,0.0007819008,0.0037551876,0.00016633996],"about_ca_topic_score_codex":0.0020000099,"about_ca_topic_score_gemma":0.004591553,"teacher_disagreement_score":0.00295918,"about_ca_system_score_codex":0.00032692132,"about_ca_system_score_gemma":0.0002140528,"threshold_uncertainty_score":0.009899497},"labels":[],"label_agreement":null},{"id":"W1965513377","doi":"10.1007/s00226-010-0378-7","title":"Toward a process monitoring of CNC wood router. Sensor selection and surface roughness prediction","year":2010,"lang":"en","type":"article","venue":"Wood Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Surface roughness; Router; Machining; Surface finish; Microphone; Process (computing); Artificial neural network; Acoustics; Mechanical engineering; Marine engineering; Materials science; Computer science; Engineering; Composite material; Artificial intelligence","score_opus":0.007371125080956181,"score_gpt":0.2396113415555915,"score_spread":0.2322402164746353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965513377","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18747872,0.00063675834,0.802537,0.00025938542,0.000088848996,0.00017477736,0.00023906259,0.0024930916,0.006092324],"genre_scores_gemma":[0.792852,0.00023769715,0.20221849,0.00012037936,0.000031979896,0.000066005174,0.00016300504,0.00006235641,0.0042481283],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996177,0.00004923695,0.000011632743,0.00011082435,0.00018043841,0.000030064608],"domain_scores_gemma":[0.9995701,0.0000623132,0.00006800164,0.000047147405,0.0002310679,0.000021408565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004893253,0.0005368471,0.0004192183,0.00068215793,0.00033179886,0.00075987587,0.0009136852,0.0006685411,0.0008107666],"category_scores_gemma":[0.0008155505,0.0002779011,0.00016082436,0.00046730865,0.00025931027,0.0006803822,0.00032242574,0.0004023314,0.00033135348],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034883476,0.0002831678,0.011371441,0.00011098982,0.000035421068,0.000074394906,0.00008427812,0.04054034,0.75143623,0.0030832333,0.0023325493,0.19029918],"study_design_scores_gemma":[0.000018612925,0.00024159509,0.009753904,0.00001013672,0.000035253182,0.00009000997,0.00004149287,0.7339062,0.2517961,0.00066814054,0.003415129,0.000023481354],"about_ca_topic_score_codex":0.005240927,"about_ca_topic_score_gemma":0.01118545,"teacher_disagreement_score":0.005240927,"about_ca_system_score_codex":0.00066855294,"about_ca_system_score_gemma":0.0006815721,"threshold_uncertainty_score":0.010420799},"labels":[],"label_agreement":null},{"id":"W1965679214","doi":"10.1115/1.2815761","title":"Virtual Five-Axis Flank Milling of Jet Engine Impellers—Part I: Mechanics of Five-Axis Flank Milling","year":2008,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Pratt and Whitney Canada","keywords":"Flank; Impeller; Machining; Mechanical engineering; Kinematics; Engineering; Structural engineering; Mechanics; Geometry; Physics; Mathematics; Classical mechanics","score_opus":0.008680805908061525,"score_gpt":0.20234155417525554,"score_spread":0.193660748267194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965679214","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15738411,0.00047012095,0.8375536,0.00006683789,0.000029038913,0.000024161114,0.000035230838,0.00018069189,0.00425616],"genre_scores_gemma":[0.9622435,0.00022148708,0.035961602,0.000008574917,0.0000072910184,0.00001285986,0.000032469223,0.00002085499,0.0014911578],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987555,0.00001726861,0.000005888801,0.0000178367,0.00007033204,0.000013122567],"domain_scores_gemma":[0.99985766,0.000052798387,0.00003850392,0.000016759534,0.00002738285,0.0000068221525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024361954,0.00026660215,0.00024909189,0.00022604609,0.0002541014,0.000587527,0.0004993258,0.0003323453,0.0008696855],"category_scores_gemma":[0.00040993327,0.00020379196,0.00031041718,0.00017416794,0.00041024503,0.00047272735,0.00019252318,0.0001775908,0.00015119468],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008501125,0.000028430562,0.0027249765,0.00011573211,0.00001237838,0.00020478228,0.0000992081,0.88934,0.044884168,0.011114304,0.0005070762,0.05088393],"study_design_scores_gemma":[0.0000037434065,0.00004443225,0.0008981276,0.000004665774,0.000002072181,0.000051932297,0.000011872538,0.99178034,0.005396789,0.0009368907,0.0008624011,0.000006828979],"about_ca_topic_score_codex":0.0016809218,"about_ca_topic_score_gemma":0.0015335316,"teacher_disagreement_score":0.0016809218,"about_ca_system_score_codex":0.0003033341,"about_ca_system_score_gemma":0.00031678012,"threshold_uncertainty_score":0.0033422709},"labels":[],"label_agreement":null},{"id":"W1966150111","doi":"10.1007/s12541-013-0178-8","title":"Simultaneous optimization of burrs size and surface finish when milling 6061-T6 aluminium alloy","year":2013,"lang":"en","type":"article","venue":"International Journal of Precision Engineering and Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Consortium de Recherche et d’innovation en Aérospatiale au Québec","keywords":"Taguchi methods; Aluminium; Surface roughness; Aluminium alloy; Surface finish; Alloy; Process (computing); Materials science; Metallurgy; Mechanical engineering; Engineering; Composite material; Computer science","score_opus":0.004104937740664471,"score_gpt":0.20441693995800675,"score_spread":0.20031200221734227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966150111","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9578777,0.0006600964,0.039176967,0.00003800491,0.000024462159,0.00002540748,0.00005502013,0.0002788254,0.0018635618],"genre_scores_gemma":[0.982272,0.0001172364,0.016992413,0.000005864487,0.0000046149653,0.000008869453,0.000035623536,0.00004967739,0.00051386293],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996362,0.000038580143,0.000029070043,0.00009163767,0.00015199096,0.000052629865],"domain_scores_gemma":[0.99907804,0.00036140147,0.00022865151,0.00007304016,0.00022442365,0.000034416353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046343953,0.00049574854,0.00052572036,0.0003736344,0.0002716092,0.00063696963,0.0004061574,0.00050865614,0.00080733356],"category_scores_gemma":[0.0010957688,0.0003566592,0.0003487274,0.00031767623,0.00017499195,0.00050426717,0.0002773426,0.00024641558,0.00020420429],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049904396,0.00010558792,0.001938341,0.00021526443,0.000038782844,0.000093741386,0.00008252838,0.026493747,0.9341941,0.00019826362,0.00017499305,0.035965648],"study_design_scores_gemma":[0.00009280233,0.0017407434,0.01625618,0.000015981546,0.00016334822,0.00020428539,0.00018301846,0.13114718,0.8482093,0.00018440957,0.0017407755,0.00006199621],"about_ca_topic_score_codex":0.00079257466,"about_ca_topic_score_gemma":0.0024496722,"teacher_disagreement_score":0.00080733356,"about_ca_system_score_codex":0.00024224324,"about_ca_system_score_gemma":0.00030112694,"threshold_uncertainty_score":0.0027008653},"labels":[],"label_agreement":null},{"id":"W1966360598","doi":"10.3722/cadaps.2013.551-565","title":"Determination of Elbow Flexion-Extension Axis Based on Planar and Closed B-Splines","year":2013,"lang":"en","type":"article","venue":"Computer-Aided Design and Applications","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Elbow; Extension (predicate logic); Planar; Elbow flexion; Orthodontics; Computer science; Mathematics; Medicine; Anatomy; Computer graphics (images); Programming language","score_opus":0.012943960530356126,"score_gpt":0.23045337840960675,"score_spread":0.21750941787925063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966360598","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052371416,0.00006953696,0.94615024,0.000016722644,0.000007914896,0.00004162431,0.000032368454,0.0005338109,0.00077627966],"genre_scores_gemma":[0.46979555,0.00012774713,0.5290175,0.0000062087947,0.000008578152,0.00006626139,0.00013109222,0.00015184909,0.00069514225],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942505,0.00014171998,0.0000330893,0.00007751956,0.00029074593,0.000031957916],"domain_scores_gemma":[0.99912244,0.0003149782,0.000112301765,0.0001093894,0.0003075609,0.00003339416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007229721,0.00045187323,0.0004189702,0.0009179977,0.00022114317,0.00056777603,0.00046696464,0.00036584053,0.00090234826],"category_scores_gemma":[0.0027537202,0.00032939788,0.00036669036,0.00050330174,0.00041269622,0.00037787668,0.000493705,0.00041694462,0.00034898482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004783138,0.00011188356,0.0095951175,0.0002649213,0.00005138274,0.00017228183,0.00034153488,0.27872336,0.17862245,0.008171927,0.000766705,0.5227002],"study_design_scores_gemma":[0.00001782971,0.0001313071,0.004763967,0.000023800589,0.000017044978,0.00021158115,0.000050855564,0.95312387,0.03681959,0.0021871247,0.0026117743,0.000041250445],"about_ca_topic_score_codex":0.0016559069,"about_ca_topic_score_gemma":0.0021665103,"teacher_disagreement_score":0.0016559069,"about_ca_system_score_codex":0.00018556339,"about_ca_system_score_gemma":0.00080444576,"threshold_uncertainty_score":0.0038235188},"labels":[],"label_agreement":null},{"id":"W1967040819","doi":"10.1115/imece2014-36767","title":"Experimental Investigation to Study Cutting Temperature During Milling of Unidirectional Carbon Fiber Reinforced Plastic","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; École de Technologie Supérieure","funders":"","keywords":"Materials science; Machinability; Composite material; Machining; Surface roughness; Fiber; Thermal; Perpendicular; Surface finish; Tool wear; Anisotropy; Metallurgy; Optics","score_opus":0.005159903395047172,"score_gpt":0.211352347225106,"score_spread":0.20619244383005883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967040819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952182,0.00015754529,0.004029795,0.000009534863,0.000011955372,0.000046087738,0.00013079624,0.00002783554,0.00036827268],"genre_scores_gemma":[0.9917555,0.00017389405,0.0073299385,0.000010089273,0.0000076214283,0.000077276585,0.00013444104,0.000017562777,0.00049388554],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995864,0.000034189234,0.00003090555,0.00009496874,0.00018988142,0.00006371523],"domain_scores_gemma":[0.99912745,0.0002993067,0.00018756447,0.00011113219,0.00023421178,0.00004042429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036914667,0.00047277083,0.0004671826,0.0002565156,0.00046728257,0.00024340779,0.00035124953,0.00047953444,0.0010754695],"category_scores_gemma":[0.00067123916,0.00027207212,0.00026954777,0.00029601523,0.00036864923,0.0002626662,0.0001951396,0.00046098192,0.0001673646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031116768,0.00017033404,0.001503931,0.00018845755,0.000007895628,0.00010073217,0.00023009913,0.0008039927,0.99322295,0.000046134643,0.000049160684,0.0033650834],"study_design_scores_gemma":[0.000027614602,0.0024560434,0.018795459,0.0000128805705,0.000028892147,0.00017140748,0.00016603735,0.0037931376,0.9735,0.000043041786,0.00097729,0.000028118651],"about_ca_topic_score_codex":0.00040467567,"about_ca_topic_score_gemma":0.000881607,"teacher_disagreement_score":0.0010754695,"about_ca_system_score_codex":0.0001822385,"about_ca_system_score_gemma":0.00020411942,"threshold_uncertainty_score":0.0035978556},"labels":[],"label_agreement":null},{"id":"W1967138896","doi":"10.1115/imece2002-33655","title":"Tool Performance in High Speed Finish Milling of Ti6Al4V","year":2002,"lang":"en","type":"article","venue":"Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Coolant; Materials science; Flank; Metallurgy; Carbide; Tool wear; Titanium alloy; Machining; Thermal shock; Alloy; Mechanical engineering; Engineering","score_opus":0.009181862131724486,"score_gpt":0.1809840541958028,"score_spread":0.17180219206407832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967138896","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983713,0.0002680283,0.0009776814,0.000008266733,0.0000052572213,0.000003871168,0.00003340446,0.000047845617,0.0002844466],"genre_scores_gemma":[0.99740523,0.000107686006,0.0014656278,0.0000046254636,0.0000031943814,0.000003552159,0.0001003898,0.000020037598,0.00088964484],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996908,0.000026894864,0.000012821005,0.00004072417,0.00015504137,0.000073745396],"domain_scores_gemma":[0.99938834,0.00024090755,0.00012551979,0.00006030149,0.00012776058,0.000057133697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005755002,0.00029564518,0.0002672093,0.000313763,0.00021992403,0.00040404237,0.0004238997,0.00045376626,0.0011990818],"category_scores_gemma":[0.0010995886,0.00018675851,0.00022496028,0.00028353685,0.00020540057,0.00037713855,0.00015512815,0.00016860387,0.00031035533],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010622978,0.000048695412,0.0024325112,0.00011323685,0.000014147083,0.00011144131,0.000100735204,0.0027711699,0.97988814,0.00007497165,0.00013394337,0.0132486895],"study_design_scores_gemma":[0.00006377257,0.0033703118,0.017326953,0.0000095359055,0.000024813595,0.00018587385,0.0000602239,0.005822088,0.9719569,0.00006696228,0.0010931782,0.000019533501],"about_ca_topic_score_codex":0.0011424278,"about_ca_topic_score_gemma":0.0018557751,"teacher_disagreement_score":0.0011990818,"about_ca_system_score_codex":0.00029277097,"about_ca_system_score_gemma":0.0001724939,"threshold_uncertainty_score":0.0040113926},"labels":[],"label_agreement":null},{"id":"W1967167595","doi":"10.1016/j.cirp.2014.05.007","title":"Virtual process systems for part machining operations","year":2014,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":350,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Process (computing); Trajectory; Grinding; Machine tool; Numerical control; Intersection (aeronautics); Mechanical engineering; Tool path; Engineering; Path (computing); Cutting tool; Computer science; Engineering drawing; Manufacturing engineering","score_opus":0.02510619509402276,"score_gpt":0.2901519386021882,"score_spread":0.26504574350816545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967167595","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07195339,0.00077700807,0.90166384,0.00018511844,0.00031185802,0.00012873471,0.00021756128,0.0039037534,0.02085879],"genre_scores_gemma":[0.86236244,0.00067579583,0.12254077,0.000080094505,0.00006640942,0.00012605106,0.00035074828,0.00023229777,0.013565401],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961025,0.00010415147,0.000015403817,0.000048320377,0.00018876237,0.0000332071],"domain_scores_gemma":[0.99971086,0.00007201565,0.000022412281,0.000090894915,0.00007605158,0.000027763477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038373913,0.00047412334,0.00043221432,0.00040810052,0.00047404537,0.0014548405,0.0009246538,0.0004911616,0.010519374],"category_scores_gemma":[0.00079860666,0.00023191317,0.00028600753,0.0005017775,0.00036437585,0.0009453106,0.0012001358,0.0004697342,0.0013910043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014510708,0.0002568629,0.001059704,0.00034255636,0.000057695248,0.00021284267,0.00030860092,0.27255213,0.12445394,0.056734886,0.010224183,0.5323456],"study_design_scores_gemma":[0.00012267039,0.0009543745,0.0016595327,0.00005360979,0.000060681035,0.00021443427,0.00012335279,0.85736716,0.0572588,0.02579898,0.05632482,0.00006153185],"about_ca_topic_score_codex":0.0009745878,"about_ca_topic_score_gemma":0.0008934324,"teacher_disagreement_score":0.010519374,"about_ca_system_score_codex":0.0004098897,"about_ca_system_score_gemma":0.0006157684,"threshold_uncertainty_score":0.03519082},"labels":[],"label_agreement":null},{"id":"W1967495781","doi":"10.1115/1.3066548","title":"Computer-Aided Machine Setting for Lapping Optimization","year":2009,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Lapping; Spiral bevel gear; Abrasive; Pinion; Process (computing); Point (geometry); Mechanical engineering; Engineering drawing; Engineering; Computer science; Mathematics; Geometry; Rack","score_opus":0.01566255347084405,"score_gpt":0.24536098524648378,"score_spread":0.22969843177563973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967495781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04031289,0.00007076721,0.9506982,0.000044348977,0.000024729372,0.00018662678,0.00011330201,0.003782117,0.004767064],"genre_scores_gemma":[0.48148683,0.00006851258,0.5143094,0.00003739693,0.000009654411,0.00057971646,0.00032207053,0.00027741626,0.0029089116],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997129,0.00007042777,0.00001470585,0.000060803744,0.00011105879,0.000030075444],"domain_scores_gemma":[0.99919564,0.00043216688,0.000046863828,0.00008115402,0.00022265497,0.000021629898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000553449,0.000794174,0.0009106056,0.00050515094,0.0004953107,0.0006747497,0.0010358331,0.00071210053,0.008025717],"category_scores_gemma":[0.001997492,0.00038975786,0.0004080412,0.0003978691,0.00032408375,0.00034742182,0.0005425942,0.0007714009,0.0008371518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015671112,0.000092343595,0.000890585,0.00016510325,0.000024735733,0.0000952789,0.00012852356,0.8486332,0.011339468,0.0029627339,0.0017289881,0.13378228],"study_design_scores_gemma":[0.000016587366,0.000038179896,0.00017721274,0.0000041661224,0.000003919088,0.000015333508,0.000009650738,0.99578625,0.0023925146,0.00039205575,0.0011579203,0.000006109249],"about_ca_topic_score_codex":0.0050923815,"about_ca_topic_score_gemma":0.004274136,"teacher_disagreement_score":0.008025717,"about_ca_system_score_codex":0.00053142966,"about_ca_system_score_gemma":0.0012321966,"threshold_uncertainty_score":0.026848674},"labels":[],"label_agreement":null},{"id":"W1968153074","doi":"10.1007/s001700170097","title":"Integration of Cutting Parameter Selection and Tool Adjustment Decisions for Multipass Turning","year":2001,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Selection (genetic algorithm); Industrial and production engineering; Engineering; Computer science; Mechanical engineering; Industrial engineering; Artificial intelligence","score_opus":0.011032264667354812,"score_gpt":0.2670522923164102,"score_spread":0.2560200276490554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968153074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5958625,0.00024473635,0.40015572,0.00009385888,0.000026775375,0.000058325786,0.000036233578,0.00050291163,0.0030188444],"genre_scores_gemma":[0.9735141,0.000041083847,0.025591845,0.000014976335,0.0000052051796,0.00001567922,0.00003788776,0.000030262143,0.0007489496],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997296,0.000058510286,0.000013376102,0.000037638267,0.000101617996,0.000059258447],"domain_scores_gemma":[0.999188,0.00046444376,0.00010069631,0.000059992533,0.00015131479,0.000035579942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006406607,0.00042436467,0.00078754395,0.00035800497,0.00037806513,0.00074860203,0.00062582246,0.0008301479,0.001101076],"category_scores_gemma":[0.0016460316,0.000577432,0.00041565442,0.00030361937,0.00025467866,0.00070178474,0.00057046604,0.00052054407,0.00017252796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084513007,0.00023896236,0.0046305247,0.00008269257,0.00006830499,0.00016929333,0.0001536449,0.7645218,0.03746905,0.0016687203,0.00038106696,0.1897709],"study_design_scores_gemma":[0.000014050754,0.00014441916,0.0018631178,0.0000030374658,0.00001939705,0.000022713723,0.000015959444,0.9911965,0.0061023105,0.0004358557,0.00017263377,0.000010064208],"about_ca_topic_score_codex":0.0036117875,"about_ca_topic_score_gemma":0.0073183253,"teacher_disagreement_score":0.0036117875,"about_ca_system_score_codex":0.000340712,"about_ca_system_score_gemma":0.0006533163,"threshold_uncertainty_score":0.007181525},"labels":[],"label_agreement":null},{"id":"W1968594536","doi":"10.1115/1.2280610","title":"Whirling Vibrations in Boring Trepanning Association Deep Hole Boring Process: Analytical and Experimental Investigations","year":2006,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Bar (unit); Deep hole drilling; Displacement (psychology); Vibration; Drilling; Boundary (topology); Process (computing); Engineering; Amplitude; Structural engineering; Mechanics; Mechanical engineering; Geology; Acoustics; Physics; Computer science; Optics; Mathematics; Mathematical analysis","score_opus":0.005443143295612077,"score_gpt":0.22961350177881681,"score_spread":0.22417035848320474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968594536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928469,0.000104525636,0.0063018813,0.00001952538,0.00000505525,0.00001903526,0.00001916358,0.000034052966,0.0006497861],"genre_scores_gemma":[0.9974452,0.00003019341,0.002153406,0.0000024589394,0.0000012395952,0.000005861739,0.000009231947,0.0000033520762,0.00034911002],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997172,0.00004084014,0.0000073449496,0.00004582908,0.00014277929,0.000045966302],"domain_scores_gemma":[0.99949145,0.00024409768,0.00008547357,0.00006062972,0.00008926785,0.000029159566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041813988,0.00022427949,0.00034066715,0.00018125452,0.00029895437,0.00021519241,0.00026755882,0.0004264147,0.0010773424],"category_scores_gemma":[0.00047735195,0.00020693899,0.00018620072,0.00023663323,0.00055639294,0.00027876356,0.00020592826,0.00028301775,0.00016610925],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030780127,0.00014740677,0.00077224796,0.000080303806,0.000003808709,0.00009144354,0.00029573197,0.0030146267,0.9874449,0.00023528973,0.000045009765,0.007561498],"study_design_scores_gemma":[0.00013328396,0.0040615755,0.014612855,0.000014589118,0.000021622765,0.00021391806,0.000514594,0.07351427,0.9047028,0.00035742836,0.0018093379,0.00004372954],"about_ca_topic_score_codex":0.00043395112,"about_ca_topic_score_gemma":0.00041578384,"teacher_disagreement_score":0.0010773424,"about_ca_system_score_codex":0.00014305211,"about_ca_system_score_gemma":0.000106081134,"threshold_uncertainty_score":0.003604114},"labels":[],"label_agreement":null},{"id":"W1969295751","doi":"10.1504/ijmmm.2013.053225","title":"Effects of lubrication modes on part quality during drilling 6061-T6 aluminium alloy","year":2013,"lang":"en","type":"article","venue":"International Journal of Machining and Machinability of Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Drilling; Machining; Lubrication; Cutting fluid; Surface roughness; Mist; Metallurgy; Aluminium; Factorial experiment; Mechanical engineering; Materials science; Surface finish; Quality (philosophy); Petroleum engineering; Composite material; Engineering; Computer science","score_opus":0.005802556074042249,"score_gpt":0.24838772688538777,"score_spread":0.2425851708113455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969295751","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996899,0.00049519347,0.0024133718,0.000008933574,0.000005129332,0.000009358797,0.00002249199,0.000018216513,0.00012837794],"genre_scores_gemma":[0.99855906,0.00013343654,0.0011276524,0.0000047522412,0.000002013168,0.0000032103214,0.000025350979,0.0000102369595,0.00013425293],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99914,0.00020136326,0.00009476677,0.00008437046,0.00038759664,0.00009188615],"domain_scores_gemma":[0.9972108,0.0014186014,0.000688658,0.00015075952,0.0004485589,0.00008267261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007155171,0.00035684425,0.00063786627,0.00031857,0.00022689793,0.0005784544,0.00022725757,0.00035823544,0.00058188726],"category_scores_gemma":[0.0030679724,0.00026408976,0.00038432414,0.00026274988,0.00049622037,0.00051446527,0.000313664,0.00026499145,0.00010521324],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019409265,0.00004578167,0.0049540494,0.0002923246,0.00003628432,0.00017195403,0.0002610929,0.0023531353,0.9777951,0.000033205164,0.000022877382,0.012093285],"study_design_scores_gemma":[0.000054048392,0.0056196377,0.04876625,0.000017713126,0.00013205607,0.00048478734,0.0003078761,0.0062218225,0.9376583,0.00007435199,0.0006160086,0.000047070687],"about_ca_topic_score_codex":0.00067299843,"about_ca_topic_score_gemma":0.0010672788,"teacher_disagreement_score":0.0007155171,"about_ca_system_score_codex":0.00022823058,"about_ca_system_score_gemma":0.00020774757,"threshold_uncertainty_score":0.00378412},"labels":[],"label_agreement":null},{"id":"W1969321662","doi":"10.1115/1.4000944","title":"Modeling of the Thread Milling Operation in a Combined Thread/Drilling Operation: Thrilling","year":2010,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"University of Illinois at Urbana-Champaign; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Thread (computing); Drilling; Torque; Computer science; Chip; Mechanical engineering; Engineering; Telecommunications","score_opus":0.006341216065024364,"score_gpt":0.20589405492068916,"score_spread":0.1995528388556648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969321662","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35768306,0.0003071312,0.6306584,0.00011281526,0.00002737223,0.0000925919,0.00010653036,0.00040138647,0.010610689],"genre_scores_gemma":[0.9600284,0.00023782077,0.03588407,0.0000150409305,0.000006796031,0.0000602248,0.00006166604,0.000047971822,0.003658085],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983585,0.000017067596,0.0000066220455,0.000041873296,0.00007026784,0.00002817123],"domain_scores_gemma":[0.99978524,0.000090610345,0.000052991847,0.000024182318,0.00003218492,0.000014770589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000257822,0.00036461634,0.00049281074,0.00021867303,0.00027209675,0.0006855279,0.00089427736,0.0008648534,0.0013219657],"category_scores_gemma":[0.00048717886,0.00030518914,0.0004969477,0.000225443,0.00045921418,0.0008073259,0.0003261471,0.00038130808,0.0003181718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055030505,0.00004442257,0.00091419637,0.000060346454,0.00001064576,0.00016303897,0.0000778445,0.9534263,0.032990243,0.0021034016,0.00012692003,0.010027478],"study_design_scores_gemma":[0.0000035585795,0.000028427736,0.00023591652,0.0000016051374,0.0000030942872,0.000024715882,0.000006879775,0.99684,0.0023469545,0.00019538405,0.00030943967,0.0000040664254],"about_ca_topic_score_codex":0.0057774824,"about_ca_topic_score_gemma":0.0030018417,"teacher_disagreement_score":0.0057774824,"about_ca_system_score_codex":0.00038651287,"about_ca_system_score_gemma":0.00074226374,"threshold_uncertainty_score":0.011487722},"labels":[],"label_agreement":null},{"id":"W1969523024","doi":"10.1016/s0007-8506(07)62063-0","title":"Generalized Modeling of Mechanics and Dynamics of Milling Cutters","year":2001,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":163,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"End mill; Engineering; Milling cutter; Vibration; Mechanical engineering; Enhanced Data Rates for GSM Evolution; Ball (mathematics); Surface roughness; Torque; Process (computing); Structural engineering; Kinematics; Coordinate system; Envelope (radar); Surface finish; Point (geometry); Parametric statistics; Geometry; Machining; Computer science; Mathematics; Materials science; Physics; Acoustics; Classical mechanics","score_opus":0.024706080389506866,"score_gpt":0.2581687426603516,"score_spread":0.23346266227084475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969523024","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12409471,0.0010966437,0.8479365,0.0004564336,0.00014485198,0.0000611778,0.00028737285,0.00043941845,0.02548286],"genre_scores_gemma":[0.95659137,0.0007869586,0.027990118,0.00009586871,0.0000657707,0.00011163416,0.00017077624,0.00008821713,0.01409931],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998323,0.000048203874,0.00000710427,0.000036568552,0.00005171743,0.000024093975],"domain_scores_gemma":[0.9998429,0.000051366573,0.000031162,0.000023464998,0.00003458674,0.00001654471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002962671,0.0006658543,0.0009864179,0.00045993662,0.00045498158,0.0012141394,0.0015365398,0.0015992512,0.002309395],"category_scores_gemma":[0.0006507688,0.000517578,0.000737721,0.0006330539,0.0009749477,0.0009961625,0.00076162297,0.00071501813,0.00033930747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008394589,0.000005901556,0.00010456768,0.000011838865,0.000005843012,0.000025391346,0.00001647174,0.9863029,0.0006328974,0.011054645,0.00011677579,0.0017142609],"study_design_scores_gemma":[0.0000031993272,0.00000432954,0.000087726636,0.0000013359489,0.000002087492,0.0000054050083,0.000004225622,0.99633586,0.000059123668,0.0032694645,0.00022472757,0.0000025141785],"about_ca_topic_score_codex":0.008160107,"about_ca_topic_score_gemma":0.006920489,"teacher_disagreement_score":0.008160107,"about_ca_system_score_codex":0.0006624834,"about_ca_system_score_gemma":0.0008224835,"threshold_uncertainty_score":0.016225219},"labels":[],"label_agreement":null},{"id":"W1969677729","doi":"10.1016/j.ijmachtools.2009.08.008","title":"An investigation of the effects of wheel-cleaning parameters in creep-feed grinding","year":2009,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Grinding wheel; Abrasive; Materials science; Coolant; Surface roughness; Thermal; Jet (fluid); Volumetric flow rate; Process (computing); Surface grinding; Surface finish; Mechanical engineering; Metallurgy; Composite material; Mechanics; Engineering; Computer science","score_opus":0.004772277578330032,"score_gpt":0.2265046200574934,"score_spread":0.22173234247916335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969677729","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99719584,0.0006728308,0.0016552764,0.000021829153,0.000015263597,0.000010001801,0.00004577876,0.00004259959,0.00034057174],"genre_scores_gemma":[0.9984237,0.00018301945,0.00106816,0.00000899351,0.000002821601,0.000004038505,0.00003980148,0.000018674124,0.00025072182],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996081,0.000056064044,0.000036852303,0.00006218236,0.0001555331,0.00008133035],"domain_scores_gemma":[0.9975147,0.0013835436,0.00037076266,0.00019678946,0.00046408578,0.0000700471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063398737,0.00034981474,0.00080069754,0.000300947,0.000479149,0.0004663777,0.0004935749,0.00053131336,0.0010093652],"category_scores_gemma":[0.0023489057,0.00030426934,0.00032119363,0.00043279317,0.0002911207,0.00055599294,0.00022231968,0.00034307656,0.00017807864],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002751357,0.0003910336,0.0041914047,0.00031512996,0.000044792007,0.00013003351,0.00017988951,0.00603845,0.9644657,0.00008286609,0.00014034362,0.021269018],"study_design_scores_gemma":[0.000042669046,0.0015588567,0.024652144,0.00001738493,0.00010197831,0.00009725875,0.00012438385,0.010343232,0.96227753,0.000050543716,0.00070550723,0.00002859669],"about_ca_topic_score_codex":0.0022104732,"about_ca_topic_score_gemma":0.004960409,"teacher_disagreement_score":0.0022104732,"about_ca_system_score_codex":0.0004951084,"about_ca_system_score_gemma":0.0004283064,"threshold_uncertainty_score":0.0043952465},"labels":[],"label_agreement":null},{"id":"W1969876422","doi":"10.1115/imece2011-62826","title":"Impact-Cutting and Regenerative Chatter in Robotic Grinding","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Hydro-Québec","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear system; Machining; Mechanism (biology); Vibration; Instability; Grinding; Control theory (sociology); Computer science; Robot; Process (computing); Stability (learning theory); Impulse (physics); Impulse response; Mechanical engineering; Engineering; Control engineering; Mechanics; Mathematics; Physics; Acoustics; Artificial intelligence; Classical mechanics; Mathematical analysis","score_opus":0.01883368068155237,"score_gpt":0.23474390438297826,"score_spread":0.2159102237014259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969876422","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78881115,0.00045342793,0.20684522,0.0000633187,0.000014607714,0.000024255054,0.000011022886,0.00012207536,0.0036550106],"genre_scores_gemma":[0.9946168,0.000052945743,0.0046407026,0.000005633323,0.0000026253658,0.0000054473703,0.0000043165705,0.000006024384,0.00066546287],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997532,0.000055395565,0.0000062713502,0.000035204444,0.00011934501,0.00003063502],"domain_scores_gemma":[0.99932337,0.0004652078,0.00009701219,0.00004177798,0.000047818085,0.000024897809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037168403,0.00024927102,0.00027281189,0.0002666545,0.00021135328,0.0002274134,0.0003740425,0.00032727746,0.0007110565],"category_scores_gemma":[0.0013823564,0.00015826485,0.00026626987,0.00010691091,0.000794735,0.00035153743,0.0003451038,0.00027903426,0.00006974994],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044259758,0.00011765354,0.004608842,0.00041471628,0.000051248517,0.0018574273,0.0012705129,0.6445119,0.29702708,0.01618824,0.00013988276,0.033369817],"study_design_scores_gemma":[0.000011629659,0.00029557417,0.0051376563,0.000011773155,0.000011243433,0.00045875285,0.000108927976,0.9660523,0.023482222,0.0040046712,0.00039738667,0.00002783493],"about_ca_topic_score_codex":0.0009751362,"about_ca_topic_score_gemma":0.0008155078,"teacher_disagreement_score":0.0009751362,"about_ca_system_score_codex":0.00023876493,"about_ca_system_score_gemma":0.00015006776,"threshold_uncertainty_score":0.0023787022},"labels":[],"label_agreement":null},{"id":"W1970026880","doi":"10.1177/0954405415577591","title":"Optimal replacement times for machining tool during turning titanium metal matrix composites under variable machining conditions","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Machining; Aerospace; Variable (mathematics); Mechanical engineering; Cutting tool; Matrix (chemical analysis); Work (physics); Computer science; Materials science; Engineering; Composite material; Mathematics","score_opus":0.008872469087103858,"score_gpt":0.22979515481140106,"score_spread":0.2209226857242972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970026880","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88037056,0.0016541504,0.11617359,0.000073062496,0.000031945165,0.00002607209,0.000051110193,0.00016870473,0.0014508032],"genre_scores_gemma":[0.99328554,0.00012470309,0.0063478844,0.0000042555394,0.0000017660863,0.000008382008,0.000023899898,0.000013346365,0.00019015804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993957,0.00014334013,0.000034221917,0.00010218006,0.00017985431,0.00014470483],"domain_scores_gemma":[0.99888366,0.00060907943,0.00029045073,0.00006778336,0.00010064673,0.000048451497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011354424,0.00039935412,0.0004965826,0.00047658902,0.00022700288,0.0006355734,0.00044819212,0.0004697064,0.0007480055],"category_scores_gemma":[0.0025556996,0.00024596677,0.0003461795,0.0002893677,0.00036559053,0.00053418905,0.00022679479,0.00031451051,0.00012313083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002090704,0.00027304766,0.00682765,0.00045318485,0.000048070684,0.00026000664,0.00023954522,0.7486432,0.16444834,0.00464336,0.00035092162,0.07172191],"study_design_scores_gemma":[0.00005205507,0.002412353,0.0069939047,0.000036777463,0.000082687846,0.00023188654,0.0002849154,0.854695,0.13066398,0.0033977544,0.0010832538,0.000065286455],"about_ca_topic_score_codex":0.0012298755,"about_ca_topic_score_gemma":0.0015048455,"teacher_disagreement_score":0.0012298755,"about_ca_system_score_codex":0.0005247006,"about_ca_system_score_gemma":0.0007551605,"threshold_uncertainty_score":0.00600487},"labels":[],"label_agreement":null},{"id":"W1970030229","doi":"10.1016/j.cirp.2015.04.100","title":"Prediction of part machining cycle times via virtual CNC","year":2015,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Trajectory; Interpolation (computer graphics); Numerical control; Smoothing; Servo; Machine tool; Tool path; Engineering; Control engineering; Computer science; Mechanical engineering; Control theory (sociology); Control (management); Artificial intelligence; Computer vision","score_opus":0.04160535250317833,"score_gpt":0.2575292024842653,"score_spread":0.215923849981087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970030229","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78324586,0.0003766513,0.20659494,0.00010199407,0.00011942615,0.0000649606,0.00059387664,0.0012809753,0.007621303],"genre_scores_gemma":[0.987276,0.000048498445,0.011442447,0.000007553015,0.0000049327787,0.000018986197,0.00015422022,0.000035213685,0.0010120258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984884,0.000025776526,0.0000042791835,0.00003963719,0.000058470236,0.000022950137],"domain_scores_gemma":[0.99915135,0.0004630063,0.00007103567,0.00008571218,0.00018487735,0.00004412047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003873679,0.00071232684,0.0005865878,0.00074224506,0.00038302568,0.0006079412,0.00082161365,0.0006458336,0.0019338615],"category_scores_gemma":[0.0015332601,0.00043085456,0.00042037,0.0006867259,0.00040952742,0.0005179612,0.00031419314,0.0004885063,0.0002768763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000076958335,0.000017472255,0.0010968052,0.0000126874775,0.0000057362336,0.00001694739,0.0000046498817,0.9902354,0.001135221,0.000262071,0.00013824625,0.0069977394],"study_design_scores_gemma":[9.361977e-7,0.0000054817083,0.00026125705,4.7620614e-7,0.0000010730315,0.0000013802222,5.920222e-7,0.99934417,0.00030399472,0.00005331491,0.000026259406,0.0000011010588],"about_ca_topic_score_codex":0.022553291,"about_ca_topic_score_gemma":0.0172386,"teacher_disagreement_score":0.022553291,"about_ca_system_score_codex":0.0010701733,"about_ca_system_score_gemma":0.0011128326,"threshold_uncertainty_score":0.04484403},"labels":[],"label_agreement":null},{"id":"W1970064874","doi":"10.1115/1.4005429","title":"A New Mechanistic Approach for Micro End Milling Force Modeling","year":2012,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Victoria","funders":"","keywords":"Rubbing; Rake angle; Enhanced Data Rates for GSM Evolution; End milling; Rake; Materials science; Shearing (physics); Root mean square; Shear force; RADIUS; Contact force; Breakage; Mechanics; Mechanical engineering; Composite material; Computer science; Engineering; Machining; Physics; Metallurgy","score_opus":0.011968883569672786,"score_gpt":0.2163986549978669,"score_spread":0.2044297714281941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970064874","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0054130303,0.00024316068,0.984347,0.00019353133,0.000055811015,0.00007650092,0.00009244278,0.000120244986,0.009458246],"genre_scores_gemma":[0.51990134,0.0031672092,0.44176522,0.0004504318,0.00023966451,0.0014229428,0.00041765478,0.00030142596,0.032334074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997476,0.000036517016,0.000014302341,0.000047117206,0.00013239728,0.00002202448],"domain_scores_gemma":[0.9997265,0.000111130335,0.000043525535,0.000041543248,0.000063935935,0.000013457066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059696595,0.0009068413,0.00069117657,0.0006636644,0.0005720393,0.0010611841,0.0023442016,0.0019560459,0.003951374],"category_scores_gemma":[0.00086028734,0.00058198406,0.0012242572,0.00035582884,0.0006576154,0.0019784311,0.0008416902,0.0013832597,0.00087059516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010393088,0.00008110808,0.00029204384,0.0001623026,0.000029662886,0.00016118783,0.000108958586,0.8524215,0.012541876,0.12042038,0.0006161261,0.01315445],"study_design_scores_gemma":[0.000005205749,0.000026314474,0.00012845686,0.000015211388,0.000007840239,0.000058400536,0.000012220106,0.9747558,0.0011532239,0.017878274,0.005946856,0.000012260075],"about_ca_topic_score_codex":0.0013610409,"about_ca_topic_score_gemma":0.0011263201,"teacher_disagreement_score":0.003951374,"about_ca_system_score_codex":0.0005278421,"about_ca_system_score_gemma":0.00089883135,"threshold_uncertainty_score":0.013218641},"labels":[],"label_agreement":null},{"id":"W1970538667","doi":"10.1007/s10845-013-0756-8","title":"Dynamic speed control of a machine tool with stochastic tool life: analysis and simulation","year":2013,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Gouvernement du Québec; Université TÉLUQ; Université Laval","funders":"","keywords":"Machine tool; Dynamic programming; Variable (mathematics); Tool wear; Computer science; Function (biology); Cutting tool; Numerical control; Mathematical optimization; Engineering; Algorithm; Machining; Mathematics; Mechanical engineering","score_opus":0.004507680548244383,"score_gpt":0.2186779869601117,"score_spread":0.21417030641186732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970538667","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6857644,0.00047421182,0.30133832,0.00030447834,0.00007464003,0.00007938664,0.000095415715,0.0002790261,0.011590155],"genre_scores_gemma":[0.9976273,0.00003949236,0.0016053654,0.0000066345947,0.000002960724,0.000011327685,0.000009809954,0.0000069306725,0.0006902744],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977785,0.00005166576,0.000009248235,0.000037351303,0.00006653174,0.000057394118],"domain_scores_gemma":[0.99900407,0.00060065155,0.00016207209,0.00004842214,0.00013495398,0.000049923405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065666914,0.0004018191,0.00067250564,0.00067696034,0.00051826297,0.00085388497,0.0006419185,0.0011427396,0.0012408893],"category_scores_gemma":[0.002075265,0.00047119503,0.000632895,0.0004705189,0.0008350421,0.00058588997,0.00047479544,0.00039431767,0.0001069158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003324573,0.000014814075,0.00021981623,0.000011317204,0.000006265309,0.00002328133,0.000012205219,0.9964619,0.0009290273,0.0011961551,0.000036622903,0.0010553957],"study_design_scores_gemma":[0.0000030070305,0.000010654922,0.00007826158,5.5363876e-7,0.0000016082049,0.000002984042,0.0000015861691,0.99968266,0.000092041504,0.00009952999,0.000025749834,0.0000013715123],"about_ca_topic_score_codex":0.009550933,"about_ca_topic_score_gemma":0.0041284966,"teacher_disagreement_score":0.009550933,"about_ca_system_score_codex":0.0007834556,"about_ca_system_score_gemma":0.00084517413,"threshold_uncertainty_score":0.018990695},"labels":[],"label_agreement":null},{"id":"W1971778361","doi":"10.1115/imece2012-89066","title":"An Integrated Approach for the Predictions of the Workpiece Vibrations During Machining of Aerospace Structure: Numerical and Experimental Validation","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Fixture; Machining; Aerospace; Vibration; Finite element method; Stiffness; Mechanical engineering; Computation; Reduction (mathematics); Machine tool; Computer science; Engineering; Structural engineering; Algorithm; Acoustics; Aerospace engineering","score_opus":0.008188804967454883,"score_gpt":0.2397995027913464,"score_spread":0.23161069782389151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971778361","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4077835,0.00033915875,0.5872556,0.000056691115,0.000027896296,0.0001098966,0.00017713517,0.00093737297,0.0033127894],"genre_scores_gemma":[0.9010729,0.00018652811,0.09755286,0.000011805059,0.0000051777743,0.00013052297,0.0000977803,0.00004299571,0.00089942134],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965966,0.000050244373,0.00001512955,0.00005237009,0.00019850158,0.000024025368],"domain_scores_gemma":[0.999551,0.00019467057,0.000053706328,0.000095529,0.00008766285,0.000017283302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006401998,0.00053361605,0.0005715273,0.00028810278,0.00021439452,0.00046019928,0.000840631,0.0009908609,0.0009826537],"category_scores_gemma":[0.00084103964,0.0002931799,0.00032497634,0.00033104027,0.0004055722,0.000454296,0.00049960695,0.00053134526,0.00020895422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016665128,0.00036970523,0.0016337459,0.0003194273,0.00004136869,0.000116650415,0.0003175469,0.7117464,0.22822018,0.0016679541,0.00025892654,0.055141453],"study_design_scores_gemma":[0.000010008565,0.00012473948,0.00072083087,0.0000075317407,0.0000065441263,0.000019542109,0.000021902119,0.9712379,0.027312782,0.00013230427,0.00039534734,0.0000105454355],"about_ca_topic_score_codex":0.0015187205,"about_ca_topic_score_gemma":0.0015780111,"teacher_disagreement_score":0.0015187205,"about_ca_system_score_codex":0.00027424935,"about_ca_system_score_gemma":0.0004672534,"threshold_uncertainty_score":0.0033857226},"labels":[],"label_agreement":null},{"id":"W1971860903","doi":"10.1007/s00170-006-0778-x","title":"Robust regenerative chatter stability in machine tools","year":2007,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Machining; Vibration; Stability (learning theory); Machine tool; Control theory (sociology); Engineering; Mechanical engineering; Control engineering; Computer science; Artificial intelligence; Machine learning","score_opus":0.01679798466663321,"score_gpt":0.2471959403658574,"score_spread":0.2303979556992242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971860903","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14374816,0.0010133922,0.8423055,0.00025569793,0.00013122795,0.000032034273,0.000033440425,0.00031364517,0.0121669015],"genre_scores_gemma":[0.987683,0.00013046281,0.0073303394,0.00003175024,0.000024470211,0.000023425317,0.000015215026,0.000035270892,0.004726139],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952066,0.00015768694,0.000021210873,0.00007090663,0.00017842866,0.000051176616],"domain_scores_gemma":[0.9985215,0.0008472947,0.00020917943,0.00009472915,0.0002801624,0.00004711973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009544238,0.0006517852,0.00071157306,0.00059072446,0.00037751626,0.0008864799,0.0009857725,0.0008398548,0.0019752674],"category_scores_gemma":[0.0032365893,0.0003000185,0.00047131834,0.00030914458,0.0012757927,0.00078602275,0.0010163679,0.00067127653,0.00025588684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009430708,0.00008334234,0.0007467707,0.00037535347,0.0001055815,0.00045243205,0.0005058848,0.6845279,0.048866883,0.22330524,0.001341075,0.03874648],"study_design_scores_gemma":[0.000012306844,0.00007473242,0.00018808365,0.000008751228,0.000008486755,0.000041087376,0.000027501861,0.97285795,0.0021171363,0.024346543,0.0003038608,0.000013498209],"about_ca_topic_score_codex":0.0014636576,"about_ca_topic_score_gemma":0.00088104437,"teacher_disagreement_score":0.0019752674,"about_ca_system_score_codex":0.0005265501,"about_ca_system_score_gemma":0.00034673605,"threshold_uncertainty_score":0.0066079497},"labels":[],"label_agreement":null},{"id":"W1972458521","doi":"10.4028/www.scientific.net/amm.232.57","title":"Surface Quality and Dust Analysis in High Speed Trimming of CFRP","year":2012,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Trimming; Tungsten carbide; Materials science; Machining; Composite material; Tungsten; Fiber; Carbide; Metallurgy; Surface (topology); Mechanical engineering; Engineering; Geometry; Mathematics","score_opus":0.016846935052881675,"score_gpt":0.25653323285666096,"score_spread":0.23968629780377929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972458521","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9933084,0.00029798664,0.006000201,0.00000715596,0.000004066156,0.0000079939455,0.000026903615,0.000022657383,0.00032452773],"genre_scores_gemma":[0.99454343,0.00014190389,0.004675741,0.000012730929,0.0000037807777,0.00000596235,0.00007130308,0.000016818325,0.00052832766],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996439,0.000041974676,0.000009613173,0.000056152046,0.00021909233,0.000029107165],"domain_scores_gemma":[0.9995189,0.00014810578,0.00010111155,0.000050094153,0.00016487969,0.000016907914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029672304,0.00018206237,0.00018184049,0.00038382784,0.00023088153,0.0002173085,0.00023778349,0.00039787102,0.000678493],"category_scores_gemma":[0.0004530052,0.0001504034,0.00021934981,0.00017804893,0.0002028115,0.00019341297,0.000112197085,0.00018465405,0.00014638118],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001597306,0.000023604456,0.00439632,0.000071349335,0.000012873911,0.00009104439,0.00009332041,0.0007792986,0.9852899,0.000017461462,0.000030286765,0.009034748],"study_design_scores_gemma":[0.000008536558,0.0010724914,0.097939946,0.000010509352,0.000041918112,0.00059830485,0.00021289397,0.005418351,0.8940255,0.00005736607,0.0005992139,0.000015025682],"about_ca_topic_score_codex":0.0006684758,"about_ca_topic_score_gemma":0.0013563489,"teacher_disagreement_score":0.000678493,"about_ca_system_score_codex":0.00012281632,"about_ca_system_score_gemma":0.000073036026,"threshold_uncertainty_score":0.0022697449},"labels":[],"label_agreement":null},{"id":"W1972972524","doi":"10.1177/0954405412450380","title":"A phenomenological modeling of deformation during metal cutting: a modified thick shear zone analysis","year":2012,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Mechanics; Machining; Materials science; Shear zone; Shear (geology); Equidistant; Simple shear; Shear rate; Deformation (meteorology); Strain rate; Geology; Geometry; Composite material; Physics; Mathematics; Metallurgy","score_opus":0.012243442267543448,"score_gpt":0.20833500895316684,"score_spread":0.1960915666856234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972972524","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08741428,0.0006669103,0.90537685,0.0000894061,0.00005189382,0.000063463085,0.000077471545,0.000111735775,0.0061478983],"genre_scores_gemma":[0.90341234,0.0010106073,0.08842719,0.00005324193,0.00004599175,0.00009076731,0.00009436417,0.00007268472,0.0067929216],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986386,0.00002486262,0.000009169609,0.00003088955,0.00005170679,0.000019401514],"domain_scores_gemma":[0.99989057,0.00003224638,0.000025675145,0.000020855001,0.00002337461,0.00000734345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034254708,0.00073762855,0.00038961595,0.0006552359,0.00024314011,0.000663765,0.0013479835,0.00068402203,0.0009846152],"category_scores_gemma":[0.00045892163,0.00038293275,0.00073648395,0.00048148265,0.00077119836,0.0010803605,0.0004943855,0.00068889686,0.00036119058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077271645,0.000046647696,0.0010306832,0.00011581576,0.000020862617,0.0001987937,0.00015678167,0.8973266,0.051629864,0.032185193,0.00022696458,0.016984608],"study_design_scores_gemma":[0.0000049821642,0.000033404376,0.00032294713,0.0000052621444,0.00000465953,0.000039757608,0.000013908188,0.99426794,0.002197245,0.0025213219,0.0005793495,0.000009250671],"about_ca_topic_score_codex":0.0017605921,"about_ca_topic_score_gemma":0.0010588156,"teacher_disagreement_score":0.0017605921,"about_ca_system_score_codex":0.0003779318,"about_ca_system_score_gemma":0.00043152247,"threshold_uncertainty_score":0.0035007},"labels":[],"label_agreement":null},{"id":"W1972980909","doi":"10.1111/j.1745-4530.2008.00272.x","title":"NEURAL NETWORK MODELING OF END‐OVER‐END THERMAL PROCESSING OF PARTICULATES IN VISCOUS FLUIDS","year":2009,"lang":"en","type":"article","venue":"Journal of Food Process Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Artificial neural network; Dimensionless quantity; Heat transfer; Mechanics; Newtonian fluid; Non-Newtonian fluid; Artificial intelligence; Computer science; Thermodynamics; Mathematics; Physics","score_opus":0.00781996431231846,"score_gpt":0.2283555982002082,"score_spread":0.22053563388788974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972980909","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73885065,0.0003284737,0.25555643,0.0001445209,0.00005169807,0.00006250851,0.000099122706,0.00026680029,0.004639784],"genre_scores_gemma":[0.99290353,0.00006788495,0.0054768133,0.000008035359,0.0000030148065,0.00003715903,0.000035611545,0.000008032288,0.0014599705],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999861,0.00003668809,0.000009279034,0.000032329674,0.000040010244,0.000020591187],"domain_scores_gemma":[0.9996755,0.0001857805,0.00003909852,0.000012347044,0.000077617115,0.000009759085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047509428,0.00048547873,0.0004334581,0.00038167267,0.00028853628,0.0005093218,0.00047156328,0.000718636,0.0008316764],"category_scores_gemma":[0.00080750743,0.00030158836,0.000492829,0.0002712004,0.00038451015,0.00048581735,0.000257648,0.00051555847,0.00014026019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022228269,0.000016424867,0.00045329583,0.000010494684,0.000005591659,0.000017082122,0.000009033775,0.9952259,0.0017470929,0.000119994256,0.000023153496,0.0023496277],"study_design_scores_gemma":[4.210048e-7,0.000005623508,0.00008059365,5.739765e-7,6.526567e-7,6.7837794e-7,8.150758e-7,0.99951625,0.00035793448,0.00002519354,0.000010394388,8.1676825e-7],"about_ca_topic_score_codex":0.011291337,"about_ca_topic_score_gemma":0.006063286,"teacher_disagreement_score":0.011291337,"about_ca_system_score_codex":0.0007819221,"about_ca_system_score_gemma":0.0005510251,"threshold_uncertainty_score":0.022451222},"labels":[],"label_agreement":null},{"id":"W1973583212","doi":"10.1016/j.ijmachtools.2011.12.008","title":"Unified cutting force model for turning, boring, drilling and milling operations","year":2011,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":200,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Machine Tool Technologies Research Foundation","keywords":"Drilling; Mechanical engineering; Rake; Machining; Enhanced Data Rates for GSM Evolution; Rake angle; Transformation matrix; Engineering; Insert (composites); Transformation (genetics); Orientation (vector space); Cutting tool; Run-out; Engineering drawing; Computer science; Kinematics; Geometry; Mathematics; Classical mechanics; Physics","score_opus":0.022777752968434498,"score_gpt":0.25381830775659725,"score_spread":0.23104055478816277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973583212","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012073301,0.00054877903,0.966417,0.00015814832,0.00011105984,0.000070064605,0.00024815483,0.00026421662,0.020109247],"genre_scores_gemma":[0.8042833,0.0017044521,0.13939612,0.00013624105,0.0001600341,0.0006021221,0.0011375202,0.0003639502,0.052216314],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994804,0.00008214399,0.000023869316,0.000064707354,0.00025800458,0.000090918526],"domain_scores_gemma":[0.9996543,0.00009993891,0.00003720084,0.000031976193,0.00015809473,0.000018416013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006138596,0.001118166,0.0010931231,0.0011552668,0.00051994954,0.0013222181,0.0022491599,0.0017110915,0.007081781],"category_scores_gemma":[0.0009085948,0.00043712623,0.0012637965,0.000970478,0.0005607041,0.001548579,0.0006515796,0.00097053574,0.0018140554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003099739,0.00004116745,0.0001363226,0.000058250127,0.000015681697,0.000070958886,0.000032258387,0.9441478,0.0016657712,0.037088986,0.001382052,0.015329788],"study_design_scores_gemma":[0.0000027721264,0.000009801402,0.00005475899,0.0000024251613,0.000003442792,0.00000751443,0.0000032651951,0.99704105,0.00011079599,0.0022382678,0.0005230748,0.0000028519246],"about_ca_topic_score_codex":0.0120559875,"about_ca_topic_score_gemma":0.009634339,"teacher_disagreement_score":0.0120559875,"about_ca_system_score_codex":0.000849599,"about_ca_system_score_gemma":0.0013400327,"threshold_uncertainty_score":0.023971617},"labels":[],"label_agreement":null},{"id":"W1973588607","doi":"10.1007/978-1-84996-432-6_46","title":"Extension of a Simple Predictive Model for Orthogonal Cutting to Include Flow below the Cutting Edge","year":2010,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Simple (philosophy); Extension (predicate logic); Flow (mathematics); Moment (physics); Mathematics; Computer science; Applied mathematics; Mechanics; Mathematical optimization; Geometry; Physics; Classical mechanics; Artificial intelligence","score_opus":0.0157859676124039,"score_gpt":0.24661645561447665,"score_spread":0.23083048800207276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973588607","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010497717,0.00049631606,0.96842885,0.00023316315,0.00033074222,0.00006534176,0.0002471755,0.0005882273,0.019112451],"genre_scores_gemma":[0.7922671,0.0016760977,0.16396907,0.0003971279,0.00034884224,0.00033655402,0.0006407892,0.0004726515,0.03989173],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998833,0.000015100152,0.0000046305604,0.0000312852,0.000052330877,0.000013295677],"domain_scores_gemma":[0.99984396,0.000060446408,0.000013234773,0.00003097903,0.000043287106,0.00000804843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035849816,0.0008153154,0.0008313163,0.00030132913,0.00036458138,0.0007153548,0.0019265807,0.0011669502,0.0043693567],"category_scores_gemma":[0.0008205394,0.0004415075,0.001024854,0.00045998197,0.00047160508,0.0014014776,0.00056127325,0.0013845712,0.00092837913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001840362,0.00006122483,0.00022825494,0.00007460792,0.000022037617,0.000054265267,0.000029742545,0.9470208,0.0024249533,0.016379738,0.0021482243,0.031537805],"study_design_scores_gemma":[0.0000023733419,0.0000058693404,0.000050468185,0.0000027909227,0.000004903054,0.000008456011,0.0000011713677,0.9964915,0.0003129378,0.0023738628,0.0007417961,0.0000039053143],"about_ca_topic_score_codex":0.0084129935,"about_ca_topic_score_gemma":0.0059841434,"teacher_disagreement_score":0.0084129935,"about_ca_system_score_codex":0.0004498554,"about_ca_system_score_gemma":0.00079913344,"threshold_uncertainty_score":0.016728044},"labels":[],"label_agreement":null},{"id":"W1973921339","doi":"10.1115/imece2005-80640","title":"A Fracture Mechanics Approach to the Prediction of Tool Wear in Dry High Speed Machining of Aluminum Cast Alloys: Part 2 — Model Calibration and Verification","year":2005,"lang":"en","type":"article","venue":"Tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Calibration; Machining; Materials science; Tool wear; Fracture (geology); Cutting tool; Mechanical engineering; Fracture mechanics; Carbide; Experimental data; Range (aeronautics); Metallurgy; Composite material; Engineering; Mathematics","score_opus":0.012860961535893401,"score_gpt":0.2160445917645948,"score_spread":0.20318363022870142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973921339","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50805587,0.00033734043,0.4892238,0.000072030874,0.000020845258,0.00015792261,0.00016625733,0.0005809862,0.0013850041],"genre_scores_gemma":[0.97088563,0.00012114467,0.028134264,0.000009501379,0.000005052732,0.00011852393,0.00006828342,0.00002651981,0.0006309607],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976796,0.00004069482,0.00001319119,0.000037043977,0.000121791934,0.000019333494],"domain_scores_gemma":[0.99939954,0.0003549127,0.00006799049,0.00008397459,0.00008452561,0.000009105985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006568957,0.0006547082,0.00048593845,0.00049178983,0.00030280795,0.00048681424,0.0009339076,0.0012858246,0.0006522391],"category_scores_gemma":[0.001458495,0.00039295046,0.0005976885,0.00026255578,0.00041690364,0.0003942282,0.00028028444,0.0007135658,0.00015625506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048905393,0.000089875495,0.0019166772,0.00006759217,0.000016800715,0.000046647117,0.000043478773,0.96239716,0.018284975,0.0004328402,0.00005996758,0.016595088],"study_design_scores_gemma":[0.00000646693,0.000060612787,0.0010462154,0.0000020463526,0.0000025092675,0.000021709886,0.000005278874,0.99434894,0.004292814,0.00011801778,0.00009106262,0.0000043697805],"about_ca_topic_score_codex":0.0048579406,"about_ca_topic_score_gemma":0.0030101717,"teacher_disagreement_score":0.0048579406,"about_ca_system_score_codex":0.00045525972,"about_ca_system_score_gemma":0.0006409037,"threshold_uncertainty_score":0.00965929},"labels":[],"label_agreement":null},{"id":"W1973997452","doi":"10.4028/www.scientific.net/amr.797.73","title":"Feasibility Study on Grinding of Titanium Alloys with Electroplated CBN Wheels","year":2013,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Grind; Materials science; Grinding; Electroplating; Titanium alloy; Titanium; Metallurgy; Surface roughness; Grinding wheel; Alloy; Surface finish; Cutting fluid; Composite material; Layer (electronics); Machining","score_opus":0.038051530917667886,"score_gpt":0.337046147658498,"score_spread":0.2989946167408301,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973997452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98126686,0.00074933894,0.016751094,0.000049326885,0.000033983993,0.00010558382,0.000050142768,0.000107337895,0.0008862182],"genre_scores_gemma":[0.954766,0.0004431826,0.043108977,0.000031692696,0.000007815312,0.000041848445,0.00007677277,0.000035781664,0.0014878801],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99938846,0.000047134254,0.000029429775,0.00008849935,0.00038184627,0.000064644715],"domain_scores_gemma":[0.9993643,0.00019186683,0.00011148839,0.00007637082,0.00021452746,0.000041344327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000696509,0.00042373565,0.00054400036,0.00034094154,0.00026394325,0.00030797406,0.00057650346,0.00044683772,0.00086068007],"category_scores_gemma":[0.001279695,0.00030937692,0.00039652793,0.00021842628,0.00038314748,0.00042745148,0.00030619986,0.0003551597,0.00024268917],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005245328,0.000022998009,0.00039244018,0.00008220665,0.0000028993863,0.00006987414,0.000050777107,0.00026097425,0.9961683,0.00003532253,0.000016367048,0.0028454205],"study_design_scores_gemma":[0.00001326272,0.00063461054,0.0053432,0.000008916559,0.000011658157,0.00013488605,0.00006667729,0.0027098441,0.98979026,0.000023373765,0.0012525107,0.000010806542],"about_ca_topic_score_codex":0.0021987476,"about_ca_topic_score_gemma":0.0077944268,"teacher_disagreement_score":0.0021987476,"about_ca_system_score_codex":0.0004384174,"about_ca_system_score_gemma":0.00050967094,"threshold_uncertainty_score":0.004371941},"labels":[],"label_agreement":null},{"id":"W1974079588","doi":"10.1177/1077546307074243","title":"The Effects of Workpiece Deflection and Motor Features on Quality of Machining Process — Nonlinear Vibrations Analysis","year":2007,"lang":"en","type":"article","venue":"Journal of Vibration and Control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Vibration; Nonlinear system; Deflection (physics); Mechanical engineering; Cutting tool; Engineering; Machine tool; Structural engineering; Acoustics; Physics","score_opus":0.0041793693158139345,"score_gpt":0.2737033506272871,"score_spread":0.2695239813114732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974079588","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9029137,0.00021699796,0.09554403,0.0000421877,0.0000054223237,0.00002290217,0.000024158091,0.00006579368,0.0011648342],"genre_scores_gemma":[0.998418,0.00003270657,0.0013702948,0.0000025635168,0.000001151806,0.0000024724488,0.000008277912,0.0000054705724,0.00015899503],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970347,0.000074025294,0.000010562309,0.00004704459,0.00013243637,0.000032447315],"domain_scores_gemma":[0.9988294,0.00080746954,0.00015642977,0.00008371149,0.000101519145,0.00002140209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049483904,0.0002805328,0.00021684117,0.00017807304,0.00012448196,0.00027128236,0.00018198325,0.000305505,0.00088700844],"category_scores_gemma":[0.0019283951,0.00015767167,0.00024667318,0.000119742355,0.00038086687,0.00027559977,0.00024509008,0.00021996094,0.00012958054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011438724,0.00016182811,0.017510185,0.00032731463,0.00008267862,0.00037355733,0.0002761558,0.31631306,0.5790711,0.00061977655,0.000105222345,0.084015206],"study_design_scores_gemma":[0.00003374243,0.00094068196,0.06568117,0.000015062181,0.00004919276,0.00026789104,0.00012851002,0.79107684,0.14088883,0.00055526866,0.00032981747,0.000033014177],"about_ca_topic_score_codex":0.000861082,"about_ca_topic_score_gemma":0.00079172687,"teacher_disagreement_score":0.00088700844,"about_ca_system_score_codex":0.0001808692,"about_ca_system_score_gemma":0.0001300632,"threshold_uncertainty_score":0.0029673576},"labels":[],"label_agreement":null},{"id":"W1974788738","doi":"10.5539/mas.v2n2p112","title":"The Forming Theory and the NC Machining for The Rotary Burs with the Spectral Edge Distribution","year":2008,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Machining; Mechanical engineering; Engineering drawing; Distribution (mathematics); Computer science; Geometry; Manufacturing engineering; Engineering; Mathematics; Mathematical analysis; Artificial intelligence","score_opus":0.00567266399721054,"score_gpt":0.20082049581505,"score_spread":0.19514783181783946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974788738","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00614379,0.0017328694,0.96202576,0.0003151017,0.00029263625,0.00003643339,0.000052300533,0.00009554306,0.029305443],"genre_scores_gemma":[0.6141004,0.0048809433,0.340805,0.0003847292,0.00037198892,0.00020913297,0.00021964528,0.00016413469,0.038864095],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99952626,0.000052348623,0.000018430925,0.000094153154,0.000282967,0.000025789623],"domain_scores_gemma":[0.99971884,0.000054562744,0.00002333681,0.00003323979,0.00015844018,0.000011539081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046704258,0.0004378179,0.0004112596,0.00076913787,0.0006016123,0.00063693133,0.0009983139,0.0006593035,0.003592336],"category_scores_gemma":[0.00087232306,0.00028130095,0.0006352857,0.0006368837,0.0011223861,0.0018601037,0.00035019664,0.0008919601,0.00073335366],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005546945,0.000036062556,0.0008201642,0.0004432626,0.000029055722,0.00022773813,0.00043565198,0.10170504,0.031033972,0.78437454,0.006764761,0.074074164],"study_design_scores_gemma":[0.000019601763,0.00008777497,0.001372118,0.00006782453,0.000043112384,0.0008194885,0.00014833931,0.83349425,0.015259472,0.10398147,0.044618737,0.000087816836],"about_ca_topic_score_codex":0.005445139,"about_ca_topic_score_gemma":0.004024582,"teacher_disagreement_score":0.005445139,"about_ca_system_score_codex":0.0008981901,"about_ca_system_score_gemma":0.0008648125,"threshold_uncertainty_score":0.012017608},"labels":[],"label_agreement":null},{"id":"W1974914224","doi":"10.4028/www.scientific.net/amr.816-817.119","title":"Prediction of Updated Cutting Parameters for a Spindle Subjected to Bearing Wear: A Free Vibration-Based Approach","year":2013,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vibration; Bearing (navigation); Bending; Natural frequency; Structural engineering; Stability (learning theory); Spinning; Beam (structure); Engineering; Timoshenko beam theory; Settling time; Machine tool; Materials science; Mechanical engineering; Acoustics; Physics; Computer science; Control engineering; Step response","score_opus":0.042572220402432984,"score_gpt":0.29716991911457075,"score_spread":0.2545976987121378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974914224","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5737569,0.00030281677,0.42313388,0.00013496027,0.000021613938,0.00007980986,0.0002455039,0.00083711994,0.0014875258],"genre_scores_gemma":[0.9872433,0.00005597507,0.012218469,0.000010571404,0.000004304906,0.000028247196,0.0000904074,0.000021998309,0.0003266727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99992275,0.000013547356,0.0000052006044,0.000024749817,0.00002137802,0.000012393848],"domain_scores_gemma":[0.99929035,0.00039935787,0.00011719397,0.00003269771,0.00012893058,0.00003141762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035282352,0.00071084383,0.00070313836,0.0007195505,0.00022087997,0.0005429418,0.00060003833,0.001219184,0.0007082199],"category_scores_gemma":[0.0018073424,0.00060971477,0.00036838045,0.00027276273,0.00033556728,0.0004748846,0.00025815258,0.0005247126,0.0001812013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004596772,0.00002616106,0.0014065914,0.000031449006,0.000013792328,0.00006052441,0.000031280873,0.9861979,0.0024658307,0.00010055816,0.00009046442,0.009529443],"study_design_scores_gemma":[0.0000027210708,0.000010520464,0.00050473,0.0000014533664,0.0000019410875,0.000004484858,0.0000035222774,0.9991283,0.00026992054,0.0000533394,0.000016712558,0.000002299894],"about_ca_topic_score_codex":0.008088999,"about_ca_topic_score_gemma":0.0073348503,"teacher_disagreement_score":0.008088999,"about_ca_system_score_codex":0.00038112313,"about_ca_system_score_gemma":0.0005618559,"threshold_uncertainty_score":0.016083837},"labels":[],"label_agreement":null},{"id":"W1975235785","doi":"10.1006/jsvi.2000.3397","title":"CUTTING-INDUCED VIBRATION IN CIRCULAR SAWS","year":2001,"lang":"en","type":"article","venue":"Journal of Sound and Vibration","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Vibration; Displacement (psychology); Structural engineering; Instability; Stiffness; Gyroscope; Circular saw; Engineering; Mechanics; Physics; Acoustics; Blade (archaeology); Aerospace engineering","score_opus":0.012825079726581845,"score_gpt":0.24234317163913016,"score_spread":0.22951809191254832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975235785","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9521451,0.0002800202,0.04011814,0.00007444207,0.00004014845,0.000014843954,0.000026778169,0.000060615996,0.007239752],"genre_scores_gemma":[0.9978136,0.000041159135,0.0009328429,0.000005848902,0.0000066906987,0.0000035994442,0.000013809914,0.000009227134,0.0011731925],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999026,0.00001529235,0.0000029503142,0.000016922892,0.000038473536,0.000023688644],"domain_scores_gemma":[0.99972373,0.00015006053,0.000031995347,0.000013249257,0.000047827027,0.00003326431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016167632,0.00017694311,0.00020910747,0.0002672794,0.00024351687,0.00030770464,0.0002641245,0.00042757357,0.0020373284],"category_scores_gemma":[0.0006780997,0.0001918406,0.00013574932,0.00020407974,0.00054751034,0.0002360928,0.00031347206,0.0002825344,0.00019349321],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019572226,0.000367828,0.008988956,0.00032858198,0.000063507396,0.0015733745,0.0006495359,0.213442,0.6710649,0.037361063,0.001112079,0.06309096],"study_design_scores_gemma":[0.00008059462,0.0003528446,0.018180989,0.000016184187,0.000022409555,0.00050699164,0.00024911595,0.9373621,0.03534469,0.006832512,0.0010156116,0.00003595591],"about_ca_topic_score_codex":0.000368928,"about_ca_topic_score_gemma":0.0004035875,"teacher_disagreement_score":0.0020373284,"about_ca_system_score_codex":0.00017325842,"about_ca_system_score_gemma":0.00018027569,"threshold_uncertainty_score":0.006815493},"labels":[],"label_agreement":null},{"id":"W1975279313","doi":"10.1016/j.measurement.2014.12.033","title":"Effect of secondary hardening on cutting forces, cutting temperature, and tool wear in hard turning of high alloy tool steels","year":2014,"lang":"en","type":"article","venue":"Measurement","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machinability; Tempering; Materials science; Metallurgy; Hardening (computing); Machining; Alloy; Work hardening; Hardened steel; Tool wear; Composite material; Microstructure","score_opus":0.006411615373033485,"score_gpt":0.20378424633891784,"score_spread":0.19737263096588437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975279313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983271,0.000107547414,0.0012542035,0.000007496568,0.000006242162,0.0000037951722,0.00001941486,0.000024038003,0.00025011462],"genre_scores_gemma":[0.99946994,0.000018529423,0.0002976147,0.0000040793548,0.000002172581,0.0000013659032,0.000017740183,0.000006476968,0.00018200038],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99957186,0.000054168595,0.00002048465,0.00007388803,0.00020793344,0.00007169483],"domain_scores_gemma":[0.9971943,0.0016597805,0.00025985282,0.00023693715,0.0005050558,0.00014402591],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045200533,0.00031336123,0.00051219785,0.0005014084,0.00039080702,0.00040864918,0.0003222002,0.00054533145,0.00091904256],"category_scores_gemma":[0.0013860704,0.0002931634,0.0003786639,0.00028609505,0.0005234024,0.00033552907,0.00027352758,0.0005018215,0.00011425173],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025466706,0.00011135967,0.011275931,0.00013598788,0.00004458048,0.00015818617,0.00034148345,0.0029703646,0.96269983,0.000076190896,0.00010350228,0.019535873],"study_design_scores_gemma":[0.000042644704,0.002095052,0.1653218,0.000011398352,0.00006902347,0.00033275408,0.00013854,0.0152067905,0.8162201,0.00008651409,0.00043646235,0.000039066384],"about_ca_topic_score_codex":0.0014966776,"about_ca_topic_score_gemma":0.0026183992,"teacher_disagreement_score":0.0014966776,"about_ca_system_score_codex":0.00026712375,"about_ca_system_score_gemma":0.00017824427,"threshold_uncertainty_score":0.0030745268},"labels":[],"label_agreement":null},{"id":"W1975356408","doi":"10.1016/s0890-6955(02)00234-1","title":"Optimized feed scheduling in three axes machining","year":2002,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Scheduling (production processes); Machine tool; Ball screw; Gain scheduling; Engineering; Control theory (sociology); Tool path; Control engineering; Computer science; Mechanical engineering; Control system; Control (management); Operations management","score_opus":0.013069183802885484,"score_gpt":0.2378326859678843,"score_spread":0.2247635021649988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975356408","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32835808,0.00081246503,0.66135746,0.00018363819,0.00014380715,0.00011897202,0.00019840144,0.00057840865,0.008248684],"genre_scores_gemma":[0.8982742,0.00021073064,0.099081814,0.00002805273,0.000019114306,0.00006349538,0.00011490053,0.00010528562,0.0021023024],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978966,0.00006437874,0.000008962803,0.000029153554,0.00005621719,0.000051683328],"domain_scores_gemma":[0.99957997,0.000225389,0.00006226606,0.000026832195,0.00006845897,0.000037006575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043532113,0.0006516063,0.00095546374,0.00041029355,0.00043460648,0.00076671346,0.0007086391,0.0005881197,0.002225371],"category_scores_gemma":[0.0009236469,0.0005170827,0.00036752506,0.0008193568,0.0004462035,0.00046279657,0.0003791161,0.0005503986,0.00023206888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004790869,0.00008414774,0.0002981064,0.00007135208,0.000016925413,0.000046950514,0.000041391188,0.9562473,0.0064722733,0.0036774753,0.00061217236,0.03195282],"study_design_scores_gemma":[0.00003502886,0.00011657517,0.00030414874,0.0000033317187,0.00000630859,0.000009677273,0.000013016978,0.99518245,0.0019702835,0.0020298685,0.00032277007,0.0000065512368],"about_ca_topic_score_codex":0.0050783646,"about_ca_topic_score_gemma":0.004981383,"teacher_disagreement_score":0.0050783646,"about_ca_system_score_codex":0.00062968355,"about_ca_system_score_gemma":0.0009920072,"threshold_uncertainty_score":0.010097623},"labels":[],"label_agreement":null},{"id":"W1975613054","doi":"10.1016/s0921-5093(01)01752-x","title":"Quantitative evaluation of plastic strain gradients generated during orthogonal cutting of an aluminum alloy","year":2002,"lang":"en","type":"article","venue":"Materials Science and Engineering A","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Alloy; Aluminium; Materials science; Strain (injury); Plasticity; Composite material; Metallurgy; Medicine; Anatomy","score_opus":0.02268861915013454,"score_gpt":0.24936268118341648,"score_spread":0.22667406203328194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975613054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99663144,0.00008295777,0.0027860808,0.000006242266,0.0000040531204,0.000004252035,0.000038121816,0.000020854435,0.00042608177],"genre_scores_gemma":[0.9985285,0.00004415996,0.0011804493,0.0000036045556,0.0000022278975,0.0000030351896,0.000037078866,0.0000071945406,0.00019382263],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998989,0.0000107933665,0.0000034708012,0.000016947975,0.00005269473,0.000017157747],"domain_scores_gemma":[0.9996705,0.000120528646,0.000086125525,0.00002208293,0.000069657835,0.000031033025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015638549,0.00023154951,0.00018194021,0.0003030208,0.00016742399,0.00023259279,0.00015721019,0.00021281245,0.00043279503],"category_scores_gemma":[0.00038483998,0.00014511525,0.00008929721,0.00024734205,0.00026788734,0.00021556638,0.00013009632,0.00019710211,0.000042251242],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006317622,0.000048884373,0.0016890097,0.00004291654,0.0000082457545,0.000083794446,0.00006452589,0.0032234194,0.9858008,0.000114945295,0.000036867747,0.008254858],"study_design_scores_gemma":[0.000028685636,0.00080869085,0.048269268,0.000007934135,0.000027529542,0.00024806545,0.00009738807,0.04828602,0.9016319,0.00009911491,0.00046913838,0.000026299504],"about_ca_topic_score_codex":0.00047524917,"about_ca_topic_score_gemma":0.0006415625,"teacher_disagreement_score":0.00047524917,"about_ca_system_score_codex":0.00014911577,"about_ca_system_score_gemma":0.00013026365,"threshold_uncertainty_score":0.0014477968},"labels":[],"label_agreement":null},{"id":"W1975675284","doi":"10.1115/1.4007622","title":"Discrete-Time Prediction of Chatter Stability, Cutting Forces, and Surface Location Errors in Flexible Milling Systems","year":2012,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":169,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Vibration; Modal; Time domain; End mill; Eigenvalues and eigenvectors; Machining; Helix angle; Stability (learning theory); Machine tool; Differential equation; Modal analysis; Matrix (chemical analysis); Structural engineering; Engineering; Mathematical analysis; Control theory (sociology); Finite element method; Mathematics; Computer science; Mechanical engineering; Physics; Materials science; Acoustics","score_opus":0.009565089274849736,"score_gpt":0.2128415512784184,"score_spread":0.20327646200356866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975675284","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33429655,0.00017679192,0.66302866,0.00012890695,0.000030330943,0.000028516255,0.00006481193,0.00040551717,0.00183995],"genre_scores_gemma":[0.9950814,0.00003670386,0.0043089055,0.000004643877,0.000002468712,0.000012686304,0.000014910931,0.000007741364,0.0005304714],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983776,0.000033561853,0.000008717724,0.00003078693,0.00006827142,0.000020863965],"domain_scores_gemma":[0.9990846,0.000610372,0.00011737037,0.000044968103,0.00011557706,0.000027193939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044864952,0.000468827,0.0004820279,0.00026190726,0.00024180411,0.00047092806,0.00045901813,0.00057860743,0.0005610687],"category_scores_gemma":[0.0016873796,0.00028086518,0.0002898205,0.00013701349,0.0005749618,0.00038282893,0.00029260243,0.0007464699,0.00007757079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004139129,0.000014976742,0.00065425364,0.000018818933,0.0000075278917,0.000051804975,0.000040346375,0.9932126,0.0021566602,0.0010107426,0.0000411095,0.0027497574],"study_design_scores_gemma":[0.0000011104343,0.0000045704774,0.000082240316,5.665289e-7,6.477643e-7,0.0000022787783,0.0000012320997,0.9995994,0.00020985783,0.00008510919,0.000012119807,8.3592863e-7],"about_ca_topic_score_codex":0.0091768,"about_ca_topic_score_gemma":0.004331967,"teacher_disagreement_score":0.0091768,"about_ca_system_score_codex":0.00054079224,"about_ca_system_score_gemma":0.00039634312,"threshold_uncertainty_score":0.01824677},"labels":[],"label_agreement":null},{"id":"W1975860293","doi":"10.1081/mst-120034251","title":"Understanding and Characterizing the Drilling of Recycled Plastics","year":2004,"lang":"en","type":"article","venue":"Machining Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Machining; Drilling; Chip formation; Mechanical engineering; Brittleness; Materials science; Chip; Process (computing); Charpy impact test; Tool wear; Engineering; Composite material; Computer science; Toughness","score_opus":0.02220027693025668,"score_gpt":0.22428694241225486,"score_spread":0.2020866654819982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975860293","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95546913,0.00033474428,0.042597953,0.000017098624,0.0000030978838,0.000025200816,0.00013022698,0.00010152336,0.0013209656],"genre_scores_gemma":[0.9913277,0.00018217869,0.007997533,0.000004296019,7.623399e-7,0.00000868564,0.0000902175,0.00001247705,0.0003762391],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997693,0.000024201128,0.000012496524,0.000054372988,0.000108958106,0.00003066375],"domain_scores_gemma":[0.9996625,0.00010438116,0.00010095649,0.00004019442,0.00008330551,0.000008657987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022860561,0.0003098941,0.00021963651,0.0007357523,0.00014639765,0.00062468933,0.00037216002,0.0004467436,0.0006787763],"category_scores_gemma":[0.0006145858,0.0002677387,0.00022608553,0.00040715854,0.0003234951,0.0008713163,0.00021634284,0.00017304513,0.00018736334],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002482135,0.00009177597,0.044373266,0.0005575991,0.000045417106,0.00046192613,0.0005575715,0.09131879,0.7854539,0.0010680265,0.0001335735,0.075689875],"study_design_scores_gemma":[0.000009759773,0.0004646597,0.12854569,0.00006138239,0.000053977983,0.00065371755,0.0009548885,0.27762333,0.58708566,0.001176616,0.0033108327,0.0000595576],"about_ca_topic_score_codex":0.0016731787,"about_ca_topic_score_gemma":0.0019097459,"teacher_disagreement_score":0.0016731787,"about_ca_system_score_codex":0.0002942746,"about_ca_system_score_gemma":0.00025822004,"threshold_uncertainty_score":0.0033268332},"labels":[],"label_agreement":null},{"id":"W1976853631","doi":"10.1016/j.jmatprotec.2010.07.032","title":"Tapping of Al–Si alloys with diamond-like carbon coated tools and minimum quantity lubrication","year":2010,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor; Natural Sciences and Engineering Research Council of Canada","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada","keywords":"Tapping; Materials science; Lubrication; Metallurgy; Diamond-like carbon; Aluminium; Softening; Natural rubber; Composite material; Mechanical engineering; Engineering; Nanotechnology","score_opus":0.00755353728327796,"score_gpt":0.2288416455045281,"score_spread":0.22128810822125014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976853631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99270695,0.00042370535,0.0047079716,0.00006898755,0.00005517326,0.000014593729,0.00005585195,0.00016432547,0.0018025191],"genre_scores_gemma":[0.9942879,0.00009249961,0.0040035243,0.000012418093,0.0000062910713,0.0000031293705,0.00003698483,0.0000320608,0.0015251868],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998134,0.000013827565,0.000011516447,0.000031665742,0.00008815196,0.00004144496],"domain_scores_gemma":[0.99967873,0.00012058609,0.000044893262,0.000060320046,0.00006541812,0.000030070745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018866824,0.00024024537,0.00040386483,0.00026309304,0.0003205607,0.00037732537,0.00050930306,0.00048275586,0.0018112245],"category_scores_gemma":[0.0006426968,0.00029280753,0.0002127021,0.0002675208,0.0002981224,0.00036021968,0.00034403865,0.0002793494,0.00030177188],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000389032,0.000023890852,0.0002310361,0.0000786765,0.0000075911253,0.00014408152,0.00009376207,0.0009374258,0.9913447,0.00024620842,0.00018660656,0.0063170795],"study_design_scores_gemma":[0.000030794214,0.0003274467,0.0011346432,0.0000050489552,0.000008984287,0.00010598325,0.000057190362,0.010398105,0.9867862,0.00011622635,0.0010183182,0.000011140423],"about_ca_topic_score_codex":0.0010018493,"about_ca_topic_score_gemma":0.002467524,"teacher_disagreement_score":0.0018112245,"about_ca_system_score_codex":0.00034291632,"about_ca_system_score_gemma":0.00037360325,"threshold_uncertainty_score":0.00605917},"labels":[],"label_agreement":null},{"id":"W1977035133","doi":"10.1007/s12206-014-0608-2","title":"Analysis on nonlinear dynamics of a thin-plate workpiece in milling process with cutting force nonlinearities","year":2014,"lang":"en","type":"article","venue":"Journal of Mechanical Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Nonlinear system; Galerkin method; Cantilever; Equations of motion; Perturbation (astronomy); Displacement (psychology); Multiple-scale analysis; Chaotic; Classical mechanics; Plate theory; Mechanics; Structural engineering; Physics; Engineering; Finite element method; Computer science","score_opus":0.003780448907264408,"score_gpt":0.2319777816079506,"score_spread":0.2281973327006862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977035133","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5444952,0.00093879603,0.4326292,0.00066290086,0.00010494727,0.00009485401,0.00008535449,0.00013066891,0.020858115],"genre_scores_gemma":[0.98856,0.00025123052,0.00425107,0.000028764258,0.000025921221,0.000020642325,0.000035390058,0.000019710706,0.0068072146],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987733,0.000026504187,0.0000039769116,0.000026580683,0.000049612867,0.00001610247],"domain_scores_gemma":[0.9997694,0.00009870233,0.000039836545,0.000012361446,0.000061574494,0.000018136581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028204644,0.000520327,0.0005169213,0.00031780556,0.0005059224,0.00064362795,0.00061722595,0.00089426624,0.0014562975],"category_scores_gemma":[0.00064536533,0.00028066122,0.00064147817,0.00021363054,0.00084735465,0.0006805651,0.00056061085,0.00062161166,0.0001342014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013626418,0.000079500074,0.0022007741,0.00019012963,0.000084433756,0.0006274868,0.00025901932,0.9211308,0.047585394,0.018036665,0.000443585,0.009225932],"study_design_scores_gemma":[0.0000030956126,0.000018377152,0.0005069434,0.0000019558036,0.0000054974416,0.000022127833,0.000014448554,0.99813193,0.00066677196,0.00052131945,0.00010292316,0.0000046098685],"about_ca_topic_score_codex":0.0065069045,"about_ca_topic_score_gemma":0.003607838,"teacher_disagreement_score":0.0065069045,"about_ca_system_score_codex":0.00047431682,"about_ca_system_score_gemma":0.0005911404,"threshold_uncertainty_score":0.012938023},"labels":[],"label_agreement":null},{"id":"W1977429097","doi":"10.1179/003258901666194","title":"Characterisation of machinability of sintered steels during drilling operations","year":2001,"lang":"en","type":"article","venue":"Powder Metallurgy","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Fédération des Comités de Parents du Québec","funders":"","keywords":"Machinability; Materials science; Metallurgy; Drilling; Thrust; Scanning electron microscope; Tool wear; Hardening (computing); Flank; Manganese; Composite material; Machining; Mechanical engineering","score_opus":0.008745016668310037,"score_gpt":0.22248219263854407,"score_spread":0.21373717597023403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977429097","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99407625,0.00040903292,0.004864535,0.000010177211,0.000007697424,0.000028718207,0.00011527317,0.000047783793,0.0004404983],"genre_scores_gemma":[0.99284476,0.00023018486,0.005328371,0.000012184329,0.000003876393,0.000020825488,0.00023814832,0.000039045186,0.0012825072],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992976,0.0000564715,0.000053494558,0.00008968055,0.00045686748,0.000045822082],"domain_scores_gemma":[0.99887794,0.0002965185,0.00025634753,0.000112681795,0.000414704,0.00004175784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004929876,0.00036102155,0.00043454207,0.0008369141,0.00021974523,0.00041323536,0.0003386201,0.00046440266,0.00089980685],"category_scores_gemma":[0.0011774444,0.00031488194,0.0003490058,0.00042377203,0.00040186316,0.00033957005,0.00019476113,0.00031522618,0.00027257114],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012437796,0.000006845774,0.0024517088,0.00010563454,0.000008750385,0.00011791793,0.00019915955,0.00031731022,0.9920203,0.000013748708,0.000014390148,0.0046197544],"study_design_scores_gemma":[0.000008546163,0.00092604634,0.09500752,0.000022325603,0.000038558817,0.0005119736,0.00041209048,0.0025888844,0.89903677,0.000036051068,0.0013898766,0.000021400841],"about_ca_topic_score_codex":0.00080353674,"about_ca_topic_score_gemma":0.0022951073,"teacher_disagreement_score":0.00089980685,"about_ca_system_score_codex":0.00020655418,"about_ca_system_score_gemma":0.00012353798,"threshold_uncertainty_score":0.0030102134},"labels":[],"label_agreement":null},{"id":"W1979016889","doi":"10.1016/s0141-6359(03)00040-0","title":"Piezoelectric tool actuator for precision machining on conventional CNC turning centers","year":2003,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":111,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Actuator; Mechanical engineering; Machine tool; Servo; Voltage; Stiffness; Surface roughness; Natural frequency; Acoustics; Engineering; Materials science; Computer science; Vibration; Structural engineering; Electrical engineering; Physics","score_opus":0.008017510509758656,"score_gpt":0.22686739260373887,"score_spread":0.2188498820939802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979016889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92171323,0.00084031007,0.06159191,0.00020321972,0.00021162383,0.00007317668,0.0001362236,0.00029470187,0.014935617],"genre_scores_gemma":[0.9790618,0.00020583981,0.017088765,0.000027309745,0.000017017159,0.000018266446,0.00005551728,0.000017784625,0.0035077296],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978894,0.000012318828,0.0000062078025,0.00003370796,0.00013148545,0.000027443397],"domain_scores_gemma":[0.9997408,0.00008912677,0.000032136595,0.00002827017,0.000090876056,0.000018760345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027409068,0.00016050006,0.0002836961,0.00016533969,0.00031328146,0.00024489925,0.00059871783,0.00024613965,0.0023299584],"category_scores_gemma":[0.00042852675,0.0002072233,0.000085076,0.00027753387,0.00019966895,0.0004531613,0.0002951622,0.0003017339,0.00027773425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049359805,0.000053262138,0.0013211269,0.00014799598,0.0000059382664,0.00009291492,0.00009922505,0.0034593088,0.9435456,0.0023284312,0.0011455859,0.04730697],"study_design_scores_gemma":[0.0001318262,0.0010829575,0.028113471,0.000034327448,0.000040888357,0.0005005613,0.00021098943,0.07586841,0.8806311,0.0009736236,0.0123613775,0.000050498427],"about_ca_topic_score_codex":0.0015729623,"about_ca_topic_score_gemma":0.00523997,"teacher_disagreement_score":0.0023299584,"about_ca_system_score_codex":0.00040799487,"about_ca_system_score_gemma":0.0006147505,"threshold_uncertainty_score":0.00779444},"labels":[],"label_agreement":null},{"id":"W1979054414","doi":"10.1007/s12541-009-0049-5","title":"Evaluation of machinability according to the changes in machine tools and cooling lubrication environments and optimization of cutting conditions using Taguchi method","year":2009,"lang":"en","type":"article","venue":"International Journal of Precision Engineering and Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Machinability; Taguchi methods; Lubrication; Mechanical engineering; Engineering drawing; Engineering; Materials science; Manufacturing engineering; Metallurgy; Composite material; Machining","score_opus":0.02104867487645753,"score_gpt":0.3119525162385621,"score_spread":0.2909038413621046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979054414","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95680356,0.0007925094,0.04145037,0.000032781143,0.00003589406,0.000053376563,0.00005303538,0.00008195047,0.00069643755],"genre_scores_gemma":[0.97822636,0.000393772,0.02025214,0.0000177212,0.000009369434,0.000037195623,0.00006222089,0.00003009896,0.00097116956],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99948394,0.00010163151,0.000054060416,0.00007400607,0.00023391045,0.000052444797],"domain_scores_gemma":[0.99856573,0.0006631223,0.00022295452,0.000120273915,0.0003799785,0.000047910235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094118813,0.0004935372,0.000598166,0.00051059364,0.000246452,0.0005054245,0.0003597346,0.0005629081,0.00046118736],"category_scores_gemma":[0.0016696474,0.0004220399,0.00044766944,0.00055596087,0.0004526773,0.0006022806,0.000244439,0.00043765677,0.00010220488],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033369902,0.000038727965,0.0009787992,0.00007727978,0.00001540335,0.00002561728,0.000078015386,0.0010761765,0.9905978,0.000046817335,0.000015071448,0.006716681],"study_design_scores_gemma":[0.000018284753,0.0009039639,0.013405168,0.000003902497,0.00006950425,0.000072903145,0.000060191822,0.011042728,0.974046,0.00004196776,0.00030650484,0.000028847984],"about_ca_topic_score_codex":0.0005040274,"about_ca_topic_score_gemma":0.0009250023,"teacher_disagreement_score":0.00094118813,"about_ca_system_score_codex":0.00018994548,"about_ca_system_score_gemma":0.00017457362,"threshold_uncertainty_score":0.0049775243},"labels":[],"label_agreement":null},{"id":"W1979055615","doi":"10.1115/msec2011-50014","title":"Five-Axis CNC Tool Grinding: Part I—Rake Face Grinding","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Grinding; Rake; Grind; Rake angle; Face (sociological concept); Process (computing); Enhanced Data Rates for GSM Evolution; Constant (computer programming); Grinding wheel; Engineering drawing; Flute; Computer science; Mechanical engineering; Machining; Engineering; Computer vision; Acoustics; Physics","score_opus":0.022243142437777266,"score_gpt":0.21870462568504057,"score_spread":0.1964614832472633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979055615","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20121464,0.001320406,0.7775252,0.000088838584,0.00011397084,0.00042627193,0.0004005279,0.0013189876,0.01759124],"genre_scores_gemma":[0.6200144,0.000338349,0.37391135,0.000025651168,0.000015090419,0.00014053193,0.00043551187,0.0001531404,0.0049659316],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99922824,0.000035355286,0.000025429008,0.00015997478,0.000496049,0.00005508639],"domain_scores_gemma":[0.99957246,0.000060532486,0.00010401195,0.00010681954,0.0001402148,0.000015892247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053302967,0.0006268343,0.0007192159,0.0004924592,0.00037929,0.00079480384,0.0008780437,0.00055436284,0.0025763223],"category_scores_gemma":[0.0006894473,0.00030151475,0.0003383389,0.0005230877,0.0006815507,0.0003555881,0.0003083225,0.00046110537,0.00071668817],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046220695,0.0001229982,0.0031648255,0.0011192713,0.000031186042,0.00021037966,0.0002893457,0.09799753,0.65336573,0.010375698,0.0023394364,0.2305215],"study_design_scores_gemma":[0.000060013528,0.00092606,0.022200456,0.00006966619,0.000034313944,0.0011729528,0.000081511746,0.22151244,0.71832144,0.001640131,0.033835288,0.00014566546],"about_ca_topic_score_codex":0.0026500192,"about_ca_topic_score_gemma":0.003528297,"teacher_disagreement_score":0.0026500192,"about_ca_system_score_codex":0.00089593994,"about_ca_system_score_gemma":0.0009604027,"threshold_uncertainty_score":0.008618653},"labels":[],"label_agreement":null},{"id":"W1980181883","doi":"10.1016/s0278-6125(03)90010-0","title":"Development of an automated system for measuring grinding wheel wear flats","year":2003,"lang":"en","type":"article","venue":"Journal of Manufacturing Systems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pulverizer; Grinding; Grinding wheel; Process (computing); Mechanical engineering; Measure (data warehouse); Digital microscope; Surface grinding; Engineering; Position (finance); Software; Engineering drawing; Automotive engineering; Computer science; Microscope; Optics","score_opus":0.01946855293796963,"score_gpt":0.24529083617026218,"score_spread":0.22582228323229256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980181883","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0932981,0.00034884416,0.8721955,0.00012533361,0.00022723094,0.0008949846,0.0012124879,0.028753813,0.0029437689],"genre_scores_gemma":[0.2880867,0.00024303312,0.7025731,0.00024803472,0.00009589417,0.00074005075,0.001713463,0.00079262897,0.005507128],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99841213,0.00012845613,0.00008712158,0.0003647944,0.0009242118,0.00008328546],"domain_scores_gemma":[0.99732673,0.00067221135,0.0002145712,0.0004095851,0.0012614153,0.00011544766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011794778,0.0011574968,0.0013725052,0.002265365,0.00073766755,0.00096829736,0.0022948496,0.0011771623,0.0049370434],"category_scores_gemma":[0.0022205536,0.00083193876,0.000387839,0.0011695247,0.00038883358,0.0009583626,0.0008811237,0.00080101733,0.0023181206],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050217053,0.00057145377,0.013490021,0.00036913602,0.00014061837,0.0001590632,0.00026797398,0.0056612436,0.45897204,0.0010270533,0.0065681157,0.51227117],"study_design_scores_gemma":[0.0004941078,0.0021167772,0.054784622,0.00010125856,0.0002933934,0.0014620759,0.00015634984,0.29121268,0.6152624,0.0012520547,0.03254489,0.00031937973],"about_ca_topic_score_codex":0.0045708083,"about_ca_topic_score_gemma":0.0059128935,"teacher_disagreement_score":0.0049370434,"about_ca_system_score_codex":0.00049858884,"about_ca_system_score_gemma":0.0014958833,"threshold_uncertainty_score":0.01651609},"labels":[],"label_agreement":null},{"id":"W1981069952","doi":"10.1016/j.cirp.2010.03.078","title":"Identification and modeling of process damping in turning and milling using a new approach","year":2010,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":152,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Pratt and Whitney Canada; National Science Foundation","keywords":"Process (computing); Machining; Stability (learning theory); Engineering; Identification (biology); Frequency domain; Time domain; Damping ratio; Limit (mathematics); Control theory (sociology); Structural engineering; Mechanical engineering; Computer science; Mathematics; Mathematical analysis; Vibration; Physics; Acoustics","score_opus":0.04914106596752228,"score_gpt":0.31335799546074783,"score_spread":0.26421692949322556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981069952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009394576,0.00013227182,0.98928726,0.000032840544,0.000026465468,0.000012809305,0.0000087227745,0.00006359134,0.001041487],"genre_scores_gemma":[0.8005751,0.00090903084,0.18891089,0.000084696054,0.000114083654,0.00021863855,0.0000847451,0.00009609483,0.009006843],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997826,0.000045974088,0.000015301177,0.00005009504,0.000086669716,0.000019461067],"domain_scores_gemma":[0.99965453,0.00019340678,0.0000417827,0.00002841612,0.000069030335,0.00001277994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004774345,0.00084164774,0.000839078,0.00055708573,0.00037730325,0.0007877504,0.0009840211,0.0011239268,0.0010118406],"category_scores_gemma":[0.0010235333,0.0006015724,0.0009470513,0.00031287762,0.00061904726,0.0008594778,0.00076223793,0.000952669,0.00030958967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028204322,0.00003692297,0.00027584375,0.00004657141,0.000039237897,0.000053922842,0.000056262645,0.97105116,0.006706171,0.005068651,0.000083692576,0.01655338],"study_design_scores_gemma":[0.0000017573817,0.000007396983,0.000038928374,0.0000011136464,0.0000035612525,0.0000046541536,0.0000019307413,0.9992894,0.0002030643,0.0003124049,0.00013390063,0.0000019055105],"about_ca_topic_score_codex":0.004822009,"about_ca_topic_score_gemma":0.0044764923,"teacher_disagreement_score":0.004822009,"about_ca_system_score_codex":0.0003662647,"about_ca_system_score_gemma":0.0004738979,"threshold_uncertainty_score":0.009587884},"labels":[],"label_agreement":null},{"id":"W1981535490","doi":"10.1007/s00170-004-2443-6","title":"Erratum to: State-of-the-art methods and results in tool condition monitoring: a review","year":2004,"lang":"en","type":"review","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":289,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Western University","funders":"","keywords":"Industrial and production engineering; State (computer science); Computer science; State of art; Engineering; Data science; Mechanical engineering; Algorithm","score_opus":0.016920093229883346,"score_gpt":0.35846058370042694,"score_spread":0.3415404904705436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981535490","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022837367,0.8357089,0.0016343512,0.01189663,0.14860588,0.000046569454,0.00034226137,0.000071928494,0.0014651048],"genre_scores_gemma":[0.0018166899,0.9292343,0.0034844556,0.015778596,0.035697535,0.0000701109,0.00064419996,0.00007863882,0.013195504],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980203,0.00018395094,0.0005142051,0.00024929608,0.0009442493,0.00008791995],"domain_scores_gemma":[0.98786443,0.0040569426,0.001145983,0.00031995936,0.0062422287,0.00037045032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027211963,0.0016353894,0.003439637,0.004892927,0.00070214027,0.0020357284,0.002919909,0.0036176902,0.009359078],"category_scores_gemma":[0.01431156,0.00069547206,0.0009999736,0.0052337153,0.0012304174,0.003641228,0.0011030093,0.0035235405,0.013076544],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020962169,0.000061458806,0.00024032946,0.014363312,0.00010436485,0.00046262535,0.00006820683,0.00018090417,0.0012793837,0.001089917,0.6208657,0.36107418],"study_design_scores_gemma":[0.000040375962,0.00015909127,0.0010020599,0.0031708176,0.00026036965,0.001996853,0.00007691501,0.00012678167,0.0014979782,0.0009760953,0.99062705,0.000065648186],"about_ca_topic_score_codex":0.0026926205,"about_ca_topic_score_gemma":0.0051705902,"teacher_disagreement_score":0.009359078,"about_ca_system_score_codex":0.0008804817,"about_ca_system_score_gemma":0.0027194705,"threshold_uncertainty_score":0.031309307},"labels":[],"label_agreement":null},{"id":"W1981977350","doi":"10.4028/www.scientific.net/amr.188.584","title":"Robotic High Speed Machining of Aluminum Alloys","year":2011,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Rigidity (electromagnetism); Vibration; Mechanical engineering; Stiffness; Stability (learning theory); Acceleration; Process (computing); Robot; Engineering; Computer science; Structural engineering; Acoustics; Artificial intelligence; Physics","score_opus":0.05689940003803647,"score_gpt":0.31628207672540415,"score_spread":0.2593826766873677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981977350","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86222345,0.0012326508,0.13068192,0.00005137446,0.0000299604,0.00007665409,0.00006288267,0.0003367605,0.0053044586],"genre_scores_gemma":[0.9641863,0.00016139411,0.03367807,0.000009163371,0.000007595448,0.000030429812,0.000045268822,0.000014937572,0.0018667312],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99963236,0.00005371341,0.000011554974,0.000039515387,0.0002411066,0.000021722577],"domain_scores_gemma":[0.99968874,0.00010772965,0.00007422292,0.000039833332,0.00008084298,0.000008615532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048289713,0.00024140695,0.00021943223,0.00053944776,0.00017856018,0.00025967121,0.00032742726,0.00022597928,0.0008621587],"category_scores_gemma":[0.0007075291,0.0001707485,0.00014305142,0.00026954443,0.00024211875,0.00025705522,0.00022896488,0.00014082104,0.00022041546],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005425995,0.00006926737,0.0032320812,0.00030952995,0.000031637457,0.00016921615,0.00023223329,0.03846117,0.7615832,0.0016430259,0.00065664115,0.19306943],"study_design_scores_gemma":[0.00015710725,0.0031337775,0.08035818,0.000050738956,0.000057236382,0.0013131202,0.00021392682,0.42414233,0.47439778,0.0027090728,0.0133448895,0.00012185962],"about_ca_topic_score_codex":0.00078474445,"about_ca_topic_score_gemma":0.0010928962,"teacher_disagreement_score":0.0008621587,"about_ca_system_score_codex":0.00016660019,"about_ca_system_score_gemma":0.00017565327,"threshold_uncertainty_score":0.0028842092},"labels":[],"label_agreement":null},{"id":"W1983185388","doi":"10.1115/1.4023453","title":"Position-Dependent Multibody Dynamic Modeling of Machine Tools Based on Improved Reduced Order Models","year":2013,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Tehran University of Medical Sciences and Health Services","keywords":"Machine tool; Position (finance); Stability (learning theory); Computer science; Modal; Frequency response; Modal analysis; Control theory (sociology); Finite element method; Function (biology); Constraint (computer-aided design); Engineering; Artificial intelligence; Structural engineering; Mechanical engineering; Control (management); Machine learning","score_opus":0.006866576807405959,"score_gpt":0.21415792110443566,"score_spread":0.2072913442970297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983185388","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03506277,0.00011996641,0.95975983,0.000045777724,0.000017545124,0.00003965818,0.000107353066,0.00034049337,0.0045066676],"genre_scores_gemma":[0.84663194,0.0003739036,0.14461604,0.000029356746,0.000019195131,0.00025681575,0.000327494,0.000157736,0.007587516],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998516,0.00003213075,0.000006422926,0.000019686888,0.00007665088,0.0000134695365],"domain_scores_gemma":[0.9998234,0.00006157459,0.000034305427,0.000032751926,0.000041098727,0.000006841386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021305995,0.00048514773,0.00053224835,0.00042977856,0.00020052848,0.00055386376,0.0008395747,0.00060513086,0.0013713966],"category_scores_gemma":[0.00052648486,0.0003504548,0.0008405373,0.0002621421,0.00032462427,0.0005136149,0.0002882006,0.0005913616,0.00041821078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001005799,0.000009028718,0.00013571438,0.000021976988,0.0000068260188,0.000023921315,0.000029623967,0.9870487,0.00550385,0.0032296858,0.00007912542,0.0039014781],"study_design_scores_gemma":[0.0000013969307,0.000006566082,0.00005198795,9.837937e-7,0.000001494972,0.000003209564,0.0000015552308,0.9989225,0.0003692576,0.00037630685,0.00026314784,0.0000015107432],"about_ca_topic_score_codex":0.0050392086,"about_ca_topic_score_gemma":0.0044995435,"teacher_disagreement_score":0.0050392086,"about_ca_system_score_codex":0.0004156883,"about_ca_system_score_gemma":0.0005326508,"threshold_uncertainty_score":0.010019779},"labels":[],"label_agreement":null},{"id":"W1983660691","doi":"10.1007/s00170-012-4612-3","title":"Cutting force prediction for ball-end mills with non-horizontal and rotational cutting motions","year":2012,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Ball (mathematics); End mill; Mechanical engineering; End milling; Engineering; Chip; Rotational speed; Cutting tool; Structural engineering; Computer science; Geometry; Mathematics","score_opus":0.004359109010505683,"score_gpt":0.22450435290466708,"score_spread":0.2201452438941614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983660691","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24366768,0.00023727615,0.75312686,0.00004997175,0.000017708575,0.000060985927,0.00006764737,0.00024302535,0.0025288514],"genre_scores_gemma":[0.9687533,0.00011912367,0.029628243,0.0000097384345,0.0000039918386,0.0000405596,0.000068176545,0.000019347623,0.001357376],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998179,0.000025994146,0.000008629845,0.00003541267,0.00009044435,0.00002169886],"domain_scores_gemma":[0.9996543,0.00017794302,0.000067411886,0.00003430856,0.000052138435,0.000013761488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042054272,0.0005187169,0.00047989975,0.00030158693,0.00024544037,0.0004977773,0.00078116544,0.0012098472,0.0007658073],"category_scores_gemma":[0.00073661,0.00035037496,0.0005535223,0.00018506368,0.00035774347,0.00047132533,0.0003666595,0.00058395823,0.00022437742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045183155,0.000049445374,0.0015987388,0.0000404918,0.000006985045,0.00009688332,0.000038796945,0.96645623,0.016677538,0.00090413034,0.00009688739,0.013988735],"study_design_scores_gemma":[0.0000018273179,0.00001638809,0.00033055243,0.0000011794675,8.205603e-7,0.000009924174,0.0000031471493,0.99857676,0.00089177437,0.00011658477,0.000048879487,0.000002128351],"about_ca_topic_score_codex":0.0035778878,"about_ca_topic_score_gemma":0.0030285735,"teacher_disagreement_score":0.0035778878,"about_ca_system_score_codex":0.00025838183,"about_ca_system_score_gemma":0.0004459033,"threshold_uncertainty_score":0.0071141124},"labels":[],"label_agreement":null},{"id":"W1983996627","doi":"10.1115/detc2013-12992","title":"Optimization of the Cutting Conditions for High Speed Drilling of Woven Composites","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Surface roughness; Population; Kriging; Thrust; Drilling; Evolutionary algorithm; Computer science; Delamination (geology); Mathematical optimization; Algorithm; Mathematics; Engineering; Mechanical engineering; Materials science; Machine learning; Geology","score_opus":0.0058202358080224675,"score_gpt":0.2121995554620242,"score_spread":0.20637931965400175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983996627","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.118189834,0.00030533064,0.87881505,0.000054750915,0.000017418224,0.00012062761,0.000039480423,0.00026496692,0.0021924705],"genre_scores_gemma":[0.58206654,0.00023471049,0.4161024,0.00002739319,0.000008366586,0.0002352619,0.000113750895,0.000087826316,0.0011236317],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99972135,0.00006740818,0.000015746798,0.000055982237,0.000101445876,0.00003811429],"domain_scores_gemma":[0.9995566,0.00025246883,0.00008701573,0.000023090386,0.00006900705,0.000011865221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069060107,0.0006773449,0.00062348426,0.00056215294,0.00031809477,0.0006981565,0.00050384965,0.000882075,0.001036854],"category_scores_gemma":[0.001625864,0.0005146504,0.00048101606,0.00029548063,0.00041856576,0.00074503117,0.0003994461,0.0005539256,0.00026703128],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008863326,0.00008682747,0.001216779,0.00017067978,0.000026103473,0.00007084814,0.0001029617,0.894297,0.036417194,0.0017842612,0.00024834686,0.065490335],"study_design_scores_gemma":[0.000020151407,0.00012525314,0.0006593635,0.000014520011,0.000009173241,0.000041651478,0.000055077573,0.98869705,0.008912107,0.00069905346,0.00075551786,0.000011047032],"about_ca_topic_score_codex":0.0012667008,"about_ca_topic_score_gemma":0.0021777651,"teacher_disagreement_score":0.0012667008,"about_ca_system_score_codex":0.00037963223,"about_ca_system_score_gemma":0.0007914829,"threshold_uncertainty_score":0.0036522746},"labels":[],"label_agreement":null},{"id":"W1984202013","doi":"10.1016/s0007-8506(07)60032-8","title":"Chatter Stability of Metal Cutting and Grinding","year":2004,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":827,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Grinding; Machining; Time domain; Engineering; Vibration; Stability (learning theory); Frequency domain; Mechanical engineering; Process (computing); Point (geometry); Control theory (sociology); Control engineering; Computer science; Mathematics; Acoustics; Artificial intelligence","score_opus":0.027209787458202045,"score_gpt":0.2630359449672002,"score_spread":0.23582615750899813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984202013","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7342082,0.0015599466,0.23220928,0.00069116306,0.00026003414,0.000049904316,0.00010744981,0.00030867718,0.03060532],"genre_scores_gemma":[0.98579305,0.00012278139,0.0049420376,0.00003251423,0.000042519852,0.000018637922,0.000036255162,0.00007166606,0.008940515],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99954575,0.00016832614,0.000015877096,0.0000820252,0.000114758135,0.00007330022],"domain_scores_gemma":[0.99482745,0.0031649107,0.000503749,0.00025712868,0.00085137907,0.0003953419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013412271,0.00051668775,0.0006444658,0.0012530348,0.0009093323,0.0010565127,0.00093019294,0.000993893,0.005241181],"category_scores_gemma":[0.00860787,0.0003468521,0.00043831565,0.00033076832,0.0019173943,0.0010886312,0.0010623732,0.0009908982,0.0004774855],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028491542,0.0002110239,0.004065899,0.00036056395,0.00012110481,0.0005809055,0.0010992122,0.37763754,0.07285042,0.5015017,0.0032374547,0.03548492],"study_design_scores_gemma":[0.000030754447,0.00010954104,0.0021799821,0.00001685899,0.000016465374,0.00008625182,0.00011736726,0.9486889,0.007970854,0.040265583,0.00047360512,0.000043842727],"about_ca_topic_score_codex":0.0031861905,"about_ca_topic_score_gemma":0.0024935151,"teacher_disagreement_score":0.005241181,"about_ca_system_score_codex":0.0008166852,"about_ca_system_score_gemma":0.00063052797,"threshold_uncertainty_score":0.01753354},"labels":[],"label_agreement":null},{"id":"W1984222652","doi":"10.1016/s0924-0136(02)00453-3","title":"Relationship between tool flank wear area and component forces in single point turning","year":2002,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Flank; Dynamometer; Mechanical engineering; Coolant; Materials science; Structural engineering; Engineering","score_opus":0.02393986729472132,"score_gpt":0.2333754146136625,"score_spread":0.2094355473189412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984222652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99891996,0.000096980155,0.0006684404,0.0000071376403,0.0000031357656,0.0000024338271,0.00002073521,0.000017417822,0.00026392756],"genre_scores_gemma":[0.9998518,0.000013601931,0.000056176632,9.2724866e-7,9.491263e-7,7.9513e-7,0.000009409677,0.0000019373038,0.00006431923],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998559,0.000025865898,0.00000814405,0.0000204043,0.000042797543,0.00004689117],"domain_scores_gemma":[0.9956002,0.0035218222,0.00030431445,0.000081581595,0.00036481253,0.00012726936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003503781,0.00021015263,0.00041739078,0.0009930667,0.00031624085,0.00037990717,0.00028672966,0.0005309069,0.0013508056],"category_scores_gemma":[0.0021917692,0.00028088715,0.00030045217,0.00042306588,0.000289106,0.00030870104,0.00017763127,0.00035759344,0.00015373967],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.013420637,0.0008032364,0.30840477,0.0005082762,0.00033208443,0.0030864917,0.001105195,0.23617963,0.33274674,0.0011938149,0.0010462234,0.101172954],"study_design_scores_gemma":[0.0000819934,0.0022385574,0.64124316,0.000027636232,0.00014555447,0.0018582485,0.0005412117,0.30461782,0.04784443,0.0009938356,0.0003270545,0.00008054595],"about_ca_topic_score_codex":0.0017429622,"about_ca_topic_score_gemma":0.0029266959,"teacher_disagreement_score":0.0017429622,"about_ca_system_score_codex":0.00020915412,"about_ca_system_score_gemma":0.00016660384,"threshold_uncertainty_score":0.004518926},"labels":[],"label_agreement":null},{"id":"W1984349687","doi":"10.1007/s00170-006-0826-6","title":"Joint identification of modular tools using a novel receptance coupling method","year":2007,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Modular design; Vibration; Flexibility (engineering); Joint (building); Machining; Coupling (piping); Engineering; Machine tool; Modularity (biology); Finite element method; Computer science; Mechanical engineering; Structural engineering; Mathematics","score_opus":0.020322122165722073,"score_gpt":0.2946884496932045,"score_spread":0.27436632752748247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984349687","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007429998,0.000031182703,0.99192625,0.000006831964,0.00000961178,0.000011425772,0.000005322342,0.00011891414,0.00046042175],"genre_scores_gemma":[0.5342696,0.0001363726,0.460889,0.000032885328,0.00002430257,0.00014193698,0.0000889465,0.000118111064,0.004298736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99956363,0.00013165768,0.0000224254,0.00009486927,0.00015204416,0.000035431905],"domain_scores_gemma":[0.9995559,0.00018275336,0.00007549793,0.00007586161,0.00008981921,0.000020080535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070562446,0.0010706903,0.0007084362,0.00060886086,0.0003817465,0.00048622527,0.0009995331,0.0010637449,0.001436077],"category_scores_gemma":[0.0013220904,0.00048584628,0.00085935695,0.00046078398,0.00038604907,0.0011023975,0.0008765169,0.00048751404,0.0006273025],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032477314,0.00010292292,0.0011874503,0.0002784612,0.00018378414,0.00027151615,0.0002211933,0.5615368,0.17731354,0.018888282,0.00064520916,0.23904604],"study_design_scores_gemma":[0.0000087491,0.0000963035,0.00028068756,0.0000063401512,0.000016418353,0.000060106544,0.000010766998,0.989305,0.008050428,0.0013227673,0.000826341,0.000016178628],"about_ca_topic_score_codex":0.0007352308,"about_ca_topic_score_gemma":0.001061932,"teacher_disagreement_score":0.001436077,"about_ca_system_score_codex":0.00014842494,"about_ca_system_score_gemma":0.0003973358,"threshold_uncertainty_score":0.004804194},"labels":[],"label_agreement":null},{"id":"W1984439717","doi":"10.1016/s0007-8506(07)60127-9","title":"Virtual Design and Optimization of Machine Tool Spindles","year":2005,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":148,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machine tool; Engineering; Stiffness; Bearing (navigation); Finite element method; Structural engineering; Process (computing); Point (geometry); Mechanical engineering; Work (physics); Computer science; Geometry","score_opus":0.01880337815182132,"score_gpt":0.25396929762101267,"score_spread":0.23516591946919135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984439717","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15496014,0.0005900724,0.8257308,0.00015863094,0.00014071062,0.00008787762,0.00006914605,0.00036549335,0.017897215],"genre_scores_gemma":[0.93091893,0.00022814266,0.06490681,0.000031396987,0.000023912758,0.00010363146,0.000065308195,0.00010186069,0.0036201354],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997334,0.00009297464,0.000008375158,0.000027100394,0.00010448008,0.000033647182],"domain_scores_gemma":[0.9995204,0.00026487795,0.000057415193,0.00003162146,0.000095861644,0.000029740653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006428019,0.00056948623,0.00084774423,0.0006356969,0.0003355654,0.0011023686,0.0008366665,0.0007386788,0.00279711],"category_scores_gemma":[0.0016673545,0.0006486047,0.00060577714,0.000388198,0.0006237678,0.00053916377,0.0007437288,0.00038832368,0.00024668826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057239078,0.000013348467,0.00012948178,0.00002831865,0.0000074520854,0.00001808745,0.000014014618,0.9857739,0.0010993164,0.0022950429,0.0001564454,0.01040722],"study_design_scores_gemma":[0.0000112963535,0.000059466296,0.00010040083,0.0000043526416,0.0000037851833,0.000008703693,0.000007740022,0.99762803,0.0004935381,0.0011023806,0.0005773631,0.0000029294824],"about_ca_topic_score_codex":0.0015905866,"about_ca_topic_score_gemma":0.0014708632,"teacher_disagreement_score":0.00279711,"about_ca_system_score_codex":0.0005299286,"about_ca_system_score_gemma":0.0007273663,"threshold_uncertainty_score":0.009357214},"labels":[],"label_agreement":null},{"id":"W1984606252","doi":"10.1109/isma.2012.6215180","title":"Hole quality assessment in peck drilling","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Peck (Imperial); Drilling; Surface roughness; Drill; Surface finish; Geology; Quality (philosophy); Materials science; Engineering drawing; Engineering; Composite material; Geometry; Metallurgy; Mathematics; Physics","score_opus":0.027622786151917388,"score_gpt":0.32390726623162963,"score_spread":0.29628448007971225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984606252","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9798995,0.00054980634,0.018393796,0.000027445982,0.00001935022,0.000033160264,0.00007250077,0.00011600581,0.0008884204],"genre_scores_gemma":[0.9941346,0.00010400709,0.0053072656,0.000008622798,0.0000023989562,0.0000048413917,0.00007414926,0.000017129521,0.0003470502],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983272,0.00012690858,0.00006544292,0.00017595214,0.001214424,0.000090129506],"domain_scores_gemma":[0.9978935,0.00039128796,0.00043309072,0.00018536586,0.0010276687,0.00006909858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074351125,0.00026031572,0.00038992416,0.00059614755,0.00021082938,0.0005638505,0.0003480535,0.0005760816,0.0009960543],"category_scores_gemma":[0.0024837577,0.00026139335,0.00028983902,0.00029322883,0.0004654553,0.0005910948,0.0005680082,0.00022082732,0.00016499746],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007596151,0.000059293397,0.023597209,0.00041082792,0.000047860078,0.00038635585,0.00037616643,0.00742386,0.9052916,0.00017276085,0.00023516027,0.0612393],"study_design_scores_gemma":[0.000047509322,0.0029791952,0.19926363,0.00004966073,0.000117707765,0.0016621895,0.00066941464,0.035675388,0.7567205,0.0002770889,0.0024413283,0.00009641363],"about_ca_topic_score_codex":0.0008009154,"about_ca_topic_score_gemma":0.0015936041,"teacher_disagreement_score":0.0009960543,"about_ca_system_score_codex":0.00025084862,"about_ca_system_score_gemma":0.00013693329,"threshold_uncertainty_score":0.0039321184},"labels":[],"label_agreement":null},{"id":"W1985100752","doi":"10.1016/j.ijmachtools.2006.09.019","title":"An expert troubleshooting system for the milling process","year":2007,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Troubleshooting; Expert system; Inference engine; Cutting tool; Robustness (evolution); Vibration; Engineering; Process (computing); Tool wear; Computer science; Machining; Mechanical engineering; Artificial intelligence; Reliability engineering; Acoustics","score_opus":0.01035453332720781,"score_gpt":0.2895572288539422,"score_spread":0.2792026955267344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985100752","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03909892,0.00054697844,0.7507952,0.00013644969,0.00010993724,0.0005923425,0.0025795074,0.19814453,0.007996171],"genre_scores_gemma":[0.3054444,0.00046939746,0.6446217,0.00046255483,0.00011700585,0.0006678322,0.0075422428,0.00636925,0.034305725],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991007,0.000122938,0.00007374946,0.00027951738,0.0003693999,0.000053667794],"domain_scores_gemma":[0.9968611,0.0014950867,0.00018678971,0.0005548353,0.0007244969,0.00017759464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092413195,0.0013203432,0.0010623924,0.0014266566,0.0005277668,0.00078053924,0.0017365061,0.0010004638,0.040467642],"category_scores_gemma":[0.0027071596,0.0006669873,0.00034401176,0.00070073886,0.0002503001,0.0010119197,0.00073675497,0.0006841143,0.008068015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016083361,0.00042787072,0.003092771,0.00064357865,0.00008204516,0.00047603867,0.00031608297,0.009200535,0.087739915,0.00092874665,0.04458859,0.8508955],"study_design_scores_gemma":[0.0011015676,0.0014373441,0.025988441,0.00027779402,0.00035933772,0.00350966,0.00024931578,0.5224823,0.264244,0.004026146,0.17593738,0.00038678953],"about_ca_topic_score_codex":0.0018226608,"about_ca_topic_score_gemma":0.0023173818,"teacher_disagreement_score":0.040467642,"about_ca_system_score_codex":0.00033588157,"about_ca_system_score_gemma":0.00097476697,"threshold_uncertainty_score":0.13537776},"labels":[],"label_agreement":null},{"id":"W1985928065","doi":"10.1115/1.4023271","title":"An Automated and Accurate CNC Programming Approach to Five-Axis Flute Grinding of Cylindrical End-Mills Using the Direct Method","year":2013,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Grinding; Rake angle; Rake; Enhanced Data Rates for GSM Evolution; Computer science; Grinding wheel; RADIUS; Mechanical engineering; Numerical control; End mill; Rigidity (electromagnetism); Engineering drawing; Engineering; Structural engineering; Machining; Computer vision","score_opus":0.012561728495027525,"score_gpt":0.278742994295948,"score_spread":0.2661812658009205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985928065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034904238,0.000024280802,0.9951143,0.000012241705,0.0000051366023,0.000025149438,0.000011268375,0.00022215574,0.0010949122],"genre_scores_gemma":[0.11673175,0.0001127341,0.88070476,0.000022538201,0.000011008256,0.00014808518,0.00009422611,0.00016095156,0.0020139583],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99958616,0.00005986427,0.000016415392,0.00008676821,0.00021428653,0.00003649681],"domain_scores_gemma":[0.9996295,0.00013067437,0.00003108664,0.000032153985,0.00016341619,0.0000131925835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043426588,0.00067609636,0.0005908602,0.0004792305,0.0005383552,0.000621407,0.0012271268,0.0003747765,0.00208398],"category_scores_gemma":[0.00080671837,0.0005025618,0.0005780763,0.00040338925,0.00047807183,0.00052369456,0.0005309598,0.0010115765,0.0004944736],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058261434,0.000052306164,0.0008457307,0.00017962069,0.000014506347,0.00016901053,0.0002474073,0.7444579,0.029832182,0.020284263,0.0014159732,0.20244288],"study_design_scores_gemma":[0.000007131411,0.000023308232,0.00009025577,0.0000053338454,0.0000028396946,0.000037537433,0.000012607085,0.9941923,0.0027000587,0.0013320461,0.0015879215,0.000008693917],"about_ca_topic_score_codex":0.0091325985,"about_ca_topic_score_gemma":0.010343537,"teacher_disagreement_score":0.0091325985,"about_ca_system_score_codex":0.00060720864,"about_ca_system_score_gemma":0.001637058,"threshold_uncertainty_score":0.018158853},"labels":[],"label_agreement":null},{"id":"W1985934471","doi":"10.1504/ijmmm.2007.013789","title":"Influence of material structure on deep hole machinability of super high strength steels: application to crankshaft manufacturing","year":2007,"lang":"en","type":"article","venue":"International Journal of Machining and Machinability of Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mitel (Canada)","funders":"H2020 European Research Council","keywords":"Machinability; Crankshaft; Forging; Machining; Materials science; Metallurgy; Ultimate tensile strength; Lubrication; Drilling; Mechanical engineering; Manufacturing engineering; Engineering; Composite material","score_opus":0.0028400404113322775,"score_gpt":0.2434119196904653,"score_spread":0.240571879279133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985934471","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977825,0.00036266353,0.00130049,0.000007791496,0.0000020274106,0.000008749303,0.000017245584,0.000017290575,0.0005011749],"genre_scores_gemma":[0.99904734,0.00009515753,0.0007049684,0.0000016109439,7.4111716e-7,0.0000015112374,0.000011831408,0.000004219536,0.00013256383],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99974984,0.000050501694,0.000012511735,0.00003069888,0.00012003438,0.000036398742],"domain_scores_gemma":[0.99903286,0.00047281757,0.00021591641,0.00007654088,0.00015701557,0.000044883556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033141792,0.00031345742,0.00025282422,0.00039700302,0.00017812858,0.00035544945,0.00024626055,0.00041986976,0.00064553786],"category_scores_gemma":[0.0012097722,0.00021795592,0.00017857498,0.0002917303,0.0003695778,0.00025542956,0.00021003303,0.00016698905,0.00012780183],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000809725,0.0000713394,0.0034281241,0.0001953357,0.000012627832,0.00017217564,0.00014788381,0.010166311,0.9747046,0.00013079957,0.000028746996,0.01013224],"study_design_scores_gemma":[0.00003560449,0.0026852842,0.017637044,0.000011140397,0.000043463657,0.00017347319,0.00008742093,0.013299073,0.9654614,0.000101707774,0.00045047607,0.000013965954],"about_ca_topic_score_codex":0.0007367518,"about_ca_topic_score_gemma":0.0011997244,"teacher_disagreement_score":0.0007367518,"about_ca_system_score_codex":0.00020302161,"about_ca_system_score_gemma":0.00010642451,"threshold_uncertainty_score":0.0021595955},"labels":[],"label_agreement":null},{"id":"W1986984388","doi":"10.1016/j.ijmachtools.2007.10.010","title":"Comparison of numerically and analytically predicted contact temperatures in shallow and deep dry grinding with infrared measurements","year":2007,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Work (physics); Mechanics; Thermal; Materials science; Process (computing); Contact area; Mechanical engineering; Engineering; Computer science; Composite material; Physics; Thermodynamics","score_opus":0.012528157489327072,"score_gpt":0.28296016098016297,"score_spread":0.2704320034908359,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986984388","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8816948,0.00033636054,0.10675638,0.00012224412,0.000041056683,0.000044814915,0.00034598523,0.0010733268,0.009585023],"genre_scores_gemma":[0.9885106,0.000047512363,0.010691523,0.000008936296,0.0000022204079,0.000014306864,0.000058118898,0.000054443593,0.00061232696],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997304,0.000030242678,0.0000111357,0.00004948948,0.00014480908,0.000033984925],"domain_scores_gemma":[0.9988657,0.000718829,0.00009305888,0.00013809053,0.00016126384,0.000023083167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004737132,0.00030589176,0.00046526807,0.00028338685,0.00032592207,0.0005491747,0.0007125445,0.000618144,0.0017255314],"category_scores_gemma":[0.0017814162,0.00030807185,0.0003351999,0.0003794627,0.00083115476,0.00084531354,0.00033328164,0.0006444597,0.0003648698],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009116344,0.00023492759,0.0097389035,0.00057222444,0.000025597377,0.0002876091,0.0007011255,0.634981,0.3003074,0.0077850325,0.00097256916,0.043481946],"study_design_scores_gemma":[0.00006838045,0.0001816399,0.0056211036,0.000019393334,0.0000124213475,0.000066433226,0.000098440425,0.8953408,0.096829124,0.0010364018,0.0006900038,0.00003593667],"about_ca_topic_score_codex":0.0032237326,"about_ca_topic_score_gemma":0.004970198,"teacher_disagreement_score":0.0032237326,"about_ca_system_score_codex":0.000860922,"about_ca_system_score_gemma":0.00065268157,"threshold_uncertainty_score":0.006409943},"labels":[],"label_agreement":null},{"id":"W1987188432","doi":"10.4028/www.scientific.net/kem.291-292.33","title":"Effect of Ultrasonic Elliptic Vibration on Friction between Shoe and Workpiece in Ultrasonic Elliptic-Vibration Shoe Centerless Grinding","year":2005,"lang":"en","type":"article","venue":"Key engineering materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Microsemi (Canada)","funders":"","keywords":"Vibration; Grinding; Ultrasonic sensor; Rotational speed; Materials science; Ultrasonic motor; Work (physics); Mechanical engineering; Acoustics; Engineering; Composite material; Physics","score_opus":0.0045266282572920665,"score_gpt":0.21127185734315482,"score_spread":0.20674522908586276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987188432","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9947425,0.00016051072,0.004786341,0.0000136456365,0.000009699626,0.000017756238,0.000016341332,0.000018645364,0.00023441063],"genre_scores_gemma":[0.9966487,0.000086337175,0.0028833302,0.00001474291,0.0000033001613,0.000009447753,0.000018415003,0.000010844336,0.00032478943],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99901736,0.00013496928,0.000057309233,0.0001844945,0.0004606128,0.00014522507],"domain_scores_gemma":[0.9980477,0.0011449903,0.00022432052,0.00022913152,0.000271425,0.00008251528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073848484,0.00043866842,0.0008583079,0.00039951078,0.000472886,0.00032721754,0.00061606546,0.00065944425,0.001581643],"category_scores_gemma":[0.003631524,0.000511855,0.00032031906,0.00028247782,0.0010754168,0.00058595865,0.00057236105,0.00035326125,0.00016035764],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029567822,0.00015469517,0.0030649237,0.00036515633,0.000027859778,0.00025325298,0.00062490196,0.0021332966,0.97197276,0.00014096404,0.000049057322,0.018256476],"study_design_scores_gemma":[0.00016850028,0.0032366111,0.034763716,0.000037542,0.00007109511,0.0003432315,0.0005276251,0.013573848,0.945919,0.00015084201,0.0011434386,0.00006470883],"about_ca_topic_score_codex":0.0011156093,"about_ca_topic_score_gemma":0.0016799106,"teacher_disagreement_score":0.001581643,"about_ca_system_score_codex":0.00027948845,"about_ca_system_score_gemma":0.00020449307,"threshold_uncertainty_score":0.0052911043},"labels":[],"label_agreement":null},{"id":"W1987218643","doi":"10.1016/j.ijmachtools.2005.09.019","title":"Machining stability in high speed drilling—Part 2: Time domain simulation of a bending–torsional model and experimental validations","year":2005,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Drilling; Torsion (gastropod); Engineering; Time domain; Mechanical engineering; Machining; Drill; Deep hole drilling; Structural engineering; Bending; Computer science","score_opus":0.012427633723288475,"score_gpt":0.2671008044306514,"score_spread":0.2546731707073629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987218643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96263206,0.00013876447,0.03218869,0.0001041894,0.000021126381,0.000059702063,0.0001764624,0.00022192567,0.004457031],"genre_scores_gemma":[0.99552286,0.000027648224,0.0039029387,0.0000054098814,0.0000022696363,0.000025446094,0.000058455094,0.000016836319,0.00043817182],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986386,0.000039179504,0.0000071041018,0.000016958247,0.000052586805,0.000020294872],"domain_scores_gemma":[0.9992029,0.00046499848,0.00009011243,0.000086252396,0.00012791532,0.000027804603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038364492,0.0003559245,0.00047887937,0.00027392217,0.00041031154,0.00043826192,0.00061524723,0.0010104943,0.001787672],"category_scores_gemma":[0.0012975835,0.0003074973,0.00044893014,0.00025070444,0.0006432759,0.00043540684,0.00029784854,0.0004923288,0.00019221871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014711775,0.00008994037,0.0011081117,0.000056945064,0.0000074097634,0.00006503486,0.00007342085,0.98269707,0.011844458,0.00071378675,0.00015460167,0.0030420127],"study_design_scores_gemma":[0.00002287204,0.000058294063,0.0005566977,0.0000029295566,0.0000023259036,0.000010145758,0.000012339623,0.99587846,0.003255038,0.00009691325,0.00009972287,0.000004251044],"about_ca_topic_score_codex":0.0051386217,"about_ca_topic_score_gemma":0.0029249708,"teacher_disagreement_score":0.0051386217,"about_ca_system_score_codex":0.00033632922,"about_ca_system_score_gemma":0.00052731205,"threshold_uncertainty_score":0.010217428},"labels":[],"label_agreement":null},{"id":"W1988008016","doi":"10.1007/s002260000069","title":"Nondestructive evaluation of veneer quality using acoustic wave measurements","year":2001,"lang":"en","type":"article","venue":"Wood Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Nondestructive testing; Laminated veneer lumber; Attenuation; Stress wave; Perpendicular; Acoustics; Materials science; Ultrasonic sensor; Veneer; Sensitivity (control systems); Composite material; Optics; Engineering; Mathematics; Physics; Electronic engineering; Geometry","score_opus":0.09345045635519532,"score_gpt":0.3425551920197441,"score_spread":0.24910473566454877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988008016","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8535094,0.00054462923,0.14265658,0.00004933598,0.00004423145,0.00005578468,0.00021672627,0.0004924115,0.0024307806],"genre_scores_gemma":[0.9596498,0.00024033662,0.037818972,0.000028629946,0.000016484346,0.000022535383,0.00013265929,0.000048147933,0.0020424295],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994686,0.000051906853,0.000017967806,0.00008958348,0.00034412657,0.00002779068],"domain_scores_gemma":[0.9984126,0.00070605136,0.00017859292,0.00021143406,0.00044456802,0.00004665384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005615213,0.0003154336,0.00027064813,0.0006511419,0.00026183334,0.00046345053,0.00038879632,0.00045196738,0.0016179289],"category_scores_gemma":[0.0016676014,0.00027879333,0.00017419718,0.00048272917,0.00035224902,0.00068713346,0.00027924794,0.00036616033,0.00027166982],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031505944,0.000071761446,0.009393075,0.00006828248,0.00001957539,0.000045030243,0.000113710674,0.0017557972,0.9415861,0.0002561747,0.0001441262,0.04623139],"study_design_scores_gemma":[0.000043069504,0.00061761885,0.11104464,0.000013654323,0.000099062825,0.0004353505,0.00015315258,0.043674696,0.8415328,0.00049113017,0.0018320063,0.00006291096],"about_ca_topic_score_codex":0.000994357,"about_ca_topic_score_gemma":0.003259613,"teacher_disagreement_score":0.0016179289,"about_ca_system_score_codex":0.0002087079,"about_ca_system_score_gemma":0.00014421131,"threshold_uncertainty_score":0.005412519},"labels":[],"label_agreement":null},{"id":"W1988105258","doi":"10.1115/1.2345391","title":"Mechanics and Dynamics of the Circular Milling Process","year":2006,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Vibration; Engineering; Airframe; Machining; Mechanical engineering; Cylinder; Process (computing); Finite element method; Mechanism (biology); Intersection (aeronautics); Trajectory; Structural engineering; Computer science; Physics; Acoustics; Aerospace engineering","score_opus":0.002958294362156126,"score_gpt":0.18272869285149324,"score_spread":0.1797703984893371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988105258","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30364367,0.00088039984,0.6583451,0.00053107896,0.00009484544,0.000090193265,0.00018077253,0.00030538696,0.035928585],"genre_scores_gemma":[0.97483826,0.0004544389,0.014500755,0.00004249214,0.0000228324,0.00007144395,0.000059627488,0.000028522787,0.009981775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998814,0.000012980178,0.0000036154822,0.000029958926,0.000060729028,0.000011370595],"domain_scores_gemma":[0.99987376,0.000046981353,0.00003090659,0.000012550311,0.000025939853,0.000009806422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013740822,0.00022570259,0.00023625583,0.00022721358,0.00028039055,0.0006032018,0.00036933762,0.00048247614,0.0014977411],"category_scores_gemma":[0.0003650236,0.00020199265,0.0001750143,0.00014582406,0.00067240535,0.00045846385,0.00040153615,0.0003517086,0.00026479544],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011611033,0.000065928725,0.0025438885,0.00009011199,0.000017251874,0.00053441554,0.0003617628,0.8414476,0.060367998,0.06696471,0.0011225564,0.026367694],"study_design_scores_gemma":[0.000009122516,0.000049005397,0.0014832342,0.0000054459424,0.0000039039423,0.0001292738,0.000035043693,0.98860615,0.0018684836,0.0058534183,0.0019407879,0.000016105323],"about_ca_topic_score_codex":0.0023025211,"about_ca_topic_score_gemma":0.000922388,"teacher_disagreement_score":0.0023025211,"about_ca_system_score_codex":0.00028531958,"about_ca_system_score_gemma":0.0003692672,"threshold_uncertainty_score":0.0050104856},"labels":[],"label_agreement":null},{"id":"W1988218985","doi":"10.1145/1029496.1029501","title":"Remote repair, diagnostics, and maintenance","year":2004,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"German; Computer science; History; Archaeology","score_opus":0.015277379997443915,"score_gpt":0.2507542770513287,"score_spread":0.23547689705388478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988218985","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018921519,0.91319966,0.0158332,0.0020882036,0.0006104732,0.000069623515,0.00032907867,0.00033599744,0.0486122],"genre_scores_gemma":[0.24713966,0.68922126,0.024280857,0.0018496063,0.002331027,0.00013939774,0.0013508336,0.000093978604,0.033593256],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99894625,0.00022244193,0.00008450685,0.00018275183,0.00044668026,0.000117351105],"domain_scores_gemma":[0.99920386,0.00030986595,0.00014898657,0.000058197387,0.00020587361,0.00007330813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007698917,0.0005791456,0.0004176379,0.004636293,0.00051068515,0.0022083772,0.0007660975,0.0010995875,0.0047902022],"category_scores_gemma":[0.0010747429,0.00028360283,0.00032672565,0.005355411,0.001015939,0.00177774,0.00088878337,0.0005203509,0.0013278959],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001882358,0.00015782037,0.008015463,0.0021297585,0.00004759406,0.0002546782,0.0005941445,0.0016477976,0.0023066897,0.014732069,0.02685204,0.94307375],"study_design_scores_gemma":[0.000028603254,0.0006858839,0.07806233,0.0011640539,0.00013914818,0.003176655,0.0022001578,0.0028443688,0.0026768092,0.018198987,0.8907506,0.00007232101],"about_ca_topic_score_codex":0.0052386154,"about_ca_topic_score_gemma":0.013345049,"teacher_disagreement_score":0.0052386154,"about_ca_system_score_codex":0.00087620504,"about_ca_system_score_gemma":0.0014001456,"threshold_uncertainty_score":0.016024888},"labels":[],"label_agreement":null},{"id":"W1988243374","doi":"10.1115/imece2012-86412","title":"Burr Size Minimization When Drilling 6061-T6 Aluminum Alloy","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Lubrication; Drilling; Taguchi methods; Orthogonal array; Mist; Factorial experiment; Machining; Design of experiments; Materials science; Cutting fluid; Mechanical engineering; Response surface methodology; Metallurgy; Composite material; Mathematics; Engineering; Statistics","score_opus":0.008664072254941462,"score_gpt":0.21638296323007153,"score_spread":0.20771889097513008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988243374","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.930304,0.00061784324,0.06847861,0.000025907819,0.000010910506,0.00003662456,0.000030039984,0.00007297986,0.00042307188],"genre_scores_gemma":[0.94264984,0.00027242443,0.05656613,0.0000112739235,0.0000053374592,0.000023378921,0.000034170083,0.0000136724975,0.0004238642],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99923503,0.00015269255,0.00007751532,0.00010494205,0.00037980915,0.000049942657],"domain_scores_gemma":[0.9988193,0.00044611478,0.0004914279,0.00007669715,0.00014478642,0.000021738944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008347971,0.00035749577,0.00047376673,0.00031345861,0.00011569847,0.00034658337,0.0003147388,0.0003724159,0.00018298373],"category_scores_gemma":[0.0016564991,0.00020402312,0.00028253303,0.0002577151,0.00025260713,0.00035247675,0.0002532341,0.00017144937,0.00006345099],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022146443,0.00002990996,0.0013988016,0.00018166803,0.000009855378,0.00007111495,0.00007552934,0.0073169987,0.970709,0.000114908915,0.000030155616,0.019840676],"study_design_scores_gemma":[0.00002898268,0.002228761,0.013081429,0.000012182462,0.00003860779,0.00036870057,0.000081822145,0.04145678,0.9416416,0.00017683549,0.00085675594,0.000027574883],"about_ca_topic_score_codex":0.0003130602,"about_ca_topic_score_gemma":0.00090943807,"teacher_disagreement_score":0.0008347971,"about_ca_system_score_codex":0.00014573424,"about_ca_system_score_gemma":0.00023277271,"threshold_uncertainty_score":0.0044148564},"labels":[],"label_agreement":null},{"id":"W1989320863","doi":"10.1016/j.cirp.2010.03.093","title":"Laser-assisted high-speed finish turning of superalloy Inconel 718 under dry conditions","year":2010,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":172,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Inconel; Machinability; Superalloy; Materials science; Machining; Microstructure; Metallurgy; Ceramic; Surface roughness; Surface integrity; Laser; Surface finish; Alloy; Composite material; Optics","score_opus":0.017203080596755793,"score_gpt":0.26890311969673736,"score_spread":0.25170003909998157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989320863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996732,0.00021938318,0.0011982371,0.000015002316,0.000019088928,0.0000083774285,0.00011211292,0.000055568133,0.0016402117],"genre_scores_gemma":[0.9954833,0.00009776383,0.0024096102,0.000004513041,0.0000046052796,0.0000071359877,0.0001557886,0.000024315297,0.0018128948],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998584,0.000007767763,0.0000048469897,0.00002427381,0.000061032973,0.000043679236],"domain_scores_gemma":[0.9998958,0.00002690387,0.000024640676,0.000018243694,0.000023895002,0.000010523346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001771526,0.00022331011,0.0004137016,0.00026824514,0.00034461985,0.0003201908,0.00025825473,0.00029472355,0.0016351568],"category_scores_gemma":[0.00019671443,0.00016974288,0.00017660094,0.0002753723,0.00022550728,0.00026169783,0.00016445604,0.00026327046,0.00023449575],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024384755,0.000016637056,0.00022069427,0.00007492865,0.000005181602,0.000073123505,0.00007657747,0.00067025254,0.9955426,0.00012425413,0.0001582471,0.00279365],"study_design_scores_gemma":[0.00004934371,0.00049156055,0.0059755743,0.0000058957676,0.000014032732,0.00010766788,0.00010962394,0.004192418,0.9868721,0.000068349815,0.0020947831,0.000018837169],"about_ca_topic_score_codex":0.0018525223,"about_ca_topic_score_gemma":0.00414348,"teacher_disagreement_score":0.0018525223,"about_ca_system_score_codex":0.00019769538,"about_ca_system_score_gemma":0.00036933183,"threshold_uncertainty_score":0.0054701567},"labels":[],"label_agreement":null},{"id":"W1990696399","doi":"10.1016/j.ijmachtools.2007.04.007","title":"The influence of cutter orientation and workpiece angle on machinability when high-speed milling Inconel 718 under finishing conditions","year":2007,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":119,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Government of the United Kingdom","keywords":"Machinability; Inconel; Materials science; Machining; Residual stress; Surface finish; Orientation (vector space); Ultimate tensile strength; Ball (mathematics); Microstructure; Surface roughness; Composite material; Metallurgy; Geometry; Alloy","score_opus":0.006357946603668801,"score_gpt":0.2539430518732462,"score_spread":0.24758510526957736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990696399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984326,0.00018880413,0.00077878626,0.000010214425,0.000008496838,0.0000032777352,0.000024836147,0.00001893997,0.0005340224],"genre_scores_gemma":[0.99938655,0.00005742869,0.00023550277,0.0000034095713,0.0000030121057,0.000001521042,0.00003333902,0.000014545027,0.00026457084],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99965036,0.000048206643,0.000024339268,0.000061907704,0.00012434204,0.000090875634],"domain_scores_gemma":[0.9972753,0.0017261475,0.00037806187,0.00011974105,0.00038728083,0.000113449336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004129487,0.00029996992,0.0003606456,0.00028391858,0.00039448874,0.000625858,0.0002484721,0.00044709162,0.0016166314],"category_scores_gemma":[0.0019987775,0.0003279099,0.00021770048,0.00034173016,0.00033386456,0.0004209107,0.00019158579,0.00028675565,0.00023974356],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027897565,0.000090704976,0.009337068,0.00012851415,0.000021767326,0.0003429228,0.00022900337,0.003231001,0.9752092,0.00007339414,0.00010702886,0.008439634],"study_design_scores_gemma":[0.000079972255,0.0019164084,0.13718908,0.000019883746,0.00012463935,0.0003268681,0.00044909978,0.007969859,0.8511575,0.00008547087,0.00063566037,0.000045591503],"about_ca_topic_score_codex":0.0010349838,"about_ca_topic_score_gemma":0.002020645,"teacher_disagreement_score":0.0016166314,"about_ca_system_score_codex":0.00021291558,"about_ca_system_score_gemma":0.000243183,"threshold_uncertainty_score":0.005408168},"labels":[],"label_agreement":null},{"id":"W1990910739","doi":"10.1016/j.ijmachtools.2005.07.019","title":"Chip formation during microscale cutting of a medium carbon steel","year":2005,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":141,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Microscale chemistry; Materials science; Chip formation; Chip; Shearing (physics); Composite material; Extrusion; Finite element method; Scanning electron microscope; Carbon steel; Lüders band; Thread (computing); Metallurgy; Mechanical engineering; Machining; Structural engineering; Tool wear; Microstructure; Engineering","score_opus":0.004838784836428894,"score_gpt":0.22197477789251582,"score_spread":0.21713599305608694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990910739","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965216,0.00019788071,0.0016166139,0.000032291464,0.00003403283,0.000010100924,0.000041048213,0.000055875,0.0014906686],"genre_scores_gemma":[0.998309,0.000039229344,0.0007577164,0.000010495499,0.00000539429,0.0000038804733,0.000036564343,0.000011099504,0.00082661817],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987006,0.00000601713,0.000003018712,0.000029576624,0.000047858208,0.00004347565],"domain_scores_gemma":[0.99974066,0.00007136747,0.00005603342,0.000032039614,0.0000564252,0.00004348217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001096988,0.00016262238,0.00032174194,0.00018391885,0.00040765025,0.00038180605,0.00024490088,0.0003681977,0.0013260419],"category_scores_gemma":[0.00026016735,0.00023960049,0.00018587877,0.00015245241,0.00036003682,0.00026659272,0.0002478255,0.00033266455,0.00016522007],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025326156,0.000037660593,0.0006906346,0.00007124472,0.000014280669,0.00029445637,0.00012797186,0.0021700303,0.9926885,0.00036919196,0.00031170514,0.002971044],"study_design_scores_gemma":[0.000034165507,0.00034384988,0.011633862,0.000004715714,0.000015002783,0.0001664331,0.00013113701,0.011855747,0.97447747,0.00011810352,0.001202908,0.000016615882],"about_ca_topic_score_codex":0.0011528218,"about_ca_topic_score_gemma":0.002392491,"teacher_disagreement_score":0.0013260419,"about_ca_system_score_codex":0.00041879987,"about_ca_system_score_gemma":0.00045989102,"threshold_uncertainty_score":0.0044360757},"labels":[],"label_agreement":null},{"id":"W1991345719","doi":"10.1117/12.506587","title":"Performance evaluation of a MEMS-based deformable mirror for adaptive optics","year":2003,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Adaptive optics; Deformable mirror; Actuator; Microelectromechanical systems; Zernike polynomials; Active optics; Optics; Computer science; Residual; Telescope; Physics; Wavefront; Artificial intelligence; Optoelectronics; Algorithm","score_opus":0.019630640118797633,"score_gpt":0.2493468269642558,"score_spread":0.22971618684545816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991345719","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98834586,0.0003807392,0.008698205,0.000072005714,0.000038419606,0.000035418074,0.00008318768,0.00017815214,0.0021681827],"genre_scores_gemma":[0.993447,0.000118257354,0.0052729147,0.000016506803,0.0000067482,0.000011323786,0.00005397564,0.000015218562,0.0010579907],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99966276,0.000034694207,0.000017128112,0.000049830705,0.00019858607,0.00003707832],"domain_scores_gemma":[0.99910957,0.00024213511,0.00013131792,0.00013228235,0.000312622,0.000071956216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003452998,0.0003307803,0.00034363155,0.0002403379,0.00019847808,0.00029475498,0.00057051086,0.0005790645,0.001125155],"category_scores_gemma":[0.0012468393,0.000103806095,0.0002272968,0.00016619402,0.00015649991,0.0003363725,0.0002142184,0.00019611794,0.00034386473],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075719546,0.00009040875,0.0029597278,0.00013089461,0.000032542248,0.00014968947,0.00007915443,0.00946423,0.95668256,0.00033593376,0.00025173466,0.029065924],"study_design_scores_gemma":[0.000054209075,0.003727141,0.012662343,0.0000113887245,0.00004269308,0.00034971267,0.000057579593,0.13014048,0.8505787,0.0000898055,0.0022526465,0.000033306533],"about_ca_topic_score_codex":0.0010922581,"about_ca_topic_score_gemma":0.0008633873,"teacher_disagreement_score":0.001125155,"about_ca_system_score_codex":0.0004230834,"about_ca_system_score_gemma":0.00020042027,"threshold_uncertainty_score":0.0037640333},"labels":[],"label_agreement":null},{"id":"W1992876273","doi":"10.1115/imece2014-39547","title":"Vibration Analysis of Machine Tool Spindle Systems: A Calibrated Finite Element Model","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; FedDev Ontario","keywords":"Finite element method; Vibration; Machine tool; Natural frequency; Inertia; Spring (device); Rotary inertia; Beam (structure); Structural engineering; Bearing (navigation); Software; Stability (learning theory); Engineering; Control theory (sociology); Computer science; Mechanical engineering; Acoustics; Physics","score_opus":0.0071913297380223245,"score_gpt":0.21435818353276845,"score_spread":0.20716685379474611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992876273","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08961369,0.00023506736,0.90141356,0.00006628438,0.000024626494,0.00008175028,0.00030351113,0.000506069,0.007755451],"genre_scores_gemma":[0.9252719,0.00030900154,0.069304444,0.000029582654,0.000012058597,0.0002062733,0.0004014981,0.00008839671,0.00437685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998493,0.000029327717,0.00000853933,0.00003074283,0.00007048099,0.000011553736],"domain_scores_gemma":[0.9998503,0.00006140331,0.000019270492,0.000024470666,0.00004020949,0.0000043139858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020023271,0.00032691134,0.0003834734,0.0003122152,0.0001123641,0.00032013038,0.0007406249,0.00080424105,0.0025446075],"category_scores_gemma":[0.00056223327,0.00024071148,0.00040547075,0.00022816402,0.00026033705,0.00034106278,0.00020326547,0.00039396898,0.00050361827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023631877,0.000023656748,0.00046024832,0.00006305891,0.000012089612,0.000045015793,0.000062539315,0.9674086,0.017233262,0.0018596476,0.00022679259,0.01258144],"study_design_scores_gemma":[0.0000029302175,0.00002230252,0.00045307574,0.0000041527965,0.0000029332484,0.00001328184,0.000006981632,0.9970868,0.0013271262,0.00022848105,0.0008483428,0.0000035929793],"about_ca_topic_score_codex":0.001851819,"about_ca_topic_score_gemma":0.001029615,"teacher_disagreement_score":0.0025446075,"about_ca_system_score_codex":0.0002136992,"about_ca_system_score_gemma":0.0003010638,"threshold_uncertainty_score":0.008512557},"labels":[],"label_agreement":null},{"id":"W1992991167","doi":"10.1016/j.jmatprotec.2004.07.097","title":"Optimization of CNC ball end milling: a neural network-based model","year":2004,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"End milling; Artificial neural network; Ball (mathematics); Machining; Ball mill; Cnc milling; End mill; Mechanical engineering; Engineering; Numerical control; Materials science; Computer science; Artificial intelligence; Geometry; Metallurgy; Mathematics","score_opus":0.009529409537227059,"score_gpt":0.22900351020057716,"score_spread":0.2194741006633501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992991167","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27735776,0.0012074689,0.68581146,0.0009854981,0.00022103345,0.0002157539,0.00042649178,0.0007734174,0.03300103],"genre_scores_gemma":[0.9673351,0.00021922064,0.024331963,0.00008302161,0.000028634642,0.00012858442,0.00015278315,0.00006441345,0.007656271],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999808,0.000050988398,0.000008784612,0.00005178917,0.000048277514,0.00003217522],"domain_scores_gemma":[0.9992811,0.00044264318,0.0000718,0.000025853642,0.0001451706,0.00003340781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063538196,0.00082375883,0.0011892889,0.0004824621,0.0005476084,0.0011084029,0.0011499806,0.0024269603,0.0033197415],"category_scores_gemma":[0.0015351914,0.00073292304,0.0005374083,0.0005849796,0.00073932874,0.0009571877,0.0004887883,0.0009355819,0.00035524266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012997802,0.0000072751586,0.000055500488,0.0000064303786,0.0000029005862,0.000005858797,0.0000017439313,0.9984756,0.000091859554,0.00016985934,0.00005583122,0.0011141587],"study_design_scores_gemma":[0.0000019251077,0.0000026137056,0.000021714006,5.0298377e-7,7.306083e-7,5.078045e-7,4.679966e-7,0.99986327,0.00003504652,0.000054628217,0.000017852752,6.450671e-7],"about_ca_topic_score_codex":0.032597728,"about_ca_topic_score_gemma":0.022959618,"teacher_disagreement_score":0.032597728,"about_ca_system_score_codex":0.0013158107,"about_ca_system_score_gemma":0.0016059467,"threshold_uncertainty_score":0.06481594},"labels":[],"label_agreement":null},{"id":"W1993073331","doi":"10.1115/imece2004-62015","title":"Cutter Engagement Feature Extraction From Solid Models for End Milling","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robustness (evolution); Machining; Mechanical engineering; Computer science; Solid modeling; Process (computing); Rotation (mathematics); Engineering drawing; Geometry; Algorithm; Engineering; Mathematics; Artificial intelligence","score_opus":0.018812949169814762,"score_gpt":0.26878247703854574,"score_spread":0.24996952786873097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993073331","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01999988,0.00012904387,0.976434,0.000040125535,0.000010313043,0.00007015224,0.00028094766,0.0017809455,0.0012545331],"genre_scores_gemma":[0.34482914,0.0004076912,0.6488638,0.000025992505,0.000015109534,0.00019814463,0.0024129625,0.00054617424,0.0027010525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995802,0.000036381705,0.000024034574,0.000048364473,0.00027960647,0.00003140756],"domain_scores_gemma":[0.9993678,0.0002920782,0.00008737912,0.000099165845,0.00012902643,0.000024620758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035412563,0.0010036889,0.00085777976,0.0012858093,0.00034724432,0.0015266248,0.0010347832,0.0010827339,0.0024054388],"category_scores_gemma":[0.001414791,0.0007349993,0.0012707477,0.0009193715,0.00033707795,0.0008699039,0.0009130991,0.0010788105,0.0013881642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016573655,0.00012488088,0.0026561785,0.0002750957,0.000042906937,0.0004459235,0.00019742205,0.5506587,0.07647511,0.009664209,0.003191825,0.35610205],"study_design_scores_gemma":[0.0000049084492,0.000031426647,0.0004480539,0.000014668198,0.000005029299,0.00010066322,0.000022540635,0.9846971,0.009862015,0.0018175619,0.002982998,0.000012986494],"about_ca_topic_score_codex":0.0018974908,"about_ca_topic_score_gemma":0.0037497573,"teacher_disagreement_score":0.0024054388,"about_ca_system_score_codex":0.00043345586,"about_ca_system_score_gemma":0.00069723,"threshold_uncertainty_score":0.008046985},"labels":[],"label_agreement":null},{"id":"W1993482151","doi":"10.1142/s021968670500062x","title":"PERFORMANCE OF A COHERENT JET COOLANT SYSTEM IN NON-CONTINUOUS DRESS CREEP-FEED GRINDING OF INCONEL 718","year":2005,"lang":"en","type":"article","venue":"Journal of Advanced Manufacturing Systems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Pratt and Whitney Canada","keywords":"Grinding; Nozzle; Inconel; Materials science; Coolant; Jet (fluid); Creep; Volumetric flow rate; Mechanics; Flow (mathematics); Metallurgy; Alloy; Mechanical engineering; Engineering; Physics","score_opus":0.004740212736821582,"score_gpt":0.205482737089696,"score_spread":0.20074252435287443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993482151","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989812,0.000096066564,0.00076217705,0.0000042545553,0.000003623074,0.0000047986077,0.000009808157,0.000024327801,0.00011384364],"genre_scores_gemma":[0.9981988,0.000048138576,0.0012331164,0.000006053569,0.000002561676,0.0000048007746,0.000038946313,0.000013637715,0.00045398957],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996606,0.000035966055,0.000017135771,0.000065695276,0.0001589317,0.00006159939],"domain_scores_gemma":[0.9995018,0.00014799497,0.00010427245,0.00004843693,0.00014494188,0.000052584313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039268457,0.00026374578,0.00045522457,0.00022475857,0.0002780649,0.0003440967,0.00039379098,0.0002430006,0.0011503652],"category_scores_gemma":[0.00085634686,0.00020518427,0.00016487071,0.0001930099,0.00025268085,0.00028688525,0.00022277377,0.0002456691,0.00018112772],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009899781,0.000063552325,0.0015717379,0.00010721649,0.000013301412,0.00008398521,0.000110860594,0.0009949902,0.9890548,0.000027628981,0.000048253307,0.0069337417],"study_design_scores_gemma":[0.00006395488,0.0025573687,0.019929701,0.0000074168565,0.000031946674,0.0001160912,0.000058140475,0.006655688,0.9701108,0.000009013388,0.0004411343,0.000018784189],"about_ca_topic_score_codex":0.0017965698,"about_ca_topic_score_gemma":0.0030791042,"teacher_disagreement_score":0.0017965698,"about_ca_system_score_codex":0.00025582465,"about_ca_system_score_gemma":0.00029828787,"threshold_uncertainty_score":0.003848374},"labels":[],"label_agreement":null},{"id":"W1994334861","doi":"10.1016/j.jmatprotec.2009.01.013","title":"Tool wear monitoring of micro-milling operations","year":2009,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":224,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tool wear; Enhanced Data Rates for GSM Evolution; Acoustic emission; Accelerometer; Mechanical engineering; Vibration; Machine tool; Engineering; Materials science; Engineering drawing; Machining; Computer science; Acoustics; Composite material","score_opus":0.007449716125362531,"score_gpt":0.24888748860049295,"score_spread":0.24143777247513043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994334861","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941717,0.00025025284,0.0046765585,0.000015603171,0.000018512126,0.000016025004,0.00017433384,0.00017444992,0.00050263025],"genre_scores_gemma":[0.99810237,0.000046771765,0.0012728873,0.00000754255,0.0000048558863,0.0000055539795,0.00008140386,0.000010285942,0.00046831038],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99968946,0.000019941455,0.000019437388,0.00004554061,0.00018368398,0.000042062788],"domain_scores_gemma":[0.99872595,0.00051672256,0.00021029687,0.0001423081,0.0003354652,0.000069265734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017639309,0.00030384757,0.00039494797,0.0007755359,0.0002475466,0.00028396837,0.00051917223,0.00055246527,0.0014785075],"category_scores_gemma":[0.00086562877,0.00018963513,0.00020696857,0.00046932083,0.00016623332,0.00036952834,0.0002068157,0.00031335346,0.00021066862],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002372069,0.00021360748,0.025558937,0.00025251362,0.00004842993,0.00031998588,0.00032124406,0.00219443,0.8843031,0.000091716836,0.00059535215,0.08372868],"study_design_scores_gemma":[0.00004459409,0.0021348519,0.26730168,0.00002564775,0.000060292252,0.0013511897,0.00024468306,0.037316877,0.68961275,0.00014566805,0.0017081372,0.000053678206],"about_ca_topic_score_codex":0.00049585867,"about_ca_topic_score_gemma":0.00085705915,"teacher_disagreement_score":0.0014785075,"about_ca_system_score_codex":0.00015490747,"about_ca_system_score_gemma":0.000115023715,"threshold_uncertainty_score":0.004946053},"labels":[],"label_agreement":null},{"id":"W1994393480","doi":"10.1007/s00170-014-5838-z","title":"Vibro-impact dynamics of material removal in a robotic grinding process","year":2014,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hydro-Québec; École de Technologie Supérieure","funders":"","keywords":"Waviness; Grinding; Stiffness; Process (computing); Mechanical engineering; Vibration; Power (physics); Engineering; Robot; Structural engineering; Computer science; Acoustics; Artificial intelligence","score_opus":0.003926874029620375,"score_gpt":0.2472313064910347,"score_spread":0.2433044324614143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994393480","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94574,0.00023596293,0.03810432,0.00039878752,0.00006776195,0.000035506055,0.000048241604,0.000112869224,0.015256562],"genre_scores_gemma":[0.99721164,0.000037080714,0.00058836146,0.000009466747,0.0000046814444,0.0000037197008,0.000010852945,0.000009519574,0.0021246604],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998995,0.000012799882,0.0000030468534,0.000017302786,0.000039690458,0.000027625738],"domain_scores_gemma":[0.99983513,0.000080545055,0.000025293386,0.000008600916,0.000020746786,0.000029701712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013831804,0.00025176944,0.00037725002,0.00028433435,0.0005484395,0.0005839184,0.0005457009,0.00071499974,0.003059608],"category_scores_gemma":[0.0005250866,0.00023618693,0.00030844155,0.00017773989,0.0007621501,0.0005778865,0.00055881834,0.0004581443,0.00022059373],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007278548,0.0003615503,0.003051122,0.0001506232,0.000060790328,0.0012697463,0.00036082865,0.8436266,0.12134382,0.012028913,0.000714848,0.01630331],"study_design_scores_gemma":[0.0000147915325,0.000066005654,0.0033288887,0.0000027921978,0.0000041574713,0.00004805564,0.000048529597,0.99318224,0.0023636352,0.00076235,0.00016354297,0.0000150687765],"about_ca_topic_score_codex":0.0044007753,"about_ca_topic_score_gemma":0.0029018896,"teacher_disagreement_score":0.0044007753,"about_ca_system_score_codex":0.0003909386,"about_ca_system_score_gemma":0.0004324321,"threshold_uncertainty_score":0.010235369},"labels":[],"label_agreement":null},{"id":"W1994575779","doi":"10.1007/s00170-012-4452-1","title":"3D metal removal simulation to determine uncut chip thickness, contact length, and surface finish in grinding","year":2012,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Abrasive; Grinding wheel; Chip formation; Materials science; Chip; Surface roughness; Surface finish; Mechanical engineering; Surface grinding; Machining; Composite material; Tool wear; Metallurgy; Computer science; Engineering","score_opus":0.011346610794566028,"score_gpt":0.260615128862396,"score_spread":0.24926851806782999,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994575779","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86517805,0.00034994955,0.10063214,0.00025251994,0.00012623066,0.00011580893,0.0014918179,0.0022840141,0.029569471],"genre_scores_gemma":[0.9729653,0.00009334721,0.023249127,0.00004946176,0.0000074496124,0.000057243287,0.0003920038,0.00020941181,0.0029766741],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978274,0.000024944413,0.000008681073,0.000029827092,0.00010899045,0.000044886416],"domain_scores_gemma":[0.9990428,0.00056017033,0.00007926953,0.000086808424,0.00019521374,0.000035695175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035299544,0.0006874635,0.0007557833,0.00051061506,0.00057154556,0.00063241407,0.0011908398,0.0015164235,0.00582161],"category_scores_gemma":[0.0011581855,0.0007667811,0.000802462,0.00053456164,0.0004219643,0.00046523678,0.00037817346,0.00053861237,0.0005526488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054658747,0.000052028667,0.00095803523,0.000056136298,0.000017531805,0.00006656827,0.00004704537,0.9902748,0.004777933,0.00049854175,0.0003413202,0.0028553735],"study_design_scores_gemma":[0.000008097411,0.000016754528,0.00028065607,0.0000022624977,0.0000050460935,0.0000070541646,0.000007325573,0.99807113,0.0013574022,0.000053431093,0.00018652716,0.000004455668],"about_ca_topic_score_codex":0.023211122,"about_ca_topic_score_gemma":0.028597703,"teacher_disagreement_score":0.023211122,"about_ca_system_score_codex":0.00104037,"about_ca_system_score_gemma":0.0012575345,"threshold_uncertainty_score":0.046152055},"labels":[],"label_agreement":null},{"id":"W1995648607","doi":"10.1115/imece2010-37029","title":"Nonlinear Dynamic Analysis of an Electrically Actuated Piezoelectric Laminated Microbeam With the Effect of AC","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Microbeam; Galerkin method; Direct current; Piezoelectricity; Nonlinear system; Alternating current; Voltage; Current (fluid); Acoustics; Mechanics; Physics; Electrical engineering; Engineering; Optics","score_opus":0.0009932146800686128,"score_gpt":0.20248459508211086,"score_spread":0.20149138040204226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995648607","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83724207,0.00094040274,0.14296219,0.00037139968,0.000081811006,0.0000613793,0.00007124973,0.000114750175,0.018154653],"genre_scores_gemma":[0.9860924,0.00029790954,0.006047674,0.000028949089,0.000014858178,0.000029564377,0.000025729001,0.000008467323,0.007454557],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99995136,0.0000056418608,0.0000012323337,0.000008989764,0.000025532929,0.000007289039],"domain_scores_gemma":[0.99995494,0.000015148502,0.000011120349,0.0000038995618,0.000010553063,0.0000043672353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007789413,0.00022364805,0.00017291895,0.00012950481,0.00017358137,0.00020690128,0.00018399481,0.00029969035,0.00093004666],"category_scores_gemma":[0.00016943175,0.0000996458,0.00019488632,0.000081100006,0.00036745955,0.0002404789,0.00019038863,0.00017523806,0.000132693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011693568,0.0000601566,0.0014910152,0.0002453941,0.00004491437,0.00062652584,0.00027437453,0.19107053,0.7792272,0.008430622,0.00031137053,0.018100923],"study_design_scores_gemma":[0.0000062759113,0.00010575886,0.002846866,0.000009055292,0.000009659672,0.00012135319,0.00006349887,0.9533857,0.041267514,0.0005654157,0.0016061377,0.000012781789],"about_ca_topic_score_codex":0.0015188544,"about_ca_topic_score_gemma":0.0013537864,"teacher_disagreement_score":0.0015188544,"about_ca_system_score_codex":0.0002116144,"about_ca_system_score_gemma":0.00018598532,"threshold_uncertainty_score":0.0031113029},"labels":[],"label_agreement":null},{"id":"W1996377999","doi":"10.1115/msec2014-3975","title":"Exploration of a New Approach for Calibrating Grinding Power Model","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Grinding; Calibration; Power (physics); Grinding wheel; Mechanical engineering; Materials science; Surface grinding; Specific energy; Constant (computer programming); Chip; Mechanics; Computer science; Metallurgy; Mathematics; Engineering; Physics; Thermodynamics; Statistics","score_opus":0.03466166558686758,"score_gpt":0.2553169219900034,"score_spread":0.22065525640313582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996377999","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00848978,0.00014875543,0.9893367,0.000040678333,0.000014181588,0.000038734368,0.000044332704,0.0006808965,0.0012059024],"genre_scores_gemma":[0.49554247,0.0005671464,0.50075597,0.00009857934,0.00003204672,0.00024222548,0.00046166076,0.0005905933,0.0017093256],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99761885,0.00039917877,0.00009789688,0.0006733717,0.0011160743,0.00009457395],"domain_scores_gemma":[0.99777585,0.00064971374,0.00021909268,0.00075698685,0.0005673956,0.00003092209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023571353,0.0012710533,0.0009623097,0.0015422631,0.00033760682,0.0014275135,0.0024671636,0.0012793745,0.0015270312],"category_scores_gemma":[0.006851045,0.00069736986,0.0008372639,0.0010836517,0.000587499,0.0021354803,0.0012209993,0.0014528442,0.00090696884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001259465,0.00020666141,0.0055497037,0.00074360793,0.00013865695,0.00026408737,0.00048481513,0.54509085,0.1282552,0.023137625,0.0012479972,0.29475474],"study_design_scores_gemma":[0.00001392845,0.00010441559,0.0013384952,0.000043450164,0.000030191139,0.00013481308,0.00004798051,0.95046014,0.036587834,0.005190595,0.0060067135,0.00004137784],"about_ca_topic_score_codex":0.0026230172,"about_ca_topic_score_gemma":0.0022110129,"teacher_disagreement_score":0.0026230172,"about_ca_system_score_codex":0.0008030104,"about_ca_system_score_gemma":0.0014092374,"threshold_uncertainty_score":0.012465894},"labels":[],"label_agreement":null},{"id":"W1996761699","doi":"10.5539/mer.v2n2p114","title":"Surface Grinding Machine Stability Characteristics Limited Prediction","year":2012,"lang":"en","type":"article","venue":"Mechanical Engineering Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Flutter; Grinding; Reliability (semiconductor); Stability (learning theory); Process (computing); Limit (mathematics); Surface (topology); Work (physics); Machine tool; Mechanical engineering; Surface grinding; Computer science; Control theory (sociology); Engineering; Mathematics; Artificial intelligence; Machine learning; Mathematical analysis; Geometry","score_opus":0.049851033971812786,"score_gpt":0.29957292084076753,"score_spread":0.24972188686895475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996761699","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45542496,0.00029671073,0.5334291,0.0001023897,0.000026878648,0.00006290576,0.00020895187,0.0022204102,0.008227683],"genre_scores_gemma":[0.98568904,0.00005112696,0.012907385,0.0000062567465,0.0000033623814,0.00001996271,0.00012465172,0.0000528229,0.001145252],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977773,0.000027037317,0.0000069761745,0.00005813316,0.00011198525,0.000018087865],"domain_scores_gemma":[0.9991172,0.00034804153,0.00007824111,0.00013387806,0.00030007045,0.000022563372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029845658,0.00033641662,0.00031153343,0.00057788874,0.0001868718,0.0003232235,0.00042800195,0.00038099778,0.0016128708],"category_scores_gemma":[0.0014348016,0.00017336685,0.00038213158,0.00024831697,0.000243353,0.00043597663,0.00018972575,0.00035143693,0.00048472776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033280012,0.00007099401,0.01157138,0.00019453329,0.000027017255,0.00018095427,0.00020948646,0.7165039,0.11172654,0.0027942958,0.0015544902,0.15483361],"study_design_scores_gemma":[0.0000046416976,0.000047266098,0.0030848791,0.0000029862922,0.0000035607973,0.000023746134,0.000006698588,0.9843609,0.011730496,0.00038900506,0.0003377445,0.0000081700155],"about_ca_topic_score_codex":0.0031697012,"about_ca_topic_score_gemma":0.0018242256,"teacher_disagreement_score":0.0031697012,"about_ca_system_score_codex":0.00039779118,"about_ca_system_score_gemma":0.00029821164,"threshold_uncertainty_score":0.0063025355},"labels":[],"label_agreement":null},{"id":"W1996937036","doi":"10.1115/1.2917285","title":"An Acoustic Emission-Based Method for Determining Contact Between a Tool and Workpiece at the Microscale","year":2008,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Institute of Standards and Technology","keywords":"Microscale chemistry; Acoustic emission; Surface (topology); Surface roughness; Overshoot (microwave communication); Surface finish; Acoustics; Materials science; Mechanical engineering; Computer science; Geometry; Engineering; Physics; Mathematics; Composite material","score_opus":0.010598327656750992,"score_gpt":0.257532661330782,"score_spread":0.246934333674031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996937036","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14040858,0.0006989019,0.85584766,0.000080551385,0.000061107174,0.00014427456,0.00020413182,0.0011466041,0.0014082462],"genre_scores_gemma":[0.56900394,0.00041907706,0.4279132,0.00007254055,0.000024242167,0.00019578366,0.000169961,0.00007598082,0.0021252653],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99951434,0.000031248583,0.000015427919,0.00009323873,0.00032946072,0.000016300444],"domain_scores_gemma":[0.9992366,0.00031152208,0.0001102427,0.00008544183,0.00022878463,0.000027502623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033083328,0.00038447473,0.00043725004,0.00040019958,0.0002243229,0.00026643876,0.00075441715,0.0005268445,0.0009221055],"category_scores_gemma":[0.00111829,0.00025027146,0.00018229062,0.00028477548,0.00029673267,0.00046882947,0.00041494932,0.0004949704,0.00034398583],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052800828,0.000050621642,0.0020078153,0.00018564898,0.000016719949,0.00004461669,0.00008136962,0.0036727388,0.9358391,0.00040519008,0.0002609605,0.057382453],"study_design_scores_gemma":[0.00005378871,0.00033106346,0.011805715,0.000028147557,0.00004035629,0.0005789122,0.000060956467,0.19834048,0.7826519,0.00036243538,0.0056419647,0.00010418576],"about_ca_topic_score_codex":0.0010776124,"about_ca_topic_score_gemma":0.002410583,"teacher_disagreement_score":0.0010776124,"about_ca_system_score_codex":0.00029722843,"about_ca_system_score_gemma":0.00037582713,"threshold_uncertainty_score":0.0030847788},"labels":[],"label_agreement":null},{"id":"W1996974949","doi":"10.1007/s00170-015-7086-2","title":"A novel numerical modeling approach to determine the temperature distribution in the cutting tool using conjugate heat transfer (CHT) analysis","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Heat transfer; Computational fluid dynamics; Finite element method; Mechanical engineering; Mechanics; Heat flux; Machining; Heat equation; Heat transfer coefficient; Flow (mathematics); Heat generation; Materials science; Engineering; Thermodynamics; Structural engineering; Mathematics; Physics","score_opus":0.020185145679771276,"score_gpt":0.25891257512215904,"score_spread":0.23872742944238776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996974949","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042154416,0.000038566624,0.99282277,0.000049411086,0.00003397299,0.000044038676,0.000021144702,0.00024103042,0.0025335825],"genre_scores_gemma":[0.40821755,0.00030473084,0.5822453,0.00013052704,0.000082368075,0.00042155804,0.00015760098,0.00032007534,0.008120198],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974626,0.00003614516,0.000011166527,0.000040274725,0.00014713546,0.000018930414],"domain_scores_gemma":[0.999713,0.00009375056,0.00004099821,0.0000517267,0.000084736974,0.000015797734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040078603,0.0006791079,0.00064114865,0.00058812374,0.00051091495,0.00094840664,0.0012254415,0.0009989766,0.00230578],"category_scores_gemma":[0.0009982127,0.0004858491,0.00067196274,0.0005555729,0.0005430694,0.0012656474,0.0007924874,0.0008558782,0.0006534119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003136683,0.00012056596,0.0009129253,0.00010587973,0.00003297156,0.00011631606,0.00007251188,0.8758958,0.047258116,0.03431284,0.0008808173,0.040259875],"study_design_scores_gemma":[0.0000022178594,0.000010713854,0.000052018055,0.0000016188245,0.0000020203895,0.00001760427,0.0000025601644,0.99665314,0.0019266021,0.00074213365,0.0005858001,0.0000035771795],"about_ca_topic_score_codex":0.0017418658,"about_ca_topic_score_gemma":0.001812512,"teacher_disagreement_score":0.00230578,"about_ca_system_score_codex":0.000521467,"about_ca_system_score_gemma":0.0013282663,"threshold_uncertainty_score":0.007713616},"labels":[],"label_agreement":null},{"id":"W1997016081","doi":"10.1007/s00170-014-6520-1","title":"Interaction of cemented carbide micro-drills and printed circuit boards during micro-drilling","year":2014,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MD Precision (Canada)","funders":"","keywords":"Drilling; Abrasive; Cemented carbide; Materials science; Printed circuit board; Enhanced Data Rates for GSM Evolution; Composite material; Tool wear; Metallurgy; Carbide; Flank; Machining; Engineering","score_opus":0.005298659785353677,"score_gpt":0.22688046584976368,"score_spread":0.22158180606441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997016081","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954059,0.0004670677,0.0023870617,0.00004870063,0.000052781874,0.000014752989,0.00003843139,0.000075957054,0.0015093941],"genre_scores_gemma":[0.9986279,0.00007167796,0.0005614384,0.000011478135,0.000004794313,0.0000035439657,0.00001949657,0.00001491007,0.00068479433],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997141,0.000037754846,0.0000095878895,0.000047947407,0.000101579215,0.00008910857],"domain_scores_gemma":[0.9992046,0.00048032484,0.000113497445,0.000035250752,0.00010395008,0.000062405175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022481193,0.000261427,0.00046575617,0.00021324592,0.00033612442,0.00083759456,0.00031199236,0.00048014434,0.0025589883],"category_scores_gemma":[0.0009610031,0.0003011014,0.00017400445,0.00018815644,0.00048771926,0.00066502986,0.00036635651,0.00035858018,0.0003338225],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013823599,0.00005834829,0.0016591821,0.00014905413,0.00001757516,0.00043536414,0.00020596854,0.0030610915,0.98510146,0.00024188754,0.00022025454,0.007467438],"study_design_scores_gemma":[0.00009404128,0.0007627233,0.029367635,0.000020333604,0.000050335322,0.00036352477,0.0007108584,0.033104252,0.93266666,0.00022046265,0.002598474,0.000040704635],"about_ca_topic_score_codex":0.00070805487,"about_ca_topic_score_gemma":0.0014712912,"teacher_disagreement_score":0.0025589883,"about_ca_system_score_codex":0.0002434484,"about_ca_system_score_gemma":0.00029003748,"threshold_uncertainty_score":0.0085606575},"labels":[],"label_agreement":null},{"id":"W1997107348","doi":"10.1177/2041297510393522","title":"Mechanistic modelling for cutting with serrated end mills – a parametric representation approach","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Serration; Waviness; End mill; Chip; Machining; Enhanced Data Rates for GSM Evolution; Vibration; Structural engineering; Chip formation; Parametric model; End milling; Parametric statistics; Ball (mathematics); Engineering; Spline (mechanical); Mechanical engineering; Geometry; Tool wear; Mathematics; Acoustics; Physics","score_opus":0.0228954201809754,"score_gpt":0.20514395793918477,"score_spread":0.18224853775820937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997107348","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034108486,0.00035851233,0.95500565,0.000104663006,0.000025268855,0.000065450105,0.00007887625,0.00011888738,0.010134163],"genre_scores_gemma":[0.8671772,0.0012942068,0.122372,0.000052760923,0.000048851518,0.00034722575,0.00014088726,0.00008734984,0.008479461],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997665,0.000060894865,0.000011204857,0.000038164893,0.000092578506,0.000030555133],"domain_scores_gemma":[0.99965346,0.00013656866,0.00007048494,0.000057577578,0.00006436525,0.000017661932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066589075,0.0006009037,0.0007151077,0.0007256911,0.00036784142,0.001573026,0.0018487445,0.0017694085,0.0025432138],"category_scores_gemma":[0.0010585135,0.00047396656,0.0010631522,0.00052283844,0.0007408787,0.0014527861,0.0006289305,0.0009014073,0.0005229678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009204683,0.00002810448,0.00022715845,0.000047563848,0.000008394349,0.0000927773,0.00005868833,0.97360253,0.0027028294,0.018791938,0.000086713146,0.0043440866],"study_design_scores_gemma":[0.0000021917924,0.000015062985,0.00007168161,0.000005189588,0.0000029817588,0.00003125776,0.000011588535,0.99561465,0.0002731833,0.0032266849,0.0007400045,0.0000055217856],"about_ca_topic_score_codex":0.0014015677,"about_ca_topic_score_gemma":0.0011346163,"teacher_disagreement_score":0.0025432138,"about_ca_system_score_codex":0.0005047322,"about_ca_system_score_gemma":0.0007977533,"threshold_uncertainty_score":0.008507907},"labels":[],"label_agreement":null},{"id":"W1997181967","doi":"10.1007/s12289-014-1170-2","title":"Comparison of two models for predicting tool wear and cutting force components during high speed trimming of CFRP","year":2014,"lang":"en","type":"article","venue":"International Journal of Material Forming","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Trimming; Tool wear; Materials science; Composite material; Cutting tool; Exponential function; Mechanical engineering; Mathematics; Metallurgy; Engineering; Machining","score_opus":0.014579453573354382,"score_gpt":0.2864838099869285,"score_spread":0.27190435641357413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997181967","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.857438,0.0006732537,0.1370438,0.00008262115,0.00007957124,0.00008727664,0.0003720259,0.0012180393,0.0030054427],"genre_scores_gemma":[0.98911065,0.000113043905,0.009694901,0.00001336559,0.0000073593346,0.00004324393,0.00014666587,0.00004550396,0.000825247],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997719,0.000042298692,0.000015856504,0.00005490138,0.00007728997,0.000037657814],"domain_scores_gemma":[0.9985061,0.00094844215,0.000102993276,0.000097234966,0.00030904272,0.00003622396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007945611,0.0009050636,0.0007032329,0.0009656017,0.00040819682,0.0008197028,0.001011674,0.0014418447,0.0011941474],"category_scores_gemma":[0.0016393688,0.00037985487,0.00076738343,0.00053319096,0.0002504309,0.00059258373,0.00029037145,0.00047068732,0.00027986124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075719843,0.0003097875,0.011072609,0.00014928488,0.00011215352,0.000073276715,0.000093917486,0.91926175,0.008669107,0.00035521036,0.00039613585,0.058749568],"study_design_scores_gemma":[0.000017839055,0.00015677385,0.0031349766,0.0000050796857,0.000024273124,0.000018635927,0.000019019117,0.9942107,0.002240267,0.00007043449,0.0000929542,0.0000091255415],"about_ca_topic_score_codex":0.01740592,"about_ca_topic_score_gemma":0.011165689,"teacher_disagreement_score":0.01740592,"about_ca_system_score_codex":0.00070833997,"about_ca_system_score_gemma":0.00056926324,"threshold_uncertainty_score":0.0346092},"labels":[],"label_agreement":null},{"id":"W1997403214","doi":"10.1016/j.cirp.2015.04.074","title":"Prediction and control of drilling-induced damage in fibre-reinforced polymers using a new hybrid force and temperature modelling approach","year":2015,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Delamination (geology); Drilling; Fibre-reinforced plastic; Transient (computer programming); Materials science; Thermal; Structural engineering; Mechanical engineering; Composite material; Computer science; Engineering; Geology","score_opus":0.04729463938534048,"score_gpt":0.24715489270088586,"score_spread":0.19986025331554538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997403214","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37937623,0.00048572724,0.6152411,0.00021480175,0.000077283694,0.00006266908,0.00006496617,0.0003285937,0.0041486337],"genre_scores_gemma":[0.9831629,0.0001159428,0.015080805,0.000015658652,0.000013121556,0.000045610606,0.00002858769,0.00002352535,0.0015138971],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988997,0.00002551846,0.000006069298,0.000024323288,0.00003468601,0.000019458166],"domain_scores_gemma":[0.99949074,0.00031257546,0.00007827417,0.000022853106,0.00007206973,0.000023398376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041846005,0.00070760155,0.00068270264,0.00030354242,0.00032208808,0.0006053379,0.00053820974,0.0011815075,0.000677683],"category_scores_gemma":[0.0008035968,0.00054462167,0.00062689226,0.00018814782,0.0005973547,0.00057716767,0.00049006334,0.00063433946,0.00010877538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014519144,0.000015238776,0.0001490767,0.0000111264835,0.0000054652855,0.000010413281,0.000008128641,0.99557894,0.0021322556,0.00021988236,0.000021836991,0.0018330322],"study_design_scores_gemma":[0.0000012185048,0.0000068691897,0.000047728852,4.901234e-7,9.367484e-7,0.0000010254637,7.1930947e-7,0.9996698,0.00022251115,0.000035344205,0.00001230928,0.0000010511956],"about_ca_topic_score_codex":0.01058661,"about_ca_topic_score_gemma":0.0071469527,"teacher_disagreement_score":0.01058661,"about_ca_system_score_codex":0.0004434344,"about_ca_system_score_gemma":0.0006495382,"threshold_uncertainty_score":0.021049976},"labels":[],"label_agreement":null},{"id":"W1997502775","doi":"10.1007/s11665-009-9587-3","title":"Microscopic Observations on the Origin of Defects During Machining of Direct Aged (DA) Inconel 718 Superalloy","year":2010,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Pratt and Whitney Canada","keywords":"Materials science; Superalloy; Inconel; Machining; Carbide; Metallography; Metallurgy; Shearing (physics); Cemented carbide; Alloy; Surface roughness; Microstructure; Composite material","score_opus":0.01112384588423465,"score_gpt":0.2106531856524914,"score_spread":0.19952933976825674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997502775","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99775887,0.00027201418,0.0010438253,0.000014126956,0.000008416473,0.0000053275407,0.00011305009,0.00003070552,0.0007536187],"genre_scores_gemma":[0.9981951,0.00008353142,0.00083623035,0.000008391511,0.0000028861393,0.0000034202376,0.00009555248,0.000010137396,0.000764903],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999527,0.0000025324107,0.0000029323744,0.0000115803905,0.000016767282,0.000013397793],"domain_scores_gemma":[0.9997676,0.00006787525,0.000051772313,0.00003560445,0.000057341113,0.000019921003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008937814,0.00010639438,0.00010086124,0.0002110977,0.00022651903,0.00015562878,0.00024311275,0.00021149723,0.00097534014],"category_scores_gemma":[0.00016547849,0.00013980328,0.000100017256,0.00012340657,0.0003004811,0.00019578407,0.00010478821,0.0002743045,0.00010482808],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013611169,0.000010926502,0.0016714697,0.00003406929,0.000005122995,0.00019029308,0.000090465226,0.00018364715,0.9961242,0.00012467818,0.00004852744,0.0013806112],"study_design_scores_gemma":[0.00001720592,0.00025174415,0.09619098,0.000008142257,0.00002595921,0.0006314288,0.00030737894,0.0022092587,0.89827245,0.00009022371,0.0019811923,0.00001404854],"about_ca_topic_score_codex":0.0018449086,"about_ca_topic_score_gemma":0.0020558438,"teacher_disagreement_score":0.0018449086,"about_ca_system_score_codex":0.00019797757,"about_ca_system_score_gemma":0.0000955033,"threshold_uncertainty_score":0.0036683083},"labels":[],"label_agreement":null},{"id":"W1997649178","doi":"10.1504/ijmms.2014.067164","title":"Characterisation and optimisation of minimum quantity lubrication in milling of Ti-6Al-4V alloy using phase Doppler anemometry (PDA)","year":2014,"lang":"en","type":"article","venue":"International Journal of Mechatronics and Manufacturing Systems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"Mitacs","keywords":"Nozzle; Machining; Lubrication; Materials science; Volumetric flow rate; Surface roughness; Mechanical engineering; Flow visualization; Spray characteristics; Surface finish; Flow (mathematics); Metallurgy; Spray nozzle; Engineering drawing; Composite material; Mechanics; Engineering","score_opus":0.011850816557924977,"score_gpt":0.26155857587418324,"score_spread":0.24970775931625827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997649178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9896625,0.00090205605,0.008950648,0.000038156628,0.0000100300595,0.000034052977,0.00005382851,0.000047073132,0.00030164252],"genre_scores_gemma":[0.98570806,0.0004717831,0.013298424,0.000013381542,0.0000044680855,0.000020657853,0.00005853106,0.000019273499,0.00040540035],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995061,0.00008088682,0.000033362507,0.00005888807,0.00028733094,0.000033491706],"domain_scores_gemma":[0.9994642,0.00021048564,0.00014805477,0.000027930793,0.00013052835,0.000018682054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000658533,0.00025601033,0.0004021387,0.0003623019,0.00019553033,0.00056024786,0.00035952253,0.00034881954,0.0002800331],"category_scores_gemma":[0.0014068868,0.00019974246,0.00022905505,0.0002508015,0.0003370532,0.0004273191,0.00021234344,0.00028686694,0.000095827694],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010091303,0.000018549004,0.00048175518,0.0000988744,0.0000030650326,0.000027839484,0.0000649524,0.000704723,0.994218,0.000046235335,0.000014201305,0.004220854],"study_design_scores_gemma":[0.000011709733,0.00064804754,0.0037257953,0.0000074001264,0.00001083028,0.000067298744,0.000054888413,0.007218652,0.9875442,0.0000476912,0.0006529141,0.000010630573],"about_ca_topic_score_codex":0.00062962295,"about_ca_topic_score_gemma":0.0010482157,"teacher_disagreement_score":0.000658533,"about_ca_system_score_codex":0.00031950013,"about_ca_system_score_gemma":0.0002562565,"threshold_uncertainty_score":0.0034826398},"labels":[],"label_agreement":null},{"id":"W1998191126","doi":"10.1016/j.ijmachtools.2004.07.003","title":"Effect of coolant strategy on tool performance, chip morphology and surface quality during high-speed machining of A356 aluminum alloy","year":2004,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":229,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of New Brunswick","funders":"","keywords":"Coolant; Machining; Materials science; Surface roughness; Aluminium; Lubricant; Alloy; Metallurgy; Cutting fluid; Tool wear; Surface finish; Mechanical engineering; Composite material; Engineering","score_opus":0.007057834732705413,"score_gpt":0.25599126464675515,"score_spread":0.24893342991404974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998191126","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99935657,0.00020872877,0.00022650984,0.000012698026,0.00000812768,0.0000034351024,0.000024199053,0.00001638005,0.00014339482],"genre_scores_gemma":[0.99951684,0.00005261901,0.00019347109,0.0000055780415,0.000003311373,0.0000024639667,0.000024850413,0.000013830639,0.0001870403],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980205,0.00003594021,0.000016900884,0.000048878734,0.000039992246,0.000056136134],"domain_scores_gemma":[0.99913675,0.00041236874,0.00017017098,0.000055284167,0.00015378933,0.00007170663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039244618,0.00034117792,0.00048001666,0.00021845254,0.00038874298,0.00051182497,0.00038303446,0.0003839321,0.0013308262],"category_scores_gemma":[0.00094222673,0.00031569772,0.00021621685,0.00025055723,0.0003478999,0.00051908393,0.00018468116,0.0002754277,0.00018478862],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031074635,0.00010996067,0.0017010006,0.00016787145,0.000029348064,0.00020005905,0.00020767188,0.0017490429,0.9875537,0.000044747467,0.00014498526,0.004984206],"study_design_scores_gemma":[0.00006547286,0.0020717857,0.01808742,0.0000103600405,0.000069852125,0.00011123433,0.00014356255,0.006427649,0.97253686,0.00002325853,0.00042595324,0.000026524913],"about_ca_topic_score_codex":0.0014387668,"about_ca_topic_score_gemma":0.003572834,"teacher_disagreement_score":0.0014387668,"about_ca_system_score_codex":0.00037845186,"about_ca_system_score_gemma":0.00031888662,"threshold_uncertainty_score":0.0044520497},"labels":[],"label_agreement":null},{"id":"W1998532408","doi":"10.1115/1.4025832","title":"Integrated Process of Laser-Assisted Machining and Laser Surface Heat Treatment","year":2013,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Materials science; Finite element method; Machining; Laser; Process (computing); Hardenability; Mechanical engineering; Microstructure; Surface (topology); Metallurgy; Computer science; Engineering; Optics; Structural engineering; Mathematics; Geometry; Physics","score_opus":0.006830082025414782,"score_gpt":0.2167415494733569,"score_spread":0.20991146744794212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998532408","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4372883,0.0015415692,0.55039656,0.00011092557,0.00022000233,0.00033119036,0.00020540762,0.002988722,0.006917259],"genre_scores_gemma":[0.76942855,0.00026342907,0.22610922,0.00003590035,0.000040502975,0.00014252534,0.00014819979,0.000047842008,0.003783734],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99956876,0.000015371994,0.000015473908,0.00008068817,0.00026379214,0.00005586149],"domain_scores_gemma":[0.9998136,0.000030432971,0.000036793714,0.00003908148,0.00006455256,0.000015421063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023642438,0.00038353357,0.0007600037,0.00044869867,0.0002644082,0.00047001388,0.0011781815,0.00066952466,0.0010782465],"category_scores_gemma":[0.00024118034,0.00036939202,0.0004118836,0.00048108233,0.0002699976,0.00047415568,0.0005268385,0.0005348761,0.00043798544],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011971513,0.00013844908,0.0007962413,0.0001627087,0.00002787305,0.000106039166,0.00004149905,0.0061271233,0.9502799,0.0014232143,0.00026196308,0.040515266],"study_design_scores_gemma":[0.000049096147,0.0011420533,0.004602229,0.000013491454,0.00008246999,0.00045853315,0.00002397392,0.102644995,0.88362724,0.00041470554,0.006893275,0.00004793017],"about_ca_topic_score_codex":0.0006551969,"about_ca_topic_score_gemma":0.0011829141,"teacher_disagreement_score":0.0011781815,"about_ca_system_score_codex":0.00035002508,"about_ca_system_score_gemma":0.0007699692,"threshold_uncertainty_score":0.0036070943},"labels":[],"label_agreement":null},{"id":"W1998963757","doi":"10.4028/www.scientific.net/amr.223.591","title":"Dynamic Study of Thin Wall Part Turning","year":2011,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Process (computing); Machining; Engineering; Context (archaeology); Time domain; Reliability (semiconductor); Mechanical engineering; Computer science; Control engineering","score_opus":0.052631470660445545,"score_gpt":0.34192788134466284,"score_spread":0.2892964106842173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998963757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93098056,0.00044945808,0.05738616,0.00009137802,0.000029313489,0.000044862274,0.000056711502,0.00009978146,0.010861757],"genre_scores_gemma":[0.997384,0.00010232839,0.0014325159,0.000006867327,0.0000035473645,0.000012595535,0.000023646851,0.0000058000687,0.0010286532],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99992657,0.000019462366,0.000002344114,0.000009840911,0.000025314572,0.000016521875],"domain_scores_gemma":[0.99984705,0.0000768009,0.000025292482,0.000009594159,0.000026283671,0.0000149417465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011197134,0.00020026459,0.0003351999,0.00037786012,0.00020376629,0.00040101534,0.00024913013,0.00034539096,0.001100808],"category_scores_gemma":[0.0004963486,0.00010781645,0.00027252178,0.00016994336,0.00037575493,0.0001557079,0.00024045617,0.00024062842,0.00009517601],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002055413,0.000075824704,0.0040037064,0.00015831192,0.000046859972,0.0012462783,0.00035213286,0.8647274,0.10576338,0.0110931825,0.00032568458,0.012001714],"study_design_scores_gemma":[0.00000829759,0.00007659901,0.0024646737,0.000007645404,0.0000056286644,0.0000886953,0.00005073529,0.9925403,0.003591408,0.0007119895,0.00044440475,0.000009763748],"about_ca_topic_score_codex":0.0017710254,"about_ca_topic_score_gemma":0.00073296105,"teacher_disagreement_score":0.0017710254,"about_ca_system_score_codex":0.00014937477,"about_ca_system_score_gemma":0.00017855779,"threshold_uncertainty_score":0.0036825538},"labels":[],"label_agreement":null},{"id":"W1999357280","doi":"10.1016/s1526-6125(06)70098-6","title":"Mechanistic Modeling of Ball End Milling Including Tool Wear","year":2006,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Flank; Tungsten carbide; Enhanced Data Rates for GSM Evolution; Ball (mathematics); Materials science; Rake; Tool wear; Rake angle; Mechanical engineering; Cutting tool; Geometry; Structural engineering; Computer science; Composite material; Metallurgy; Machining; Mathematics; Engineering; Artificial intelligence","score_opus":0.013175431833496943,"score_gpt":0.222153563012358,"score_spread":0.20897813117886105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999357280","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36930016,0.0033766278,0.5324375,0.0017116005,0.00049905153,0.00028513663,0.00048308863,0.0005392574,0.09136756],"genre_scores_gemma":[0.9826707,0.0006786951,0.0073784296,0.00005194612,0.000031367388,0.00007161123,0.00006123902,0.000039581402,0.009016373],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997874,0.000037532445,0.000012012918,0.00003634745,0.00007823202,0.00004850939],"domain_scores_gemma":[0.99952304,0.00019946095,0.00006858118,0.00008422382,0.00008764894,0.000036991903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005373975,0.00057629717,0.000987241,0.0005528084,0.0007343374,0.0013639247,0.0022616866,0.0023625551,0.004169391],"category_scores_gemma":[0.0015737774,0.00073848735,0.00082374905,0.00036359613,0.0010477449,0.0018290596,0.00088502164,0.00078021386,0.0005147392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003517322,0.00008093178,0.000365003,0.00008975528,0.00001600251,0.00018962055,0.000051132873,0.9705519,0.005207251,0.019460032,0.00027990874,0.0036733518],"study_design_scores_gemma":[0.0000111504,0.000020740363,0.00031890147,0.0000043947753,0.000005687641,0.000043763164,0.00001138801,0.99322563,0.00054404984,0.0053272494,0.00047933974,0.0000077243785],"about_ca_topic_score_codex":0.0024676062,"about_ca_topic_score_gemma":0.0019121106,"teacher_disagreement_score":0.004169391,"about_ca_system_score_codex":0.0006126025,"about_ca_system_score_gemma":0.00093385146,"threshold_uncertainty_score":0.013948023},"labels":[],"label_agreement":null},{"id":"W2000003935","doi":"10.1016/j.cirp.2007.05.079","title":"Power and Wheel Wear for Grinding Nickel Alloy with Plated CBN Wheels","year":2007,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":103,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Grinding; Materials science; Grinding wheel; Metallurgy; Abrasive; Alloy; Electroplating; Layer (electronics); Composite material","score_opus":0.013494915803328534,"score_gpt":0.2596897788980951,"score_spread":0.24619486309476654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000003935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960587,0.0001947077,0.0025468206,0.000013128757,0.000010191636,0.0000066657717,0.00004281176,0.000030113333,0.0010968652],"genre_scores_gemma":[0.99783957,0.000037070604,0.00055100594,0.0000015704579,0.0000010712891,0.0000018018548,0.000031679665,0.000015558227,0.0015205508],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996382,0.000028503973,0.00001566791,0.00004362624,0.00020453401,0.00006955634],"domain_scores_gemma":[0.9986563,0.0005836606,0.00013570988,0.0001922793,0.0003862392,0.000045832345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005929744,0.0002361509,0.00050336553,0.000623544,0.0005571268,0.0005506712,0.00062237727,0.0003664505,0.0022753738],"category_scores_gemma":[0.0022877979,0.00030272626,0.0003880402,0.0003362667,0.00049792277,0.00053546246,0.00035115526,0.0002483108,0.0003198253],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00455764,0.00022351235,0.03569261,0.00049920747,0.00009397474,0.0006223501,0.001017117,0.08773116,0.78724444,0.0016782584,0.0008396127,0.079800144],"study_design_scores_gemma":[0.000061461666,0.0020500426,0.14837418,0.000029358585,0.00012562236,0.0005965879,0.000919959,0.21760428,0.62591,0.0010648858,0.0031793464,0.00008433581],"about_ca_topic_score_codex":0.0065792236,"about_ca_topic_score_gemma":0.0153513225,"teacher_disagreement_score":0.0065792236,"about_ca_system_score_codex":0.00094935636,"about_ca_system_score_gemma":0.00037637728,"threshold_uncertainty_score":0.013081849},"labels":[],"label_agreement":null},{"id":"W2000211413","doi":"10.1007/s00107-001-0269-6","title":"Factors controlling bandsaw tracking","year":2002,"lang":"de","type":"article","venue":"European Journal of Wood and Wood Products","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Tracking (education); Pulp and paper industry; Environmental science; Business; Engineering","score_opus":0.02752085136302225,"score_gpt":0.2125929994064439,"score_spread":0.18507214804342165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000211413","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86906195,0.00084794086,0.112963155,0.00008210247,0.000059147198,0.000053632506,0.00019336313,0.00053979625,0.0161989],"genre_scores_gemma":[0.99388075,0.0001291541,0.0035448163,0.000010719567,0.000005797936,0.0000066497514,0.0000914282,0.000067783236,0.0022627995],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999428,0.000069617105,0.000028665287,0.00020703036,0.00014072299,0.00012590541],"domain_scores_gemma":[0.996479,0.0021088324,0.00048560236,0.00026667307,0.00047457265,0.000185346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007855907,0.0004458576,0.00043103163,0.0008548623,0.00067369116,0.002117469,0.00034799214,0.00055290933,0.0047550467],"category_scores_gemma":[0.0064260894,0.0003869879,0.0002142529,0.0008631665,0.0004143019,0.001434995,0.0005259056,0.00041613952,0.0018080935],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001480784,0.00029825678,0.07717752,0.0001689249,0.00010171588,0.00047182327,0.0003451373,0.065073185,0.69053084,0.0073877154,0.001327889,0.15563618],"study_design_scores_gemma":[0.00008290862,0.00089730654,0.24783579,0.000058688835,0.00043640615,0.0017080151,0.00054842775,0.24785298,0.48155886,0.007164128,0.011659738,0.00019678922],"about_ca_topic_score_codex":0.0017579995,"about_ca_topic_score_gemma":0.0022189494,"teacher_disagreement_score":0.0047550467,"about_ca_system_score_codex":0.000622229,"about_ca_system_score_gemma":0.0006194191,"threshold_uncertainty_score":0.015907228},"labels":[],"label_agreement":null},{"id":"W2000417540","doi":"10.1243/095440504323055524","title":"A fuzzy system for chatter suppression in end milling","year":2004,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Control theory (sociology); Fuzzy logic; Vibration; Machining; Controller (irrigation); End milling; Engineering; Control engineering; Computer science; Control (management); Mechanical engineering; Physics; Acoustics; Artificial intelligence","score_opus":0.006742018436838872,"score_gpt":0.2009785747522755,"score_spread":0.19423655631543665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000417540","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021195846,0.00054814754,0.97468215,0.00008885843,0.00007238284,0.000052867053,0.00002166963,0.00034872594,0.0029893196],"genre_scores_gemma":[0.80321914,0.00031390603,0.19112608,0.00010647541,0.000048771522,0.00010086313,0.000055660705,0.000025761545,0.0050033764],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99962103,0.00008135669,0.000024436562,0.00007128118,0.00017154035,0.000030284014],"domain_scores_gemma":[0.99966466,0.00012337229,0.000028981845,0.00002566347,0.00013900122,0.000018355973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005469553,0.00038256714,0.0005327696,0.0002922074,0.00058784685,0.00069415756,0.00068190444,0.00076138385,0.0014961304],"category_scores_gemma":[0.0010483344,0.00014200903,0.00030323147,0.0001497253,0.00033318793,0.00041968792,0.00042145254,0.000828867,0.00037403445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011407613,0.0002082856,0.001184304,0.0007383658,0.00009815336,0.0009950444,0.00099492,0.23644312,0.27143744,0.03372831,0.0027685906,0.45026267],"study_design_scores_gemma":[0.00009093488,0.00048606677,0.000697786,0.000060164046,0.000048598282,0.0002967272,0.00005420703,0.9481098,0.035948154,0.0069195516,0.0072378097,0.000050207662],"about_ca_topic_score_codex":0.0016791711,"about_ca_topic_score_gemma":0.0015315016,"teacher_disagreement_score":0.0016791711,"about_ca_system_score_codex":0.0003062381,"about_ca_system_score_gemma":0.0004283889,"threshold_uncertainty_score":0.0050050616},"labels":[],"label_agreement":null},{"id":"W2000514531","doi":"10.1177/0954405412458741","title":"Experimental and numerical investigation into workpiece surface topology in point grinding","year":2012,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Grinding; Surface roughness; Materials science; Point (geometry); Surface (topology); Grinding wheel; Surface finish; Yield (engineering); Mechanical engineering; Single point; Geometry; Composite material; Mechanics; Engineering; Computer simulation; Physics; Mathematics","score_opus":0.007421329839136376,"score_gpt":0.2156549894105094,"score_spread":0.20823365957137302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000514531","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931144,0.00009191771,0.005223489,0.000021280728,0.000009356759,0.000022061176,0.00017931564,0.00010911887,0.0012291014],"genre_scores_gemma":[0.9931646,0.00005137161,0.006257812,0.000004488523,0.0000026210425,0.00001410911,0.00010993831,0.000019326071,0.00037579128],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994122,0.000042785206,0.000025162803,0.00009686106,0.00034161116,0.00008150571],"domain_scores_gemma":[0.9985232,0.00067873206,0.00010381511,0.0003622038,0.00027697207,0.00005509668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060475577,0.00026238564,0.00053289556,0.00034551282,0.00036153957,0.00039727197,0.00077909173,0.0008590148,0.0031406523],"category_scores_gemma":[0.0016109999,0.00027761087,0.00028492487,0.00052398787,0.0006741709,0.00042042247,0.00029430797,0.00048093035,0.00025345923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039326656,0.00034363597,0.0028302425,0.00026400125,0.000016565795,0.0002320782,0.0004501674,0.058287613,0.9226611,0.00068587955,0.0003307177,0.013504785],"study_design_scores_gemma":[0.00010374524,0.0018720262,0.022068193,0.00002395687,0.000025030013,0.00025888736,0.00037279067,0.3236181,0.6493017,0.0005301065,0.0017556198,0.00006990126],"about_ca_topic_score_codex":0.0006240794,"about_ca_topic_score_gemma":0.00089524407,"teacher_disagreement_score":0.0031406523,"about_ca_system_score_codex":0.00028083788,"about_ca_system_score_gemma":0.00013231044,"threshold_uncertainty_score":0.01050657},"labels":[],"label_agreement":null},{"id":"W2001641369","doi":"10.1504/ijat.2014.060695","title":"High removal rate grinding of titanium alloys with electroplated CBN wheels","year":2014,"lang":"en","type":"article","venue":"International Journal of Abrasive Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Materials science; Grind; Grinding; Titanium alloy; Electroplating; Metallurgy; Surface roughness; Titanium; Grinding wheel; Surface finish; Composite material; Alloy; Creep feeding; Layer (electronics)","score_opus":0.0023167616048084946,"score_gpt":0.2046155926719724,"score_spread":0.20229883106716393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001641369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889797,0.00067455956,0.009653709,0.000019577863,0.000020730255,0.000029536723,0.000045037956,0.00009397267,0.00048311302],"genre_scores_gemma":[0.97954434,0.00034526642,0.018317798,0.000020411782,0.0000062207437,0.000019402569,0.00008173041,0.000055040273,0.0016097702],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994444,0.000031352538,0.00002711559,0.000080279424,0.00034446924,0.00007230265],"domain_scores_gemma":[0.99963653,0.00009495892,0.00008295816,0.000047526737,0.00011190486,0.000026181482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004556127,0.00040205746,0.00061816047,0.00041506742,0.00019526131,0.00030689954,0.00054680754,0.0003590346,0.00048833335],"category_scores_gemma":[0.0007388329,0.0002764598,0.00034074546,0.0002530181,0.00034049313,0.00032102465,0.00031001377,0.0003416403,0.00021045441],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031350253,0.0000071106324,0.00020451416,0.000040271458,0.0000021397973,0.00002412181,0.000028358836,0.000118241864,0.9979315,0.000012449569,0.000009022279,0.0015908869],"study_design_scores_gemma":[0.0000060198636,0.00017798095,0.0043681944,0.0000035106857,0.000007759185,0.00005254568,0.000023536082,0.0011037387,0.99363166,0.000010110529,0.00060847605,0.0000063667685],"about_ca_topic_score_codex":0.002705313,"about_ca_topic_score_gemma":0.011430429,"teacher_disagreement_score":0.002705313,"about_ca_system_score_codex":0.00042515039,"about_ca_system_score_gemma":0.00030486318,"threshold_uncertainty_score":0.0053792},"labels":[],"label_agreement":null},{"id":"W2002132069","doi":"10.1007/s00170-011-3478-0","title":"Geometry of chip formation in circular end milling","year":2011,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; National Research Council Canada; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Chip; End mill; Chip formation; End milling; RADIUS; Mechanical engineering; Kinematics; Process (computing); Numerical control; Geometry; Engineering; Materials science; Tool wear; Computer science; Mathematics; Physics; Classical mechanics","score_opus":0.010392009943737993,"score_gpt":0.22120779718130498,"score_spread":0.210815787237567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002132069","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88856536,0.0003071877,0.07704988,0.0003053323,0.0000827397,0.000074829324,0.00027919564,0.00037170335,0.032963842],"genre_scores_gemma":[0.99072886,0.000041483585,0.007099344,0.000012241749,0.000003409804,0.00001024371,0.00005427653,0.000029685543,0.0020204948],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99985266,0.00002438946,0.0000051389,0.000033404227,0.000055821056,0.000028655486],"domain_scores_gemma":[0.99973696,0.000078107834,0.00005691789,0.00003757181,0.000058383408,0.00003203363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001495066,0.00020637503,0.00026160278,0.00021009851,0.00044595133,0.00068414916,0.0004095456,0.00046898704,0.0019462679],"category_scores_gemma":[0.00050133985,0.00030273982,0.00015996194,0.0001401523,0.0006701777,0.00025589005,0.0003557132,0.00026808894,0.00039331996],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001104409,0.000102290716,0.0059291506,0.00018988867,0.000024113815,0.0014070441,0.00054903445,0.40710032,0.45798934,0.09672219,0.002740431,0.026141642],"study_design_scores_gemma":[0.00018426037,0.00070630043,0.020575885,0.000022386517,0.000026257267,0.0016410894,0.00050128356,0.7096072,0.23957385,0.0188524,0.008169277,0.00013974556],"about_ca_topic_score_codex":0.0016442821,"about_ca_topic_score_gemma":0.0020713413,"teacher_disagreement_score":0.0019462679,"about_ca_system_score_codex":0.00057044893,"about_ca_system_score_gemma":0.0006531143,"threshold_uncertainty_score":0.0065109134},"labels":[],"label_agreement":null},{"id":"W2002713147","doi":"10.1115/1.2390719","title":"A Fracture Mechanics Approach to the Prediction of Tool Wear in Dry High Speed Machining of Aluminum Cast Alloys—Part 2: Model Calibration and Verification","year":2006,"lang":"en","type":"article","venue":"Journal of Tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Calibration; Materials science; Tool wear; Automotive industry; Fracture (geology); Carbide; Microstructure; Mechanical engineering; Cutting tool; Fracture mechanics; Work (physics); Range (aeronautics); Metallurgy; Composite material; Engineering","score_opus":0.009263386343383707,"score_gpt":0.2069240536491353,"score_spread":0.1976606673057516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002713147","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3349442,0.00041881407,0.66046214,0.00009258948,0.000029845793,0.00019644608,0.00022688785,0.00066312257,0.0029659518],"genre_scores_gemma":[0.96898705,0.00013756524,0.02940727,0.000013517087,0.000007497435,0.00014584442,0.00009747722,0.00003619241,0.0011676097],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998055,0.000032498385,0.000011540169,0.00003329411,0.000099326106,0.000017865174],"domain_scores_gemma":[0.9994936,0.00027724364,0.00005949324,0.00006202955,0.0000985897,0.000009119739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057232345,0.0005782571,0.0004295805,0.0005653045,0.0003270959,0.0005084935,0.0009413617,0.0012538054,0.0010147821],"category_scores_gemma":[0.0011637831,0.00036520112,0.00076706463,0.0002572592,0.0003674769,0.00033284535,0.00032112442,0.00072293077,0.0002023753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018507799,0.000042931537,0.001181666,0.000037989445,0.000012898452,0.00003243768,0.000024217208,0.9828,0.0068604336,0.0003746268,0.00004561482,0.008568569],"study_design_scores_gemma":[0.000002374513,0.000021881939,0.00053544337,0.000002068975,0.0000017125975,0.000010701387,0.000003343227,0.997965,0.0012918647,0.00009345295,0.00006983673,0.0000024659216],"about_ca_topic_score_codex":0.0076261954,"about_ca_topic_score_gemma":0.0039291074,"teacher_disagreement_score":0.0076261954,"about_ca_system_score_codex":0.00049501524,"about_ca_system_score_gemma":0.0007873804,"threshold_uncertainty_score":0.01516366},"labels":[],"label_agreement":null},{"id":"W2003008485","doi":"10.1016/j.ijmachtools.2014.05.004","title":"A novel magnetic actuator design for active damping of machining tools","year":2014,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Actuator; Machining; Vibration; Stiffness; Engineering; Mechanical engineering; Torque; Bar (unit); Structural engineering; Flexibility (engineering); Control theory (sociology); Machine tool; Acoustics; Computer science; Physics; Control (management)","score_opus":0.017453938045683317,"score_gpt":0.25577738469515615,"score_spread":0.23832344664947283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003008485","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05421712,0.0011343249,0.9289351,0.00026757014,0.00039514745,0.000120339624,0.000057055306,0.000543534,0.014329771],"genre_scores_gemma":[0.7298434,0.000595242,0.25621298,0.0001278152,0.00022990705,0.00020148967,0.0000797286,0.000054375418,0.012655156],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998412,0.000017293727,0.0000085486145,0.00003527197,0.00008224021,0.000015386524],"domain_scores_gemma":[0.9998851,0.00001989919,0.000028932116,0.0000083314635,0.00004560316,0.000012011882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014378826,0.0003772029,0.0003575488,0.00020146812,0.0003037158,0.0003895025,0.0009386435,0.0005552896,0.0024011745],"category_scores_gemma":[0.00015275333,0.00018804685,0.000220193,0.000115330135,0.00019684144,0.00039110854,0.00022879618,0.00027523658,0.000579054],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018355236,0.00006758138,0.00020797699,0.0003302829,0.000025678926,0.00012191907,0.00005565363,0.0053679273,0.922948,0.005496301,0.0012729133,0.06392224],"study_design_scores_gemma":[0.0002834887,0.002215983,0.002968693,0.00008763915,0.0001471782,0.00198785,0.000107615975,0.5502708,0.36105257,0.0021711923,0.078628,0.00007890657],"about_ca_topic_score_codex":0.00019756047,"about_ca_topic_score_gemma":0.0005589334,"teacher_disagreement_score":0.0024011745,"about_ca_system_score_codex":0.00021166888,"about_ca_system_score_gemma":0.00023519859,"threshold_uncertainty_score":0.008032739},"labels":[],"label_agreement":null},{"id":"W2003140062","doi":"10.1177/0021998311428362","title":"A comprehensive analysis of cutting forces during routing of multilayer carbon fiber-reinforced polymer laminates","year":2012,"lang":"en","type":"article","venue":"Journal of Composite Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Bombardier (Canada); Université du Québec à Montréal","funders":"","keywords":"Materials science; Composite material; SIGNAL (programming language); Distortion (music); Fiber; Consistency (knowledge bases); Computer science","score_opus":0.007490939381209245,"score_gpt":0.23968702106744602,"score_spread":0.2321960816862368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003140062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929153,0.00011508924,0.0066498965,0.000006014852,0.0000026551338,0.000011146489,0.000038145885,0.000038825274,0.0002230406],"genre_scores_gemma":[0.99624807,0.00006345056,0.0033630761,0.0000015384769,7.4414754e-7,0.000008195557,0.000034263336,0.000004909754,0.00027574602],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999043,0.000007387381,0.0000046628256,0.000018222288,0.000050768544,0.000014638403],"domain_scores_gemma":[0.99979633,0.00007819796,0.000052726875,0.00001926833,0.00004149147,0.000012066647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019384887,0.00026535144,0.00020016362,0.00023579228,0.00014529012,0.00013867368,0.00017152328,0.00025849123,0.00036847108],"category_scores_gemma":[0.00035200344,0.00014117853,0.00019037847,0.00014397444,0.00015713376,0.0001782142,0.000075805954,0.00016483974,0.00005796632],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016496445,0.000054125598,0.0024596655,0.00011141592,0.000011372086,0.00014214886,0.00011666136,0.027593069,0.95037895,0.00011266669,0.000052015257,0.01880307],"study_design_scores_gemma":[0.00001356171,0.0011481647,0.04222798,0.000014621685,0.000022644306,0.00015344359,0.000102497186,0.26431105,0.69098574,0.0000840492,0.000900883,0.000035447185],"about_ca_topic_score_codex":0.0010840157,"about_ca_topic_score_gemma":0.0013855055,"teacher_disagreement_score":0.0010840157,"about_ca_system_score_codex":0.00018410028,"about_ca_system_score_gemma":0.00018129636,"threshold_uncertainty_score":0.0021554232},"labels":[],"label_agreement":null},{"id":"W2003659684","doi":"10.1504/ijmpt.2009.025222","title":"Neural Network prediction of dry grinding by CBN grinding wheel using special conditioning","year":2009,"lang":"en","type":"article","venue":"International Journal of Materials and Product Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Bundesministerium für Wirtschaft und Technologie","keywords":"Grinding; Machining; Artificial neural network; Surface roughness; Materials science; Grinding wheel; Process (computing); Surface grinding; Mechanical engineering; Process engineering; Surface finish; Metallurgy; Computer science; Composite material; Engineering; Artificial intelligence","score_opus":0.007628929556064587,"score_gpt":0.23761169155799597,"score_spread":0.22998276200193138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003659684","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88169783,0.00009498793,0.11695291,0.000042590556,0.000019727819,0.00003260145,0.000068063346,0.00028921722,0.00080206094],"genre_scores_gemma":[0.98811394,0.000036561814,0.011078784,0.000005083917,0.0000018015706,0.0000190619,0.000059339513,0.000008113515,0.0006773661],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999089,0.0000141081355,0.0000039674874,0.000025538371,0.000030822437,0.000016663238],"domain_scores_gemma":[0.99961555,0.00024949602,0.000038079663,0.000016242566,0.000066754554,0.000013823037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047073598,0.00047953028,0.0003256916,0.00027186182,0.00011044001,0.00032003273,0.00029971404,0.0005489455,0.00076069706],"category_scores_gemma":[0.0012318615,0.00022400655,0.0003201365,0.00019094857,0.00021439676,0.00031654403,0.00012690235,0.00036111966,0.00011431015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029760355,0.00009403414,0.0053607356,0.00005389853,0.000025823187,0.000042266605,0.00003105646,0.9371295,0.02240848,0.00019446068,0.00015542543,0.034206677],"study_design_scores_gemma":[0.0000034141742,0.000029197176,0.0014557076,7.9048283e-7,0.0000027586957,0.000002368622,0.0000017907095,0.99577385,0.0026787391,0.00003206447,0.000016788303,0.000002536132],"about_ca_topic_score_codex":0.0101904245,"about_ca_topic_score_gemma":0.009174892,"teacher_disagreement_score":0.0101904245,"about_ca_system_score_codex":0.0004979762,"about_ca_system_score_gemma":0.00032275173,"threshold_uncertainty_score":0.020262241},"labels":[],"label_agreement":null},{"id":"W2005812670","doi":"10.1109/ieem.2010.5674634","title":"An intelligent approach of obtaining feasible machining methods and their selection priorities based on features using neural network","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Artificial neural network; Computer science; Machining; Selection (genetic algorithm); Backpropagation; Artificial intelligence; Machine learning; Sample (material); Linear regression; Data mining; Engineering","score_opus":0.01907193468892025,"score_gpt":0.3116306201545924,"score_spread":0.29255868546567215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005812670","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019033521,0.00011452214,0.97912383,0.00006174425,0.000014506095,0.00008907798,0.000021829685,0.00018749497,0.0013534656],"genre_scores_gemma":[0.34456846,0.0001963239,0.6535577,0.000055702178,0.00003360109,0.00026040495,0.00010369386,0.00006788202,0.0011562449],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99795973,0.00042808615,0.00021472869,0.00035056323,0.00089267874,0.00015413055],"domain_scores_gemma":[0.9981469,0.00074769894,0.00028227214,0.00010934733,0.000635846,0.00007799579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023873218,0.0012113117,0.0013029719,0.0028575177,0.0006732595,0.0014486575,0.0013102182,0.00081825745,0.001434512],"category_scores_gemma":[0.0057429965,0.0006610615,0.0006427461,0.0013050641,0.0006327722,0.0018613385,0.00078400824,0.00082485075,0.00020370608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004002812,0.00028843852,0.004818212,0.00048825488,0.00016144635,0.0001796582,0.000331518,0.3758817,0.030811654,0.01763894,0.0018254134,0.5671746],"study_design_scores_gemma":[0.000042275347,0.00015144379,0.001316128,0.000026102078,0.000046839014,0.00006258292,0.00006362037,0.9807217,0.0075682593,0.008794469,0.0011723285,0.000034212248],"about_ca_topic_score_codex":0.0024408335,"about_ca_topic_score_gemma":0.0031397599,"teacher_disagreement_score":0.0028575177,"about_ca_system_score_codex":0.00075945375,"about_ca_system_score_gemma":0.0016515495,"threshold_uncertainty_score":0.012625456},"labels":[],"label_agreement":null},{"id":"W2006351494","doi":"10.1115/1.1644552","title":"Mechanics and Dynamics of Serrated Cylindrical and Tapered End Mills","year":2004,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":112,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Tangent; Flute; Vibration; Kinematics; Enhanced Data Rates for GSM Evolution; Point (geometry); Mechanics; Geometry; Engineering; Structural engineering; Mechanical engineering; Physics; Mathematics; Classical mechanics; Acoustics","score_opus":0.004428754296810158,"score_gpt":0.1958773557486685,"score_spread":0.19144860145185832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006351494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69096583,0.00051831774,0.29695126,0.00013072907,0.000040480405,0.00004806626,0.00007934391,0.0001686066,0.011097435],"genre_scores_gemma":[0.9865941,0.0001770022,0.008444416,0.00001045642,0.0000066996818,0.00002187868,0.000024405335,0.000008233003,0.0047127567],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.999895,0.00001584343,0.000004225122,0.00002047717,0.000051798368,0.000012613693],"domain_scores_gemma":[0.999899,0.000023389815,0.00003542879,0.000010190713,0.000019074378,0.000012851885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016347702,0.00022296757,0.00021699359,0.00020723241,0.00019034144,0.0005050684,0.00042868446,0.0004216167,0.0009421065],"category_scores_gemma":[0.00028810912,0.00017006948,0.0002170234,0.000107757245,0.00057787,0.00042089124,0.0003644914,0.0002581265,0.00015604722],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002170671,0.000051390023,0.0027657163,0.00009171393,0.00001561794,0.0007893213,0.0004965766,0.8199661,0.11440943,0.038980383,0.00055302324,0.021663645],"study_design_scores_gemma":[0.000010182977,0.00010620676,0.0015473905,0.0000044381213,0.0000027564495,0.00013651076,0.000056287605,0.9912929,0.003182665,0.0029230812,0.00072167785,0.00001590444],"about_ca_topic_score_codex":0.00077332626,"about_ca_topic_score_gemma":0.00045189995,"teacher_disagreement_score":0.0009421065,"about_ca_system_score_codex":0.00016686058,"about_ca_system_score_gemma":0.00021803552,"threshold_uncertainty_score":0.0031516552},"labels":[],"label_agreement":null},{"id":"W2006593106","doi":"10.1108/09576060410512374","title":"A decision support system for machine tool selection","year":2004,"lang":"en","type":"article","venue":"Journal of Manufacturing Technology Management","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Flexibility (engineering); Selection (genetic algorithm); Computer science; Process (computing); Machine tool; Decision support system; Rank (graph theory); Product (mathematics); Productivity; Manufacturing engineering; Decision maker; Industrial engineering; Flexible manufacturing system; Operations research; Risk analysis (engineering); Engineering; Machine learning; Artificial intelligence; Operations management; Business; Economics; Mathematics; Mechanical engineering","score_opus":0.004596457634378293,"score_gpt":0.22023209338497454,"score_spread":0.21563563575059624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006593106","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0111127645,0.00029037296,0.96217597,0.00036046852,0.00015409611,0.0005934499,0.0012908751,0.020685159,0.0033369288],"genre_scores_gemma":[0.21977286,0.0004346917,0.76988155,0.0003930638,0.00012978418,0.0018743604,0.0028464529,0.00026450783,0.004402658],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988243,0.0003374447,0.00019077996,0.00020149151,0.0003768707,0.0000691333],"domain_scores_gemma":[0.9971668,0.0017547203,0.00016829539,0.00013193993,0.00066150876,0.00011666311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020153527,0.001386155,0.0014768,0.0015054833,0.0010208864,0.0024082635,0.0016226409,0.001467857,0.011761176],"category_scores_gemma":[0.006620252,0.00043938344,0.0007221104,0.0011917396,0.0003162885,0.0013421803,0.001125727,0.0013667888,0.0035323028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016364716,0.0005570667,0.0029476935,0.0011074649,0.0002775316,0.0013466103,0.0003998481,0.20749836,0.016163107,0.014316145,0.037421454,0.71632826],"study_design_scores_gemma":[0.00027995848,0.00024070096,0.0007519041,0.00009596106,0.00009348539,0.0002241516,0.00006486081,0.9655336,0.0070163347,0.008751498,0.016881604,0.00006602853],"about_ca_topic_score_codex":0.0033699197,"about_ca_topic_score_gemma":0.0026220307,"teacher_disagreement_score":0.011761176,"about_ca_system_score_codex":0.00071834703,"about_ca_system_score_gemma":0.0013450288,"threshold_uncertainty_score":0.039345086},"labels":[],"label_agreement":null},{"id":"W2006705900","doi":"10.1115/imece2010-38017","title":"A New Mechanistic Approach for Micro End Milling Force Modeling","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Victoria","funders":"","keywords":"Rubbing; Rake angle; End milling; Enhanced Data Rates for GSM Evolution; Rake; Shearing (physics); Materials science; Shear force; Root mean square; Contact force; Mechanics; Mechanical engineering; Computer science; Composite material; Machining; Engineering; Physics; Metallurgy","score_opus":0.01052575349908398,"score_gpt":0.22046318297736253,"score_spread":0.20993742947827856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006705900","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00517375,0.00022241403,0.98568475,0.00017708057,0.000047918547,0.00006849459,0.00008157114,0.000112013564,0.008432029],"genre_scores_gemma":[0.5211965,0.0031469269,0.44235468,0.00041868904,0.00022461187,0.0013403354,0.0003947437,0.00028414244,0.03063939],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976283,0.000033008124,0.000013246578,0.000043766668,0.00012697659,0.000020229676],"domain_scores_gemma":[0.99974626,0.00010261146,0.00004097514,0.000037561913,0.000059936814,0.000012568089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056226086,0.000888242,0.00068526925,0.00064041186,0.00055166485,0.0009999326,0.002208951,0.0018401702,0.00382937],"category_scores_gemma":[0.0008095241,0.0005634693,0.0011683572,0.00034824386,0.00062733155,0.0019194018,0.00077486323,0.0013202231,0.00082240516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000100379775,0.000076156,0.00028064803,0.00015945842,0.000028813633,0.00015060621,0.00010072783,0.86376923,0.012326212,0.10894275,0.0005918017,0.013563611],"study_design_scores_gemma":[0.0000050256353,0.000025850137,0.00012605099,0.000014353642,0.000007837847,0.000057191493,0.000011338045,0.97619027,0.0011805256,0.0167054,0.0056645107,0.000011560212],"about_ca_topic_score_codex":0.0013294226,"about_ca_topic_score_gemma":0.0011668269,"teacher_disagreement_score":0.00382937,"about_ca_system_score_codex":0.0004942152,"about_ca_system_score_gemma":0.000873557,"threshold_uncertainty_score":0.012810469},"labels":[],"label_agreement":null},{"id":"W2006724892","doi":"10.1243/09544054jem931","title":"Arbitrary Lagrangian Eulerian analysis on cutting with a honed tool","year":2008,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Enhanced Data Rates for GSM Evolution; Chip formation; Materials science; Shear zone; Trailing edge; Mechanics; Shear (geology); Shear stress; Finite element method; Stagnation point; Viscoplasticity; Geometry; Composite material; Geology; Structural engineering; Machining; Metallurgy; Engineering; Tool wear; Mathematics; Physics; Constitutive equation","score_opus":0.005907820727845919,"score_gpt":0.18163624968559025,"score_spread":0.17572842895774432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006724892","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.63841265,0.0002475635,0.3400694,0.00020856959,0.00005216647,0.000058925376,0.00011963616,0.00016745937,0.020663727],"genre_scores_gemma":[0.9611509,0.00012898122,0.029387876,0.00004098372,0.000015593378,0.000038598064,0.00008012615,0.000065100365,0.009091899],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990654,0.000018203224,0.000003346736,0.00001136366,0.00004013922,0.000020368801],"domain_scores_gemma":[0.9998406,0.000045780132,0.000041526637,0.00001611924,0.00003749273,0.000018397343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020259405,0.00024247915,0.0003246252,0.00048203967,0.0002669076,0.0005053621,0.00045629372,0.0004660502,0.0019000571],"category_scores_gemma":[0.00078116026,0.00020007258,0.00031397396,0.0002225222,0.0009292339,0.0003865453,0.0005354558,0.00031939903,0.00018541729],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043698343,0.000026485988,0.0012159852,0.000038642138,0.000010147788,0.00016378668,0.000060435606,0.94439846,0.008510011,0.038496207,0.0001749553,0.0068611857],"study_design_scores_gemma":[0.000005181168,0.000011575989,0.0003187374,0.0000025031707,0.0000012814999,0.000014306742,0.000006993126,0.9968586,0.00040193473,0.0020080425,0.00036603241,0.0000046991513],"about_ca_topic_score_codex":0.0048290435,"about_ca_topic_score_gemma":0.0035606287,"teacher_disagreement_score":0.0048290435,"about_ca_system_score_codex":0.0005042165,"about_ca_system_score_gemma":0.00056030025,"threshold_uncertainty_score":0.009601891},"labels":[],"label_agreement":null},{"id":"W2007064664","doi":"10.1016/s0890-6955(02)00140-2","title":"Fuzzy control of spindle power in end milling processes","year":2002,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada); University of Ottawa","funders":"","keywords":"End milling; Machining; Engineering; Mechanical engineering; End mill; Fuzzy logic; Carbide; Power (physics); Fuzzy control system; Control engineering; Engineering drawing; Control theory (sociology); Materials science; Control (management); Computer science; Metallurgy","score_opus":0.007449884719437825,"score_gpt":0.21877749804725288,"score_spread":0.21132761332781505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007064664","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4488031,0.00078578293,0.5347033,0.0002646558,0.00019228445,0.000053375454,0.000054167467,0.00017714547,0.014966163],"genre_scores_gemma":[0.9925073,0.000078836856,0.0063572265,0.000011052451,0.000012991895,0.00000941933,0.000009715218,0.0000052570003,0.0010082133],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987125,0.000024051662,0.000009189006,0.00002186302,0.00005021261,0.000023488052],"domain_scores_gemma":[0.99959904,0.00019203365,0.00004285385,0.00001449895,0.00013106388,0.000020419651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034776097,0.00033236592,0.00039081057,0.00028853904,0.0004017607,0.000790625,0.0004895892,0.00037959256,0.0010476625],"category_scores_gemma":[0.0010409708,0.00017261338,0.00022517037,0.00018982436,0.00026456986,0.00033344183,0.00024169184,0.00043728793,0.00010918056],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016131058,0.00024975493,0.0011385066,0.00029578106,0.00007267201,0.00026782454,0.00032750345,0.7134966,0.08157397,0.012879727,0.0012697187,0.18681479],"study_design_scores_gemma":[0.000042050862,0.0001600585,0.0010902605,0.000009423304,0.000015657359,0.000023160695,0.000024267896,0.98729265,0.008069036,0.0027211783,0.00053909916,0.000013175316],"about_ca_topic_score_codex":0.0026238095,"about_ca_topic_score_gemma":0.0032107013,"teacher_disagreement_score":0.0026238095,"about_ca_system_score_codex":0.00037209777,"about_ca_system_score_gemma":0.00022881976,"threshold_uncertainty_score":0.0052170753},"labels":[],"label_agreement":null},{"id":"W2007630047","doi":"10.1016/s0007-8506(07)60435-1","title":"Chatter Stability of Plunge Milling","year":2006,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Stability (learning theory); Engineering; Vibration; Eigenvalues and eigenvectors; Machining; Structural engineering; Torque; Mechanical engineering; Chip; Chip formation; Tool wear; Computer science; Physics; Acoustics","score_opus":0.019693136001301632,"score_gpt":0.23777751932470917,"score_spread":0.21808438332340754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007630047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6242716,0.0014532829,0.34067968,0.0007629883,0.000250044,0.000052425086,0.0001318193,0.00033120802,0.032067],"genre_scores_gemma":[0.9873126,0.00013594372,0.0043868166,0.00002942449,0.000034410194,0.000021200982,0.00003793911,0.000055426743,0.00798615],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996382,0.00012970298,0.000014035173,0.00007321253,0.00009597009,0.000048881633],"domain_scores_gemma":[0.99614716,0.002434414,0.00036007504,0.00020125869,0.00060948,0.00024770782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012015862,0.0006215575,0.0007787907,0.0010692751,0.0008343084,0.0012836313,0.0009283318,0.0010575978,0.0056178067],"category_scores_gemma":[0.007034035,0.0003485647,0.00040384516,0.000351422,0.0019494189,0.0012897667,0.0011212672,0.0012217363,0.00039309092],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022824255,0.00015876122,0.0029141887,0.0003990476,0.00011071065,0.0006068158,0.0010013724,0.5244395,0.05006333,0.38702834,0.0026484665,0.028347021],"study_design_scores_gemma":[0.000019290264,0.00007562996,0.00096858427,0.000011657746,0.00000864657,0.000043974942,0.000064247,0.9676275,0.00269072,0.028173463,0.00028534257,0.000030884785],"about_ca_topic_score_codex":0.0026812202,"about_ca_topic_score_gemma":0.0016582482,"teacher_disagreement_score":0.0056178067,"about_ca_system_score_codex":0.0007205228,"about_ca_system_score_gemma":0.0004946895,"threshold_uncertainty_score":0.018793404},"labels":[],"label_agreement":null},{"id":"W2007755221","doi":"10.1115/imece2012-88616","title":"High Speed Routing of Woven Carbon Fiber Reinforced Epoxy Laminates","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Delamination (geology); Materials science; Composite material; Epoxy; Surface roughness; Machining; Tool wear; Surface finish; Carbon fiber reinforced polymer; Graphite; Tribology; Drilling; Chip formation; Composite number; Metallurgy","score_opus":0.006333694380926734,"score_gpt":0.20968649214063514,"score_spread":0.2033527977597084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007755221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97451335,0.00066482206,0.023223791,0.000016054744,0.000030383448,0.000015648833,0.000026977816,0.00017093177,0.0013379465],"genre_scores_gemma":[0.9838499,0.00020138118,0.014737867,0.000006145695,0.0000052328483,0.000005438059,0.0000281373,0.00002377642,0.0011421294],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997631,0.000036575366,0.000015015197,0.000042987456,0.0000986079,0.000043730586],"domain_scores_gemma":[0.99949217,0.000084077255,0.00026264612,0.00006952139,0.00007528238,0.000016265765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020905804,0.00023596677,0.00011856978,0.00032483853,0.000081295904,0.00024361305,0.00019175775,0.00019741114,0.0005328801],"category_scores_gemma":[0.00036830845,0.00013556187,0.00013933575,0.00018335538,0.00017969495,0.0003210773,0.00013919816,0.0001257299,0.00017469602],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000083404564,0.000015596184,0.00075752474,0.000089661386,0.000006617066,0.00011720756,0.000046473324,0.002852738,0.9717999,0.00021851258,0.00007359542,0.023938833],"study_design_scores_gemma":[0.000011400651,0.000834041,0.0077394554,0.0000143848465,0.000013343489,0.00035622722,0.000053769698,0.009027745,0.978221,0.00018686388,0.0035237113,0.000018069984],"about_ca_topic_score_codex":0.00011422363,"about_ca_topic_score_gemma":0.00029642333,"teacher_disagreement_score":0.0005328801,"about_ca_system_score_codex":0.00011730595,"about_ca_system_score_gemma":0.00006100379,"threshold_uncertainty_score":0.0017825961},"labels":[],"label_agreement":null},{"id":"W2007986765","doi":"10.1115/1.4004322","title":"Development of a New Model for the Varying Dynamics of Flexible Pocket-Structures During Machining","year":2011,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Aerospace; Computation; Vibration; Finite element method; Structural engineering; Reduction (mathematics); Rayleigh–Ritz method; Mechanical engineering; Computer science; Limit (mathematics); Materials science; Engineering; Algorithm; Acoustics; Aerospace engineering; Geometry; Mathematics; Physics; Mathematical analysis","score_opus":0.022717168833789853,"score_gpt":0.23079074187920115,"score_spread":0.2080735730454113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007986765","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03026993,0.00022757429,0.9653856,0.00007694418,0.00003736844,0.00005684644,0.00007618532,0.00020949455,0.0036601718],"genre_scores_gemma":[0.8667952,0.00082121504,0.11716943,0.00008519676,0.00003688554,0.0005028923,0.00028419486,0.00016428436,0.014140692],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999846,0.000026336385,0.000009864171,0.000037850466,0.000058246173,0.000021582964],"domain_scores_gemma":[0.99984646,0.00006050977,0.000024069743,0.000019244797,0.000038990813,0.000010762962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003128785,0.0006080206,0.00073699653,0.00030578242,0.00027924182,0.0006456951,0.0013142575,0.001451576,0.0012096191],"category_scores_gemma":[0.0005535711,0.00060495356,0.0008011753,0.0002771016,0.0004920003,0.00085743977,0.000600977,0.0009544106,0.0003437056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012702274,0.000019636385,0.0003296772,0.000041940166,0.000009290782,0.00008491429,0.00005396637,0.98053384,0.010167399,0.0027340585,0.00013660062,0.005876005],"study_design_scores_gemma":[0.0000019360803,0.000007521259,0.00006930748,0.0000024769033,0.0000018912833,0.000013122526,0.0000035300714,0.99883074,0.0005285713,0.00021874736,0.00031899664,0.0000031122245],"about_ca_topic_score_codex":0.004187132,"about_ca_topic_score_gemma":0.0030957195,"teacher_disagreement_score":0.004187132,"about_ca_system_score_codex":0.00037578217,"about_ca_system_score_gemma":0.00087532087,"threshold_uncertainty_score":0.008325517},"labels":[],"label_agreement":null},{"id":"W2008097481","doi":"10.1016/j.jmatprotec.2008.05.050","title":"A force-temperature model including a constitutive law for Dry High Speed Milling of aluminium alloys","year":2008,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Aluminium; Materials science; Constitutive equation; Machining; Shear (geology); Work (physics); Metallurgy; Mechanical engineering; Composite material; Mechanics; Structural engineering; Engineering; Finite element method","score_opus":0.01865172020530769,"score_gpt":0.2552955374020955,"score_spread":0.2366438171967878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008097481","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23282428,0.0018228348,0.7304174,0.00094857404,0.00033500706,0.00017917619,0.00034905627,0.0005203404,0.03260348],"genre_scores_gemma":[0.9536674,0.00073935854,0.022064514,0.00009453924,0.000056572306,0.000117863514,0.0001569506,0.00014233035,0.022960503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982005,0.000035282294,0.0000119174365,0.00003303439,0.0000745097,0.00002519137],"domain_scores_gemma":[0.99973553,0.00010497259,0.000044578344,0.000032010314,0.0000677458,0.000015255538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005264939,0.00053820177,0.0011246166,0.00047830658,0.00065784954,0.0010016761,0.0014108563,0.002272471,0.0021128342],"category_scores_gemma":[0.0010433835,0.00076017674,0.0008817024,0.00044043304,0.0010256696,0.001139757,0.00054191734,0.0008314284,0.00042474087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017234415,0.000028319228,0.00017442937,0.000032350054,0.00000752346,0.000057081503,0.00002777967,0.9888249,0.003938464,0.0046531665,0.00019658415,0.0020422197],"study_design_scores_gemma":[0.000004933574,0.000007255018,0.00009964218,0.000001935811,0.0000025384313,0.000009737495,0.0000033574759,0.9989624,0.00023480259,0.00043953166,0.0002305441,0.0000032504302],"about_ca_topic_score_codex":0.015621358,"about_ca_topic_score_gemma":0.013311494,"teacher_disagreement_score":0.015621358,"about_ca_system_score_codex":0.00090276013,"about_ca_system_score_gemma":0.0014135056,"threshold_uncertainty_score":0.031060874},"labels":[],"label_agreement":null},{"id":"W2008198708","doi":"10.1006/jsvi.2001.3725","title":"STABILITY ANALYSIS OF SPINNING STEPPED-SHAFT WORKPIECES IN A TURNING PROCESS","year":2002,"lang":"en","type":"article","venue":"Journal of Sound and Vibration","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Machining; Stiffness; Stability (learning theory); Chart; Engineering; Position (finance); Machine tool; Process (computing); Cutting tool; Spinning; Mechanical engineering; Structural engineering; Control theory (sociology); Computer science; Mathematics; Artificial intelligence; Control (management)","score_opus":0.016839376732820467,"score_gpt":0.25543532830131216,"score_spread":0.2385959515684917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008198708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9427723,0.0001717963,0.05329233,0.00006038185,0.000015366017,0.000018780498,0.000026676158,0.00007437067,0.0035679934],"genre_scores_gemma":[0.9984816,0.000020630585,0.00088870275,0.000002295829,0.0000015775452,0.0000030213957,0.0000093416065,0.0000074499944,0.0005853619],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999018,0.000020954558,0.000003553919,0.000015493948,0.000040911615,0.00001735975],"domain_scores_gemma":[0.99955386,0.00024584154,0.000055675468,0.000022862769,0.00010187899,0.000019887664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000254233,0.00021037237,0.00033086987,0.00035954016,0.00047371993,0.00047818373,0.00042203753,0.0004237783,0.0013739968],"category_scores_gemma":[0.0009128477,0.00021149439,0.00033654494,0.00015647426,0.0006384313,0.0002415967,0.00027224337,0.00024269448,0.0001548924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001753782,0.00013125196,0.0055019385,0.00022537679,0.00013066722,0.0009720926,0.00079036114,0.64690655,0.29535365,0.016532052,0.00064783654,0.031054411],"study_design_scores_gemma":[0.000018430972,0.00013089455,0.0044574356,0.0000057648117,0.000014125817,0.000068977104,0.00008291513,0.98173606,0.0122557925,0.0010410025,0.00017567837,0.000012796407],"about_ca_topic_score_codex":0.003974055,"about_ca_topic_score_gemma":0.0025973506,"teacher_disagreement_score":0.003974055,"about_ca_system_score_codex":0.00040979535,"about_ca_system_score_gemma":0.0003349667,"threshold_uncertainty_score":0.007901847},"labels":[],"label_agreement":null},{"id":"W2008431418","doi":"10.1243/1464419011544349","title":"On machining dynamics of flexible parts","year":2001,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part K Journal of Multi-body Dynamics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Mechanical engineering; Deflection (physics); Machine tool; Torque; Finite element method; Computer science; Numerical control; Engineering; Cutting tool; Tool path; Engineering drawing; Structural engineering; Physics","score_opus":0.011350226719773947,"score_gpt":0.23961887344114827,"score_spread":0.2282686467213743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008431418","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07333596,0.004723037,0.89150125,0.00061258854,0.00018436095,0.000054613378,0.0002228554,0.00042496674,0.028940368],"genre_scores_gemma":[0.87568194,0.0074062874,0.09706559,0.00015626384,0.00018639104,0.00017526459,0.00042466243,0.00019596082,0.018707654],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999877,0.00002740318,0.000004580466,0.000021589647,0.000059040794,0.000010453251],"domain_scores_gemma":[0.9998448,0.00007324051,0.000022959806,0.00001895618,0.000029483224,0.000010592695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017177271,0.00044989897,0.00040374856,0.00038109208,0.00026831293,0.00058124424,0.00033216982,0.00048688456,0.0029041863],"category_scores_gemma":[0.0007373783,0.00021977122,0.00046649596,0.00045267516,0.0006917689,0.0009092413,0.0005201126,0.00048101105,0.0005360707],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054287346,0.000021940827,0.0006941573,0.00015097157,0.00002401268,0.00024998747,0.00018421498,0.82313716,0.014996445,0.11232198,0.0012886502,0.046876185],"study_design_scores_gemma":[0.00001005551,0.000035086403,0.00064829335,0.000025178135,0.0000050326644,0.00010290794,0.000020771635,0.9589882,0.0015584405,0.02949094,0.009102604,0.000012584584],"about_ca_topic_score_codex":0.002048161,"about_ca_topic_score_gemma":0.0012501671,"teacher_disagreement_score":0.0029041863,"about_ca_system_score_codex":0.00035109854,"about_ca_system_score_gemma":0.0002635389,"threshold_uncertainty_score":0.009715438},"labels":[],"label_agreement":null},{"id":"W2008796844","doi":"10.4271/2014-01-9003","title":"A New Method for Monitoring Gears Surface Failures Using Enhanced Image Registration Approach","year":2014,"lang":"en","type":"article","venue":"SAE International Journal of Aerospace","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Image registration; Transmission (telecommunications); Image (mathematics); Image processing","score_opus":0.013250663233498045,"score_gpt":0.3163839727736458,"score_spread":0.3031333095401478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008796844","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012658707,0.00025402458,0.98396194,0.00006052516,0.000060526712,0.00007128968,0.00007117467,0.0016342711,0.0012275722],"genre_scores_gemma":[0.12586415,0.00037677572,0.8695563,0.00007795766,0.00006511618,0.00013436799,0.00022648244,0.00024341856,0.0034554086],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989286,0.0001230436,0.000067275185,0.00029291757,0.00051783037,0.00007025672],"domain_scores_gemma":[0.99926776,0.0001231927,0.00012095302,0.00019986142,0.00026160132,0.000026662981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006023943,0.0007959347,0.00076228555,0.0019212406,0.00028177685,0.0007673659,0.0012131522,0.0009155941,0.0025145127],"category_scores_gemma":[0.0015420258,0.00046351113,0.0008915552,0.0014127675,0.00046125747,0.0013873205,0.0009575097,0.0009643224,0.0017384471],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025025874,0.00013514461,0.0018901171,0.0002899934,0.00009828333,0.00024060057,0.00024144356,0.0138009135,0.33696944,0.0032373043,0.0027236461,0.6401229],"study_design_scores_gemma":[0.0000416823,0.00039698838,0.0077723367,0.00004118518,0.0001819688,0.0018344544,0.00013117139,0.6384303,0.33110657,0.0023450993,0.017584277,0.00013402435],"about_ca_topic_score_codex":0.0007931424,"about_ca_topic_score_gemma":0.0009074931,"teacher_disagreement_score":0.0025145127,"about_ca_system_score_codex":0.0003040968,"about_ca_system_score_gemma":0.00052256737,"threshold_uncertainty_score":0.008411884},"labels":[],"label_agreement":null},{"id":"W2008960294","doi":"10.4028/www.scientific.net/msf.723.421","title":"A New Approach to Five-Axis CNC Flute Grinding of Solid End-Mills","year":2012,"lang":"en","type":"article","venue":"Materials science forum","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Rake; Rake angle; Flute; Grinding; Grind; End mill; Enhanced Data Rates for GSM Evolution; Ball (mathematics); Machining; Materials science; Mechanical engineering; Engineering drawing; Geometry; Computer science; Structural engineering; Engineering; Acoustics; Mathematics; Physics; Computer vision","score_opus":0.012066986541105324,"score_gpt":0.25611899863306176,"score_spread":0.24405201209195643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008960294","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05727974,0.00030023506,0.9329625,0.000040467003,0.000055365766,0.000108562825,0.00004666589,0.00039253975,0.008813933],"genre_scores_gemma":[0.35910848,0.0002030403,0.63569486,0.000024183493,0.000013906205,0.000081680184,0.00011560505,0.00006234825,0.0046958337],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99949586,0.000032788503,0.000015867889,0.000089470406,0.00034038365,0.000025562123],"domain_scores_gemma":[0.9998171,0.000020941477,0.000026341551,0.000053047283,0.000072567294,0.000009985671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028585814,0.00034699202,0.00038056308,0.0005446185,0.00035081114,0.00047612062,0.0007932879,0.00034325663,0.0013461078],"category_scores_gemma":[0.00030542142,0.0002060907,0.00032823486,0.00035533428,0.0004772862,0.0003192462,0.00043007324,0.0006029015,0.00037004548],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012865853,0.0001534316,0.0020118998,0.000413947,0.00002972323,0.00022661519,0.00026553796,0.07203336,0.6393439,0.042539332,0.0010963689,0.24175711],"study_design_scores_gemma":[0.00004521762,0.00085643807,0.006713451,0.000051385276,0.00003546709,0.0013346308,0.000087401306,0.5584644,0.38239482,0.007238336,0.04265076,0.00012757434],"about_ca_topic_score_codex":0.0009992055,"about_ca_topic_score_gemma":0.0023778556,"teacher_disagreement_score":0.0013461078,"about_ca_system_score_codex":0.00040406836,"about_ca_system_score_gemma":0.0005346182,"threshold_uncertainty_score":0.0045031905},"labels":[],"label_agreement":null},{"id":"W2010392253","doi":"10.1016/j.wear.2007.11.025","title":"An exploration of friction models for the chip–tool interface using an Arbitrary Lagrangian–Eulerian finite element model","year":2008,"lang":"en","type":"article","venue":"Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":90,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Finite element method; Chip formation; Chip; Machining; Materials science; Mechanical engineering; Interface (matter); Mechanics; Structural engineering; Computer science; Tool wear; Engineering; Composite material; Contact angle; Physics","score_opus":0.06252489827925828,"score_gpt":0.27912528994245417,"score_spread":0.2166003916631959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010392253","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21469264,0.00079267874,0.76077396,0.00040070256,0.000043428892,0.0000651388,0.00013852865,0.00025964016,0.022833278],"genre_scores_gemma":[0.9558443,0.000303121,0.039745547,0.000052228042,0.000013339334,0.000053056534,0.0000841857,0.00008357781,0.003820643],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985564,0.000041946787,0.000007327342,0.00001952393,0.000052821353,0.000022770691],"domain_scores_gemma":[0.99969697,0.00016018008,0.0000351933,0.0000430358,0.00004593264,0.000018791236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045321963,0.0005101249,0.00074837374,0.00055462896,0.00039351106,0.0008776008,0.0012924562,0.0014969277,0.0018080988],"category_scores_gemma":[0.0015766999,0.00060595415,0.0006482228,0.00047369243,0.0007560077,0.0011471829,0.00052979094,0.0005037652,0.0002466459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022690754,0.000034274468,0.00036062702,0.000043222328,0.000009406684,0.00004806785,0.00003839268,0.975808,0.002595179,0.017932113,0.00015446907,0.0029534127],"study_design_scores_gemma":[0.0000031271445,0.0000045172956,0.000049081867,0.0000025181578,0.0000013843113,0.0000058141336,0.0000035597536,0.998643,0.00015994284,0.0009863331,0.00013888125,0.0000018636332],"about_ca_topic_score_codex":0.0044088676,"about_ca_topic_score_gemma":0.0035995473,"teacher_disagreement_score":0.0044088676,"about_ca_system_score_codex":0.00056522235,"about_ca_system_score_gemma":0.000808545,"threshold_uncertainty_score":0.008766413},"labels":[],"label_agreement":null},{"id":"W2011042386","doi":"10.1016/j.precisioneng.2009.09.002","title":"Burr height model for vibration assisted drilling of aluminum 6061-T6","year":2009,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Drilling; Vibration; Thrust; Drill; Machining; Structural engineering; Engineering; Acoustics; Mechanical engineering; Physics","score_opus":0.012713735521361897,"score_gpt":0.23521445694390902,"score_spread":0.22250072142254712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011042386","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22603822,0.00044588605,0.74804777,0.00015581168,0.00008021263,0.00010336454,0.0007872061,0.002802708,0.021538746],"genre_scores_gemma":[0.96537805,0.00011578482,0.028777892,0.000015871545,0.000005024357,0.000053083102,0.0002728496,0.000091053,0.00529047],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998561,0.000018778728,0.0000062159684,0.000022224625,0.000082173305,0.000014487252],"domain_scores_gemma":[0.99983585,0.0000568845,0.000022716451,0.000017797169,0.00005915853,0.000007601196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022836009,0.0002841111,0.00038936065,0.0002437373,0.0002457715,0.00040591977,0.00086982973,0.0007872157,0.0033110846],"category_scores_gemma":[0.00038580553,0.00020914635,0.0003720314,0.00021977769,0.00014026462,0.00035688677,0.00020636483,0.00033284535,0.0005073026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084053856,0.000027558659,0.00048488905,0.0000702173,0.00001022907,0.00004556673,0.000036315836,0.9675021,0.010281252,0.0024264727,0.00050838524,0.018523017],"study_design_scores_gemma":[0.000005921514,0.000025029845,0.00023223064,0.0000024042574,0.0000035029045,0.000013192494,0.000004749547,0.99774075,0.0014010805,0.00014374412,0.00042295773,0.0000045377583],"about_ca_topic_score_codex":0.0100334715,"about_ca_topic_score_gemma":0.008771995,"teacher_disagreement_score":0.0100334715,"about_ca_system_score_codex":0.0003299976,"about_ca_system_score_gemma":0.0006639333,"threshold_uncertainty_score":0.019950092},"labels":[],"label_agreement":null},{"id":"W2011498489","doi":"10.4028/www.scientific.net/amm.325-326.34","title":"Effect of Tool Wear on Quality of Carbon Fiber Reinforced Polymer Laminate during Edge Trimming","year":2013,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec","keywords":"Materials science; Composite material; Trimming; Delamination (geology); Surface roughness; Surface integrity; Carbon fiber reinforced polymer; Drilling; Tool wear; Fiber; Scanning electron microscope; Machining; Composite number; Mechanical engineering; Metallurgy","score_opus":0.004656811226338243,"score_gpt":0.21702677087333724,"score_spread":0.212369959646999,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011498489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999127,0.00023856384,0.0004776403,0.0000051214374,0.0000059401323,0.000005382028,0.000019680614,0.000015321666,0.00010536741],"genre_scores_gemma":[0.99891675,0.00009542943,0.0006728616,0.00001012719,0.000003159946,0.000003711209,0.00004042818,0.000012675695,0.00024486732],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99952126,0.000076289565,0.000045317433,0.000088643916,0.00017057304,0.00009796988],"domain_scores_gemma":[0.9971553,0.0013700662,0.00050295494,0.00025517822,0.00059222605,0.00012424549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053032197,0.0003687079,0.00035109266,0.00030539028,0.00023836961,0.00036905077,0.00021500209,0.00043766538,0.00073659664],"category_scores_gemma":[0.0021232145,0.00025382318,0.0003474882,0.00017949032,0.00022305794,0.00029983037,0.00021543735,0.00031916343,0.00013456943],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007475003,0.00007102254,0.007920373,0.00019514751,0.0000404902,0.00030175183,0.00027412764,0.000922692,0.97748363,0.000009397564,0.000040915827,0.011993019],"study_design_scores_gemma":[0.000011070844,0.002850159,0.048851714,0.000015295607,0.00005039064,0.00030303176,0.00024652688,0.0020564294,0.945261,0.000013979477,0.00032285092,0.000017623144],"about_ca_topic_score_codex":0.0004179972,"about_ca_topic_score_gemma":0.00089611113,"teacher_disagreement_score":0.00073659664,"about_ca_system_score_codex":0.00013385034,"about_ca_system_score_gemma":0.00009048595,"threshold_uncertainty_score":0.002804637},"labels":[],"label_agreement":null},{"id":"W2012202682","doi":"10.1007/s00170-015-7104-4","title":"Determining the minimum clamping force by cutting force simulation in aerospace fuselage pocket machining","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Thrust; Clamping; Dynamometer; Fuselage; Machining; Engineering; Structural engineering; Aerospace; Mechanical engineering; Torus; Milling cutter; Aerospace engineering; Geometry","score_opus":0.01010744011329925,"score_gpt":0.26098149671279547,"score_spread":0.25087405659949624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012202682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8383985,0.0003521296,0.14671378,0.00017864675,0.000039464012,0.00006058242,0.00010684426,0.0003904861,0.0137595385],"genre_scores_gemma":[0.9850654,0.00005650149,0.014117495,0.000011282875,0.000003551604,0.000019762912,0.000030917327,0.000035177152,0.0006599293],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999002,0.000022646702,0.000004270895,0.0000140197735,0.000034298184,0.000024499584],"domain_scores_gemma":[0.99937135,0.00044455862,0.000055308014,0.00003076532,0.00007392142,0.00002421818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002988253,0.0003865318,0.00057958794,0.0003831524,0.0004971604,0.00048255135,0.00056912214,0.0012040507,0.0017753891],"category_scores_gemma":[0.0012287326,0.0004803698,0.000432306,0.0002772522,0.00039114547,0.00047402421,0.00029971063,0.00048348925,0.00017173243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055184955,0.000031648135,0.000687395,0.000036052006,0.000006107494,0.000048757247,0.000032450782,0.9896427,0.0037167752,0.00057817786,0.00009338462,0.0050714556],"study_design_scores_gemma":[0.000004600177,0.000012925297,0.00015703075,0.0000023425578,0.0000016237539,0.0000043977743,0.000006745315,0.9990903,0.00055245205,0.000100329125,0.000065136584,0.0000021217668],"about_ca_topic_score_codex":0.0139107695,"about_ca_topic_score_gemma":0.00941741,"teacher_disagreement_score":0.0139107695,"about_ca_system_score_codex":0.00050451094,"about_ca_system_score_gemma":0.0009250442,"threshold_uncertainty_score":0.027659595},"labels":[],"label_agreement":null},{"id":"W2013096730","doi":"10.1115/imece2013-65311","title":"Experimental Characterization and Multi-Objective Optimization of the Orbital Drilling Process of CFRP","year":2013,"lang":"en","type":"article","venue":"Volume 2B: Advanced Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Drilling; Delamination (geology); Materials science; Aerospace; Dynamometer; Machining; Deep hole drilling; Composite material; Carbon fiber reinforced polymer; End mill; Mechanical engineering; Chip formation; Surface roughness; Structural engineering; Tool wear; Composite number; Engineering; Metallurgy; Geology; Aerospace engineering","score_opus":0.004878569215812987,"score_gpt":0.2124588234171678,"score_spread":0.2075802542013548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013096730","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98575914,0.00046607206,0.011649075,0.000028832173,0.000020028549,0.00016497119,0.000212504,0.00005394502,0.0016455236],"genre_scores_gemma":[0.9775367,0.00034829899,0.020957418,0.00000812585,0.0000042201486,0.00021590233,0.00012800806,0.000016252206,0.0007850222],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99960846,0.000044641853,0.00003293913,0.00007960487,0.00017202622,0.00006233069],"domain_scores_gemma":[0.9990526,0.0003546178,0.0002547304,0.00007049283,0.0002138256,0.000053776846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009034429,0.0007841797,0.0005966682,0.0004722058,0.00029509718,0.00042235988,0.00047330357,0.0006224354,0.0010996253],"category_scores_gemma":[0.0007244315,0.00022542388,0.0005005355,0.00042619347,0.00033337218,0.00025847176,0.00031670672,0.0005266078,0.000113917326],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008174122,0.0016585032,0.0019131964,0.0015772623,0.000033397475,0.0002078221,0.0001407672,0.14141113,0.82892036,0.00032551534,0.0001897334,0.022804886],"study_design_scores_gemma":[0.00010881847,0.012220244,0.010139201,0.00006171542,0.000108059416,0.00007515642,0.00018344066,0.1852419,0.7896137,0.00019612169,0.0019878133,0.00006393089],"about_ca_topic_score_codex":0.0011013073,"about_ca_topic_score_gemma":0.0015087123,"teacher_disagreement_score":0.0011013073,"about_ca_system_score_codex":0.0002662422,"about_ca_system_score_gemma":0.00040885416,"threshold_uncertainty_score":0.0047779083},"labels":[],"label_agreement":null},{"id":"W2013243513","doi":"10.1109/systol.2013.6693954","title":"Online tool wear monitoring and estimation using power signals and S-transform","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Tool wear; Fault (geology); Signal processing; Computer science; Fault detection and isolation; Frequency domain; SIGNAL (programming language); Time domain; Machining; Time–frequency analysis; Process (computing); Power (physics); Representation (politics); Real-time computing; Electronic engineering; Engineering; Artificial intelligence; Digital signal processing; Computer hardware; Telecommunications; Computer vision","score_opus":0.009408337994201597,"score_gpt":0.24657363557340953,"score_spread":0.23716529757920793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013243513","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1588694,0.00037806938,0.8381196,0.000056114233,0.000033652796,0.000043137756,0.000066204986,0.001109233,0.00132449],"genre_scores_gemma":[0.87768453,0.00021016077,0.120948404,0.000022615171,0.000026785761,0.000030485251,0.00008212874,0.000037008864,0.0009578478],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996903,0.00003948133,0.000017496825,0.00006799957,0.00016489241,0.000019779096],"domain_scores_gemma":[0.9994844,0.00018956118,0.00010610454,0.00005009572,0.00015349552,0.000016256148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020417996,0.0005473097,0.00048401486,0.0011255796,0.00013174693,0.00044370312,0.00038461882,0.00041439332,0.0006687142],"category_scores_gemma":[0.0010399955,0.00015289964,0.00025255705,0.00067809486,0.00022116573,0.0007710731,0.00023856902,0.00020038684,0.00028206364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043847752,0.00017960097,0.008797206,0.00027804423,0.000053919666,0.0003045106,0.00015841161,0.046751827,0.26917514,0.0009627499,0.00080542715,0.67209476],"study_design_scores_gemma":[0.000035196463,0.00051031844,0.01621642,0.00002105103,0.00004461529,0.00062380434,0.00008765911,0.8375715,0.14192665,0.0009121735,0.002010204,0.00004043276],"about_ca_topic_score_codex":0.00044569463,"about_ca_topic_score_gemma":0.0005790311,"teacher_disagreement_score":0.0011255796,"about_ca_system_score_codex":0.0001118738,"about_ca_system_score_gemma":0.00017681104,"threshold_uncertainty_score":0.002237022},"labels":[],"label_agreement":null},{"id":"W2014943134","doi":"10.1016/j.ijmachtools.2005.05.013","title":"A survey of recent grinding wheel topography models","year":2005,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":138,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Grinding; Grinding wheel; Mechanical engineering; Machining; 3d model; Engineering; Engineering drawing; Geology; Computer science; Artificial intelligence","score_opus":0.02242168210858301,"score_gpt":0.26549304473770585,"score_spread":0.24307136262912285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014943134","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026048476,0.038241033,0.91188836,0.0005993615,0.00025282634,0.00013631898,0.002249434,0.0021208385,0.018463343],"genre_scores_gemma":[0.381625,0.11600545,0.4717433,0.00035498154,0.0004535916,0.00034435157,0.008971658,0.002164528,0.0183371],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99963665,0.000058283593,0.00003594767,0.00007611406,0.0001652475,0.000027659964],"domain_scores_gemma":[0.9992612,0.0003012357,0.000076831995,0.00014318859,0.00019369426,0.000023893459],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076899835,0.0011485372,0.0018779311,0.0017605376,0.00039911337,0.0012318657,0.0030023914,0.0010453301,0.0048071216],"category_scores_gemma":[0.0015427844,0.0010651635,0.0017152106,0.0033058547,0.00029471144,0.0014544147,0.00049087516,0.0008568456,0.001995908],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055443972,0.00009310975,0.001865293,0.00086998934,0.000112374575,0.00005406404,0.000040544026,0.6689581,0.0011998,0.008642776,0.005187941,0.31292054],"study_design_scores_gemma":[0.000010282099,0.00004880421,0.0008581116,0.00009284192,0.00004448291,0.00009686309,0.000015837504,0.97281927,0.0006959476,0.0054895654,0.019801904,0.000026076119],"about_ca_topic_score_codex":0.009799586,"about_ca_topic_score_gemma":0.015284005,"teacher_disagreement_score":0.009799586,"about_ca_system_score_codex":0.0006542924,"about_ca_system_score_gemma":0.0012014741,"threshold_uncertainty_score":0.019485116},"labels":[],"label_agreement":null},{"id":"W2015352856","doi":"10.1016/j.ijmachtools.2010.12.008","title":"Analytical stability lobes including nonlinear process damping effect on machining chatter","year":2011,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":110,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Nonlinear system; Discretization; Enhanced Data Rates for GSM Evolution; Vibration; Indentation; Stability (learning theory); Process (computing); Face (sociological concept); Engineering; Work (physics); Mechanical engineering; Structural engineering; Computer science; Physics; Acoustics; Mathematics; Mathematical analysis","score_opus":0.029529736382226314,"score_gpt":0.2904928879070828,"score_spread":0.26096315152485644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015352856","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1759509,0.001458102,0.769551,0.00049534516,0.00027400363,0.00010534273,0.000084827734,0.0005741664,0.051506307],"genre_scores_gemma":[0.97799873,0.00039142967,0.012276289,0.0000490838,0.000065543594,0.00004418286,0.000028384073,0.0001483246,0.008998089],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998204,0.00005791103,0.000006159029,0.000029962985,0.00006168879,0.000023764258],"domain_scores_gemma":[0.9991033,0.00048620242,0.00008075342,0.00007507153,0.00023039726,0.00002438769],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005932989,0.00090867496,0.000565228,0.0005905035,0.00041634208,0.00070673286,0.0006368306,0.0007096664,0.004070735],"category_scores_gemma":[0.0029178413,0.00036736464,0.0007994015,0.00023619682,0.00083407515,0.000936628,0.0006407889,0.00076307193,0.0005660599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045051475,0.000118803146,0.001220281,0.0007905188,0.00009082955,0.0009869413,0.001018822,0.7299934,0.10371032,0.12616916,0.0024123355,0.033038165],"study_design_scores_gemma":[0.000006127825,0.000015871148,0.00029366938,0.000013000881,0.000009022322,0.00005592828,0.000020861753,0.9936314,0.002389466,0.0032449213,0.00031289036,0.0000067262044],"about_ca_topic_score_codex":0.001104825,"about_ca_topic_score_gemma":0.0010697228,"teacher_disagreement_score":0.004070735,"about_ca_system_score_codex":0.00036858913,"about_ca_system_score_gemma":0.0003709285,"threshold_uncertainty_score":0.013617933},"labels":[],"label_agreement":null},{"id":"W2016095313","doi":"10.1016/j.ijmachtools.2014.11.012","title":"Modeling the mechanics and dynamics of arbitrary edge drills","year":2014,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Irkutsk State University","keywords":"Drilling; Drill; Engineering; Parametric statistics; Enhanced Data Rates for GSM Evolution; Stability (learning theory); Structural engineering; Vibration; Oblique case; Point (geometry); Mechanical engineering; Geometry; Mathematics; Computer science; Physics; Acoustics","score_opus":0.005479999861164144,"score_gpt":0.21792413299417582,"score_spread":0.21244413313301166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016095313","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28275874,0.00085607986,0.6842885,0.00040564267,0.00014694431,0.00007286664,0.00017622052,0.00038300816,0.030911988],"genre_scores_gemma":[0.96760345,0.00038818762,0.023599908,0.000035393743,0.00002155842,0.000051535666,0.000052539937,0.00004768839,0.008199844],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998543,0.000032269178,0.0000074737463,0.00002495455,0.000050524173,0.000030373261],"domain_scores_gemma":[0.99973553,0.0001231362,0.000059802565,0.000022933096,0.000032659595,0.000025933497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002712371,0.00048717984,0.00059411884,0.0005046716,0.0004280291,0.001034318,0.001162174,0.001654295,0.0025810392],"category_scores_gemma":[0.0008980779,0.0006743177,0.00044923747,0.0005365811,0.0010134793,0.0011927753,0.0007694194,0.0006096959,0.00036536614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020576661,0.00001634022,0.00035520765,0.000013508718,0.0000045450765,0.000043816442,0.000020466086,0.98832345,0.0011900462,0.0075528463,0.00010051219,0.0023586105],"study_design_scores_gemma":[0.000003195797,0.0000047820427,0.000089299996,0.0000013228455,0.0000011899735,0.000009406021,0.00000554824,0.99872017,0.00008968234,0.0008948495,0.00017818835,0.0000024934268],"about_ca_topic_score_codex":0.006453405,"about_ca_topic_score_gemma":0.0049081435,"teacher_disagreement_score":0.006453405,"about_ca_system_score_codex":0.00047013306,"about_ca_system_score_gemma":0.00085342134,"threshold_uncertainty_score":0.012831688},"labels":[],"label_agreement":null},{"id":"W2016555895","doi":"10.1016/s0890-6955(00)00025-0","title":"Integrated tool path and feed rate optimization for the finishing machining of 3D plane surfaces","year":2000,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Machining; Tool path; Cutter location; Ball (mathematics); Engineering; Mechanical engineering; Plane (geometry); Path (computing); Engineering drawing; Computer science; Mathematics; Geometry","score_opus":0.007271815533675499,"score_gpt":0.22587274076340527,"score_spread":0.21860092522972976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016555895","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22358112,0.00033346232,0.77259195,0.000034622568,0.000023781564,0.00006603357,0.0000690193,0.0007097616,0.0025902954],"genre_scores_gemma":[0.80778694,0.000126987,0.19045845,0.000013496666,0.000008229349,0.00007276771,0.00011114624,0.00016680396,0.0012551665],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971944,0.000047936963,0.000011548424,0.000031691226,0.00015044879,0.000038898397],"domain_scores_gemma":[0.9996799,0.00014140806,0.000048618662,0.00002773983,0.00009070412,0.000011606617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005697678,0.0006674471,0.000686384,0.00046348348,0.00024279377,0.0006355703,0.00066655746,0.00066234573,0.00092679047],"category_scores_gemma":[0.00079907896,0.000573278,0.0006345607,0.0004728682,0.00025436148,0.00043832965,0.00042122827,0.0004665189,0.00016942642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021605106,0.00012901232,0.0011262713,0.000114249415,0.000048471982,0.000039067672,0.00008217494,0.8724268,0.050541047,0.0015806233,0.00033995695,0.07335628],"study_design_scores_gemma":[0.000024497564,0.00013695464,0.00053121214,0.0000027600581,0.000012578988,0.000013690142,0.000008302968,0.9901978,0.008344973,0.0003319153,0.00038649028,0.000008758566],"about_ca_topic_score_codex":0.0027535183,"about_ca_topic_score_gemma":0.0043566097,"teacher_disagreement_score":0.0027535183,"about_ca_system_score_codex":0.0004564749,"about_ca_system_score_gemma":0.0007533004,"threshold_uncertainty_score":0.005474925},"labels":[],"label_agreement":null},{"id":"W2016706338","doi":"10.1016/j.ijmachtools.2006.03.006","title":"Modeling the effects of microstructure in metal cutting","year":2006,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Microstructure; Materials science; Chip formation; Homogeneous; Finite element method; Composite material; Chip; Metallurgy; Machining; Structural engineering; Thermodynamics; Computer science; Engineering; Tool wear; Physics","score_opus":0.0029561534897072036,"score_gpt":0.21302235673662331,"score_spread":0.2100662032469161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016706338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84152067,0.0016042185,0.13654947,0.00037655717,0.00015245292,0.000045726545,0.0001256173,0.00026413018,0.019361144],"genre_scores_gemma":[0.9911578,0.00026542114,0.0067397044,0.000020965115,0.00001358498,0.000008628208,0.000020210195,0.000023289716,0.0017503425],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999161,0.000021376452,0.0000030916995,0.000010533208,0.000027347729,0.000021586948],"domain_scores_gemma":[0.999668,0.0001841004,0.000054558514,0.000023384857,0.000047629008,0.000022258087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029252656,0.0003190247,0.00037378582,0.00026453883,0.00025459394,0.0005747593,0.00070830423,0.00096669164,0.0012117276],"category_scores_gemma":[0.001186106,0.0004875222,0.0003264084,0.0002835931,0.00039487157,0.00050805695,0.00028344415,0.00031125732,0.00015455249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002449957,0.000028926466,0.000512315,0.000015346432,0.000006207637,0.000028898838,0.0000096643835,0.99126524,0.004012788,0.0019608554,0.000066768815,0.0020685475],"study_design_scores_gemma":[0.0000066062494,0.000020548801,0.00035530148,0.0000014312709,0.0000041141957,0.000008132307,0.0000040630853,0.99831116,0.00059035845,0.00056018704,0.00013548107,0.0000026328514],"about_ca_topic_score_codex":0.008063681,"about_ca_topic_score_gemma":0.0097358925,"teacher_disagreement_score":0.008063681,"about_ca_system_score_codex":0.0005909109,"about_ca_system_score_gemma":0.0005966372,"threshold_uncertainty_score":0.01603347},"labels":[],"label_agreement":null},{"id":"W2016814109","doi":"10.1504/ijmr.2013.057750","title":"Parametric simulation of tool and workpiece interaction in broaching operation","year":2013,"lang":"en","type":"article","venue":"International Journal of Manufacturing Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Broaching; Parametric statistics; Oblique case; Engineering; Parametric model; Spline (mechanical); Structural engineering; Mechanical engineering; Enhanced Data Rates for GSM Evolution; Intersection (aeronautics); Engineering drawing; Computer science; Mathematics","score_opus":0.03543826490629944,"score_gpt":0.3595651119114366,"score_spread":0.32412684700513716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016814109","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4843809,0.00011963764,0.5070442,0.000055381093,0.000016485237,0.000073950025,0.00011351039,0.0004543214,0.0077415635],"genre_scores_gemma":[0.9829822,0.000066232875,0.01523044,0.0000057321495,0.0000018587996,0.000040108836,0.000043277225,0.000031853066,0.0015983114],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997434,0.000044105916,0.000009664902,0.000028817218,0.000119484255,0.00005442335],"domain_scores_gemma":[0.9994174,0.0003561998,0.0000648662,0.00008900537,0.000049922106,0.000022707984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040379632,0.00027967396,0.00033921623,0.00027546159,0.00023734792,0.00053362694,0.00091594964,0.00097346347,0.0017028303],"category_scores_gemma":[0.0013981143,0.00030983178,0.0004194425,0.00032525128,0.0005381066,0.0004997944,0.00063354976,0.0005073103,0.0002757848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008921607,0.000035399004,0.0008653945,0.000058132508,0.000008336032,0.00021785632,0.00020759586,0.96121037,0.027516833,0.0016916284,0.00008549824,0.008013734],"study_design_scores_gemma":[0.0000038862336,0.000045098663,0.0005343154,0.0000034667944,0.000002223773,0.000048596437,0.000025366186,0.9942325,0.004414726,0.0003303883,0.00035201025,0.00000749254],"about_ca_topic_score_codex":0.0011017717,"about_ca_topic_score_gemma":0.0007867976,"teacher_disagreement_score":0.0017028303,"about_ca_system_score_codex":0.00019628742,"about_ca_system_score_gemma":0.00034515088,"threshold_uncertainty_score":0.0056965947},"labels":[],"label_agreement":null},{"id":"W2016824127","doi":"10.1016/j.ijmachtools.2008.04.010","title":"Minimum quantity lubrication drilling of aluminium–silicon alloys in water using diamond-like carbon coated drills","year":2008,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":123,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"General Motors (Canada); University of Windsor; Natural Sciences and Engineering Research Council of Canada","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada","keywords":"Materials science; Lubrication; Drilling; Aluminium; Metallurgy; Drill; Tribology; Diamond-like carbon; Cutting fluid; Machining; Composite material; Carbon fibers; Thin film; Nanotechnology","score_opus":0.015448136566033444,"score_gpt":0.24554959586096242,"score_spread":0.23010145929492898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016824127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95445555,0.00060439465,0.04284173,0.00008060347,0.000030047908,0.000028441384,0.000029819561,0.00009952366,0.0018299477],"genre_scores_gemma":[0.9855606,0.000083405495,0.013586382,0.0000046119067,0.000002666696,0.0000063169073,0.000012070911,0.000010473935,0.00073342083],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997948,0.00002610103,0.000015000402,0.00003151326,0.000099810924,0.00003283674],"domain_scores_gemma":[0.99959797,0.00019588764,0.00008268712,0.000021644697,0.000075337906,0.000026562033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027145364,0.00019439991,0.00044910735,0.00023759087,0.00034223113,0.00043035214,0.00033837924,0.00035740703,0.00066143234],"category_scores_gemma":[0.0007456153,0.0003324927,0.00013673575,0.00018114361,0.00042183397,0.00074240705,0.00045782054,0.00018886822,0.000088499844],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015067094,0.000041320898,0.0020076463,0.00029952664,0.000008259885,0.00018293082,0.00021571296,0.015793009,0.9466554,0.0015217639,0.00020411883,0.031563617],"study_design_scores_gemma":[0.00015723152,0.0014380538,0.0043419874,0.00002205826,0.000021240388,0.00023236204,0.00023022444,0.14242807,0.847498,0.0009999921,0.0025994952,0.000031424806],"about_ca_topic_score_codex":0.0013409754,"about_ca_topic_score_gemma":0.0036366053,"teacher_disagreement_score":0.0013409754,"about_ca_system_score_codex":0.00033302122,"about_ca_system_score_gemma":0.00068822986,"threshold_uncertainty_score":0.0026663542},"labels":[],"label_agreement":null},{"id":"W2016984368","doi":"10.1115/imece2004-59340","title":"Kinematic Model of Dynamic Drilling Process","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Pratt and Whitney Canada","keywords":"Thrust; Kinematics; Torque; Vibration; Drilling; Drill; Axial symmetry; Mechanics; Machining; Structural engineering; Engineering; Control theory (sociology); Physics; Mechanical engineering; Computer science; Acoustics; Classical mechanics","score_opus":0.006107119396543949,"score_gpt":0.23361753562306042,"score_spread":0.22751041622651647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016984368","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0075714947,0.00056969747,0.97286385,0.00028603652,0.0000917098,0.00008127463,0.0006770365,0.00042367296,0.017435178],"genre_scores_gemma":[0.7584256,0.0034189771,0.16767766,0.0002195232,0.00023452064,0.0012964375,0.002272102,0.000235534,0.06621968],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994704,0.00010135205,0.00003728036,0.00012499707,0.0002134211,0.000052573134],"domain_scores_gemma":[0.99958056,0.0001245154,0.00011084919,0.00003993293,0.00012485572,0.000019278876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048297126,0.0011899989,0.001017155,0.0008624044,0.0004560363,0.0017011096,0.0017659647,0.0015122175,0.008650268],"category_scores_gemma":[0.0012082275,0.00052701554,0.0006778855,0.0008048889,0.00082968886,0.001402644,0.0009874715,0.0011543713,0.0027046558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037069985,0.000029574367,0.0005097418,0.0001418019,0.000016165206,0.0002510072,0.0001042498,0.89257145,0.0034999656,0.09044804,0.0012538004,0.0111370925],"study_design_scores_gemma":[0.000016531025,0.000042279968,0.00022070414,0.000014417887,0.000009663441,0.00013758187,0.000017821058,0.9749443,0.0005142766,0.01533289,0.008732152,0.000017281674],"about_ca_topic_score_codex":0.005158786,"about_ca_topic_score_gemma":0.0020726812,"teacher_disagreement_score":0.008650268,"about_ca_system_score_codex":0.0007482155,"about_ca_system_score_gemma":0.0010545594,"threshold_uncertainty_score":0.028938055},"labels":[],"label_agreement":null},{"id":"W2017174465","doi":"10.1016/j.ijmachtools.2004.01.006","title":"Application of region growing method to evaluate the surface condition of grinding wheels","year":2004,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pulverizer; Grinding; Grinding wheel; Process (computing); Mechanical engineering; Measure (data warehouse); Software; Machine tool; Position (finance); Digital microscope; Surface grinding; Image processing; Automotive engineering; Engineering; Computer science; Engineering drawing; Microscope; Computer vision; Optics; Image (mathematics)","score_opus":0.010612311178898985,"score_gpt":0.2971810667013933,"score_spread":0.28656875552249433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017174465","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52216417,0.0005979394,0.47354597,0.00005468591,0.00003817623,0.000069690795,0.0001823926,0.0010357624,0.002311254],"genre_scores_gemma":[0.86144894,0.00015196971,0.13756189,0.000007755316,0.00000678425,0.000025769605,0.000115230614,0.00006377248,0.0006179231],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997186,0.000046555422,0.000010982937,0.00005995042,0.0001419012,0.000022017015],"domain_scores_gemma":[0.99908686,0.00042888997,0.00007962261,0.000050349467,0.0003284112,0.000025839843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004859,0.00045809997,0.00058000075,0.0010660376,0.00024780657,0.0003863992,0.00052661385,0.0005518518,0.0006009071],"category_scores_gemma":[0.0009883849,0.00026674758,0.00044918482,0.0005358388,0.00022275742,0.0004427953,0.00017899433,0.00025663964,0.00014985612],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066025025,0.0001304663,0.011835444,0.0002531339,0.00008496619,0.0002171215,0.00024319076,0.13311921,0.6685822,0.0013883808,0.00053247076,0.18295315],"study_design_scores_gemma":[0.000014949942,0.00016674216,0.011117921,0.000006447089,0.00004393006,0.00016518949,0.00004671561,0.86770684,0.11977691,0.0003379011,0.0005810299,0.000035328765],"about_ca_topic_score_codex":0.0025217193,"about_ca_topic_score_gemma":0.0027544312,"teacher_disagreement_score":0.0025217193,"about_ca_system_score_codex":0.0003464063,"about_ca_system_score_gemma":0.00040427622,"threshold_uncertainty_score":0.0050140023},"labels":[],"label_agreement":null},{"id":"W2017481364","doi":"10.1115/1.1789531","title":"Dynamic Compensation of Spindle Integrated Force Sensors With Kalman Filter","year":2004,"lang":"en","type":"article","venue":"Journal of Dynamic Systems Measurement and Control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":90,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kalman filter; Compensation (psychology); Bandwidth (computing); Contact force; Force dynamics; SIGNAL (programming language); Control theory (sociology); Filter (signal processing); Signal processing; Engineering; Computer science; Electronic engineering; Mechanical engineering; Physics; Digital signal processing; Electrical engineering; Artificial intelligence","score_opus":0.006913623496983904,"score_gpt":0.19572803455961524,"score_spread":0.18881441106263133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017481364","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022598341,0.00043732263,0.97476554,0.00009582126,0.00007668597,0.000022594559,0.000032726584,0.00070878974,0.0012622008],"genre_scores_gemma":[0.85874504,0.00055916834,0.1365426,0.00009985193,0.00008161608,0.00008745287,0.00017708608,0.000058254835,0.0036489991],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995214,0.000064973254,0.000026343056,0.00012390014,0.00022128975,0.000042214313],"domain_scores_gemma":[0.99965286,0.000108077504,0.000050859275,0.000033377746,0.00014550604,0.000009315899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049392384,0.0006107716,0.00049232005,0.00035825765,0.0003139027,0.0004449772,0.0006041218,0.0006207636,0.0009408148],"category_scores_gemma":[0.001396306,0.00035546132,0.00030491053,0.0003416235,0.00020139111,0.0007442055,0.00031590337,0.00048409082,0.00037858196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005627717,0.00012392252,0.0033845678,0.0004193505,0.00014647277,0.00020420783,0.0002989076,0.24497408,0.14681244,0.007819283,0.0026167794,0.59263724],"study_design_scores_gemma":[0.00004572242,0.00019389034,0.002492974,0.000023272245,0.00004231666,0.0001028367,0.000017257164,0.96058893,0.030645417,0.0011297403,0.00468401,0.000033588407],"about_ca_topic_score_codex":0.0050859596,"about_ca_topic_score_gemma":0.004801431,"teacher_disagreement_score":0.0050859596,"about_ca_system_score_codex":0.0004413659,"about_ca_system_score_gemma":0.00045968234,"threshold_uncertainty_score":0.010112703},"labels":[],"label_agreement":null},{"id":"W2018464046","doi":"10.1016/s0890-6955(01)00088-8","title":"Chatter suppression in five-axis machining of flexible parts","year":2002,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Engineering; Mechanical engineering; Engineering drawing","score_opus":0.011730898563486199,"score_gpt":0.24062200093323746,"score_spread":0.22889110236975127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018464046","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5662477,0.0010692657,0.42375767,0.00012340037,0.00007275403,0.00002410873,0.00001644885,0.00019797533,0.008490657],"genre_scores_gemma":[0.9850584,0.00013420281,0.013187547,0.000011938027,0.000011619786,0.0000073015026,0.000010426911,0.000020449936,0.0015580765],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998336,0.000061706014,0.0000060047237,0.000017010487,0.000063795385,0.000017932403],"domain_scores_gemma":[0.99890924,0.0007179289,0.0001256874,0.000059086175,0.00014273779,0.000045288987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044802,0.0003196214,0.00032674902,0.0002541026,0.00025762912,0.00024123784,0.0004034175,0.000385597,0.0008435502],"category_scores_gemma":[0.0012890219,0.00018263877,0.0001945143,0.00022683087,0.0005207068,0.00033679078,0.00026862827,0.00025542226,0.00014397719],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030577588,0.00013434791,0.0027584257,0.00048166377,0.00008075259,0.0013358652,0.0011511118,0.2475551,0.6195628,0.030706497,0.00091713294,0.09225859],"study_design_scores_gemma":[0.000034440047,0.0002681619,0.0017571026,0.000013903257,0.000019557956,0.00029942486,0.00007737476,0.94395405,0.049929325,0.0030490158,0.0005796373,0.00001799234],"about_ca_topic_score_codex":0.0005069965,"about_ca_topic_score_gemma":0.0008141122,"teacher_disagreement_score":0.0008435502,"about_ca_system_score_codex":0.0001343904,"about_ca_system_score_gemma":0.0001324287,"threshold_uncertainty_score":0.002821982},"labels":[],"label_agreement":null},{"id":"W2019323033","doi":"10.1016/s0010-4485(03)00044-7","title":"Mechanistic modelling of the milling process using an adaptive depth buffer","year":2003,"lang":"en","type":"article","venue":"Computer-Aided Design","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Innovation Trust","keywords":"Buffer (optical fiber); Machining; Process (computing); Rendering (computer graphics); Computation; Computer science; Graphics; Acceleration; Enhanced Data Rates for GSM Evolution; Mechanical engineering; Engineering; Algorithm; Computer graphics (images); Artificial intelligence; Physics","score_opus":0.08937894858519509,"score_gpt":0.2532837282242138,"score_spread":0.16390477963901873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019323033","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23147787,0.00075374614,0.7545767,0.00029696347,0.00006961808,0.00012821,0.00034099296,0.00037435238,0.011981487],"genre_scores_gemma":[0.9610031,0.0006236758,0.034713168,0.000029018654,0.000009639838,0.00008510385,0.00008426307,0.0000338951,0.0034180854],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987185,0.000020629817,0.000009313125,0.000030820822,0.000049024864,0.000018353547],"domain_scores_gemma":[0.9997975,0.000104783256,0.000037037367,0.000018816223,0.00003019813,0.000011642184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036263035,0.00047889035,0.00051651767,0.0003893143,0.00033333563,0.0010160572,0.0014554703,0.0010569189,0.0024587486],"category_scores_gemma":[0.0007477568,0.00055592274,0.000456498,0.0005056503,0.00058080925,0.0013983427,0.0006427284,0.0005835879,0.00024273082],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003317654,0.000029091161,0.00024920094,0.000036097143,0.0000063498196,0.000029384742,0.000021113488,0.9849236,0.0073097902,0.0046761488,0.000041668896,0.002644395],"study_design_scores_gemma":[0.0000090860985,0.000012408653,0.00012202762,0.0000017644824,0.000003468306,0.0000090050535,0.0000031767618,0.9978136,0.0012373175,0.00062492205,0.0001581702,0.000004996366],"about_ca_topic_score_codex":0.0040543494,"about_ca_topic_score_gemma":0.0030780563,"teacher_disagreement_score":0.0040543494,"about_ca_system_score_codex":0.00077929924,"about_ca_system_score_gemma":0.0010651276,"threshold_uncertainty_score":0.008225322},"labels":[],"label_agreement":null},{"id":"W2019767413","doi":"10.1016/j.wear.2008.04.052","title":"Diffusion wear mechanism during high-speed machining of 7475-T7351 aluminum alloy with carbide end mills","year":2008,"lang":"en","type":"article","venue":"Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Materials science; Tungsten carbide; Metallurgy; Eutectic system; Machining; Alloy; Carbide; High-speed steel; Brittleness; Cobalt; Aluminium; Cemented carbide; Composite material","score_opus":0.004833488937412875,"score_gpt":0.17603918612962471,"score_spread":0.17120569719221185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019767413","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998546,0.00018565751,0.0008967654,0.0000089342975,0.000007392728,0.000005686719,0.000012967641,0.0000187594,0.00031778848],"genre_scores_gemma":[0.99928135,0.000021547256,0.00030390226,0.0000018081809,0.0000014324814,0.0000013449232,0.000011287581,0.000002160898,0.00037526348],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998097,0.000021760334,0.000008646653,0.00003457692,0.000088109184,0.000037212223],"domain_scores_gemma":[0.99938893,0.00021592871,0.00010326538,0.000071605056,0.0001770249,0.0000432356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000349948,0.0002451422,0.00046889312,0.0004850127,0.00061430037,0.00039841852,0.0005979497,0.0005128801,0.0009628499],"category_scores_gemma":[0.00066075625,0.00026544812,0.00031067213,0.00020805204,0.0004138655,0.00045830745,0.00022637782,0.00027533135,0.000089425965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040864493,0.00017229049,0.016462564,0.00031905784,0.00007409797,0.0016627148,0.0010283992,0.011883612,0.94103235,0.0008935782,0.00056448416,0.021820256],"study_design_scores_gemma":[0.00019074506,0.0027416465,0.15732372,0.000032001826,0.00011381253,0.00245499,0.0010460677,0.09007818,0.74236876,0.0005541939,0.0029943935,0.0001014745],"about_ca_topic_score_codex":0.0012226432,"about_ca_topic_score_gemma":0.0018127346,"teacher_disagreement_score":0.0012226432,"about_ca_system_score_codex":0.00034843863,"about_ca_system_score_gemma":0.00022126528,"threshold_uncertainty_score":0.0032210946},"labels":[],"label_agreement":null},{"id":"W2020145690","doi":"10.1016/j.jmatprotec.2014.01.017","title":"Adhesion phenomena in the secondary shear zone in turning of austenitic stainless steel and carbon steel","year":2014,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Materials science; Austenitic stainless steel; Metallurgy; Coating; Carbon steel; Machining; Scanning electron microscope; Adhesion; X-ray photoelectron spectroscopy; Tin; Composite material; Carbide; Tool steel; Surface roughness; Corrosion; Chemical engineering","score_opus":0.006018189065099767,"score_gpt":0.22000381928008952,"score_spread":0.21398563021498976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020145690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99799913,0.00026699583,0.00037154104,0.00001855768,0.000013645808,0.0000055499004,0.000015386646,0.000011526682,0.0012975709],"genre_scores_gemma":[0.99952507,0.000035276356,0.00005344186,0.0000045031343,0.0000025514585,0.0000014674335,0.000014895482,0.0000015076406,0.0003612166],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99990225,0.000010877952,0.0000024649612,0.000011169099,0.00003463867,0.00003845426],"domain_scores_gemma":[0.9997706,0.00008020245,0.000039256258,0.000011015881,0.00005607615,0.00004289277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010621707,0.00015747394,0.0002882979,0.0006765198,0.00050393684,0.00040861516,0.00029290805,0.00032940978,0.0019256274],"category_scores_gemma":[0.0003107222,0.00015162159,0.00020653509,0.00024305783,0.00045415506,0.00021065256,0.00015901787,0.00032908557,0.00015643635],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010669733,0.00007848408,0.0029103877,0.00008350548,0.00002524502,0.00086090976,0.000432097,0.0018493801,0.9854312,0.0017977844,0.00037245607,0.005091524],"study_design_scores_gemma":[0.000117847114,0.0015937592,0.22056267,0.000030460142,0.0000749522,0.0013982039,0.0017693959,0.05193219,0.71805376,0.0014698938,0.0029038866,0.000092881564],"about_ca_topic_score_codex":0.0025524478,"about_ca_topic_score_gemma":0.0025775812,"teacher_disagreement_score":0.0025524478,"about_ca_system_score_codex":0.00034281728,"about_ca_system_score_gemma":0.0001786995,"threshold_uncertainty_score":0.0064418316},"labels":[],"label_agreement":null},{"id":"W2020405737","doi":"10.1007/s00170-010-2980-0","title":"A cutting force model considering influence of radius of curvature for sculptured surface machining","year":2010,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Machining; Curvature; RADIUS; Radius of curvature; Surface (topology); Ball (mathematics); Enhanced Data Rates for GSM Evolution; Point (geometry); Geometry; Engineering; Principal curvature; Mechanical engineering; Structural engineering; Mathematics; Computer science; Mean curvature","score_opus":0.005014997907460116,"score_gpt":0.2426091579412869,"score_spread":0.23759416003382677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020405737","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1698464,0.0020843695,0.77817535,0.00046562494,0.00026253422,0.00017564216,0.0002889433,0.0006270038,0.048074074],"genre_scores_gemma":[0.9665707,0.00059766154,0.020492062,0.000052476305,0.00002956587,0.000094792405,0.00012935302,0.000074138086,0.011959275],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984086,0.000019763389,0.0000054563498,0.000035104335,0.00007516229,0.000023555061],"domain_scores_gemma":[0.9998048,0.000075537544,0.000026011587,0.000014682201,0.0000684228,0.000010561959],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023206402,0.0006102601,0.00089080544,0.00050014374,0.0004909987,0.0007583072,0.0012701747,0.0021954556,0.0023744092],"category_scores_gemma":[0.0005690972,0.0004119533,0.000794395,0.00050072686,0.000420802,0.0006249692,0.00029692936,0.0005060457,0.0004293466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018895922,0.00002374389,0.00018005501,0.00005805236,0.000010338846,0.00013847188,0.000033066834,0.986132,0.005067927,0.0024238261,0.00035500084,0.0055586025],"study_design_scores_gemma":[0.0000019729862,0.0000065514187,0.00007177599,0.000002042973,0.0000023458542,0.00000894678,0.0000022809993,0.9994597,0.0001922031,0.00011625887,0.00013378238,0.0000021067606],"about_ca_topic_score_codex":0.019315194,"about_ca_topic_score_gemma":0.011827234,"teacher_disagreement_score":0.019315194,"about_ca_system_score_codex":0.0006172242,"about_ca_system_score_gemma":0.000926053,"threshold_uncertainty_score":0.038405538},"labels":[],"label_agreement":null},{"id":"W2020572503","doi":"10.1007/s00500-013-0983-0","title":"RETRACTED ARTICLE: Experimental and fuzzy modelling analysis on dynamic cutting force in micro milling","year":2013,"lang":"en","type":"article","venue":"Soft Computing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":32,"is_retracted":true,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Subtractive color; Fuzzy logic; Process (computing); Computer science; Cluster analysis; Machining; Fuzzy clustering; Data mining; Engineering; Mechanical engineering; Machine learning; Artificial intelligence","score_opus":0.005624717884446579,"score_gpt":0.2264216441757648,"score_spread":0.22079692629131822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020572503","genre_codex":"editorial","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01497373,0.00692739,0.055276908,0.11076753,0.7953993,0.00009327492,0.0014183586,0.0016861507,0.013457232],"genre_scores_gemma":[0.20621769,0.010722267,0.05290843,0.04368535,0.2539969,0.00026971422,0.004532242,0.0030356746,0.42463163],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99650323,0.0004136321,0.0004481711,0.00040469528,0.0020065974,0.00022359673],"domain_scores_gemma":[0.9808652,0.0051213894,0.0004449735,0.0012738747,0.011641392,0.0006531938],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0031102276,0.0010719651,0.0013770157,0.0024945366,0.0022955146,0.0025752971,0.0037107696,0.0063522016,0.027655361],"category_scores_gemma":[0.02091449,0.0005421493,0.0011183236,0.001499822,0.0019175839,0.0032110799,0.001781372,0.0037581334,0.008703066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006681888,0.00015432025,0.0009785987,0.0008718866,0.000092830116,0.00280888,0.00037802604,0.0024905454,0.00924963,0.00955832,0.8896035,0.08314522],"study_design_scores_gemma":[0.00017845209,0.00054301193,0.0061061736,0.00036312462,0.0002853618,0.0048060506,0.0006762587,0.02391826,0.035771538,0.021350596,0.90572983,0.00027141653],"about_ca_topic_score_codex":0.0057686525,"about_ca_topic_score_gemma":0.0054175034,"teacher_disagreement_score":0.9936478,"about_ca_system_score_codex":0.0017998694,"about_ca_system_score_gemma":0.0017314752,"threshold_uncertainty_score":0.09251642},"labels":[],"label_agreement":null},{"id":"W2020854366","doi":"10.1115/1.1334864","title":"A Mechanistic Cutting Force Model for 3D Ball-end Milling","year":2000,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"End milling; Ball (mathematics); Chip; Mechanical engineering; Chip formation; Milling cutter; Enhanced Data Rates for GSM Evolution; Machining; Engineering; Geometry; Structural engineering; Computer science; Tool wear; Mathematics; Artificial intelligence","score_opus":0.007379957403397237,"score_gpt":0.21127446554317267,"score_spread":0.20389450813977544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020854366","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073809586,0.00008644782,0.98905396,0.000047455454,0.000017798257,0.00002954021,0.00006584084,0.00017458061,0.0031434328],"genre_scores_gemma":[0.67503,0.00097594,0.30908135,0.00014538948,0.000044988985,0.0005573853,0.00045290994,0.00019800177,0.013514031],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972075,0.000029137203,0.000012046052,0.00004170254,0.00017347447,0.000022790038],"domain_scores_gemma":[0.99980086,0.000070514354,0.00003546611,0.000029907158,0.00005388204,0.000009339163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040809193,0.0005519089,0.00053936674,0.00046577418,0.0003339467,0.0006772362,0.0018155159,0.001504718,0.0025279617],"category_scores_gemma":[0.0006970981,0.00044297517,0.0007572381,0.00026416607,0.0004590116,0.0010438006,0.0005896543,0.00077063753,0.0008691173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014812187,0.000028294628,0.00025290425,0.000055981116,0.00000921028,0.000089120535,0.000044690645,0.958782,0.013281322,0.014797527,0.00031028912,0.012333907],"study_design_scores_gemma":[0.0000036875301,0.0000149748175,0.00015752965,0.0000038377575,0.0000031729073,0.000038649247,0.0000037797288,0.99563676,0.00094893517,0.0015542252,0.0016276961,0.000006721524],"about_ca_topic_score_codex":0.002162895,"about_ca_topic_score_gemma":0.0019686606,"teacher_disagreement_score":0.0025279617,"about_ca_system_score_codex":0.0003882241,"about_ca_system_score_gemma":0.00059964985,"threshold_uncertainty_score":0.008456826},"labels":[],"label_agreement":null},{"id":"W2021235715","doi":"10.1115/1.4001412","title":"Identification and Compensation of Dynamic Scale Mismatches in High-Speed End Mill Boring Trajectory on CNC Machines","year":2010,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Trajectory; Compensation (psychology); Scale (ratio); Control theory (sociology); Computer science; RADIUS; Machine tool; Roundness (object); Engineering; Mechanical engineering; Physics; Artificial intelligence","score_opus":0.00394401644264389,"score_gpt":0.20838624074681597,"score_spread":0.20444222430417208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021235715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90092075,0.00009323341,0.09761615,0.00005919684,0.00001409024,0.000038405746,0.000039762363,0.0005618883,0.0006565281],"genre_scores_gemma":[0.98799175,0.000016381193,0.011763158,0.0000040178465,0.0000015036177,0.0000065960667,0.000027388112,0.000015972573,0.0001732627],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99950194,0.00009553069,0.000021854696,0.00010082116,0.0002363109,0.000043602333],"domain_scores_gemma":[0.99850583,0.0005932179,0.00028855074,0.00018795185,0.00036534198,0.00005923481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006524141,0.00041469705,0.0005142336,0.0003420186,0.00027811978,0.00037409525,0.00048378843,0.00049726985,0.00043861073],"category_scores_gemma":[0.0021548418,0.0002768821,0.00015572882,0.00043718706,0.00034209885,0.00045287606,0.00022165719,0.00036773467,0.000118989425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024660644,0.0002137371,0.020585414,0.00031227074,0.000034639947,0.0004278219,0.00053365686,0.2819715,0.5212212,0.0014327678,0.00061876443,0.17018211],"study_design_scores_gemma":[0.000040469975,0.0004560843,0.029710656,0.000010662515,0.000013850554,0.0001470959,0.00006224229,0.8229872,0.14572956,0.00025410805,0.00054933736,0.000038813363],"about_ca_topic_score_codex":0.00402351,"about_ca_topic_score_gemma":0.003749547,"teacher_disagreement_score":0.00402351,"about_ca_system_score_codex":0.0004538231,"about_ca_system_score_gemma":0.00048182832,"threshold_uncertainty_score":0.008000195},"labels":[],"label_agreement":null},{"id":"W2021283004","doi":"10.1115/1.2122987","title":"Wear of Electroplated CBN Grinding Wheels","year":2005,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":132,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"Ford Motor Company; National Science Foundation","keywords":"Materials science; Abrasive; Grinding; Grain size; Metallurgy; Electroplating; Composite material; Boron nitride; Surface roughness; Grinding wheel; Surface finish; Layer (electronics)","score_opus":0.0035117615492054055,"score_gpt":0.1941523662270368,"score_spread":0.1906406046778314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021283004","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974445,0.0003666159,0.0018598821,0.0000069163166,0.000015429217,0.000008490081,0.00006526021,0.000049136,0.00018366991],"genre_scores_gemma":[0.99597746,0.0001424158,0.0026139237,0.000009672672,0.0000027694437,0.000006150987,0.00013884925,0.000019084811,0.0010896652],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995109,0.000018966033,0.000019778623,0.00008458664,0.00029902946,0.00006669482],"domain_scores_gemma":[0.9991468,0.00020615912,0.0001670303,0.00012681572,0.00030632954,0.00004687186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038393357,0.0002916947,0.0004887443,0.0003680496,0.00025093905,0.00024739205,0.00045808597,0.000334793,0.00065412314],"category_scores_gemma":[0.0011031233,0.0002437034,0.00027929986,0.00019192166,0.00030634148,0.00021260417,0.00020786666,0.00024392028,0.00015023726],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021089579,0.000017606078,0.0024729182,0.00011184398,0.000011138706,0.00013756599,0.00007086844,0.0011687122,0.98813313,0.000026135167,0.00006928132,0.007569872],"study_design_scores_gemma":[0.000025165164,0.0007948501,0.07311299,0.000019514257,0.000029248586,0.0006007232,0.00009746405,0.013161069,0.90960073,0.000050358965,0.0024630884,0.000044731965],"about_ca_topic_score_codex":0.0037514998,"about_ca_topic_score_gemma":0.0104042245,"teacher_disagreement_score":0.0037514998,"about_ca_system_score_codex":0.0005243724,"about_ca_system_score_gemma":0.00025991345,"threshold_uncertainty_score":0.007459283},"labels":[],"label_agreement":null},{"id":"W2022392197","doi":"10.1016/j.ijmachtools.2015.03.002","title":"Chatter identification in end milling process based on EEMD and nonlinear dimensionless indicators","year":2015,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":179,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of British Columbia; National Natural Science Foundation of China","keywords":"Hilbert–Huang transform; Vibration; Nonlinear system; Frequency domain; Control theory (sociology); Dimensionless quantity; Harmonics; Machining; Spectral density; Bispectrum; Filter (signal processing); Time domain; Engineering; Acoustics; Mathematics; Computer science; Mathematical analysis; Artificial intelligence; Mechanical engineering; Mechanics; Physics","score_opus":0.009338313873965253,"score_gpt":0.25888724375472644,"score_spread":0.2495489298807612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022392197","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28012773,0.00047089477,0.7170986,0.00007698701,0.00006448093,0.00003236914,0.000026870428,0.0002551161,0.0018469905],"genre_scores_gemma":[0.97660154,0.00010595985,0.022218455,0.000010781889,0.000009462976,0.000015702688,0.000019479605,0.0000165044,0.0010020937],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997073,0.00006890795,0.000022331702,0.000069647715,0.000107843174,0.00002401751],"domain_scores_gemma":[0.99887186,0.00069843995,0.00012227477,0.000047784724,0.00022849075,0.000031103125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056455174,0.00038846972,0.0005566279,0.00051022874,0.00026396464,0.0005329133,0.0004466961,0.00050824904,0.00073060155],"category_scores_gemma":[0.0015808918,0.00018110285,0.0002863603,0.0003176202,0.0004161159,0.0007318388,0.00045293156,0.00047442922,0.00010422526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024506273,0.00027761806,0.015917718,0.0010564451,0.00017155615,0.0011922873,0.0011324342,0.48193705,0.18240443,0.009455091,0.000840733,0.30316392],"study_design_scores_gemma":[0.000007623394,0.00011231057,0.003590807,0.000013505517,0.000015943098,0.000069485344,0.00004220323,0.98455805,0.010983793,0.0003875108,0.00020196557,0.000016807277],"about_ca_topic_score_codex":0.0010993404,"about_ca_topic_score_gemma":0.0013046353,"teacher_disagreement_score":0.0010993404,"about_ca_system_score_codex":0.00020218283,"about_ca_system_score_gemma":0.00018920418,"threshold_uncertainty_score":0.0029856563},"labels":[],"label_agreement":null},{"id":"W2022584498","doi":"10.1115/1.4027676","title":"Identification of Machining Process Damping Using Output-Only Modal Analysis","year":2014,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Sandvik Coromant; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Pratt and Whitney Canada","keywords":"Machining; Modal; Vibration; Process (computing); Modal analysis; Stability (learning theory); Enhanced Data Rates for GSM Evolution; Frequency domain; Cutting tool; Mechanical engineering; Structural engineering; Materials science; Control theory (sociology); Engineering; Computer science; Acoustics; Mathematics; Mathematical analysis; Physics; Composite material","score_opus":0.007477080718816636,"score_gpt":0.24182406003067888,"score_spread":0.23434697931186224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022584498","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07203874,0.00004824999,0.92688465,0.000015284926,0.0000059384984,0.000021678956,0.000024317746,0.00036022975,0.00060100475],"genre_scores_gemma":[0.85972846,0.00007947359,0.13935529,0.000009765377,0.000006783317,0.000044309327,0.00008543339,0.000054169046,0.00063621113],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998223,0.000024668207,0.000007660972,0.000036003483,0.00009728676,0.000012195215],"domain_scores_gemma":[0.999542,0.00022105828,0.000060816023,0.000056376175,0.00011014429,0.0000097805505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032230926,0.0005162496,0.00025867662,0.00043809295,0.00017644811,0.00035468614,0.000379371,0.00029765695,0.00062064436],"category_scores_gemma":[0.0010966292,0.00021504104,0.00029385768,0.0001512688,0.00020933388,0.00050550234,0.00037488405,0.0003694135,0.00019334584],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002724466,0.00011014013,0.007096342,0.0003630618,0.00007119222,0.00011728438,0.00052879564,0.18261315,0.49344093,0.0032754433,0.0003255936,0.3117857],"study_design_scores_gemma":[0.000008895966,0.00006199405,0.00275744,0.000012686715,0.000014048686,0.000048137572,0.000019033792,0.95295054,0.04286245,0.00062920764,0.0006231797,0.000012395381],"about_ca_topic_score_codex":0.0009145914,"about_ca_topic_score_gemma":0.0015525905,"teacher_disagreement_score":0.0009145914,"about_ca_system_score_codex":0.00016817517,"about_ca_system_score_gemma":0.00022968183,"threshold_uncertainty_score":0.0020762086},"labels":[],"label_agreement":null},{"id":"W2022967382","doi":"10.1520/jte101415","title":"Sawblade Vibration Mode Shape Measurement Using ESPI","year":2008,"lang":"en","type":"article","venue":"Journal of Testing and Evaluation","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Vibration; Materials science; Mode (computer interface); Structural engineering; Acoustics; Composite material; Physics; Engineering; Computer science","score_opus":0.15008768189269464,"score_gpt":0.3185164886742071,"score_spread":0.16842880678151248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022967382","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7306962,0.0005451613,0.25740924,0.00013305512,0.000091713206,0.00009359927,0.0007651647,0.0017799557,0.008485864],"genre_scores_gemma":[0.86902404,0.000178565,0.12813637,0.000047071884,0.000009817245,0.000047316997,0.00039795446,0.00008317961,0.0020756032],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996481,0.000026671707,0.000012750762,0.000071759336,0.00022010351,0.000020638148],"domain_scores_gemma":[0.99954295,0.00012230557,0.000041731364,0.000060973398,0.00020675444,0.000025408941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029395352,0.00029284245,0.00026644737,0.00077761005,0.00015157157,0.00030255687,0.00033166952,0.00041053945,0.0024600378],"category_scores_gemma":[0.0005814728,0.00024679975,0.00017017541,0.00059471827,0.00023268751,0.00046001637,0.00034034674,0.00038356025,0.00049892545],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000104759085,0.000029574763,0.001946899,0.00007659355,0.000007188525,0.000043288732,0.000075212236,0.00055027264,0.9369899,0.00035694428,0.0005102488,0.059309058],"study_design_scores_gemma":[0.000031918247,0.00031226221,0.021456463,0.000018143715,0.000023717796,0.0003950004,0.00013500988,0.040541746,0.93294066,0.0004711131,0.003635373,0.000038571503],"about_ca_topic_score_codex":0.00052684476,"about_ca_topic_score_gemma":0.0008803059,"teacher_disagreement_score":0.0024600378,"about_ca_system_score_codex":0.00019614992,"about_ca_system_score_gemma":0.0001364695,"threshold_uncertainty_score":0.008229613},"labels":[],"label_agreement":null},{"id":"W2024017272","doi":"10.1016/j.jmapro.2013.08.005","title":"Robust prediction of chatter stability in milling based on the analytical chatter stability","year":2013,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Stability (learning theory); Control theory (sociology); Machine tool; Natural frequency; Stiffness; Enhanced Data Rates for GSM Evolution; Reliability (semiconductor); Materials science; Mechanical engineering; Computer science; Engineering; Structural engineering; Vibration; Artificial intelligence","score_opus":0.032995306401417,"score_gpt":0.2151502290780646,"score_spread":0.18215492267664762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024017272","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.076819025,0.0002469217,0.92105985,0.000108611726,0.00006044778,0.000026544685,0.00002740434,0.00028612078,0.0013649754],"genre_scores_gemma":[0.98325825,0.0000894061,0.01561317,0.000018089271,0.000016465052,0.00002661899,0.000024349414,0.000029148021,0.00092443055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997029,0.0000834579,0.000014460642,0.00007156419,0.00009841859,0.000029179033],"domain_scores_gemma":[0.99821186,0.001204068,0.0001482731,0.00007880089,0.00031766333,0.000039245846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009370249,0.00066949404,0.00088226,0.00037040212,0.00031894655,0.0007167496,0.00072195486,0.0006508255,0.0008655277],"category_scores_gemma":[0.0035991508,0.00038710525,0.00046310414,0.00021145387,0.0006950963,0.0007098422,0.0005965883,0.0010486181,0.00015212555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015019788,0.000026454016,0.000573696,0.00006986981,0.000033228334,0.00006118286,0.00005681394,0.97633535,0.006708804,0.00365708,0.00024247749,0.012084921],"study_design_scores_gemma":[0.0000010890337,0.000007107381,0.000044421264,8.959155e-7,0.0000011481281,0.0000016611768,7.5569227e-7,0.99941576,0.00034231893,0.00017154684,0.0000119111855,0.0000015187065],"about_ca_topic_score_codex":0.005100953,"about_ca_topic_score_gemma":0.0027233697,"teacher_disagreement_score":0.005100953,"about_ca_system_score_codex":0.00052219245,"about_ca_system_score_gemma":0.00060144026,"threshold_uncertainty_score":0.010142565},"labels":[],"label_agreement":null},{"id":"W2024301145","doi":"10.4028/www.scientific.net/msf.800-801.852","title":"Micro Ball End Milling of Nickel-Based Alloy for Laval Nozzle","year":2014,"lang":"en","type":"article","venue":"Materials science forum","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Nozzle; Ball (mathematics); Materials science; End milling; Machining; Mechanical engineering; Spray nozzle; Milling cutter; Residual; Alloy; Metallurgy; Engineering; Geometry; Computer science","score_opus":0.006713381204833125,"score_gpt":0.22749933799566058,"score_spread":0.22078595679082746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024301145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8418316,0.0012159882,0.14640594,0.00013289947,0.00009152978,0.00009617428,0.000145361,0.00054818316,0.009532366],"genre_scores_gemma":[0.95573014,0.0001408117,0.042496063,0.000007459409,0.000004425353,0.000015064785,0.00004178956,0.000017635848,0.0015465958],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981755,0.000009220657,0.000008430566,0.000028331939,0.00011874563,0.000017752007],"domain_scores_gemma":[0.99984396,0.000035720495,0.000040485116,0.000025721492,0.0000436729,0.000010437516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018998985,0.00012577379,0.00031342875,0.00013048842,0.00020576928,0.00034824005,0.00040348884,0.0002728738,0.00063532323],"category_scores_gemma":[0.0002940432,0.0001389979,0.0003279349,0.00012955978,0.00020391848,0.00025157363,0.00017207189,0.00014528913,0.00015449649],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014185073,0.000028330374,0.0014957746,0.00024246181,0.000010014602,0.00032188525,0.000114745686,0.027899535,0.94752955,0.0022665835,0.00042107535,0.019528171],"study_design_scores_gemma":[0.00007034252,0.00077958626,0.008069823,0.000024370727,0.000018495468,0.00059488835,0.00007124632,0.31862548,0.6633243,0.0006807893,0.0076855607,0.00005502697],"about_ca_topic_score_codex":0.00090400386,"about_ca_topic_score_gemma":0.0014345004,"teacher_disagreement_score":0.00090400386,"about_ca_system_score_codex":0.00034833053,"about_ca_system_score_gemma":0.00038110185,"threshold_uncertainty_score":0.0025272965},"labels":[],"label_agreement":null},{"id":"W2024475804","doi":"10.1016/s0007-8506(07)60373-4","title":"Effects of Edge Preparation and Feed when Hard Turning a Hot Work Die Steel with Polycrystalline Cubic Boron Nitride Tools","year":2006,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Boron nitride; Residual stress; Materials science; Enhanced Data Rates for GSM Evolution; Surface integrity; Machining; Die (integrated circuit); Ultimate tensile strength; Finite element method; Metallurgy; Composite material; Crystallite; Work (physics); Structural engineering; Mechanical engineering; Engineering","score_opus":0.01051980813065391,"score_gpt":0.22809512584020186,"score_spread":0.21757531770954797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024475804","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966659,0.00043032455,0.0012147189,0.00003850162,0.000054400378,0.000007874209,0.000062095074,0.00012501131,0.0014011542],"genre_scores_gemma":[0.9986166,0.000102120845,0.0006446725,0.000013262254,0.0000072536827,0.0000028743518,0.00004787257,0.000049693084,0.0005155378],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99961275,0.000048655937,0.000023644563,0.00006711543,0.0000890237,0.00015895258],"domain_scores_gemma":[0.99732333,0.0014732258,0.00047401045,0.00016305722,0.0003509257,0.00021547913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042045274,0.000517629,0.00063521543,0.00042340864,0.00071825803,0.0011542651,0.0005566128,0.0008618605,0.002426382],"category_scores_gemma":[0.0022538858,0.00055026927,0.00034663806,0.0004267689,0.0005131441,0.0007653554,0.00036528643,0.0005807915,0.00034494232],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011606768,0.0003372226,0.0034700981,0.00038189263,0.00008476017,0.00057215657,0.0003476295,0.010506857,0.9558752,0.0003635801,0.0004482885,0.016005514],"study_design_scores_gemma":[0.00008660072,0.002316179,0.007112174,0.000022039892,0.00012280142,0.00010373411,0.00021627183,0.006707307,0.9825829,0.000070011454,0.00062518916,0.000034805344],"about_ca_topic_score_codex":0.0020362148,"about_ca_topic_score_gemma":0.004208214,"teacher_disagreement_score":0.002426382,"about_ca_system_score_codex":0.000606106,"about_ca_system_score_gemma":0.00054438424,"threshold_uncertainty_score":0.00811708},"labels":[],"label_agreement":null},{"id":"W2024485013","doi":"10.1115/1.1347034","title":"Geometric Simulation of Ball-End Milling Operations","year":2000,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Ball (mathematics); Machining; End milling; Computer science; Mechanical engineering; Numerical control; Engineering drawing; Engineering; Geometry; Mathematics","score_opus":0.006766465794684741,"score_gpt":0.22022593159331766,"score_spread":0.21345946579863292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024485013","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31653517,0.00013803017,0.6432899,0.0001802988,0.00007751945,0.0003022443,0.0014389304,0.003224596,0.03481326],"genre_scores_gemma":[0.8330799,0.00016685072,0.15748483,0.00005814403,0.000012549334,0.0003282396,0.001186821,0.00041662564,0.0072660395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971753,0.000038228227,0.0000151244385,0.000038695493,0.0001570152,0.000033256176],"domain_scores_gemma":[0.9995505,0.0001553858,0.00005786675,0.000109192944,0.00011092951,0.000016071253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002463702,0.00038427082,0.00040572227,0.00034223372,0.00033489038,0.00045397502,0.0013688678,0.00077136885,0.0040887087],"category_scores_gemma":[0.00082040805,0.00025379125,0.00039672002,0.00034791237,0.00031886992,0.0004559902,0.00036209417,0.00042820213,0.0009616613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007328816,0.000034940746,0.0006884435,0.000050226652,0.0000068086747,0.00014167462,0.00007072171,0.9674963,0.015549545,0.005655828,0.00061000534,0.009622213],"study_design_scores_gemma":[0.000008263189,0.00003366261,0.00026688442,0.0000016364678,0.000001748609,0.000035826146,0.000008455298,0.9902678,0.0069772108,0.00056300143,0.0018286605,0.0000069205134],"about_ca_topic_score_codex":0.0034833269,"about_ca_topic_score_gemma":0.0022542858,"teacher_disagreement_score":0.0040887087,"about_ca_system_score_codex":0.00042775722,"about_ca_system_score_gemma":0.0004938191,"threshold_uncertainty_score":0.013678074},"labels":[],"label_agreement":null},{"id":"W2026510543","doi":"10.1016/j.ijmachtools.2013.01.006","title":"Stability of lateral, torsional and axial vibrations in drilling","year":2013,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Machine Tool Technologies Research Foundation","keywords":"Drilling; Deflection (physics); Torsional vibration; Vibration; Instability; Torsion (gastropod); Structural engineering; Engineering; Mechanics; Mechanical engineering; Physics; Acoustics; Classical mechanics","score_opus":0.007500005513805349,"score_gpt":0.22661229168943745,"score_spread":0.2191122861756321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026510543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9623985,0.0003736741,0.032465186,0.00014475804,0.000029273106,0.000010183071,0.00004643994,0.000036116824,0.0044959504],"genre_scores_gemma":[0.9987789,0.00003128231,0.00042694793,0.0000044480653,0.00000603437,0.0000034845277,0.0000140966395,0.000007874237,0.0007269856],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987626,0.000034895358,0.000005724541,0.000019933012,0.00004237292,0.000020878224],"domain_scores_gemma":[0.99898833,0.000677149,0.00009516516,0.000026910335,0.00013795913,0.000074511714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003483709,0.0001936551,0.00022302964,0.00040968735,0.00037596977,0.0004640447,0.00022233027,0.00036769328,0.0017064787],"category_scores_gemma":[0.002009424,0.00017667438,0.00018136777,0.00018437151,0.00077360414,0.00042063874,0.00041523777,0.00030572645,0.00016707632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00352328,0.0002966005,0.04571733,0.0002933598,0.00015187683,0.0011829145,0.0012694389,0.58573127,0.23541567,0.055244002,0.0019291837,0.06924503],"study_design_scores_gemma":[0.0000362681,0.00015254985,0.021938974,0.000017223116,0.000012538677,0.00023998317,0.00026914236,0.9606009,0.006565676,0.00973721,0.00038971004,0.000039756433],"about_ca_topic_score_codex":0.0010641271,"about_ca_topic_score_gemma":0.0010168101,"teacher_disagreement_score":0.0017064787,"about_ca_system_score_codex":0.00020074617,"about_ca_system_score_gemma":0.00021678866,"threshold_uncertainty_score":0.005708754},"labels":[],"label_agreement":null},{"id":"W2028553492","doi":"10.1177/0954405414563420","title":"Belt grinding process with force control system for blade of aero-engine","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Grinding; Machining; Abrasive; Mechanical engineering; Surface roughness; Process (computing); Grinding wheel; Materials science; Control theory (sociology); Engineering; Computer science; Composite material; Control (management)","score_opus":0.007690221109199252,"score_gpt":0.20152689993768808,"score_spread":0.19383667882848882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028553492","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20554784,0.00095410366,0.78270346,0.00016597126,0.0002287764,0.00035860718,0.00014137395,0.003280299,0.0066195806],"genre_scores_gemma":[0.9175651,0.00021201618,0.07813257,0.000027659073,0.00002173716,0.00009765463,0.0001284056,0.00002225067,0.003792585],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999701,0.000019224186,0.00002366777,0.00007112072,0.00016580278,0.00001912619],"domain_scores_gemma":[0.9998356,0.000023064365,0.000028278784,0.000023247834,0.000079373676,0.000010416327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031251065,0.00051580055,0.0003347726,0.00028959318,0.0004181195,0.0003346756,0.0007834585,0.0004419376,0.0017698895],"category_scores_gemma":[0.00042206107,0.0002013166,0.0002940757,0.00022229234,0.00021358472,0.00036910706,0.0001926306,0.00025351578,0.0003356276],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006366529,0.00022832643,0.0037689388,0.0007475281,0.000036329362,0.0005506465,0.00045212428,0.06413382,0.6751397,0.0038226964,0.0019602044,0.24852307],"study_design_scores_gemma":[0.00028172505,0.001317223,0.009232892,0.000035119392,0.00007076393,0.00076214696,0.0000561254,0.80596524,0.16588284,0.0012806637,0.01502892,0.00008632077],"about_ca_topic_score_codex":0.003189548,"about_ca_topic_score_gemma":0.0026370876,"teacher_disagreement_score":0.003189548,"about_ca_system_score_codex":0.00035333904,"about_ca_system_score_gemma":0.0004381669,"threshold_uncertainty_score":0.006341934},"labels":[],"label_agreement":null},{"id":"W2028798335","doi":"10.4028/www.scientific.net/kem.389-390.1","title":"Prediction of Grinding Force Distribution in Wheel and Workpiece Contact Zone","year":2008,"lang":"en","type":"article","venue":"Key engineering materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Grinding; Materials science; Tungsten carbide; Contact force; Mechanics; Abrasive; Normal force; Power (physics); Transient (computer programming); Diamond; Resultant force; Composite material; Classical mechanics; Physics","score_opus":0.0089042847688743,"score_gpt":0.17939709154164618,"score_spread":0.17049280677277187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028798335","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45922798,0.00008100244,0.53802854,0.000017041213,0.000007717709,0.000041447267,0.00017264854,0.0014356616,0.0009879813],"genre_scores_gemma":[0.9586989,0.000039697774,0.040375873,0.0000023285527,0.0000019685613,0.000023214543,0.00015229877,0.000045684188,0.00066001934],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986887,0.0000047756735,0.000003178264,0.00002812926,0.00008144891,0.000013540168],"domain_scores_gemma":[0.9996952,0.00013442349,0.00004992717,0.000027044212,0.000073558665,0.00001990116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016100942,0.00040048853,0.00034269635,0.00055648974,0.0001501217,0.00026288218,0.00049872027,0.00042441665,0.00067779794],"category_scores_gemma":[0.00058400416,0.00028251472,0.00021834031,0.00028048066,0.00014270048,0.00030925393,0.00011342555,0.00027995944,0.00019065369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026559658,0.00015061391,0.0334638,0.000097968776,0.00003378131,0.00042232274,0.00014410245,0.6204879,0.22458403,0.0008663493,0.00058097555,0.11890262],"study_design_scores_gemma":[0.000007765433,0.000029077626,0.009340978,0.0000015543505,0.0000033272408,0.000043102995,0.000008325091,0.966208,0.024028309,0.00010831566,0.00021414434,0.0000070914757],"about_ca_topic_score_codex":0.007231541,"about_ca_topic_score_gemma":0.00907029,"teacher_disagreement_score":0.007231541,"about_ca_system_score_codex":0.00057276076,"about_ca_system_score_gemma":0.00051163964,"threshold_uncertainty_score":0.014378905},"labels":[],"label_agreement":null},{"id":"W2029603595","doi":"10.1016/s0007-8506(07)60647-7","title":"High Speed Face Milling of a Aluminium Silicon Alloy Casting","year":2004,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Shandong Academy of Sciences","keywords":"Materials science; Aluminium; Machining; Metallurgy; Microstructure; Alloy; Tool wear; Finite element method; Silicon carbide; Die (integrated circuit); Engineering; Structural engineering","score_opus":0.024379621158017343,"score_gpt":0.260193542896463,"score_spread":0.23581392173844568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029603595","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94882774,0.0005437788,0.030122673,0.00009167351,0.00012138281,0.000045484492,0.00012770818,0.00035134205,0.01976827],"genre_scores_gemma":[0.9691936,0.00011477099,0.021290366,0.000014407806,0.000012370762,0.0000075199882,0.00009914942,0.000056840152,0.009211012],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998574,0.0000058304554,0.0000046302953,0.000020955948,0.00008462984,0.000026478825],"domain_scores_gemma":[0.9998204,0.00003694515,0.00002157733,0.000043175878,0.00006052822,0.000017346918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019938093,0.00020749496,0.00047294525,0.0003880352,0.00052075426,0.0006866614,0.00025064516,0.00043631982,0.0036507153],"category_scores_gemma":[0.00027071344,0.00024331242,0.00030648813,0.00031073668,0.00023100969,0.00021679816,0.00018830055,0.0004975375,0.0006536358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044354616,0.00006895892,0.000753651,0.000106254,0.000012382652,0.00021803527,0.00014425334,0.009652945,0.93790317,0.0015363054,0.00064042344,0.048520066],"study_design_scores_gemma":[0.000058329708,0.0012880963,0.013992244,0.000022676893,0.000042089836,0.0003855037,0.00017409254,0.06246699,0.9115167,0.0008020432,0.009218951,0.000032223972],"about_ca_topic_score_codex":0.0013889518,"about_ca_topic_score_gemma":0.003269335,"teacher_disagreement_score":0.0036507153,"about_ca_system_score_codex":0.00033961993,"about_ca_system_score_gemma":0.0007243952,"threshold_uncertainty_score":0.0122128725},"labels":[],"label_agreement":null},{"id":"W2029826950","doi":"10.1115/imece2014-36494","title":"Chaotic Tool Wear During Machining of Titanium Metal Matrix Composite (TiMMCs)","year":2014,"lang":"en","type":"article","venue":"Volume 2B: Advanced Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Tool wear; Machining; Materials science; Chaotic; Titanium alloy; Lyapunov exponent; Tribology; Composite number; Matrix (chemical analysis); Cutting tool; Composite material; Metallurgy; Computer science; Alloy","score_opus":0.0029835466385993363,"score_gpt":0.20093412388362109,"score_spread":0.19795057724502174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029826950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99639684,0.00009436339,0.0032041187,0.000008885437,0.000004396077,0.0000049264168,0.000014138286,0.000023844494,0.0002485976],"genre_scores_gemma":[0.99923146,0.000015954434,0.00064840616,0.0000011988933,6.896658e-7,0.000001428503,0.000006930452,0.000001563103,0.00009234938],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99988735,0.00001196638,0.000005544409,0.000020801881,0.000048683272,0.00002565837],"domain_scores_gemma":[0.9997507,0.000110156456,0.000061830135,0.000025769963,0.00003651828,0.000015121263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001921782,0.000136638,0.00016028486,0.00027595364,0.00013643515,0.00018319898,0.00016172475,0.00019126383,0.0002779109],"category_scores_gemma":[0.00048482692,0.00008022222,0.00020090798,0.00015067024,0.00022378647,0.00015298072,0.00011841826,0.00015770445,0.000029001683],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052339444,0.00008137619,0.01488875,0.0002958383,0.00003976449,0.0012042987,0.00072662596,0.08874406,0.86290914,0.00077483966,0.00023250507,0.029579427],"study_design_scores_gemma":[0.000018860715,0.0011042826,0.058787443,0.00001993377,0.000026897622,0.0006216052,0.00037217524,0.5624599,0.3748067,0.00055277755,0.0011783313,0.0000510998],"about_ca_topic_score_codex":0.0010734177,"about_ca_topic_score_gemma":0.0015469791,"teacher_disagreement_score":0.0010734177,"about_ca_system_score_codex":0.0002196118,"about_ca_system_score_gemma":0.00009855716,"threshold_uncertainty_score":0.0021343231},"labels":[],"label_agreement":null},{"id":"W2030100924","doi":"10.1016/j.cirp.2013.03.034","title":"Generalized dynamic model of metal cutting operations","year":2013,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Rake; Point (geometry); Enhanced Data Rates for GSM Evolution; Stability (learning theory); Vibration; Cutting tool; Set (abstract data type); Machine tool; Mechanical engineering; Engineering; Face (sociological concept); Computer science; Mathematics; Geometry; Artificial intelligence; Acoustics; Physics","score_opus":0.02474879329744417,"score_gpt":0.27600024236416004,"score_spread":0.25125144906671587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030100924","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06822329,0.0017588701,0.8672019,0.0014810867,0.00038919586,0.00008685641,0.0008153388,0.0003091167,0.05973433],"genre_scores_gemma":[0.9183093,0.0014722345,0.018625924,0.00026566733,0.00017673781,0.00021064976,0.000617281,0.00012578903,0.060196426],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960774,0.000113096045,0.0000136893805,0.00009375589,0.00010214961,0.00006964078],"domain_scores_gemma":[0.99965334,0.00013233139,0.000059620386,0.000025521815,0.00008807465,0.000041161944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053405133,0.0012612368,0.0017826706,0.0009861764,0.0005419964,0.0020570485,0.002247258,0.0024077238,0.0073903054],"category_scores_gemma":[0.0012149949,0.00073545927,0.001042747,0.0012195173,0.0015645339,0.0015499413,0.0011857107,0.0014012093,0.0012013047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016218222,0.00001604665,0.000092823466,0.000029253837,0.000018084385,0.0000554983,0.0000245999,0.9668902,0.0004244141,0.030027341,0.0005064528,0.0018990694],"study_design_scores_gemma":[0.0000054318343,0.0000067482847,0.00006406161,0.0000027580488,0.0000048421743,0.00000794301,0.0000066078915,0.9921292,0.000027857935,0.0074126828,0.0003261036,0.000005704072],"about_ca_topic_score_codex":0.018105535,"about_ca_topic_score_gemma":0.011285381,"teacher_disagreement_score":0.018105535,"about_ca_system_score_codex":0.0013550686,"about_ca_system_score_gemma":0.0013402062,"threshold_uncertainty_score":0.03600031},"labels":[],"label_agreement":null},{"id":"W2030236369","doi":"10.1115/1.2948384","title":"Theoretical and Experimental Studies of Chatter in Turning for Uniform and Stepped Workpieces","year":2008,"lang":"en","type":"article","venue":"Journal of vibration and acoustics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Modal; Modal analysis; Timoshenko beam theory; Equations of motion; Engineering; Vibration; Beam (structure); Coupling (piping); Structural engineering; Natural frequency; Finite element method; Mechanical engineering; Acoustics; Classical mechanics; Physics; Materials science","score_opus":0.014929637535411908,"score_gpt":0.2791943960497472,"score_spread":0.2642647585143353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030236369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.965376,0.00023767263,0.03288431,0.000016142714,0.000011760719,0.000040031635,0.000038046775,0.00019965698,0.0011964211],"genre_scores_gemma":[0.99706215,0.000035829624,0.002659041,0.000002218486,0.0000012251913,0.000009434012,0.000016437416,0.000006742403,0.00020697841],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995358,0.00006195955,0.000019964247,0.000058821566,0.00026482544,0.00005849219],"domain_scores_gemma":[0.9958332,0.003085681,0.00021071674,0.00029133537,0.000489861,0.00008924095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008772714,0.00027201918,0.00032164162,0.000566963,0.0003024193,0.00033026826,0.0008789569,0.00043940856,0.0017008965],"category_scores_gemma":[0.003735445,0.00027425302,0.000315963,0.00021454686,0.0008254718,0.00042802273,0.0002922322,0.0003979025,0.00014278296],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001343559,0.00027958665,0.008338562,0.00068968034,0.00004757533,0.0007719201,0.0017607079,0.07071902,0.8797167,0.0018870956,0.00018628057,0.034259237],"study_design_scores_gemma":[0.000062284955,0.0021762382,0.024346363,0.000056453056,0.000042999596,0.00039791246,0.0005836437,0.32460418,0.6464369,0.00054495817,0.00067533477,0.0000726868],"about_ca_topic_score_codex":0.0008695829,"about_ca_topic_score_gemma":0.0010194416,"teacher_disagreement_score":0.0017008965,"about_ca_system_score_codex":0.0003400103,"about_ca_system_score_gemma":0.00014320127,"threshold_uncertainty_score":0.005690098},"labels":[],"label_agreement":null},{"id":"W2030254167","doi":"10.1007/s00170-014-5758-y","title":"Analytical modelling of slot milling exit burr size","year":2014,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rake angle; Abrasion (mechanical); Materials science; Work (physics); Mechanics; Range (aeronautics); Enhanced Data Rates for GSM Evolution; Machining; Mechanical engineering; Composite material; Engineering; Metallurgy; Physics","score_opus":0.009875775781508271,"score_gpt":0.23236132127622838,"score_spread":0.2224855454947201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030254167","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16681905,0.0011358557,0.7873612,0.00028676412,0.00008691405,0.00010713789,0.0002937135,0.000894522,0.043014847],"genre_scores_gemma":[0.96171314,0.00036881273,0.025870075,0.000023134748,0.000014617979,0.000041172785,0.00006605597,0.00010797063,0.011794954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998054,0.000027350909,0.0000063595467,0.000039616345,0.00008875626,0.00003256745],"domain_scores_gemma":[0.99942243,0.0003045554,0.00006750778,0.00004305358,0.00014698655,0.00001542541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035455546,0.0003613576,0.00047090565,0.00035259503,0.0002615367,0.0009345177,0.0010295096,0.00094641175,0.003292715],"category_scores_gemma":[0.0012722719,0.00036881847,0.0004231294,0.00034564626,0.00043302323,0.00074453355,0.00030216397,0.00036913768,0.0007105261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049774208,0.000022633993,0.00028916195,0.000075180535,0.000005933716,0.00006888041,0.000065532,0.9697314,0.014354597,0.0070610293,0.0003454781,0.007930382],"study_design_scores_gemma":[0.000002825358,0.00001169991,0.00016549452,0.0000025014413,0.0000021288981,0.000017758552,0.000006052764,0.99739045,0.0016387692,0.0003639125,0.00039507786,0.0000034687268],"about_ca_topic_score_codex":0.0035396803,"about_ca_topic_score_gemma":0.0034147515,"teacher_disagreement_score":0.0035396803,"about_ca_system_score_codex":0.0009143566,"about_ca_system_score_gemma":0.0007401497,"threshold_uncertainty_score":0.011015236},"labels":[],"label_agreement":null},{"id":"W2030286516","doi":"10.1007/s11665-009-9551-2","title":"Effects of Speeds, Materials, and Tool Rake Angles on Metallic Particle Emission During Orthogonal Cutting","year":2009,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Machining; Materials science; Rake; Particle (ecology); Nanoparticle; Particle size; Particle-size distribution; Composite material; Mechanical engineering; Metallurgy; Process engineering; Nanotechnology; Chemical engineering; Engineering","score_opus":0.00322865049506437,"score_gpt":0.18533781865811852,"score_spread":0.18210916816305414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030286516","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982432,0.00012929873,0.0012814151,0.000008896106,0.000005851164,0.0000032340388,0.000020303874,0.000020624795,0.00028714832],"genre_scores_gemma":[0.99906486,0.000058678517,0.0005170431,0.00000623819,0.0000021671572,0.0000030148947,0.000031598855,0.000018540153,0.00029786877],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977785,0.000040018745,0.0000122273495,0.000038269274,0.000054040895,0.00007763194],"domain_scores_gemma":[0.99806184,0.0015493961,0.00013540965,0.000063867046,0.0001320736,0.000057470614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004734843,0.0002379713,0.00038499758,0.0001746617,0.0003048867,0.0003722207,0.00026996492,0.00033302914,0.0013924948],"category_scores_gemma":[0.0014544852,0.00031778106,0.0002186601,0.00015502154,0.00039069753,0.0004167904,0.00026435527,0.00025943117,0.00018700013],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008782475,0.00017701108,0.0057154624,0.00016310354,0.000027823555,0.00025629438,0.00049491355,0.0041696415,0.96008366,0.00017597695,0.0002119752,0.019741701],"study_design_scores_gemma":[0.00006453554,0.0009565773,0.027123114,0.000015538417,0.000051509807,0.00019302875,0.00023830277,0.01016488,0.96037275,0.000095808646,0.0006946891,0.000029253975],"about_ca_topic_score_codex":0.00043714602,"about_ca_topic_score_gemma":0.00081970944,"teacher_disagreement_score":0.0013924948,"about_ca_system_score_codex":0.00018512017,"about_ca_system_score_gemma":0.00019207176,"threshold_uncertainty_score":0.0046583414},"labels":[],"label_agreement":null},{"id":"W2030355037","doi":"10.1016/s0890-6955(01)00045-1","title":"Mechanics and dynamics of general milling cutters.","year":2001,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":400,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"End mill; Machining; Helix angle; Ball (mathematics); Engineering; Mechanical engineering; Vibration; Parametric statistics; Surface finish; Kinematics; Geometry; Aerospace; Enhanced Data Rates for GSM Evolution; Surface roughness; Structural engineering; Materials science; Mathematics; Physics; Classical mechanics; Acoustics; Composite material","score_opus":0.005833559049368189,"score_gpt":0.22874563303873396,"score_spread":0.22291207398936577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030355037","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50027096,0.011340081,0.3527076,0.0027746323,0.00072319125,0.00015844234,0.0006016757,0.00040490302,0.13101843],"genre_scores_gemma":[0.9612683,0.0013611253,0.008759176,0.000100072626,0.00008081745,0.000051844952,0.00012276914,0.00005721183,0.028198747],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998932,0.00001765852,0.0000031453771,0.000022446533,0.00004522586,0.000018452713],"domain_scores_gemma":[0.9998677,0.000046391586,0.000030132212,0.000010534847,0.000025785273,0.000019520181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014851653,0.00029058996,0.0003437649,0.00045955396,0.00035548725,0.0008124444,0.0006134111,0.0006994588,0.0074819755],"category_scores_gemma":[0.0007141097,0.0003060315,0.0002676527,0.00023674381,0.00074845226,0.0008670094,0.00065695297,0.0004985993,0.0007302883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029577705,0.00010837285,0.003953726,0.00026481482,0.000053610915,0.00065176573,0.000525701,0.59465724,0.029217139,0.29355803,0.010441347,0.06627244],"study_design_scores_gemma":[0.00005719084,0.00009331639,0.0059634675,0.000026082065,0.000011314443,0.00041962415,0.0001532665,0.91729516,0.0015856444,0.06453129,0.009825333,0.000038417063],"about_ca_topic_score_codex":0.0017163442,"about_ca_topic_score_gemma":0.0015987463,"teacher_disagreement_score":0.0074819755,"about_ca_system_score_codex":0.00032591616,"about_ca_system_score_gemma":0.00033716136,"threshold_uncertainty_score":0.02502966},"labels":[],"label_agreement":null},{"id":"W2030774477","doi":"10.1016/s0307-904x(02)00122-1","title":"Finite element and experimental studies of diametral errors in cantilever bar turning","year":2003,"lang":"en","type":"article","venue":"Applied Mathematical Modelling","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Polytechnique Montréal","keywords":"Finite element method; Cantilever; Deflection (physics); Stiffness; Structural engineering; Engineering; Mechanical engineering; Physics; Classical mechanics","score_opus":0.028634812711883697,"score_gpt":0.2698889032928001,"score_spread":0.24125409058091637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030774477","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894855,0.00019149925,0.008934563,0.00004835279,0.000022043349,0.00001101753,0.00006747098,0.00008749716,0.0011519557],"genre_scores_gemma":[0.99743026,0.000041773546,0.0020580092,0.000004276787,0.000002032048,0.0000054921466,0.00004433813,0.000017757295,0.00039606847],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906904,0.00016317106,0.000056497312,0.00007434071,0.0005551838,0.000081795755],"domain_scores_gemma":[0.99198616,0.005260922,0.00058982667,0.0006922128,0.0013422177,0.00012866213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000967999,0.00030673284,0.00046978705,0.00052585243,0.0004237619,0.00043364367,0.00073430553,0.0008860585,0.0019608298],"category_scores_gemma":[0.0066125668,0.00036101928,0.00021544842,0.00059634954,0.00088902394,0.00049962243,0.0003927862,0.00055893126,0.00021662997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002718881,0.0008857774,0.011631133,0.0004960407,0.000037603073,0.0003352145,0.0016621352,0.11843468,0.8020636,0.005769542,0.00059106987,0.0553744],"study_design_scores_gemma":[0.0001061907,0.001423997,0.030472513,0.000051791925,0.000037836464,0.0004884055,0.00070430234,0.34825638,0.6152909,0.0010623791,0.0019986343,0.00010663327],"about_ca_topic_score_codex":0.0011726985,"about_ca_topic_score_gemma":0.0014278581,"teacher_disagreement_score":0.0019608298,"about_ca_system_score_codex":0.00039132097,"about_ca_system_score_gemma":0.00026007186,"threshold_uncertainty_score":0.00655967},"labels":[],"label_agreement":null},{"id":"W2030928743","doi":"10.1177/1077546313493919","title":"Chatter detection in milling machines by neural network classification and feature selection","year":2013,"lang":"en","type":"article","venue":"Journal of Vibration and Control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":136,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Artificial neural network; Perceptron; Artificial intelligence; Pattern recognition (psychology); Signal processing; Engineering; Feature selection; Feature extraction; Radial basis function; Noise (video); Entropy (arrow of time); Multilayer perceptron; Computer science; Noise reduction; Electronic engineering","score_opus":0.003123031739783147,"score_gpt":0.19009553928937875,"score_spread":0.1869725075495956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030928743","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1456381,0.00052279077,0.8520574,0.000078241756,0.00003006359,0.00006341694,0.000037861842,0.00077534205,0.0007967799],"genre_scores_gemma":[0.877444,0.0001694884,0.12116474,0.000030891366,0.000017960429,0.00008762029,0.00006706379,0.000029712131,0.0009884574],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994697,0.00011740845,0.000040819596,0.00011693822,0.00020505983,0.00005004108],"domain_scores_gemma":[0.99916685,0.0004808739,0.0001047643,0.00003939925,0.00018844308,0.000019624387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082239887,0.0005995267,0.00072635844,0.0007838663,0.00028785542,0.00047573296,0.0005026437,0.0005888226,0.00057657214],"category_scores_gemma":[0.0016836413,0.00026872562,0.00037280202,0.0005390795,0.00036733225,0.00045418256,0.0002806101,0.00044604807,0.00013510222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007318821,0.00018629553,0.0050823423,0.00021857665,0.00009229935,0.00025681482,0.00018356633,0.27469873,0.07047862,0.0009969,0.0006889074,0.6463851],"study_design_scores_gemma":[0.0000074880504,0.00006459153,0.0019441068,0.0000060750635,0.000010576352,0.00003341958,0.000011263719,0.98955333,0.007958361,0.00024944975,0.00015333605,0.000008033904],"about_ca_topic_score_codex":0.0027294452,"about_ca_topic_score_gemma":0.0023102192,"teacher_disagreement_score":0.0027294452,"about_ca_system_score_codex":0.00040163336,"about_ca_system_score_gemma":0.0002489029,"threshold_uncertainty_score":0.0054270625},"labels":[],"label_agreement":null},{"id":"W2031009520","doi":"10.1115/1.2383070","title":"Dynamics and Stability of Plunge Milling Operations","year":2006,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Sandvik Coromant; Canada Research Chairs; Pratt and Whitney Canada","keywords":"Vibration; Rigidity (electromagnetism); Time domain; Frequency domain; Stability (learning theory); Torque; Rigid body; Domain (mathematical analysis); Engineering; Structural engineering; Process (computing); Eigenvalues and eigenvectors; Milling cutter; Mechanical engineering; Control theory (sociology); Computer science; Machining; Mathematics; Mathematical analysis; Acoustics; Physics; Classical mechanics","score_opus":0.004714350509778671,"score_gpt":0.19825170716263538,"score_spread":0.1935373566528567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031009520","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83988655,0.00010996458,0.15173301,0.00015559504,0.000012031844,0.000038406768,0.00013125829,0.00022129092,0.0077119255],"genre_scores_gemma":[0.9961046,0.00003921536,0.0024366432,0.0000056954736,0.0000027965013,0.000022107413,0.000045913206,0.000016947046,0.001326058],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998839,0.000014442531,0.000004865157,0.000033093762,0.000044123397,0.000019561085],"domain_scores_gemma":[0.9996019,0.0001650748,0.000092952396,0.00003278435,0.00007829847,0.000028973118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017607551,0.00028049698,0.0002864709,0.0002924705,0.00034309732,0.0006165395,0.000287163,0.00040456015,0.001734388],"category_scores_gemma":[0.0012159455,0.00018655686,0.00019643646,0.00011713773,0.0004669769,0.0006498245,0.0003633082,0.0003558148,0.00032846243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034568703,0.000088579254,0.009657586,0.000060572864,0.00003282716,0.00041894405,0.00049593754,0.88293535,0.06466376,0.017231744,0.0006302232,0.023438817],"study_design_scores_gemma":[0.0000071942045,0.00003964144,0.0022533708,0.0000033399956,0.0000028845607,0.00003646539,0.00003414188,0.99276686,0.0025939592,0.0019882116,0.00026393135,0.000009998181],"about_ca_topic_score_codex":0.0022445056,"about_ca_topic_score_gemma":0.0006956119,"teacher_disagreement_score":0.0022445056,"about_ca_system_score_codex":0.00034006135,"about_ca_system_score_gemma":0.0002680355,"threshold_uncertainty_score":0.005802095},"labels":[],"label_agreement":null},{"id":"W2031144465","doi":"10.1115/1.4006768","title":"Modified Primary Shear Zone Analysis for Identification of Material Mechanical Behavior During Machining Process Using Genetic Algorithm","year":2012,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Shear (geology); Machining; Equidistant; Shear rate; Materials science; Constitutive equation; Nonlinear system; Simple shear; Shear zone; Mechanics; Algorithm; Computer science; Structural engineering; Mechanical engineering; Geology; Engineering; Finite element method; Composite material; Physics; Rheology; Metallurgy","score_opus":0.01086431085439468,"score_gpt":0.24861216901321959,"score_spread":0.2377478581588249,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031144465","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017867858,0.0000678308,0.98086435,0.000018487543,0.000009136788,0.000026057469,0.000011764572,0.00023183478,0.000902562],"genre_scores_gemma":[0.5441026,0.0001559334,0.45350036,0.000022022337,0.00000976179,0.00016871939,0.00007361004,0.000069904,0.0018969459],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982387,0.00004126889,0.000007983885,0.00003750383,0.000069963084,0.000019406623],"domain_scores_gemma":[0.9998129,0.00009460459,0.000023552402,0.000012205525,0.000051391835,0.0000053871822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044774692,0.00070241507,0.00049931556,0.0006992425,0.00028655477,0.0004391655,0.0005923954,0.00061669346,0.0011178198],"category_scores_gemma":[0.00078335026,0.0002638011,0.0005386187,0.00040231546,0.0003192103,0.00035415113,0.00025842863,0.00041753624,0.0002240181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046947272,0.000033763874,0.00075424556,0.00007499986,0.000033709788,0.000058292753,0.00008151108,0.9083401,0.02043554,0.0051064044,0.00018922114,0.0648453],"study_design_scores_gemma":[0.0000025019876,0.0000100413645,0.000120928016,0.0000018144824,0.0000034645843,0.000007831334,0.0000025278398,0.9977501,0.0015339322,0.00040175303,0.0001628132,0.0000022268446],"about_ca_topic_score_codex":0.0036578928,"about_ca_topic_score_gemma":0.002234943,"teacher_disagreement_score":0.0036578928,"about_ca_system_score_codex":0.00043142334,"about_ca_system_score_gemma":0.00075064047,"threshold_uncertainty_score":0.007273257},"labels":[],"label_agreement":null},{"id":"W2031243301","doi":"10.1115/detc2012-70207","title":"Nonlinear Oscillation of Shell Workpiece in High Speed Milling Under 1:2 Internal Resonance Condition","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Galerkin method; Nonlinear system; Shell (structure); Cantilever; Multiple-scale analysis; Parametric oscillator; Equations of motion; Nonlinear resonance; Ordinary differential equation; Resonance (particle physics); Mechanics; Chaotic; Displacement (psychology); Differential equation; Classical mechanics; Perturbation (astronomy); Mathematical analysis; Physics; Mathematics; Materials science; Structural engineering; Engineering; Computer science","score_opus":0.010307202606507214,"score_gpt":0.24320070817131215,"score_spread":0.23289350556480493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031243301","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9750762,0.00006493356,0.023858236,0.000030352621,0.0000035737312,0.000003878161,0.0000064635365,0.000022948405,0.0009332451],"genre_scores_gemma":[0.99792516,0.000027202694,0.0016969036,0.0000024415108,0.0000016076297,0.0000026376354,0.0000044626363,0.0000036058423,0.0003358738],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999554,0.000010789921,0.0000012978187,0.000011546666,0.000013318693,0.000007641406],"domain_scores_gemma":[0.99990404,0.000041180556,0.000026903374,0.0000071489044,0.000012030567,0.000008591457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013846108,0.00015975419,0.00015061005,0.00010673183,0.00015217095,0.00016013393,0.00017020704,0.00027157064,0.00030885058],"category_scores_gemma":[0.00032779362,0.00010344404,0.00014900633,0.00007388717,0.00044393414,0.00025912563,0.00018788787,0.00014724645,0.000048424314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002919895,0.00006367952,0.0071029076,0.00018860713,0.000037054953,0.001331027,0.0014724508,0.33644876,0.62661016,0.0105590345,0.00028262052,0.0156117],"study_design_scores_gemma":[0.000011833007,0.0000928845,0.0042670653,0.0000049050727,0.0000066453986,0.00014186393,0.00010082681,0.9787217,0.015490846,0.000929659,0.00021892539,0.000012814596],"about_ca_topic_score_codex":0.00060394936,"about_ca_topic_score_gemma":0.000458715,"teacher_disagreement_score":0.00060394936,"about_ca_system_score_codex":0.00011756923,"about_ca_system_score_gemma":0.00009201205,"threshold_uncertainty_score":0.0012009144},"labels":[],"label_agreement":null},{"id":"W2031399396","doi":"10.1016/j.cirp.2012.03.144","title":"Prediction of workpiece dynamics and its effects on chatter stability in milling","year":2012,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":204,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; Pratt and Whitney Canada","keywords":"Machining; Stability (learning theory); Dynamics (music); Process (computing); Task (project management); Engineering; Mechanical engineering; Control theory (sociology); Computer science; Artificial intelligence; Control (management); Physics","score_opus":0.027492019535545947,"score_gpt":0.24989125747263188,"score_spread":0.22239923793708594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031399396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87333953,0.0002462283,0.12505637,0.00009107555,0.000022179722,0.000013950141,0.000036801357,0.0002258305,0.0009680571],"genre_scores_gemma":[0.9969067,0.000032611188,0.0027994635,0.000003191698,0.0000030858416,0.0000040419704,0.000010507758,0.000009310778,0.00023097765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983776,0.000059957907,0.000007880841,0.00003638216,0.000038866692,0.000019166531],"domain_scores_gemma":[0.9954358,0.0039015294,0.00023364813,0.000113159644,0.0002410748,0.000074724165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000658909,0.0004797761,0.00047692782,0.0003218557,0.00027328698,0.0004196491,0.00042365913,0.0008120455,0.00058635755],"category_scores_gemma":[0.0038086346,0.0003406832,0.00030740554,0.00015935482,0.0004199753,0.00044486672,0.00035423622,0.0006271232,0.000096495256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035056486,0.00006914568,0.0036914644,0.000058193473,0.000016717657,0.00007380215,0.00005941536,0.9660609,0.015419347,0.00044948602,0.000092028524,0.0136590125],"study_design_scores_gemma":[0.0000020859898,0.000027905813,0.000604817,0.0000012051916,0.0000017586998,0.0000030016888,0.000001919515,0.99787736,0.0014377107,0.000032120348,0.000007919332,0.0000022991317],"about_ca_topic_score_codex":0.00421201,"about_ca_topic_score_gemma":0.0027098092,"teacher_disagreement_score":0.00421201,"about_ca_system_score_codex":0.00028644197,"about_ca_system_score_gemma":0.0002735127,"threshold_uncertainty_score":0.008374989},"labels":[],"label_agreement":null},{"id":"W2031744962","doi":"10.1007/s00170-014-5760-4","title":"A new CAD/CAM/CAE integration approach to predicting tool deflection of end mills","year":2014,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Deflection (physics); Machining; Engineering; End mill; CAD; Cantilever; Mechanical engineering; Grinding; Finite element method; Structural engineering; Moment of inertia; Engineering drawing","score_opus":0.005131427252016631,"score_gpt":0.22672593357859272,"score_spread":0.2215945063265761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031744962","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0741116,0.000524347,0.91078335,0.00011674628,0.00019305604,0.0001390923,0.00028917257,0.0023911681,0.011451492],"genre_scores_gemma":[0.6636982,0.00031101162,0.32744527,0.00008778453,0.00006680237,0.00019343129,0.00035268426,0.0002907444,0.007554139],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996517,0.000028630064,0.000014935494,0.000055198572,0.00022540904,0.00002415915],"domain_scores_gemma":[0.9995726,0.00011870102,0.000027476053,0.000051337116,0.00020945811,0.000020387492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035407633,0.0007661777,0.00084377796,0.0008553919,0.00065292977,0.0010735032,0.0013308098,0.0014913022,0.0033146907],"category_scores_gemma":[0.0010090518,0.00081025256,0.00062510924,0.00076007063,0.00032039417,0.00095652626,0.0006384261,0.0011961078,0.0008757589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006685369,0.00018810134,0.0032374414,0.00010374864,0.00006051547,0.00014648857,0.00006137368,0.8618753,0.029085182,0.0033123554,0.0012091425,0.100653425],"study_design_scores_gemma":[0.0000026367802,0.000009324105,0.00026371828,0.000002038858,0.0000026760467,0.000009775185,0.0000031161924,0.99802136,0.0011774101,0.00012762986,0.0003761682,0.000004198449],"about_ca_topic_score_codex":0.013854629,"about_ca_topic_score_gemma":0.019855104,"teacher_disagreement_score":0.013854629,"about_ca_system_score_codex":0.0005971606,"about_ca_system_score_gemma":0.0010630221,"threshold_uncertainty_score":0.027547956},"labels":[],"label_agreement":null},{"id":"W2031837549","doi":"10.1016/j.ijmachtools.2009.08.006","title":"Predicting the effect of vibration on ultraprecision machining surface finish as described by surface finish lobes","year":2009,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Machining; Vibration; Surface finish; Surface roughness; Mechanical engineering; Surface (topology); Materials science; Engineering; Engineering drawing; Composite material; Geometry; Physics; Acoustics; Mathematics","score_opus":0.004085350767663865,"score_gpt":0.23623222584875497,"score_spread":0.2321468750810911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031837549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9797401,0.00005222828,0.019563714,0.000010788054,0.000009519761,0.000004035294,0.000019828176,0.000120248544,0.00047947164],"genre_scores_gemma":[0.9987099,0.000008290288,0.0011342866,0.0000012374406,9.211554e-7,0.0000010736941,0.000013290387,0.0000050062176,0.00012595627],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99991167,0.000013369725,0.0000029078012,0.00001862533,0.00003577446,0.000017653156],"domain_scores_gemma":[0.9994105,0.00044173916,0.00004416269,0.000036670375,0.000049127037,0.000017812516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021719189,0.00025467016,0.00020865198,0.00016522259,0.00011937844,0.00027600076,0.00023759564,0.00048265097,0.00056219846],"category_scores_gemma":[0.0010147821,0.00015974323,0.00021778746,0.00013057467,0.0001625108,0.00024155478,0.000115713156,0.0002809627,0.00012111347],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006371401,0.00011198373,0.035878368,0.00005336383,0.00003188451,0.00016641032,0.00006854639,0.7758871,0.14306274,0.00035264174,0.00025246225,0.04349732],"study_design_scores_gemma":[0.000009276663,0.00015295821,0.018922107,0.0000014015274,0.000007963764,0.000022256976,0.000014872253,0.96674204,0.013989957,0.000073309224,0.000056764762,0.0000072862476],"about_ca_topic_score_codex":0.0026509885,"about_ca_topic_score_gemma":0.0030086178,"teacher_disagreement_score":0.0026509885,"about_ca_system_score_codex":0.0002058313,"about_ca_system_score_gemma":0.00014152697,"threshold_uncertainty_score":0.005271077},"labels":[],"label_agreement":null},{"id":"W2031982284","doi":"10.1115/1.2815340","title":"Virtual Five-Axis Flank Milling of Jet Engine Impellers—Part II: Feed Rate Optimization of Five-Axis Flank Milling","year":2008,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Pratt and Whitney Canada","keywords":"Deflection (physics); Control theory (sociology); Machine tool; Nonlinear system; Impeller; Torque; Mechanical engineering; Engineering; Computer science; Physics","score_opus":0.007958042509058166,"score_gpt":0.20075635996455787,"score_spread":0.19279831745549972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031982284","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2056201,0.00027798608,0.7902954,0.000051550458,0.000023339639,0.000049527156,0.00002863095,0.00029637894,0.0033569885],"genre_scores_gemma":[0.9137055,0.0001006008,0.085048616,0.000011504502,0.000004195503,0.000033938868,0.00003137342,0.000037694874,0.0010264295],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998479,0.000026077012,0.000007743053,0.000024361681,0.000074450116,0.000019395191],"domain_scores_gemma":[0.9998754,0.000045846347,0.000032763313,0.000015311021,0.000023942095,0.000006609033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032039202,0.0003957866,0.00041184868,0.00020940935,0.0001956482,0.00061294826,0.00047328777,0.00032599946,0.00074106193],"category_scores_gemma":[0.00054291514,0.00023135905,0.0003465857,0.00018699745,0.0003282289,0.0003292252,0.00030107642,0.00029688206,0.00010925679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000948743,0.00003962103,0.00053336116,0.00008282205,0.000013739818,0.00004268175,0.000046244746,0.925748,0.038313843,0.0025970978,0.00013332219,0.03235438],"study_design_scores_gemma":[0.0000095497535,0.00008437781,0.00024495105,0.0000027949566,0.000003444422,0.000012210965,0.0000061382557,0.98880506,0.010033404,0.00033428386,0.00045800384,0.0000057681614],"about_ca_topic_score_codex":0.0013134886,"about_ca_topic_score_gemma":0.0013080095,"teacher_disagreement_score":0.0013134886,"about_ca_system_score_codex":0.0003981823,"about_ca_system_score_gemma":0.0004453222,"threshold_uncertainty_score":0.0028890967},"labels":[],"label_agreement":null},{"id":"W2032584736","doi":"10.1007/s00170-014-6583-z","title":"A machining-based methodology to identify material constitutive law for finite element simulation","year":2014,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Rake angle; Constitutive equation; Finite element method; Machining; Rake; Materials science; Chip formation; Chip; Mechanical engineering; Structural engineering; Mechanics; Engineering; Metallurgy; Tool wear; Physics","score_opus":0.021207214021126977,"score_gpt":0.33102768345689065,"score_spread":0.3098204694357637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032584736","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013266983,0.000022028078,0.9970667,0.000016087555,0.000010292098,0.0000374875,0.000019760459,0.0001913976,0.0013096614],"genre_scores_gemma":[0.11996844,0.0001411585,0.8748506,0.00008200577,0.000023700286,0.00047102396,0.00023736173,0.00035768742,0.0038680967],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997489,0.000041859672,0.000013667114,0.000033888457,0.00014245833,0.000019239029],"domain_scores_gemma":[0.999574,0.00015718023,0.00003802503,0.00006232563,0.00015180868,0.000016612807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000510867,0.0006289419,0.0007292576,0.0009891037,0.0006207861,0.0007756944,0.0018634629,0.0013650963,0.0048771044],"category_scores_gemma":[0.0013306184,0.00064974657,0.0007090704,0.0006787641,0.00053428864,0.0007518034,0.0007764902,0.0012944901,0.001543905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026598193,0.00016232632,0.0005054421,0.00018068307,0.000039903338,0.00010155158,0.00009608478,0.8483352,0.028643087,0.0440403,0.0013120531,0.07655676],"study_design_scores_gemma":[0.0000033145234,0.000007843805,0.000051722873,0.0000047253357,0.0000026156504,0.00001461374,0.0000053153717,0.99567443,0.0009971196,0.0021780217,0.00105659,0.0000036934737],"about_ca_topic_score_codex":0.0026119233,"about_ca_topic_score_gemma":0.0042819194,"teacher_disagreement_score":0.0048771044,"about_ca_system_score_codex":0.00045995062,"about_ca_system_score_gemma":0.001215902,"threshold_uncertainty_score":0.01631552},"labels":[],"label_agreement":null},{"id":"W2034458339","doi":"10.1016/j.procir.2014.02.032","title":"Analysis of Friction and Burr Formation in Slot Milling","year":2014,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Enhanced Data Rates for GSM Evolution; Mechanical engineering; Materials science; Shear (geology); Engineering; Engineering drawing; Composite material","score_opus":0.004947346909165442,"score_gpt":0.201745780799997,"score_spread":0.19679843389083157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034458339","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92801225,0.00054641056,0.0699144,0.000027529317,0.000014489372,0.000023146973,0.000077523226,0.00018514904,0.0011990584],"genre_scores_gemma":[0.99249035,0.000067002344,0.007069871,0.000002809558,0.000001128727,0.0000064015812,0.000044646513,0.000011900577,0.0003058187],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981636,0.00001604153,0.000011080806,0.000041197287,0.00009142241,0.000023948127],"domain_scores_gemma":[0.9995505,0.0002781543,0.00005647874,0.000030343886,0.00006983885,0.000014660113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000326621,0.00023354031,0.00052909454,0.00056940643,0.0002639362,0.0004562363,0.00036391534,0.00047577696,0.00044576157],"category_scores_gemma":[0.0011940724,0.00022287555,0.00039636545,0.0004976905,0.00026500458,0.0003184522,0.00016941414,0.00021693132,0.000092094124],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087692315,0.00015553324,0.02986983,0.00046286418,0.000066316876,0.00083805644,0.00048653505,0.71715635,0.15821704,0.002437537,0.00052255363,0.08891041],"study_design_scores_gemma":[0.000009049762,0.00012724785,0.008963411,0.000006092579,0.000008246183,0.00009849743,0.000043445983,0.97826606,0.011889797,0.00017593695,0.00039809293,0.000014248426],"about_ca_topic_score_codex":0.0022134727,"about_ca_topic_score_gemma":0.0017644193,"teacher_disagreement_score":0.0022134727,"about_ca_system_score_codex":0.00032998598,"about_ca_system_score_gemma":0.00024245188,"threshold_uncertainty_score":0.004401207},"labels":[],"label_agreement":null},{"id":"W2034764259","doi":"10.1080/10940340008945698","title":"SIMULATION OF CHIP FORMATION IN ORTHOGONAL METAL CUTTING PROCESS: AN ALE FINITE ELEMENT APPROACH","year":2000,"lang":"en","type":"article","venue":"Machining Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Finite element method; Chip formation; Process (computing); Constitutive equation; Mechanical engineering; Machining; Lagrangian; Materials science; Cutting tool; Plane stress; Eulerian path; Applied mathematics; Structural engineering; Computer science; Engineering; Mathematics; Tool wear","score_opus":0.008881703240282802,"score_gpt":0.2560429363889306,"score_spread":0.2471612331486478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034764259","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3161922,0.00008614711,0.6748341,0.00009686408,0.000018638902,0.000053254957,0.000091105314,0.00042517934,0.008202624],"genre_scores_gemma":[0.9359557,0.00007435988,0.061489344,0.000021868249,0.0000036845702,0.000056111265,0.000074931944,0.000034527304,0.0022894172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999064,0.00002322745,0.0000045065585,0.000011530816,0.000036441994,0.000017841028],"domain_scores_gemma":[0.99978536,0.000096365686,0.000029306326,0.000027428698,0.000045679044,0.000015893645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031338123,0.00024730572,0.00037177332,0.00028706802,0.00020694116,0.00040984532,0.00051031285,0.0007172357,0.0012585201],"category_scores_gemma":[0.0005801124,0.00021955592,0.00034958855,0.00021720327,0.0005107881,0.00037162768,0.00045505402,0.00029813946,0.0001525209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018083416,0.00001911174,0.0005324741,0.000011329704,0.00000410821,0.000034959667,0.000020298467,0.9926703,0.0025408063,0.0016729214,0.00004476487,0.002430863],"study_design_scores_gemma":[0.00000258179,0.000007456742,0.000057007284,8.6150453e-7,8.944741e-7,0.000005163002,0.000003583859,0.999099,0.0005262632,0.00018759027,0.00010842488,0.0000011091336],"about_ca_topic_score_codex":0.0021104098,"about_ca_topic_score_gemma":0.0013264107,"teacher_disagreement_score":0.0021104098,"about_ca_system_score_codex":0.00026406712,"about_ca_system_score_gemma":0.00045835157,"threshold_uncertainty_score":0.004210174},"labels":[],"label_agreement":null},{"id":"W2034776775","doi":"10.1016/s0007-8506(07)61522-4","title":"A Piezo Tool Actuator for Precision Turning of Hardened Shafts","year":2002,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Actuator; Stiffness; Mechanical engineering; Engineering; Servo; Machining; Position (finance); Machine tool; Stack (abstract data type); Natural frequency; Control theory (sociology); Hinge; Acoustics; Rotary actuator; Structural engineering; Computer science; Vibration; Electrical engineering; Physics; Control (management); Artificial intelligence","score_opus":0.0356572754738922,"score_gpt":0.26844136375748767,"score_spread":0.23278408828359548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034776775","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57527494,0.0026039197,0.3994009,0.00048658648,0.00046087804,0.00014456906,0.00022308932,0.00075746165,0.020647734],"genre_scores_gemma":[0.9434591,0.00043018252,0.05019753,0.000042526644,0.000038956594,0.00002921189,0.00004495103,0.000021835358,0.005735644],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998529,0.000012108277,0.00000551936,0.000022298262,0.00009096047,0.000016295193],"domain_scores_gemma":[0.9998605,0.00005224681,0.000020442805,0.000023641698,0.000028897985,0.000014201038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016414537,0.0002011965,0.00026135024,0.00018185333,0.00031818423,0.00029334627,0.0004253393,0.00026691472,0.0018175392],"category_scores_gemma":[0.0002457757,0.0001946631,0.00013407886,0.00018614037,0.0002772337,0.00029276847,0.0003274747,0.0002742279,0.00020467116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003095843,0.000040317704,0.0007409259,0.00020158969,0.000012898497,0.00019206273,0.00008013233,0.005193972,0.8845033,0.0032897834,0.00091888075,0.10451653],"study_design_scores_gemma":[0.00020413757,0.0018575764,0.017721063,0.000057248933,0.000086541055,0.0018681239,0.00014393863,0.21028075,0.72426474,0.0031607738,0.04024347,0.00011178383],"about_ca_topic_score_codex":0.00042079677,"about_ca_topic_score_gemma":0.00093301997,"teacher_disagreement_score":0.0018175392,"about_ca_system_score_codex":0.0001420277,"about_ca_system_score_gemma":0.00028925075,"threshold_uncertainty_score":0.00608021},"labels":[],"label_agreement":null},{"id":"W2035084964","doi":"10.1115/1.3159047","title":"Chatter Stability of General Turning Operations With Process Damping","year":2009,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":148,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Sandvik Coromant","keywords":"Chip; Chip formation; Vibration; Cutting tool; Enhanced Data Rates for GSM Evolution; Machining; Machine tool; Engineering; Mechanical engineering; Stability (learning theory); Structural engineering; Control theory (sociology); Tool wear; Computer science; Acoustics; Physics","score_opus":0.006318527755168367,"score_gpt":0.22264243085526508,"score_spread":0.21632390310009672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035084964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.54758847,0.0005149312,0.44443616,0.000105256295,0.000025919728,0.000033103657,0.00006543345,0.00037057354,0.006860088],"genre_scores_gemma":[0.99699616,0.00006423151,0.0021409944,0.000005040625,0.0000036522088,0.000012094437,0.000017592722,0.000012197295,0.0007480038],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974114,0.00006311002,0.000009469261,0.000042389223,0.00010212242,0.000041817133],"domain_scores_gemma":[0.9991037,0.0005673588,0.00012072275,0.0000661035,0.00012001586,0.000021960832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005545785,0.0004395793,0.00038006908,0.00045586942,0.00020514886,0.00044357794,0.00039065842,0.00038295906,0.0008348635],"category_scores_gemma":[0.0020640327,0.00018039504,0.00041381837,0.00015146508,0.00076031114,0.00042336018,0.0003604093,0.00041629502,0.0001431715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026811153,0.00003186347,0.0026642764,0.00014459601,0.000042256142,0.00039782093,0.0005419428,0.92751575,0.035288103,0.017454073,0.00036858642,0.015282582],"study_design_scores_gemma":[0.000002443275,0.000019201632,0.00037890737,0.000002620949,0.0000024980618,0.000022519056,0.000010804896,0.997212,0.0011877998,0.0010958739,0.000061572406,0.0000037069608],"about_ca_topic_score_codex":0.0029748995,"about_ca_topic_score_gemma":0.0013890159,"teacher_disagreement_score":0.0029748995,"about_ca_system_score_codex":0.00038193475,"about_ca_system_score_gemma":0.00021806755,"threshold_uncertainty_score":0.005915165},"labels":[],"label_agreement":null},{"id":"W2035530332","doi":"10.1504/ijmr.2009.022743","title":"On-line monitoring of surface roughness in turning operations with opto-electrical transducer","year":2009,"lang":"en","type":"article","venue":"International Journal of Manufacturing Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Western University","funders":"","keywords":"Transducer; Surface roughness; Surface finish; Line (geometry); Acoustics; Vibration; Artificial neural network; Mechanical engineering; Engineering; Computer science; Materials science; Artificial intelligence; Mathematics; Physics; Composite material","score_opus":0.033964297388504594,"score_gpt":0.3615791170339878,"score_spread":0.3276148196454832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035530332","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9479676,0.00036188174,0.049382184,0.00010379542,0.000056375895,0.000029855553,0.000086765016,0.00026806348,0.001743436],"genre_scores_gemma":[0.98889416,0.000093471186,0.010013841,0.000044680535,0.000010996086,0.000009497053,0.00004956402,0.000019275629,0.0008645327],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992834,0.00009379736,0.000015012658,0.00007871241,0.0004792613,0.00004985647],"domain_scores_gemma":[0.9992986,0.00032329504,0.00012547332,0.00005733477,0.00017249933,0.000022901724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022129947,0.00023137206,0.00031586873,0.000287375,0.00015038217,0.0002922127,0.00042560598,0.0005471626,0.00071126694],"category_scores_gemma":[0.0011738926,0.00012594661,0.00015549037,0.0002515554,0.0002254961,0.00036921038,0.00024058415,0.00026856092,0.00019586884],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006368439,0.00012894663,0.012535227,0.00014556364,0.0000207728,0.0001896201,0.00018915122,0.0038452412,0.9159746,0.00014667357,0.0004360056,0.065751456],"study_design_scores_gemma":[0.00005447892,0.0016890856,0.07798137,0.000026673386,0.00007715485,0.0011311686,0.0004002588,0.12526017,0.78952533,0.00033851727,0.0034447783,0.00007103873],"about_ca_topic_score_codex":0.0005424385,"about_ca_topic_score_gemma":0.0014254379,"teacher_disagreement_score":0.00071126694,"about_ca_system_score_codex":0.0001670459,"about_ca_system_score_gemma":0.00011796384,"threshold_uncertainty_score":0.0023794174},"labels":[],"label_agreement":null},{"id":"W2035710746","doi":"10.1177/0892705705041157","title":"Effect of Friction on Cut Resistance of Polymers","year":2004,"lang":"en","type":"article","venue":"Journal of Thermoplastic Composite Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut de recherche Robert-Sauvé en santé et en sécurité du travail; École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Materials science; Composite material; Dissipation; Normal force; Coefficient of friction; Enhanced Data Rates for GSM Evolution; Microstructure; Elasticity (physics); Friction coefficient; Work (physics); Mechanics; Mechanical engineering; Computer science","score_opus":0.003049204872415722,"score_gpt":0.2160648320072122,"score_spread":0.21301562713479646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035710746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942625,0.0022181924,0.0020717564,0.000020553758,0.000014621003,0.000010758533,0.00005458155,0.000025434538,0.0013215074],"genre_scores_gemma":[0.99865437,0.00037819153,0.00042640377,0.0000053452754,0.0000031084185,0.000004166348,0.000047084497,0.000011369341,0.000469963],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995074,0.00004329842,0.000020994972,0.00008740584,0.00022082034,0.000120068355],"domain_scores_gemma":[0.9992718,0.00043684847,0.00013148086,0.000044323213,0.00008422096,0.000031296524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028152953,0.00029749607,0.0004426411,0.00050284405,0.00026150103,0.0003848528,0.0002114075,0.0002595462,0.0015676229],"category_scores_gemma":[0.0012810262,0.00017455449,0.0003532577,0.00031002177,0.00027869022,0.00047743658,0.0002527442,0.00032161496,0.00020524707],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015955478,0.00009706587,0.0032648034,0.0004040857,0.000053333235,0.00047810317,0.00020798546,0.0130329365,0.9593989,0.0005783223,0.00015229941,0.020736665],"study_design_scores_gemma":[0.000019495812,0.0011497906,0.013622056,0.000024694893,0.000056462195,0.00032060087,0.000058743655,0.018609475,0.96403706,0.00023088205,0.0018420193,0.000028739118],"about_ca_topic_score_codex":0.00036617322,"about_ca_topic_score_gemma":0.00035933545,"teacher_disagreement_score":0.0015676229,"about_ca_system_score_codex":0.00022697757,"about_ca_system_score_gemma":0.00009144628,"threshold_uncertainty_score":0.005244255},"labels":[],"label_agreement":null},{"id":"W2037264876","doi":"10.1016/s0007-8506(07)60703-3","title":"Dynamic Compensation of Spindle-Integrated Force Sensors","year":2004,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Compensation (psychology); Contact force; SIGNAL (programming language); Kalman filter; Bandwidth (computing); Engineering; Acoustics; Force dynamics; Filter (signal processing); Control theory (sociology); Mechanical engineering; Computer science; Physics; Electrical engineering; Classical mechanics","score_opus":0.013615605036533576,"score_gpt":0.2647171697418882,"score_spread":0.2511015647053546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037264876","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3905597,0.0010644181,0.59630185,0.0002844235,0.00021196491,0.00005563298,0.00014302092,0.0007954592,0.010583511],"genre_scores_gemma":[0.9685081,0.00015227472,0.027339244,0.000051877683,0.000032979235,0.000019139448,0.000082331215,0.000022262577,0.00379173],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997079,0.000027073767,0.0000064132146,0.00007156652,0.0001589759,0.000028062384],"domain_scores_gemma":[0.9996685,0.000072746836,0.00006136557,0.00002934664,0.00015482634,0.000013228651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023932355,0.00043354035,0.00032414866,0.00034145208,0.0002454879,0.00044458502,0.0006238879,0.00056659884,0.0011694356],"category_scores_gemma":[0.0007192262,0.00024619317,0.000117386866,0.00036403487,0.00017864958,0.00045435491,0.0002636563,0.00027377988,0.00028772125],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010910679,0.00012546497,0.0023366213,0.00016673529,0.000038794133,0.000112227994,0.00019986644,0.033559393,0.7196553,0.0030187818,0.0021755146,0.23752025],"study_design_scores_gemma":[0.00008929825,0.00071737194,0.013263653,0.000040757313,0.00005294062,0.00038172214,0.00006658124,0.6220632,0.35333857,0.0013201335,0.008617424,0.000048302154],"about_ca_topic_score_codex":0.0009334058,"about_ca_topic_score_gemma":0.0019948967,"teacher_disagreement_score":0.0011694356,"about_ca_system_score_codex":0.000332192,"about_ca_system_score_gemma":0.00020725986,"threshold_uncertainty_score":0.003912151},"labels":[],"label_agreement":null},{"id":"W2037283268","doi":"10.1016/j.ymssp.2013.05.002","title":"Indicators for monitoring chatter in milling based on instantaneous angular speeds","year":2013,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":115,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Angular velocity; SIGNAL (programming language); Engineering; Angular displacement; Process (computing); Mechanical engineering; Data acquisition; Rotary encoder; Time domain; Machine tool; Structural engineering; Encoder; Acoustics; Computer science; Physics; Computer vision","score_opus":0.009871735175784609,"score_gpt":0.22346939844713984,"score_spread":0.21359766327135524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037283268","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6521747,0.0013940856,0.3348486,0.000081928585,0.00035587733,0.00014854745,0.0010137049,0.0045363083,0.005446252],"genre_scores_gemma":[0.9701643,0.00017400862,0.028127862,0.000023568424,0.000050617473,0.000066116554,0.00028832842,0.000075516116,0.0010296248],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99881387,0.00017583874,0.00009847774,0.00019980532,0.00061226316,0.0000997755],"domain_scores_gemma":[0.99356294,0.0029340184,0.0014181492,0.00030906458,0.0014290905,0.00034671437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009078359,0.000971952,0.0008814441,0.0038863996,0.0003236675,0.0009857918,0.00048677385,0.00062223437,0.00152177],"category_scores_gemma":[0.0046082814,0.00026236786,0.00026458246,0.0015389001,0.00044806566,0.0006703464,0.0004735714,0.0006103639,0.00061228755],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008752945,0.0006039261,0.1284737,0.0014993107,0.00026450388,0.00055915746,0.0009987709,0.03200615,0.32480744,0.0025988896,0.0030092981,0.4964259],"study_design_scores_gemma":[0.00015878795,0.0035944923,0.2725115,0.00023413375,0.0003829296,0.0016666445,0.00057826436,0.44749144,0.26698184,0.0017417273,0.0042823283,0.00037584268],"about_ca_topic_score_codex":0.0004381788,"about_ca_topic_score_gemma":0.0006889267,"teacher_disagreement_score":0.0038863996,"about_ca_system_score_codex":0.00028644197,"about_ca_system_score_gemma":0.00020501921,"threshold_uncertainty_score":0.0050908327},"labels":[],"label_agreement":null},{"id":"W2037605786","doi":"10.1007/bf03266685","title":"Vibration Welding Quality Control using Piezoelectric Shear Stress Transducers","year":2008,"lang":"en","type":"article","venue":"Welding in the World","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MAHLE Filter Systems (Canada); Queen's University; Royal Military College of Canada","funders":"","keywords":"Welding; Solid mechanics; Materials science; Vibration; Piezoelectricity; Transducer; Structural engineering; Shear (geology); Shear stress; Mechanical engineering; Acoustics; Composite material; Engineering","score_opus":0.025709460827391274,"score_gpt":0.27194881928233205,"score_spread":0.24623935845494077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037605786","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5014371,0.00057022553,0.49398056,0.00019991481,0.000103736704,0.000023418004,0.000041811647,0.00040938746,0.0032338214],"genre_scores_gemma":[0.98628646,0.00007544844,0.012768796,0.000015198992,0.000013540455,0.0000049026107,0.000019624325,0.000022137614,0.0007938562],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99961424,0.000040677856,0.000013473558,0.00007169363,0.00023350985,0.000026299287],"domain_scores_gemma":[0.99952424,0.00014468176,0.00009872915,0.00002944579,0.00018389567,0.000019041787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003165908,0.00026492978,0.00027455387,0.00029143563,0.00017426528,0.0006000343,0.0003417916,0.00024350225,0.0005103204],"category_scores_gemma":[0.0008720455,0.00018249742,0.00016393437,0.00031672878,0.00025273673,0.0003458104,0.00035409018,0.00022340528,0.00008874136],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073317817,0.00008567034,0.008032645,0.000116477546,0.000052894145,0.000044755947,0.00016565663,0.04559422,0.73178995,0.0016797907,0.0005049819,0.21119979],"study_design_scores_gemma":[0.00014526052,0.00090408185,0.028018208,0.000014994842,0.00010636551,0.00014669624,0.00015525908,0.5830452,0.38327265,0.0021205128,0.002011308,0.000059529008],"about_ca_topic_score_codex":0.0012301579,"about_ca_topic_score_gemma":0.001478982,"teacher_disagreement_score":0.0012301579,"about_ca_system_score_codex":0.00030840628,"about_ca_system_score_gemma":0.0002612755,"threshold_uncertainty_score":0.0024460554},"labels":[],"label_agreement":null},{"id":"W2037976190","doi":"10.2495/hpsm140031","title":"Identification of material constitutive law constants using machining tests: a response surface methodology based approach","year":2014,"lang":"en","type":"article","venue":"WIT transactions on the built environment","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Constitutive equation; Finite element method; Chip formation; Mechanical engineering; Materials science; Structural engineering; Law; Computer science; Engineering; Tool wear","score_opus":0.035795683138077856,"score_gpt":0.2559970513735576,"score_spread":0.22020136823547976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037976190","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031530067,0.00016575374,0.9654935,0.000032540884,0.000009692125,0.00010611952,0.000030331845,0.00036322113,0.002268663],"genre_scores_gemma":[0.7109122,0.00042637973,0.28615934,0.000037096816,0.000019976078,0.00035692076,0.00015890111,0.00010674701,0.0018224393],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993206,0.00018026355,0.000029241235,0.00009458345,0.00033969813,0.00003565423],"domain_scores_gemma":[0.99921083,0.00039599868,0.00012231359,0.000068597175,0.00018707401,0.000015137475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086103147,0.0008120926,0.0007850115,0.001443461,0.00021545748,0.0008908568,0.00085154653,0.0011055461,0.0010257678],"category_scores_gemma":[0.0016306854,0.00043816253,0.0006745697,0.0006791448,0.0006704863,0.00071040593,0.0004270957,0.0006864517,0.00042500513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000099828016,0.0004051496,0.0026695845,0.0005581852,0.00006013586,0.00024232347,0.0002315831,0.5878222,0.18666252,0.011579782,0.0005000358,0.20916867],"study_design_scores_gemma":[0.0000053999565,0.000099024895,0.0008057565,0.0000105801455,0.000008534611,0.00005286427,0.0000269015,0.98405933,0.012886111,0.0012840991,0.0007454222,0.000015937303],"about_ca_topic_score_codex":0.0008417769,"about_ca_topic_score_gemma":0.00087459304,"teacher_disagreement_score":0.001443461,"about_ca_system_score_codex":0.0003252029,"about_ca_system_score_gemma":0.0006853689,"threshold_uncertainty_score":0.004553616},"labels":[],"label_agreement":null},{"id":"W2038184220","doi":"10.1007/s00170-013-5440-9","title":"Tool orientation optimization and location determination for four-axis plunge milling of open blisks","year":2013,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Machining; Machine tool; Orientation (vector space); Residual; Mechanical engineering; Engineering drawing; Engineering; Computer science; Geometry; Algorithm; Mathematics","score_opus":0.011138356457033543,"score_gpt":0.26705838516733427,"score_spread":0.25592002871030073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038184220","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39082155,0.00018225484,0.6047569,0.00006502731,0.000019180996,0.00007683163,0.00011688595,0.0006255479,0.003335772],"genre_scores_gemma":[0.8236198,0.000051864256,0.17447627,0.000009897191,0.0000033375973,0.000033520584,0.00013794111,0.000103751605,0.0015637024],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968326,0.000045159693,0.000018185347,0.000073977506,0.00013049945,0.000048883372],"domain_scores_gemma":[0.999493,0.00020885204,0.00008128314,0.00006319492,0.00012486822,0.000028752413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051526004,0.00074076356,0.000855751,0.0005228464,0.00046019536,0.00081584085,0.00066925795,0.0007558333,0.0016382954],"category_scores_gemma":[0.001035583,0.000536654,0.0004961932,0.00053153903,0.0003974631,0.0005828244,0.0006416313,0.00056927133,0.00037214265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009265797,0.00028584083,0.004718819,0.0002560397,0.00004137281,0.00026038097,0.0003021113,0.5887788,0.16830997,0.0030207946,0.0007746612,0.23232454],"study_design_scores_gemma":[0.00003179117,0.00017480692,0.0016734438,0.0000070133997,0.000012351786,0.000051734016,0.00008559247,0.9625277,0.034091428,0.00067753595,0.00064776716,0.000018784822],"about_ca_topic_score_codex":0.0030595819,"about_ca_topic_score_gemma":0.004077437,"teacher_disagreement_score":0.0030595819,"about_ca_system_score_codex":0.00041351395,"about_ca_system_score_gemma":0.0009623817,"threshold_uncertainty_score":0.006083548},"labels":[],"label_agreement":null},{"id":"W2038191565","doi":"10.1115/1.1559155","title":"Surface Finish Enhancement in a Turning Operation via Adaptive STR Control of the Depth of Cut","year":2003,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Control theory (sociology); Surface (topology); Vibration; Adaptive control; Process (computing); Linear-quadratic-Gaussian control; Regulator; Computer science; Engineering; Control engineering; Control (management); Mechanical engineering; Acoustics; Physics; Mathematics; Artificial intelligence; Chemistry","score_opus":0.006069119904472162,"score_gpt":0.20542505706135672,"score_spread":0.19935593715688454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038191565","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27402464,0.0002081719,0.72045565,0.00009225599,0.00004671736,0.000036905018,0.000021769269,0.00068096735,0.004432916],"genre_scores_gemma":[0.9857428,0.000054330256,0.013282104,0.000012329946,0.0000063463012,0.0000145716585,0.000009199753,0.000014935052,0.0008634628],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999056,0.000015663407,0.000002456479,0.000022778868,0.000040533047,0.000012903673],"domain_scores_gemma":[0.99988306,0.000048777638,0.000025241368,0.000010874238,0.000026382688,0.0000056590466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018643007,0.00021747123,0.00021186314,0.00011153817,0.000106172425,0.00034460868,0.00034702691,0.00024076313,0.00055303],"category_scores_gemma":[0.00030489106,0.00011123852,0.00020695002,0.00007383624,0.00025213358,0.00016659383,0.00015026635,0.00026303183,0.00011914531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034341612,0.00012968655,0.001071129,0.0001647255,0.000033338547,0.00017864062,0.00015107363,0.47068283,0.44969904,0.0034342434,0.00047045675,0.073641464],"study_design_scores_gemma":[0.000019071136,0.0002882905,0.00082209025,0.0000038548365,0.000015093966,0.000044215165,0.000011434167,0.97797024,0.019690905,0.00048965536,0.0006369307,0.000008314497],"about_ca_topic_score_codex":0.0007522208,"about_ca_topic_score_gemma":0.0009620499,"teacher_disagreement_score":0.0007522208,"about_ca_system_score_codex":0.00013487297,"about_ca_system_score_gemma":0.00016235233,"threshold_uncertainty_score":0.0018501282},"labels":[],"label_agreement":null},{"id":"W2038492394","doi":"10.1016/j.cirp.2011.03.084","title":"Mechanics of micro-milling with round edge tools","year":2011,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Sandvik Coromant","keywords":"Brass; Materials science; Strain hardening exponent; Flow stress; Enhanced Data Rates for GSM Evolution; Chip formation; Mechanics; Slip line field; Work hardening; Constitutive equation; Slip (aerodynamics); Mechanical engineering; Strain rate; Machining; Composite material; Metallurgy; Engineering; Structural engineering; Tool wear; Finite element method; Shear (geology); Physics","score_opus":0.060813066650216456,"score_gpt":0.24450146712456775,"score_spread":0.18368840047435128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038492394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5639372,0.004757786,0.3218491,0.0015135722,0.00048121298,0.00022184689,0.00019167086,0.00025156292,0.10679603],"genre_scores_gemma":[0.9748267,0.0006603134,0.009159124,0.000054860408,0.000052197014,0.000047803573,0.000033328128,0.000036091118,0.015129636],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997247,0.000040004026,0.000010430411,0.0000437179,0.00014392847,0.000037140286],"domain_scores_gemma":[0.99973494,0.00013379395,0.00004118105,0.000029586394,0.000034595574,0.000025817082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026230558,0.00031121756,0.0004657331,0.000398993,0.00057841337,0.0012790748,0.0009160247,0.0008889362,0.0038147385],"category_scores_gemma":[0.0010396754,0.00040556776,0.00034261812,0.0003495977,0.0011988453,0.0010554494,0.00079240394,0.0005870481,0.00044072012],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034422023,0.00020250278,0.0022301953,0.00029692028,0.000051372004,0.00087947136,0.0005176174,0.583759,0.06760971,0.30109137,0.0021012805,0.04091629],"study_design_scores_gemma":[0.000067676294,0.00015638315,0.0050375178,0.000020663503,0.000014540393,0.0004120615,0.00019229385,0.92279106,0.008696702,0.058365136,0.004185495,0.000060498773],"about_ca_topic_score_codex":0.00078581675,"about_ca_topic_score_gemma":0.00081823097,"teacher_disagreement_score":0.0038147385,"about_ca_system_score_codex":0.00041630256,"about_ca_system_score_gemma":0.0005178709,"threshold_uncertainty_score":0.012761533},"labels":[],"label_agreement":null},{"id":"W2039515465","doi":"10.1016/j.jsv.2006.10.041","title":"Stability analysis of doubly regenerative cylindrical grinding process","year":2007,"lang":"en","type":"article","venue":"Journal of Sound and Vibration","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Université de Sherbrooke; École de Technologie Supérieure","funders":"","keywords":"Grinding; Stability (learning theory); Control theory (sociology); Process (computing); Sensitivity (control systems); Forcing (mathematics); Engineering; Mathematics; Computer science; Mechanical engineering; Mathematical analysis","score_opus":0.017142431141161204,"score_gpt":0.28318635884671217,"score_spread":0.26604392770555096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039515465","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58361566,0.00064839335,0.39008987,0.00026844573,0.000067335364,0.00007405323,0.00007579142,0.00022564387,0.02493472],"genre_scores_gemma":[0.99527943,0.00007149753,0.002256727,0.000005744826,0.000005603181,0.000011329957,0.000018073873,0.000012311989,0.002339309],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998423,0.00003286302,0.0000048360616,0.000030516065,0.00006735862,0.000022101833],"domain_scores_gemma":[0.99974245,0.00009455237,0.000044718443,0.000018538012,0.00008867655,0.000011046446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038973687,0.0003279668,0.0004870131,0.00036603535,0.0005399236,0.0005601988,0.00054209377,0.00043409909,0.0020052572],"category_scores_gemma":[0.0006333834,0.0001745217,0.0005219765,0.00018432122,0.0005892526,0.00038019213,0.00040816335,0.0003040794,0.0002012243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005520496,0.00007798489,0.0017242546,0.0001826905,0.0000604719,0.0003533126,0.00031179294,0.8050816,0.12693949,0.041224476,0.0006374953,0.022854408],"study_design_scores_gemma":[0.0000055001015,0.00004012286,0.0005142044,0.0000018544204,0.000005161588,0.000016665892,0.00001415119,0.99530053,0.0028750657,0.0010951135,0.00012677819,0.0000049496784],"about_ca_topic_score_codex":0.003644423,"about_ca_topic_score_gemma":0.001951016,"teacher_disagreement_score":0.003644423,"about_ca_system_score_codex":0.00049043505,"about_ca_system_score_gemma":0.00055782293,"threshold_uncertainty_score":0.0072464347},"labels":[],"label_agreement":null},{"id":"W2039579632","doi":"10.1016/j.ijmachtools.2006.08.003","title":"Modeling and identification of tool holder–spindle interface dynamics","year":2006,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":144,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Stiffness; Vibration; Timoshenko beam theory; Interface (matter); Coupling (piping); Engineering; Frequency response; Mechanical engineering; Machine tool; Structural engineering; Control theory (sociology); Beam (structure); Acoustics; Computer science; Physics; Contact angle","score_opus":0.004911568589785277,"score_gpt":0.23185725333832108,"score_spread":0.2269456847485358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039579632","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12182497,0.0003463717,0.87262446,0.00011143699,0.0000379801,0.00005043989,0.000057993922,0.00031239714,0.0046338565],"genre_scores_gemma":[0.9801569,0.0001738615,0.01693094,0.000011274698,0.000007608883,0.000039943887,0.000046262998,0.000025754247,0.0026074373],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99988675,0.000021031923,0.0000061203586,0.000023804669,0.000046795943,0.000015533931],"domain_scores_gemma":[0.99978393,0.000102205515,0.000039809212,0.000018928598,0.000044273715,0.00001094171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028202464,0.0004374476,0.0005482192,0.0003531917,0.00027523816,0.0007341008,0.00082632614,0.0010671488,0.0014961475],"category_scores_gemma":[0.00084467774,0.00047541293,0.00040495585,0.000252117,0.00032269914,0.000967214,0.00051764114,0.0005376708,0.00030708217],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007211682,0.00004754486,0.0012627015,0.000059770184,0.000020542142,0.00013676482,0.00006676162,0.9534959,0.022140173,0.004235274,0.00021324128,0.018249277],"study_design_scores_gemma":[0.0000019675724,0.000005044456,0.00013572982,7.1082377e-7,0.0000012728233,0.0000063513535,0.0000022187915,0.9990688,0.000539514,0.00015610582,0.00008115386,0.0000012144798],"about_ca_topic_score_codex":0.0039820187,"about_ca_topic_score_gemma":0.0025348112,"teacher_disagreement_score":0.0039820187,"about_ca_system_score_codex":0.00035373977,"about_ca_system_score_gemma":0.0005304524,"threshold_uncertainty_score":0.007917643},"labels":[],"label_agreement":null},{"id":"W2039602296","doi":"10.1007/s00170-013-5105-8","title":"Investigation on surface finish and metallic particle emission during machining of aluminum alloys using response surface methodology and desirability functions","year":2013,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail","keywords":"Machining; Materials science; Surface roughness; Metallurgy; Tin; Surface finish; Coating; Particle (ecology); Aluminium; Mechanical engineering; Composite material; Engineering","score_opus":0.03827373256496077,"score_gpt":0.27225405422829047,"score_spread":0.2339803216633297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039602296","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99144006,0.00017726436,0.0075955465,0.000015470601,0.0000053528843,0.000011813426,0.000021031248,0.00003387169,0.0006997218],"genre_scores_gemma":[0.99708027,0.00005175902,0.0021147053,0.000005893034,0.000002027731,0.000005854651,0.000028249953,0.000013064595,0.0006982099],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998393,0.00002859153,0.0000039643937,0.000032148775,0.00007625986,0.000019683455],"domain_scores_gemma":[0.9996816,0.0001663915,0.00003667567,0.000028094235,0.000078871766,0.000008382394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023101697,0.00020504267,0.00024294775,0.00014749575,0.00018204209,0.00019021262,0.00021910336,0.00034057267,0.00055617554],"category_scores_gemma":[0.00044670844,0.00015395312,0.00025246677,0.00012207561,0.0003072863,0.00021988273,0.000110702655,0.00022292144,0.00010267788],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020368006,0.000019805888,0.0010435373,0.000041957584,0.000005595999,0.00006718578,0.00011890676,0.0006098026,0.99331385,0.00009209263,0.000025353578,0.0044583105],"study_design_scores_gemma":[0.000010425272,0.0003831427,0.018044248,0.0000027093383,0.000011925068,0.0001160771,0.0001142411,0.008930311,0.97182447,0.00004835824,0.0005049661,0.0000091658785],"about_ca_topic_score_codex":0.00071378786,"about_ca_topic_score_gemma":0.0009786381,"teacher_disagreement_score":0.00071378786,"about_ca_system_score_codex":0.0001748515,"about_ca_system_score_gemma":0.00009144035,"threshold_uncertainty_score":0.001860559},"labels":[],"label_agreement":null},{"id":"W2039935001","doi":"10.1016/s0007-8506(07)60105-x","title":"Novel Kinematics for Cylindrical Grinding of Brittle Materials","year":2005,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Grinding; Kinematics; Brittleness; Traverse; Flexural strength; Anisotropy; Materials science; Ultimate tensile strength; Population; Mechanical engineering; Structural engineering; Composite material; Engineering; Geology; Physics; Optics; Classical mechanics","score_opus":0.036861810168229626,"score_gpt":0.29571804051679734,"score_spread":0.2588562303485677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039935001","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015061558,0.00022348108,0.97886753,0.00006526398,0.00010332709,0.000064320084,0.000023771554,0.00017913012,0.005411581],"genre_scores_gemma":[0.33919147,0.00073704874,0.64756745,0.000054956123,0.0000673384,0.0001873262,0.00009755891,0.00019115319,0.011905753],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997826,0.000037618054,0.0000100711795,0.000038907718,0.00011233408,0.000018363779],"domain_scores_gemma":[0.9998646,0.00003242647,0.000029548944,0.000022214408,0.000037920687,0.000013355257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033437644,0.00065077527,0.000547509,0.0003417714,0.00031755268,0.00052565924,0.00080655457,0.00059199176,0.0031682372],"category_scores_gemma":[0.0005618535,0.0003595287,0.0004192996,0.000276795,0.00052924285,0.00056441856,0.00078630174,0.00060256483,0.00070173293],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016280734,0.00016327084,0.0008004084,0.00038331805,0.00003316955,0.00036216175,0.0002580133,0.4398613,0.15828381,0.19018586,0.002555617,0.2069503],"study_design_scores_gemma":[0.000042388987,0.0002525126,0.0005198533,0.00002349878,0.000011837359,0.0002243049,0.000040226238,0.96014166,0.01133362,0.017352507,0.010032833,0.00002477515],"about_ca_topic_score_codex":0.0006264571,"about_ca_topic_score_gemma":0.0022190993,"teacher_disagreement_score":0.0031682372,"about_ca_system_score_codex":0.00037955475,"about_ca_system_score_gemma":0.0005579835,"threshold_uncertainty_score":0.010598779},"labels":[],"label_agreement":null},{"id":"W2040566018","doi":"10.1016/j.jmatprotec.2005.05.033","title":"Computer aided classification of flaws occurred during casting of aluminum","year":2005,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor; Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Casting; Computer-aided; Identification (biology); Computer science; Engineering drawing; Engineering; Artificial intelligence; Data mining; Pattern recognition (psychology); Materials science; Mechanical engineering; Metallurgy","score_opus":0.010736237693318836,"score_gpt":0.2440540684109631,"score_spread":0.23331783071764428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040566018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96624726,0.0002535033,0.031923115,0.000020810465,0.000023465387,0.000056670167,0.00032551988,0.0007919792,0.00035764425],"genre_scores_gemma":[0.9692602,0.00009606694,0.029496387,0.0000069610105,0.000005986465,0.000012215592,0.00043767394,0.000026830345,0.00065751345],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999826,0.000016317099,0.000015759339,0.000040261846,0.00007470837,0.000026926351],"domain_scores_gemma":[0.99841726,0.0006327207,0.00023835503,0.00012573766,0.0005349733,0.000050939907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039732616,0.00043207244,0.00058092637,0.0021212718,0.00027322967,0.0004895521,0.00059823866,0.000719195,0.0007954335],"category_scores_gemma":[0.0009120578,0.00040200417,0.00029663395,0.000608748,0.0002233001,0.0002988358,0.00021053829,0.00029756982,0.00020427383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004052265,0.00034462337,0.04630004,0.00048614517,0.00012213724,0.0007350963,0.00045242422,0.027379168,0.66206706,0.00045227757,0.0011233942,0.2564853],"study_design_scores_gemma":[0.000102504266,0.0008636019,0.18437625,0.000036889225,0.00016255082,0.0014671554,0.00023487315,0.5971489,0.21385251,0.00024057856,0.0014362049,0.000077904726],"about_ca_topic_score_codex":0.0038866503,"about_ca_topic_score_gemma":0.009590208,"teacher_disagreement_score":0.0038866503,"about_ca_system_score_codex":0.00030218586,"about_ca_system_score_gemma":0.000532486,"threshold_uncertainty_score":0.00772804},"labels":[],"label_agreement":null},{"id":"W2040811668","doi":"10.1115/imece2002-33613","title":"Minimum Time Trajectory Planning Along Specified Tool Path With Consideration of Cutting Force Constraint and Feed Drive Dynamics","year":2002,"lang":"en","type":"article","venue":"Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Trajectory; Control theory (sociology); Computer science; Acceleration; Machine tool; Scheduling (production processes); Engineering; Mathematical optimization; Mechanical engineering; Mathematics; Control (management)","score_opus":0.007528537133324401,"score_gpt":0.18499782605876,"score_spread":0.1774692889254356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040811668","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025762944,0.00007180185,0.9722624,0.000029507042,0.000009143035,0.000023402752,0.00002219226,0.00020566738,0.001613053],"genre_scores_gemma":[0.6654397,0.00019677833,0.3317821,0.000022605294,0.000020422902,0.000080807054,0.00014297932,0.00008009773,0.002234573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997669,0.000043997767,0.000011329396,0.000040256244,0.00010388485,0.000033672],"domain_scores_gemma":[0.99967813,0.00012497535,0.00007215188,0.000032862263,0.00007353462,0.000018412464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027362903,0.00057781354,0.0004642062,0.00041195055,0.00025629927,0.0004129638,0.0005749223,0.00033869452,0.0009302465],"category_scores_gemma":[0.0008359581,0.00022259691,0.00026224507,0.00035316678,0.00022854436,0.0004919553,0.00021815115,0.00026195095,0.00016211336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013815315,0.000052523,0.0008520805,0.00009219762,0.000022621207,0.0000891829,0.000096627715,0.8096967,0.015796311,0.008120351,0.0005942584,0.1644491],"study_design_scores_gemma":[0.000015245869,0.00013694078,0.0003709001,0.0000059293325,0.000010324817,0.00007392278,0.000023845629,0.9902648,0.005655395,0.0018220921,0.0016119604,0.000008743652],"about_ca_topic_score_codex":0.0036607177,"about_ca_topic_score_gemma":0.003559176,"teacher_disagreement_score":0.0036607177,"about_ca_system_score_codex":0.00033241409,"about_ca_system_score_gemma":0.00097417383,"threshold_uncertainty_score":0.0072788},"labels":[],"label_agreement":null},{"id":"W2040870428","doi":"10.1115/1.1765139","title":"Multi Frequency Solution of Chatter Stability for Low Immersion Milling","year":2004,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":504,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Harmonics; Transfer function; Machining; Vibration; Stability (learning theory); Control theory (sociology); Immersion (mathematics); Natural frequency; Mechanics; Materials science; Engineering; Acoustics; Mechanical engineering; Mathematics; Physics; Mathematical analysis; Computer science","score_opus":0.011341922981776362,"score_gpt":0.22199393003776255,"score_spread":0.2106520070559862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040870428","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032541633,0.00013541871,0.9648028,0.00008167864,0.00002061999,0.000021253489,0.00001337366,0.000094294475,0.0022890035],"genre_scores_gemma":[0.87175393,0.00036601434,0.11761935,0.00006366541,0.00004287725,0.00016555999,0.000049410046,0.00009967805,0.009839457],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998264,0.000052298165,0.000006881328,0.000029026645,0.00006628342,0.000019184949],"domain_scores_gemma":[0.9990785,0.00063630345,0.00007651394,0.000038674996,0.00013798672,0.00003200737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006009507,0.0007080194,0.00062314887,0.0005357162,0.0003077554,0.0005473582,0.00056085613,0.000935037,0.0018250525],"category_scores_gemma":[0.0022185599,0.00034978508,0.00055217405,0.00019730671,0.0008365234,0.00048417918,0.0006140595,0.0009047372,0.00024018924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008621345,0.000035741825,0.00105533,0.0001918083,0.000038203394,0.00033708254,0.00043584066,0.90580434,0.018089958,0.0537217,0.00053283287,0.019670807],"study_design_scores_gemma":[0.000002773173,0.000009434891,0.00006980974,0.0000037445745,0.0000016306296,0.000010480558,0.000013595354,0.9957761,0.00054526463,0.0034265744,0.00013717053,0.000003419441],"about_ca_topic_score_codex":0.00263846,"about_ca_topic_score_gemma":0.0023891916,"teacher_disagreement_score":0.00263846,"about_ca_system_score_codex":0.00047945834,"about_ca_system_score_gemma":0.00065949076,"threshold_uncertainty_score":0.006105423},"labels":[],"label_agreement":null},{"id":"W2041202010","doi":"10.1115/1.4024038","title":"Chatter Stability Model of Micro-Milling With Process Damping","year":2013,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":113,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Finite element method; Constitutive equation; Enhanced Data Rates for GSM Evolution; Rake angle; Materials science; Slip (aerodynamics); Frequency domain; End mill; Mechanical engineering; Mechanism (biology); Structural engineering; Engineering; Mechanics; Machining; Physics; Mathematical analysis; Mathematics","score_opus":0.00814904354097878,"score_gpt":0.19688823792880786,"score_spread":0.18873919438782907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041202010","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0964498,0.00032764184,0.89728606,0.00013265907,0.000046299276,0.000045372253,0.000068632085,0.00039428804,0.0052491436],"genre_scores_gemma":[0.9808013,0.00017320548,0.013216688,0.000023450786,0.00001687662,0.000080376994,0.00005484309,0.000039127364,0.0055941446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997832,0.000035292098,0.000008227641,0.00004776961,0.00010400204,0.000021506288],"domain_scores_gemma":[0.99953866,0.00021466843,0.00007707058,0.00003494411,0.000114313734,0.00002036923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036129958,0.00058577023,0.000429025,0.0003621215,0.00026781452,0.00036893436,0.0010165975,0.0007353654,0.0014517959],"category_scores_gemma":[0.0009616947,0.00026353967,0.00048479592,0.00011485789,0.00061138254,0.0005708106,0.00037085704,0.00070571626,0.0003622689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001391584,0.000030763968,0.001178026,0.00012688425,0.000041301064,0.0003326743,0.00029251855,0.9360188,0.036055103,0.01680368,0.00037460192,0.008606391],"study_design_scores_gemma":[0.0000021940298,0.0000103596185,0.00010982602,0.0000013440927,0.0000018713916,0.000014721573,0.0000030774277,0.99853754,0.000705177,0.00052568084,0.00008601143,0.0000022075337],"about_ca_topic_score_codex":0.0032280763,"about_ca_topic_score_gemma":0.0017238582,"teacher_disagreement_score":0.0032280763,"about_ca_system_score_codex":0.00043402042,"about_ca_system_score_gemma":0.00033070022,"threshold_uncertainty_score":0.006418586},"labels":[],"label_agreement":null},{"id":"W2042284509","doi":"10.1016/s0007-8506(07)60582-4","title":"Surface Generation with Engineered Diamond Grinding Wheels: Insights from Simulation","year":2003,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Abrasive; Grinding; Offset (computer science); Surface roughness; Surface finish; Grinding wheel; Mechanical engineering; Materials science; Diamond; Computer science; Engineering; Composite material","score_opus":0.032006285299376235,"score_gpt":0.25397022462860475,"score_spread":0.2219639393292285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042284509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7071437,0.0007561154,0.23597325,0.0009938552,0.00021028522,0.00009584547,0.00023743935,0.00038484077,0.054204505],"genre_scores_gemma":[0.9876488,0.00017222104,0.009126851,0.000025824254,0.000008703305,0.000019834708,0.00004478337,0.000044446686,0.0029085884],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987304,0.00002880584,0.0000042847964,0.000017247503,0.000042768414,0.00003383399],"domain_scores_gemma":[0.99941945,0.000331573,0.000048715978,0.00005843348,0.00009139684,0.000050451024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002990165,0.00035817394,0.0008487898,0.00043121303,0.0005246428,0.00097442616,0.00091575336,0.001417184,0.0030708176],"category_scores_gemma":[0.0014627178,0.00043520267,0.0005586602,0.00035780726,0.00084694615,0.00089686754,0.0004863599,0.00053566514,0.00024748428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035085824,0.000040889856,0.0005658436,0.000026024485,0.000007397064,0.000064922344,0.00003725184,0.98188055,0.0022497606,0.012309363,0.00021702227,0.002565971],"study_design_scores_gemma":[0.000011281216,0.0000072744397,0.000106238236,0.0000014497937,0.0000015979961,0.000008044387,0.000009267029,0.99734724,0.00027946438,0.0020542613,0.00016991756,0.000003873852],"about_ca_topic_score_codex":0.011928367,"about_ca_topic_score_gemma":0.0071558673,"teacher_disagreement_score":0.011928367,"about_ca_system_score_codex":0.0009853443,"about_ca_system_score_gemma":0.00095379795,"threshold_uncertainty_score":0.02371788},"labels":[],"label_agreement":null},{"id":"W2043464967","doi":"10.1016/j.cirp.2011.03.123","title":"Predictive compliance based model for compensation in multi-pass milling by on-machine probing","year":2011,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Deflection (physics); Machine tool; Deflection angle; Compensation (psychology); Mechanical engineering; Variable (mathematics); Engineering; End milling; Control theory (sociology); Engineering drawing; Structural engineering; Computer science; Machining; Optics; Mathematics; Artificial intelligence; Physics; Mathematical analysis","score_opus":0.1491360141701295,"score_gpt":0.3110478690137052,"score_spread":0.16191185484357568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043464967","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045279574,0.000332829,0.9481015,0.0002020401,0.000096742624,0.000054311706,0.00007875403,0.0005801265,0.0052739955],"genre_scores_gemma":[0.97657794,0.00015455513,0.018369393,0.000055926852,0.00001664357,0.00008191892,0.000063731386,0.00005117445,0.0046287966],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967647,0.000076740434,0.0000131653005,0.00007540176,0.00011566924,0.000042533225],"domain_scores_gemma":[0.9995912,0.00019813847,0.00005371115,0.000038402362,0.0001065119,0.0000120148925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005300627,0.00061154686,0.0011644851,0.00029795023,0.00044269318,0.000934296,0.0012216548,0.0016232475,0.0018852466],"category_scores_gemma":[0.0011533931,0.00053548184,0.00050692336,0.00042878604,0.00059129315,0.00085536786,0.00066709414,0.0010014218,0.00030228152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006477219,0.000033442626,0.00022715559,0.000051536743,0.000012827017,0.000033232376,0.00003173757,0.9815894,0.0030316499,0.0015986295,0.0003282431,0.012997312],"study_design_scores_gemma":[0.0000019272786,0.0000071948057,0.0000617775,0.0000013197158,0.0000018564851,0.0000023682794,0.0000012047142,0.9994332,0.000280156,0.0001438942,0.00006330533,0.0000017921212],"about_ca_topic_score_codex":0.009116364,"about_ca_topic_score_gemma":0.0076737683,"teacher_disagreement_score":0.009116364,"about_ca_system_score_codex":0.0006978502,"about_ca_system_score_gemma":0.00093730073,"threshold_uncertainty_score":0.018126547},"labels":[],"label_agreement":null},{"id":"W2043916816","doi":"10.1016/j.cirpj.2013.04.001","title":"On the micro and nanoparticle emission during machining of titanium and aluminum alloys","year":2013,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Materials science; Titanium alloy; Aluminium; Titanium; Machining; Metallurgy; Alloy; Thermal; Particle (ecology); Geology","score_opus":0.004010297812765337,"score_gpt":0.19460770115906095,"score_spread":0.1905974033462956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043916816","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99419665,0.0005417382,0.0024833898,0.00004914003,0.000026748126,0.0000106610805,0.000042254673,0.00002498798,0.0026244286],"genre_scores_gemma":[0.9966118,0.00012041441,0.0006622464,0.000016442405,0.000008724422,0.000004616506,0.00005517381,0.0000149542275,0.0025055504],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998716,0.000015142315,0.0000028774373,0.000028809975,0.000056839897,0.00002474317],"domain_scores_gemma":[0.9998035,0.000111213434,0.000020773272,0.000012232981,0.00004279204,0.000009586525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018532945,0.00016860162,0.00020690821,0.0002069011,0.00028788947,0.00029307173,0.0002433725,0.00029363728,0.0015900424],"category_scores_gemma":[0.00030873486,0.00013845025,0.00025969004,0.00013621339,0.00042949273,0.000313271,0.00015958154,0.00025061457,0.00021749776],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005385997,0.00003133972,0.0011767701,0.00006412959,0.000011667991,0.00023277148,0.0002743349,0.0009817234,0.9910287,0.00029060137,0.00016930029,0.005200027],"study_design_scores_gemma":[0.000015156965,0.00023161047,0.018874306,0.000006843425,0.000016114946,0.0001964294,0.00024050627,0.008782663,0.96946377,0.00011705644,0.00204054,0.000014994546],"about_ca_topic_score_codex":0.0015977451,"about_ca_topic_score_gemma":0.0020227847,"teacher_disagreement_score":0.0015977451,"about_ca_system_score_codex":0.00041016252,"about_ca_system_score_gemma":0.00013205268,"threshold_uncertainty_score":0.0053192377},"labels":[],"label_agreement":null},{"id":"W2044900414","doi":"10.1115/1.4025415","title":"On the Optimized Design of Broaching Tools","year":2013,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Broaching; Machining; Engineering; Mechanical engineering; Engineering drawing; Computer science","score_opus":0.01343601512752023,"score_gpt":0.2027993291588892,"score_spread":0.18936331403136897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044900414","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061795376,0.0005456754,0.924335,0.00012848793,0.000028768129,0.0001052428,0.00009851041,0.00035814795,0.012604758],"genre_scores_gemma":[0.7936922,0.00052560674,0.20163654,0.00006470294,0.000010889577,0.00019290166,0.000148834,0.00007767078,0.0036506488],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996784,0.000055538258,0.000011715783,0.000056527137,0.00015569096,0.000042294134],"domain_scores_gemma":[0.9996942,0.00010689411,0.000073713796,0.000026893598,0.00008571721,0.000012555263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004621573,0.0005660841,0.0006742914,0.00044188224,0.00023952992,0.0007310197,0.0008232508,0.00090218097,0.0020471632],"category_scores_gemma":[0.0010950305,0.00049965456,0.00047979568,0.00029092262,0.00039039727,0.0005027956,0.00044455496,0.0004942076,0.0004060943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028982073,0.000018409444,0.00029782404,0.000089723,0.000007484925,0.00006141922,0.000032993714,0.9767386,0.0073923673,0.003907371,0.00024044598,0.011184326],"study_design_scores_gemma":[0.000006970452,0.00005280537,0.00017030135,0.000009843787,0.0000040356235,0.000018132245,0.000010191901,0.99722713,0.000981114,0.00069406914,0.0008205246,0.000004891289],"about_ca_topic_score_codex":0.0019001748,"about_ca_topic_score_gemma":0.0023927426,"teacher_disagreement_score":0.0020471632,"about_ca_system_score_codex":0.00041888634,"about_ca_system_score_gemma":0.0008111715,"threshold_uncertainty_score":0.006848395},"labels":[],"label_agreement":null},{"id":"W2045186718","doi":"10.1115/1.2927434","title":"Virtual Simulation and Optimization of Milling Operations—Part I: Process Simulation","year":2008,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Torque; Enhanced Data Rates for GSM Evolution; Process (computing); Intersection (aeronautics); Mechanical engineering; Power (physics); Engineering; Computer science; Artificial intelligence; Physics","score_opus":0.012443686788191608,"score_gpt":0.24466906584373646,"score_spread":0.23222537905554486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045186718","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.102575034,0.00022275209,0.8801641,0.00016912649,0.000049668357,0.00017358309,0.0002837191,0.00084881426,0.015513261],"genre_scores_gemma":[0.91501105,0.0002216026,0.07990194,0.000041639363,0.0000150985215,0.0004107961,0.00023226895,0.00010252054,0.0040631564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998023,0.000054558193,0.000010235854,0.000026694985,0.00007636081,0.000029804216],"domain_scores_gemma":[0.99960476,0.00021543431,0.0000444626,0.000050719947,0.00006241826,0.000022239898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003769565,0.0005464332,0.0007911029,0.00034228773,0.00034674365,0.0009399009,0.0007799203,0.00081999344,0.0031082446],"category_scores_gemma":[0.0010591424,0.00039071278,0.0004957925,0.00040308767,0.00065353676,0.00063625036,0.00058380933,0.0005777056,0.0003060452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011607998,0.000007255044,0.00010524961,0.00000764915,0.0000023266352,0.000006194511,0.0000057966454,0.9969502,0.0003386418,0.0010086643,0.00004153596,0.0015148676],"study_design_scores_gemma":[0.0000043450677,0.0000055838877,0.000024925877,9.769007e-7,6.685075e-7,0.0000018127589,0.0000016874324,0.9991732,0.00026139928,0.00036215252,0.0001619566,0.0000011616614],"about_ca_topic_score_codex":0.0062461793,"about_ca_topic_score_gemma":0.0026358613,"teacher_disagreement_score":0.0062461793,"about_ca_system_score_codex":0.0006632111,"about_ca_system_score_gemma":0.0009578317,"threshold_uncertainty_score":0.012419641},"labels":[],"label_agreement":null},{"id":"W2045392269","doi":"10.1177/0954405414543482","title":"On a novel solid lubricant–coated cutting tool: Experimental investigation and finite element simulations","year":2014,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Machining; Lubricant; Coating; Finite element method; Materials science; Mechanical engineering; Tool wear; Process (computing); Cutting tool; Manufacturing engineering; Computer science; Process engineering; Metallurgy; Engineering; Composite material; Structural engineering","score_opus":0.009214126768613086,"score_gpt":0.21684351113836398,"score_spread":0.2076293843697509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045392269","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95576775,0.00018308424,0.036710594,0.00008806925,0.000034507462,0.00011672734,0.00031245305,0.0002651519,0.006521661],"genre_scores_gemma":[0.9790461,0.00010371057,0.019274436,0.000012065708,0.0000030488652,0.000061127525,0.00015622193,0.000019116456,0.0013240516],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998264,0.000017899656,0.000008538125,0.000023405384,0.00009149843,0.000032268985],"domain_scores_gemma":[0.99956554,0.00020528847,0.000059785783,0.000045579192,0.000096970485,0.000026764876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040483425,0.00044206422,0.00061651925,0.00055473525,0.0003675156,0.0006339423,0.00093096157,0.001565923,0.0021199277],"category_scores_gemma":[0.0008293233,0.0002934769,0.00039500016,0.0004989692,0.000566068,0.00053036696,0.00034809532,0.0003406566,0.00021963609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000369875,0.00031433377,0.0035955536,0.0005129934,0.00003318165,0.00048163562,0.00028224825,0.8956246,0.08014021,0.0020998607,0.0005259536,0.016019499],"study_design_scores_gemma":[0.0000451331,0.0002109076,0.00084879575,0.000009654797,0.00000815922,0.00003078441,0.000046907953,0.98930025,0.008876548,0.00012920736,0.00048163394,0.000012049234],"about_ca_topic_score_codex":0.0040544113,"about_ca_topic_score_gemma":0.0056678117,"teacher_disagreement_score":0.0040544113,"about_ca_system_score_codex":0.0003452802,"about_ca_system_score_gemma":0.0007477147,"threshold_uncertainty_score":0.008061588},"labels":[],"label_agreement":null},{"id":"W2045634514","doi":"10.1115/1.4028749","title":"Mechanics and Dynamics of Multifunctional Tools","year":2014,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Chamfer (geometry); Drilling; Oblique case; Vibration; Enhanced Data Rates for GSM Evolution; Stability (learning theory); Structural engineering; Dynamics (music); Mechanics; Mechanical engineering; Engineering; Computer science; Geometry; Physics; Acoustics; Mathematics","score_opus":0.005679921692689143,"score_gpt":0.19378359016448773,"score_spread":0.1881036684717986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045634514","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31233123,0.0010554555,0.6535645,0.00026344147,0.000095293326,0.000074625874,0.00016467801,0.0002996898,0.03215102],"genre_scores_gemma":[0.9807567,0.00029314792,0.013216754,0.00002492059,0.000017019374,0.000054615542,0.000043586973,0.000018539591,0.0055748033],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997813,0.00002218584,0.0000074921745,0.000045739976,0.00011353274,0.000029735369],"domain_scores_gemma":[0.99987555,0.00003056044,0.00003370342,0.000017669092,0.000025386676,0.00001711267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017613932,0.0003655008,0.00027490433,0.0004214086,0.00026995206,0.0006851217,0.0004890642,0.00059225055,0.001732924],"category_scores_gemma":[0.00042582428,0.00019912103,0.00030218673,0.00022245772,0.00087400456,0.00061849644,0.0006906037,0.0003008632,0.0002502736],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011427103,0.000052472344,0.0019347988,0.00012554109,0.000025071035,0.000795172,0.00032396297,0.69598556,0.11652151,0.14217693,0.00090984436,0.04103492],"study_design_scores_gemma":[0.000013017962,0.00012229937,0.0017393847,0.000011946922,0.0000061517076,0.00036884123,0.00007329364,0.9733557,0.0044419686,0.015992887,0.003848064,0.000026475367],"about_ca_topic_score_codex":0.00083006127,"about_ca_topic_score_gemma":0.00035886437,"teacher_disagreement_score":0.001732924,"about_ca_system_score_codex":0.00033432193,"about_ca_system_score_gemma":0.0003889118,"threshold_uncertainty_score":0.0057972074},"labels":[],"label_agreement":null},{"id":"W2045797166","doi":"10.1115/detc2007-35107","title":"On the Investigation of Machine Tool Chatter in the Milling Process","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Budapesti Műszaki és Gazdaságtudományi Egyetem","keywords":"Process (computing); Stability (learning theory); Differential equation; Control theory (sociology); Chart; Constant (computer programming); Characteristic equation; Machine tool; Instability; Computer science; Mathematics; Mathematical analysis; Mechanics; Mechanical engineering; Engineering; Physics; Artificial intelligence","score_opus":0.009842811877058823,"score_gpt":0.23196646489715725,"score_spread":0.22212365302009843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045797166","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4748387,0.00074103643,0.5200815,0.000106058564,0.000036493773,0.00003225713,0.000023466711,0.00029044918,0.0038499448],"genre_scores_gemma":[0.9931624,0.00012820499,0.005959317,0.000009969346,0.0000056217823,0.0000065349655,0.000008464668,0.000012690138,0.0007069471],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997397,0.000077267214,0.000008690838,0.0000509265,0.00010109069,0.000022363949],"domain_scores_gemma":[0.99829346,0.0012320683,0.00017737401,0.000085843494,0.00017721979,0.0000341712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051510043,0.00034836988,0.00046554624,0.00032208225,0.00019145341,0.00040310592,0.00040390025,0.0005254273,0.00080094824],"category_scores_gemma":[0.0022702548,0.00015833534,0.00036468898,0.00016387108,0.00046278947,0.0005777395,0.00023737532,0.00037813504,0.000083482664],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005689282,0.00011483468,0.0054528136,0.000700752,0.000120553166,0.0015398985,0.0011895811,0.79633695,0.13550004,0.017515747,0.00027049796,0.040689357],"study_design_scores_gemma":[0.0000046451296,0.000108080654,0.00088460837,0.000009761661,0.000010344013,0.00011412077,0.00002809682,0.9903296,0.0073486157,0.0009868128,0.00016725688,0.00000806912],"about_ca_topic_score_codex":0.00096490193,"about_ca_topic_score_gemma":0.0005574084,"teacher_disagreement_score":0.00096490193,"about_ca_system_score_codex":0.00020928001,"about_ca_system_score_gemma":0.00018233513,"threshold_uncertainty_score":0.0027241707},"labels":[],"label_agreement":null},{"id":"W2047445266","doi":"10.1115/1.1468864","title":"Generic Simulation Approach for Multi-Axis Machining, Part 2: Model Calibration and Feed Rate Scheduling","year":2002,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Deflection (physics); Scheduling (production processes); Mechanical engineering; Calibration; Computer science; Machine tool; Engineering; Mathematical optimization; Mathematics; Physics","score_opus":0.03481570658326264,"score_gpt":0.24414770720610177,"score_spread":0.20933200062283913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047445266","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0061124447,0.000078529476,0.98782235,0.00007375311,0.00003649895,0.00009732997,0.0001495551,0.0011819538,0.0044476404],"genre_scores_gemma":[0.34417176,0.00068352965,0.6453558,0.00014918644,0.000055243854,0.0010375135,0.0008228022,0.00092619465,0.0067979917],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997048,0.00007262567,0.000019303754,0.00004385968,0.00012787538,0.00003149642],"domain_scores_gemma":[0.9996735,0.00010740169,0.0000447108,0.00008363487,0.000074819676,0.000015953166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005555128,0.0008637313,0.0007112314,0.00045251488,0.00040565594,0.00080102263,0.0017505052,0.0014606947,0.0059498],"category_scores_gemma":[0.0010837115,0.0004942333,0.0010792383,0.00046517802,0.00038274354,0.000908901,0.00067536865,0.001117204,0.0010471975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029196495,0.00003474478,0.00024418172,0.00006303689,0.000015616197,0.000043180327,0.00004164891,0.97354436,0.004773154,0.01063275,0.00054387806,0.010034311],"study_design_scores_gemma":[0.000008535138,0.000014761959,0.00004620155,0.000005011002,0.0000039188817,0.00001831596,0.0000040194745,0.99367154,0.0019406674,0.0015029833,0.0027787723,0.0000052385],"about_ca_topic_score_codex":0.0026871918,"about_ca_topic_score_gemma":0.0020064332,"teacher_disagreement_score":0.0059498,"about_ca_system_score_codex":0.0008026444,"about_ca_system_score_gemma":0.0011181431,"threshold_uncertainty_score":0.019904077},"labels":[],"label_agreement":null},{"id":"W2047460476","doi":"10.1016/j.ijmachtools.2009.09.005","title":"Machining chatter in flank milling","year":2009,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Flank; Machining; Tool path; Mechanical engineering; Machine tool; End milling; Milling cutter; Path (computing); Engineering; Cutting tool; Computer science","score_opus":0.005790979792898873,"score_gpt":0.234743284119252,"score_spread":0.2289523043263531,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047460476","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53747475,0.0015029302,0.45153606,0.0001107601,0.00016433006,0.00007051374,0.000020106861,0.0003075021,0.008813032],"genre_scores_gemma":[0.9713481,0.00015693191,0.023787146,0.000018582112,0.00001749261,0.000012626807,0.000012100724,0.000036460442,0.004610557],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997553,0.000060588733,0.000010951063,0.000039342456,0.00010556961,0.00002820084],"domain_scores_gemma":[0.9989498,0.0006500373,0.00011409429,0.000087423745,0.00014528782,0.000053396336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000520096,0.00031250587,0.00055220834,0.00040022688,0.000408582,0.00047891543,0.00076248456,0.0006806945,0.0021667155],"category_scores_gemma":[0.0018269791,0.00029686594,0.00026532135,0.0002482727,0.0006585295,0.0005434554,0.0005349368,0.0005499091,0.00022757174],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002616673,0.00026404107,0.004343736,0.0007904845,0.0000878368,0.0018069418,0.0009627974,0.34008136,0.46241924,0.03535163,0.0011689469,0.15010631],"study_design_scores_gemma":[0.000043032953,0.0005246228,0.0019814798,0.000021593778,0.000026176409,0.00050694164,0.0001049833,0.94952047,0.041622758,0.004548915,0.001068831,0.000030228039],"about_ca_topic_score_codex":0.0006314375,"about_ca_topic_score_gemma":0.0010821898,"teacher_disagreement_score":0.0021667155,"about_ca_system_score_codex":0.00021059853,"about_ca_system_score_gemma":0.0001955007,"threshold_uncertainty_score":0.0072484016},"labels":[],"label_agreement":null},{"id":"W2047508649","doi":"10.1007/s11661-006-0219-3","title":"An eulerian finite-element model for determination of deformation state of a copper subjected to orthogonal cutting","year":2004,"lang":"en","type":"article","venue":"Metallurgical and Materials Transactions A","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada","keywords":"Materials science; Finite element method; Eulerian path; Deformation (meteorology); Plasticity; Stress (linguistics); Flow stress; Plane stress; Chip formation; Stress–strain curve; Shear stress; Material flow; Mechanics; Flow (mathematics); Computer simulation; Shear (geology); Composite material; Machining; Structural engineering; Strain rate; Metallurgy; Mathematics; Tool wear; Physics; Mathematical analysis; Engineering","score_opus":0.01132419298094487,"score_gpt":0.2456036444311216,"score_spread":0.23427945145017673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047508649","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21676327,0.0003880863,0.761961,0.00034259752,0.00012221052,0.0001333086,0.0004658975,0.00053938216,0.01928434],"genre_scores_gemma":[0.95162773,0.00029461793,0.038889196,0.00005156501,0.0000140925595,0.00012423524,0.00027969782,0.00008227423,0.008636688],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988604,0.000024178391,0.000007493546,0.000020187877,0.00004857154,0.000013555905],"domain_scores_gemma":[0.9998554,0.000053267864,0.000023328892,0.000021750975,0.000035049783,0.000011121364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026876404,0.00038898038,0.0005970013,0.00048332888,0.00039757468,0.00059300807,0.0009782354,0.0016073548,0.0020217425],"category_scores_gemma":[0.0007076322,0.00051140925,0.00042515766,0.0005694689,0.0007533083,0.00056686625,0.00045006993,0.0005304759,0.0003113345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022882263,0.000017335808,0.00031231027,0.000022814105,0.0000047892986,0.000054448687,0.000028992561,0.99189043,0.002169051,0.002456897,0.00010777191,0.0029121502],"study_design_scores_gemma":[0.0000021201683,0.0000062169784,0.00011019679,0.00000191326,0.000001546037,0.0000068029453,0.000005609779,0.99922633,0.00026035254,0.00019786601,0.00017907169,0.0000020464556],"about_ca_topic_score_codex":0.009125292,"about_ca_topic_score_gemma":0.006790263,"teacher_disagreement_score":0.009125292,"about_ca_system_score_codex":0.0005433466,"about_ca_system_score_gemma":0.0011614503,"threshold_uncertainty_score":0.01814437},"labels":[],"label_agreement":null},{"id":"W2047527504","doi":"10.1243/09544054jem856","title":"Effects of workpiece thermal properties on machining-induced residual stresses - thermal softening and conductivity","year":2007,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Residual stress; Materials science; Ultimate tensile strength; Composite material; Machining; Softening; Thermal conductivity; Residual; Metallurgy","score_opus":0.00835632293319987,"score_gpt":0.1975140197185538,"score_spread":0.18915769678535393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047527504","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99312735,0.00038373287,0.0056496146,0.000012230306,0.000005536551,0.000011252912,0.000045982448,0.000060475075,0.00070382573],"genre_scores_gemma":[0.9985989,0.00009824635,0.0010282814,0.0000035604892,0.0000011189194,0.000005162362,0.0000214408,0.000013046352,0.00023034486],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997087,0.000042440428,0.00002800792,0.00006468345,0.00010748202,0.000048585905],"domain_scores_gemma":[0.99906796,0.0004967382,0.0002068956,0.00010530705,0.00009375943,0.00002940802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043117994,0.000418559,0.00029697065,0.0002756957,0.00013283138,0.00034680782,0.00023820058,0.00026463091,0.0008026475],"category_scores_gemma":[0.0011566916,0.00023504726,0.0003585882,0.00024327854,0.00035785197,0.00035452642,0.00024293666,0.00023989765,0.00017872623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003273696,0.000049895465,0.004380412,0.00023909929,0.000027309548,0.00013968194,0.00010887325,0.018734334,0.96478826,0.00012065119,0.000028743418,0.011055529],"study_design_scores_gemma":[0.000016648153,0.0007983782,0.02997822,0.000013088676,0.0000478915,0.00014675567,0.00008103033,0.034138422,0.93417317,0.00009430148,0.0004836713,0.000028438219],"about_ca_topic_score_codex":0.00027107965,"about_ca_topic_score_gemma":0.00038618763,"teacher_disagreement_score":0.0008026475,"about_ca_system_score_codex":0.00022485093,"about_ca_system_score_gemma":0.00014699395,"threshold_uncertainty_score":0.00268507},"labels":[],"label_agreement":null},{"id":"W2047697359","doi":"10.1016/j.procir.2014.03.047","title":"Survival Life Analysis of the Cutting Tools During Turning Titanium Metal Matrix Composites (Ti-MMCs)","year":2014,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University; Polytechnique Montréal","funders":"National Research Council Canada","keywords":"Materials science; Titanium; Composite material; Matrix (chemical analysis); Metal; Titanium alloy; Metallurgy; Alloy","score_opus":0.007026608356058002,"score_gpt":0.22100487521376247,"score_spread":0.21397826685770446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047697359","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9499193,0.00039296263,0.04874633,0.00004109584,0.000006955535,0.000018362167,0.00020327052,0.000117651354,0.0005542045],"genre_scores_gemma":[0.99819297,0.00006165678,0.0012658264,0.0000031821671,0.0000017913524,0.000010438503,0.00015779483,0.000005205678,0.00030116175],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9997712,0.00003818073,0.000012146191,0.00004482105,0.0000839596,0.000049817674],"domain_scores_gemma":[0.9984939,0.0008619099,0.00030781858,0.00007704871,0.00020151207,0.00005775995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088219857,0.00040884208,0.00029865012,0.000858251,0.00018137779,0.00029359697,0.00037195394,0.0004519241,0.00058834604],"category_scores_gemma":[0.0019326049,0.00011421699,0.0005020043,0.00034818708,0.00027130407,0.00024522026,0.00024688378,0.00029743594,0.0001377183],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042392605,0.00011888796,0.083315484,0.00016002914,0.00011443051,0.0004831305,0.00028634255,0.8412799,0.026475484,0.0019412055,0.0003160346,0.045085188],"study_design_scores_gemma":[0.0000024345616,0.0003229804,0.02615809,0.000009149308,0.000025139914,0.00014987889,0.000077983765,0.9669134,0.0056552268,0.00048511877,0.00018068917,0.000019898009],"about_ca_topic_score_codex":0.0033669055,"about_ca_topic_score_gemma":0.0019823746,"teacher_disagreement_score":0.0033669055,"about_ca_system_score_codex":0.00047193153,"about_ca_system_score_gemma":0.00033010994,"threshold_uncertainty_score":0.006694615},"labels":[],"label_agreement":null},{"id":"W2047947848","doi":"10.1115/1.2927449","title":"Cutter-Workpiece Engagement Calculations by Parallel Slicing for Five-Axis Flank Milling of Jet Engine Impellers","year":2008,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Slicing; Ball (mathematics); End mill; Machining; Milling cutter; Mechanical engineering; Geometry; Intersection (aeronautics); Engineering drawing; Computer science; Engineering; Mathematics","score_opus":0.01150733229918984,"score_gpt":0.22485296249933526,"score_spread":0.2133456302001454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047947848","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41278827,0.00015589313,0.5771145,0.000036646346,0.000016651515,0.00009494621,0.00033645518,0.004098922,0.0053577563],"genre_scores_gemma":[0.7866916,0.00008846047,0.21157856,0.0000066890516,0.000002991626,0.000037775215,0.00040909753,0.0003105964,0.0008742325],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976176,0.000016903541,0.000011861207,0.000021458995,0.00017061328,0.000017248822],"domain_scores_gemma":[0.9995097,0.00020702576,0.00006767394,0.0000608437,0.00013694886,0.000017887673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025437845,0.0005534123,0.00034992996,0.0006793594,0.00028437312,0.0005212824,0.00057789206,0.00027009984,0.0023911644],"category_scores_gemma":[0.00093961344,0.0003262942,0.00038631487,0.0005526993,0.00018618119,0.0004471443,0.00033857525,0.00030928757,0.00022924252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023070027,0.00011051095,0.007933367,0.000247013,0.00004954606,0.0003506836,0.00048086146,0.6648967,0.072916,0.0029096105,0.0013339099,0.24854106],"study_design_scores_gemma":[0.000009959626,0.000048051294,0.0019230628,0.0000063382504,0.0000075178486,0.000055659995,0.00004025436,0.98104984,0.015387768,0.00036001764,0.0010992282,0.000012198459],"about_ca_topic_score_codex":0.0064173574,"about_ca_topic_score_gemma":0.0074703316,"teacher_disagreement_score":0.0064173574,"about_ca_system_score_codex":0.00049549626,"about_ca_system_score_gemma":0.0007636946,"threshold_uncertainty_score":0.012760043},"labels":[],"label_agreement":null},{"id":"W2048174155","doi":"10.3390/ma7031603","title":"Surface Finish and Residual Stresses Induced by Orthogonal Dry Machining of AA7075-T651","year":2014,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Materials science; Residual stress; Machining; Surface roughness; Drilling; Enhanced Data Rates for GSM Evolution; Surface finish; Composite material; Surface integrity; Ultimate tensile strength; Stress (linguistics); Cutting tool; Metallurgy; Engineering","score_opus":0.007016216033007729,"score_gpt":0.21686611692672148,"score_spread":0.20984990089371375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048174155","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993722,0.00009026679,0.00027327996,0.0000023883204,0.0000029631371,0.000002052047,0.000018804112,0.000007189874,0.00023090764],"genre_scores_gemma":[0.9991346,0.000051287716,0.00044791168,0.0000033609379,0.00000100484,0.0000019661431,0.000040037077,0.000004249069,0.00031562225],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998097,0.0000076467,0.000010214768,0.000027580665,0.00009608117,0.000048758153],"domain_scores_gemma":[0.9998124,0.000027869071,0.00008174015,0.000016039387,0.000039827853,0.000022134669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013451451,0.00025233536,0.0002016903,0.0003186077,0.00016304736,0.00025446917,0.00012670961,0.00022347858,0.00047338163],"category_scores_gemma":[0.00024832715,0.00015826078,0.00016573636,0.0002394977,0.00033078913,0.00014007722,0.0001816762,0.00019496348,0.000086218504],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096164214,0.000008661162,0.000965029,0.000035552646,0.000004687521,0.000071467606,0.00006721435,0.00038560486,0.99643433,0.000038873648,0.000024905674,0.0018674679],"study_design_scores_gemma":[0.00001053811,0.00072155875,0.040150322,0.0000064861583,0.000022559434,0.00020137189,0.00019598378,0.003979018,0.9534497,0.000043003543,0.0012057635,0.000013691199],"about_ca_topic_score_codex":0.002371614,"about_ca_topic_score_gemma":0.004591143,"teacher_disagreement_score":0.002371614,"about_ca_system_score_codex":0.00025569322,"about_ca_system_score_gemma":0.00021066461,"threshold_uncertainty_score":0.0047156215},"labels":[],"label_agreement":null},{"id":"W2049007674","doi":"10.1016/j.cirp.2007.05.016","title":"Grain Size and Orientation Effects When Microcutting AISI 1045 Steel","year":2007,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Grain size; Microstructure; Microscale chemistry; Dimple; Metallurgy; Grain boundary; Finite element method; Composite material; Shear (geology); Grain boundary strengthening; Shear stress; Structural engineering","score_opus":0.008004995428030367,"score_gpt":0.25838580706447933,"score_spread":0.250380811636449,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049007674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967354,0.000122002646,0.00073000987,0.000019479305,0.000014076414,0.0000033333997,0.000027575057,0.000035084526,0.002313108],"genre_scores_gemma":[0.9990748,0.000032035343,0.00016198945,0.0000037393995,0.0000020480159,7.175321e-7,0.0000199295,0.000014862613,0.00068999425],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981433,0.00001736926,0.0000060770517,0.000030549487,0.000075618555,0.000056148496],"domain_scores_gemma":[0.9994049,0.0002584537,0.00010147317,0.00004036435,0.00015458753,0.000040153613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021744653,0.00022021105,0.00026861316,0.00027839487,0.00041482155,0.0004940081,0.00024894398,0.00024243061,0.0027090902],"category_scores_gemma":[0.0009820932,0.0002292598,0.0001587718,0.0003245692,0.00036393286,0.00029509494,0.00016275207,0.00019935527,0.00019432949],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003090397,0.00022190226,0.020774405,0.0001511713,0.00004919735,0.0007928345,0.00026453572,0.16821991,0.7842681,0.0016083256,0.00085233635,0.019707039],"study_design_scores_gemma":[0.000065988155,0.00152964,0.11812979,0.000016535078,0.00013315603,0.00026133616,0.00065616,0.20308389,0.6740091,0.00045575143,0.001596944,0.00006174875],"about_ca_topic_score_codex":0.01082681,"about_ca_topic_score_gemma":0.031805012,"teacher_disagreement_score":0.01082681,"about_ca_system_score_codex":0.00081538426,"about_ca_system_score_gemma":0.00054202764,"threshold_uncertainty_score":0.021527529},"labels":[],"label_agreement":null},{"id":"W2050514004","doi":"10.4028/www.scientific.net/amr.325.103","title":"Ceramic Balls Machining by Centerless Grinding Using a Surface Grinder","year":2011,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Microsemi (Canada)","funders":"","keywords":"Pulverizer; Grinding; Materials science; Mechanical engineering; Ceramic; Machining; Ball (mathematics); Grinding wheel; Relay; Engineering; Composite material; Geometry","score_opus":0.07684291363050896,"score_gpt":0.33870662640096105,"score_spread":0.26186371277045206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050514004","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1939764,0.0014766286,0.7983212,0.00012354065,0.00014687068,0.00010123002,0.00006312336,0.0018743576,0.003916697],"genre_scores_gemma":[0.50972736,0.00051519874,0.48674273,0.00004905787,0.00005721657,0.000039520586,0.00012370029,0.0001431317,0.0026020324],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991804,0.00004752213,0.000026434667,0.0001592874,0.00054196693,0.000044396824],"domain_scores_gemma":[0.9995665,0.000080619226,0.00008933126,0.00010254371,0.00012320121,0.00003773977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037653808,0.0005080361,0.00081811094,0.0005594888,0.00026241541,0.00041669625,0.0009739919,0.0004474037,0.0009735136],"category_scores_gemma":[0.00039325343,0.00035222617,0.0006055289,0.00037551392,0.0006986561,0.00062278315,0.0005076167,0.00064768555,0.0005911782],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011575238,0.000038851733,0.00059683545,0.00022624993,0.000014407038,0.00009727344,0.00010753078,0.0024955028,0.93038416,0.0013975945,0.00044100906,0.06408478],"study_design_scores_gemma":[0.0001009559,0.0013781026,0.00487689,0.000014142263,0.0000473378,0.001780038,0.00005707257,0.07135829,0.9040806,0.000802225,0.015404657,0.000099674835],"about_ca_topic_score_codex":0.0006076452,"about_ca_topic_score_gemma":0.0011969974,"teacher_disagreement_score":0.0009739919,"about_ca_system_score_codex":0.00027725063,"about_ca_system_score_gemma":0.0004209091,"threshold_uncertainty_score":0.0032567382},"labels":[],"label_agreement":null},{"id":"W2050950112","doi":"10.1016/s0890-6955(02)00276-6","title":"Mechanics of boring processes—Part I","year":2003,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Engineering; Mechanical engineering; Mechanics; Physics","score_opus":0.008198708812425374,"score_gpt":0.23186936953220655,"score_spread":0.22367066071978117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050950112","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22963464,0.09862168,0.4401087,0.0031835455,0.0032261924,0.0003929744,0.0009180072,0.0004887083,0.22342551],"genre_scores_gemma":[0.8402909,0.030077554,0.019013233,0.00041211687,0.001600435,0.00022321925,0.0006793279,0.00032213138,0.10738118],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998616,0.000023677621,0.00000913343,0.00002994642,0.000053919906,0.000021691822],"domain_scores_gemma":[0.99987245,0.000052500567,0.000027888398,0.00001776965,0.000020839176,0.0000085275815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020081509,0.00044847548,0.0005763107,0.00045414595,0.00037328925,0.0009920057,0.00072215474,0.0004553137,0.014728247],"category_scores_gemma":[0.0005500619,0.00036380938,0.0005667612,0.0005727982,0.00088657625,0.00087296707,0.00057839626,0.00055785774,0.0013861511],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018105215,0.0003035742,0.0026327448,0.0018762136,0.000087960005,0.00038868724,0.0005652468,0.2984344,0.0818603,0.44001892,0.0141040385,0.15954687],"study_design_scores_gemma":[0.00008869276,0.0005567141,0.022673603,0.00026789165,0.00006364304,0.00085026614,0.0005248209,0.53876317,0.020731864,0.29412434,0.12125361,0.000101370126],"about_ca_topic_score_codex":0.000656742,"about_ca_topic_score_gemma":0.00050673395,"teacher_disagreement_score":0.014728247,"about_ca_system_score_codex":0.00021067826,"about_ca_system_score_gemma":0.0002671823,"threshold_uncertainty_score":0.049270928},"labels":[],"label_agreement":null},{"id":"W2051034453","doi":"10.1115/1.1643080","title":"Characteristics of Heat Transfer During Machining With Rotary Tools","year":2004,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Rotational speed; Machining; Rake; Mechanical engineering; Discretization; Heat transfer; Rake angle; Chip; Rotational energy; Materials science; Mechanics; Machine tool; Computer science; Engineering; Physics; Mathematics; Mathematical analysis; Classical mechanics","score_opus":0.004873497844882069,"score_gpt":0.18500759291393784,"score_spread":0.18013409506905578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051034453","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92218655,0.0003511641,0.07358181,0.00007572615,0.000013938954,0.000058032358,0.00006531987,0.00032160574,0.0033458692],"genre_scores_gemma":[0.99812967,0.000039183305,0.0013007316,0.0000056148233,0.0000024396857,0.000013070578,0.0000330524,0.000018980798,0.00045718468],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99982846,0.000024040588,0.000004329174,0.000035217876,0.00007442659,0.00003360276],"domain_scores_gemma":[0.9994025,0.00042979023,0.000049929076,0.000052593627,0.00005028647,0.000014874594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023179424,0.00024822017,0.0003625078,0.00022317578,0.00026300325,0.00041141722,0.00035085843,0.0005197476,0.000940502],"category_scores_gemma":[0.0012773472,0.00022460219,0.00032288162,0.00020184208,0.00054896536,0.0005742074,0.00016901594,0.00036465644,0.0001580082],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011091067,0.00014236492,0.010184333,0.00025881312,0.00004573741,0.00070391415,0.0012542908,0.3609443,0.5861085,0.003180999,0.0004119197,0.035655726],"study_design_scores_gemma":[0.000060059057,0.00051731186,0.025142502,0.000017023372,0.000023820137,0.00055874285,0.00020858076,0.73040426,0.23942573,0.0015676818,0.001996513,0.0000777704],"about_ca_topic_score_codex":0.0008487259,"about_ca_topic_score_gemma":0.00047876526,"teacher_disagreement_score":0.000940502,"about_ca_system_score_codex":0.0003228188,"about_ca_system_score_gemma":0.00017750108,"threshold_uncertainty_score":0.0031462908},"labels":[],"label_agreement":null},{"id":"W2052642425","doi":"10.1115/imece2011-63824","title":"Milling Burr Size Estimation Using Acoustic Emission and Cutting Forces","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Machining; Enhanced Data Rates for GSM Evolution; Coating; Mechanical engineering; Engineering; Materials science; Composite material","score_opus":0.01830337319997699,"score_gpt":0.2361040191734808,"score_spread":0.21780064597350382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052642425","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35489476,0.0003903911,0.6426511,0.000053616128,0.000013880817,0.000035644145,0.000068510184,0.00056300714,0.0013291285],"genre_scores_gemma":[0.9736534,0.00020703867,0.025163276,0.0000069098696,0.000004361085,0.00001981359,0.000060069302,0.000015181379,0.0008699422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977964,0.000035368994,0.000013041566,0.000059758117,0.000095926844,0.000016317419],"domain_scores_gemma":[0.99929965,0.0004138457,0.00013906114,0.00004562734,0.00008992172,0.000011964582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035484292,0.0004244634,0.00037800692,0.0003999843,0.00009429819,0.000498832,0.0004902932,0.0005880343,0.00040372682],"category_scores_gemma":[0.0013017154,0.0003257919,0.0004076858,0.00021752159,0.00024840765,0.00068216183,0.0002142666,0.0003213042,0.00018461779],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016565454,0.00012737274,0.016720029,0.00014215322,0.000055338925,0.00014535245,0.00014727186,0.82770866,0.06355763,0.0009670499,0.00032165658,0.08994179],"study_design_scores_gemma":[0.0000042545944,0.000053672673,0.0034713156,0.000004709784,0.000007606895,0.000043355085,0.000011304221,0.9890671,0.00695786,0.0002173928,0.00015106688,0.000010424727],"about_ca_topic_score_codex":0.0014931699,"about_ca_topic_score_gemma":0.0014461951,"teacher_disagreement_score":0.0014931699,"about_ca_system_score_codex":0.00019603138,"about_ca_system_score_gemma":0.00020997698,"threshold_uncertainty_score":0.0029689074},"labels":[],"label_agreement":null},{"id":"W2052722312","doi":"10.1109/icsmc.2006.384353","title":"Application of Artificial Neural Network in Friction Compensation During Particle Micro Manipulation","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial neural network; Compensation (psychology); Scaling; Computer science; Artificial intelligence; Control engineering; Particle (ecology); Engineering; Mathematics","score_opus":0.008224721145026235,"score_gpt":0.21364609790579378,"score_spread":0.20542137676076755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052722312","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08834368,0.0021475963,0.90587187,0.00027183603,0.00016932515,0.000040321902,0.000019625706,0.00049554097,0.0026402085],"genre_scores_gemma":[0.81186885,0.00080608897,0.18475571,0.000089160545,0.00007125249,0.000039788265,0.000023430164,0.000031930118,0.0023138653],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997781,0.00004303183,0.0000124804355,0.00004224574,0.000100520345,0.0000237035],"domain_scores_gemma":[0.9997751,0.000098860604,0.000028463599,0.000017538223,0.0000707431,0.000009226247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000421803,0.0003042972,0.0003461508,0.00026021025,0.00023274118,0.00029045588,0.0004187917,0.00064680807,0.00051216414],"category_scores_gemma":[0.0008025756,0.00019460576,0.00014545521,0.00031044177,0.000256365,0.0005579657,0.000266325,0.0002979184,0.00012348333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050019694,0.00012267876,0.002039697,0.00025746677,0.00006736527,0.0003228062,0.00013881306,0.21373898,0.26187402,0.0052876486,0.0011044947,0.51454586],"study_design_scores_gemma":[0.0000148914705,0.00011071136,0.0009588303,0.000010021248,0.00001649798,0.00009595818,0.000011057929,0.94723105,0.048178814,0.00076031504,0.0025938142,0.000017956],"about_ca_topic_score_codex":0.001203275,"about_ca_topic_score_gemma":0.0012534991,"teacher_disagreement_score":0.001203275,"about_ca_system_score_codex":0.0002590698,"about_ca_system_score_gemma":0.00021130433,"threshold_uncertainty_score":0.00239259},"labels":[],"label_agreement":null},{"id":"W2052736202","doi":"10.1115/1.2927444","title":"Dynamics Modeling and Analysis of Thin-Walled Aerospace Structures for Fixture Design in Multiaxis Milling","year":2008,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fixture; Aerospace; Machining; Flexibility (engineering); Finite element method; Mechanical engineering; Machine tool; Reduction (mathematics); Structural engineering; Process (computing); Calibration; Engineering; Computer science; Aerospace engineering","score_opus":0.012157287488269018,"score_gpt":0.22433422170293482,"score_spread":0.2121769342146658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052736202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21878429,0.00044150394,0.7765848,0.000067549394,0.000016433893,0.000057927627,0.00006835033,0.00020529334,0.003773869],"genre_scores_gemma":[0.9528791,0.0005076181,0.044124477,0.000012219598,0.0000062159033,0.000096172625,0.000074459036,0.000031853404,0.0022680212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999933,0.000014618329,0.0000026127018,0.000010331189,0.000031958338,0.000007523637],"domain_scores_gemma":[0.9999237,0.00003612025,0.000015699254,0.000009006145,0.0000108769,0.0000046288137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014768644,0.00038785953,0.0003815777,0.00023987296,0.00017050626,0.000438334,0.0003975724,0.00051845395,0.000870727],"category_scores_gemma":[0.00028901536,0.0002860629,0.00044619158,0.00014489455,0.00029113152,0.00032672068,0.00029467465,0.00031825947,0.0002059648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018167906,0.000013924623,0.000528112,0.000045570603,0.0000069744096,0.00009967898,0.00004332482,0.96583086,0.020750998,0.0017442763,0.00008552935,0.010832638],"study_design_scores_gemma":[0.0000027139872,0.000020452257,0.00033260684,0.0000039308497,0.0000021398312,0.000028819893,0.000011419342,0.99741447,0.0015607601,0.00028330216,0.00033654593,0.0000028762495],"about_ca_topic_score_codex":0.0015765416,"about_ca_topic_score_gemma":0.0013334213,"teacher_disagreement_score":0.0015765416,"about_ca_system_score_codex":0.00019875153,"about_ca_system_score_gemma":0.00035725167,"threshold_uncertainty_score":0.0031347275},"labels":[],"label_agreement":null},{"id":"W2052746072","doi":"10.1007/s11665-009-9567-7","title":"Investigations of White Layer Formation During Machining of Powder Metallurgical Ni-Based ME 16 Superalloy","year":2009,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Materials science; Superalloy; Metallurgy; Layer (electronics); Machining; Microstructure; Surface integrity; Scanning electron microscope; Metallography; Coating; Carbide; Tungsten carbide; Alloy; Ceramic; Composite material","score_opus":0.007667410379428274,"score_gpt":0.2011660047203581,"score_spread":0.1934985943409298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052746072","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99883777,0.0001460298,0.00038962415,0.000010001391,0.0000036060815,0.0000066895227,0.000039678227,0.000019075133,0.00054761727],"genre_scores_gemma":[0.99895763,0.000055414705,0.0003238172,0.0000042298334,0.0000012056945,0.0000036173096,0.00004928371,0.0000073210044,0.00059744524],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999008,0.000008812583,0.0000046856107,0.000019397272,0.000043146054,0.000023176626],"domain_scores_gemma":[0.9998161,0.000058462192,0.000051532956,0.000021099122,0.000039807117,0.000013035252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016015243,0.00016175419,0.00021037737,0.0001487718,0.0002640024,0.00026348012,0.0002588925,0.0002543649,0.0010139076],"category_scores_gemma":[0.0003156511,0.00019216996,0.00015364529,0.00015231961,0.0002773873,0.00033847,0.00016111783,0.00027381824,0.00014852261],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021138077,0.00001264239,0.00056240946,0.000039705148,0.0000053288336,0.000117952535,0.00015140814,0.00009683837,0.9978992,0.000062894214,0.000036110563,0.0008041736],"study_design_scores_gemma":[0.0000075495846,0.00018011448,0.008067042,0.0000022358665,0.000007093457,0.00009599438,0.0001397419,0.0008229073,0.9901647,0.000016004984,0.00049238745,0.0000042190622],"about_ca_topic_score_codex":0.0014110537,"about_ca_topic_score_gemma":0.0017548047,"teacher_disagreement_score":0.0014110537,"about_ca_system_score_codex":0.00023975885,"about_ca_system_score_gemma":0.0001591339,"threshold_uncertainty_score":0.003391862},"labels":[],"label_agreement":null},{"id":"W2053479326","doi":"10.1177/0954405412466995","title":"Integration of finite element simulation and intelligent methods for evaluation of thermo-mechanical loads during hard turning process","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Finite element method; Artificial neural network; Machining; Residual stress; Structural engineering; Mechanical engineering; Process (computing); Genetic algorithm; Materials science; Thermal; Engineering; Computer science; Mathematical optimization; Composite material; Mathematics; Artificial intelligence","score_opus":0.02218582912461053,"score_gpt":0.303333709739983,"score_spread":0.2811478806153725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053479326","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.044956446,0.00019681266,0.9512676,0.00005628864,0.00003307884,0.000057756297,0.00002611155,0.00037374915,0.0030321965],"genre_scores_gemma":[0.6809726,0.00031467402,0.3161329,0.00003537754,0.000016930097,0.0003238996,0.00009423382,0.0000868035,0.0020226387],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969435,0.00009705968,0.000021002465,0.000032824424,0.00013762401,0.000017148448],"domain_scores_gemma":[0.99948597,0.00031126034,0.000040993276,0.000043254815,0.00010392591,0.0000146626335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064417376,0.00062681723,0.0005380815,0.0006339164,0.00027550335,0.00048378494,0.0005497112,0.00084690214,0.00083782093],"category_scores_gemma":[0.0010886395,0.00038324902,0.00048939226,0.00034033068,0.0003751309,0.00046342186,0.0004119995,0.0004366673,0.00016993834],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057331574,0.00006647725,0.0010535783,0.000083253384,0.000035146702,0.000040320112,0.000079077516,0.9463457,0.012197102,0.002680131,0.00010567461,0.037256178],"study_design_scores_gemma":[0.0000022923175,0.000010684782,0.00009238239,0.0000029245211,0.0000027303845,0.000004746075,0.000004309975,0.9984444,0.0010566154,0.00019387415,0.00018249304,0.0000025152185],"about_ca_topic_score_codex":0.0027238063,"about_ca_topic_score_gemma":0.0032619191,"teacher_disagreement_score":0.0027238063,"about_ca_system_score_codex":0.00040944215,"about_ca_system_score_gemma":0.0006453589,"threshold_uncertainty_score":0.0054159164},"labels":[],"label_agreement":null},{"id":"W2053739820","doi":"10.1115/1.2772338","title":"Effects of Strain Hardening and Initial Yield Strength on Machining-Induced Residual Stresses","year":2007,"lang":"en","type":"article","venue":"Journal of Engineering Materials and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Materials science; Machining; Strain hardening exponent; Ultimate tensile strength; Hardening (computing); Composite material; Finite element method; Work hardening; Residual stress; Metallurgy; Tensile testing; Structural engineering; Microstructure","score_opus":0.005473249659711953,"score_gpt":0.22397679367725104,"score_spread":0.21850354401753908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053739820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98959607,0.00024051596,0.009140059,0.000008854278,0.0000043856485,0.000019436002,0.00004275996,0.00006279843,0.00088512484],"genre_scores_gemma":[0.9979785,0.00009804646,0.0015675492,0.000004747092,0.0000010422916,0.000008212273,0.0000347231,0.00001155711,0.00029569346],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99967325,0.000039191313,0.000025862064,0.000058151807,0.0001439746,0.000059558723],"domain_scores_gemma":[0.9990355,0.0006188828,0.00012657867,0.00007128257,0.000115119925,0.000032659893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046419952,0.0005281357,0.00032784863,0.00034666134,0.00013624327,0.00027994128,0.00040758826,0.00036036497,0.0009428168],"category_scores_gemma":[0.0012096064,0.0002817328,0.00042946896,0.00020111786,0.00033937168,0.0003015481,0.00023190012,0.00032522617,0.0001613186],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038464493,0.00018871983,0.008054619,0.0002492152,0.000029117473,0.00032474045,0.00016105066,0.087589666,0.87774104,0.0002589674,0.00003654041,0.02498164],"study_design_scores_gemma":[0.000019934001,0.0011387885,0.051316395,0.000020255622,0.00004422906,0.00019256414,0.00007989281,0.20415598,0.7423374,0.00013355038,0.0005216775,0.000039267936],"about_ca_topic_score_codex":0.0006389274,"about_ca_topic_score_gemma":0.0008611254,"teacher_disagreement_score":0.0009428168,"about_ca_system_score_codex":0.00019754276,"about_ca_system_score_gemma":0.00021686783,"threshold_uncertainty_score":0.0031540394},"labels":[],"label_agreement":null},{"id":"W2053771221","doi":"10.1016/j.rcim.2009.04.011","title":"Chatter detection based on probability distribution of wavelet modulus maxima","year":2009,"lang":"en","type":"article","venue":"Robotics and Computer-Integrated Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wavelet; Wavelet transform; Discrete wavelet transform; Mathematics; Stationary wavelet transform; Thresholding; Second-generation wavelet transform; Maxima; Machining; Pattern recognition (psychology); Artificial intelligence; Computer science; Engineering","score_opus":0.006417607256519973,"score_gpt":0.18877597241588384,"score_spread":0.18235836515936388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053771221","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.064506344,0.00016668292,0.93443346,0.000057634792,0.000026707545,0.000014489654,0.0000323908,0.00020465761,0.000557666],"genre_scores_gemma":[0.8245078,0.00031168183,0.17357793,0.000036071873,0.000067823436,0.000044451455,0.00010214873,0.00009147668,0.0012606259],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995383,0.000101153644,0.000032745833,0.000114281,0.00016487348,0.00004862327],"domain_scores_gemma":[0.9922747,0.0058440217,0.00062106655,0.0003383004,0.00071477704,0.0002071212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015854464,0.0005916934,0.00079212233,0.0016335812,0.00031386412,0.0008475524,0.00074107037,0.00091943494,0.0015401447],"category_scores_gemma":[0.010360175,0.00040567954,0.00038420456,0.00080576993,0.00077958556,0.0017069287,0.00085897755,0.00078014255,0.00034591922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002723139,0.00018993058,0.015681399,0.0007542805,0.000241166,0.0013317923,0.0005710988,0.2023118,0.19301806,0.060991842,0.0016857822,0.52049977],"study_design_scores_gemma":[0.0000210404,0.000095703785,0.004880956,0.000021528516,0.000024964942,0.000430196,0.000029253715,0.9715225,0.015369555,0.0072905743,0.00028390484,0.000029941022],"about_ca_topic_score_codex":0.00035818524,"about_ca_topic_score_gemma":0.00039346193,"teacher_disagreement_score":0.0016335812,"about_ca_system_score_codex":0.00028415062,"about_ca_system_score_gemma":0.0003110126,"threshold_uncertainty_score":0.008384764},"labels":[],"label_agreement":null},{"id":"W2054843759","doi":"10.1115/msec2014-4204","title":"Identification of Process Damping Coefficient Based on Material Constitutive Property","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of British Columbia; Johns Hopkins University","keywords":"Dissipation; Materials science; Vibration; Process (computing); Constitutive equation; Machining; Enhanced Data Rates for GSM Evolution; Finite element method; Property (philosophy); Structural engineering; Mechanical engineering; Machine tool; Computer science; Engineering; Acoustics; Metallurgy; Physics","score_opus":0.006123513677223517,"score_gpt":0.22929242863513813,"score_spread":0.2231689149579146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054843759","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20473514,0.00014871533,0.79201406,0.000045983303,0.0000101484075,0.000047844398,0.000035407407,0.00025025127,0.0027124537],"genre_scores_gemma":[0.9727923,0.00011465474,0.026391253,0.0000052002097,0.0000037683542,0.000034616376,0.000036028923,0.00001983719,0.00060246215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998845,0.000017077004,0.000003968836,0.000026659804,0.00005598325,0.000011847377],"domain_scores_gemma":[0.9997948,0.00009248846,0.00003893982,0.000019613793,0.000046511264,0.00000767992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016470824,0.00037417747,0.0002758458,0.00042931119,0.00013254139,0.0003532914,0.00029348276,0.00035697132,0.00046571647],"category_scores_gemma":[0.0007698478,0.00020898129,0.00028454262,0.00018979287,0.00026221332,0.00037290386,0.00021757845,0.0002676101,0.00013515867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011971959,0.00010113283,0.0064429766,0.00021058202,0.000030000594,0.00027767578,0.0002073563,0.54939586,0.3683257,0.006118123,0.00029617237,0.06847469],"study_design_scores_gemma":[0.0000067330884,0.000031269887,0.001514404,0.0000065596646,0.000006421278,0.000054086948,0.000010503498,0.9858374,0.011711685,0.00045758853,0.00035481816,0.000008488918],"about_ca_topic_score_codex":0.0011321311,"about_ca_topic_score_gemma":0.0009622465,"teacher_disagreement_score":0.0011321311,"about_ca_system_score_codex":0.00017523623,"about_ca_system_score_gemma":0.0003224949,"threshold_uncertainty_score":0.0022510886},"labels":[],"label_agreement":null},{"id":"W2055084924","doi":"10.1016/s0007-8506(07)60375-8","title":"The Effect of Microstructure on Chip Formation and Surface Defects in Microscale, Mesoscale, and Macroscale Cutting of Steel","year":2006,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microscale chemistry; Dimple; Microstructure; Materials science; Chip formation; Mesoscale meteorology; Homogeneous; Chip; Composite material; Surface (topology); Metallurgy; Machining; Geometry; Geology; Tool wear; Thermodynamics; Engineering","score_opus":0.003917387193084762,"score_gpt":0.2235716687925298,"score_spread":0.21965428159944503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055084924","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99861646,0.00026708533,0.0004894725,0.000021296528,0.0000062996983,0.0000019257316,0.000015554015,0.0000144089345,0.000567519],"genre_scores_gemma":[0.99958843,0.000055800614,0.00018946866,0.000004129304,0.0000027955118,7.880585e-7,0.000007833473,0.000004395341,0.00014640667],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99992204,0.000011510077,0.0000038026062,0.000012772259,0.000029307399,0.000020477293],"domain_scores_gemma":[0.9994424,0.00024367332,0.00012356197,0.000045557153,0.000100771525,0.000044002492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019362202,0.00007914702,0.00014812124,0.000190993,0.00017823697,0.00031550968,0.0001594629,0.00020791798,0.0005388303],"category_scores_gemma":[0.00079581334,0.00019598969,0.00012916283,0.00011221258,0.00032377648,0.00018587132,0.00013745093,0.00017332155,0.000072454706],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071663194,0.00012582469,0.021815797,0.00012047224,0.00004670416,0.00030592395,0.00012212388,0.032667022,0.92407703,0.00108939,0.00030026186,0.018612824],"study_design_scores_gemma":[0.00011444755,0.0017444063,0.31632352,0.000017293982,0.0001103207,0.00045901953,0.00019545293,0.12571788,0.5531579,0.00092662877,0.0011780235,0.00005502529],"about_ca_topic_score_codex":0.0015295692,"about_ca_topic_score_gemma":0.0036712724,"teacher_disagreement_score":0.0015295692,"about_ca_system_score_codex":0.00039908162,"about_ca_system_score_gemma":0.0001898734,"threshold_uncertainty_score":0.003041327},"labels":[],"label_agreement":null},{"id":"W2055398483","doi":"10.1007/s00170-011-3848-7","title":"Diagnostics of spindle unit, model design and analysis","year":2012,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Vibration; Fault (geology); Machine tool; Engineering; Process (computing); Unit (ring theory); Fault detection and isolation; Work (physics); Stability (learning theory); Control engineering; Computer science; Mechanical engineering; Mathematics; Physics; Machine learning","score_opus":0.012268309851707666,"score_gpt":0.25384528137904994,"score_spread":0.24157697152734228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055398483","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14300479,0.00021140178,0.84849,0.0002248344,0.000039766855,0.00015785769,0.0005028984,0.0024412528,0.004927228],"genre_scores_gemma":[0.9353532,0.000076250915,0.062180363,0.000028220726,0.000008801744,0.00015262791,0.0003332195,0.0001276265,0.0017397183],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972075,0.00008674341,0.000017346281,0.000043994187,0.00010781676,0.000023178533],"domain_scores_gemma":[0.99917835,0.00048498993,0.00007660965,0.00009354061,0.0001486005,0.00001785133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070479076,0.0007369052,0.0005963129,0.00069495157,0.000366341,0.00094281003,0.0007654298,0.0010089317,0.0031646972],"category_scores_gemma":[0.0034438712,0.0005677327,0.00047846805,0.0003111541,0.0002567882,0.0008097042,0.00039873007,0.0004972054,0.00052917853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027848914,0.00007090182,0.0021913853,0.00017793193,0.000022238151,0.000101863065,0.00009553028,0.93292075,0.015725795,0.0056501753,0.0013769743,0.041387867],"study_design_scores_gemma":[0.000012852015,0.000059022484,0.00074528606,0.0000054807815,0.000006999278,0.000035484976,0.000017163078,0.99171257,0.0056868712,0.0011237503,0.0005878927,0.0000066226003],"about_ca_topic_score_codex":0.0029417833,"about_ca_topic_score_gemma":0.001991465,"teacher_disagreement_score":0.0031646972,"about_ca_system_score_codex":0.0006096343,"about_ca_system_score_gemma":0.0011840741,"threshold_uncertainty_score":0.010586977},"labels":[],"label_agreement":null},{"id":"W2055499161","doi":"10.1007/s11071-010-9924-y","title":"Nonlinear analysis of chatter vibration in a cylindrical transverse grinding process with two time delays using a nonlinear time transformation method","year":2011,"lang":"en","type":"article","venue":"Nonlinear Dynamics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; University of Hong Kong; City University of Hong Kong","keywords":"Nonlinear system; Harmonic balance; Fourier series; Harmonics; Vibration; Mathematical analysis; Transverse plane; Damper; Bifurcation; Mathematics; Eigenvalues and eigenvectors; Control theory (sociology); Physics; Engineering; Structural engineering; Computer science","score_opus":0.012262823995472136,"score_gpt":0.2660992439492322,"score_spread":0.25383641995376005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055499161","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18217678,0.00029436615,0.8135408,0.000110543115,0.000058306872,0.000036036254,0.00001972277,0.00007043596,0.0036930717],"genre_scores_gemma":[0.9694229,0.00024195766,0.024201231,0.000017735245,0.00002202248,0.00003720182,0.000020272471,0.000026682346,0.0060099787],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998305,0.000049783106,0.0000067680517,0.000029142873,0.00006718307,0.00001659748],"domain_scores_gemma":[0.99956375,0.0002446129,0.000058013058,0.000018490455,0.00009668866,0.000018462879],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000491671,0.00056536647,0.00041822757,0.00028115266,0.00026694883,0.00034888135,0.0005191633,0.00064038474,0.0010328606],"category_scores_gemma":[0.0008601189,0.00019683507,0.00040051865,0.00020391168,0.0007079678,0.00058424636,0.0003940905,0.0005132623,0.00009034602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032511383,0.0001116865,0.0011035152,0.00030901012,0.000072074334,0.0004690557,0.00037624664,0.8288692,0.1063858,0.039462596,0.00034040195,0.022175385],"study_design_scores_gemma":[0.0000035177284,0.000025789874,0.00017866417,0.0000015945841,0.0000036766469,0.000015746959,0.000008696885,0.99786454,0.0012580592,0.0005479348,0.00008697686,0.0000047894655],"about_ca_topic_score_codex":0.0034149608,"about_ca_topic_score_gemma":0.0023703598,"teacher_disagreement_score":0.0034149608,"about_ca_system_score_codex":0.00038882688,"about_ca_system_score_gemma":0.0004559798,"threshold_uncertainty_score":0.006790161},"labels":[],"label_agreement":null},{"id":"W2056093440","doi":"10.4028/www.scientific.net/amr.325.134","title":"Experimental Study on Grinding of a Nickel-Based Alloy Using Vitrified CBN Wheels","year":2011,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Grinding; Materials science; Surface roughness; Abrasive; Metallurgy; Alloy; Grinding wheel; Surface finish; Composite material","score_opus":0.139379405885725,"score_gpt":0.3902572491962922,"score_spread":0.2508778433105672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056093440","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99486274,0.0002012451,0.0039686277,0.000011520631,0.000011323043,0.00004550779,0.00006636282,0.000035231085,0.00079749356],"genre_scores_gemma":[0.98320735,0.00019395509,0.014328634,0.000012353033,0.000004062312,0.000029350442,0.000101233774,0.00003191994,0.002091119],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994898,0.000036181507,0.000035277233,0.00011300842,0.00026425824,0.00006149379],"domain_scores_gemma":[0.9995135,0.00013549258,0.00006394707,0.00010460056,0.00014582733,0.000036605732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005900891,0.00030532535,0.0005690069,0.0002842693,0.00031321574,0.0002725558,0.0006919248,0.0004213732,0.0015310475],"category_scores_gemma":[0.00083712785,0.00024390026,0.00021378255,0.00029202612,0.00044303344,0.00023748669,0.0002721196,0.00039511538,0.00034092544],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013623314,0.00004755278,0.0005938254,0.00010766277,0.0000042895654,0.000057593657,0.00015429394,0.0009469107,0.9948543,0.00006928437,0.000030420753,0.0029976214],"study_design_scores_gemma":[0.00003078765,0.0012399427,0.008148441,0.000011719423,0.000014229583,0.00008452095,0.00011715753,0.006674133,0.9816065,0.000036192432,0.0020162796,0.000019988696],"about_ca_topic_score_codex":0.0026726488,"about_ca_topic_score_gemma":0.0062788096,"teacher_disagreement_score":0.0026726488,"about_ca_system_score_codex":0.00045680205,"about_ca_system_score_gemma":0.00031780405,"threshold_uncertainty_score":0.005314231},"labels":[],"label_agreement":null},{"id":"W2056211204","doi":"10.1016/j.jmatprotec.2006.10.024","title":"Impact velocity measurement of media in a vibratory finisher","year":2006,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Amplitude; Impact; Mechanics; Deformation (meteorology); Flux (metallurgy); Acoustics; Power (physics); Environmental science; Optics; Composite material; Physics; Structural engineering; Engineering; Metallurgy","score_opus":0.008668107152946655,"score_gpt":0.23217669444150474,"score_spread":0.22350858728855807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056211204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.988562,0.00012520594,0.009776968,0.000035000143,0.00002373476,0.000026499662,0.00009436395,0.00015246769,0.001203813],"genre_scores_gemma":[0.9955788,0.000062865554,0.0025055772,0.000010752618,0.000005458378,0.000007963295,0.00007362026,0.000022481792,0.0017324239],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996716,0.000020561072,0.000010349608,0.00006379058,0.00016893516,0.00006467796],"domain_scores_gemma":[0.9993218,0.00030471967,0.00006156865,0.000059912625,0.0001568311,0.00009515771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002924574,0.00040054903,0.0005829456,0.0005996393,0.00072322704,0.00070018746,0.00081386545,0.00083955267,0.004443905],"category_scores_gemma":[0.0006805002,0.00032300694,0.0002799039,0.0003372901,0.00046058724,0.00062027125,0.0006190107,0.00055480713,0.000516561],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087371154,0.000043312823,0.0020685554,0.000031189084,0.0000075801904,0.00012759956,0.00014001498,0.00035035392,0.9904351,0.0001049139,0.000067486355,0.005750184],"study_design_scores_gemma":[0.000093197465,0.0016805439,0.048444334,0.000016408027,0.000058037847,0.00027511036,0.0005784999,0.011254321,0.9354333,0.00011399435,0.0020083454,0.000043867836],"about_ca_topic_score_codex":0.0019562237,"about_ca_topic_score_gemma":0.0018966725,"teacher_disagreement_score":0.004443905,"about_ca_system_score_codex":0.00038901693,"about_ca_system_score_gemma":0.00040303214,"threshold_uncertainty_score":0.014866352},"labels":[],"label_agreement":null},{"id":"W2056766345","doi":"10.1016/j.ijmachtools.2004.06.005","title":"Surface shape prediction in high speed milling","year":2004,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Waviness; Machining; Surface (topology); Mechanical engineering; Surface roughness; Process (computing); Surface finish; Position (finance); Stability (learning theory); Test bench; Engineering; MATLAB; Computer science; Structural engineering; Materials science; Mathematics; Geometry; Composite material","score_opus":0.007417891612997811,"score_gpt":0.22984542712203615,"score_spread":0.22242753550903835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056766345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51730186,0.0003453146,0.47863832,0.00010425673,0.00005724905,0.000047956473,0.000067193905,0.0008178653,0.0026199843],"genre_scores_gemma":[0.9798615,0.00008130822,0.018943686,0.000012434524,0.000007236025,0.000012099043,0.000034206863,0.00003903191,0.0010085566],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998528,0.000031994838,0.0000056217177,0.0000204027,0.000073380725,0.000015746946],"domain_scores_gemma":[0.9991685,0.00052223675,0.000056830482,0.000060528804,0.0001651821,0.000026763404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033767652,0.00040191665,0.0004592807,0.00030028008,0.000234289,0.00054300646,0.0004937803,0.00089422875,0.001081575],"category_scores_gemma":[0.0012538192,0.00039970299,0.00034865178,0.0004391678,0.0003361585,0.00046504816,0.00032215964,0.00046673306,0.00025821215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015591901,0.000041157517,0.0020807083,0.0000340344,0.000009711632,0.00005235479,0.000021299524,0.9246889,0.0118439365,0.00050607836,0.00024813207,0.060317785],"study_design_scores_gemma":[0.0000020593363,0.000014025888,0.0002667535,5.8444425e-7,7.489278e-7,0.0000044372314,0.0000018314826,0.9981988,0.0013657903,0.000115249706,0.000028549981,0.0000012478732],"about_ca_topic_score_codex":0.0029626403,"about_ca_topic_score_gemma":0.0030067335,"teacher_disagreement_score":0.0029626403,"about_ca_system_score_codex":0.00031094174,"about_ca_system_score_gemma":0.00033658213,"threshold_uncertainty_score":0.0058907866},"labels":[],"label_agreement":null},{"id":"W2057437493","doi":"10.1115/imece2002-39109","title":"Analysis of the Machining Process Using a Thermo-Elastic-Viscoplastic Finite Element Model","year":2002,"lang":"en","type":"article","venue":"Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Finite element method; Viscoplasticity; Materials science; Machining; Ceramic; Plane stress; Deformation (meteorology); Stress (linguistics); Chip formation; Thrust; Enhanced Data Rates for GSM Evolution; Stress–strain curve; Composite material; Mechanical engineering; Structural engineering; Tool wear; Constitutive equation; Metallurgy; Engineering","score_opus":0.017273106549822292,"score_gpt":0.23135201638826763,"score_spread":0.21407890983844535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057437493","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034070168,0.00013845589,0.9539769,0.00009715674,0.00004165097,0.00017494302,0.00040464342,0.0007499523,0.010346115],"genre_scores_gemma":[0.61365134,0.0006945848,0.3596031,0.0000754434,0.000023752205,0.0010520907,0.0011656248,0.00028358822,0.023450414],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979776,0.000027190601,0.000013450328,0.000025258598,0.0001161747,0.000020086029],"domain_scores_gemma":[0.99979776,0.00008911485,0.000021052083,0.000024226201,0.00005890991,0.000008929754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003597929,0.00061661325,0.00064170564,0.00041691735,0.0003313298,0.00065696734,0.0011440754,0.0013456175,0.0053144833],"category_scores_gemma":[0.0006042724,0.0005168966,0.0006667957,0.00037678008,0.00029725904,0.00052610185,0.00029499058,0.00062327634,0.001628897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002281758,0.000032072985,0.00029487492,0.00006348216,0.000012032164,0.00004790441,0.000035230856,0.9732026,0.012512468,0.0036268733,0.00025691453,0.009892647],"study_design_scores_gemma":[0.0000049613514,0.000018272927,0.00012269168,0.000004714924,0.0000047341728,0.000016823473,0.0000054169273,0.99579984,0.002017493,0.00035623176,0.001643122,0.000005596773],"about_ca_topic_score_codex":0.003905621,"about_ca_topic_score_gemma":0.0031305947,"teacher_disagreement_score":0.0053144833,"about_ca_system_score_codex":0.00042766507,"about_ca_system_score_gemma":0.0010488813,"threshold_uncertainty_score":0.017778695},"labels":[],"label_agreement":null},{"id":"W2058213140","doi":"10.1007/s11665-009-9538-z","title":"Modeling of Particle Emission During Dry Orthogonal Cutting","year":2009,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Materials science; Machining; Particle (ecology); Mechanical engineering; Acoustic emission; Metallurgy; Composite material; Alloy; Cast iron; Engineering","score_opus":0.005135146753505273,"score_gpt":0.19700808357690638,"score_spread":0.19187293682340112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058213140","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8974834,0.00023380219,0.08957347,0.00012662046,0.00005024189,0.000079827994,0.0002512152,0.00025652058,0.011944775],"genre_scores_gemma":[0.99418265,0.00007779872,0.003368688,0.000011975391,0.0000049621926,0.000017005003,0.00009042151,0.000043863354,0.0022026086],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999107,0.0000118034,0.0000026015098,0.000015930329,0.000031654516,0.000027259208],"domain_scores_gemma":[0.99974555,0.00015055577,0.00002560753,0.000017169748,0.00004076588,0.000020348167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029192923,0.00041631985,0.0004589151,0.00020981966,0.0004274621,0.00066552823,0.00060615485,0.00081360847,0.0011888858],"category_scores_gemma":[0.0006527098,0.00039137428,0.0004858113,0.00018996051,0.0004141499,0.0005958783,0.00035616857,0.00044879856,0.00017036113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013801192,0.00007830396,0.0017499182,0.000033633114,0.000013254116,0.00011053206,0.000046077017,0.9799401,0.013674868,0.0010428551,0.0001542809,0.0030180707],"study_design_scores_gemma":[0.000008877536,0.00001843634,0.0007048649,0.0000010734657,0.000002418686,0.000011228692,0.0000064800893,0.99692744,0.0021311848,0.00009961479,0.000084865744,0.0000033993658],"about_ca_topic_score_codex":0.009489836,"about_ca_topic_score_gemma":0.004683149,"teacher_disagreement_score":0.009489836,"about_ca_system_score_codex":0.00062717585,"about_ca_system_score_gemma":0.0006026254,"threshold_uncertainty_score":0.018869221},"labels":[],"label_agreement":null},{"id":"W2058287642","doi":"10.1016/s0307-904x(00)00027-5","title":"Prediction of diameter errors in bar turning: a computationally effective model","year":2000,"lang":"en","type":"article","venue":"Applied Mathematical Modelling","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Finite element method; Deflection (physics); Computation; Machine tool; Mechanical engineering; Structural engineering; Engineering; Computer science; Algorithm; Physics; Optics","score_opus":0.014656941638057787,"score_gpt":0.2161455514176869,"score_spread":0.20148860977962912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058287642","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4240287,0.0008450639,0.5632017,0.0005939525,0.00019639116,0.00006366403,0.00012538815,0.000434398,0.010510674],"genre_scores_gemma":[0.982505,0.00018542263,0.014881966,0.000039836537,0.00004123516,0.00003427263,0.000044462613,0.00005215964,0.0022156264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983895,0.00004549663,0.000007013064,0.000027611422,0.000049942024,0.00003097412],"domain_scores_gemma":[0.9987122,0.0009301268,0.000104399536,0.00006472406,0.00013815137,0.00005050387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055732817,0.00047903828,0.0009075341,0.00037358064,0.00049814663,0.0008968919,0.00091096264,0.0018627243,0.0008863296],"category_scores_gemma":[0.0026815238,0.0005693481,0.00046402987,0.00036334287,0.0008973518,0.00076090737,0.00071781594,0.0009214951,0.00019014951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012661264,0.000008090221,0.00007368643,0.00000565212,0.0000016897293,0.000009654593,0.0000044349526,0.9975949,0.00029639786,0.0008627137,0.000043866403,0.001086229],"study_design_scores_gemma":[0.0000016543696,0.0000031949235,0.000027014312,4.340852e-7,6.044589e-7,0.0000012826695,7.0939717e-7,0.99969435,0.0000716201,0.00018373675,0.000014606202,9.2615875e-7],"about_ca_topic_score_codex":0.009776326,"about_ca_topic_score_gemma":0.006064324,"teacher_disagreement_score":0.009776326,"about_ca_system_score_codex":0.0006270231,"about_ca_system_score_gemma":0.0008742348,"threshold_uncertainty_score":0.019438863},"labels":[],"label_agreement":null},{"id":"W2058887939","doi":"10.1016/s0007-8506(07)62890-x","title":"Improving Productivity and Part Quality in Milling of Titanium Based Impellers by Chatter Suppression and Force Control","year":2000,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Pratt and Whitney Canada","keywords":"Impeller; Mechanical engineering; Vibration; End milling; Milling cutter; Engineering; Machining; Tool wear; Constant (computer programming); Variable (mathematics); Control theory (sociology); Materials science; Structural engineering; Control (management); Computer science; Acoustics; Mathematics; Physics","score_opus":0.010869718245735033,"score_gpt":0.248796980827399,"score_spread":0.23792726258166397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058887939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9695179,0.00055443094,0.028750878,0.00004394595,0.000022033651,0.000010723331,0.00001302399,0.000076922675,0.0010101714],"genre_scores_gemma":[0.9934929,0.0001582065,0.005677853,0.000008054727,0.0000065902027,0.000004830866,0.00001561734,0.00001227938,0.0006236822],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997192,0.000035481382,0.000012426234,0.000033055887,0.00014559134,0.00005421116],"domain_scores_gemma":[0.9994223,0.00021904752,0.00015035747,0.000032309756,0.00013736184,0.000038611786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004312198,0.00039149707,0.0003859703,0.00046966947,0.00039859934,0.0004676335,0.0006773691,0.000384304,0.00055613817],"category_scores_gemma":[0.0007076322,0.00019216372,0.00033735426,0.00042373463,0.00045767965,0.00040896313,0.00029813463,0.00031203488,0.000117843425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013432364,0.00010965764,0.0017867135,0.000118237214,0.000017088436,0.000094721385,0.00012859817,0.009381135,0.95792264,0.00038488643,0.000110919995,0.02860208],"study_design_scores_gemma":[0.0000714787,0.0013336188,0.007971247,0.000007378972,0.00006008431,0.0001240023,0.000102456106,0.07681529,0.9128589,0.00013920481,0.0004893883,0.000026883698],"about_ca_topic_score_codex":0.0014580291,"about_ca_topic_score_gemma":0.0023181227,"teacher_disagreement_score":0.0014580291,"about_ca_system_score_codex":0.00033099862,"about_ca_system_score_gemma":0.0002789172,"threshold_uncertainty_score":0.0028991103},"labels":[],"label_agreement":null},{"id":"W2059168238","doi":"10.1016/j.ijmachtools.2006.01.005","title":"High-power diode laser assisted hard turning of AISI D2 tool steel","year":2006,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":159,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Laser; Machining; Materials science; Diode; Machine tool; Mechanical engineering; Optoelectronics; Optics; Engineering; Metallurgy","score_opus":0.005468922516329161,"score_gpt":0.21952079217544948,"score_spread":0.21405186965912032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059168238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9828378,0.00045723174,0.0071346667,0.00010472114,0.000053906027,0.000031718326,0.00014504939,0.00023151985,0.009003385],"genre_scores_gemma":[0.99359554,0.000086212516,0.0016281176,0.000020189078,0.000010249198,0.0000070035517,0.00006120937,0.000026161764,0.004565391],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998248,0.0000135388345,0.0000049812907,0.000024525836,0.000087057175,0.00004518436],"domain_scores_gemma":[0.99979466,0.0000970971,0.000022453547,0.00002101527,0.000043282453,0.00002151626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017046627,0.00027046085,0.0004531559,0.000369538,0.00038346832,0.00038985742,0.00030963568,0.00045340977,0.0033293352],"category_scores_gemma":[0.00020001557,0.00021688914,0.00020752799,0.00035576272,0.0003464144,0.00025036835,0.00028912368,0.0002951653,0.00032871147],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038484085,0.00002137806,0.00028715562,0.000112751564,0.000010148725,0.00012731095,0.00010232679,0.0009942461,0.9905207,0.00021631263,0.00037396688,0.006848822],"study_design_scores_gemma":[0.0001311472,0.00061435776,0.017618502,0.0000103727125,0.00002400253,0.00024946558,0.00024019623,0.009255769,0.96632206,0.00024926866,0.005249451,0.000035506677],"about_ca_topic_score_codex":0.0012837981,"about_ca_topic_score_gemma":0.0031357121,"teacher_disagreement_score":0.0033293352,"about_ca_system_score_codex":0.00032922864,"about_ca_system_score_gemma":0.0003192602,"threshold_uncertainty_score":0.011137724},"labels":[],"label_agreement":null},{"id":"W2060450673","doi":"10.1007/s11340-011-9471-6","title":"Novel Experimental Method to Determine the Cutting Effectiveness of Grinding Grits","year":2011,"lang":"en","type":"article","venue":"Experimental Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Solid mechanics; Grinding; Asperity (geotechnical engineering); Scratch; Drilling; Ranging; Reduction (mathematics); Mechanics; Mechanical engineering; Composite material; Geology; Engineering; Geometry; Metallurgy; Mathematics","score_opus":0.033148679874894116,"score_gpt":0.29417082186891386,"score_spread":0.26102214199401974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060450673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5914724,0.0006067718,0.39868665,0.00016903425,0.0002991437,0.000618212,0.00081532885,0.00096376723,0.0063686944],"genre_scores_gemma":[0.7963554,0.00031141748,0.19980836,0.000075408396,0.00006837054,0.00051088346,0.00037198234,0.00008771194,0.0024105054],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988889,0.0000651772,0.000043785327,0.00020533525,0.00073110405,0.00006558786],"domain_scores_gemma":[0.998522,0.0003180719,0.00026450763,0.00027633985,0.0005584694,0.000060626975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010178069,0.00080878776,0.00041176684,0.0007224246,0.0006908996,0.00032216366,0.0010040733,0.0007846757,0.00303009],"category_scores_gemma":[0.0011499927,0.00040875518,0.00019554861,0.00043641592,0.0007330878,0.00070068805,0.00040026923,0.00074190315,0.0003910465],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012161011,0.00018003793,0.00047670896,0.00007832295,0.000006260994,0.000014103394,0.000029115841,0.00046269168,0.9912845,0.00054157415,0.000109767236,0.0066953762],"study_design_scores_gemma":[0.00005026321,0.0007724634,0.0030677796,0.0000050167555,0.000016754602,0.000094325886,0.000023071418,0.0071559497,0.9873503,0.00013818133,0.0013056204,0.000020302363],"about_ca_topic_score_codex":0.00060353044,"about_ca_topic_score_gemma":0.0013176717,"teacher_disagreement_score":0.00303009,"about_ca_system_score_codex":0.00055391545,"about_ca_system_score_gemma":0.0006165401,"threshold_uncertainty_score":0.010136664},"labels":[],"label_agreement":null},{"id":"W2060731635","doi":"10.1108/02602280010311365","title":"Integration of an optical roughness sensor with a co‐ordinate measuring machine","year":2000,"lang":"en","type":"article","venue":"Sensor Review","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Stylus; Profilometer; Surface finish; Surface roughness; Amplitude; Noise (video); Software; Optics; Dynamic range; Acoustics; Proximity sensor; Materials science; Engineering; Computer science; Computer vision; Physics; Mechanical engineering; Image (mathematics)","score_opus":0.015740803246990127,"score_gpt":0.26316391155249597,"score_spread":0.24742310830550585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060731635","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26019856,0.0032621794,0.71301126,0.0004641323,0.00093169947,0.000765043,0.0006487704,0.0067492705,0.0139691625],"genre_scores_gemma":[0.45241293,0.0006265015,0.53924006,0.00017360906,0.00008728705,0.0003014446,0.0003632182,0.0001280765,0.0066668424],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972325,0.00016018584,0.000120918085,0.0003198059,0.0020445115,0.00012207641],"domain_scores_gemma":[0.9984394,0.0002817413,0.00015422345,0.00027208912,0.00078663527,0.000065903114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070958625,0.0004025445,0.0008088902,0.0011895178,0.0003431763,0.00082192576,0.0012459833,0.00083397183,0.0015428351],"category_scores_gemma":[0.0019425156,0.0005025978,0.0002647071,0.0009000735,0.000275605,0.0006887925,0.00043723956,0.0007176846,0.0007286095],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001971463,0.00012789428,0.0018726976,0.00023757353,0.000027493714,0.00011063168,0.00005155435,0.0014036149,0.8782799,0.0012667314,0.0018080926,0.11461667],"study_design_scores_gemma":[0.000041642594,0.0008512992,0.01069146,0.000027342196,0.00006278622,0.0012386047,0.00006145966,0.042694163,0.90792185,0.00035053806,0.03595285,0.00010591119],"about_ca_topic_score_codex":0.0015336953,"about_ca_topic_score_gemma":0.0021410233,"teacher_disagreement_score":0.0015428351,"about_ca_system_score_codex":0.0006016002,"about_ca_system_score_gemma":0.0007331403,"threshold_uncertainty_score":0.0051612854},"labels":[],"label_agreement":null},{"id":"W2061286055","doi":"10.4028/www.scientific.net/kem.499.162","title":"Study on Drilling Tools for Ti/Carbon Fibre Interlaminated Composites","year":2012,"lang":"en","type":"article","venue":"Key engineering materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MD Precision (Canada)","funders":"","keywords":"Drilling; Delamination (geology); Drill; Materials science; Enhanced Data Rates for GSM Evolution; Composite material; Carbon fibers; Engineering; Metallurgy; Geology; Composite number","score_opus":0.01752616189950579,"score_gpt":0.24199367913265016,"score_spread":0.22446751723314437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061286055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98269916,0.002663715,0.009730748,0.00007180013,0.000060225197,0.00006863917,0.00010647369,0.000063011124,0.0045363163],"genre_scores_gemma":[0.986832,0.0010249319,0.009818059,0.000015744425,0.000008394224,0.000015914618,0.00009832592,0.000021114369,0.002165566],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999602,0.00004207026,0.00002104971,0.000053029602,0.00022704393,0.00005476201],"domain_scores_gemma":[0.9991297,0.00029161063,0.00012391112,0.00006749703,0.0003424624,0.000044945995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034220977,0.00025777012,0.00033819766,0.000488019,0.0003825699,0.00036847053,0.00034802564,0.00043761692,0.0016209062],"category_scores_gemma":[0.00097257126,0.0001906613,0.00038519103,0.00049496075,0.0002911457,0.0005574974,0.00013595217,0.00026624475,0.00029610106],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033766305,0.00013296369,0.0031269467,0.0014156098,0.000022507036,0.00055518106,0.00059287465,0.0055126008,0.9527833,0.0014653951,0.00045717778,0.033597704],"study_design_scores_gemma":[0.000048136382,0.0049894997,0.032432266,0.00014586544,0.00011725069,0.001713603,0.0015452004,0.025496416,0.91225463,0.000907505,0.020268364,0.00008128754],"about_ca_topic_score_codex":0.0013653712,"about_ca_topic_score_gemma":0.0020458652,"teacher_disagreement_score":0.0016209062,"about_ca_system_score_codex":0.00023715611,"about_ca_system_score_gemma":0.00036560517,"threshold_uncertainty_score":0.0054225326},"labels":[],"label_agreement":null},{"id":"W2061303464","doi":"10.1016/j.ijmachtools.2008.10.002","title":"Finite element modeling approaches in grinding","year":2008,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":166,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Finite element method; Grinding; Macro; Scale (ratio); Focus (optics); Mechanical engineering; Macroscopic scale; Computer science; Engineering; Engineering drawing; Structural engineering; Physics","score_opus":0.03477988075758565,"score_gpt":0.24590186026909214,"score_spread":0.2111219795115065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061303464","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00431011,0.0012339843,0.98736316,0.00019840483,0.00008126474,0.000039956158,0.000058415975,0.00014948458,0.0065651797],"genre_scores_gemma":[0.2945048,0.005337534,0.6766802,0.00029903714,0.00015169474,0.00034866954,0.00032899482,0.0004661733,0.021882977],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995209,0.000145033,0.000028282504,0.000053294752,0.00022479889,0.000027662432],"domain_scores_gemma":[0.999476,0.00028909018,0.000045055833,0.000052312156,0.00012033799,0.000017257464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077117304,0.0008670729,0.0013635975,0.0011338822,0.00052840734,0.0011929782,0.0025110957,0.0022384864,0.0044818358],"category_scores_gemma":[0.0015789294,0.0010286062,0.001027015,0.00115511,0.00091897557,0.0013501613,0.0008064213,0.0014026694,0.0014834505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001589387,0.00006272099,0.00016469478,0.00012944336,0.000021193877,0.000044430904,0.00008765312,0.92971146,0.0024120063,0.040451262,0.00048521947,0.02641391],"study_design_scores_gemma":[0.0000050291196,0.00001006667,0.0000574455,0.000017943008,0.0000049963637,0.000020061036,0.000015036704,0.9871066,0.0003894595,0.009607077,0.00275879,0.0000073741326],"about_ca_topic_score_codex":0.0059547964,"about_ca_topic_score_gemma":0.0055537582,"teacher_disagreement_score":0.0059547964,"about_ca_system_score_codex":0.0007429962,"about_ca_system_score_gemma":0.0008127208,"threshold_uncertainty_score":0.014993191},"labels":[],"label_agreement":null},{"id":"W2062750487","doi":"10.1016/j.cirp.2009.03.100","title":"Characterization of the dry high speed drilling process of woven composites using Machinability Maps approach","year":2009,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":124,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"National Research Council Canada","keywords":"Machinability; Delamination (geology); Drilling; Materials science; Tool wear; Thrust; Composite material; Surface roughness; Fiber; Surface finish; Machining; Characterization (materials science); Thermal; Mechanical engineering; Geology; Metallurgy; Engineering","score_opus":0.017574915075916048,"score_gpt":0.2586302418408275,"score_spread":0.24105532676491145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062750487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97993636,0.00018899232,0.018175783,0.00001680999,0.0000075539488,0.00001886402,0.00010336556,0.000080291094,0.0014719166],"genre_scores_gemma":[0.9930642,0.000051705734,0.0060474267,0.000003680887,0.000001895801,0.000010340546,0.00006934813,0.000016999824,0.00073435635],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998227,0.000014700173,0.0000068504232,0.000019745512,0.00012108045,0.000015072089],"domain_scores_gemma":[0.9995746,0.00014256193,0.00007988675,0.000047736965,0.000140018,0.000015306794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024011254,0.00021643363,0.00021634469,0.00053977384,0.0002140326,0.00033333947,0.00018222131,0.00027789184,0.00084895844],"category_scores_gemma":[0.0005067376,0.00020339168,0.00017315967,0.00032753966,0.0002395539,0.00036726784,0.00014294071,0.00020525824,0.00012317873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023572493,0.00002446386,0.0013646904,0.000060015882,0.0000052634196,0.000048720405,0.00008498935,0.0029067255,0.9869992,0.00018660382,0.000051414852,0.008032231],"study_design_scores_gemma":[0.000012530424,0.00045264472,0.029453503,0.000005253783,0.00001879648,0.000149364,0.000101928235,0.033751745,0.9346294,0.0001414877,0.0012657604,0.000017671726],"about_ca_topic_score_codex":0.0009233258,"about_ca_topic_score_gemma":0.0014008671,"teacher_disagreement_score":0.0009233258,"about_ca_system_score_codex":0.00016058271,"about_ca_system_score_gemma":0.00018480782,"threshold_uncertainty_score":0.002840042},"labels":[],"label_agreement":null},{"id":"W2063917576","doi":"10.5539/mas.v3n7p52","title":"Prediction of the coating thickness of wire coating extrusion processes using artificial neural network (ANN)","year":2009,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Coating; Artificial neural network; Materials science; Composite material; Backpropagation; Biological system; Computer science; Artificial intelligence","score_opus":0.025873653305786237,"score_gpt":0.2411809434210736,"score_spread":0.21530729011528738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063917576","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48828745,0.00040781804,0.5086065,0.00009240676,0.000038711853,0.000041863004,0.00013520682,0.000552251,0.0018377987],"genre_scores_gemma":[0.948559,0.00019802325,0.049886476,0.000013930876,0.000008998748,0.000035714842,0.0001454832,0.000028308621,0.0011239878],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981517,0.000041433414,0.000013719487,0.00003433896,0.00007667763,0.00001879256],"domain_scores_gemma":[0.9993413,0.00039987123,0.00009417371,0.000039073824,0.00011256798,0.000012873928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004291158,0.0005337496,0.00034974323,0.00046022714,0.0001621489,0.00040233848,0.00030748674,0.0007289814,0.00054530887],"category_scores_gemma":[0.0017703116,0.00033759087,0.00043018395,0.00024727226,0.00017800379,0.0005145567,0.00016002388,0.00046754282,0.00012684199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001207247,0.0000517142,0.004560763,0.00006923756,0.000049714286,0.000073180716,0.000027297248,0.9461344,0.015370082,0.00028239374,0.00015400966,0.033106547],"study_design_scores_gemma":[0.0000019235279,0.000018278264,0.0010495133,0.000002283009,0.000004450433,0.0000056507924,0.0000029989044,0.99637955,0.002379514,0.00009480501,0.000057768506,0.0000032188616],"about_ca_topic_score_codex":0.0036921129,"about_ca_topic_score_gemma":0.004138922,"teacher_disagreement_score":0.0036921129,"about_ca_system_score_codex":0.0003971622,"about_ca_system_score_gemma":0.00027289253,"threshold_uncertainty_score":0.0073412657},"labels":[],"label_agreement":null},{"id":"W2064063827","doi":"10.1016/j.cirp.2013.03.084","title":"Feedrate optimization for freeform milling considering constraints from the feed drive system and process mechanics","year":2013,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Jerk; Machining; Acceleration; Mechanical engineering; Engineering; Process (computing); Limiting; Actuator; Machine tool; Control theory (sociology); Control engineering; Computer science; Control (management); Artificial intelligence; Physics","score_opus":0.017447378460688636,"score_gpt":0.23596375232694933,"score_spread":0.2185163738662607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064063827","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13648461,0.0009055624,0.8422145,0.00025807004,0.000095409996,0.0001352735,0.00023408994,0.00028402975,0.019388502],"genre_scores_gemma":[0.899853,0.00045479022,0.087264575,0.00005546392,0.0000435186,0.00016122067,0.0002561311,0.00025802947,0.01165322],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963367,0.00009649709,0.0000149714615,0.00004959278,0.00013142076,0.000073766794],"domain_scores_gemma":[0.9992331,0.0004994912,0.00007398454,0.000036558493,0.00011838526,0.00003840787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011130738,0.0013285663,0.0018487701,0.00086089404,0.00046657448,0.0017842886,0.0008707071,0.0018373346,0.0037957355],"category_scores_gemma":[0.0025774166,0.001142264,0.0010869509,0.0007888497,0.000665402,0.0012509765,0.0010161104,0.001012972,0.0004721678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007453518,0.00003528689,0.00021122902,0.00007752665,0.000017031205,0.000036731282,0.000022561735,0.98598087,0.0018377677,0.0030952794,0.00024080499,0.008370432],"study_design_scores_gemma":[0.000013203465,0.000049760445,0.00016949922,0.000006863933,0.0000059418703,0.000010097144,0.0000095310725,0.99755764,0.0007484272,0.00118447,0.00023765929,0.0000067648743],"about_ca_topic_score_codex":0.005651606,"about_ca_topic_score_gemma":0.0067546545,"teacher_disagreement_score":0.005651606,"about_ca_system_score_codex":0.00091859966,"about_ca_system_score_gemma":0.0014289784,"threshold_uncertainty_score":0.012698054},"labels":[],"label_agreement":null},{"id":"W2064103617","doi":"10.1080/10910344.2010.503455","title":"CURRENT STATUS AND FUTURE DIRECTION IN THE NUMERICAL MODELING AND SIMULATION OF MACHINING PROCESSES: A CRITICAL LITERATURE REVIEW","year":2010,"lang":"en","type":"article","venue":"Machining Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Constitutive equation; Finite element method; Machining; Mechanical engineering; Interface (matter); Process (computing); Chip formation; Computer science; Tool wear; Engineering; Materials science; Structural engineering","score_opus":0.006104714214915646,"score_gpt":0.29309893973773826,"score_spread":0.2869942255228226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064103617","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003942059,0.84344566,0.13739856,0.0039703497,0.0013348198,0.00008577719,0.00015784409,0.00060898875,0.009055933],"genre_scores_gemma":[0.020567328,0.90232337,0.07139608,0.0006528508,0.0014862776,0.00012670353,0.00045919602,0.00016458663,0.0028236553],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99785787,0.00072336156,0.00031577615,0.00023706227,0.00078412396,0.000081691374],"domain_scores_gemma":[0.98943055,0.0070814956,0.0003735581,0.00042681393,0.0025202974,0.0001672412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005436807,0.0012172341,0.0022323118,0.0034963572,0.00060915254,0.0040979204,0.0029349294,0.0030042615,0.005726154],"category_scores_gemma":[0.008596525,0.00085214194,0.0010084396,0.005893764,0.00113708,0.0055209068,0.0010231219,0.0012865192,0.0040343395],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018707337,0.00014544855,0.0015967735,0.0129643995,0.00013065581,0.00020845135,0.00028499478,0.041415557,0.003343057,0.032084327,0.014121598,0.89351755],"study_design_scores_gemma":[0.00008006389,0.0004636167,0.0016072048,0.00948785,0.00052511593,0.0010083629,0.00074680615,0.11565384,0.005170265,0.044468913,0.8205955,0.00019244208],"about_ca_topic_score_codex":0.0017575786,"about_ca_topic_score_gemma":0.0018593841,"teacher_disagreement_score":0.005726154,"about_ca_system_score_codex":0.00093322527,"about_ca_system_score_gemma":0.0022137337,"threshold_uncertainty_score":0.028752923},"labels":[],"label_agreement":null},{"id":"W2064446798","doi":"10.1115/detc2009-86221","title":"Analytical Calculation of Cutter/Workpiece Engagements for Helical Hole Milling","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Pratt and Whitney Canada","keywords":"Machining; Intersection (aeronautics); Contouring; Process (computing); Mechanical engineering; Milling cutter; End mill; Helix (gastropod); Cylinder; Engineering drawing; Geometry; Engineering; Computer science; Mathematics; Geology","score_opus":0.014964338331711853,"score_gpt":0.2776647509521242,"score_spread":0.2627004126204123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064446798","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1533981,0.00051545136,0.8121174,0.00016850022,0.000042946762,0.00012235166,0.0001669716,0.00072389364,0.032744385],"genre_scores_gemma":[0.9391731,0.00035397752,0.056164768,0.000030260875,0.000017735954,0.00006695695,0.00009278471,0.00021186237,0.003888686],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999699,0.00003204696,0.000010343459,0.000022382284,0.0001878331,0.00004840972],"domain_scores_gemma":[0.99938846,0.000280836,0.00008021156,0.000055847046,0.00015751368,0.000037216774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004888424,0.0005313658,0.0006617608,0.00068565796,0.00046420173,0.0011380955,0.00088314345,0.00092959707,0.002893114],"category_scores_gemma":[0.0020956106,0.00036074285,0.0004860103,0.0005443678,0.0007514435,0.0006656046,0.0006957163,0.00060493394,0.00064732484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043400036,0.000044714798,0.0009452587,0.000103226615,0.0000069391326,0.00036862315,0.00021146497,0.9505368,0.010207275,0.024195174,0.00051509746,0.012822031],"study_design_scores_gemma":[0.000003639349,0.000012432178,0.00013979174,0.000005729908,0.0000016722981,0.000033357028,0.000025126505,0.9965507,0.0012920856,0.0013035391,0.0006270784,0.000004865475],"about_ca_topic_score_codex":0.003807546,"about_ca_topic_score_gemma":0.003674399,"teacher_disagreement_score":0.003807546,"about_ca_system_score_codex":0.0011499358,"about_ca_system_score_gemma":0.0012068627,"threshold_uncertainty_score":0.009678423},"labels":[],"label_agreement":null},{"id":"W2064881717","doi":"10.1115/1.4025739","title":"The Performance of Diamond-Like Carbon Coated Drills in Thermally Assisted Drilling of Ti-6Al-4V","year":2013,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drilling; Materials science; Metallurgy; Diamond-like carbon; Enhanced Data Rates for GSM Evolution; Adhesion; Carbon fibers; Diamond; Tool wear; Machining; Composite material; Thin film; Nanotechnology; Composite number","score_opus":0.0044962562129196035,"score_gpt":0.1870397738657802,"score_spread":0.1825435176528606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064881717","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984016,0.0003410232,0.0009054693,0.000008252112,0.000013375263,0.00001065699,0.000048608803,0.000036865888,0.00023419212],"genre_scores_gemma":[0.99637574,0.00019238674,0.0028846636,0.0000068055433,0.000002858585,0.000010771164,0.000050048475,0.000011546453,0.00046510575],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996991,0.000026805517,0.00002487171,0.00005183225,0.00014188842,0.00005543527],"domain_scores_gemma":[0.9994199,0.00012958243,0.00016995742,0.00004948548,0.00016883659,0.00006216567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002548776,0.00038930238,0.00025777752,0.00034648675,0.00013207585,0.00027787092,0.00047123362,0.0005217795,0.0004953216],"category_scores_gemma":[0.00084028183,0.0003548302,0.00020469536,0.00022202778,0.00024540807,0.00029312485,0.00019513493,0.00022785681,0.00012147654],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001505483,0.000011771235,0.00017003757,0.00007638989,0.0000039035885,0.000034392997,0.000024341489,0.00023862864,0.99771285,0.00001270236,0.000015378491,0.0015489238],"study_design_scores_gemma":[0.000010018157,0.00052697194,0.003003393,0.0000055243586,0.000009605029,0.000064458705,0.000028763541,0.0013191479,0.9946518,0.0000066398406,0.00036249746,0.000011191111],"about_ca_topic_score_codex":0.0007825978,"about_ca_topic_score_gemma":0.0021665886,"teacher_disagreement_score":0.0007825978,"about_ca_system_score_codex":0.00015436074,"about_ca_system_score_gemma":0.00017879577,"threshold_uncertainty_score":0.0016570091},"labels":[],"label_agreement":null},{"id":"W2065351994","doi":"10.1115/imece2014-37986","title":"Nonlinear Vibration of Nanobeam With Quadratic Rational Bezier Arc Curvature","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Curvature; Nonlinear system; Mathematical analysis; Vibration; Natural frequency; Mathematics; Galerkin method; Boundary value problem; Arc length; Classical mechanics; Physics; Geometry; Arc (geometry); Acoustics","score_opus":0.00323003294182018,"score_gpt":0.1919992905893912,"score_spread":0.18876925764757102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065351994","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7783544,0.00044429337,0.21224403,0.00018572631,0.000052594154,0.000033824115,0.000059475427,0.00011317041,0.008512449],"genre_scores_gemma":[0.9822204,0.00011212633,0.015316246,0.000013963725,0.0000041929584,0.000016010406,0.000026651063,0.000010324179,0.0022800616],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998945,0.000013059618,0.0000029550322,0.000021886559,0.000051171497,0.000016410795],"domain_scores_gemma":[0.9998958,0.000036626163,0.00002539235,0.000016600969,0.000017092809,0.000008547109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016942724,0.00022655897,0.00024096845,0.00012361858,0.00014307066,0.00025243306,0.00027141665,0.00037045244,0.0010415491],"category_scores_gemma":[0.00024258622,0.00014685804,0.00025613923,0.00017107901,0.0003898223,0.00036047542,0.00030177963,0.00018686593,0.00012477871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000259256,0.00007646917,0.004036749,0.00022588459,0.000039106653,0.00039647083,0.00032552305,0.28277203,0.64023113,0.041332405,0.0006482651,0.029656773],"study_design_scores_gemma":[0.000017393333,0.00012121788,0.0023495047,0.0000057947404,0.000004561019,0.0001269982,0.00004041966,0.97134084,0.02245167,0.0023846386,0.0011370883,0.000019934083],"about_ca_topic_score_codex":0.00074447755,"about_ca_topic_score_gemma":0.000769975,"teacher_disagreement_score":0.0010415491,"about_ca_system_score_codex":0.00026744636,"about_ca_system_score_gemma":0.0001953183,"threshold_uncertainty_score":0.0034843683},"labels":[],"label_agreement":null},{"id":"W2065882648","doi":"10.1115/1.1580852","title":"An Improved Time Domain Simulation for Dynamic Milling at Small Radial Immersions","year":2003,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":250,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Kinematics; Discretization; Vibration; Time domain; Immersion (mathematics); Deflection (physics); Stability (learning theory); Mechanics; Control theory (sociology); Dynamic simulation; Materials science; Computer science; Mathematics; Physics; Simulation; Mathematical analysis; Classical mechanics; Acoustics","score_opus":0.005407938519887931,"score_gpt":0.2206521650435262,"score_spread":0.21524422652363825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065882648","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08988313,0.00009365725,0.90127057,0.0001208935,0.000055003566,0.000074824755,0.00021228682,0.0009466041,0.0073430967],"genre_scores_gemma":[0.7905527,0.00017939818,0.2023172,0.000054485496,0.000016664255,0.0002451865,0.00035385683,0.00021636911,0.0060641924],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999881,0.000020289803,0.0000054723437,0.000012892987,0.00006784139,0.000012440057],"domain_scores_gemma":[0.999759,0.00011434679,0.000016513815,0.000029405104,0.00006743914,0.000013171863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002491147,0.0003683915,0.00048237244,0.00019577789,0.00023682439,0.00043125558,0.00069135736,0.00065952784,0.0026617555],"category_scores_gemma":[0.0007111026,0.00024358189,0.00041510307,0.00016413974,0.00025167703,0.0004731615,0.0002932291,0.00055251474,0.00037663823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003760219,0.000021829868,0.00022385722,0.000021234462,0.0000055545597,0.00003989531,0.000031645868,0.9809873,0.011670399,0.0021755206,0.00017845666,0.004606627],"study_design_scores_gemma":[0.000005499761,0.000006872938,0.000025932806,9.723759e-7,0.0000011109669,0.000004196789,0.0000015833677,0.9983664,0.0010925604,0.00010400005,0.00038903754,0.000001717232],"about_ca_topic_score_codex":0.0041997447,"about_ca_topic_score_gemma":0.0026049602,"teacher_disagreement_score":0.0041997447,"about_ca_system_score_codex":0.00036192976,"about_ca_system_score_gemma":0.00067096285,"threshold_uncertainty_score":0.008904517},"labels":[],"label_agreement":null},{"id":"W2065966048","doi":"10.4028/www.scientific.net/amr.1017.55","title":"An Experimental Study on Grinding Fir-Tree Root Forms Using Vitrified CBN Wheels","year":2014,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Grinding; Abrasive; Materials science; Surface roughness; Metallurgy; Mechanical engineering; Composite material; Engineering","score_opus":0.05536238581090959,"score_gpt":0.3943943300530784,"score_spread":0.3390319442421688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065966048","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99702364,0.00007833321,0.002467732,0.000004469922,0.000005457215,0.000030199652,0.0000432092,0.000019543022,0.00032739967],"genre_scores_gemma":[0.9867286,0.00009264011,0.011709865,0.000007739586,0.0000018252683,0.000018586104,0.00007243382,0.000016445096,0.0013518927],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997137,0.00001967436,0.000018870243,0.00007120917,0.00013901638,0.00003763713],"domain_scores_gemma":[0.9996402,0.00010231897,0.00006255176,0.00007195648,0.00009053899,0.000032304568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045177614,0.00025247037,0.0003887861,0.00020108122,0.00018247897,0.00022628762,0.00046414582,0.0003016824,0.0013803528],"category_scores_gemma":[0.00056821806,0.0001613786,0.00023359398,0.00016804533,0.0003198567,0.00019692311,0.00016515407,0.00031768956,0.00021490965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014371038,0.00004614026,0.0005164318,0.00005731306,0.0000023420116,0.00003688395,0.00006214947,0.0006034983,0.99618703,0.000034082,0.00001054319,0.002299845],"study_design_scores_gemma":[0.000025857913,0.0030355437,0.0107548935,0.000009214508,0.000014066348,0.00009679206,0.00009182353,0.004383205,0.9803862,0.000032462856,0.0011545025,0.00001539788],"about_ca_topic_score_codex":0.0012582798,"about_ca_topic_score_gemma":0.0037309527,"teacher_disagreement_score":0.0013803528,"about_ca_system_score_codex":0.00024090297,"about_ca_system_score_gemma":0.00022136953,"threshold_uncertainty_score":0.0046177506},"labels":[],"label_agreement":null},{"id":"W2066292330","doi":"10.1007/s00170-002-1452-6","title":"A solid modeler based ball-end milling process simulation","year":2003,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Ball (mathematics); End mill; Deflection (physics); Engineering; Mechanical engineering; Structural engineering; Enhanced Data Rates for GSM Evolution; Milling cutter; Machining; Geometry; Physics; Mathematics","score_opus":0.00836390495850415,"score_gpt":0.2823515992929467,"score_spread":0.27398769433444253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066292330","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19543618,0.00022652476,0.75065947,0.0003303969,0.00024721053,0.00053236214,0.0011221475,0.005817218,0.04562854],"genre_scores_gemma":[0.7837593,0.00022411508,0.2022066,0.000094377516,0.00003166963,0.0005716062,0.0009368786,0.00054065813,0.011634796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997023,0.00006173947,0.000017537028,0.00003594129,0.0001478239,0.00003468823],"domain_scores_gemma":[0.9993986,0.0003077982,0.00004870047,0.00007327698,0.00012810153,0.00004350495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000516607,0.0007394366,0.0012872295,0.0005182415,0.00081616745,0.0013704762,0.0018381823,0.0019768453,0.0098704845],"category_scores_gemma":[0.0010565248,0.00070920156,0.0009177611,0.00054273015,0.00048961927,0.0008467755,0.0008786174,0.0009988786,0.0011622388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006236011,0.00006896956,0.0002671189,0.000036826586,0.000018406367,0.000038974085,0.000028295226,0.9888598,0.002408582,0.0027954022,0.0002820507,0.0051333196],"study_design_scores_gemma":[0.000013454535,0.000015942007,0.000031501393,0.0000013441484,0.00000265376,0.0000033934402,0.0000022619051,0.99884087,0.0005253631,0.00019151485,0.00036870578,0.000002889461],"about_ca_topic_score_codex":0.008792202,"about_ca_topic_score_gemma":0.0064589228,"teacher_disagreement_score":0.0098704845,"about_ca_system_score_codex":0.0007423985,"about_ca_system_score_gemma":0.0014835169,"threshold_uncertainty_score":0.03302014},"labels":[],"label_agreement":null},{"id":"W2066355821","doi":"10.1115/1.2816104","title":"Substructure Coupling of Microend Mills to Aid in the Suppression of Chatter","year":2008,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Substructure; Coupling (piping); Frequency response; Displacement (psychology); Hammer; Mechanical engineering; Modal analysis; Dynamics (music); Engineering; Acoustics; Finite element method; Structural engineering; Materials science; Physics; Electrical engineering","score_opus":0.006495255031136362,"score_gpt":0.20645120231381942,"score_spread":0.19995594728268307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066355821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52281296,0.00011441564,0.4733053,0.00004416428,0.000033895238,0.00008890294,0.000013892482,0.00049044634,0.003096043],"genre_scores_gemma":[0.87130314,0.00005938417,0.12584949,0.000026084554,0.000008406256,0.000041872925,0.000024968009,0.000049872935,0.0026368282],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99972206,0.00003958472,0.000014586644,0.000052126703,0.00014935528,0.000022324324],"domain_scores_gemma":[0.9992778,0.00028347943,0.0001759751,0.00014625557,0.00008812582,0.000028411208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040952902,0.0003548011,0.00021834571,0.00023144356,0.000189531,0.00038259706,0.0006262273,0.0003349453,0.0016267954],"category_scores_gemma":[0.0010238839,0.00024431827,0.00021174559,0.00013567103,0.00043894158,0.00041908622,0.0004459607,0.00045209253,0.00029012543],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012937801,0.00011156698,0.0009393355,0.00006526924,0.000009578987,0.00024365286,0.00016595949,0.022647012,0.93859285,0.0034369624,0.000104772604,0.033553574],"study_design_scores_gemma":[0.000025455927,0.0008633137,0.0019423559,0.0000129457785,0.000014029209,0.0004171421,0.00004809096,0.2141495,0.7786856,0.0013194843,0.002500412,0.000021730917],"about_ca_topic_score_codex":0.00022520732,"about_ca_topic_score_gemma":0.0005360275,"teacher_disagreement_score":0.0016267954,"about_ca_system_score_codex":0.00018344773,"about_ca_system_score_gemma":0.00018467342,"threshold_uncertainty_score":0.0054421425},"labels":[],"label_agreement":null},{"id":"W2067134944","doi":"10.1080/10910340802523314","title":"NUMERICAL AND EXPERIMENTAL INVESTIGATION OF LASER-ASSISTED MACHINING OF INCONEL 718","year":2008,"lang":"en","type":"article","venue":"Machining Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"National Research Council Canada; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inconel; Machining; Materials science; Finite element method; Chip formation; Deformation (meteorology); Mechanical engineering; Heat transfer; Strain rate; Tool wear; Mechanics; Structural engineering; Metallurgy; Composite material; Engineering; Alloy; Physics","score_opus":0.009962738926227274,"score_gpt":0.23210609390628661,"score_spread":0.22214335498005933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067134944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99429154,0.00007062371,0.0037397693,0.000027789472,0.000005089113,0.000018142999,0.00007323394,0.00007618365,0.0016977161],"genre_scores_gemma":[0.9928993,0.000040761748,0.0065938006,0.0000049712276,0.0000010988347,0.00001825057,0.000048893904,0.0000066377506,0.0003863841],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997669,0.000026160984,0.00001293421,0.000035859044,0.00012380935,0.000034306468],"domain_scores_gemma":[0.9990434,0.000509156,0.00012738413,0.00011095151,0.00017453442,0.000034384648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003624952,0.00022592997,0.0004174027,0.00041263012,0.00044948896,0.00031043257,0.0006735258,0.00071825215,0.0012250405],"category_scores_gemma":[0.0010285297,0.00022441082,0.00019250996,0.00049798354,0.000553584,0.0002935102,0.0002041352,0.00027080506,0.00011814227],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005528367,0.00050216966,0.011427121,0.0004286973,0.00003720701,0.00079183857,0.0004990055,0.67131025,0.27938342,0.0021097006,0.000497614,0.03246024],"study_design_scores_gemma":[0.00005717018,0.0007772256,0.011195294,0.000015313828,0.00001879214,0.00019182831,0.00017520419,0.921975,0.06418056,0.0002786713,0.0010936673,0.00004130773],"about_ca_topic_score_codex":0.0029310836,"about_ca_topic_score_gemma":0.0047021513,"teacher_disagreement_score":0.0029310836,"about_ca_system_score_codex":0.00037648782,"about_ca_system_score_gemma":0.00034838647,"threshold_uncertainty_score":0.0058280826},"labels":[],"label_agreement":null},{"id":"W2067364586","doi":"10.1007/s00170-015-6979-4","title":"Modal analysis of spindles while accounting for system decay and its application to machine tool chatter prevention","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Machining; Stiffness; Machine tool; Modal; Natural frequency; Span (engineering); Engineering; Vibration; Modal analysis; Stability (learning theory); Life span; Process (computing); Structural engineering; Control theory (sociology); Mechanical engineering; Computer science; Acoustics; Finite element method; Materials science; Physics","score_opus":0.009620853663816542,"score_gpt":0.2611161387221141,"score_spread":0.25149528505829755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067364586","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2111924,0.00014864684,0.786142,0.000060780145,0.000020307782,0.000022371432,0.00004307554,0.0002668678,0.0021035348],"genre_scores_gemma":[0.9777649,0.00006486272,0.02094494,0.000007367478,0.0000060840357,0.000013023131,0.000032288983,0.000030575142,0.0011359622],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999876,0.000022976381,0.00000550333,0.000020158817,0.00005857391,0.00001679988],"domain_scores_gemma":[0.99952626,0.00020661164,0.000068777445,0.000045210818,0.00013906523,0.000014150468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032568694,0.00031382672,0.00029658983,0.00041267302,0.00025461672,0.00030053238,0.00038271124,0.0003336921,0.0013693463],"category_scores_gemma":[0.0012313566,0.00017678003,0.00032102127,0.00021709687,0.00024261513,0.00039743676,0.00030116513,0.0003920313,0.00015591366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060700177,0.00014168551,0.008682056,0.0003525251,0.00006877053,0.00031740486,0.00059396547,0.54786533,0.2306781,0.011811275,0.0010845994,0.19779734],"study_design_scores_gemma":[0.0000016001322,0.00002780862,0.0017415673,0.0000047479257,0.000005420187,0.000028325854,0.000029893736,0.993997,0.003529226,0.00044303722,0.00018667537,0.000004604754],"about_ca_topic_score_codex":0.0021366542,"about_ca_topic_score_gemma":0.0030807515,"teacher_disagreement_score":0.0021366542,"about_ca_system_score_codex":0.00014179577,"about_ca_system_score_gemma":0.00025371794,"threshold_uncertainty_score":0.0045809746},"labels":[],"label_agreement":null},{"id":"W2068433811","doi":"10.1007/s001700050013","title":"Integration of Milling Process Simulation with On-Line Monitoring and Control","year":2000,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Process (computing); Industrial and production engineering; Manufacturing engineering; Line (geometry); Control (management); Process control; Engineering; Computer science; Process engineering; Process management; Mechanical engineering; Artificial intelligence; Mathematics; Operating system","score_opus":0.007529202795813576,"score_gpt":0.2638644436619112,"score_spread":0.2563352408660976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068433811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12556475,0.00013353096,0.84714603,0.00016834916,0.00015727928,0.00022943506,0.00021209115,0.017262563,0.009125979],"genre_scores_gemma":[0.87801737,0.00010632046,0.118036404,0.0000858281,0.000031236435,0.0001784999,0.00031077748,0.00053825224,0.0026952657],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934024,0.00015743206,0.000044998702,0.000114442984,0.00027960094,0.000063263586],"domain_scores_gemma":[0.9982309,0.0008516301,0.00014787629,0.00032776108,0.0003440972,0.000097709686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000680532,0.0011642711,0.0012867834,0.0005180807,0.0003892547,0.0014283023,0.0017529816,0.0009445867,0.0042320257],"category_scores_gemma":[0.0022010114,0.0006471583,0.000583569,0.00034493886,0.00043877526,0.0009707268,0.0007322891,0.00093360146,0.000605284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051331375,0.0004993194,0.0029063113,0.0001318185,0.00013822882,0.00010584492,0.00013772838,0.89246565,0.0162353,0.002036174,0.0011168406,0.083713405],"study_design_scores_gemma":[0.000016153203,0.000036746165,0.00019411767,0.0000026197977,0.00000995541,0.0000105763565,0.000004727293,0.99492294,0.0039724656,0.00031135386,0.00051127834,0.0000070469587],"about_ca_topic_score_codex":0.0075007984,"about_ca_topic_score_gemma":0.0044397064,"teacher_disagreement_score":0.0075007984,"about_ca_system_score_codex":0.00053842063,"about_ca_system_score_gemma":0.0010804536,"threshold_uncertainty_score":0.014914274},"labels":[],"label_agreement":null},{"id":"W2069337792","doi":"10.1007/s00170-012-4479-3","title":"Modeling of burr thickness in milling of ductile materials","year":2012,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Enhanced Data Rates for GSM Evolution; Materials science; Mechanical engineering; Scanning electron microscope; Sensitivity (control systems); Work (physics); Machining; Yield (engineering); Characterization (materials science); Process (computing); Engineering drawing; Composite material; Engineering; Computer science; Nanotechnology","score_opus":0.008545733691823909,"score_gpt":0.24424864391008835,"score_spread":0.23570291021826445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069337792","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6220569,0.0019884026,0.3407237,0.0004385994,0.00010573472,0.00016236755,0.00042839046,0.00072781765,0.033368204],"genre_scores_gemma":[0.9819449,0.00037819287,0.012526442,0.000022001272,0.000008210337,0.000039369686,0.00007290029,0.00007525566,0.0049328147],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998017,0.000047456997,0.000009561591,0.000036241017,0.00006582434,0.000039336628],"domain_scores_gemma":[0.99928015,0.00042058202,0.00011422806,0.00005867297,0.00009070676,0.000035720925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005465176,0.0005662342,0.0007086168,0.00042043952,0.00047765076,0.0010906601,0.0011558149,0.0016665641,0.0022833017],"category_scores_gemma":[0.0014140899,0.0007684606,0.0005541505,0.00046160675,0.0005666326,0.00091371953,0.00035884298,0.00055590284,0.00032797302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020399639,0.000015528689,0.0002738105,0.000024595236,0.0000043494892,0.000043516073,0.000016402408,0.9951284,0.0020778792,0.00093505887,0.00005588001,0.0014041542],"study_design_scores_gemma":[0.00000378908,0.000013009923,0.00019456193,0.0000026450023,0.0000024154647,0.0000106982625,0.0000053202775,0.9987779,0.0007095815,0.00015651317,0.00012018903,0.0000032987195],"about_ca_topic_score_codex":0.007825442,"about_ca_topic_score_gemma":0.0062310193,"teacher_disagreement_score":0.007825442,"about_ca_system_score_codex":0.0010021381,"about_ca_system_score_gemma":0.00092496746,"threshold_uncertainty_score":0.0155597925},"labels":[],"label_agreement":null},{"id":"W2069484705","doi":"10.1115/imece2014-39307","title":"Design of a Retrofittable Spindle Attachment for High Frequency Vibration-Assisted Drilling","year":2014,"lang":"en","type":"article","venue":"Volume 2A: Advanced Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Vibration; Actuator; Thrust; Slip ring; Acoustics; Drilling; Mechanical engineering; Amplitude; Engineering; Power (physics); Materials science; Electrical engineering; Physics; Optics","score_opus":0.010485695475446439,"score_gpt":0.22506696911095095,"score_spread":0.2145812736355045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069484705","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46392882,0.0007036048,0.5258005,0.00021627665,0.0003818582,0.0006929524,0.00033391404,0.0026582587,0.0052837944],"genre_scores_gemma":[0.7937239,0.0002590466,0.19973892,0.00009986907,0.000067922774,0.00022196957,0.00021574143,0.000082673956,0.0055900244],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996258,0.000023604565,0.000024330036,0.000097968266,0.0001925552,0.00003573403],"domain_scores_gemma":[0.99940264,0.00005329536,0.00017349423,0.000059029728,0.00024513574,0.0000663536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036176987,0.000689282,0.00047875798,0.0007266994,0.00016992181,0.0003671318,0.0015410997,0.00081196654,0.0019651833],"category_scores_gemma":[0.00039441092,0.00048329364,0.00028384358,0.00027178225,0.00022705548,0.0003301584,0.00041305475,0.0003449997,0.0013430716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026043702,0.000093822804,0.0016400336,0.00034273494,0.000020289426,0.0006790697,0.00013023759,0.0028099464,0.91944975,0.00071329606,0.00079240836,0.07306799],"study_design_scores_gemma":[0.00052584993,0.012019005,0.050068513,0.00011811464,0.00022355023,0.0085385535,0.00023771849,0.12972827,0.7372237,0.0005256353,0.060494777,0.0002963984],"about_ca_topic_score_codex":0.0003007769,"about_ca_topic_score_gemma":0.000491738,"teacher_disagreement_score":0.0019651833,"about_ca_system_score_codex":0.00017630246,"about_ca_system_score_gemma":0.0003109278,"threshold_uncertainty_score":0.0065742135},"labels":[],"label_agreement":null},{"id":"W2069528629","doi":"10.1016/j.cirp.2008.03.048","title":"Identification of dynamic cutting force coefficients and chatter stability with process damping","year":2008,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":348,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Sandvik Coromant","keywords":"Acceleration; Control theory (sociology); Process (computing); Nyquist stability criterion; Machine tool; Stability (learning theory); Engineering; Cutting tool; Servo; Structural engineering; Mechanical engineering; Computer science; Mathematics; Physics; Classical mechanics","score_opus":0.016892360455651376,"score_gpt":0.2667385789488624,"score_spread":0.249846218493211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069528629","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07107192,0.000108326436,0.9266219,0.000047964153,0.000014539824,0.000029857494,0.000013950912,0.000121842095,0.0019697463],"genre_scores_gemma":[0.9292546,0.00009575459,0.0683488,0.000015127504,0.000011117852,0.000065953165,0.00003537994,0.000040524403,0.0021327254],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963033,0.00010366265,0.000016038635,0.00007019539,0.00014809913,0.000031574462],"domain_scores_gemma":[0.997846,0.0014461887,0.00018643601,0.00014447438,0.00033990815,0.00003699583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009894511,0.000843252,0.0005834845,0.00059584476,0.00026358664,0.0006142047,0.0007275441,0.000763472,0.0011661607],"category_scores_gemma":[0.00509769,0.00048761416,0.00038127557,0.00026342587,0.0005400517,0.0009130534,0.0007909716,0.0007302455,0.00021910107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054857106,0.00014368272,0.0026825757,0.00038193725,0.00008086217,0.0002081198,0.00040642003,0.7388061,0.09112994,0.020822939,0.00045554622,0.14433326],"study_design_scores_gemma":[0.000013410651,0.000045285084,0.00051714753,0.00000833697,0.0000089098685,0.000040385738,0.000011715276,0.9910398,0.006614872,0.0015123956,0.00017924506,0.000008497738],"about_ca_topic_score_codex":0.0009347555,"about_ca_topic_score_gemma":0.0011126212,"teacher_disagreement_score":0.0011661607,"about_ca_system_score_codex":0.00022168193,"about_ca_system_score_gemma":0.00043049656,"threshold_uncertainty_score":0.005232811},"labels":[],"label_agreement":null},{"id":"W2069793359","doi":"10.1016/j.asoc.2015.01.059","title":"Prediction of surface roughness during hard turning of AISI 4340 steel (69 HRC)","year":2015,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":170,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University","keywords":"Surface roughness; Materials science; Metallurgy; Surface finish; Environmental science; Composite material","score_opus":0.018674115295325283,"score_gpt":0.21859431653526984,"score_spread":0.19992020123994456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069793359","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99853945,0.000033455202,0.00084764976,0.0000105096415,0.000009853649,0.000003560542,0.000081785474,0.00006277446,0.00041089093],"genre_scores_gemma":[0.99927396,0.00000914208,0.00033852985,0.0000018983419,9.660248e-7,0.0000012676558,0.00010184716,0.0000049431014,0.000267457],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989617,0.0000064525725,0.000002796231,0.000020963676,0.000035653473,0.000038017337],"domain_scores_gemma":[0.9997224,0.00010845829,0.000026217062,0.00001805567,0.00008785022,0.000036962607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013663682,0.00035904933,0.00036156888,0.00047874585,0.00036493887,0.000417106,0.00023706093,0.00054573704,0.00076642784],"category_scores_gemma":[0.00028994653,0.00020194199,0.00040419295,0.00018806495,0.0001858552,0.00012586209,0.00015324279,0.00034204812,0.0001619176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027722034,0.0005625261,0.07378429,0.0002234595,0.00011069426,0.00086539006,0.000382909,0.43992022,0.42978057,0.00032257088,0.0023679754,0.048907176],"study_design_scores_gemma":[0.000021948563,0.0008619967,0.1496734,0.000007558488,0.00003124087,0.000078469835,0.00021649837,0.79250264,0.056043573,0.00007284378,0.00045208537,0.000037739424],"about_ca_topic_score_codex":0.020671848,"about_ca_topic_score_gemma":0.02204432,"teacher_disagreement_score":0.020671848,"about_ca_system_score_codex":0.00036464343,"about_ca_system_score_gemma":0.00037632618,"threshold_uncertainty_score":0.041103065},"labels":[],"label_agreement":null},{"id":"W2070137110","doi":"10.1115/1.4002454","title":"Identification of Material Constitutive Laws for Machining—Part I: An Analytical Model Describing the Stress, Strain, Strain Rate, and Temperature Fields in the Primary Shear Zone in Orthogonal Metal Cutting","year":2010,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Constitutive equation; Machining; Plasticity; Finite element method; Materials science; Strain rate; Deformation (meteorology); Shear (geology); Residual stress; Shear stress; Mechanics; Structural engineering; Mechanical engineering; Engineering; Composite material; Metallurgy","score_opus":0.01612445920819597,"score_gpt":0.23999705316997663,"score_spread":0.22387259396178066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070137110","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028700255,0.002048133,0.9611128,0.0002629136,0.00008149385,0.00012138588,0.00009629778,0.000160078,0.007416746],"genre_scores_gemma":[0.6911804,0.00538957,0.2868528,0.00017134682,0.00017239056,0.00080994953,0.0003324107,0.0001478593,0.014943225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963987,0.000052427218,0.000016195381,0.000055602468,0.00021368948,0.000022205562],"domain_scores_gemma":[0.99976724,0.00008560502,0.000059002065,0.00002892661,0.000052483378,0.0000067683986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058013346,0.00065754337,0.00059053564,0.00053295266,0.00034473828,0.0008776041,0.00118157,0.0010945111,0.000539192],"category_scores_gemma":[0.00086705934,0.00057231466,0.0006502793,0.00053562864,0.00091743364,0.0012087385,0.00042742887,0.0008578104,0.0003257242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003689926,0.00014222249,0.0010318827,0.00030302742,0.000017359373,0.00024143077,0.00031657954,0.7880038,0.06224854,0.09127203,0.0014690663,0.054917168],"study_design_scores_gemma":[0.0000058401083,0.000036284837,0.00045183278,0.000020082241,0.000008023536,0.00011938849,0.000020159341,0.9817485,0.005808928,0.0068449816,0.0049214447,0.000014498253],"about_ca_topic_score_codex":0.0016565867,"about_ca_topic_score_gemma":0.0014932106,"teacher_disagreement_score":0.0016565867,"about_ca_system_score_codex":0.00073656783,"about_ca_system_score_gemma":0.001027063,"threshold_uncertainty_score":0.0053441525},"labels":[],"label_agreement":null},{"id":"W2071316369","doi":"10.5963/amsa0301003","title":"Experimental Investigation on the Effect of Pre-holes on Drilling Process Performance of Aluminum Alloys: Forces, Surface Finish and Dust Emission","year":2014,"lang":"en","type":"article","venue":"Advances in Materials Science and Applications","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut de recherche Robert-Sauvé en santé et en sécurité du travail; École de Technologie Supérieure","funders":"","keywords":"Materials science; Aluminium; Drilling; Metallurgy; Process (computing); Surface roughness; Surface (topology); Surface finish; Composite material; Computer science; Geometry","score_opus":0.006276937208291727,"score_gpt":0.2555741582998374,"score_spread":0.24929722109154565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071316369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99823195,0.00016426572,0.0012583914,0.00000883818,0.000008893766,0.000023330118,0.00007281514,0.000023421117,0.00020805829],"genre_scores_gemma":[0.99487853,0.00018232402,0.0042617163,0.000007736296,0.0000046701794,0.000025456657,0.000088903056,0.000014445682,0.0005362027],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994412,0.0000642281,0.000069034366,0.000086002205,0.00025060805,0.000088948684],"domain_scores_gemma":[0.9980844,0.0007719106,0.0003480654,0.00021224646,0.0005221837,0.000061236846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005320279,0.00054007774,0.0004877734,0.00031685806,0.00027976118,0.00023659895,0.00038372813,0.00058495783,0.0013070774],"category_scores_gemma":[0.0013665381,0.0003192243,0.00027721096,0.0002809011,0.00036734377,0.00034828106,0.00026597833,0.00033311517,0.00017551916],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055090815,0.00013531862,0.0013516115,0.00021516229,0.0000085697175,0.00008066385,0.0001484643,0.00053325924,0.9929455,0.000028196675,0.00003142172,0.0039710333],"study_design_scores_gemma":[0.000017628063,0.0026836977,0.011105271,0.0000084593285,0.000020276875,0.000091851194,0.00009961695,0.0010626233,0.9842992,0.000023410454,0.0005745846,0.0000133749345],"about_ca_topic_score_codex":0.0004893554,"about_ca_topic_score_gemma":0.0011493284,"teacher_disagreement_score":0.0013070774,"about_ca_system_score_codex":0.00015758166,"about_ca_system_score_gemma":0.00019086593,"threshold_uncertainty_score":0.0043725967},"labels":[],"label_agreement":null},{"id":"W2071782538","doi":"10.5267/j.msl.2015.2.010","title":"Surface roughness and cutting force estimation in the CNC turning using artificial neural networks","year":2015,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Surface roughness; Artificial neural network; Machinability; Machining; Surface finish; Noise (video); RADIUS; Process (computing); Mechanical engineering; Computer science; Materials science; Engineering; Artificial intelligence; Composite material","score_opus":0.021851896657303502,"score_gpt":0.26121500030684036,"score_spread":0.23936310364953686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071782538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8693972,0.00042786406,0.12657548,0.00011512445,0.00004105488,0.00003899659,0.000080276135,0.00036397608,0.0029600868],"genre_scores_gemma":[0.99497074,0.000052161995,0.004591571,0.000009037663,0.0000035166038,0.00001037894,0.00004465325,0.0000044103303,0.00031343795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979824,0.000033859375,0.000013299872,0.000044931312,0.00007436517,0.000035240697],"domain_scores_gemma":[0.9994954,0.00022842809,0.000055030432,0.000026613972,0.0001774958,0.000016917644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005291523,0.0005138999,0.00050425594,0.0006463092,0.00023776696,0.00044512865,0.00034568843,0.0006587765,0.0003391603],"category_scores_gemma":[0.0011636402,0.00030266825,0.00034407177,0.0003882563,0.00021710762,0.0003318859,0.00017543501,0.00045534258,0.00008465727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032229518,0.00010923165,0.010133386,0.000082267405,0.000038348597,0.00014378935,0.000065099295,0.8871432,0.01490783,0.00018653777,0.00031858345,0.086549416],"study_design_scores_gemma":[0.000002748352,0.000026450907,0.0035845016,0.0000031966933,0.000005547876,0.000009194811,0.000009692873,0.9948949,0.0013599377,0.000058515183,0.000040319086,0.000004968874],"about_ca_topic_score_codex":0.015941137,"about_ca_topic_score_gemma":0.0119673945,"teacher_disagreement_score":0.015941137,"about_ca_system_score_codex":0.00044699298,"about_ca_system_score_gemma":0.00031070763,"threshold_uncertainty_score":0.031696737},"labels":[],"label_agreement":null},{"id":"W2072388321","doi":"10.1016/j.cirp.2012.03.004","title":"An energy based analysis of broaching operation: Cutting forces and resultant surface integrity","year":2012,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Broaching; Surface integrity; Machining; Mechanical engineering; Indentation hardness; Surface (topology); Structural engineering; Materials science; Microstructure; Engineering; Metallurgy; Geometry; Mathematics","score_opus":0.027607195743848047,"score_gpt":0.2998189772917522,"score_spread":0.27221178154790415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072388321","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6073606,0.0004948507,0.3735293,0.00017885244,0.000049413247,0.000057157533,0.00008982037,0.0001754485,0.018064633],"genre_scores_gemma":[0.9829474,0.00014592432,0.010052625,0.000017073797,0.0000067315186,0.00001737477,0.000058335525,0.00006913833,0.006685507],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99983394,0.000019047615,0.0000058598566,0.000020827545,0.00009097063,0.000029314628],"domain_scores_gemma":[0.99980384,0.00008056864,0.000027240885,0.00002260206,0.000055716006,0.000010042755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003219263,0.00047476782,0.0005299675,0.00071450416,0.00045674824,0.0007485157,0.00087677466,0.0009639978,0.0026552773],"category_scores_gemma":[0.00073889806,0.00030738857,0.0005346523,0.00046733668,0.000567975,0.00072153157,0.0004088803,0.0005768261,0.00036858418],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017855593,0.00011591896,0.0027435112,0.000084858526,0.000032846237,0.0002209964,0.00007628739,0.9161686,0.04299911,0.006520809,0.00028354532,0.030574916],"study_design_scores_gemma":[0.0000017487537,0.00002620304,0.0017651407,0.0000028448976,0.0000062030576,0.000030183483,0.000017467744,0.9949563,0.0026152763,0.00045909418,0.00011464812,0.000004854875],"about_ca_topic_score_codex":0.003351199,"about_ca_topic_score_gemma":0.0038436812,"teacher_disagreement_score":0.003351199,"about_ca_system_score_codex":0.00042120833,"about_ca_system_score_gemma":0.00039964434,"threshold_uncertainty_score":0.008882761},"labels":[],"label_agreement":null},{"id":"W2072849927","doi":"10.1016/j.ijmecsci.2015.03.015","title":"Application of a new thick zone model to the cutting mechanics during end-milling","year":2015,"lang":"en","type":"article","venue":"International Journal of Mechanical Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Thrust; Machining; Mechanical engineering; Nonlinear system; Mechanics; Constitutive equation; Engineering; Structural engineering; Finite element method; Physics","score_opus":0.03195959223779378,"score_gpt":0.30231987218411505,"score_spread":0.2703602799463213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072849927","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09105816,0.00047304723,0.8975282,0.00015128555,0.0001556142,0.00010137314,0.00010286883,0.0003272006,0.010102339],"genre_scores_gemma":[0.91405916,0.00047539594,0.07177115,0.00005912165,0.000050027294,0.00015700056,0.00014009043,0.00020028617,0.013087766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981433,0.00004142295,0.000011793656,0.000034665165,0.00007446445,0.000023373519],"domain_scores_gemma":[0.9996681,0.00013421733,0.000050529845,0.0000405361,0.00008061359,0.00002599531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005036802,0.0008274536,0.0008493314,0.00047088883,0.0005151179,0.0010394473,0.0015576473,0.0017078618,0.002494939],"category_scores_gemma":[0.0009873789,0.00066865864,0.000687902,0.00047006292,0.00067156355,0.0012868011,0.0007888738,0.0009362748,0.0003739052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004723057,0.000043350963,0.00030012403,0.000044774824,0.0000096301255,0.000058663696,0.000037364025,0.98091185,0.00949556,0.0038665482,0.00013262877,0.005052234],"study_design_scores_gemma":[0.000005286782,0.000015018,0.00008785376,0.0000020248215,0.0000021183307,0.000007301682,0.000004207351,0.9988851,0.0004843459,0.0002884969,0.00021452419,0.000003798793],"about_ca_topic_score_codex":0.004882467,"about_ca_topic_score_gemma":0.0033039434,"teacher_disagreement_score":0.004882467,"about_ca_system_score_codex":0.00045003067,"about_ca_system_score_gemma":0.0008548048,"threshold_uncertainty_score":0.009708047},"labels":[],"label_agreement":null},{"id":"W2073164081","doi":"10.1016/s0890-6955(02)00277-8","title":"Mechanics of boring processes—Part II—multi-insert boring heads","year":2003,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Insert (composites); Mechanical engineering; Enhanced Data Rates for GSM Evolution; Process (computing); Mechanics; Head (geology); Engineering; Kinematics; Mach number; Structural engineering; Engineering drawing; Physics; Computer science; Geology; Classical mechanics","score_opus":0.012511016410707843,"score_gpt":0.25043042097673535,"score_spread":0.2379194045660275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073164081","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61368257,0.008170759,0.31625745,0.001150676,0.00042083114,0.0002708549,0.00036150732,0.0003831485,0.059302226],"genre_scores_gemma":[0.97944504,0.0012287856,0.005100434,0.000037217535,0.00006164682,0.000048536185,0.00008528315,0.000059908245,0.013933037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979883,0.000027722712,0.000008793752,0.0000339612,0.0000903372,0.000040350926],"domain_scores_gemma":[0.9997768,0.00010794401,0.000046555426,0.000025100473,0.000030304045,0.000013309344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019339287,0.00026374703,0.00047543313,0.0003777029,0.00044288588,0.0009588243,0.00081554113,0.0005077963,0.006968899],"category_scores_gemma":[0.000589536,0.0004579668,0.00037427148,0.00034808088,0.000785998,0.0008746769,0.00060885015,0.000397911,0.0006981529],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052003935,0.00024217946,0.004101264,0.0007570462,0.00006771943,0.0007518173,0.0005950068,0.5389368,0.274531,0.09548175,0.00351258,0.080502845],"study_design_scores_gemma":[0.00011231007,0.00063612696,0.034474585,0.00006616581,0.00006510603,0.0009578364,0.0006743895,0.8394383,0.075566374,0.02621829,0.021673348,0.00011714282],"about_ca_topic_score_codex":0.00051220687,"about_ca_topic_score_gemma":0.0006200836,"teacher_disagreement_score":0.006968899,"about_ca_system_score_codex":0.0002540452,"about_ca_system_score_gemma":0.00030059973,"threshold_uncertainty_score":0.023313224},"labels":[],"label_agreement":null},{"id":"W2073548243","doi":"10.1016/s1526-6125(03)70045-0","title":"Surface Finish Enhancement in a Turning Operation via PID Control of the Depth of Cut","year":2003,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"PID controller; Control theory (sociology); Materials science; Controller (irrigation); Displacement (psychology); Process (computing); Surface (topology); Control (management); Mechanical engineering; Engineering; Computer science; Mathematics; Temperature control; Geometry; Artificial intelligence","score_opus":0.00741936718140134,"score_gpt":0.22260538108518263,"score_spread":0.21518601390378128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073548243","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9505971,0.00024558912,0.044817574,0.000076766875,0.00006465097,0.000022278351,0.000025752752,0.0002720958,0.0038781099],"genre_scores_gemma":[0.99701,0.000029233726,0.0024914206,0.000006884486,0.000003269861,0.000001966402,0.0000057665006,0.000007978576,0.0004432879],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99992454,0.0000069447237,0.000003111161,0.000016981981,0.000022767223,0.000025693751],"domain_scores_gemma":[0.99979764,0.00008853838,0.00002812259,0.000017169057,0.000041530715,0.000027068376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013809689,0.00020560631,0.00030729128,0.00020624087,0.00020371714,0.00036806084,0.00021515017,0.00027677655,0.0009327209],"category_scores_gemma":[0.00034308978,0.00015368604,0.00015047498,0.00011367773,0.00021738932,0.00020025944,0.00020256374,0.00025959424,0.00010583409],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009919476,0.00004741578,0.00071450777,0.00006142954,0.000008223839,0.00013425639,0.000065489905,0.004825741,0.9704772,0.0003453984,0.0001372843,0.022191143],"study_design_scores_gemma":[0.00012150707,0.0013547651,0.016955176,0.000015080948,0.00006178567,0.0003811616,0.00012550576,0.13596341,0.8424839,0.000645692,0.001846469,0.00004547378],"about_ca_topic_score_codex":0.0005560004,"about_ca_topic_score_gemma":0.0007994708,"teacher_disagreement_score":0.0009327209,"about_ca_system_score_codex":0.0001428358,"about_ca_system_score_gemma":0.00013951909,"threshold_uncertainty_score":0.0031202435},"labels":[],"label_agreement":null},{"id":"W2073561110","doi":"10.1016/j.procir.2013.06.066","title":"Finite Element-based Modeling of Machining-induced Residual Stresses in Ti-6Al-4V under Finish Turning Conditions","year":2013,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"","keywords":"Residual stress; Machining; Materials science; Finite element method; Enhanced Data Rates for GSM Evolution; Surface integrity; Titanium alloy; Residual; RADIUS; Surface roughness; Cutting tool; Composite material; Structural engineering; Mechanical engineering; Metallurgy; Alloy; Engineering; Computer science","score_opus":0.01616516015510692,"score_gpt":0.24634087827626103,"score_spread":0.23017571812115412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073561110","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68728995,0.00044567697,0.29153594,0.00022690266,0.000064004016,0.00017478352,0.00057990855,0.0006476113,0.019035222],"genre_scores_gemma":[0.98098755,0.00015675863,0.015121683,0.000019350084,0.0000046596715,0.000113010385,0.00017811936,0.00003997126,0.0033789128],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985766,0.000025826828,0.000009108838,0.000021663973,0.00006079364,0.000024931182],"domain_scores_gemma":[0.9997646,0.000113082955,0.00003949221,0.000022207529,0.00004809097,0.000012541284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032209148,0.00042715154,0.00059922197,0.00049239164,0.00035877374,0.0006800752,0.0010581344,0.0014159145,0.0018349132],"category_scores_gemma":[0.0006196142,0.00047813132,0.00069895206,0.00030696273,0.0005605972,0.00030403215,0.00032917433,0.0004277197,0.00031635788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028238595,0.000027251486,0.0004697628,0.000023382103,0.0000059654926,0.00004098563,0.00003599746,0.99215955,0.0050195223,0.00046183474,0.000041318668,0.0016861868],"study_design_scores_gemma":[0.000002940746,0.000014906906,0.00020055543,0.0000026969028,0.000002224161,0.0000065638105,0.000008766167,0.9989465,0.0006567849,0.000057477137,0.00009760718,0.0000029962998],"about_ca_topic_score_codex":0.0112674115,"about_ca_topic_score_gemma":0.008203476,"teacher_disagreement_score":0.0112674115,"about_ca_system_score_codex":0.00058136805,"about_ca_system_score_gemma":0.0008399752,"threshold_uncertainty_score":0.022403657},"labels":[],"label_agreement":null},{"id":"W2073786083","doi":"10.1115/imece2012-86201","title":"Analysys and Optimization of Exit Burr Size and Surface Roughness in Milling Using Desireability Function","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Surface roughness; Machining; Materials science; Surface finish; Mechanical engineering; Coating; Alloy; Minification; Selection (genetic algorithm); Composite material; Engineering drawing; Metallurgy; Computer science; Mathematics; Mathematical optimization; Engineering","score_opus":0.017934991896859806,"score_gpt":0.2431086225280112,"score_spread":0.22517363063115137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073786083","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85796887,0.00027377577,0.14036714,0.00003071102,0.000004507622,0.000030438565,0.00004015853,0.00015949612,0.0011249153],"genre_scores_gemma":[0.9772255,0.00007602528,0.022201365,0.0000034289296,0.0000012133277,0.000021410444,0.000040869658,0.000022129048,0.00040807738],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99968433,0.00007717221,0.000019678266,0.000046832985,0.00014390262,0.000028059636],"domain_scores_gemma":[0.99925417,0.0005233465,0.000092008544,0.00003839212,0.0000822745,0.0000098512455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007485753,0.00037233075,0.00028011962,0.00032835724,0.00010101496,0.00024402334,0.00016987823,0.0002654367,0.00030185157],"category_scores_gemma":[0.001145683,0.00014048172,0.00027293208,0.00022178466,0.00014656875,0.00022055756,0.0001023339,0.00017395268,0.000062750456],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004647845,0.00021562852,0.009152508,0.00022675845,0.00004618112,0.00010287026,0.00013445581,0.26645678,0.62387675,0.0011054544,0.00016003015,0.098057866],"study_design_scores_gemma":[0.000025794196,0.0009451655,0.02122634,0.000006400911,0.000033255645,0.000117894975,0.000035292447,0.7465978,0.23015775,0.00022718526,0.00059982337,0.00002734601],"about_ca_topic_score_codex":0.00061721035,"about_ca_topic_score_gemma":0.00059530005,"teacher_disagreement_score":0.0007485753,"about_ca_system_score_codex":0.00017878965,"about_ca_system_score_gemma":0.00013379521,"threshold_uncertainty_score":0.003958881},"labels":[],"label_agreement":null},{"id":"W2074003021","doi":"10.1109/nafips.2010.5548197","title":"Acoustic emission signal feature analysis using type-2 fuzzy logic System","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Feature (linguistics); SIGNAL (programming language); Estimator; Fuzzy logic; Mean squared error; Acoustic emission; Computer science; Process (computing); Pattern recognition (psychology); Artificial intelligence; Algorithm; Mathematics; Acoustics; Statistics","score_opus":0.008525606169164788,"score_gpt":0.24197994920417631,"score_spread":0.23345434303501153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074003021","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058951043,0.00009701143,0.93802357,0.000054582248,0.000023940418,0.00006616494,0.000055667653,0.0006730762,0.0020549016],"genre_scores_gemma":[0.83536845,0.0001105738,0.16270274,0.000038771694,0.000018228753,0.000100373916,0.000084727086,0.000026457148,0.001549699],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967396,0.00007704339,0.000021600028,0.00006929598,0.0001357091,0.000022347853],"domain_scores_gemma":[0.9997304,0.00011627184,0.000025862999,0.000015298438,0.00010520557,0.000006872024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042194157,0.00045355954,0.00039902722,0.0005700057,0.0003142105,0.0006084168,0.00037370692,0.00048486548,0.0013598942],"category_scores_gemma":[0.0009771641,0.00013584786,0.00043552654,0.000294237,0.00018817617,0.0005269952,0.00016536114,0.00027552096,0.00025525503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009925634,0.00017854407,0.0054760557,0.00041521646,0.00014139456,0.00041598617,0.00039820618,0.30960867,0.20516272,0.007242716,0.0013066693,0.4686612],"study_design_scores_gemma":[0.000020133271,0.0001262332,0.0014394626,0.000009900578,0.00002309729,0.00007667384,0.00002492939,0.98232377,0.01383706,0.0013563061,0.0007412949,0.000021086793],"about_ca_topic_score_codex":0.0031056893,"about_ca_topic_score_gemma":0.0020021086,"teacher_disagreement_score":0.0031056893,"about_ca_system_score_codex":0.0003653963,"about_ca_system_score_gemma":0.00027872898,"threshold_uncertainty_score":0.00617522},"labels":[],"label_agreement":null},{"id":"W2074369346","doi":"10.1016/s0007-8506(07)60372-2","title":"Modelling of Material Side Flow in Hard Turning","year":2006,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; University of New Brunswick","funders":"","keywords":"Viscoplasticity; Flow (mathematics); RADIUS; Materials science; Finite element method; Mechanics; Scanning electron microscope; Material flow; Mechanical engineering; Surface (topology); Engineering drawing; Engineering; Structural engineering; Composite material; Computer science; Geometry; Physics; Mathematics","score_opus":0.02514451491967294,"score_gpt":0.23549682539495026,"score_spread":0.2103523104752773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074369346","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6097661,0.0029383842,0.29395083,0.0008836776,0.00049921265,0.00015274443,0.0003203598,0.00046525942,0.0910235],"genre_scores_gemma":[0.98440313,0.00048703625,0.0042570517,0.000038706596,0.000029841814,0.000036390727,0.000077975084,0.00006507362,0.010604803],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984014,0.0000456535,0.000005608671,0.00002058251,0.00003459509,0.000053487063],"domain_scores_gemma":[0.99963605,0.00020701205,0.00003466107,0.000021593689,0.000047313937,0.00005337516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031368074,0.0007989826,0.001273203,0.0007587788,0.00070523244,0.0018500922,0.0010363094,0.0020566296,0.003967038],"category_scores_gemma":[0.0010927937,0.00073698384,0.0010264487,0.00043818468,0.0013019249,0.00087138684,0.0008826796,0.0010500266,0.00039043187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043160213,0.000015115172,0.00014547566,0.000019054269,0.0000056039266,0.00006828394,0.00001949549,0.9929848,0.0010642193,0.004492316,0.000096759286,0.0010458787],"study_design_scores_gemma":[0.000008064088,0.000013581877,0.00012645892,0.0000036503602,0.0000027620008,0.000011826311,0.0000107610485,0.9982293,0.00022981165,0.0011378151,0.0002216517,0.0000043013974],"about_ca_topic_score_codex":0.01328641,"about_ca_topic_score_gemma":0.006656655,"teacher_disagreement_score":0.01328641,"about_ca_system_score_codex":0.0010021625,"about_ca_system_score_gemma":0.00094776804,"threshold_uncertainty_score":0.02641815},"labels":[],"label_agreement":null},{"id":"W2075554123","doi":"10.1115/imece2002-32037","title":"Dynamic Compensation of Cutting Forces Measured From the Spindle Integrated Force Sensor System","year":2002,"lang":"en","type":"article","venue":"Dynamic Systems and Control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Acceleration; Kalman filter; Compensation (psychology); Bandwidth (computing); SIGNAL (programming language); Contact force; Signal processing; Acoustics; Engineering; Control theory (sociology); Computer science; Electronic engineering; Physics; Digital signal processing","score_opus":0.005771575259250661,"score_gpt":0.1865342643595201,"score_spread":0.18076268910026946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075554123","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41545808,0.00059256156,0.575861,0.0001975014,0.00020276064,0.000095768024,0.00030629698,0.001772355,0.005513677],"genre_scores_gemma":[0.9500922,0.00017105327,0.04783033,0.000058514546,0.00003712182,0.000056018554,0.00022453285,0.000029040071,0.001501115],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995252,0.000031705837,0.000017323086,0.000078547346,0.00030854702,0.000038670376],"domain_scores_gemma":[0.99967027,0.000063518775,0.000046970003,0.000033316883,0.00017194683,0.000013980197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002491976,0.0004845806,0.00043178047,0.00055865647,0.00019947314,0.00035443905,0.0004925226,0.00047694508,0.0009821006],"category_scores_gemma":[0.0010350045,0.0002096225,0.00012544058,0.00032905606,0.00014349351,0.00039140825,0.00021867553,0.00031879364,0.00026230782],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004671402,0.00009772891,0.004985938,0.00023803074,0.000034724897,0.00017441045,0.00021436777,0.015773278,0.6802373,0.0010540297,0.0012881362,0.2954349],"study_design_scores_gemma":[0.00013019804,0.0012425932,0.05251419,0.000057861434,0.00008320652,0.0009402489,0.00012536747,0.37002355,0.5619034,0.00079425256,0.012079661,0.00010548295],"about_ca_topic_score_codex":0.0013000105,"about_ca_topic_score_gemma":0.0020454952,"teacher_disagreement_score":0.0013000105,"about_ca_system_score_codex":0.00025581807,"about_ca_system_score_gemma":0.00027562972,"threshold_uncertainty_score":0.0032854676},"labels":[],"label_agreement":null},{"id":"W2075722502","doi":"10.1016/j.ijmachtools.2006.08.028","title":"Modelling of the stability of variable helix end mills","year":2006,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":112,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of Sheffield","keywords":"Helix (gastropod); Variable (mathematics); Stability (learning theory); Helix angle; Range (aeronautics); Machining; Control theory (sociology); Time domain; Engineering; Mathematics; Computer science; Mechanical engineering; Mathematical analysis; Artificial intelligence","score_opus":0.009067435674291146,"score_gpt":0.20674269741120305,"score_spread":0.1976752617369119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075722502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6680729,0.00048586665,0.30306318,0.00023767826,0.000059972066,0.00006413259,0.00014021278,0.00026408758,0.027611991],"genre_scores_gemma":[0.9912971,0.00009287521,0.00413843,0.000008961068,0.000006870689,0.00002092563,0.000033135577,0.000030098272,0.0043715304],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998265,0.00006586408,0.000006544223,0.000028331922,0.00004459503,0.000028261811],"domain_scores_gemma":[0.9994469,0.00032393812,0.00008209417,0.000036674017,0.00007547861,0.000034827324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056202564,0.0005122577,0.00073128456,0.0004627919,0.0005273613,0.001311669,0.00094718614,0.001516207,0.0030855779],"category_scores_gemma":[0.0013637177,0.00048201458,0.0005862254,0.00034471383,0.0009530363,0.0007582414,0.00057704415,0.0006150069,0.00037401268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048589343,0.000009820068,0.00016442973,0.000011482794,0.0000055891837,0.000030289595,0.000019932926,0.99475694,0.0015388393,0.0025238756,0.00003729754,0.00085285294],"study_design_scores_gemma":[0.0000056349577,0.000013828133,0.00011074546,0.0000015943893,0.0000016972476,0.0000044809626,0.000005350622,0.9989556,0.00028659706,0.00051082316,0.00010110248,0.0000025600243],"about_ca_topic_score_codex":0.004581752,"about_ca_topic_score_gemma":0.0018710626,"teacher_disagreement_score":0.004581752,"about_ca_system_score_codex":0.00069056544,"about_ca_system_score_gemma":0.0006255434,"threshold_uncertainty_score":0.010322332},"labels":[],"label_agreement":null},{"id":"W2076119837","doi":"10.1007/s00170-003-1794-8","title":"Modelling and experimental investigation of spindle and cutter dynamics for a high-precision machining center","year":2004,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Western University","funders":"National Research Council Canada","keywords":"Machining; Aerospace; Machine tool; Mechanical engineering; Engineering; Process (computing); Quality (philosophy); System dynamics; Computer science; Aerospace engineering; Artificial intelligence","score_opus":0.007035887563221823,"score_gpt":0.23624833013121319,"score_spread":0.22921244256799136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076119837","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9866491,0.00006205152,0.01119893,0.000042349933,0.000009746366,0.000045565892,0.00016724026,0.00027248147,0.0015524579],"genre_scores_gemma":[0.99729294,0.000026194488,0.00203055,0.0000026987705,9.802266e-7,0.000016577078,0.000072545256,0.000012143616,0.0005452797],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997564,0.000030677802,0.000011680271,0.00006038373,0.00010054827,0.000040243693],"domain_scores_gemma":[0.99931145,0.000317121,0.000074749005,0.00009780912,0.00015044848,0.000048470447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047504986,0.0004889202,0.00066473836,0.00026420082,0.0005550092,0.0005647716,0.0010485072,0.0011786399,0.002393847],"category_scores_gemma":[0.0007458413,0.00045133987,0.00040561537,0.00030405505,0.00046931795,0.00064758986,0.00024238092,0.00046490075,0.00035201854],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024914173,0.0010717395,0.015890662,0.00037421277,0.000052717758,0.0004795189,0.00062448316,0.513141,0.43894255,0.0009492066,0.00087818207,0.025104312],"study_design_scores_gemma":[0.00013084647,0.0012769687,0.018723067,0.000009595367,0.0000447279,0.00010159099,0.00012974394,0.8827415,0.095502675,0.00013678204,0.001159653,0.000042782354],"about_ca_topic_score_codex":0.0054686936,"about_ca_topic_score_gemma":0.0054930737,"teacher_disagreement_score":0.0054686936,"about_ca_system_score_codex":0.0006078424,"about_ca_system_score_gemma":0.00078884716,"threshold_uncertainty_score":0.010873735},"labels":[],"label_agreement":null},{"id":"W2076760958","doi":"10.1115/1.4000773","title":"A New Low-Frequency Resonance Sensor for Low Speed Roller Bearing Monitoring","year":2010,"lang":"en","type":"article","venue":"Journal of vibration and acoustics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Accelerometer; Bearing (navigation); Demodulation; Fault (geology); Vibration; Acoustics; SIGNAL (programming language); Mechanical resonance; Engineering; Condition monitoring; Resonance (particle physics); Rotational speed; Fault detection and isolation; Piezoelectric sensor; Piezoelectricity; Computer science; Electronic engineering; Electrical engineering; Mechanical engineering; Physics; Actuator","score_opus":0.007836443157929964,"score_gpt":0.24174335327489102,"score_spread":0.23390691011696105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076760958","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2527028,0.0064010317,0.7269736,0.00078658975,0.0010003375,0.00037660002,0.0005251379,0.004112288,0.007121589],"genre_scores_gemma":[0.6374313,0.0010029477,0.3546903,0.000413543,0.00025475372,0.00012736271,0.00025173006,0.00007135393,0.005756696],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990852,0.00010010439,0.000033541968,0.00017127076,0.0005689833,0.000040921503],"domain_scores_gemma":[0.9994235,0.00015699433,0.00011543579,0.00004769371,0.00020554608,0.000050913794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003720518,0.0005636877,0.00068910467,0.00060532405,0.00018680232,0.00040721544,0.0008963699,0.001067015,0.0014253489],"category_scores_gemma":[0.00072592765,0.00025696502,0.00018861805,0.00035399228,0.00032344018,0.0009530853,0.00032865288,0.0005396005,0.0007928091],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000100725636,0.000043846223,0.00062212296,0.00015405858,0.000007973584,0.00010249846,0.000039459555,0.00032980493,0.95208657,0.0003243665,0.00062535744,0.045563255],"study_design_scores_gemma":[0.000098517434,0.0014156089,0.0073765675,0.000040800922,0.00009027699,0.0023553611,0.00006144508,0.05834073,0.90708,0.00034929463,0.02265301,0.0001383026],"about_ca_topic_score_codex":0.00018836842,"about_ca_topic_score_gemma":0.0005009104,"teacher_disagreement_score":0.0014253489,"about_ca_system_score_codex":0.00025958952,"about_ca_system_score_gemma":0.00023121064,"threshold_uncertainty_score":0.004768312},"labels":[],"label_agreement":null},{"id":"W2077877553","doi":"10.1016/j.cirp.2014.03.127","title":"Magnetic actuator for active damping of boring bars","year":2014,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":76,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Actuator; Displacement (psychology); Bar (unit); Bending; Engineering; Stiffness; Structural engineering; Acoustics; Mechanical engineering; Physics; Electrical engineering","score_opus":0.015990849897790906,"score_gpt":0.2640122502943088,"score_spread":0.2480214003965179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077877553","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45960438,0.0025198124,0.4902907,0.00060761656,0.0005164659,0.00007728662,0.000118496144,0.0007597518,0.04550567],"genre_scores_gemma":[0.96766776,0.00028248836,0.023647118,0.000035842753,0.00005393771,0.00003561996,0.000039405,0.000032844262,0.0082050245],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999492,0.000011818532,0.0000016642763,0.000008768752,0.000019914969,0.000008583934],"domain_scores_gemma":[0.99993634,0.000025143894,0.000012492463,0.0000062653075,0.000012276485,0.0000074474206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011506946,0.00020572123,0.00022855222,0.00018058367,0.0002683444,0.00028050313,0.00033192828,0.0002389403,0.0043725693],"category_scores_gemma":[0.00019580012,0.00008946282,0.00012844322,0.00008015356,0.000181737,0.00015562432,0.00024717703,0.00024083682,0.00053476193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069304975,0.00009375026,0.00056932925,0.0005165846,0.000028333749,0.00012826467,0.00011825764,0.018863652,0.8751798,0.012639021,0.0022016529,0.08896824],"study_design_scores_gemma":[0.00031794282,0.0023087934,0.0062823016,0.00010546999,0.000090591566,0.00049126113,0.00019885521,0.66455126,0.27514452,0.0059901197,0.044472028,0.000046851863],"about_ca_topic_score_codex":0.00015658261,"about_ca_topic_score_gemma":0.00036291548,"teacher_disagreement_score":0.0043725693,"about_ca_system_score_codex":0.00009364502,"about_ca_system_score_gemma":0.00010649536,"threshold_uncertainty_score":0.014627695},"labels":[],"label_agreement":null},{"id":"W2078101084","doi":"10.1007/s10845-007-0038-4","title":"Finite element modeling of low speed reaming vibrations with reamer geometry modifications","year":2007,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"","keywords":"Reamer; Vibration; Finite element method; Structural engineering; Engineering; Acoustics; Mechanical engineering; Physics","score_opus":0.01572611735385083,"score_gpt":0.24782994119505994,"score_spread":0.23210382384120912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078101084","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34059864,0.00028392556,0.6368323,0.00018217198,0.00009394964,0.000088728935,0.00017413485,0.0006443835,0.02110178],"genre_scores_gemma":[0.9681414,0.000101956946,0.024169272,0.000023467122,0.000008090492,0.0000483739,0.000065398344,0.000072817405,0.007369291],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980944,0.00004914065,0.000008912867,0.000027483062,0.00008277611,0.000022171153],"domain_scores_gemma":[0.99971145,0.00013835396,0.000036765432,0.000041035262,0.00005848964,0.0000139247395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003287284,0.00046586827,0.0005715183,0.0004279251,0.0002758716,0.0006096381,0.0012154094,0.00142775,0.0034651554],"category_scores_gemma":[0.0008367773,0.0004956217,0.0005333852,0.00032873562,0.00048810948,0.00058832805,0.00034470478,0.00043527273,0.0005830375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005072739,0.000026645073,0.00027066492,0.000022821818,0.000008963776,0.000059793027,0.000049095313,0.98439157,0.0077456846,0.001180017,0.00012097071,0.006073052],"study_design_scores_gemma":[0.0000030434292,0.000017023778,0.00011450975,0.0000020444625,0.0000027656115,0.000010868869,0.000011597944,0.99878246,0.0007264937,0.0001114051,0.00021499734,0.0000028515162],"about_ca_topic_score_codex":0.0031563444,"about_ca_topic_score_gemma":0.0031673443,"teacher_disagreement_score":0.0034651554,"about_ca_system_score_codex":0.00034165496,"about_ca_system_score_gemma":0.0003596331,"threshold_uncertainty_score":0.01159209},"labels":[],"label_agreement":null},{"id":"W2078932163","doi":"10.1115/msec_icmp2008-72209","title":"Modeling and Analysis of the Thread Milling Operation in the Combined Drilling/Thread Milling Process","year":2008,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"University of Illinois at Urbana-Champaign; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Thread (computing); Helix angle; Drilling; Torque; Mechanical engineering; Computer science; Machining; Engineering drawing; Engineering","score_opus":0.01880027662517499,"score_gpt":0.25832254200681737,"score_spread":0.23952226538164237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078932163","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21693683,0.0004096634,0.7764796,0.000074194,0.00001657922,0.000044802462,0.000050717317,0.00022147197,0.0057661305],"genre_scores_gemma":[0.96412206,0.00032333037,0.03282719,0.000011146437,0.0000068965496,0.000041013685,0.000040801417,0.000041050625,0.0025865072],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982834,0.000019095854,0.0000068592935,0.000035444227,0.000088344226,0.000021826687],"domain_scores_gemma":[0.99982965,0.000077653225,0.000039378603,0.000017690905,0.000026820986,0.000008816427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030528518,0.00037343657,0.0005341651,0.00022706286,0.0002145712,0.000625943,0.00058722444,0.00061991723,0.0008933954],"category_scores_gemma":[0.00054076203,0.00028138678,0.00045683316,0.00024219912,0.00032491036,0.0006948579,0.0002999376,0.00036394363,0.00021492197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000499206,0.000035260124,0.0009495132,0.000062799365,0.000010767029,0.00011020339,0.00006932514,0.949148,0.032872427,0.0031999848,0.00009455024,0.013397365],"study_design_scores_gemma":[0.000002485138,0.000020540985,0.00024556587,0.0000012319585,0.0000033392303,0.000019596926,0.0000049074706,0.9969887,0.0021802403,0.0003046415,0.00022578014,0.0000029680589],"about_ca_topic_score_codex":0.0040042545,"about_ca_topic_score_gemma":0.002022008,"teacher_disagreement_score":0.0040042545,"about_ca_system_score_codex":0.00030984447,"about_ca_system_score_gemma":0.0006075968,"threshold_uncertainty_score":0.007961869},"labels":[],"label_agreement":null},{"id":"W2079188516","doi":"10.4028/www.scientific.net/amm.232.966","title":"Cutting Tool Condition Monitoring in Machining Processes - A Comprehensive Approach Using ANN Based Multisensor Fusion Strategy","year":2012,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université du Québec à Rimouski","funders":"","keywords":"Tool wear; Machining; Condition monitoring; Reliability (semiconductor); Cutting tool; Machine tool; Sensor fusion; Engineering; Computer science; Reliability engineering; Artificial intelligence; Mechanical engineering","score_opus":0.027883764200118788,"score_gpt":0.26384501113418896,"score_spread":0.23596124693407017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079188516","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08233575,0.0005048962,0.91549194,0.00006709925,0.000009844932,0.000037591202,0.000018814171,0.00022752746,0.0013065822],"genre_scores_gemma":[0.89176077,0.00039743248,0.10693634,0.000029904782,0.00001575093,0.00005846647,0.000051751067,0.000013262842,0.0007363241],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996817,0.000086231536,0.000022878039,0.000060450373,0.00012366641,0.00002505535],"domain_scores_gemma":[0.9997862,0.00008768623,0.00003809165,0.000017458748,0.000061564664,0.000008883003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067648245,0.0006815425,0.0007411964,0.00050419226,0.0002549432,0.0005166026,0.0004033483,0.0007113304,0.0003636655],"category_scores_gemma":[0.0008125966,0.0003411664,0.00066035055,0.00034246268,0.00023091852,0.0008575345,0.0004447283,0.00035648805,0.00008026875],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000120533565,0.00015906534,0.001996593,0.00014719853,0.00013677821,0.0001323488,0.00010591287,0.79948926,0.037801586,0.0015444454,0.00024193231,0.1581244],"study_design_scores_gemma":[0.0000028858162,0.00004840589,0.0008996916,0.000005710348,0.000016594142,0.000022370205,0.0000104542405,0.99570847,0.0026737805,0.0005096422,0.000095364994,0.000006609329],"about_ca_topic_score_codex":0.0014971422,"about_ca_topic_score_gemma":0.0017777712,"teacher_disagreement_score":0.0014971422,"about_ca_system_score_codex":0.00027186493,"about_ca_system_score_gemma":0.00029616346,"threshold_uncertainty_score":0.0035776496},"labels":[],"label_agreement":null},{"id":"W2079672984","doi":"10.1016/j.ijmachtools.2009.03.006","title":"A new approach to the modeling of oblique cutting processes","year":2009,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Rake angle; Oblique case; Slip (aerodynamics); Rake; Kinematics; Shear (geology); Slip angle; Mechanics; Slip line field; Geometry; Structural engineering; Engineering; Geology; Mechanical engineering; Mathematics; Physics; Machining; Classical mechanics","score_opus":0.011343531639077298,"score_gpt":0.24926375018419653,"score_spread":0.23792021854511922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079672984","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008519302,0.0005089459,0.9817832,0.00011961027,0.00015735089,0.0000374264,0.000069613925,0.00011539869,0.008689183],"genre_scores_gemma":[0.49221784,0.0037453808,0.4697082,0.00032341518,0.0005356291,0.0004021874,0.0003336624,0.0004169533,0.03231679],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974483,0.00006190889,0.00001787423,0.00003623647,0.00011049935,0.000028644037],"domain_scores_gemma":[0.99976057,0.000072798444,0.0000421309,0.0000310831,0.00007116431,0.000022197064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004085207,0.0010782435,0.001197692,0.0007962977,0.0005954176,0.001522086,0.0019070857,0.0015678357,0.0028588849],"category_scores_gemma":[0.0009834386,0.00070574577,0.0013316015,0.00081934436,0.000808625,0.0015006935,0.0012110394,0.001592073,0.0007126776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022558857,0.000041474643,0.00022310451,0.000051669613,0.000026332984,0.000086023305,0.00005014643,0.9024285,0.0039098836,0.08084256,0.00041750114,0.011900234],"study_design_scores_gemma":[0.00000420807,0.000008020983,0.000035119043,0.0000034221716,0.000004909403,0.000011149538,0.00000397427,0.99151367,0.00020013847,0.006394438,0.0018168406,0.000004104996],"about_ca_topic_score_codex":0.005647146,"about_ca_topic_score_gemma":0.0041206973,"teacher_disagreement_score":0.005647146,"about_ca_system_score_codex":0.0005769103,"about_ca_system_score_gemma":0.0007927789,"threshold_uncertainty_score":0.011228561},"labels":[],"label_agreement":null},{"id":"W2079676414","doi":"10.1109/iecon.2012.6389274","title":"Cyclostationarity analysis of instantaneous angular speeds for monitoring chatter in high speed milling","year":2012,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cyclostationary process; Machining; SIGNAL (programming language); Angular velocity; Process (computing); Encoder; Engineering; Acoustics; Computer science; Mechanical engineering; Control theory (sociology); Artificial intelligence; Physics; Telecommunications","score_opus":0.017830442646727146,"score_gpt":0.2707264460925508,"score_spread":0.25289600344582364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079676414","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43707943,0.00042705442,0.5605215,0.00004690662,0.000037050533,0.000049378923,0.00013237314,0.00027045794,0.0014358745],"genre_scores_gemma":[0.97316754,0.00016043668,0.026262581,0.0000074535633,0.000018927542,0.00001692728,0.00008903099,0.000023217968,0.00025391974],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99969685,0.00007013422,0.0000184687,0.000062650404,0.00012565748,0.000026295167],"domain_scores_gemma":[0.9989889,0.00054621254,0.0001912718,0.000098995435,0.00013734197,0.000037310725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037468667,0.00032294163,0.0002680069,0.0010013283,0.00013430484,0.00033020056,0.0002466398,0.0002694139,0.0006506633],"category_scores_gemma":[0.0018471436,0.00014292421,0.00019142492,0.00061207515,0.00032051915,0.00035404292,0.00019077897,0.00032309964,0.00012530178],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012209838,0.00028375382,0.02869272,0.00056160596,0.00016146355,0.0011773455,0.00064555305,0.15251455,0.57797277,0.01036288,0.0008403861,0.22556603],"study_design_scores_gemma":[0.000021379243,0.00037891063,0.055377595,0.000027304235,0.00006470278,0.0005793753,0.00010984922,0.848935,0.08951247,0.0036057048,0.001325494,0.00006215834],"about_ca_topic_score_codex":0.00046892825,"about_ca_topic_score_gemma":0.00044342724,"teacher_disagreement_score":0.0010013283,"about_ca_system_score_codex":0.00015118199,"about_ca_system_score_gemma":0.00012193623,"threshold_uncertainty_score":0.002176702},"labels":[],"label_agreement":null},{"id":"W2080557359","doi":"10.1115/imece2004-60465","title":"Real-Time Adaptive Modeling Approach to Compensate the Thermal Deformation of Nonlinear Machine Tool Structures","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear system; Machining; Machine tool; Control theory (sociology); Computer science; Noise (video); Displacement (psychology); Finite element method; Thermal; Mechanical engineering; Engineering; Structural engineering; Artificial intelligence","score_opus":0.01069393904420533,"score_gpt":0.21494617042091782,"score_spread":0.2042522313767125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080557359","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015685977,0.000090969625,0.9822796,0.00009035772,0.000027505877,0.000016966755,0.000013690236,0.0003111658,0.0014837587],"genre_scores_gemma":[0.8405328,0.00026941765,0.15155874,0.000064728716,0.000042048378,0.00015781887,0.00007463969,0.00006437768,0.0072354926],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998745,0.000032943626,0.000006479206,0.000029760751,0.000044382352,0.000011975302],"domain_scores_gemma":[0.9998542,0.00005916802,0.00002553196,0.00002304127,0.00003318164,0.000004870118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003269534,0.00044376912,0.00035917753,0.0002005669,0.0001576816,0.00039288244,0.00058582745,0.0005031588,0.0009929929],"category_scores_gemma":[0.0005557699,0.00022932123,0.00046030633,0.00018820523,0.00027415183,0.00051437115,0.0002735771,0.0007531651,0.00021781008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042090956,0.000030952186,0.0003116065,0.000043428885,0.00002249662,0.000039238657,0.00005358437,0.9333525,0.016543727,0.0054765968,0.00030827028,0.043775547],"study_design_scores_gemma":[0.0000015354808,0.000011644568,0.000046510046,7.6788945e-7,0.0000022854174,0.0000060927614,0.0000015717003,0.99828714,0.0010042909,0.0003166099,0.00031951824,0.0000019393422],"about_ca_topic_score_codex":0.0028899275,"about_ca_topic_score_gemma":0.0029846078,"teacher_disagreement_score":0.0028899275,"about_ca_system_score_codex":0.00030301153,"about_ca_system_score_gemma":0.00054673856,"threshold_uncertainty_score":0.0057462454},"labels":[],"label_agreement":null},{"id":"W2081521210","doi":"10.1115/imece2005-80597","title":"Evaluation of Tool Wear Suppressive Ability of Lubricants Usein in Minimum Quantity Lubrication Application in High Speed Machining of Cast Aluminum Alloys","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metalworking; Lubricant; Lubrication; Machining; Tribology; Materials science; Tool wear; Metallurgy; Alloy; Lubricity; Cutting tool; Aluminium; Mechanical engineering; Composite material; Engineering","score_opus":0.017139863954296328,"score_gpt":0.2773115969000993,"score_spread":0.260171732945803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081521210","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99812216,0.0010635932,0.0005682511,0.0000063224115,0.0000063964385,0.000012373713,0.00003902839,0.00000957653,0.00017224747],"genre_scores_gemma":[0.997872,0.0005946842,0.001002023,0.00000602257,0.0000040661225,0.000010257249,0.00006254416,0.0000054589004,0.00044301158],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992785,0.00013108348,0.00006376319,0.00008486331,0.00035443477,0.00008748071],"domain_scores_gemma":[0.9992925,0.00015953666,0.00019505259,0.00005583886,0.0002621645,0.000034928773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046127202,0.00030653665,0.0003093377,0.00050108304,0.00021159303,0.0002932241,0.00029011522,0.00035953883,0.00038929275],"category_scores_gemma":[0.00074509677,0.00015728232,0.0003392536,0.00039465705,0.00020886854,0.0002760876,0.0001981689,0.00024078011,0.00009034317],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035256209,0.00008746621,0.0014998723,0.00017467045,0.0000137122815,0.000050945462,0.00011626442,0.00028039492,0.9921095,0.00001675801,0.000018145009,0.0052797925],"study_design_scores_gemma":[0.0000069172647,0.0021226525,0.009791556,0.00000999752,0.00003167494,0.000058999463,0.00009933593,0.00091721455,0.9865761,0.0000086795535,0.00036690157,0.000009992421],"about_ca_topic_score_codex":0.0011055171,"about_ca_topic_score_gemma":0.0012290686,"teacher_disagreement_score":0.0011055171,"about_ca_system_score_codex":0.00018572481,"about_ca_system_score_gemma":0.00013334015,"threshold_uncertainty_score":0.0024394393},"labels":[],"label_agreement":null},{"id":"W2081939767","doi":"10.1115/imece2002-39114","title":"Mechanics and Dynamics of Serrated End Mills","year":2002,"lang":"en","type":"article","venue":"Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Flute; Tangent; Kinematics; Geometry; Mechanics; Point (geometry); Enhanced Data Rates for GSM Evolution; Oblique case; Engineering; Materials science; Classical mechanics; Structural engineering; Mechanical engineering; Physics; Mathematics; Acoustics","score_opus":0.006916680781081905,"score_gpt":0.18119363597445654,"score_spread":0.17427695519337463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081939767","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42797202,0.0010086935,0.53234345,0.00041647014,0.00012009763,0.00007637591,0.00019849399,0.00030320327,0.037561193],"genre_scores_gemma":[0.95793957,0.0005567369,0.019601233,0.000046307592,0.00003234055,0.000057353354,0.00007906668,0.000035942874,0.021651424],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983644,0.00002351133,0.000006313298,0.000034318145,0.00008380029,0.00001555482],"domain_scores_gemma":[0.9999007,0.000020736574,0.000028618684,0.000011787522,0.00002266832,0.000015541067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018582915,0.00025145037,0.00023414966,0.00032862092,0.00028270308,0.00088445004,0.00051411084,0.00048866577,0.0028266986],"category_scores_gemma":[0.0003331679,0.00022583711,0.00022869019,0.00013728288,0.0007496704,0.000728673,0.00068316865,0.0003964257,0.00037460148],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014842866,0.000064510976,0.0021342738,0.00011368727,0.000019551846,0.00067193585,0.000503519,0.66717535,0.060788568,0.23225203,0.0014633151,0.034664776],"study_design_scores_gemma":[0.000020849799,0.0001201762,0.0018819966,0.000013595913,0.0000040991604,0.0002678783,0.0000994053,0.951876,0.0037564752,0.037036143,0.0048909243,0.000032458916],"about_ca_topic_score_codex":0.0005907434,"about_ca_topic_score_gemma":0.00033194572,"teacher_disagreement_score":0.0028266986,"about_ca_system_score_codex":0.00027923434,"about_ca_system_score_gemma":0.00030536638,"threshold_uncertainty_score":0.009456217},"labels":[],"label_agreement":null},{"id":"W2082495855","doi":"10.1016/s0007-8506(07)60642-8","title":"A New Approach to Cutting Temperature Prediction Considering the Thermal Constriction Phenomenon in Multi-layer Coated Tools","year":2004,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Materials science; Asperity (geotechnical engineering); Constriction; Coating; Thermal; Layer (electronics); Thermal contact conductance; Thermal resistance; Thermal contact; Redistribution (election); Composite material; Mechanical engineering; Mechanics; Thermodynamics; Engineering","score_opus":0.0594571338192174,"score_gpt":0.2764905302515293,"score_spread":0.2170333964323119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082495855","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035538014,0.00027203962,0.9620259,0.00004929636,0.000067620895,0.000036844976,0.000022167458,0.00021312028,0.0017749787],"genre_scores_gemma":[0.8044084,0.00048297417,0.19120088,0.000060287617,0.000109354136,0.00014917986,0.00007838012,0.00012373744,0.0033868775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998292,0.000033379172,0.000009203107,0.000040707677,0.00007040072,0.000017088361],"domain_scores_gemma":[0.99963033,0.00017881177,0.000031904365,0.000033042295,0.00010557896,0.00002028228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003712934,0.0007098233,0.0009074597,0.00039583055,0.00041837012,0.00078672153,0.0012782454,0.0012921564,0.00083484047],"category_scores_gemma":[0.00081313023,0.00067605387,0.00082207925,0.0003898803,0.0004565178,0.0008610524,0.0005049418,0.0009305559,0.0001959572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003270122,0.000038734725,0.00036759314,0.000051633713,0.000027999316,0.00006440337,0.000026986323,0.96846205,0.012135551,0.0022412702,0.00015957175,0.016391534],"study_design_scores_gemma":[0.0000013352886,0.0000048173947,0.00003258436,6.9478034e-7,0.0000016283607,0.0000020799082,6.948022e-7,0.9995065,0.00030632853,0.00010059266,0.00004135112,0.0000013906537],"about_ca_topic_score_codex":0.0049812486,"about_ca_topic_score_gemma":0.0038927882,"teacher_disagreement_score":0.0049812486,"about_ca_system_score_codex":0.0004728783,"about_ca_system_score_gemma":0.00065496465,"threshold_uncertainty_score":0.009904504},"labels":[],"label_agreement":null},{"id":"W2082833593","doi":"10.1115/imece2007-41353","title":"Virtual Five-Axis Flank Milling of Jet Engine Impellers: Part 2 — Feed Rate Optimization of Five-Axis Flank Milling","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Pratt and Whitney Canada","keywords":"Deflection (physics); Impeller; Machine tool; Control theory (sociology); Torque; Mechanical engineering; Computer science; Engineering; Physics","score_opus":0.008085774446030775,"score_gpt":0.22352861946068525,"score_spread":0.21544284501465447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082833593","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16286768,0.00022153338,0.8337911,0.000043368647,0.000018596478,0.000051222396,0.00002816747,0.000272636,0.0027057407],"genre_scores_gemma":[0.8722666,0.00009208648,0.1264499,0.00001010367,0.000004189926,0.00003746887,0.000031052303,0.000043298503,0.0010653203],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982446,0.00002682796,0.000010618654,0.000029253579,0.000087697954,0.000021206719],"domain_scores_gemma":[0.9998275,0.00006550234,0.000041342428,0.000024105537,0.000033432647,0.000008014703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003635644,0.000385999,0.00040390601,0.00022071283,0.00020983307,0.0006467849,0.0005338409,0.00034493933,0.000838465],"category_scores_gemma":[0.0007040519,0.00023394793,0.00035224142,0.00018194196,0.00036068427,0.00036859192,0.00029677426,0.00033830502,0.00011301518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011180788,0.000044161305,0.0005556112,0.00009997487,0.000013921903,0.000039659884,0.00006893784,0.90436924,0.047031112,0.0038228717,0.00015080487,0.043691896],"study_design_scores_gemma":[0.000011478292,0.00008357985,0.0002563267,0.0000034627296,0.0000036758586,0.0000150143815,0.000008214266,0.985457,0.013184732,0.00042801638,0.0005413969,0.000007147522],"about_ca_topic_score_codex":0.0013728274,"about_ca_topic_score_gemma":0.0012896409,"teacher_disagreement_score":0.0013728274,"about_ca_system_score_codex":0.0004651605,"about_ca_system_score_gemma":0.0004747151,"threshold_uncertainty_score":0.0033749342},"labels":[],"label_agreement":null},{"id":"W2083387274","doi":"10.1016/j.cirpj.2008.06.003","title":"Chatter stability of milling in frequency and discrete time domain","year":2008,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":317,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Discretization; Stability (learning theory); Machining; Frequency domain; Control theory (sociology); Time domain; Process (computing); Harmonics; Domain (mathematical analysis); Engineering; Computer science; Mechanical engineering; Mathematics; Mathematical analysis; Artificial intelligence","score_opus":0.006311199253750427,"score_gpt":0.2059932831517132,"score_spread":0.19968208389796277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083387274","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2962348,0.0012069498,0.6875413,0.00042767968,0.00020845052,0.000035792007,0.00009642825,0.00020995944,0.01403866],"genre_scores_gemma":[0.98890954,0.00019629952,0.006866048,0.000034088032,0.00003802008,0.000017298418,0.000031935702,0.000036124864,0.0038706642],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999629,0.00011480338,0.000017661316,0.000075203636,0.00012610537,0.000037276746],"domain_scores_gemma":[0.9965777,0.002332402,0.00031626134,0.00016520108,0.0005104085,0.00009806312],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009510534,0.00054439664,0.00058533595,0.00057237875,0.00037009522,0.00082447665,0.00061699096,0.0007101017,0.002605975],"category_scores_gemma":[0.0045520714,0.0002481125,0.00044619665,0.0002754062,0.0011218217,0.00096598227,0.00070394593,0.00088234985,0.0001966291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018161689,0.00016839577,0.0038596443,0.0007219231,0.00021873233,0.000934827,0.0012952018,0.5426588,0.08663614,0.31664485,0.0020887337,0.042956512],"study_design_scores_gemma":[0.000009534869,0.000053353237,0.00070421945,0.000008131816,0.000009512807,0.000057157187,0.000032995133,0.98515433,0.0019812416,0.011779232,0.00019467676,0.00001559421],"about_ca_topic_score_codex":0.0017959841,"about_ca_topic_score_gemma":0.0011506294,"teacher_disagreement_score":0.002605975,"about_ca_system_score_codex":0.000465637,"about_ca_system_score_gemma":0.00031368763,"threshold_uncertainty_score":0.008717835},"labels":[],"label_agreement":null},{"id":"W2084018692","doi":"10.1007/s00170-015-6890-z","title":"Tool life and hole surface integrity studies for hole-making of Ti6Al4V alloy","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Seed Foundation of Tianjin University; Natural Science Foundation of Tianjin City; Tianjin University; National Natural Science Foundation of China","keywords":"Surface integrity; Residual stress; Materials science; Titanium alloy; Drilling; Surface roughness; Indentation hardness; Alloy; Ultimate tensile strength; Metallurgy; Layer (electronics); Surface finish; Machining; Titanium; Composite material; Mechanical engineering; Microstructure; Engineering","score_opus":0.02821254930536126,"score_gpt":0.3084979731091139,"score_spread":0.28028542380375265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084018692","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988053,0.00025282483,0.00056957296,0.0000055439787,0.0000042100896,0.0000050076796,0.00007315614,0.00001729071,0.00026714752],"genre_scores_gemma":[0.9992111,0.000049845396,0.00029581285,0.0000021266708,0.0000013922515,0.0000023606644,0.00008283986,0.00000785884,0.0003466423],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995932,0.000032680866,0.000023376106,0.00005757153,0.00021674,0.00007647046],"domain_scores_gemma":[0.9985648,0.00034553962,0.00025532456,0.00017423065,0.0005913719,0.00006869654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049826247,0.00027513978,0.00038395464,0.0006690479,0.00040198083,0.00031197717,0.00060167594,0.00053826644,0.001350756],"category_scores_gemma":[0.0012046467,0.00021299008,0.00042805745,0.00044657543,0.00031855667,0.0006512887,0.00024212153,0.0002876376,0.00022345131],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012903658,0.0001936724,0.01956327,0.00019217492,0.00004986019,0.00046273653,0.0006209384,0.0074680573,0.9420459,0.00022276976,0.0002265681,0.02766378],"study_design_scores_gemma":[0.000017291943,0.003641489,0.06791994,0.000015616606,0.00008564203,0.00040795695,0.00051104405,0.0376803,0.8878482,0.00018700052,0.0016363862,0.000049206257],"about_ca_topic_score_codex":0.0015897024,"about_ca_topic_score_gemma":0.0025359446,"teacher_disagreement_score":0.0015897024,"about_ca_system_score_codex":0.00040081312,"about_ca_system_score_gemma":0.00022439261,"threshold_uncertainty_score":0.0045187473},"labels":[],"label_agreement":null},{"id":"W2084173566","doi":"10.1007/s00170-015-6940-6","title":"Effects of minimum quantity lubricating (MQL) conditions on machining of 7075-T6 aluminum alloy","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure","funders":"","keywords":"Machining; Lubrication; Surface roughness; Metallurgy; Surface finish; Alloy; Materials science; Mechanical engineering; Environmental science; Engineering; Composite material","score_opus":0.008556911668085957,"score_gpt":0.25652570449162204,"score_spread":0.2479687928235361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084173566","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984675,0.0006770848,0.00030865174,0.000029680295,0.00001574952,0.0000045112665,0.000048206115,0.00002247596,0.00042614658],"genre_scores_gemma":[0.99914837,0.00018318302,0.00042055701,0.000008831551,0.0000054064712,0.0000021448354,0.000036944304,0.000009393896,0.00018527021],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999645,0.000068007386,0.000038272326,0.00005925716,0.00010493565,0.000084467945],"domain_scores_gemma":[0.9991404,0.00034156322,0.00020772062,0.00004020225,0.00020628682,0.00006386391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003652913,0.00030637535,0.00047869844,0.00036530293,0.0005511149,0.0006153927,0.0003242454,0.00035346724,0.0014918213],"category_scores_gemma":[0.0014325135,0.00022589118,0.000255479,0.0003922979,0.0004399994,0.00052483217,0.00030672463,0.00028844524,0.00018684026],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003382675,0.000119170065,0.0025237435,0.00070170074,0.000039379902,0.00036696848,0.0005610178,0.0042194817,0.9749122,0.0002670942,0.00030143515,0.012605199],"study_design_scores_gemma":[0.00004218091,0.002219068,0.008183485,0.00002003976,0.000062333456,0.000093441624,0.00036636295,0.004883079,0.98252374,0.00006772985,0.0015073675,0.000031187854],"about_ca_topic_score_codex":0.0029736455,"about_ca_topic_score_gemma":0.00620369,"teacher_disagreement_score":0.0029736455,"about_ca_system_score_codex":0.00046760074,"about_ca_system_score_gemma":0.00060992694,"threshold_uncertainty_score":0.0059126616},"labels":[],"label_agreement":null},{"id":"W2084709039","doi":"10.1108/13552511111180186","title":"Diagnosis of rotor bearings using logical analysis of data","year":2011,"lang":"en","type":"article","venue":"Journal of Quality in Maintenance Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Interpretability; Rotor (electric); Bearing (navigation); Property (philosophy); Artificial intelligence; Engineering; Fault (geology); Data mining; Computer science; Condition monitoring; Field (mathematics); Rolling-element bearing; Machine learning; Reliability engineering; Vibration; Pattern recognition (psychology); Mathematics","score_opus":0.11843594164467783,"score_gpt":0.3344910602180075,"score_spread":0.21605511857332968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084709039","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37843764,0.00026170636,0.61616373,0.0005202152,0.00005609281,0.00028946713,0.00072554784,0.0010534377,0.0024922604],"genre_scores_gemma":[0.84694266,0.0001012923,0.15201825,0.00008178404,0.000021791977,0.00010061192,0.00040826484,0.000015932164,0.00030937427],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983296,0.0006014401,0.00016530206,0.00027365432,0.00055174436,0.00007834961],"domain_scores_gemma":[0.9907652,0.006852189,0.00096810196,0.00045947143,0.00084372505,0.000111239606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020026062,0.0005825054,0.00044323344,0.0014041294,0.00035204925,0.001426675,0.000598565,0.00044574734,0.0012818053],"category_scores_gemma":[0.011804746,0.0001707433,0.0006308011,0.0006414317,0.0005422842,0.0012562572,0.0005894256,0.00039635826,0.0003072412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035914357,0.00097113784,0.12489272,0.0009206341,0.00036046776,0.0006941068,0.0004947952,0.2005318,0.061798405,0.010813656,0.0016975052,0.59323335],"study_design_scores_gemma":[0.00006187918,0.0008027006,0.008053134,0.00004225532,0.000058608835,0.0002549416,0.0001932389,0.9618163,0.022733059,0.005019385,0.0009362562,0.000028136923],"about_ca_topic_score_codex":0.0013898237,"about_ca_topic_score_gemma":0.0016008338,"teacher_disagreement_score":0.0020026062,"about_ca_system_score_codex":0.00067553343,"about_ca_system_score_gemma":0.0009320972,"threshold_uncertainty_score":0.0105909705},"labels":[],"label_agreement":null},{"id":"W2084795187","doi":"10.1016/s0890-6955(01)00129-8","title":"A chip formation based analytic force model for oblique cutting","year":2002,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Oblique case; Chip formation; Chip; Constitutive equation; Materials science; Shear (geology); Structural engineering; Shear force; Machining; Shear stress; Mechanics; Geometry; Mechanical engineering; Engineering; Composite material; Mathematics; Finite element method; Physics; Tool wear","score_opus":0.01723914490832018,"score_gpt":0.2442785536516148,"score_spread":0.22703940874329462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084795187","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026156379,0.0005143966,0.9530549,0.00019536252,0.00012366693,0.000067436835,0.00012812344,0.00047145784,0.019288287],"genre_scores_gemma":[0.88125527,0.0008273973,0.094845384,0.00014485692,0.000054665277,0.00019099754,0.00020267813,0.00018336305,0.022295458],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998852,0.000014396304,0.0000033471563,0.00001948656,0.00005511835,0.000022456461],"domain_scores_gemma":[0.9998485,0.000043486365,0.000019778812,0.000017776869,0.000061049075,0.000009363687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021233576,0.0004939792,0.0006750643,0.00038642334,0.00044132254,0.0006520529,0.0012545305,0.0011672319,0.002618722],"category_scores_gemma":[0.00054575945,0.00040114074,0.000549612,0.0003470155,0.00051625626,0.00071443676,0.0005230847,0.00059105427,0.00057560223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010824698,0.000015050851,0.00012520644,0.000022528724,0.0000053134004,0.000043427735,0.000023080334,0.9794128,0.0028840299,0.011120708,0.00044306892,0.0058938996],"study_design_scores_gemma":[0.0000025655909,0.0000056760587,0.00003415435,0.0000013167983,0.0000018232936,0.00000892028,0.0000024207804,0.99868554,0.00025250542,0.00061697385,0.00038605055,0.000002040855],"about_ca_topic_score_codex":0.009514492,"about_ca_topic_score_gemma":0.0065366197,"teacher_disagreement_score":0.009514492,"about_ca_system_score_codex":0.0007029082,"about_ca_system_score_gemma":0.0010375779,"threshold_uncertainty_score":0.018918216},"labels":[],"label_agreement":null},{"id":"W2086523624","doi":"10.1007/s11665-008-9209-5","title":"Enhancement of Wet- and MQL-Based Machining of Automotive Alloys Using Cutting Tools with DLC/Polymer Surface Treatments","year":2008,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Materials science; Machining; Lubrication; Scanning electron microscope; Lubricant; Metallurgy; Composite material; Drill; Tool wear; Tribology; Alloy; Drilling","score_opus":0.012406245722776198,"score_gpt":0.20848603211201677,"score_spread":0.19607978638924056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086523624","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98969996,0.00067948067,0.00679158,0.000040186278,0.000020373944,0.000025830914,0.000054900374,0.0001567487,0.0025309084],"genre_scores_gemma":[0.994091,0.00014915131,0.0040565208,0.000019124238,0.0000068189443,0.000013093466,0.00004776737,0.000036532976,0.0015799504],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99982256,0.000013975115,0.000009522751,0.000027662785,0.00008712509,0.000039117775],"domain_scores_gemma":[0.9998072,0.000036454123,0.000064400694,0.000024540517,0.00005189592,0.000015678259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019904188,0.00029882614,0.0002882116,0.00020994413,0.00016478851,0.00030233947,0.00029952152,0.0003291803,0.00093651563],"category_scores_gemma":[0.00024980755,0.00026155563,0.0002382987,0.00017427244,0.0002393635,0.00033578568,0.00025815627,0.00033156615,0.0003145552],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030247198,0.000010496757,0.0000679512,0.000042744035,0.0000024849091,0.000011865562,0.000028454691,0.00015206164,0.9977471,0.00006299057,0.000031666525,0.0018118739],"study_design_scores_gemma":[0.0000035362443,0.000052818606,0.00078496436,0.0000014057599,0.0000033256713,0.000017532804,0.0000068736035,0.0008703065,0.99785197,0.000007564513,0.000397106,0.0000026031944],"about_ca_topic_score_codex":0.00042088304,"about_ca_topic_score_gemma":0.0014260543,"teacher_disagreement_score":0.00093651563,"about_ca_system_score_codex":0.00027699856,"about_ca_system_score_gemma":0.00019707732,"threshold_uncertainty_score":0.0031329393},"labels":[],"label_agreement":null},{"id":"W2086666975","doi":"10.1243/0954405011518700","title":"Tool wear and surface integrity during high-speed turning of hardened steel with polycrystalline cubic boron nitride tools","year":2001,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Surface integrity; Materials science; Residual stress; Boron nitride; Enhanced Data Rates for GSM Evolution; Scanning electron microscope; Tool wear; Ultimate tensile strength; Metallurgy; Composite material; Cutting tool; Machining","score_opus":0.0068935482014106245,"score_gpt":0.19007974399468736,"score_spread":0.18318619579327672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086666975","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99947566,0.00013306078,0.0002887195,0.0000040474974,0.0000021973606,0.0000027528872,0.0000149231255,0.000009412509,0.00006933703],"genre_scores_gemma":[0.9994667,0.00003399155,0.0002759992,0.00000361061,0.000001806863,0.0000014835985,0.000043000826,0.000006351284,0.00016720619],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99962413,0.000045495748,0.000017566004,0.000046623485,0.0001819122,0.000084285864],"domain_scores_gemma":[0.9987651,0.00045552797,0.00028734558,0.00012972744,0.00028544,0.00007700609],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002942673,0.00022276228,0.0003606167,0.0003647319,0.00027517418,0.00033200742,0.00026563596,0.00044795274,0.0004887056],"category_scores_gemma":[0.0012045044,0.00021816882,0.000287707,0.00020518151,0.00034472978,0.00025869216,0.00021306687,0.0002444728,0.00010846785],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010242679,0.000040861687,0.0070374515,0.0001167049,0.00003297758,0.0004964201,0.00044037966,0.0008589452,0.98149145,0.000015422664,0.000053909866,0.008391226],"study_design_scores_gemma":[0.0000599188,0.0029812306,0.26788813,0.000024785215,0.000077427845,0.0016216438,0.0005491811,0.007514856,0.71819854,0.000056067503,0.00097268197,0.000055571472],"about_ca_topic_score_codex":0.001448954,"about_ca_topic_score_gemma":0.002655035,"teacher_disagreement_score":0.001448954,"about_ca_system_score_codex":0.00023699652,"about_ca_system_score_gemma":0.00009771205,"threshold_uncertainty_score":0.0028809905},"labels":[],"label_agreement":null},{"id":"W2087513454","doi":"10.1016/j.finel.2007.11.005","title":"A modified time-efficient FE approach for predicting machining-induced residual stresses","year":2008,"lang":"en","type":"article","venue":"Finite Elements in Analysis and Design","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Finite element method; Residual stress; Software; Residual; Current (fluid); Work (physics); Computer science; Mechanical engineering; Field (mathematics); Structural engineering; Materials science; Engineering; Algorithm; Mathematics; Metallurgy","score_opus":0.03281250539290516,"score_gpt":0.255014214451635,"score_spread":0.22220170905872988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087513454","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01648501,0.00011996914,0.9787602,0.000046936613,0.000059322236,0.000052724812,0.0000878233,0.00050759123,0.003880365],"genre_scores_gemma":[0.41618448,0.00035978286,0.5690927,0.00012848926,0.000090383226,0.00037676707,0.0003970609,0.0006146962,0.012755682],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984396,0.000019151266,0.000008262441,0.000020543917,0.00009193975,0.000016150007],"domain_scores_gemma":[0.9996884,0.00010116381,0.000030126033,0.000051026364,0.0001126409,0.00001673568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002866206,0.00067168,0.0006224295,0.00055779103,0.0003744531,0.0005608056,0.0016400637,0.0013701284,0.0036058465],"category_scores_gemma":[0.0010906315,0.00041314712,0.00052196457,0.0005389446,0.0003040333,0.00072387076,0.00042955758,0.00066565984,0.0009300631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003567227,0.000072750474,0.00032094854,0.00004739913,0.000023431601,0.0000607068,0.000029419007,0.9446487,0.011869866,0.005742241,0.00060665683,0.036542263],"study_design_scores_gemma":[0.0000019250472,0.0000057628818,0.000048790815,0.0000014045343,0.000002066817,0.0000057223874,0.0000016215704,0.9988588,0.0005016308,0.00026833647,0.0003020434,0.0000018810204],"about_ca_topic_score_codex":0.004723747,"about_ca_topic_score_gemma":0.0071818205,"teacher_disagreement_score":0.004723747,"about_ca_system_score_codex":0.00043035354,"about_ca_system_score_gemma":0.0008090363,"threshold_uncertainty_score":0.012062728},"labels":[],"label_agreement":null},{"id":"W2087733453","doi":"10.1115/msec2013-1176","title":"Experimental Investigation and Modeling of Milling Burrs","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Controllability; Mechanical engineering; Aluminium; Materials science; Yield (engineering); Metallurgy; Engineering; Mathematics; Applied mathematics","score_opus":0.014593996272732565,"score_gpt":0.22251115060884633,"score_spread":0.20791715433611377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087733453","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96600634,0.00024199388,0.030649647,0.000034331915,0.00002037131,0.00008140128,0.0003815545,0.00025105852,0.0023331426],"genre_scores_gemma":[0.98833954,0.0001335575,0.010517578,0.0000047084927,0.0000028486588,0.00004615012,0.00015488111,0.000017387922,0.00078335026],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995084,0.000035686382,0.00003391587,0.000093890805,0.00028172816,0.000046356345],"domain_scores_gemma":[0.99868983,0.00056260364,0.00019186795,0.00027539936,0.00025015563,0.00003017443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000635062,0.00033927025,0.0003622247,0.00024318209,0.00027707437,0.00039465853,0.0006454336,0.0004571436,0.0015275736],"category_scores_gemma":[0.0015271635,0.00024027009,0.0001987773,0.000319836,0.00039003385,0.00032515917,0.00023990155,0.00034754604,0.00021010934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005176057,0.00037249824,0.0043822634,0.00048401926,0.000013530026,0.0003678374,0.00037241334,0.12020703,0.84961367,0.0014682546,0.00042055268,0.021780265],"study_design_scores_gemma":[0.00005085829,0.001585174,0.008527975,0.000017527813,0.000017721608,0.00016253929,0.00015369404,0.2653983,0.7208527,0.00027527154,0.0029235613,0.00003470295],"about_ca_topic_score_codex":0.00054989,"about_ca_topic_score_gemma":0.0007669426,"teacher_disagreement_score":0.0015275736,"about_ca_system_score_codex":0.00024898408,"about_ca_system_score_gemma":0.00024324932,"threshold_uncertainty_score":0.005110264},"labels":[],"label_agreement":null},{"id":"W2087753470","doi":"10.1115/imece2002-33633","title":"3D Finite Element Analysis for the High Speed Machining of Hardened Steel","year":2002,"lang":"en","type":"article","venue":"Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Finite element method; Chip; Materials science; Chip formation; Slip (aerodynamics); Stress (linguistics); Mechanical engineering; Structural engineering; Hardened steel; Computer science; Composite material; Engineering; Metallurgy; Tool wear","score_opus":0.015687549282022175,"score_gpt":0.2170513387235259,"score_spread":0.2013637894415037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087753470","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07580377,0.00022789549,0.918578,0.00013207477,0.000046931757,0.00007736654,0.00020659882,0.0005296994,0.0043975897],"genre_scores_gemma":[0.69726855,0.000378132,0.29292503,0.000083319144,0.000022126846,0.00044556562,0.00050402776,0.00028771308,0.008085624],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997968,0.000054863176,0.0000096086205,0.000012195323,0.000110633104,0.000015898086],"domain_scores_gemma":[0.999706,0.00015818857,0.000030223111,0.000026036338,0.00006936597,0.000010164686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000448986,0.00046853683,0.00042849962,0.00046718973,0.00030080357,0.0004993465,0.00062805275,0.0011973954,0.0026780039],"category_scores_gemma":[0.0009202462,0.00051431375,0.0008171728,0.00025022542,0.00034815856,0.0003161245,0.0003625239,0.0005100038,0.00065389567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033222506,0.00002853199,0.000518056,0.00005399271,0.000015348787,0.000052301893,0.00006233689,0.9751751,0.010528033,0.0033713423,0.0002908426,0.009871011],"study_design_scores_gemma":[0.0000042188967,0.000009025187,0.0001315903,0.0000037576785,0.0000017197739,0.0000092062655,0.0000061663163,0.99811506,0.00068026286,0.00037171124,0.0006645097,0.0000028330383],"about_ca_topic_score_codex":0.004887307,"about_ca_topic_score_gemma":0.005772201,"teacher_disagreement_score":0.004887307,"about_ca_system_score_codex":0.0004783011,"about_ca_system_score_gemma":0.00074698473,"threshold_uncertainty_score":0.009717703},"labels":[],"label_agreement":null},{"id":"W2088301890","doi":"10.1115/pvp2006-icpvt-11-93149","title":"Finite Element Analysis of Turning Hardened AISI 42100 Bearing Steel With Various Cutting Inserts","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Materials science; Boron nitride; Hardened steel; Residual stress; Machining; Metallurgy; Abrasive; Finite element method; Rockwell scale; Carbide; Bearing (navigation); High-speed steel; Tool wear; Composite material; Structural engineering; Engineering","score_opus":0.004687480688231597,"score_gpt":0.20224086844966183,"score_spread":0.19755338776143022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088301890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9235689,0.00013989121,0.062764935,0.00013847587,0.000044776007,0.00013252544,0.0007440508,0.00040804944,0.012058354],"genre_scores_gemma":[0.9769974,0.000082718114,0.018642452,0.000029606608,0.0000051077072,0.00012800201,0.00057872006,0.000068089386,0.003467922],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997311,0.00004332587,0.00001516348,0.000029955823,0.0001268202,0.000053666954],"domain_scores_gemma":[0.9992544,0.0003667533,0.000088794855,0.00006534559,0.00018008545,0.00004465286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050404016,0.00052576495,0.00085008726,0.00075095845,0.00049224193,0.00064046285,0.0010892645,0.0016014422,0.003550636],"category_scores_gemma":[0.0010020039,0.0005349597,0.0007020011,0.0005257274,0.000637238,0.00028388714,0.00032433934,0.00045902337,0.00043500253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000911727,0.000073399606,0.0011577688,0.00007017673,0.000017880897,0.00006927876,0.00008276121,0.98368406,0.010977712,0.0006706712,0.00019525817,0.0029098822],"study_design_scores_gemma":[0.000013161888,0.00004839262,0.00068233407,0.0000058503474,0.0000057556263,0.000012498118,0.000034420027,0.99681014,0.0020274718,0.00009245274,0.00026098904,0.00000657144],"about_ca_topic_score_codex":0.009503265,"about_ca_topic_score_gemma":0.008832686,"teacher_disagreement_score":0.009503265,"about_ca_system_score_codex":0.00068146,"about_ca_system_score_gemma":0.0009626857,"threshold_uncertainty_score":0.018895924},"labels":[],"label_agreement":null},{"id":"W2088812951","doi":"10.1504/ijbcrm.2011.042299","title":"A new sustainability model for machining processes","year":2011,"lang":"en","type":"article","venue":"International Journal of Business Continuity and Risk Management","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Sustainability; Machining; Process (computing); Productivity; Manufacturing engineering; Engineering; Fuzzy logic; Mechanical engineering; Risk analysis (engineering); Computer science; Business; Artificial intelligence","score_opus":0.011496914775837386,"score_gpt":0.23957137544102558,"score_spread":0.2280744606651882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088812951","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018647134,0.00093646056,0.9423152,0.0011690451,0.00012961567,0.00011285458,0.0002842857,0.00022283028,0.036182445],"genre_scores_gemma":[0.80061543,0.0025478648,0.14302365,0.00035513655,0.00017426861,0.0007722883,0.0005537957,0.00020125855,0.051756416],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99924266,0.00021731376,0.000038796028,0.0001565772,0.00025833707,0.00008631804],"domain_scores_gemma":[0.9993747,0.0002913744,0.00008275092,0.000028653702,0.00018552509,0.000037010763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012603393,0.0013639494,0.00082013884,0.0011073406,0.00071222335,0.0022559639,0.0020369485,0.002480885,0.0056652837],"category_scores_gemma":[0.002067666,0.00044266472,0.0012840519,0.00085507124,0.0009900451,0.00310755,0.0012076849,0.0017040011,0.00079586904],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019364645,0.000045353692,0.00040661864,0.00010327686,0.000027191501,0.00015560679,0.00012717502,0.8387084,0.0016656178,0.1462366,0.00088552677,0.011619175],"study_design_scores_gemma":[0.000011384607,0.000025099855,0.00014101183,0.0000167481,0.000010979504,0.000046982947,0.000030694446,0.9439762,0.00026503994,0.050553992,0.004907609,0.000014169427],"about_ca_topic_score_codex":0.0065837316,"about_ca_topic_score_gemma":0.004003642,"teacher_disagreement_score":0.0065837316,"about_ca_system_score_codex":0.002361381,"about_ca_system_score_gemma":0.0015619901,"threshold_uncertainty_score":0.01895225},"labels":[],"label_agreement":null},{"id":"W2090135844","doi":"10.1007/s00170-015-7109-z","title":"Characterization of grinding wheel grain topography under different robotic grinding conditions using confocal microscope","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hydro-Québec; École de Technologie Supérieure; Université du Québec; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Materials science; Rake angle; Grinding wheel; Microscope; Rake; Grain size; Optical microscope; Optics; Geometry; Composite material; Machining; Metallurgy; Mechanical engineering; Scanning electron microscope; Engineering; Mathematics; Physics","score_opus":0.015572907147789902,"score_gpt":0.26607409693833245,"score_spread":0.25050118979054253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090135844","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848733,0.0001931914,0.012610013,0.000054815606,0.00002437374,0.00002555925,0.0003600093,0.00023584299,0.0016229321],"genre_scores_gemma":[0.9756186,0.00017914361,0.021413678,0.000028205413,0.000006393001,0.00003134591,0.0004584307,0.00006986821,0.002194248],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978644,0.00000590151,0.000010493353,0.000051113195,0.00010840794,0.0000376431],"domain_scores_gemma":[0.99968123,0.000053466527,0.000052573087,0.00005072499,0.00014244394,0.000019663421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017831483,0.00020237474,0.0002046257,0.00038795147,0.00030666322,0.0002813232,0.00032029033,0.00037177937,0.0024984253],"category_scores_gemma":[0.00031877751,0.00027201633,0.00022704856,0.00037644294,0.00026121645,0.00035060433,0.00014020818,0.00033428145,0.0002923406],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025731902,0.000010458204,0.00056396506,0.00001905519,0.0000027993306,0.000028474471,0.00004204391,0.00014544108,0.9970981,0.000055735745,0.000083589504,0.0019245711],"study_design_scores_gemma":[0.000008312979,0.00008476602,0.04412288,0.000003320693,0.000014635497,0.00014665321,0.000104267376,0.0052750213,0.9486432,0.000047677026,0.0015307708,0.000018601191],"about_ca_topic_score_codex":0.004110966,"about_ca_topic_score_gemma":0.011225413,"teacher_disagreement_score":0.004110966,"about_ca_system_score_codex":0.00038328627,"about_ca_system_score_gemma":0.0003619082,"threshold_uncertainty_score":0.008358061},"labels":[],"label_agreement":null},{"id":"W2091014384","doi":"10.1007/s11740-009-0177-x","title":"Optimization of surface roughness in an end-milling operation using nested experimental design","year":2009,"lang":"en","type":"article","venue":"Production Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Machining; Surface roughness; Materials science; Aluminium; Surface finish; Metallurgy; Taguchi methods; Carbon steel; Alloy; Aluminium alloy; Composite material; Mechanical engineering; Engineering","score_opus":0.02204599708791042,"score_gpt":0.2580967823862313,"score_spread":0.23605078529832088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091014384","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6839566,0.00013249817,0.31285322,0.000055660978,0.000025754845,0.00017664359,0.00004183694,0.00019810633,0.0025596737],"genre_scores_gemma":[0.9385645,0.000025297446,0.060951006,0.000008357828,0.000002794571,0.0000839839,0.000021465998,0.000022496173,0.00032008032],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991881,0.00023724206,0.00004166125,0.00013848214,0.00028893907,0.00010553055],"domain_scores_gemma":[0.9982936,0.0009622268,0.00024177611,0.00017039098,0.00027463085,0.000057368074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020827735,0.0006424142,0.00097314594,0.0003052552,0.0004578055,0.0008051605,0.0008563901,0.0006733282,0.0007812652],"category_scores_gemma":[0.0028968307,0.00054617884,0.0006198307,0.00022295755,0.0007015908,0.000878242,0.00069432333,0.00066173245,0.000079478596],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008206079,0.00058655516,0.0014082902,0.00017278353,0.000042750205,0.00004590033,0.00010199471,0.8627598,0.108547114,0.0020176338,0.00009314415,0.023403388],"study_design_scores_gemma":[0.0000561274,0.00060697336,0.0006442462,0.0000034200891,0.000017501483,0.000009550393,0.000013680175,0.97211516,0.02605007,0.00030729052,0.0001630012,0.0000130107355],"about_ca_topic_score_codex":0.0013431796,"about_ca_topic_score_gemma":0.0019291579,"teacher_disagreement_score":0.0020827735,"about_ca_system_score_codex":0.0007062114,"about_ca_system_score_gemma":0.0009799943,"threshold_uncertainty_score":0.011014938},"labels":[],"label_agreement":null},{"id":"W2091062369","doi":"10.1016/j.polymer.2013.01.031","title":"Plane stress local failure criterion for polycarbonate containing laser drilled microvoids","year":2013,"lang":"en","type":"article","venue":"Polymer","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Polycarbonate; Microscale chemistry; Composite material; Void (composites); Plane stress; Plasticity; Polymer; Deformation (meteorology); Shear (geology); Finite element method; Structural engineering","score_opus":0.004225665260381561,"score_gpt":0.2038187329173141,"score_spread":0.19959306765693252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091062369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7176122,0.00072133343,0.27658796,0.000110947054,0.00002313997,0.0000709644,0.00014746956,0.00019443719,0.0045316066],"genre_scores_gemma":[0.9899312,0.00007848195,0.0084689045,0.000009219163,0.0000048663273,0.000030595354,0.000061976665,0.00003027983,0.0013844395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975234,0.000036522273,0.000011929797,0.000036782963,0.00013308985,0.000029272653],"domain_scores_gemma":[0.9991929,0.00030878643,0.00011184026,0.00003268938,0.00030407513,0.000049733662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081873714,0.00043627076,0.0005823408,0.00059834076,0.00027694125,0.0005954394,0.0006524303,0.00072133244,0.00097144843],"category_scores_gemma":[0.0010612357,0.00015323183,0.00026476162,0.0002088805,0.00043849784,0.00036783004,0.000378661,0.00036199324,0.00018070165],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050426193,0.00010863358,0.0041122567,0.00037174992,0.00002861864,0.0002764153,0.00013358782,0.57510406,0.38212663,0.010229,0.0009053209,0.02609951],"study_design_scores_gemma":[0.000012213744,0.00039848784,0.0033091456,0.000022871525,0.000010051774,0.0000746055,0.000053996624,0.95250255,0.04216845,0.0010652378,0.00035774356,0.000024640603],"about_ca_topic_score_codex":0.0026559986,"about_ca_topic_score_gemma":0.0024136282,"teacher_disagreement_score":0.0026559986,"about_ca_system_score_codex":0.0008765169,"about_ca_system_score_gemma":0.0005375827,"threshold_uncertainty_score":0.006359577},"labels":[],"label_agreement":null},{"id":"W2091480134","doi":"10.1115/imece2014-39503","title":"Identification and Validation of Marusich’s Constitutive Law for Finite Element Modeling of High Speed Machining","year":2014,"lang":"en","type":"article","venue":"Volume 2A: Advanced Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Machining; Constitutive equation; Finite element method; Chip; Structural engineering; Chip formation; Materials science; Mechanical engineering; Computer science; Engineering; Tool wear","score_opus":0.008491980805322812,"score_gpt":0.22480949222998706,"score_spread":0.21631751142466424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091480134","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14285836,0.00043978632,0.8499504,0.000099914316,0.00003784516,0.0001297507,0.00007906391,0.00042059843,0.005984426],"genre_scores_gemma":[0.85156393,0.00035318037,0.14568387,0.00002136567,0.000014180904,0.00017939486,0.00017138217,0.00008382088,0.001928888],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925166,0.00017715001,0.00003134877,0.0000629157,0.00043972934,0.000037267757],"domain_scores_gemma":[0.9989894,0.00047675654,0.00011535903,0.000144594,0.00025652556,0.000017379707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011842229,0.0005903468,0.0004674345,0.00078298274,0.0002984483,0.0007563132,0.0009988168,0.0012406878,0.0006801663],"category_scores_gemma":[0.002590489,0.00036815804,0.00054650044,0.00041252963,0.0004664146,0.00072748965,0.00032079272,0.0005660896,0.00038322966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041669693,0.0001387998,0.0022394895,0.0001346657,0.00002073632,0.0001078557,0.00014555252,0.8850987,0.052298233,0.009042429,0.00037388736,0.050357986],"study_design_scores_gemma":[0.0000022741865,0.000020895406,0.00035501548,0.000006927016,0.0000027016215,0.00002570125,0.0000071492545,0.9949818,0.003687608,0.00028497094,0.0006204708,0.000004573516],"about_ca_topic_score_codex":0.002193476,"about_ca_topic_score_gemma":0.0017445915,"teacher_disagreement_score":0.002193476,"about_ca_system_score_codex":0.00041334386,"about_ca_system_score_gemma":0.00092275935,"threshold_uncertainty_score":0.006262839},"labels":[],"label_agreement":null},{"id":"W2091507676","doi":"10.1016/s0007-8506(07)60022-5","title":"Virtual Machine Tool","year":2005,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":466,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machine tool; Virtual finite-state machine; Machining; Kinematics; Control engineering; Numerical control; Process (computing); Computer science; Virtual machine; Finite element method; Engineering; Mechanical engineering","score_opus":0.013373778206427857,"score_gpt":0.2531536677591433,"score_spread":0.23977988955271543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091507676","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025255103,0.0005113444,0.684879,0.00044100237,0.0017506534,0.0005006203,0.002863041,0.03522597,0.24857335],"genre_scores_gemma":[0.46651682,0.0005943852,0.28613034,0.0005634341,0.00033012018,0.00059173093,0.0055373455,0.005343178,0.2343927],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932814,0.000056914036,0.00003114465,0.00012921316,0.00038217622,0.00007250718],"domain_scores_gemma":[0.99927086,0.00012480738,0.00003786255,0.00029387456,0.00014049785,0.00013214548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004400384,0.0011349926,0.00079106516,0.001455539,0.00060366996,0.0023538575,0.0020741532,0.001178988,0.14846317],"category_scores_gemma":[0.0015088178,0.00055285,0.0006510901,0.000571423,0.00059694494,0.0015631679,0.002950159,0.00078190793,0.032993373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094026554,0.00019428585,0.0010245652,0.00050641067,0.00004754233,0.0008250061,0.00023798452,0.028127166,0.060909927,0.04910415,0.11959047,0.7384923],"study_design_scores_gemma":[0.00022015967,0.0007776391,0.0018884281,0.00013087166,0.00005454804,0.0020377468,0.00011069732,0.12183534,0.05404984,0.018090893,0.80065596,0.0001479316],"about_ca_topic_score_codex":0.00043441923,"about_ca_topic_score_gemma":0.0005281281,"teacher_disagreement_score":0.14846317,"about_ca_system_score_codex":0.00031596,"about_ca_system_score_gemma":0.0008625679,"threshold_uncertainty_score":0.4966588},"labels":[],"label_agreement":null},{"id":"W2091551351","doi":"10.1081/mst-120016248","title":"PHYSICS-BASED SIMULATION OF HIGH SPEED MACHINING","year":2002,"lang":"en","type":"article","venue":"Machining Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":119,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Chip formation; Nonlinear system; Mechanical engineering; Chip; Constitutive equation; Materials science; Process (computing); Characterization (materials science); Stress (linguistics); Empirical modelling; Strain rate; Computer science; Mechanics; Engineering; Structural engineering; Finite element method; Tool wear; Physics; Simulation; Composite material; Nanotechnology","score_opus":0.01011056541773387,"score_gpt":0.23363773003587968,"score_spread":0.2235271646181458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091551351","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37124053,0.0008561458,0.5660385,0.00079855,0.00021037918,0.0002709462,0.00085638993,0.0009955865,0.05873294],"genre_scores_gemma":[0.94800705,0.00050170755,0.044895295,0.000074740194,0.000031633623,0.00030581438,0.00034516398,0.00008652288,0.005752163],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980766,0.000045324923,0.000008220251,0.000020514432,0.000091043315,0.000027234886],"domain_scores_gemma":[0.9996234,0.0002131775,0.00003774174,0.000042186708,0.00005922899,0.000024248904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033723447,0.00034291076,0.00050581276,0.00034549076,0.0005226192,0.0007880511,0.00092959654,0.0013282018,0.0022500684],"category_scores_gemma":[0.0013283956,0.00038831902,0.0004411608,0.0004870665,0.0005851023,0.00070834946,0.0004723118,0.000662765,0.00029811758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008886243,0.0000131813995,0.00019815435,0.000013837617,0.000005879737,0.00002529749,0.000015345795,0.9924661,0.0007878481,0.004931384,0.00012863897,0.0014053915],"study_design_scores_gemma":[0.000005838389,0.0000056688286,0.00012152157,0.0000010776506,0.0000013376745,0.0000046241785,0.0000023757643,0.99803954,0.00018628695,0.001231698,0.00039769345,0.0000023635857],"about_ca_topic_score_codex":0.0054805325,"about_ca_topic_score_gemma":0.0033930952,"teacher_disagreement_score":0.0054805325,"about_ca_system_score_codex":0.00067861425,"about_ca_system_score_gemma":0.0010281125,"threshold_uncertainty_score":0.010897279},"labels":[],"label_agreement":null},{"id":"W2091599728","doi":"10.1016/j.cirp.2011.05.010","title":"Machine tool feed drives","year":2011,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":635,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machine tool; Ball screw; Levitation; Engineering; Control engineering; Linear motor; Mechanical engineering; Motion control; Hydrostatic equilibrium; Computer science; Magnet","score_opus":0.03139597662399654,"score_gpt":0.24662399796702406,"score_spread":0.21522802134302751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091599728","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045348577,0.0035117855,0.31029925,0.0007341955,0.0018399896,0.0006333427,0.004125705,0.014773418,0.6187337],"genre_scores_gemma":[0.3073962,0.0018116491,0.086440906,0.00048383028,0.00029634012,0.0002717672,0.006076685,0.00096836995,0.5962543],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991504,0.00004429138,0.000030162242,0.00013458634,0.00058703154,0.000053492182],"domain_scores_gemma":[0.99939704,0.00008045204,0.000033917848,0.00014773001,0.000305403,0.000035518555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031789014,0.0007901807,0.00059040537,0.0013331395,0.0009377487,0.0014076969,0.0010387116,0.0009570144,0.086203314],"category_scores_gemma":[0.0010303211,0.00039504233,0.00029038862,0.0011437611,0.0002636588,0.0013683594,0.00082796474,0.0007505711,0.035947528],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036413633,0.00016906898,0.0010413212,0.0008176247,0.000025771618,0.00020084258,0.00014279896,0.0035396211,0.103250355,0.019472688,0.09517869,0.775797],"study_design_scores_gemma":[0.0000497681,0.00041938992,0.004491697,0.00008588011,0.000022279311,0.00088836503,0.000072615054,0.011970407,0.08814302,0.0029392699,0.8908787,0.00003866404],"about_ca_topic_score_codex":0.0005206269,"about_ca_topic_score_gemma":0.0011681002,"teacher_disagreement_score":0.086203314,"about_ca_system_score_codex":0.0004513922,"about_ca_system_score_gemma":0.00056737516,"threshold_uncertainty_score":0.28837878},"labels":[],"label_agreement":null},{"id":"W2091748074","doi":"10.1016/s0007-8506(07)60694-5","title":"Model-Based Monitoring and Control of Continuous Dress Creep-Feed Form Grinding","year":2004,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Pratt and Whitney Canada","keywords":"Grinding; Serration; Power (physics); Mechanical engineering; Heat flux; Materials science; Flux (metallurgy); Process (computing); Turbine; Structural engineering; Mechanics; Engineering; Computer science; Metallurgy; Composite material; Heat transfer","score_opus":0.019527336869793077,"score_gpt":0.2630407357534,"score_spread":0.2435133988836069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091748074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5355548,0.00024409326,0.4594465,0.0001862427,0.00008219717,0.000055310968,0.00009062762,0.0015298371,0.0028104018],"genre_scores_gemma":[0.99478006,0.000019476314,0.0048940573,0.0000059797317,0.0000027066742,0.000010909834,0.000013756145,0.000010963768,0.0002620871],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968886,0.000052984466,0.000012947886,0.00009896914,0.000107950356,0.00003821033],"domain_scores_gemma":[0.9993235,0.0002818741,0.0001517796,0.000055281,0.00015315805,0.00003438419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005303427,0.0007482522,0.0007625587,0.00031751787,0.00033269468,0.00094795856,0.0007793323,0.0005853558,0.0006142093],"category_scores_gemma":[0.0014429683,0.0003249048,0.00029885146,0.00017799038,0.00042743093,0.00051361514,0.00047359033,0.0004883477,0.00013932631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075310294,0.00028996714,0.0033811512,0.00009415651,0.00004311136,0.00007660712,0.000090185575,0.8705232,0.059189115,0.00103378,0.00058063853,0.06394491],"study_design_scores_gemma":[0.00000696535,0.000037576556,0.0005909917,9.518421e-7,0.0000031269076,0.000004187642,0.0000023362481,0.99606776,0.003095075,0.0001376369,0.000049721206,0.0000037242535],"about_ca_topic_score_codex":0.0065211644,"about_ca_topic_score_gemma":0.00829297,"teacher_disagreement_score":0.0065211644,"about_ca_system_score_codex":0.0006616038,"about_ca_system_score_gemma":0.0005939317,"threshold_uncertainty_score":0.012966394},"labels":[],"label_agreement":null},{"id":"W2092824369","doi":"10.1115/1.1445147","title":"Numerical Analysis of Metal Cutting With Chamfered and Blunt Tools","year":2002,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Chamfer (geometry); Enhanced Data Rates for GSM Evolution; Materials science; Chip formation; Finite element method; Chip; Machining; Cutting tool; Carbide; Process (computing); Tool wear; Structural engineering; Composite material; Geometry; Metallurgy; Computer science; Engineering; Mathematics","score_opus":0.009574345320053346,"score_gpt":0.20120537993250967,"score_spread":0.1916310346124563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092824369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9241154,0.00031265814,0.06819297,0.00013361164,0.000039351788,0.000056741857,0.00010106343,0.00021541474,0.006832818],"genre_scores_gemma":[0.9773466,0.00009739726,0.021319265,0.000017527569,0.000004402664,0.00003104598,0.000058509704,0.000018951077,0.0011062172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983716,0.000027729804,0.000008120353,0.000016555286,0.00007990004,0.000030611427],"domain_scores_gemma":[0.9992404,0.00047059116,0.000096183,0.000058604535,0.00010451554,0.00002980443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042578368,0.00030564485,0.00037892157,0.00038565786,0.0004001687,0.0005664577,0.00043097883,0.0010704094,0.0011799566],"category_scores_gemma":[0.0016958105,0.00025678184,0.0004287954,0.00028840677,0.0006104573,0.00040494176,0.0002806128,0.0002795623,0.00013578519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012233292,0.000053895084,0.002009745,0.0001067704,0.00002078663,0.00016355193,0.00012990728,0.9594865,0.026833208,0.0031597668,0.00014941389,0.007764158],"study_design_scores_gemma":[0.0000149265925,0.000059108774,0.000764641,0.000004811913,0.000006413141,0.00004419673,0.00002797642,0.9948042,0.0034010161,0.00048568117,0.00037886787,0.000008142892],"about_ca_topic_score_codex":0.002193736,"about_ca_topic_score_gemma":0.0018832756,"teacher_disagreement_score":0.002193736,"about_ca_system_score_codex":0.00043685877,"about_ca_system_score_gemma":0.00048235955,"threshold_uncertainty_score":0.004361987},"labels":[],"label_agreement":null},{"id":"W2093029951","doi":"10.1115/msec2009-84039","title":"Chatter Stability in Micro Milling Processes Considering Ploughing and Process Damping Effects","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chip formation; Shearing (physics); Chip; Machining; Plough; Mechanical engineering; Materials science; Process (computing); Engineering; Structural engineering; Computer science; Tool wear; Composite material; Electrical engineering","score_opus":0.008845009104099204,"score_gpt":0.23415521145939716,"score_spread":0.22531020235529794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093029951","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34044337,0.0016595091,0.6500081,0.0002591296,0.00006564594,0.0000823109,0.000053093805,0.00032460995,0.0071042185],"genre_scores_gemma":[0.9920135,0.0002971059,0.0052047647,0.000014865272,0.000013573879,0.00002604345,0.000015120735,0.0000311113,0.0023839925],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997471,0.000066758636,0.0000095603755,0.00004566606,0.000094100775,0.000036739508],"domain_scores_gemma":[0.99912375,0.00053607376,0.0001309039,0.000040004314,0.00013326494,0.00003596121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063535594,0.000709213,0.0006125082,0.00053009455,0.0003669532,0.00077104114,0.000644222,0.000981305,0.00095799373],"category_scores_gemma":[0.0019022324,0.0003797703,0.00075891946,0.00024722368,0.00089667435,0.0008012177,0.000569787,0.0006119722,0.00021267614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023002244,0.00005429448,0.0015323346,0.00019168078,0.000056652894,0.0004882751,0.00039902335,0.939491,0.03663757,0.011029705,0.00026909637,0.009620349],"study_design_scores_gemma":[0.0000040748687,0.000018491277,0.0001246638,0.000002236458,0.0000051462403,0.000019584622,0.000008216183,0.9980994,0.0010401787,0.0006147595,0.00005947272,0.0000038013984],"about_ca_topic_score_codex":0.0051881573,"about_ca_topic_score_gemma":0.002106118,"teacher_disagreement_score":0.0051881573,"about_ca_system_score_codex":0.0006982763,"about_ca_system_score_gemma":0.0004812397,"threshold_uncertainty_score":0.010315955},"labels":[],"label_agreement":null},{"id":"W2093908963","doi":"10.1007/s12206-014-0106-6","title":"Characteristic recognition of chatter mark vibration in a rolling mill based on the non-dimensional parameters of the vibration signal","year":2014,"lang":"en","type":"article","venue":"Journal of Mechanical Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Kurtosis; Vibration; SIGNAL (programming language); Engineering; Acoustics; Structural engineering; Control theory (sociology); Mathematics; Computer science; Artificial intelligence; Physics; Statistics","score_opus":0.007568930392016495,"score_gpt":0.20161797607454868,"score_spread":0.19404904568253217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093908963","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81083405,0.00028220998,0.18596718,0.00011531375,0.000085504355,0.00002747418,0.00008289721,0.000377679,0.002227701],"genre_scores_gemma":[0.9904033,0.000047179583,0.008908628,0.00001608217,0.000013167936,0.000006263236,0.000034885587,0.000010169261,0.00056020706],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987113,0.000015973892,0.000007034658,0.000030499052,0.000062359315,0.000013052203],"domain_scores_gemma":[0.99956065,0.00018865602,0.00006156093,0.000028574703,0.00011828308,0.000042178508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001731024,0.0002233265,0.00025412903,0.0005178109,0.00013249174,0.00021877814,0.00030475477,0.0004247939,0.00078813743],"category_scores_gemma":[0.00058894465,0.000108476124,0.0001405557,0.0002457038,0.0002032238,0.00030862217,0.00013675883,0.00024469243,0.00011892965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016464948,0.00009387283,0.012191658,0.0002584108,0.000055396387,0.00082450453,0.00035805997,0.009459254,0.8277664,0.001290479,0.00079891353,0.14525662],"study_design_scores_gemma":[0.0000762994,0.0010335612,0.16486147,0.00004188972,0.00011469889,0.002398168,0.00032458757,0.63266987,0.1957027,0.0012395162,0.0014220775,0.0001151634],"about_ca_topic_score_codex":0.0003520915,"about_ca_topic_score_gemma":0.0005483441,"teacher_disagreement_score":0.00078813743,"about_ca_system_score_codex":0.0000810095,"about_ca_system_score_gemma":0.000091594826,"threshold_uncertainty_score":0.0026366115},"labels":[],"label_agreement":null},{"id":"W2094800275","doi":"10.5539/mas.v4n6p54","title":"Using Power Spectral Density for Condition Monitoring of Fan","year":2010,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Tehran","keywords":"Spectral density; Vibration; Fault (geology); Power (physics); Jet (fluid); Automotive engineering; Turbulence; Computer science; Flow (mathematics); Acoustics; Engineering; Mechanics; Physics; Telecommunications","score_opus":0.016151407378857948,"score_gpt":0.27975735614908354,"score_spread":0.2636059487702256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094800275","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23253554,0.00081571494,0.757752,0.000118721655,0.0001228192,0.00007139823,0.00047249286,0.003418336,0.0046929894],"genre_scores_gemma":[0.9156328,0.00028732372,0.08262392,0.000024745395,0.000034083478,0.000045111567,0.00032375258,0.00007769746,0.0009505849],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995196,0.00009512001,0.00001900498,0.000095884796,0.00024388907,0.000026503427],"domain_scores_gemma":[0.9990538,0.0005444692,0.00007396815,0.000066369095,0.00024279261,0.000018581082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006110697,0.0005839919,0.00030324908,0.0023565218,0.00016307239,0.000356166,0.0003823442,0.00048114016,0.0018287373],"category_scores_gemma":[0.002249864,0.00019986113,0.0002450118,0.0009731436,0.00021168544,0.00076012244,0.00018580044,0.00026228908,0.00051521213],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045632565,0.00023754546,0.032499682,0.00056719634,0.00014666446,0.00038867997,0.00041643457,0.06993206,0.19906989,0.0030399715,0.002845598,0.6903998],"study_design_scores_gemma":[0.000029028011,0.0003069461,0.053567644,0.000057767047,0.000079001344,0.0009631432,0.00014584007,0.81753427,0.11893217,0.0027653922,0.005512646,0.00010613006],"about_ca_topic_score_codex":0.0008817209,"about_ca_topic_score_gemma":0.0006539558,"teacher_disagreement_score":0.0023565218,"about_ca_system_score_codex":0.00019162304,"about_ca_system_score_gemma":0.00011296476,"threshold_uncertainty_score":0.0061177015},"labels":[],"label_agreement":null},{"id":"W2096388130","doi":"10.1115/imece2006-13129","title":"Substructure Coupling of Micro-End Mills","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Substructure; Coupling (piping); Vibration; Mechanical engineering; Machine tool; Modal analysis; Hammer; Displacement (psychology); Finite element method; Machining; Engineering; Gauge (firearms); Flatness (cosmology); Materials science; Acoustics; Structural engineering; Physics","score_opus":0.00237726036127071,"score_gpt":0.1809282128998715,"score_spread":0.1785509525386008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096388130","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8626372,0.00022629075,0.13233912,0.00003312897,0.000018741788,0.00005260045,0.000027246888,0.0002471189,0.0044185487],"genre_scores_gemma":[0.98154795,0.000053128933,0.016724402,0.000012843758,0.000004377264,0.000014674203,0.000022302096,0.000017219201,0.0016032399],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99920493,0.000092916634,0.000025937266,0.00012911817,0.00048975844,0.00005729693],"domain_scores_gemma":[0.99876523,0.0005595708,0.00027554703,0.0001506483,0.00020254939,0.00004650783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043165556,0.00030624744,0.00030693086,0.00038376433,0.00021471815,0.00040352522,0.00060798466,0.00039518846,0.0017416858],"category_scores_gemma":[0.001462984,0.0002945516,0.00021014441,0.00018286303,0.0004356586,0.0004898403,0.0004998365,0.00034115973,0.0002973197],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002514168,0.00009163906,0.0043774,0.00012617931,0.000019604024,0.00044224702,0.00047526334,0.01829011,0.92373854,0.0022830237,0.00013083722,0.049773734],"study_design_scores_gemma":[0.000032560994,0.0014538812,0.025313523,0.000032487053,0.000027937167,0.0012787762,0.00018386448,0.2139242,0.7513063,0.0024649997,0.003919025,0.00006245439],"about_ca_topic_score_codex":0.00040143722,"about_ca_topic_score_gemma":0.0003991269,"teacher_disagreement_score":0.0017416858,"about_ca_system_score_codex":0.00019375296,"about_ca_system_score_gemma":0.0001485195,"threshold_uncertainty_score":0.0058264732},"labels":[],"label_agreement":null},{"id":"W2096656234","doi":"10.1243/095440503322617162","title":"Automatic adjustment of cutting conditions in rough turning","year":2003,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Toronto Metropolitan University","funders":"","keywords":"Cutting tool; Tool wear; Line (geometry); Computer science; Engineering; Engineering drawing; Machining; Mechanical engineering; Mathematics","score_opus":0.006360290860217916,"score_gpt":0.20997145914716783,"score_spread":0.20361116828694992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096656234","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40731484,0.00044723868,0.5778013,0.00010305627,0.00014403656,0.00019425958,0.00012549861,0.0075446274,0.0063251113],"genre_scores_gemma":[0.9798207,0.000054134674,0.019147163,0.000037692284,0.000020325027,0.000038670525,0.000050700055,0.00007686461,0.0007537303],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994809,0.000085023086,0.000018438737,0.00015450113,0.00018655902,0.00007460351],"domain_scores_gemma":[0.9992562,0.00030930556,0.00013477991,0.00012977266,0.00011951866,0.00005052579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032777767,0.00043945128,0.00077712676,0.0003878396,0.0003345483,0.00085892394,0.0007356047,0.0004718407,0.0013870648],"category_scores_gemma":[0.0016031258,0.00031754997,0.00022502057,0.00015815215,0.0003516707,0.0004370558,0.0005467302,0.00052402314,0.0003914286],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001593094,0.00039680878,0.0069143064,0.00036398738,0.00008532623,0.00061621336,0.0009812671,0.114996046,0.42045626,0.0025779845,0.0024982635,0.44852036],"study_design_scores_gemma":[0.00022675947,0.0009727395,0.014159021,0.00005386339,0.00009862856,0.0006817336,0.00018290729,0.8349308,0.13491733,0.004908917,0.008676173,0.00019122381],"about_ca_topic_score_codex":0.0007799578,"about_ca_topic_score_gemma":0.0010615633,"teacher_disagreement_score":0.0013870648,"about_ca_system_score_codex":0.00017612654,"about_ca_system_score_gemma":0.00023166808,"threshold_uncertainty_score":0.004640162},"labels":[],"label_agreement":null},{"id":"W2096944874","doi":"10.1109/im-m.2008.4449013","title":"Control output devices - actuators and displays for process automation - part 12 in a series of tutorials in instrumentation and measurement","year":2008,"lang":"en","type":"article","venue":"IEEE Instrumentation & Measurement Magazine","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Automation; Actuator; Stepper; Process (computing); Control engineering; Instrumentation (computer programming); Engineering; Torque; Servomotor; Realization (probability); Process control; Machining; Solenoid; Control system; Computer science; Automotive engineering; Electrical engineering; Mechanical engineering","score_opus":0.03432399400738799,"score_gpt":0.2499740367352159,"score_spread":0.2156500427278279,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096944874","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0072290148,0.25222784,0.53430814,0.003416833,0.012908075,0.00045741905,0.000565708,0.004591732,0.1842952],"genre_scores_gemma":[0.08118484,0.21579558,0.22692308,0.0040942356,0.007196597,0.0007410741,0.0012965882,0.0017896653,0.4609784],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99946314,0.00008041134,0.00003220159,0.000085366795,0.00030396855,0.000035029854],"domain_scores_gemma":[0.99968755,0.00016272599,0.00002018928,0.000027179542,0.00008910426,0.000013265921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040138155,0.0011943482,0.0007625046,0.0008458609,0.00039355757,0.0021634302,0.00078294845,0.0013815252,0.022002991],"category_scores_gemma":[0.0006150614,0.00045622652,0.0003433432,0.0011571606,0.00072787865,0.002058335,0.0005757817,0.0015333755,0.010297292],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012393853,0.00018981185,0.00046755315,0.0024657324,0.00003708191,0.00031771953,0.00027253648,0.0036846835,0.043304764,0.054045904,0.17644285,0.7186475],"study_design_scores_gemma":[0.000012310585,0.00019654715,0.00094689796,0.0004500275,0.000022568878,0.0012245633,0.00012212111,0.00582954,0.014995761,0.014546316,0.9616042,0.00004918039],"about_ca_topic_score_codex":0.00024212153,"about_ca_topic_score_gemma":0.00044171544,"teacher_disagreement_score":0.022002991,"about_ca_system_score_codex":0.00041481468,"about_ca_system_score_gemma":0.00028131838,"threshold_uncertainty_score":0.073607326},"labels":[],"label_agreement":null},{"id":"W2099325291","doi":"10.1177/0954405413484725","title":"Factors governing burr formation during high-speed slot milling of wrought aluminum alloys","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Enhanced Data Rates for GSM Evolution; Mechanical engineering; Materials science; Metallurgy; Process (computing); Aluminium; Engineering drawing; Engineering; Computer science","score_opus":0.007832276111374166,"score_gpt":0.18323886365200756,"score_spread":0.1754065875406334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099325291","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99617565,0.000859355,0.0027610334,0.000009798305,0.0000054115762,0.000019503545,0.000022353546,0.00001915444,0.00012762462],"genre_scores_gemma":[0.99808085,0.00024538726,0.0014609954,0.0000036121635,0.0000029363741,0.000005369588,0.000023659944,0.000005181192,0.00017206909],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99935764,0.00012628605,0.00006884761,0.00011029454,0.00027720327,0.000059712158],"domain_scores_gemma":[0.99756765,0.001244813,0.0007589886,0.000105844614,0.0002854011,0.000037320693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095950137,0.00028642014,0.00045936106,0.00027925806,0.00025650632,0.00058089563,0.0002962685,0.00038565823,0.00035830817],"category_scores_gemma":[0.0025183547,0.00031166623,0.00024636905,0.000283575,0.000497927,0.0005270864,0.00017587685,0.00025511414,0.0000931637],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007877686,0.00012399464,0.010207261,0.00047772945,0.000031850468,0.00019121055,0.00031998754,0.006282148,0.966932,0.00009800348,0.000052269417,0.014495945],"study_design_scores_gemma":[0.000047281254,0.0028968307,0.11632009,0.000023275543,0.00007284622,0.0002918181,0.00040466915,0.017113952,0.8619065,0.00014069758,0.00073287124,0.000049174898],"about_ca_topic_score_codex":0.00061621703,"about_ca_topic_score_gemma":0.0017681894,"teacher_disagreement_score":0.00095950137,"about_ca_system_score_codex":0.00026547594,"about_ca_system_score_gemma":0.00021295474,"threshold_uncertainty_score":0.005074382},"labels":[],"label_agreement":null},{"id":"W2100428166","doi":"","title":"Effect of tool cutter immersion on Al-Si bi-metallic materials in High-Speed-Milling","year":2006,"lang":"en","type":"article","venue":"Journal of Achievements of Materials and Manufacturing Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Brockhouse Institute for Materials Research; University of Windsor","funders":"","keywords":"Materials science; Immersion (mathematics); Metallurgy; High-speed steel; Metal; Mechanical engineering; Composite material; Engineering; Geometry","score_opus":0.0028252203123623654,"score_gpt":0.20065546886943822,"score_spread":0.19783024855707584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100428166","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979826,0.0005109299,0.0007481061,0.000028789242,0.000021099651,0.0000068358145,0.000045238306,0.00004889305,0.0006074695],"genre_scores_gemma":[0.9984773,0.00014862871,0.00072003424,0.000014399592,0.0000057291168,0.0000036122854,0.00003637603,0.000041721833,0.00055219023],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99973136,0.00003919546,0.000020601874,0.00006509073,0.00007948016,0.000064229906],"domain_scores_gemma":[0.99898165,0.00045893254,0.00019876196,0.0000717691,0.0002003669,0.00008838643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037271535,0.00030431896,0.0003798923,0.00017205368,0.00028807452,0.00064921787,0.00032875285,0.00044990992,0.0022559802],"category_scores_gemma":[0.0010083177,0.00041647602,0.00021620901,0.00023183713,0.00041414102,0.0005895158,0.00033585133,0.00042431592,0.00020997359],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090170384,0.00003250424,0.00032997204,0.000082757775,0.0000103110615,0.00005638641,0.00009126269,0.00024349322,0.99603003,0.000057567275,0.000044930563,0.002119115],"study_design_scores_gemma":[0.00002162105,0.00030197957,0.0018230013,0.0000043018376,0.000014516558,0.000027034766,0.000040509054,0.00072664826,0.99677426,0.000013584526,0.00024607935,0.0000064927945],"about_ca_topic_score_codex":0.0007314793,"about_ca_topic_score_gemma":0.0016344384,"teacher_disagreement_score":0.0022559802,"about_ca_system_score_codex":0.00040312688,"about_ca_system_score_gemma":0.00027677548,"threshold_uncertainty_score":0.007547021},"labels":[],"label_agreement":null},{"id":"W2101300165","doi":"10.3390/s100807263","title":"A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines","year":2010,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Field-programmable gate array; Wireless sensor network; Embedded system; Gate array; Field (mathematics); Wireless; Node (physics); Computer science; Engineering; Computer hardware; Computer network; Telecommunications","score_opus":0.011723115862835354,"score_gpt":0.23992126219335544,"score_spread":0.22819814633052007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101300165","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3019918,0.0010266762,0.6826748,0.00043071053,0.00020714907,0.00017407739,0.00018029343,0.0015743577,0.011740082],"genre_scores_gemma":[0.9233162,0.00020405382,0.07346607,0.00010722948,0.000023952638,0.000054739732,0.000070366616,0.000012300071,0.00274514],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99986136,0.00003459754,0.00000603723,0.000034057808,0.0000529067,0.00001093805],"domain_scores_gemma":[0.9998635,0.00004151357,0.000032015934,0.000019076666,0.00003277683,0.000011060424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019762112,0.00021112668,0.00016504766,0.00017934559,0.00012823078,0.00021866467,0.00057649193,0.00020148637,0.0007674013],"category_scores_gemma":[0.00024403846,0.00008041294,0.00007156641,0.00014573564,0.00018024494,0.00046055389,0.0001891589,0.00018986562,0.0001531902],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008213172,0.00023789423,0.005540445,0.0003172124,0.00006213149,0.00045007817,0.00012765173,0.08045119,0.5725389,0.014101526,0.005360781,0.31999072],"study_design_scores_gemma":[0.00011688848,0.0015235278,0.0061852,0.000028678622,0.00008523962,0.00086612965,0.00005227422,0.67150825,0.29007128,0.0033583846,0.026149465,0.000054689935],"about_ca_topic_score_codex":0.0003101696,"about_ca_topic_score_gemma":0.00081394153,"teacher_disagreement_score":0.0007674013,"about_ca_system_score_codex":0.00022908126,"about_ca_system_score_gemma":0.00022147699,"threshold_uncertainty_score":0.0025672317},"labels":[],"label_agreement":null},{"id":"W2101698175","doi":"10.1139/tcsme-2008-0029","title":"EFFECT OF FACE COOLING ON WORKPIECE TEMPERATURES USING 2D AND 3D FINITE ELEMENT ANALYSIS OF CREEP-FEED GRINDING","year":2008,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Grinding; Materials science; Finite element method; Coolant; Creep; Heat generation; Steady state (chemistry); Contact area; Work (physics); Intensity (physics); Mechanics; Mechanical engineering; Composite material; Structural engineering; Engineering; Thermodynamics","score_opus":0.008515589042147399,"score_gpt":0.22130817755594775,"score_spread":0.21279258851380037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101698175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8691732,0.00017211349,0.12603311,0.000066042594,0.000035525518,0.00007589453,0.00020233137,0.0004667607,0.0037749542],"genre_scores_gemma":[0.95957416,0.00008244637,0.038854614,0.000015917518,0.000004460465,0.00006251193,0.00014720409,0.000088497945,0.0011701883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995814,0.00005639571,0.000020948683,0.000050326373,0.0002433549,0.00004757241],"domain_scores_gemma":[0.9991744,0.0005033686,0.0000791714,0.0000974477,0.0001199669,0.000025636993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056576054,0.0006811218,0.00075768057,0.0003707798,0.00041422708,0.0009691936,0.000672258,0.0010052708,0.0019350171],"category_scores_gemma":[0.0016620426,0.0006585518,0.0009899754,0.00022300603,0.00065361965,0.0004804923,0.00041358432,0.00059995515,0.00030550442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022866132,0.000097897784,0.0035511171,0.00010245393,0.000025704341,0.00014499157,0.00029490722,0.87325245,0.10746546,0.0006678313,0.00016998682,0.013998444],"study_design_scores_gemma":[0.00001266444,0.00009018811,0.0020368288,0.0000071076242,0.000011894111,0.000042587788,0.00004015105,0.96425927,0.033001013,0.00009499318,0.00037656297,0.000026786365],"about_ca_topic_score_codex":0.0068235286,"about_ca_topic_score_gemma":0.0075182305,"teacher_disagreement_score":0.0068235286,"about_ca_system_score_codex":0.0007070309,"about_ca_system_score_gemma":0.000993405,"threshold_uncertainty_score":0.0135676265},"labels":[],"label_agreement":null},{"id":"W2101854606","doi":"10.5897/jmer.9000029","title":"Investigation of cutting parameters of surface roughness for a non-ferrous material using artificial neural network in CNC turning","year":2011,"lang":"en","type":"article","venue":"Mechanical Engineering Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Surface roughness; Artificial neural network; Machining; Process (computing); Mechanical engineering; Surface finish; Cnc milling; Cutting tool; Materials science; Numerical control; Engineering; Engineering drawing; Computer science; Composite material; Artificial intelligence","score_opus":0.10032607530063252,"score_gpt":0.3109572856480181,"score_spread":0.21063121034738558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101854606","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93463373,0.00037391938,0.06261369,0.00007595561,0.000024810142,0.000025343503,0.000054976557,0.00017308393,0.002024496],"genre_scores_gemma":[0.9948612,0.000069368754,0.004654676,0.000005873916,0.0000016552522,0.000008744851,0.00003418377,0.0000045881548,0.0003596829],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998808,0.000020778802,0.000007056079,0.000023636,0.000055487926,0.000012187231],"domain_scores_gemma":[0.9996979,0.00017538013,0.00002866729,0.000013036247,0.00007861743,0.000006316338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002998601,0.0002461812,0.00024919855,0.0003010084,0.00011900259,0.00024345,0.00021344364,0.0004404599,0.00034142865],"category_scores_gemma":[0.00062019704,0.0001562813,0.00027576534,0.000232499,0.00015495149,0.00017490337,0.00007129931,0.00023409363,0.000056758818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065693905,0.00025487808,0.018135682,0.0004333016,0.00008539647,0.00033571172,0.00023399314,0.63713914,0.19398774,0.00050482637,0.0006150695,0.1476173],"study_design_scores_gemma":[0.00000584906,0.00016233814,0.011453178,0.0000075428575,0.000018951696,0.00004659079,0.000029802213,0.9651279,0.022881635,0.00009941748,0.00015504485,0.000011741648],"about_ca_topic_score_codex":0.0032323494,"about_ca_topic_score_gemma":0.0039228513,"teacher_disagreement_score":0.0032323494,"about_ca_system_score_codex":0.00022617524,"about_ca_system_score_gemma":0.00014552123,"threshold_uncertainty_score":0.0064271092},"labels":[],"label_agreement":null},{"id":"W2103067845","doi":"10.1016/j.ijmachtools.2009.06.010","title":"Estimation of machine-tool dynamic parameters during machining operation through operational modal analysis","year":2009,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":230,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Modal; Modal analysis; Machine tool; Operational Modal Analysis; Stability (learning theory); Numerical control; Computer science; Cutting tool; Autoregressive–moving-average model; Mechanical engineering; Engineering; Autoregressive model; Structural engineering; Finite element method; Mathematics; Machine learning; Materials science; Statistics","score_opus":0.0053857236275409864,"score_gpt":0.25471854652696796,"score_spread":0.249332822899427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103067845","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8849203,0.00009744812,0.11323498,0.00002340743,0.000006086809,0.000032253767,0.00009952423,0.00019279517,0.0013931682],"genre_scores_gemma":[0.9962767,0.000016932072,0.0034843609,0.0000015160126,0.0000011116863,0.000006186024,0.00003314775,0.000008796432,0.00017136981],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998802,0.00001851152,0.0000052168243,0.000025341538,0.00005102973,0.000019622184],"domain_scores_gemma":[0.99948716,0.0002947438,0.000070158836,0.00003095587,0.00009561532,0.00002141079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020838437,0.00032413227,0.00032480044,0.00044614077,0.00023035711,0.00026129867,0.00030057968,0.00031490807,0.0008234673],"category_scores_gemma":[0.00078669493,0.00020235774,0.00014877123,0.0002702902,0.00020230103,0.00048805898,0.0002117549,0.00026095958,0.00016484555],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002257035,0.0003104218,0.039218303,0.00026487128,0.00006557255,0.00022139035,0.0005684099,0.1058422,0.66536117,0.000759161,0.0004519795,0.18467951],"study_design_scores_gemma":[0.000029998078,0.00041016244,0.1270568,0.000017683531,0.000047401223,0.0001722166,0.00019813787,0.76094645,0.10967515,0.0006692564,0.00071549456,0.00006119275],"about_ca_topic_score_codex":0.0015304019,"about_ca_topic_score_gemma":0.0023981256,"teacher_disagreement_score":0.0015304019,"about_ca_system_score_codex":0.00015534737,"about_ca_system_score_gemma":0.00018490954,"threshold_uncertainty_score":0.003042996},"labels":[],"label_agreement":null},{"id":"W2103594559","doi":"10.5267/j.ijiec.2013.04.002","title":"Optimization of multiple performance characteristics in turning using Taguchi’s quality loss function: An experimental investigation","year":2013,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taguchi methods; Quality (philosophy); Function (biology); Computer science; Engineering; Control theory (sociology); Statistics; Mathematics; Artificial intelligence; Biology; Physics","score_opus":0.03909334774248556,"score_gpt":0.2811338005585801,"score_spread":0.24204045281609454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103594559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900794,0.00018197807,0.008874163,0.000016474478,0.000009457818,0.000038826078,0.000038274986,0.000042789863,0.0007187139],"genre_scores_gemma":[0.9955075,0.0000889183,0.0040058233,0.0000050866556,0.0000026728062,0.000016710394,0.000021421014,0.000008844465,0.00034306894],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99920195,0.00011398745,0.000028938997,0.000088114684,0.00038556123,0.00018143696],"domain_scores_gemma":[0.99906343,0.00038939176,0.00014959833,0.00015080874,0.00018053177,0.0000662851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010280052,0.00050337083,0.0007547649,0.0005354089,0.00033617293,0.00042726146,0.0005891664,0.0007248655,0.0007057031],"category_scores_gemma":[0.0010672889,0.0002799469,0.0004225802,0.0006292945,0.0005332512,0.0002593204,0.00030406172,0.00044675657,0.00014302482],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064610946,0.0004302203,0.0011284804,0.00016051832,0.000018198574,0.000118582255,0.0002447906,0.011505726,0.9691834,0.00023752658,0.00006854891,0.016257977],"study_design_scores_gemma":[0.000077071214,0.008333123,0.011507729,0.000016135065,0.000054921693,0.00016946218,0.000163739,0.03770292,0.94114435,0.00010295323,0.0006764848,0.000050945913],"about_ca_topic_score_codex":0.00047157874,"about_ca_topic_score_gemma":0.00075066154,"teacher_disagreement_score":0.0010280052,"about_ca_system_score_codex":0.00025640483,"about_ca_system_score_gemma":0.0002175577,"threshold_uncertainty_score":0.005436659},"labels":[],"label_agreement":null},{"id":"W2104326779","doi":"10.3233/ifs-120706","title":"Fuzzy cutting force modelling in micro-milling","year":2013,"lang":"en","type":"article","venue":"Journal of Intelligent & Fuzzy Systems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Subtractive color; Computer science; Machining; Process (computing); Filter (signal processing); Fuzzy logic; Cluster analysis; Noise (video); Fuzzy clustering; Mechanical engineering; Artificial intelligence; Engineering; Computer vision","score_opus":0.014599760818364558,"score_gpt":0.2263373130541962,"score_spread":0.21173755223583163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104326779","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052252017,0.00046565474,0.9452974,0.00006421088,0.00002698638,0.000020349205,0.000032618475,0.00017031682,0.0016704929],"genre_scores_gemma":[0.9448314,0.00032244867,0.053057224,0.000018397197,0.000012209725,0.00003501324,0.000055671935,0.000012892966,0.0016546862],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998233,0.000022868146,0.00001117056,0.000034905624,0.000092899776,0.000014923306],"domain_scores_gemma":[0.99985576,0.000061283135,0.000022752654,0.000011113182,0.000043835567,0.000005170575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031837996,0.00029877285,0.00042933962,0.00029410433,0.00023215964,0.00048588196,0.000617103,0.0006452525,0.00044917906],"category_scores_gemma":[0.00057124434,0.0001826325,0.0003655266,0.00028708144,0.000266714,0.00047361926,0.00019804972,0.00040279038,0.00015189117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030481626,0.000016079868,0.00038509959,0.000042156687,0.000015008068,0.00004562374,0.000044110115,0.95707345,0.009253087,0.0026605825,0.00011949083,0.030314842],"study_design_scores_gemma":[9.3494396e-7,0.000006949647,0.00013893953,0.000001775754,0.0000015121306,0.0000069972702,0.000002719658,0.9983267,0.0008651764,0.00050974434,0.00013566625,0.0000028170198],"about_ca_topic_score_codex":0.009407807,"about_ca_topic_score_gemma":0.006218902,"teacher_disagreement_score":0.009407807,"about_ca_system_score_codex":0.00036723597,"about_ca_system_score_gemma":0.00039983753,"threshold_uncertainty_score":0.018706143},"labels":[],"label_agreement":null},{"id":"W2108138788","doi":"10.1109/icma.2005.1626684","title":"Robust adaptive control of machining operations","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Machining; Numerical control; Robustness (evolution); Parametric statistics; Machine tool; Control theory (sociology); Adaptive control; Noise (video); Cutting tool; Computer science; Process (computing); Engineering; Control engineering; Mechanical engineering; Control (management); Mathematics; Artificial intelligence","score_opus":0.009025337983348388,"score_gpt":0.19435385394768845,"score_spread":0.18532851596434005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108138788","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01775075,0.0004628504,0.97641796,0.00009817437,0.0000925124,0.000046279478,0.000030048273,0.0007383357,0.004363091],"genre_scores_gemma":[0.96895504,0.00037763358,0.02772356,0.000054080538,0.00007803656,0.00013167408,0.000059641174,0.000031132284,0.0025891312],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938834,0.000120376666,0.00003776112,0.00018503271,0.00020713471,0.00006129644],"domain_scores_gemma":[0.99925655,0.0003605236,0.00014022838,0.00005908209,0.00016206481,0.000021510421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064775744,0.00096747524,0.0006520346,0.00028848954,0.00026800612,0.0009028405,0.000878794,0.00058026344,0.0012220984],"category_scores_gemma":[0.002500864,0.00024109324,0.00030601514,0.00033672384,0.0006351101,0.00039005297,0.00047088362,0.0008887106,0.00026902478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001484713,0.000051827534,0.00026012363,0.00015308456,0.00004707902,0.000071622264,0.00007053823,0.8994831,0.013325807,0.0077744494,0.00080054975,0.07781339],"study_design_scores_gemma":[0.00001811625,0.00006752561,0.0002148675,0.0000043926075,0.0000053167078,0.000009327679,0.0000038848266,0.9965527,0.0011376207,0.0014005135,0.0005799367,0.000005789202],"about_ca_topic_score_codex":0.0037859303,"about_ca_topic_score_gemma":0.0019577164,"teacher_disagreement_score":0.0037859303,"about_ca_system_score_codex":0.0004934396,"about_ca_system_score_gemma":0.00047097297,"threshold_uncertainty_score":0.007527828},"labels":[],"label_agreement":null},{"id":"W21084331","doi":"10.1093/rpd/ncq384","title":"A comparative study on predictive modeling of tool wear using experimental, analytical and numerical schemes","year":2008,"lang":"en","type":"article","venue":"international conference on Modelling and simulation","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Tool wear; Machining; Artificial neural network; Flank; Carbide; Computer science; Process (computing); Mechanical engineering; Cutting tool; Materials science; Engineering; Machine learning; Metallurgy","score_opus":0.14741114451745185,"score_gpt":0.36751206970442335,"score_spread":0.2201009251869715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W21084331","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25213686,0.004141952,0.6970498,0.0013069676,0.00045757796,0.00043055872,0.0008924707,0.0016338871,0.04195],"genre_scores_gemma":[0.9289332,0.0012682928,0.06530327,0.00009490594,0.0000951011,0.0003842311,0.0003452333,0.00021843058,0.003357334],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924123,0.00035356267,0.000045361237,0.000055011616,0.00024254514,0.00006234738],"domain_scores_gemma":[0.99155796,0.006461611,0.00035138728,0.0005741488,0.00094979396,0.00010505578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026253946,0.0009451448,0.0010731356,0.0010089509,0.0006166374,0.0012461073,0.0018482378,0.0017985402,0.0045002676],"category_scores_gemma":[0.010348282,0.00039479608,0.0009058555,0.0010463753,0.00081976916,0.001157526,0.0006841459,0.0010050357,0.0003319688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056714867,0.000057350197,0.0006654693,0.000101055346,0.0000130364215,0.00002033812,0.000028986517,0.98667264,0.00033765167,0.003687251,0.00019438769,0.008165079],"study_design_scores_gemma":[0.0000036883198,0.000022282928,0.00009290346,0.000009269058,0.0000025909321,0.0000046340933,0.0000073789365,0.99907565,0.00017429586,0.00038211283,0.0002220373,0.0000032484807],"about_ca_topic_score_codex":0.014701769,"about_ca_topic_score_gemma":0.006184089,"teacher_disagreement_score":0.014701769,"about_ca_system_score_codex":0.0013559213,"about_ca_system_score_gemma":0.0011249873,"threshold_uncertainty_score":0.029232442},"labels":[],"label_agreement":null},{"id":"W2108832095","doi":"10.1016/j.ijmachtools.2005.10.001","title":"Surface defects during microcutting","year":2005,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":79,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Dimple; Microscale chemistry; Microstructure; Materials science; Grain boundary; Dissipation; Grain size; Chip formation; Surface (topology); Composite material; Metallurgy; Machining; Geometry; Tool wear; Physics","score_opus":0.004752591393421377,"score_gpt":0.22690664144298253,"score_spread":0.22215405004956115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108832095","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980564,0.0001863713,0.0011309863,0.00001172058,0.0000138979485,0.000006225668,0.000019603867,0.000048638358,0.0005261225],"genre_scores_gemma":[0.9991547,0.000035104807,0.00025033797,0.0000041899452,0.0000019220618,0.0000015528324,0.000025912994,0.000014024345,0.0005122742],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979645,0.000019310257,0.0000045924926,0.000030074976,0.00008575304,0.00006384457],"domain_scores_gemma":[0.998936,0.0005300918,0.00015863002,0.000101283375,0.00020603603,0.000068006215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024801175,0.00025021465,0.0002731549,0.00033068637,0.0003537477,0.00046485176,0.0003919999,0.0003444443,0.0016583563],"category_scores_gemma":[0.0013050386,0.00023303962,0.00014269067,0.00032453702,0.000501,0.0005007844,0.00026920054,0.00033542383,0.00015105058],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020616017,0.000121774945,0.009511936,0.00014898821,0.000027014388,0.0015999232,0.00079474633,0.01815652,0.93523353,0.0008917274,0.00050825067,0.030943919],"study_design_scores_gemma":[0.000041728134,0.0013305879,0.043145373,0.000018975647,0.000041890497,0.0007282949,0.00055729196,0.059766866,0.8926334,0.00033862836,0.0013624869,0.00003446459],"about_ca_topic_score_codex":0.0020190945,"about_ca_topic_score_gemma":0.0028593226,"teacher_disagreement_score":0.0020190945,"about_ca_system_score_codex":0.00044157545,"about_ca_system_score_gemma":0.00023184597,"threshold_uncertainty_score":0.005547762},"labels":[],"label_agreement":null},{"id":"W2109884555","doi":"10.1364/ao.48.004851","title":"One-dimensional single-mode fiber-optic displacement sensors for submillimeter measurements","year":2009,"lang":"en","type":"article","venue":"Applied Optics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Optics; Optical fiber; Single-mode optical fiber; Displacement (psychology); Fiber optic sensor; Materials science; Optoelectronics; Physics","score_opus":0.027832369265636536,"score_gpt":0.25313302436635043,"score_spread":0.2253006551007139,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109884555","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3152338,0.0029124995,0.6731506,0.0005006651,0.00023367419,0.0001167407,0.00036537438,0.0023653004,0.0051214052],"genre_scores_gemma":[0.47391063,0.00059563824,0.5233069,0.00007615449,0.000028474009,0.00007918497,0.00010537369,0.000031263517,0.0018664364],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997898,0.000029708664,0.000009070357,0.00003852063,0.00012057211,0.000012333627],"domain_scores_gemma":[0.9996668,0.00014924223,0.00006421399,0.00003455164,0.000066030836,0.0000191139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021550781,0.00038097383,0.00026363163,0.00020517469,0.00018313629,0.0002328908,0.0004407008,0.0002765911,0.0013504024],"category_scores_gemma":[0.0005246588,0.00021269947,0.00014803623,0.00019696048,0.00023674629,0.00046462077,0.0002670761,0.0003020891,0.0003756883],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007469188,0.00003202236,0.001521466,0.00022022321,0.000010724253,0.000031470867,0.000060420687,0.005930728,0.91300684,0.0028805297,0.00076692435,0.07546389],"study_design_scores_gemma":[0.000024994506,0.0004514742,0.0043054833,0.000024159037,0.000031557254,0.0004732016,0.000038218423,0.14274594,0.8384949,0.001572309,0.011764135,0.00007355674],"about_ca_topic_score_codex":0.0003339467,"about_ca_topic_score_gemma":0.0014583596,"teacher_disagreement_score":0.0013504024,"about_ca_system_score_codex":0.0002750438,"about_ca_system_score_gemma":0.00021181669,"threshold_uncertainty_score":0.0045175552},"labels":[],"label_agreement":null},{"id":"W2109975817","doi":"10.4028/www.scientific.net/aef.1.273","title":"Improving the Performance of Process Controllers Using a New Clustered Neural Network","year":2011,"lang":"en","type":"article","venue":"Advanced engineering forum","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Artificial neural network; Controller (irrigation); Multilayer perceptron; Machining; Scheme (mathematics); Process (computing); Line (geometry); Perceptron; Adaptability; Control engineering; Artificial intelligence; Engineering; Mechanical engineering","score_opus":0.008848094786354855,"score_gpt":0.1992693480790223,"score_spread":0.19042125329266746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109975817","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1067438,0.00034765428,0.88840294,0.00012172255,0.00008254694,0.00008201891,0.000035904577,0.0010129563,0.003170442],"genre_scores_gemma":[0.84653795,0.00015280624,0.15094645,0.000074070624,0.000040692892,0.00008192384,0.00007325112,0.000049689414,0.0020432216],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997241,0.000033895634,0.00001504365,0.00008062764,0.000116982046,0.000029327288],"domain_scores_gemma":[0.9995436,0.00014633618,0.000051157538,0.00006266925,0.00017555404,0.000020757892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054915325,0.00056943117,0.000364218,0.00027447692,0.00022393525,0.0004897432,0.0011299794,0.00064320577,0.0011311404],"category_scores_gemma":[0.0015146652,0.0002441213,0.00027032988,0.0002336617,0.00028329933,0.0005899514,0.0004667682,0.0006181467,0.0002543513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021372645,0.00016329798,0.0009193843,0.00013735867,0.00010033363,0.00007588777,0.00007413125,0.7325922,0.07042736,0.0016930914,0.000775431,0.19282773],"study_design_scores_gemma":[0.00000963732,0.000097080774,0.00026263352,0.0000036422705,0.000010415102,0.000015433387,0.0000028792404,0.99107575,0.0079357,0.00018882648,0.00039207685,0.000005778266],"about_ca_topic_score_codex":0.002944149,"about_ca_topic_score_gemma":0.004022488,"teacher_disagreement_score":0.002944149,"about_ca_system_score_codex":0.00052427745,"about_ca_system_score_gemma":0.00046350074,"threshold_uncertainty_score":0.0058540106},"labels":[],"label_agreement":null},{"id":"W2111683180","doi":"10.1177/0954405413477067","title":"An experimental study on the vibration response of a robotic machining system","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Vibration; Rigidity (electromagnetism); Surface roughness; SIGNAL (programming language); Stiffness; Root mean square; Mechanical engineering; Surface finish; Aerospace; Machine tool; Robot; Computer science; Engineering; Acoustics; Structural engineering; Materials science; Artificial intelligence; Physics; Composite material","score_opus":0.010053982165464015,"score_gpt":0.22136015368176704,"score_spread":0.21130617151630302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111683180","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9780343,0.00010159583,0.020303776,0.00004570439,0.00004986818,0.000081654165,0.000084698404,0.00013198848,0.0011664309],"genre_scores_gemma":[0.99387276,0.000038443806,0.0051334044,0.000021294338,0.000007721542,0.000045471737,0.000056838755,0.000011108336,0.0008129653],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999395,0.000104231876,0.000047671343,0.00015568972,0.0002129236,0.00008451104],"domain_scores_gemma":[0.9989318,0.00047173927,0.00009098898,0.00014525751,0.00029364237,0.00006648406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005880105,0.00038698368,0.0003158218,0.00029789683,0.00031289432,0.00021789504,0.00045166072,0.0007543931,0.0024395217],"category_scores_gemma":[0.0012998367,0.00018318553,0.0002872676,0.00016750813,0.0004325251,0.0002933994,0.00026799284,0.00027748596,0.00029979722],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066915934,0.00022343517,0.0013942987,0.00017493263,0.00001605715,0.00014681689,0.00026856648,0.0021876039,0.9828736,0.0001087647,0.000107512424,0.011829194],"study_design_scores_gemma":[0.00020609387,0.020806946,0.05331384,0.00005655633,0.000108354616,0.00067943,0.0006167219,0.054437954,0.8669024,0.00027869237,0.0025113407,0.00008173905],"about_ca_topic_score_codex":0.00027920745,"about_ca_topic_score_gemma":0.0003264613,"teacher_disagreement_score":0.0024395217,"about_ca_system_score_codex":0.00011673909,"about_ca_system_score_gemma":0.0001613789,"threshold_uncertainty_score":0.008161008},"labels":[],"label_agreement":null},{"id":"W2112050740","doi":"10.1115/1.2338648","title":"Analysis of the Chatter Instability in a Nonlinear Model for Drilling","year":2006,"lang":"en","type":"article","venue":"Journal of Computational and Nonlinear Dynamics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear system; Bifurcation; Instability; Vibration; Stability (learning theory); Hopf bifurcation; Drilling; Work (physics); Criticality; Control theory (sociology); Deep hole drilling; Structural engineering; Engineering; Mathematics; Mechanics; Geology; Computer science; Physics; Mechanical engineering","score_opus":0.006319411402548107,"score_gpt":0.23248015223705915,"score_spread":0.22616074083451104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112050740","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23948254,0.0006138138,0.74733144,0.000397909,0.000061206105,0.00007518951,0.00009287791,0.00025355187,0.0116914725],"genre_scores_gemma":[0.98460394,0.00018700147,0.009737553,0.000041084335,0.000018666871,0.00006977905,0.000040723193,0.000030238214,0.0052710036],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985874,0.000044399778,0.000005974258,0.000022109574,0.00005052064,0.00001826133],"domain_scores_gemma":[0.99948347,0.00028451942,0.000098951066,0.00002750803,0.0000835976,0.00002195387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004210949,0.0007002455,0.00055402634,0.00043262343,0.0003132492,0.0005255017,0.00062913646,0.0008503615,0.0020588876],"category_scores_gemma":[0.0016973208,0.00022395873,0.0005439394,0.00012238261,0.00069816184,0.00047705352,0.00065295584,0.0006388111,0.00017426611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057715257,0.000026618596,0.00073131337,0.00014454522,0.000038484875,0.00023903722,0.00017352871,0.95108944,0.020034682,0.023760187,0.00029216762,0.0034122155],"study_design_scores_gemma":[0.000002331749,0.000012491092,0.00010376046,0.0000026919035,0.000003176551,0.000015137302,0.000006499858,0.9980652,0.00046967162,0.0011920322,0.00012372386,0.0000033603962],"about_ca_topic_score_codex":0.0043792087,"about_ca_topic_score_gemma":0.0023835532,"teacher_disagreement_score":0.0043792087,"about_ca_system_score_codex":0.000490954,"about_ca_system_score_gemma":0.00043199584,"threshold_uncertainty_score":0.008707464},"labels":[],"label_agreement":null},{"id":"W2113444627","doi":"10.1016/j.ijmachtools.2005.05.015","title":"Investigation of micro-cutting operations","year":2005,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":752,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Machining; Macro; Miniaturization; Mechanical engineering; Manufacturing engineering; Power consumption; Machine tool; Engineering; Computer science; Power (physics); Electrical engineering","score_opus":0.008829870154080523,"score_gpt":0.23713074564701195,"score_spread":0.22830087549293143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113444627","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96062756,0.0008015301,0.022788497,0.000051409213,0.000028550487,0.000038134087,0.00008738716,0.00008072362,0.015496254],"genre_scores_gemma":[0.99263966,0.00016126303,0.0051144334,0.000005329752,0.000005237259,0.000006289915,0.00006064366,0.000007874499,0.0019992609],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981886,0.000016032545,0.000006069845,0.000028703858,0.00010489097,0.000025522877],"domain_scores_gemma":[0.9996637,0.00013781799,0.00004240939,0.000041861455,0.00009304044,0.000021093712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014699633,0.00019666397,0.00021932702,0.00038292343,0.00030251622,0.00041766086,0.0003640087,0.00027041134,0.004190406],"category_scores_gemma":[0.00054857857,0.00012623963,0.00017924319,0.00038934377,0.00021058708,0.00047129096,0.00017520615,0.0002499021,0.00033282125],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014102319,0.00029962912,0.011237807,0.00037618825,0.000043351043,0.00057333417,0.0002341375,0.036657605,0.7703172,0.018364327,0.000586336,0.15989995],"study_design_scores_gemma":[0.000041946216,0.0017170752,0.07505835,0.00004018558,0.00006483042,0.0017480685,0.00067259365,0.3737846,0.53034407,0.0062804623,0.010200427,0.000047470636],"about_ca_topic_score_codex":0.00051831733,"about_ca_topic_score_gemma":0.00056138163,"teacher_disagreement_score":0.004190406,"about_ca_system_score_codex":0.00021901209,"about_ca_system_score_gemma":0.00026508773,"threshold_uncertainty_score":0.014018357},"labels":[],"label_agreement":null},{"id":"W2113695885","doi":"10.1115/1.4030936","title":"A New Approach to Blade Design With Constant Rake and Relief Angles for Face-Hobbing of Bevel Gears","year":2015,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Rake; Hobbing; Bevel; Rake angle; Enhanced Data Rates for GSM Evolution; Kinematics; Machining; Face (sociological concept); Mechanical engineering; Bevel gear; Blade (archaeology); Cutting tool; Structural engineering; Drilling; Engineering; Finite element method; Tool wear; Engineering drawing; Computer science; Artificial intelligence","score_opus":0.02268060016770981,"score_gpt":0.22321966435499208,"score_spread":0.20053906418728226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113695885","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011463653,0.00019138429,0.98671454,0.000020847894,0.000025422323,0.00007378318,0.000011586771,0.0001236587,0.0013750802],"genre_scores_gemma":[0.18892747,0.00029128784,0.80911106,0.000026278307,0.000022353554,0.00012216394,0.000047800866,0.000058931473,0.001392542],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996197,0.000082948376,0.000038353824,0.00006282422,0.00016593671,0.000030065874],"domain_scores_gemma":[0.9996717,0.00007089516,0.000057819536,0.000039961946,0.00014343839,0.00001619426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051833165,0.0007562469,0.0006365797,0.00066364993,0.00028923946,0.0007011012,0.0009410985,0.0006439209,0.0015716613],"category_scores_gemma":[0.000858269,0.00044889635,0.0007287081,0.00035443195,0.00037085227,0.00043443998,0.00048084164,0.0005846939,0.0005662107],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013770661,0.00015565321,0.0016697274,0.0011418376,0.00008611972,0.00045074668,0.0005035631,0.3819598,0.2304407,0.017265724,0.001618759,0.3645696],"study_design_scores_gemma":[0.000057389538,0.0005150268,0.00073428004,0.000066338915,0.00004639841,0.00045347438,0.00012589323,0.9587945,0.018073307,0.0041789184,0.016911505,0.00004305121],"about_ca_topic_score_codex":0.00067487353,"about_ca_topic_score_gemma":0.0007941997,"teacher_disagreement_score":0.0015716613,"about_ca_system_score_codex":0.00024756286,"about_ca_system_score_gemma":0.0004519706,"threshold_uncertainty_score":0.0052577257},"labels":[],"label_agreement":null},{"id":"W2115588091","doi":"10.1109/acc.2003.1243995","title":"Two degree-of-freedom modeling and robust chatter control in metal cutting by piezoelectricity","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Control theory (sociology); Adaptive control; Vibration; Hysteresis; Displacement (psychology); Robust control; Computer science; Process (computing); Control engineering; Engineering; Control (management); Control system; Physics; Acoustics; Artificial intelligence","score_opus":0.012564672307594347,"score_gpt":0.21810902977916571,"score_spread":0.20554435747157138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115588091","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0970435,0.00040329807,0.89927536,0.00015643156,0.000038588845,0.000018723915,0.000018919458,0.00020414374,0.0028411264],"genre_scores_gemma":[0.9876271,0.00013262358,0.010770844,0.000017779495,0.00001052855,0.0000291918,0.000014530618,0.000009368922,0.0013881407],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978226,0.00007034104,0.000010068987,0.00003203557,0.00007811137,0.000027284965],"domain_scores_gemma":[0.99977833,0.00010969404,0.000048664737,0.000022445665,0.000032578428,0.000008385509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004279332,0.00047070056,0.00038140587,0.0002232356,0.0001714296,0.00042871755,0.00068468763,0.00060164265,0.0005920697],"category_scores_gemma":[0.0006808317,0.00031103072,0.00044795935,0.00014451126,0.00056904374,0.0004273847,0.0003997434,0.0006239631,0.000093598246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006514772,0.000021822334,0.00027955082,0.00005232321,0.000019725161,0.0001172252,0.0001203003,0.9655604,0.013434855,0.012302659,0.00011119106,0.007914762],"study_design_scores_gemma":[0.000004532647,0.000027426884,0.00008672045,0.000001423608,0.0000023199273,0.000008244992,0.0000031817547,0.99821305,0.00056981866,0.0009769122,0.000103313796,0.0000031098964],"about_ca_topic_score_codex":0.0038951295,"about_ca_topic_score_gemma":0.0020850385,"teacher_disagreement_score":0.0038951295,"about_ca_system_score_codex":0.00025447088,"about_ca_system_score_gemma":0.0002829522,"threshold_uncertainty_score":0.0077449083},"labels":[],"label_agreement":null},{"id":"W2116310856","doi":"10.1007/978-1-4614-4226-4_23","title":"Experimental Study of High Speed Ball End Milling of Titanium Alloy (Ti-6Al-4V)","year":2012,"lang":"en","type":"book-chapter","venue":"Conference proceedings of the Society for Experimental Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"American Water (Canada)","funders":"","keywords":"Aerospace; Materials science; Titanium alloy; End milling; Machining; Surface roughness; Ball (mathematics); Mechanical engineering; Microstructure; Metallurgy; Surface finish; Residual stress; Alloy; Surface integrity; Engineering; Composite material; Geometry; Aerospace engineering","score_opus":0.02358857055800223,"score_gpt":0.2455494691686597,"score_spread":0.22196089861065746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116310856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918445,0.00046038732,0.004578369,0.000031346026,0.000029669498,0.000023530165,0.000120959514,0.000059483053,0.0028517141],"genre_scores_gemma":[0.9957228,0.0001339826,0.002012995,0.000008907585,0.0000075564026,0.0000091364755,0.000109156485,0.000017664875,0.0019778253],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996872,0.000032398122,0.0000123708905,0.000061310624,0.00016499446,0.00004162184],"domain_scores_gemma":[0.99922407,0.0003137651,0.00008894166,0.00013353149,0.00020917054,0.000030463507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033412376,0.00024223469,0.00035027176,0.00029280447,0.0006049939,0.00033992587,0.0005802681,0.0005671543,0.00266279],"category_scores_gemma":[0.00062751723,0.00026267424,0.00027208222,0.00036945575,0.0005172739,0.0004207043,0.00019832334,0.00038396305,0.00037617484],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007807853,0.00017236186,0.00097556657,0.00015117905,0.00001408846,0.00009868436,0.00016433102,0.00094419357,0.9888787,0.00027538434,0.0002255872,0.0073190667],"study_design_scores_gemma":[0.000059549042,0.002276462,0.018155405,0.000010419868,0.000032291267,0.00024696166,0.00021774741,0.0059224386,0.97090393,0.00014465801,0.002007452,0.000022637536],"about_ca_topic_score_codex":0.00077895354,"about_ca_topic_score_gemma":0.00097304955,"teacher_disagreement_score":0.00266279,"about_ca_system_score_codex":0.00024393166,"about_ca_system_score_gemma":0.00022472642,"threshold_uncertainty_score":0.008907855},"labels":[],"label_agreement":null},{"id":"W2117073511","doi":"10.2991/ijndc.2014.2.2.5","title":"Multi-Objective Optimization for Milling Operations using Genetic Algorithms under Various Constraints","year":2014,"lang":"en","type":"article","venue":"˜The œInternational journal of networked and distributed computing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Collège de Maisonneuve; Concordia University","funders":"Natural Science Foundation of Hebei Province; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Computer science; Genetic algorithm; Mathematical optimization; Algorithm; Machine learning; Mathematics","score_opus":0.015289614348946434,"score_gpt":0.26002909212342307,"score_spread":0.24473947777447663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117073511","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021569429,0.0005073432,0.9743774,0.00012389393,0.00002538927,0.00005792417,0.00004831758,0.00013958987,0.003150735],"genre_scores_gemma":[0.6064049,0.00088267855,0.3881227,0.00011031488,0.00004366062,0.0004684349,0.00018571067,0.000118622695,0.003662958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996402,0.00014066296,0.000013571197,0.000056359404,0.00010889076,0.000040282397],"domain_scores_gemma":[0.9994235,0.00040836632,0.00006852794,0.000019799616,0.00006369295,0.00001607939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000920339,0.0013259194,0.0013520141,0.00083017204,0.00047803952,0.0011352835,0.00096880674,0.0015266424,0.0015072885],"category_scores_gemma":[0.0017008715,0.00060139096,0.0009569753,0.0011753198,0.00049680367,0.00087606895,0.0006149972,0.0010598283,0.00025561205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007109836,0.00001031013,0.000071691844,0.00002456371,0.0000128049805,0.000016178863,0.000010561314,0.9911646,0.0002806643,0.0019587213,0.000092406866,0.006350352],"study_design_scores_gemma":[0.000004085102,0.000010982071,0.00002364139,0.0000037205384,0.00000374387,0.000004069649,0.0000040999726,0.9987336,0.00011403816,0.00096281985,0.00013340768,0.0000018804474],"about_ca_topic_score_codex":0.0056385146,"about_ca_topic_score_gemma":0.0042481134,"teacher_disagreement_score":0.0056385146,"about_ca_system_score_codex":0.00094448455,"about_ca_system_score_gemma":0.0011036068,"threshold_uncertainty_score":0.011211395},"labels":[],"label_agreement":null},{"id":"W2118247032","doi":"10.4028/www.scientific.net/kem.257-258.495","title":"Determination of an Optimum Geometrical Arrangement of Workpiece in the Ultrasonic Elliptic-Vibration Shoe Centerless Grinding","year":2004,"lang":"en","type":"article","venue":"Key engineering materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Microsemi (Canada)","funders":"","keywords":"Grinding; Materials science; Vibration; Mechanical engineering; Ultrasonic sensor; Acoustics; Composite material; Engineering; Physics","score_opus":0.008120514832858592,"score_gpt":0.22063533515665337,"score_spread":0.2125148203237948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118247032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8383334,0.00042876284,0.15930219,0.000038269336,0.000016821343,0.000083705265,0.000052085972,0.00020020096,0.0015446036],"genre_scores_gemma":[0.8924731,0.00012320766,0.10697018,0.000007548312,0.0000026532114,0.000025516381,0.0000456977,0.00002650886,0.00032553836],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994271,0.00010799911,0.000037224952,0.00013282837,0.00023923203,0.000055751927],"domain_scores_gemma":[0.9991036,0.00030552596,0.0002602836,0.00014543663,0.00013753679,0.000047648355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006501067,0.0004953057,0.00051174377,0.0002801394,0.00029210965,0.00030460022,0.0006138763,0.00033930084,0.0008423778],"category_scores_gemma":[0.002127781,0.0005439133,0.00020754266,0.00027311067,0.00047110967,0.00041511963,0.00041191955,0.0002337379,0.00023823054],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051409507,0.000060628365,0.0035245295,0.00049237965,0.0000219719,0.00015366248,0.00020545669,0.08090811,0.8694028,0.0008112651,0.00013127575,0.04377381],"study_design_scores_gemma":[0.00017502405,0.0018883361,0.0216651,0.00003953603,0.000106460895,0.0005084446,0.0002544029,0.1546882,0.8158633,0.00067198207,0.004014119,0.00012502799],"about_ca_topic_score_codex":0.0005472422,"about_ca_topic_score_gemma":0.0017815076,"teacher_disagreement_score":0.0008423778,"about_ca_system_score_codex":0.00029896206,"about_ca_system_score_gemma":0.00057179295,"threshold_uncertainty_score":0.0034381151},"labels":[],"label_agreement":null},{"id":"W2120964534","doi":"10.1109/nafips.2001.943709","title":"A technique for fuzzy logic modeling of machining process","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Machinability; Machining; Flute; Face (sociological concept); Process (computing); Fuzzy logic; Quality (philosophy); Mechanical engineering; Computer science; Engineering drawing; Surface roughness; Head (geology); Materials science; Engineering; Acoustics; Artificial intelligence; Composite material; Geology; Physics","score_opus":0.025511490814499833,"score_gpt":0.2614867879610223,"score_spread":0.2359752971465225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120964534","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006468692,0.000111046014,0.9967269,0.00004365278,0.000029715797,0.000026937745,0.000041795196,0.00020303324,0.0021701318],"genre_scores_gemma":[0.12091355,0.00068922207,0.87056416,0.00008746049,0.000091187176,0.00042151578,0.0002710135,0.00010715373,0.0068548215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996655,0.0000783249,0.00002607728,0.00006801228,0.00013708574,0.000025044481],"domain_scores_gemma":[0.99973553,0.0001244758,0.000027065635,0.000029650162,0.00007474572,0.000008504868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007284238,0.0009880546,0.00077267113,0.00064636406,0.0007082995,0.001031002,0.0013994409,0.0012389873,0.004748538],"category_scores_gemma":[0.0010178204,0.00044140566,0.0015623904,0.0006857851,0.00044586507,0.0009871362,0.00047519297,0.0017610404,0.0013066754],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008389008,0.00006742301,0.00036386214,0.0004090151,0.00010843126,0.0004066995,0.00034397587,0.6262189,0.017302023,0.22452332,0.004135396,0.12603709],"study_design_scores_gemma":[0.00001657029,0.000042356878,0.00007223297,0.000030509445,0.000032600827,0.000100187564,0.000016964488,0.95158595,0.0024203279,0.029836262,0.015831513,0.000014506235],"about_ca_topic_score_codex":0.005107971,"about_ca_topic_score_gemma":0.0038408486,"teacher_disagreement_score":0.005107971,"about_ca_system_score_codex":0.0006420038,"about_ca_system_score_gemma":0.00062582607,"threshold_uncertainty_score":0.015885472},"labels":[],"label_agreement":null},{"id":"W2121828446","doi":"10.1115/1.2137749","title":"Identification of Spindle Integrated Force Sensor’s Transfer Function for Modular End Mills","year":2005,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Transfer function; End mill; Modular design; Control theory (sociology); Mill; Coupling (piping); Bandwidth (computing); Calibration; Engineering; Mechanical engineering; Acoustics; Structural engineering; Computer science; Physics; Machining; Electrical engineering; Artificial intelligence","score_opus":0.005529333818081602,"score_gpt":0.20581883062601852,"score_spread":0.20028949680793692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121828446","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11404371,0.0001350399,0.88431543,0.000052879153,0.000010408819,0.000038555063,0.000035462945,0.0004941335,0.0008744258],"genre_scores_gemma":[0.94772136,0.00008078236,0.051250894,0.000014714648,0.0000076573515,0.000038640625,0.000049362952,0.000024494155,0.0008120777],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997259,0.00006347193,0.000009195103,0.0000641717,0.00011724685,0.000020069707],"domain_scores_gemma":[0.9995136,0.00023682602,0.000079089135,0.000058702575,0.00010006255,0.000011588229],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046470072,0.0006953567,0.0003971866,0.00023939864,0.00020536728,0.00043180684,0.00068493106,0.0008909459,0.0009879594],"category_scores_gemma":[0.0012682441,0.00029541136,0.00027184887,0.00014970545,0.0002568668,0.0005066661,0.00027106726,0.0004842761,0.00035629355],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006008471,0.00021072717,0.00502773,0.00039004278,0.00009218543,0.0005632837,0.00036460668,0.30189073,0.500563,0.0054296018,0.00070874166,0.18415855],"study_design_scores_gemma":[0.000025833086,0.00022445107,0.003040516,0.000014435682,0.0000138536025,0.00022510982,0.000022152079,0.9471908,0.04762212,0.000866876,0.00073619833,0.000017586619],"about_ca_topic_score_codex":0.00075751235,"about_ca_topic_score_gemma":0.0007602858,"teacher_disagreement_score":0.0009879594,"about_ca_system_score_codex":0.000314221,"about_ca_system_score_gemma":0.0003089663,"threshold_uncertainty_score":0.003305018},"labels":[],"label_agreement":null},{"id":"W2122748611","doi":"10.1109/icma.2005.1626842","title":"Electro-thermo-dynamic performance of a microgripping system","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; National Research Council Canada","funders":"","keywords":"Computer science","score_opus":0.0014308763451939446,"score_gpt":0.16456590748541267,"score_spread":0.1631350311402187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122748611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97975487,0.000367878,0.016734084,0.00006229041,0.000023074574,0.000023525483,0.000060478367,0.00029709787,0.0026767831],"genre_scores_gemma":[0.99557424,0.000071410555,0.0028501255,0.000020309795,0.0000047475664,0.000010353896,0.000029549536,0.000011747583,0.0014275459],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998179,0.000014298355,0.000009658582,0.000044780118,0.00008411652,0.000029228846],"domain_scores_gemma":[0.999752,0.000076583914,0.000044480006,0.000033663084,0.00006646179,0.000026862775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013384943,0.00018894674,0.0001924839,0.0001477973,0.00015766536,0.000280722,0.00028458005,0.00030939077,0.0014082232],"category_scores_gemma":[0.0005088375,0.0001255715,0.00011645647,0.000088664725,0.0001735564,0.00029005963,0.00018878072,0.00013539988,0.0004047193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085932385,0.00001292735,0.00041743377,0.00004199525,0.0000064720234,0.00007259284,0.000040948045,0.0016008754,0.9888996,0.000086042026,0.00007355551,0.008661686],"study_design_scores_gemma":[0.000019365978,0.0009632494,0.010505689,0.000010834473,0.000025568748,0.00044404416,0.000047347592,0.025743049,0.9595285,0.00004586706,0.002643131,0.000023261546],"about_ca_topic_score_codex":0.0003553778,"about_ca_topic_score_gemma":0.00031624327,"teacher_disagreement_score":0.0014082232,"about_ca_system_score_codex":0.00022631718,"about_ca_system_score_gemma":0.00012433036,"threshold_uncertainty_score":0.0047109723},"labels":[],"label_agreement":null},{"id":"W2122994162","doi":"10.1109/acc.1995.529236","title":"Open-architecture controller for die and mold machining","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Mold; Die (integrated circuit); Architecture; Software; Schedule; Numerical control; Manufacturing engineering; Computer science; Electrical discharge machining; Engineering; Controller (irrigation); Engineering drawing; Mechanical engineering; Operating system; Materials science","score_opus":0.008283714422137534,"score_gpt":0.2506706414986952,"score_spread":0.24238692707655768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122994162","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0633525,0.0009563699,0.7164849,0.0002492537,0.0006280167,0.0006169594,0.0011296106,0.1030435,0.11353899],"genre_scores_gemma":[0.73363554,0.00032383314,0.15811878,0.00035632416,0.00021145966,0.0005372459,0.0023878927,0.0017089994,0.10271996],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994598,0.000027754413,0.000021596452,0.0001210776,0.00030415083,0.00006562898],"domain_scores_gemma":[0.99959475,0.000052665888,0.000025492613,0.00010105946,0.00018355907,0.00004258819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002841303,0.0006040251,0.0003522043,0.0005670816,0.00046544438,0.0009832367,0.0014687687,0.00048261412,0.021985175],"category_scores_gemma":[0.00073606404,0.00020193911,0.00017758776,0.0003345668,0.00032713456,0.0006736045,0.00072714523,0.00092976535,0.005333849],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010368855,0.0003714868,0.0022312114,0.00032661174,0.00006493062,0.00035941377,0.00054001913,0.018632991,0.21005508,0.03574023,0.07561092,0.6550302],"study_design_scores_gemma":[0.00032546747,0.0005433373,0.004413227,0.00007696394,0.00006172848,0.0005993778,0.000095617164,0.38713712,0.2349355,0.014646288,0.35701698,0.00014835187],"about_ca_topic_score_codex":0.003300196,"about_ca_topic_score_gemma":0.00556979,"teacher_disagreement_score":0.021985175,"about_ca_system_score_codex":0.0006752718,"about_ca_system_score_gemma":0.00079870486,"threshold_uncertainty_score":0.07354772},"labels":[],"label_agreement":null},{"id":"W2123687894","doi":"10.5267/j.dsl.2015.3.001","title":"Surface roughness prediction of particulate composites using artificial neural networks in turning operation","year":2015,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Surface roughness; Particulates; Materials science; Composite material; Surface finish; Surface (topology); Mechanical engineering; Process engineering; Artificial intelligence; Computer science; Engineering; Mathematics; Geometry","score_opus":0.03802366358877306,"score_gpt":0.28991492019227394,"score_spread":0.25189125660350087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123687894","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9442909,0.00017540429,0.054178614,0.000045910325,0.000019487321,0.000015876762,0.00004459909,0.00013433292,0.00109493],"genre_scores_gemma":[0.99678123,0.00003505547,0.0029080666,0.0000037895811,0.0000017674861,0.0000057753305,0.000030094167,0.0000022958047,0.00023182463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990463,0.000021998108,0.000007091314,0.000020356394,0.000028628132,0.000017322061],"domain_scores_gemma":[0.9997292,0.00013536126,0.00003191906,0.000015617303,0.00007791454,0.000009905948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031195278,0.0003770018,0.00028588975,0.00035378465,0.00013423685,0.00029347412,0.00019789868,0.00037732933,0.00027971878],"category_scores_gemma":[0.0007363538,0.0001860254,0.00029944873,0.0001978651,0.00013475792,0.00022030367,0.00011911736,0.00026237036,0.00006775332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023947585,0.00010485638,0.0069739055,0.000043717566,0.000030255138,0.00006701956,0.000027162436,0.9396883,0.011639504,0.00010951798,0.00014601123,0.04093024],"study_design_scores_gemma":[0.0000015468544,0.000030779996,0.0017931047,0.0000014985837,0.0000037158065,0.0000035319185,0.000005293388,0.99653816,0.001563639,0.00003545612,0.000020737027,0.0000024856834],"about_ca_topic_score_codex":0.007659577,"about_ca_topic_score_gemma":0.0067717107,"teacher_disagreement_score":0.007659577,"about_ca_system_score_codex":0.00030586115,"about_ca_system_score_gemma":0.00019954944,"threshold_uncertainty_score":0.01523},"labels":[],"label_agreement":null},{"id":"W2123726757","doi":"10.1115/imece2014-39370","title":"Effect of Tool Kinematics on the Drilling Forces and Temperature in Low Frequency High Amplitude Vibration Assisted Drilling","year":2014,"lang":"en","type":"article","venue":"Volume 2A: Advanced Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Drilling; Amplitude; Vibration; Materials science; Delamination (geology); Kinematics; Thermal; Fibre-reinforced plastic; Chip; Propeller; Acoustics; Mechanical engineering; Composite material; Geology; Engineering; Marine engineering; Optics; Physics; Metallurgy; Electrical engineering","score_opus":0.0028941338496527107,"score_gpt":0.1988132511798607,"score_spread":0.195919117330208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123726757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968641,0.00018207393,0.0027419995,0.000008216476,0.000006952137,0.000013193894,0.000012150323,0.00001996776,0.00015143077],"genre_scores_gemma":[0.99800354,0.00008462678,0.0017665831,0.000004328469,0.0000012761296,0.0000077543955,0.000008901428,0.000004356959,0.000118461816],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993868,0.00012572156,0.00005984822,0.00010120275,0.00023094051,0.00009561393],"domain_scores_gemma":[0.9970258,0.0017073225,0.00066625734,0.00015121214,0.00037383454,0.000075620315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073439715,0.00040620388,0.00035544403,0.00032404822,0.00020431864,0.0004964969,0.00033642192,0.0004444261,0.0006339342],"category_scores_gemma":[0.0025129346,0.00037045,0.00023276338,0.00023787057,0.0005914143,0.00047162126,0.0003031612,0.0002859181,0.00014417901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010772788,0.00015650636,0.0030555062,0.00022848047,0.000013359374,0.00012726462,0.0002268536,0.004979994,0.97817856,0.00008308361,0.000022477576,0.011850722],"study_design_scores_gemma":[0.00004806121,0.004112193,0.024329135,0.000021347176,0.000040871102,0.00013576346,0.00020861195,0.011201347,0.9593932,0.000056293356,0.00041382367,0.000039415336],"about_ca_topic_score_codex":0.00031367625,"about_ca_topic_score_gemma":0.0005490805,"teacher_disagreement_score":0.00073439715,"about_ca_system_score_codex":0.00017058349,"about_ca_system_score_gemma":0.00018894566,"threshold_uncertainty_score":0.0038839579},"labels":[],"label_agreement":null},{"id":"W2124157143","doi":"10.3390/s120708732","title":"Method for Vibration Response Simulation and Sensor Placement Optimization of a Machine Tool Spindle System with a Bearing Defect","year":2012,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Specialized Research Fund for the Doctoral Program of Higher Education of China; University of British Columbia; National Natural Science Foundation of China","keywords":"Bearing (navigation); Vibration; Structural engineering; Finite element method; Noise (video); Engineering; Nonlinear system; Newmark-beta method; Timoshenko beam theory; Acoustics; Control theory (sociology); Computer science; Physics","score_opus":0.011585658308007427,"score_gpt":0.268087944315238,"score_spread":0.2565022860072306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124157143","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018843327,0.00005305215,0.9783718,0.000031726897,0.000013751476,0.000036732803,0.000033156884,0.00034225796,0.002274269],"genre_scores_gemma":[0.68076503,0.00012362802,0.31347638,0.000034560046,0.000009566877,0.00033450377,0.00010612229,0.00010774722,0.0050424626],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999089,0.000019268038,0.0000035380162,0.000013144837,0.000045192555,0.0000099327235],"domain_scores_gemma":[0.99985516,0.000079217854,0.00001577956,0.0000088870065,0.000035825014,0.000005069239],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026543066,0.00040776783,0.00035435628,0.00023699336,0.00020251815,0.00020670846,0.00049793534,0.0006512049,0.0030427116],"category_scores_gemma":[0.0004405571,0.00025863494,0.00040707184,0.00014487289,0.0001952131,0.00025395656,0.00022942072,0.00036173954,0.000298349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003370186,0.000029912628,0.0003300476,0.00005543212,0.00001546885,0.00005734727,0.000047326506,0.96892357,0.013873576,0.0026902582,0.00025132584,0.013692062],"study_design_scores_gemma":[0.0000032138255,0.000009954131,0.000036460737,0.0000010178214,0.0000011533803,0.0000057739894,0.0000025783852,0.9988619,0.0007702219,0.000116783325,0.00018964829,0.000001267856],"about_ca_topic_score_codex":0.0031746589,"about_ca_topic_score_gemma":0.0027755045,"teacher_disagreement_score":0.0031746589,"about_ca_system_score_codex":0.0002767446,"about_ca_system_score_gemma":0.0005693281,"threshold_uncertainty_score":0.010178864},"labels":[],"label_agreement":null},{"id":"W2124536805","doi":"10.1109/tro.2015.2489502","title":"Spline Path Following for Redundant Mechanical Systems","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spline (mechanical); Mechanical system; Computer science; Path (computing); Algorithm; Mathematics; Control engineering; Mathematical optimization; Engineering; Artificial intelligence; Mechanical engineering","score_opus":0.029376387630417354,"score_gpt":0.26052552830836995,"score_spread":0.23114914067795259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124536805","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01139345,0.00022105838,0.98616356,0.000034655313,0.00001556651,0.000021676276,0.00001519049,0.00018080411,0.0019540014],"genre_scores_gemma":[0.7909157,0.0005225865,0.20251113,0.000040133975,0.000031071097,0.00017459576,0.000098721895,0.00006002319,0.005645919],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99982846,0.000043487067,0.000007791999,0.000027769789,0.000079802936,0.000012632042],"domain_scores_gemma":[0.9998022,0.000079927195,0.000039280454,0.000021309395,0.000047571255,0.000009669248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003126334,0.00031615465,0.00022749645,0.000247284,0.00017814284,0.0002553967,0.0002847394,0.00035959794,0.0018501637],"category_scores_gemma":[0.00069846865,0.00015110502,0.0002639893,0.00023936304,0.0003920786,0.0002279218,0.00032581892,0.00039330308,0.00029426417],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062910374,0.000032786593,0.00026190266,0.0001951883,0.0000134114425,0.000085534855,0.00016007836,0.81164175,0.027417254,0.05718997,0.00087754696,0.10206161],"study_design_scores_gemma":[0.0000116955725,0.000084717765,0.00008742458,0.000010080627,0.0000029086357,0.000024617435,0.0000080687405,0.98534113,0.00224215,0.009809071,0.0023713112,0.000006834568],"about_ca_topic_score_codex":0.0011582099,"about_ca_topic_score_gemma":0.0009810611,"teacher_disagreement_score":0.0018501637,"about_ca_system_score_codex":0.00030164933,"about_ca_system_score_gemma":0.0004561835,"threshold_uncertainty_score":0.006189406},"labels":[],"label_agreement":null},{"id":"W2124605097","doi":"10.4028/www.scientific.net/amr.314-316.263","title":"Investigation into Tribological Properties of TD-Treated D2 Steel for Applications in Dry Machining of Aluminum Alloy","year":2011,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Metallurgy; Coating; Machining; Tin; Aluminium; Tribology; Alloy; Adhesive; Hardened steel; Carbide; Composite material; Layer (electronics)","score_opus":0.09726772411271074,"score_gpt":0.3248313778797144,"score_spread":0.22756365376700366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124605097","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961861,0.0008210727,0.0019260602,0.000023278171,0.000015431664,0.000015618318,0.00012849516,0.000022998725,0.0008610293],"genre_scores_gemma":[0.99647385,0.000210355,0.0016681047,0.000020754263,0.0000056071344,0.000009469284,0.00021989772,0.000017339251,0.0013746433],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998136,0.000023238941,0.000012286328,0.000032050448,0.000085538384,0.000033208977],"domain_scores_gemma":[0.9997781,0.000028854738,0.00004321879,0.000020006659,0.000104492225,0.000025268557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018013481,0.0003325377,0.00026394275,0.00037388684,0.00023054825,0.0003000148,0.00023885828,0.00040037476,0.0014217739],"category_scores_gemma":[0.00025298676,0.00015080621,0.00024972798,0.00025741477,0.00015493494,0.0001768038,0.00011412249,0.00023405145,0.0002719344],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061626684,0.0000073856686,0.00045417986,0.00004050899,0.0000042112183,0.000032119355,0.000013317642,0.000057511723,0.9984586,0.00000778171,0.000014570183,0.00084818754],"study_design_scores_gemma":[0.0000075298067,0.00034194865,0.008515981,0.0000027101746,0.000013806193,0.000113085334,0.00004883102,0.0004407781,0.98928916,0.000008135329,0.0012115821,0.0000064918236],"about_ca_topic_score_codex":0.0010607474,"about_ca_topic_score_gemma":0.0025345953,"teacher_disagreement_score":0.0014217739,"about_ca_system_score_codex":0.00022301583,"about_ca_system_score_gemma":0.00015827766,"threshold_uncertainty_score":0.0047563314},"labels":[],"label_agreement":null},{"id":"W2125000245","doi":"10.1109/nafips.2009.5156421","title":"Application of Type-2 fuzzy estimation on uncertainty in machining: An approach on acoustic emission during turning process","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Machining; Fuzzy logic; Acoustic emission; Process (computing); Reliability (semiconductor); Filter (signal processing); Computer science; Reliability engineering; Quality (philosophy); Engineering; Manufacturing engineering; Automotive engineering; Mechanical engineering; Artificial intelligence; Acoustics","score_opus":0.008085768955707666,"score_gpt":0.2653627405052516,"score_spread":0.25727697154954393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125000245","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029221712,0.00029626553,0.9693875,0.000094193,0.000036461322,0.000019297247,0.000013688927,0.000030076191,0.0009009353],"genre_scores_gemma":[0.8612179,0.00051799417,0.136511,0.000066098204,0.000071629955,0.0000528278,0.000036746653,0.000017070539,0.0015086379],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996309,0.00011420312,0.000023050012,0.0000699203,0.00013070309,0.000031169184],"domain_scores_gemma":[0.9992366,0.0004884425,0.00005331614,0.000022108168,0.00018151524,0.000017919967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007978574,0.00053857645,0.00057999743,0.00043045715,0.00035155253,0.0006402401,0.00056349137,0.0008416654,0.0004466695],"category_scores_gemma":[0.0018315145,0.00024164829,0.00069487013,0.00028595192,0.00039195415,0.0006005896,0.00026738184,0.0005314309,0.00006401091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034621084,0.00009022754,0.002347125,0.00031305716,0.00015782387,0.0006424018,0.00043887572,0.80632097,0.028333254,0.012659937,0.00067837985,0.1476718],"study_design_scores_gemma":[0.0000073346,0.00005980018,0.0005418282,0.000011312892,0.00001917324,0.000052357493,0.000028996734,0.99232846,0.003098698,0.0034999964,0.00033209415,0.000019895875],"about_ca_topic_score_codex":0.003660149,"about_ca_topic_score_gemma":0.0023795418,"teacher_disagreement_score":0.003660149,"about_ca_system_score_codex":0.00043690647,"about_ca_system_score_gemma":0.00037247484,"threshold_uncertainty_score":0.0072776675},"labels":[],"label_agreement":null},{"id":"W2125226428","doi":"10.1007/s00170-015-7336-3","title":"Dynamic characterization of machining robot and stability analysis","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":171,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"European Regional Development Fund; Beijing International Studies University; Agence Nationale de la Recherche","keywords":"Machining; Workspace; Robot; Modal analysis; Machine tool; Vibration; Rigidity (electromagnetism); Engineering; Modal; Mechanical engineering; Stability (learning theory); Flexibility (engineering); Control engineering; Computer science; Artificial intelligence; Structural engineering; Materials science; Finite element method; Acoustics; Mathematics","score_opus":0.008079382080213327,"score_gpt":0.24128090869331326,"score_spread":0.23320152661309992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125226428","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7051845,0.0005004206,0.27129027,0.00015774718,0.000035582034,0.00024916625,0.0007121899,0.0010716196,0.020798454],"genre_scores_gemma":[0.9819165,0.000068096284,0.0131024225,0.000012616805,0.0000050286408,0.00007478159,0.0003203836,0.00004239084,0.004457709],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997453,0.000016635093,0.0000090936155,0.000049385268,0.00014942842,0.000030160953],"domain_scores_gemma":[0.99967635,0.000075075484,0.000036425477,0.000041406645,0.00015711851,0.0000135932405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020579007,0.00033696726,0.0003195967,0.00079056894,0.0004977183,0.0003357281,0.0005422175,0.0004167866,0.004657784],"category_scores_gemma":[0.0005608797,0.00022585972,0.00022440481,0.0004178195,0.00028637258,0.00043916132,0.00023414475,0.00021211963,0.000763041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053639116,0.000097972836,0.0037119472,0.00020531846,0.000021676988,0.00022169415,0.00023738695,0.04202562,0.879315,0.0026756967,0.0007860924,0.07016514],"study_design_scores_gemma":[0.000046328285,0.0008274709,0.052033752,0.000028607023,0.00003596696,0.0006233359,0.00025793482,0.40477625,0.52953905,0.0014631007,0.010305791,0.00006237952],"about_ca_topic_score_codex":0.0014935525,"about_ca_topic_score_gemma":0.0012263189,"teacher_disagreement_score":0.004657784,"about_ca_system_score_codex":0.0003312799,"about_ca_system_score_gemma":0.00036446686,"threshold_uncertainty_score":0.015581787},"labels":[],"label_agreement":null},{"id":"W2125277364","doi":"10.1016/j.ijmachtools.2006.10.005","title":"Generalized modeling of drilling vibrations. Part I: Time domain model of drilling kinematics, dynamics and hole formation","year":2006,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":91,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Machine Tool Technologies Research Foundation; Pratt and Whitney Canada","keywords":"Vibration; Kinematics; Torsional vibration; Drilling; Deep hole drilling; Thrust; Mechanism (biology); Drill; Engineering; Time domain; Structural engineering; Frequency domain; Mechanics; Mechanical engineering; Acoustics; Physics; Classical mechanics; Computer science","score_opus":0.007568155755001757,"score_gpt":0.2161625231253997,"score_spread":0.20859436737039797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125277364","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02530108,0.00060363405,0.96812093,0.00014343773,0.00012875209,0.000026634596,0.00021409614,0.00029804042,0.005163404],"genre_scores_gemma":[0.9291386,0.001100496,0.055413354,0.00008960149,0.00008036224,0.00015018511,0.00040570617,0.00007551494,0.013546238],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991727,0.0000230183,0.0000040303,0.000016871509,0.000027971637,0.000010750439],"domain_scores_gemma":[0.999928,0.000019339133,0.000014172176,0.000016022068,0.00001646218,0.0000059928357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014197813,0.00053562503,0.000516056,0.00016771942,0.00012408117,0.00035167372,0.00083200174,0.00074863737,0.001871326],"category_scores_gemma":[0.00036690597,0.00020713994,0.0004601096,0.00025273868,0.00039669714,0.0005865032,0.0004204223,0.00046044128,0.0004888952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032891043,0.000014080499,0.00021011228,0.00007242488,0.00001813394,0.00007924085,0.000040704825,0.958288,0.011107432,0.01590103,0.00074192684,0.013494083],"study_design_scores_gemma":[0.0000045945553,0.000020303358,0.00013594024,0.0000034502525,0.000004358301,0.00001940866,0.0000063052894,0.9939241,0.00041344538,0.0044182567,0.0010463878,0.0000034050058],"about_ca_topic_score_codex":0.0016751392,"about_ca_topic_score_gemma":0.0016294499,"teacher_disagreement_score":0.001871326,"about_ca_system_score_codex":0.00016719107,"about_ca_system_score_gemma":0.00032296043,"threshold_uncertainty_score":0.0062601566},"labels":[],"label_agreement":null},{"id":"W2125551950","doi":"10.1504/ijmr.2007.015084","title":"A geometric method for three-dimensional modelling of surface finish in grinding","year":2007,"lang":"en","type":"article","venue":"International Journal of Manufacturing Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Grinding; Ellipsoid; Surface roughness; Surface (topology); Consistency (knowledge bases); Surface finish; Chip; Kinematics; Materials science; Geometric modeling; Engineering drawing; Mechanical engineering; Geometry; Computer science; Mathematics; Engineering; Geology; Composite material; Physics; Classical mechanics","score_opus":0.078377223815085,"score_gpt":0.3893793483116415,"score_spread":0.3110021244965565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125551950","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006851491,0.00005184399,0.99857426,0.000013623523,0.000013268497,0.000011565177,0.000024259078,0.00016649687,0.00045944419],"genre_scores_gemma":[0.1126538,0.0004727729,0.88337874,0.000039362792,0.000038222195,0.00023784894,0.00026865976,0.00034282764,0.0025678477],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996244,0.000070522685,0.000021365508,0.000059371672,0.0002058556,0.000018525217],"domain_scores_gemma":[0.9996419,0.00016244799,0.00004397528,0.00006888616,0.00007229426,0.000010434988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062260334,0.00084354775,0.00065263925,0.00076303916,0.0003470469,0.0007409408,0.0014707015,0.0008763144,0.0028134382],"category_scores_gemma":[0.0012155835,0.0005659196,0.001289211,0.00066115725,0.0007774971,0.0008722129,0.0004956519,0.0009651152,0.0010857919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021763903,0.000018430103,0.00033231676,0.00015279523,0.000027560864,0.00009869511,0.000082672545,0.8711983,0.011524326,0.058819007,0.0009956947,0.05672848],"study_design_scores_gemma":[0.0000043962987,0.000022163113,0.00009123232,0.0000066237826,0.0000059072077,0.000054531833,0.0000054630445,0.9845968,0.0017800997,0.0065578707,0.0068631056,0.000011912091],"about_ca_topic_score_codex":0.002682909,"about_ca_topic_score_gemma":0.002542118,"teacher_disagreement_score":0.0028134382,"about_ca_system_score_codex":0.00061053096,"about_ca_system_score_gemma":0.0006508367,"threshold_uncertainty_score":0.009411871},"labels":[],"label_agreement":null},{"id":"W2126157554","doi":"10.4028/www.scientific.net/amr.223.900","title":"Simulation of Serrated End Milling Using Solid Modeling Techniques","year":2011,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Waviness; End mill; End milling; Enhanced Data Rates for GSM Evolution; Mechanical engineering; Vibration; Mill; Materials science; Engineering; Structural engineering; Engineering drawing; Machining; Acoustics","score_opus":0.14157763975240548,"score_gpt":0.3985376373965102,"score_spread":0.2569599976441047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126157554","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26288643,0.00020496691,0.71722925,0.00016416285,0.00008686256,0.00017261738,0.0004449953,0.0014765094,0.017334146],"genre_scores_gemma":[0.86200297,0.00022570556,0.13224167,0.000026181613,0.000010203423,0.00021691695,0.0003497096,0.000110611916,0.0048160087],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975723,0.00004509697,0.000015838741,0.000026996,0.00012446284,0.000030420288],"domain_scores_gemma":[0.99938285,0.0002879695,0.00008114128,0.00006973237,0.00014363852,0.000034646408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003529103,0.0006023802,0.0006238121,0.0004628173,0.00038359498,0.0008471213,0.0010876729,0.0012371966,0.002786649],"category_scores_gemma":[0.00079718826,0.00037061618,0.00061861466,0.00039301452,0.00044820408,0.00056654756,0.00042514858,0.00049408065,0.00039836988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031682408,0.000020228606,0.00031542263,0.00003363311,0.000006028579,0.00007057266,0.000052126772,0.9899872,0.004202835,0.0019963004,0.00012639372,0.0031575898],"study_design_scores_gemma":[0.00000411222,0.000011976666,0.000046253695,0.0000019636748,0.0000012968469,0.000007345478,0.0000056687018,0.99833614,0.0011196556,0.00017943313,0.00028338743,0.000002774412],"about_ca_topic_score_codex":0.003217504,"about_ca_topic_score_gemma":0.0023454954,"teacher_disagreement_score":0.003217504,"about_ca_system_score_codex":0.00042377648,"about_ca_system_score_gemma":0.0007557174,"threshold_uncertainty_score":0.009322226},"labels":[],"label_agreement":null},{"id":"W2127427832","doi":"10.1177/2041297510394057","title":"Porosity and cutting forces: from macroscale to microscale machining correlations","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Microscale chemistry; Machinability; Machining; Surface micromachining; Porosity; Materials science; Context (archaeology); Mechanical engineering; Metallurgy; Composite material; Fabrication; Engineering; Geology","score_opus":0.008946826563844035,"score_gpt":0.19166857894420083,"score_spread":0.1827217523803568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127427832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9171531,0.009576482,0.06587977,0.00024986974,0.000034159384,0.000026382786,0.00010537978,0.00018666005,0.006788188],"genre_scores_gemma":[0.9964579,0.0007207853,0.0025557799,0.000009403627,0.000010974166,0.0000042408474,0.000019792287,0.000008318727,0.00021289513],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999694,0.00002627975,0.000009066971,0.00008050165,0.00014231079,0.00004784855],"domain_scores_gemma":[0.9982615,0.0010738514,0.00041645742,0.00009797115,0.00010650969,0.000043686276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002834212,0.00016482324,0.00024173126,0.00055143674,0.000116169766,0.0005582942,0.00027016626,0.00043303028,0.0008704193],"category_scores_gemma":[0.0025553787,0.00027617105,0.00012552888,0.00037122352,0.00087788596,0.0007259121,0.00042169366,0.00046271714,0.00012433865],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005476425,0.00029055105,0.12607475,0.0013552338,0.00033604167,0.0014474476,0.00078282645,0.15318911,0.41771144,0.078109816,0.0014572755,0.21869785],"study_design_scores_gemma":[0.00006607739,0.0006659281,0.4870226,0.00016043558,0.0001677054,0.0019430203,0.00044734403,0.25734988,0.18408343,0.060091857,0.0077769705,0.00022471132],"about_ca_topic_score_codex":0.00040058073,"about_ca_topic_score_gemma":0.0005353311,"teacher_disagreement_score":0.0008704193,"about_ca_system_score_codex":0.00025546708,"about_ca_system_score_gemma":0.00019831426,"threshold_uncertainty_score":0.002911806},"labels":[],"label_agreement":null},{"id":"W2129021368","doi":"10.1007/s11071-013-0752-8","title":"Nonlinear vibrations of a shell-shaped workpiece during high-speed milling process","year":2013,"lang":"en","type":"article","venue":"Nonlinear Dynamics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Galerkin method; Nonlinear system; Shell (structure); Vibration; Parametric statistics; Parametric oscillator; Mechanics; Equations of motion; Displacement (psychology); Cantilever; Multiple-scale analysis; Hamilton's principle; Resonance (particle physics); Classical mechanics; Physics; Mathematics; Structural engineering; Engineering; Mechanical engineering; Acoustics","score_opus":0.004662625605562527,"score_gpt":0.21522152306390552,"score_spread":0.210558897458343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129021368","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944899,0.000023039584,0.0044224844,0.000041381292,0.000006172004,0.0000045691104,0.000010810934,0.000022208611,0.000979539],"genre_scores_gemma":[0.9992756,0.000005510316,0.0003536634,0.0000025372763,0.0000012563244,0.000001248294,0.000006348665,0.0000046476002,0.00034919177],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991727,0.000015513146,0.0000023897414,0.000017669625,0.000027889993,0.00001929788],"domain_scores_gemma":[0.9997727,0.000117761665,0.000030119927,0.000018760462,0.000027887452,0.000032699954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022870219,0.00019760436,0.00027398093,0.0001539468,0.00046833904,0.00025468325,0.0003117753,0.0005279862,0.0011596483],"category_scores_gemma":[0.00050161825,0.00013879327,0.0002281838,0.00013672218,0.00067716197,0.00032577856,0.00028529373,0.00029243983,0.00007953372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022481587,0.0002911905,0.015978355,0.00021487451,0.000077480996,0.003526278,0.0025524998,0.22799763,0.72022706,0.0022973965,0.00086287555,0.023726206],"study_design_scores_gemma":[0.000064208914,0.00051011326,0.050929554,0.00001594249,0.000028313512,0.00039608986,0.00061149144,0.88859904,0.05754352,0.0006966074,0.0005480843,0.000057031684],"about_ca_topic_score_codex":0.0012357938,"about_ca_topic_score_gemma":0.0012958347,"teacher_disagreement_score":0.0012357938,"about_ca_system_score_codex":0.00019755744,"about_ca_system_score_gemma":0.00018514982,"threshold_uncertainty_score":0.0038793683},"labels":[],"label_agreement":null},{"id":"W2129782329","doi":"10.1177/0954406211423575","title":"Effect of circular tool path on cutting force profile in micro-end-milling","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Western University","funders":"","keywords":"RADIUS; Path (computing); Chip; Classification of discontinuities; Mechanical engineering; Geometry; End milling; Engineering; Machining; Computer science; Mathematics; Mathematical analysis; Telecommunications","score_opus":0.00851194879335841,"score_gpt":0.21568243141410032,"score_spread":0.20717048262074192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129782329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9762018,0.00050220493,0.02241953,0.000037426216,0.000013170039,0.000027793976,0.000027160359,0.00016975176,0.0006011291],"genre_scores_gemma":[0.99364215,0.00010376074,0.0060522966,0.0000099517965,0.0000014841042,0.0000060603647,0.00001823029,0.000013728856,0.0001522696],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995302,0.00006694725,0.00002375188,0.00010477442,0.00019797622,0.00007636639],"domain_scores_gemma":[0.9958768,0.002559654,0.000732095,0.0002854896,0.00045248255,0.00009344071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050519407,0.00038520226,0.0002989173,0.0002452647,0.00019641979,0.0004502613,0.0003267244,0.0005698818,0.000641135],"category_scores_gemma":[0.0032200466,0.0003077208,0.00016370835,0.00029995217,0.00051263964,0.00043015365,0.0002445089,0.00020419224,0.00011328556],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026706425,0.00022232199,0.005188826,0.00034699903,0.00003506826,0.0006445782,0.00032292458,0.046035778,0.8909269,0.00056270213,0.0002134287,0.05282977],"study_design_scores_gemma":[0.0001064838,0.0028882662,0.026997771,0.000043058724,0.00006243654,0.00064891885,0.0001783882,0.13097142,0.8362388,0.00034956273,0.0014273745,0.000087659704],"about_ca_topic_score_codex":0.00060953293,"about_ca_topic_score_gemma":0.000772737,"teacher_disagreement_score":0.000641135,"about_ca_system_score_codex":0.00025529324,"about_ca_system_score_gemma":0.0003124442,"threshold_uncertainty_score":0.0026717782},"labels":[],"label_agreement":null},{"id":"W2130630056","doi":"10.1007/s00170-010-2982-y","title":"Force prediction and stability analysis of plunge milling of systems with rigid and flexible workpiece","year":2010,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Machining; Rigidity (electromagnetism); Vibration; Machine tool; Thread (computing); Kinematics; Insert (composites); Engineering; Structural engineering; Mechanical engineering; Enhanced Data Rates for GSM Evolution; Cutting tool; Process (computing); Computer science; Acoustics","score_opus":0.004438336040334548,"score_gpt":0.21412480130228442,"score_spread":0.20968646526194987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130630056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88445044,0.0001116703,0.11332897,0.0001225829,0.000011827326,0.000027872484,0.000047682446,0.00020372048,0.0016952885],"genre_scores_gemma":[0.9974262,0.000012073039,0.002128944,0.000002591539,0.0000019155261,0.0000073036285,0.000015848145,0.000010379184,0.00039470225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987435,0.000027270515,0.0000050736653,0.000023833722,0.00004928521,0.000020131733],"domain_scores_gemma":[0.9985526,0.0010423881,0.00012068056,0.00006363186,0.00018515233,0.000035596706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047744025,0.00036054192,0.00037998377,0.0004201835,0.0005166895,0.00040550865,0.00037332572,0.0005921137,0.0010986441],"category_scores_gemma":[0.001581808,0.00029110102,0.00037380168,0.00020884845,0.0005920863,0.00040517384,0.0003090108,0.00045305872,0.00014975328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047983264,0.000068921625,0.0038477194,0.000057314915,0.000023657221,0.00013310202,0.00013351176,0.9378341,0.033378072,0.0010969571,0.0002441315,0.02270264],"study_design_scores_gemma":[0.000003100717,0.000023278211,0.00075958675,6.41059e-7,0.0000012767779,0.000004490616,0.0000044390863,0.99717724,0.0019381158,0.000068331676,0.00001749315,0.0000020855205],"about_ca_topic_score_codex":0.007675573,"about_ca_topic_score_gemma":0.0034619605,"teacher_disagreement_score":0.007675573,"about_ca_system_score_codex":0.00044296146,"about_ca_system_score_gemma":0.00042599303,"threshold_uncertainty_score":0.015261829},"labels":[],"label_agreement":null},{"id":"W2131455420","doi":"10.1115/1.1535190","title":"Drilling in Bone: Modeling Heat Generation and Temperature Distribution","year":2003,"lang":"en","type":"article","venue":"Journal of Biomechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":230,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drill; Drilling; Heat generation; Heat transfer; Thermal; Materials science; Machining; Finite element method; Mechanics; Parametric statistics; Mechanical engineering; Composite material; Structural engineering; Engineering; Metallurgy; Thermodynamics; Physics","score_opus":0.007052013946154886,"score_gpt":0.19971224042282743,"score_spread":0.19266022647667252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131455420","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2458836,0.0007310802,0.74432135,0.00022025072,0.000057262132,0.00009895085,0.00015398458,0.00031654804,0.008217032],"genre_scores_gemma":[0.95306027,0.00050436356,0.041416775,0.000031186533,0.00001756697,0.00012621745,0.0000633717,0.00006732438,0.004712949],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999143,0.000017774155,0.000004420761,0.000014464901,0.0000359486,0.000013104416],"domain_scores_gemma":[0.9998288,0.00009865879,0.000024837933,0.000010060778,0.000026628744,0.000011016375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021894716,0.00039230366,0.00037994556,0.00030945538,0.00026788964,0.00048167794,0.00070978334,0.0010023759,0.0009843525],"category_scores_gemma":[0.0007977864,0.00046699983,0.0005346179,0.00031638652,0.0004896837,0.0005574089,0.00039141328,0.0004311633,0.00020168531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002195809,0.000016550715,0.00052471197,0.000035895628,0.000006341837,0.00005840405,0.000051758027,0.98654896,0.006223397,0.0021411898,0.00007233208,0.004298485],"study_design_scores_gemma":[0.00000427975,0.000008215667,0.00011658085,0.0000021388826,0.0000027180151,0.000020065914,0.0000052064966,0.9986166,0.00059933786,0.00041883084,0.00020333458,0.000002759641],"about_ca_topic_score_codex":0.007967118,"about_ca_topic_score_gemma":0.0056483108,"teacher_disagreement_score":0.007967118,"about_ca_system_score_codex":0.00039723527,"about_ca_system_score_gemma":0.0006786456,"threshold_uncertainty_score":0.015841484},"labels":[],"label_agreement":null},{"id":"W2131571777","doi":"10.1177/0954405413491243","title":"Framework for evaluation of the relative contribution of the process on porosity–cutting force dependence in micromilling of titanium foams","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Porosity; Materials science; Machining; Surface micromachining; Titanium; Composite material; Process (computing); Mechanical engineering; Computer science; Metallurgy; Engineering; Fabrication","score_opus":0.010224772390943044,"score_gpt":0.24472757490632321,"score_spread":0.23450280251538017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131571777","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06010712,0.0011449802,0.93385977,0.00010525832,0.000021664848,0.00015140527,0.00015261314,0.00019099923,0.004266271],"genre_scores_gemma":[0.6928407,0.0020739052,0.30218774,0.000057918758,0.00005396882,0.00054275413,0.0002587596,0.00011155406,0.001872767],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995741,0.00009105842,0.000023722632,0.000090023495,0.0001666763,0.000054320913],"domain_scores_gemma":[0.9994493,0.00028248364,0.000097088196,0.000052764495,0.00009480262,0.000023533064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011068882,0.0007011921,0.00070363143,0.0012561238,0.00032736355,0.0009987872,0.00088857295,0.00059838983,0.0010155579],"category_scores_gemma":[0.0016583533,0.00025995384,0.0007175906,0.0003970698,0.0010325217,0.00071009865,0.0010359505,0.0005922452,0.00019456363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021939352,0.0005440341,0.004306926,0.0009295157,0.00012217874,0.0008891817,0.0004613388,0.3996077,0.31997582,0.210159,0.0004930099,0.06229189],"study_design_scores_gemma":[0.000015728452,0.00026769587,0.0029454313,0.00006575441,0.000050064067,0.00018239298,0.00009443636,0.94622356,0.026568804,0.021193054,0.0023434367,0.000049691575],"about_ca_topic_score_codex":0.002515052,"about_ca_topic_score_gemma":0.0014646588,"teacher_disagreement_score":0.002515052,"about_ca_system_score_codex":0.0006523289,"about_ca_system_score_gemma":0.0011096991,"threshold_uncertainty_score":0.005853832},"labels":[],"label_agreement":null},{"id":"W2132994207","doi":"10.1142/s0219686713500017","title":"PREDICTION OF CUTTING FORCES IN BROACHING OPERATION","year":2013,"lang":"en","type":"article","venue":"Journal of Advanced Manufacturing Systems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Broaching; Machining; Parametric statistics; Enhanced Data Rates for GSM Evolution; Mechanical engineering; Engineering; Oblique case; Structural engineering; Parametric model; Computer science; Mathematics","score_opus":0.008087591583239977,"score_gpt":0.20342445258307496,"score_spread":0.19533686099983497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132994207","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7837374,0.0001817835,0.20964186,0.000076503675,0.00002726442,0.0000622387,0.0001456315,0.00048340266,0.0056438907],"genre_scores_gemma":[0.9894667,0.000066961504,0.008818528,0.00000642634,0.0000019448062,0.000019447105,0.00008176169,0.000020890138,0.0015173998],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998354,0.000016980597,0.0000075108587,0.000034794837,0.00007037001,0.00003501333],"domain_scores_gemma":[0.99950874,0.00023062818,0.000089164656,0.000050591025,0.00008961109,0.00003127673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027997384,0.00054082234,0.00040739696,0.00042283727,0.00031273448,0.0004990736,0.0005951239,0.0014083962,0.0010928322],"category_scores_gemma":[0.0010666461,0.0003128412,0.00039171882,0.00021334535,0.00041083933,0.0004836289,0.00039594775,0.0005173701,0.0002378717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009691517,0.00007609136,0.0035083133,0.000043680135,0.0000072268554,0.00024720843,0.00007166626,0.96321523,0.019237457,0.000616554,0.00022940378,0.012650204],"study_design_scores_gemma":[0.0000019786307,0.000022108585,0.0009526125,0.0000019326778,0.0000010841858,0.000017255743,0.000007861316,0.99746346,0.0013815237,0.00007951522,0.00006737579,0.0000033461454],"about_ca_topic_score_codex":0.0054189423,"about_ca_topic_score_gemma":0.003812677,"teacher_disagreement_score":0.0054189423,"about_ca_system_score_codex":0.0002933194,"about_ca_system_score_gemma":0.00036501035,"threshold_uncertainty_score":0.010774851},"labels":[],"label_agreement":null},{"id":"W2134214742","doi":"10.1109/icmens.2004.1508993","title":"Modeling and Experiments of Input-Output Displacement Relations for a Piezoelectric Nanopositioner","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Displacement (psychology); Actuator; Control theory (sociology); Piezoelectricity; Lock (firearm); Range (aeronautics); Mechanism (biology); Process (computing); Computer science; Structural engineering; Engineering; Acoustics; Physics; Control (management)","score_opus":0.008017523604420075,"score_gpt":0.23207235061579698,"score_spread":0.2240548270113769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134214742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69707596,0.00045461315,0.28737125,0.0005072454,0.000029502791,0.00011072788,0.00041688076,0.0009357294,0.013098102],"genre_scores_gemma":[0.98457414,0.00012697544,0.013024953,0.00001392667,0.000003026512,0.00004797012,0.00005125973,0.000033934837,0.0021238362],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998191,0.000023151339,0.000008339546,0.000045997258,0.000085736094,0.000017770513],"domain_scores_gemma":[0.9996106,0.00025243312,0.000051110248,0.000035946494,0.00004099381,0.000008900317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040122258,0.00029896147,0.00029934567,0.00013368197,0.0003116793,0.00037818713,0.0007114934,0.00085964205,0.0022912475],"category_scores_gemma":[0.00093658705,0.00025771384,0.00025610067,0.0001575501,0.0004372792,0.00068685156,0.0002283318,0.00042086237,0.0002848257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002767213,0.00009653175,0.0019595278,0.00026917865,0.000017726745,0.00039052402,0.00050909043,0.6976742,0.2697504,0.014293305,0.00049929967,0.014263548],"study_design_scores_gemma":[0.000007983268,0.000029982131,0.00031840825,0.000003250486,0.000002976542,0.000020212092,0.000010086831,0.97788495,0.020977944,0.00044403845,0.00029327968,0.0000069253424],"about_ca_topic_score_codex":0.0026274158,"about_ca_topic_score_gemma":0.0023051417,"teacher_disagreement_score":0.0026274158,"about_ca_system_score_codex":0.0005211167,"about_ca_system_score_gemma":0.00043292317,"threshold_uncertainty_score":0.007665038},"labels":[],"label_agreement":null},{"id":"W2135719853","doi":"10.1115/imece2014-37348","title":"Influence of Hard Turning on Microstructure Evolution in the Subsurface Layers of Inconel 718","year":2014,"lang":"en","type":"article","venue":"Volume 2A: Advanced Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec; McGill University","keywords":"Inconel; Nanoindentation; Materials science; Machining; Microstructure; Surface integrity; Residual stress; Surface roughness; Carbide; Metallurgy; Surface finish; Softening; Composite material","score_opus":0.003419782658703121,"score_gpt":0.1970483793594807,"score_spread":0.19362859670077756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135719853","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988932,0.00018173445,0.00042861057,0.0000053512363,0.000003604631,0.0000034044967,0.000027865442,0.00001771987,0.0004386106],"genre_scores_gemma":[0.9990527,0.00006549641,0.00048773887,0.0000056614263,8.5984595e-7,0.0000024804726,0.00004875963,0.000010776799,0.00032543132],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979573,0.000014309116,0.000009256668,0.00003942676,0.00008144629,0.000059852384],"domain_scores_gemma":[0.9997352,0.00007025835,0.00006913974,0.000032321106,0.0000657823,0.00002737939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013808518,0.00023734137,0.00028414303,0.00024315191,0.00025140698,0.00044299755,0.00018047728,0.00025427903,0.0010734008],"category_scores_gemma":[0.00034561413,0.00023656194,0.00017564405,0.00013442758,0.00025517205,0.0002305753,0.00020727131,0.0002451478,0.00015969053],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020870972,0.000013347432,0.002397228,0.00006174333,0.00000848298,0.0001655686,0.0000665272,0.001031117,0.9909276,0.000029838424,0.00003371499,0.0050561377],"study_design_scores_gemma":[0.000020804564,0.001201731,0.078981385,0.000013485086,0.0000434855,0.00036839503,0.000312739,0.0052327644,0.9117114,0.00007938735,0.00201091,0.000023648652],"about_ca_topic_score_codex":0.0010887717,"about_ca_topic_score_gemma":0.0029741996,"teacher_disagreement_score":0.0010887717,"about_ca_system_score_codex":0.00015423729,"about_ca_system_score_gemma":0.00014212972,"threshold_uncertainty_score":0.0035908222},"labels":[],"label_agreement":null},{"id":"W2135895503","doi":"10.5267/j.ijiec.2015.4.004","title":"Statistical analysis of AISI304 austenitic stainless steel machining using Ti(C, N)/Al2O3/TiN CVD coated carbide tool","year":2015,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Université de Tunis; Centre National de la Recherche Scientifique; Indian National Science Academy","keywords":"Metallurgy; Materials science; Machining; Carbide; Tin; Austenitic stainless steel; Austenite; Corrosion; Microstructure","score_opus":0.04571724950232368,"score_gpt":0.30381918063144114,"score_spread":0.25810193112911745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135895503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9676752,0.00022135518,0.030206714,0.00002528152,0.000018693354,0.00011120199,0.0005750164,0.00017194517,0.0009945887],"genre_scores_gemma":[0.9842657,0.00007355088,0.014375605,0.000008422188,0.0000072382986,0.00011867334,0.0005735973,0.000025418067,0.00055168103],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9967428,0.0006499451,0.00026715864,0.0006092504,0.0015911845,0.00013980255],"domain_scores_gemma":[0.9918704,0.005048145,0.0010277671,0.00051359687,0.0014358128,0.00010430857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032146869,0.0002980684,0.00062966225,0.00088771357,0.00022658662,0.00047699534,0.00030941144,0.0002502755,0.00096793904],"category_scores_gemma":[0.0058593415,0.00012261915,0.0007198704,0.0010152038,0.00043354448,0.00022833027,0.00024493635,0.00037188662,0.0001554969],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037710196,0.00096977194,0.16899043,0.0017245354,0.00077523285,0.0006378275,0.0013477836,0.028858524,0.54074377,0.0011422875,0.00092913077,0.25010973],"study_design_scores_gemma":[0.000025279625,0.006333745,0.8291196,0.000026698926,0.00028683225,0.0003348005,0.0005502231,0.054770704,0.1053187,0.0005095011,0.0026503208,0.00007349663],"about_ca_topic_score_codex":0.0007807007,"about_ca_topic_score_gemma":0.0010809355,"teacher_disagreement_score":0.0032146869,"about_ca_system_score_codex":0.0003082543,"about_ca_system_score_gemma":0.00037090053,"threshold_uncertainty_score":0.017001092},"labels":[],"label_agreement":null},{"id":"W2136352409","doi":"10.1299/jsmec.44.717","title":"Analytical Prediction of Three Dimensional Chatter Stability in Milling.","year":2001,"lang":"en","type":"article","venue":"JSME International Journal Series C","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":161,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Cartesian coordinate system; Stability (learning theory); Ball (mathematics); Milling cutter; Vibration; Frequency domain; Cutting tool; Machining; End milling; Machine tool; Control theory (sociology); Engineering; Mechanical engineering; Structural engineering; Computer science; Mathematical analysis; Mathematics; Geometry; Acoustics; Physics; Artificial intelligence","score_opus":0.016920086357124876,"score_gpt":0.24430485145353445,"score_spread":0.22738476509640956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136352409","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21925618,0.0006976843,0.7706029,0.00023941479,0.000046390905,0.000053443084,0.00006663588,0.00040771923,0.008629728],"genre_scores_gemma":[0.98793346,0.00015046122,0.010297353,0.000016516367,0.00000681774,0.00002229392,0.000020748235,0.000020093777,0.001532178],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990964,0.000019249905,0.0000031639554,0.000011435764,0.000045596407,0.000010854871],"domain_scores_gemma":[0.99920243,0.00049194257,0.00007816365,0.000042244938,0.00015939806,0.000025862162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003894414,0.00036635253,0.00027840445,0.0003460665,0.00019660473,0.00039826185,0.0004259784,0.00055192865,0.0009561121],"category_scores_gemma":[0.0023727517,0.00021215645,0.0003354149,0.000121219084,0.0005739182,0.00039539573,0.0002928081,0.00044229793,0.00020784565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071546856,0.00003223664,0.0013795799,0.00012819859,0.000019581863,0.00031316702,0.00024175197,0.9407143,0.028592719,0.01901994,0.00044275637,0.009044168],"study_design_scores_gemma":[0.0000010405042,0.000005025308,0.00009089844,0.000001647508,8.0695145e-7,0.000009758243,0.0000030443457,0.998587,0.0006269618,0.0006209041,0.000051140756,0.0000018563377],"about_ca_topic_score_codex":0.0026898717,"about_ca_topic_score_gemma":0.0016971518,"teacher_disagreement_score":0.0026898717,"about_ca_system_score_codex":0.0005291881,"about_ca_system_score_gemma":0.0003454226,"threshold_uncertainty_score":0.0053485036},"labels":[],"label_agreement":null},{"id":"W2136935623","doi":"10.1115/1.4024632","title":"New Approach of Gas–Liquid Computational Fluid Dynamics Simulations for the Study of Minimum Quantity Cooling With Airblast Plain-Jet Injectors","year":2013,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Research Council Canada; Universitatea \"Lucian Blaga\" din Sibiu","keywords":"Reynolds-averaged Navier–Stokes equations; Computational fluid dynamics; Turbulence; Mechanics; Injector; Nozzle; Jet (fluid); Particle image velocimetry; Coolant; Flow (mathematics); Reynolds number; Two-phase flow; Multiphase flow; Phase (matter); Physics; Materials science; Thermodynamics","score_opus":0.009181310362757608,"score_gpt":0.22491836395967812,"score_spread":0.21573705359692052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136935623","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18383075,0.0004881777,0.803448,0.00040448873,0.00020033559,0.0002755651,0.00027871554,0.00059445907,0.010479441],"genre_scores_gemma":[0.6427837,0.00048036073,0.35129732,0.00010592557,0.00008965428,0.00066355563,0.00034207967,0.00020231667,0.0040351734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998412,0.00005609418,0.000008563572,0.00001897762,0.00005955072,0.000015495152],"domain_scores_gemma":[0.9997384,0.00011940141,0.00002472492,0.000030920746,0.0000639459,0.000022645498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003649359,0.0006129894,0.0005766403,0.00036058848,0.00048176452,0.0006242111,0.0009933581,0.0009675901,0.0011810664],"category_scores_gemma":[0.0009192479,0.00030259206,0.0007254982,0.00025376945,0.00041194566,0.0005668641,0.000544599,0.0009217954,0.00017971602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006857768,0.0001261517,0.0012908821,0.00009026212,0.000036449164,0.00012517381,0.0000965648,0.9512004,0.020428978,0.013902401,0.0005050661,0.012129128],"study_design_scores_gemma":[0.0000055458904,0.0000065134454,0.00007334989,0.0000017267737,0.0000012973369,0.000004058667,0.000002525873,0.9986866,0.0006178359,0.0002573057,0.00034106427,0.0000022406375],"about_ca_topic_score_codex":0.0044560432,"about_ca_topic_score_gemma":0.004158275,"teacher_disagreement_score":0.0044560432,"about_ca_system_score_codex":0.00046486617,"about_ca_system_score_gemma":0.0011368748,"threshold_uncertainty_score":0.00886023},"labels":[],"label_agreement":null},{"id":"W2138622222","doi":"10.1109/pacrim.2011.6032986","title":"Neural networks approach to biocomposites processing","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Artificial neural network; Artificial intelligence; MATLAB; Computer science; Biocomposite; Backpropagation; Machine learning; Algorithm; Data mining","score_opus":0.017009610851285058,"score_gpt":0.2074528250499327,"score_spread":0.19044321419864765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138622222","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0063811955,0.0038342238,0.978131,0.0005492842,0.00012418216,0.000049282437,0.00010937102,0.00041502327,0.010406406],"genre_scores_gemma":[0.4366107,0.012680141,0.51179606,0.00046339855,0.00044672834,0.0005112389,0.0005581115,0.00017579,0.036757816],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966586,0.00007320548,0.000023769288,0.000075205695,0.00013389347,0.000028032668],"domain_scores_gemma":[0.9996476,0.00015905639,0.00002569085,0.000017301265,0.00014050218,0.000009817078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005266387,0.00069289916,0.00071238965,0.00088183384,0.00031856546,0.0013874454,0.0011288126,0.0011042862,0.0026773086],"category_scores_gemma":[0.0010861476,0.0004003402,0.0007767832,0.0009948494,0.0005747689,0.0009454344,0.00056208996,0.0014003824,0.0006043867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049626553,0.000036070393,0.00039772352,0.00024155472,0.000086699685,0.0000929813,0.0000574432,0.8517828,0.003944333,0.047281172,0.0015525612,0.09447711],"study_design_scores_gemma":[0.000003371774,0.000013864846,0.000104843406,0.000017757793,0.000010843462,0.000016474274,0.00000998636,0.97858375,0.0013680414,0.016877757,0.0029854164,0.000007936833],"about_ca_topic_score_codex":0.0062375306,"about_ca_topic_score_gemma":0.004106055,"teacher_disagreement_score":0.0062375306,"about_ca_system_score_codex":0.0012354631,"about_ca_system_score_gemma":0.00085268484,"threshold_uncertainty_score":0.012402475},"labels":[],"label_agreement":null},{"id":"W2139709018","doi":"10.5267/j.ijiec.2014.4.002","title":"A response surface methodology and desirability approach for predictive modeling and optimization of cutting temperature in machining hardened steel","year":2014,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Kalinga Institute of Industrial Technology","keywords":"Response surface methodology; Machining; Carbide; Degree (music); Process (computing); Design of experiments; Materials science; Mathematics; Mechanical engineering; Metallurgy; Engineering; Statistics; Computer science; Physics","score_opus":0.045459844305185744,"score_gpt":0.2905666867195009,"score_spread":0.24510684241431518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139709018","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02416754,0.00022781576,0.9740175,0.00006369269,0.000014391823,0.00006397986,0.000024829398,0.0003979962,0.0010222963],"genre_scores_gemma":[0.77985996,0.000512693,0.21579991,0.00007394804,0.000026057016,0.0005072736,0.00016484759,0.00017726411,0.002878031],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924374,0.0003227499,0.000036542773,0.00010319958,0.00024988106,0.000043845394],"domain_scores_gemma":[0.99929035,0.00046159275,0.000069414804,0.000038357866,0.00012786199,0.00001239128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015373644,0.0013521113,0.001092717,0.00063804135,0.00030874077,0.00081029657,0.0008810154,0.0013063903,0.0010618161],"category_scores_gemma":[0.0017684055,0.00077763235,0.001739169,0.0004190389,0.00046122455,0.00055087195,0.0004568421,0.0013809957,0.00030716212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045802753,0.000060217266,0.0003845725,0.0001342902,0.00006140647,0.00004656497,0.00005774405,0.9672248,0.010960054,0.0016142364,0.00008727461,0.019323105],"study_design_scores_gemma":[0.0000037696902,0.000074095864,0.0001253273,0.0000038048763,0.000006988915,0.00000791039,0.0000051372967,0.9977539,0.0013977684,0.00038508748,0.00023065225,0.0000056449935],"about_ca_topic_score_codex":0.004139547,"about_ca_topic_score_gemma":0.0021554795,"teacher_disagreement_score":0.004139547,"about_ca_system_score_codex":0.0006527895,"about_ca_system_score_gemma":0.00063907297,"threshold_uncertainty_score":0.008230925},"labels":[],"label_agreement":null},{"id":"W2141933071","doi":"10.1115/imece2014-37170","title":"On the Effect of Johnson Cook Material Constants to Simulate Al2024-T3 Machining Using Finite Element Modeling","year":2014,"lang":"en","type":"article","venue":"Volume 2A: Advanced Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Finite element method; Constitutive equation; Chip formation; Mechanical engineering; Materials science; Drilling; Work (physics); Chip; Structural engineering; Computer science; Tool wear; Engineering","score_opus":0.0069719831691909834,"score_gpt":0.22794723286711127,"score_spread":0.2209752496979203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141933071","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8943243,0.0007924448,0.090179674,0.00020555129,0.00007691116,0.00014130917,0.00020902812,0.0010329835,0.013037853],"genre_scores_gemma":[0.9791236,0.00018695231,0.019744217,0.000038197544,0.000006425318,0.000036187823,0.00008197009,0.000112920934,0.00066962553],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945635,0.00015686477,0.00003578444,0.0000553133,0.00023871986,0.000056989124],"domain_scores_gemma":[0.9959269,0.0028996225,0.00034997961,0.0003013706,0.00046199778,0.00006006845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009923484,0.00068372424,0.0003912922,0.0006159513,0.00043667475,0.0007265557,0.00071457255,0.0009157206,0.0011060075],"category_scores_gemma":[0.0043402035,0.00032623167,0.0005091085,0.0005111139,0.00037101688,0.00043791597,0.00030100092,0.00055954134,0.00019270611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024452413,0.00023375373,0.0049702046,0.00011884274,0.00002914609,0.00010929717,0.000082440165,0.94365925,0.033551406,0.0013249405,0.00030095773,0.015375096],"study_design_scores_gemma":[0.0000139803715,0.00011496458,0.0014514255,0.000013765593,0.000021475313,0.000023132889,0.000016432312,0.97586036,0.02179474,0.000092591494,0.000583727,0.0000133243075],"about_ca_topic_score_codex":0.008812496,"about_ca_topic_score_gemma":0.008390711,"teacher_disagreement_score":0.008812496,"about_ca_system_score_codex":0.0004974979,"about_ca_system_score_gemma":0.0007652831,"threshold_uncertainty_score":0.017522395},"labels":[],"label_agreement":null},{"id":"W2143360816","doi":"10.24908/pceea.v0i0.3956","title":"SUBSTRUCTURE COUPLING WITH JOINT IDENFICATION FOR RECONFIGURABLE MANUFACTURING SYSTEMS","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Substructure; Joint (building); Modular design; Degrees of freedom (physics and chemistry); Computer science; Coupling (piping); Fastener; Finite element method; Identification (biology); Universal joint; Convergence (economics); Algorithm; Mechanical engineering; Control engineering; Engineering; Structural engineering; Physics","score_opus":0.009689426197715494,"score_gpt":0.17468899524992498,"score_spread":0.1649995690522095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143360816","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052190274,0.00007389655,0.9456157,0.000019759613,0.00001371392,0.000029251283,0.0000051271086,0.00018887823,0.0018634236],"genre_scores_gemma":[0.703257,0.00010220108,0.29413188,0.000021939755,0.000010274045,0.000077714816,0.000028802348,0.000042634067,0.0023275458],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958867,0.00009836296,0.000021012225,0.00007552317,0.0001945827,0.000021912649],"domain_scores_gemma":[0.9996462,0.00013048813,0.0000935736,0.00007215653,0.000045998997,0.000011604034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047403906,0.00061550125,0.00034449995,0.00041190896,0.0002607994,0.00031226373,0.000458081,0.0003841029,0.001137534],"category_scores_gemma":[0.0010251953,0.000266888,0.00035561723,0.00025511076,0.00044091322,0.0005427069,0.0006656182,0.00033587197,0.00027787144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020819863,0.00010790903,0.0021201568,0.00025193757,0.000057933867,0.00032071548,0.00047074264,0.39834654,0.35924852,0.018525407,0.0002705312,0.2200713],"study_design_scores_gemma":[0.000012563756,0.00030741395,0.0012808562,0.000018403036,0.000019493265,0.00023018864,0.000052283176,0.9313893,0.060382616,0.003142451,0.003129534,0.00003484538],"about_ca_topic_score_codex":0.0005024102,"about_ca_topic_score_gemma":0.00065755245,"teacher_disagreement_score":0.001137534,"about_ca_system_score_codex":0.00016300227,"about_ca_system_score_gemma":0.000260208,"threshold_uncertainty_score":0.003805399},"labels":[],"label_agreement":null},{"id":"W2143664202","doi":"10.5267/j.ijiec.2014.11.001","title":"Response surface and artificial neural network prediction model and optimization for surface roughness in machining","year":2015,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Response surface methodology; Surface roughness; Artificial neural network; Machining; Parametric statistics; Parametric model; Materials science; Coefficient of determination; Design of experiments; Mathematics; Biological system; Computer science; Statistics; Artificial intelligence; Composite material; Metallurgy","score_opus":0.03944196855066009,"score_gpt":0.2795422055519603,"score_spread":0.2401002370013002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143664202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18668713,0.0005647046,0.80829525,0.00017683028,0.00003980623,0.000054501623,0.000075921576,0.00069892197,0.0034069251],"genre_scores_gemma":[0.9492452,0.00022711433,0.048182487,0.000027484542,0.000011032325,0.000108156455,0.00011290046,0.00003582661,0.0020499118],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996177,0.0001281499,0.000020491005,0.00007335073,0.00012454663,0.000035713438],"domain_scores_gemma":[0.9996666,0.00018202925,0.00004093438,0.00001896848,0.000083090665,0.000008505198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068541756,0.00064137054,0.0005415693,0.00037546363,0.0001990028,0.00052699546,0.0005710462,0.0008232378,0.00094694126],"category_scores_gemma":[0.0011166427,0.0003654717,0.00070673286,0.00043831335,0.00028005606,0.00052887446,0.0002631342,0.0005552436,0.00020152268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027805165,0.000023732491,0.0005954414,0.00003962387,0.000016183505,0.00002565534,0.00001056252,0.9857826,0.0019835168,0.00031523925,0.000114016926,0.011065659],"study_design_scores_gemma":[0.0000011683184,0.000014749369,0.00018112586,9.476166e-7,0.0000018057257,0.0000027052838,0.0000013524775,0.9993206,0.0003594342,0.00007261154,0.00004165807,0.0000017618516],"about_ca_topic_score_codex":0.006672028,"about_ca_topic_score_gemma":0.0043323617,"teacher_disagreement_score":0.006672028,"about_ca_system_score_codex":0.00046067333,"about_ca_system_score_gemma":0.00049832946,"threshold_uncertainty_score":0.013266385},"labels":[],"label_agreement":null},{"id":"W2147883621","doi":"10.1007/978-981-4451-48-2_48","title":"Investigation of Energy, Carbon Dioxide Emissions and Costs in Single Point Incremental Forming","year":2013,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Carbon dioxide; Point (geometry); Environmental science; Energy (signal processing); Environmental economics; Natural resource economics; Economics; Chemistry; Mathematics; Statistics","score_opus":0.011771199604171546,"score_gpt":0.1959076452063635,"score_spread":0.18413644560219194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147883621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75020325,0.0198653,0.08338978,0.00048846216,0.00015490022,0.00007524529,0.00034254667,0.0001153491,0.14536524],"genre_scores_gemma":[0.9620502,0.005384987,0.010853426,0.000020670099,0.00001679368,0.000018879284,0.00014448336,0.000036110676,0.021474598],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9998559,0.00002002213,0.0000043377645,0.000021313223,0.00008342077,0.000015011193],"domain_scores_gemma":[0.9998404,0.00011532106,0.00000800051,0.000009757976,0.000023632296,0.0000029231499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020887033,0.00030675912,0.00043624872,0.00036174915,0.00025154365,0.0006945914,0.0006631732,0.0004320292,0.0022253809],"category_scores_gemma":[0.00048362016,0.00024639443,0.00045093306,0.00095505785,0.0003938141,0.0007344756,0.0002377665,0.00039984437,0.0001543098],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041243454,0.00022791803,0.006214082,0.0007557324,0.0000776975,0.00047672333,0.00021865507,0.5942302,0.043460947,0.10732635,0.0020812908,0.24451798],"study_design_scores_gemma":[0.000017861723,0.00045149305,0.020911302,0.00009932491,0.0000929141,0.00063952635,0.00051410176,0.81611973,0.077618614,0.06787903,0.015592988,0.00006311477],"about_ca_topic_score_codex":0.003554039,"about_ca_topic_score_gemma":0.0054181814,"teacher_disagreement_score":0.003554039,"about_ca_system_score_codex":0.00075459044,"about_ca_system_score_gemma":0.00038642465,"threshold_uncertainty_score":0.00744462},"labels":[],"label_agreement":null},{"id":"W2151400380","doi":"10.1016/j.msea.2006.06.129","title":"Effect of metallurgical parameters on the machinability of heat-treated 356 and 319 aluminum alloys","year":2006,"lang":"en","type":"article","venue":"Materials Science and Engineering A","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":77,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intermetallic; Machinability; Metallurgy; Volume fraction; Alloy; Materials science; Aluminium; Volume (thermodynamics); Quenching (fluorescence); Composite material; Machining; Thermodynamics","score_opus":0.0036024304225506848,"score_gpt":0.19767258915430588,"score_spread":0.1940701587317552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151400380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99876714,0.0003964337,0.00018647611,0.00002471148,0.000009330885,0.000005019891,0.000070067654,0.000018947581,0.00052198366],"genre_scores_gemma":[0.99906486,0.00007873078,0.00019331611,0.000008140799,0.000004074941,0.0000029969094,0.00007869009,0.000015724832,0.0005534508],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999754,0.000032654032,0.000029766788,0.00004438488,0.00009025556,0.000048875172],"domain_scores_gemma":[0.99945444,0.00021884283,0.00012468408,0.00005962939,0.000101794765,0.000040757826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032484255,0.0003341489,0.00044404247,0.00042459974,0.0004891297,0.000606347,0.00034560755,0.00058221066,0.0022756162],"category_scores_gemma":[0.0010080131,0.00037487046,0.0003537391,0.00033760894,0.00035891484,0.0004127617,0.0002004132,0.00036248015,0.00037016405],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016514021,0.000048430476,0.0021929892,0.00014553129,0.000042047726,0.00020653041,0.00018530348,0.0023545497,0.9897417,0.00008599491,0.00009463798,0.003250957],"study_design_scores_gemma":[0.000030562565,0.0008344524,0.012418758,0.000007196362,0.00004600301,0.00008486518,0.0001061499,0.002125948,0.98342794,0.000038816812,0.0008614857,0.000017913804],"about_ca_topic_score_codex":0.0009682144,"about_ca_topic_score_gemma":0.0018432058,"teacher_disagreement_score":0.0022756162,"about_ca_system_score_codex":0.00038907476,"about_ca_system_score_gemma":0.00021049072,"threshold_uncertainty_score":0.007612705},"labels":[],"label_agreement":null},{"id":"W2152910626","doi":"10.1109/icma.2009.5246491","title":"Dynamic model and modal testing for vibration analysis of robotic grinding process with a 6DOF flexible-joint manipulator","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hydro-Québec; École de Technologie Supérieure","funders":"","keywords":"Vibration; Modal analysis; Modal; Robot; Machine tool; Computer science; Machining; Hammer; Mechanical engineering; Engineering; Stiffness; Automation; Process (computing); Payload (computing); Control engineering; Simulation; Structural engineering; Finite element method; Acoustics; Artificial intelligence; Materials science","score_opus":0.02032316429505217,"score_gpt":0.25865949551770995,"score_spread":0.23833633122265777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152910626","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16917157,0.00011358496,0.82704455,0.00005705428,0.000008459223,0.000029569264,0.00003315595,0.00017663697,0.003365495],"genre_scores_gemma":[0.971518,0.000076921424,0.026500754,0.000007747813,0.0000046190944,0.000053980468,0.00003666324,0.000011561527,0.0017898111],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998721,0.000024836898,0.0000040463,0.000022692242,0.00006572414,0.000010610678],"domain_scores_gemma":[0.9998946,0.00004320825,0.000025209398,0.0000137999705,0.00001832313,0.0000048937623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026597327,0.00030181272,0.00021883112,0.00020360958,0.00018942892,0.00020000049,0.00046834012,0.00049776735,0.0013670991],"category_scores_gemma":[0.00032492678,0.0001659416,0.00040222247,0.00009024631,0.0002967171,0.000275208,0.00022935576,0.00030274846,0.00018708878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050168663,0.000036611706,0.0008930512,0.000061994826,0.000013819307,0.0001369904,0.00010637522,0.9276161,0.05513215,0.004798637,0.00008454355,0.011069426],"study_design_scores_gemma":[0.0000029802782,0.00004207857,0.00038762728,0.0000017604395,0.000002042169,0.000016798576,0.000008661131,0.99770206,0.0012810013,0.00036135816,0.00019069779,0.0000029777666],"about_ca_topic_score_codex":0.0021098764,"about_ca_topic_score_gemma":0.0012900389,"teacher_disagreement_score":0.0021098764,"about_ca_system_score_codex":0.00022501007,"about_ca_system_score_gemma":0.00026522196,"threshold_uncertainty_score":0.004573405},"labels":[],"label_agreement":null},{"id":"W2153058820","doi":"10.1115/1.4029955","title":"Tool Wear Monitoring and Alarm System Based on Pattern Recognition With Logical Analysis of Data","year":2015,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"ALARM; Tool wear; Machining; Aerospace; Limit (mathematics); False alarm; Computer science; Process (computing); Moment (physics); Reliability engineering; Matrix (chemical analysis); Control limits; Data mining; Pattern recognition (psychology); Real-time computing; Engineering; Artificial intelligence; Mechanical engineering; Materials science; Mathematics; Aerospace engineering","score_opus":0.0313820879625891,"score_gpt":0.24428473315219815,"score_spread":0.21290264518960905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153058820","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07031803,0.00049930497,0.91458195,0.000149007,0.000097961725,0.00025266985,0.00040346582,0.012272323,0.001425311],"genre_scores_gemma":[0.70216846,0.0002742547,0.29391402,0.00029108606,0.00010964393,0.00048609704,0.00063020736,0.00014510287,0.0019810281],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998456,0.0002253394,0.00014441609,0.00038235795,0.00070723816,0.00008471926],"domain_scores_gemma":[0.99704486,0.0014835387,0.00049048255,0.00031532667,0.0005645772,0.00010113212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097056205,0.000637546,0.0008821431,0.0015052367,0.00028585404,0.0008665328,0.0011873037,0.0006126305,0.0013478505],"category_scores_gemma":[0.0033151882,0.0002955384,0.0004136192,0.0006025209,0.00030571947,0.0010793123,0.00066394126,0.0005140452,0.0004910965],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020737068,0.000645919,0.021028377,0.00065324624,0.00024508417,0.0007031412,0.0003191896,0.01791289,0.15703484,0.0022264845,0.0056958655,0.79146117],"study_design_scores_gemma":[0.00024580554,0.0019054369,0.020383826,0.00008365186,0.0002775721,0.0020665352,0.00013595645,0.79640514,0.1623073,0.003517768,0.012517625,0.00015336592],"about_ca_topic_score_codex":0.0005093725,"about_ca_topic_score_gemma":0.00051950413,"teacher_disagreement_score":0.0015052367,"about_ca_system_score_codex":0.0003199516,"about_ca_system_score_gemma":0.0004842429,"threshold_uncertainty_score":0.005132854},"labels":[],"label_agreement":null},{"id":"W2155497567","doi":"10.1115/1.2164508","title":"Flank Wear Progression During Machining Metal Matrix Composites","year":2005,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; University of New Brunswick","funders":"","keywords":"Flank; Machinability; Abrasion (mechanical); Machining; Abrasive; Materials science; Tool wear; Composite material; Composite number; Matrix (chemical analysis); Bar (unit); Metallurgy; Geology","score_opus":0.0036840652924135446,"score_gpt":0.23176042075546172,"score_spread":0.22807635546304816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155497567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965306,0.00019415506,0.0028685913,0.000005433567,0.0000058644455,0.000008413194,0.000028691262,0.000080133665,0.00027820052],"genre_scores_gemma":[0.99893385,0.000044122564,0.0008282063,0.0000021446344,0.0000011256865,0.000002605033,0.0000270445,0.000004571831,0.00015637063],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997602,0.000032691565,0.0000119230435,0.000037130412,0.0001294537,0.000028620749],"domain_scores_gemma":[0.9991456,0.00043333898,0.00014297485,0.0000756517,0.00017398455,0.00002843602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003809393,0.00029989326,0.00031037605,0.0004670902,0.0002154507,0.00023173612,0.00028418776,0.00038160337,0.00037376978],"category_scores_gemma":[0.0009556664,0.00020856864,0.00026833877,0.00018359961,0.00022736617,0.00022267671,0.0001303587,0.00029633092,0.00010416486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011909325,0.00010957503,0.026261305,0.00028615407,0.000031338222,0.00089251605,0.0008595916,0.0313506,0.8887319,0.000108151784,0.00019096652,0.049986895],"study_design_scores_gemma":[0.000024035737,0.0022908787,0.11318423,0.000032645297,0.000045855926,0.0011783001,0.00032706733,0.18608809,0.695687,0.00022134703,0.00084896927,0.000071539216],"about_ca_topic_score_codex":0.0013877711,"about_ca_topic_score_gemma":0.002452202,"teacher_disagreement_score":0.0013877711,"about_ca_system_score_codex":0.00024777683,"about_ca_system_score_gemma":0.00011626862,"threshold_uncertainty_score":0.002759397},"labels":[],"label_agreement":null},{"id":"W2158787990","doi":"10.1109/nafips.2004.1337439","title":"Fuzzy modeling and prediction of cylindricity error in BTA deep hole boring process","year":2004,"lang":"en","type":"article","venue":"IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04.","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Process (computing); Computer science; Set (abstract data type); Operator (biology); Fuzzy logic; Drilling; Mode (computer interface); Artificial intelligence; Algorithm; Mechanical engineering; Engineering","score_opus":0.009473853066686338,"score_gpt":0.23329195204887365,"score_spread":0.22381809898218732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158787990","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.54544544,0.00033812434,0.44988522,0.00019559544,0.000041664178,0.000023956432,0.000054588036,0.0002525247,0.0037629772],"genre_scores_gemma":[0.9947455,0.00006046499,0.0044668335,0.000005207318,0.0000029598166,0.0000050033036,0.000012694873,0.000004629435,0.0006968324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983776,0.00003850517,0.000007639822,0.000028558727,0.00006561849,0.000021814136],"domain_scores_gemma":[0.9996203,0.0001829273,0.00007061501,0.000028830435,0.00008009883,0.000017133381],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041836035,0.00038053025,0.00042874945,0.0003253502,0.00032345467,0.0007451906,0.00036394762,0.00064588716,0.00046110695],"category_scores_gemma":[0.001020076,0.00024661957,0.00031280244,0.00020866591,0.00036670108,0.00050858315,0.00021499513,0.0004092209,0.00010663743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007737947,0.000018293898,0.0009674754,0.000017051203,0.000008264159,0.000065670974,0.000050192513,0.9833294,0.006716142,0.0014470113,0.00007173692,0.007231473],"study_design_scores_gemma":[0.0000015236028,0.000013498237,0.00026440708,9.250243e-7,0.0000013985725,0.000004273029,0.0000031725276,0.99889463,0.0005000954,0.00028079096,0.000032767843,0.000002562274],"about_ca_topic_score_codex":0.011906857,"about_ca_topic_score_gemma":0.010116254,"teacher_disagreement_score":0.011906857,"about_ca_system_score_codex":0.00047958604,"about_ca_system_score_gemma":0.00041785775,"threshold_uncertainty_score":0.023675084},"labels":[],"label_agreement":null},{"id":"W2159274580","doi":"10.5267/j.ijiec.2015.3.002","title":"Machining parameter optimization in turning process for sustainable manufacturing","year":2015,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Manufacturing engineering; Process (computing); Process variable; Mechanical engineering; Process optimization; Process engineering; Engineering; Computer science","score_opus":0.028258910727770713,"score_gpt":0.28664428207193676,"score_spread":0.25838537134416606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159274580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8615768,0.0013026061,0.12982738,0.000107459164,0.00002333468,0.00009770263,0.00007164156,0.00021234306,0.0067807264],"genre_scores_gemma":[0.99168384,0.00021967142,0.00753507,0.000008117583,0.000001384898,0.000022390526,0.000031085958,0.000010572895,0.00048772295],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998271,0.000030541018,0.000010215501,0.00003137609,0.000060248734,0.000040542236],"domain_scores_gemma":[0.999808,0.00010211883,0.00003557066,0.000012317112,0.000035307647,0.0000068061786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030566932,0.00038262134,0.00047767488,0.00044266006,0.00024340683,0.00075620547,0.0003303624,0.0005238066,0.00097359065],"category_scores_gemma":[0.0005753074,0.00025654302,0.00057721906,0.00042192166,0.00022593295,0.00030700606,0.00027100858,0.00031996134,0.00015588824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019636398,0.00020636844,0.004001963,0.0004737585,0.000050904702,0.0002377056,0.00013015344,0.84775716,0.101295315,0.0010112242,0.0001968543,0.044442195],"study_design_scores_gemma":[0.000026302412,0.0008413967,0.0072133006,0.000029828821,0.00007118739,0.000121390294,0.00019889344,0.94969916,0.039348796,0.0010423835,0.001375112,0.000032306703],"about_ca_topic_score_codex":0.0019769035,"about_ca_topic_score_gemma":0.0030637912,"teacher_disagreement_score":0.0019769035,"about_ca_system_score_codex":0.00028822862,"about_ca_system_score_gemma":0.00040582864,"threshold_uncertainty_score":0.003930807},"labels":[],"label_agreement":null},{"id":"W2162784822","doi":"10.1109/cdc.2001.980628","title":"Chatter suppression with adaptive control in turning metal via application of piezoactuator","year":2003,"lang":"en","type":"article","venue":"Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Machining; Nonlinear system; Control theory (sociology); Vibration; Displacement (psychology); Controller (irrigation); Adaptive control; Computer science; Engineering; Control engineering; Mechanical engineering; Control (management); Acoustics; Artificial intelligence; Physics","score_opus":0.006921864824238704,"score_gpt":0.2092889441681408,"score_spread":0.2023670793439021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162784822","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14699244,0.00069501094,0.8494345,0.000121926976,0.0000605288,0.000023432249,0.0000070981587,0.00034103397,0.002324081],"genre_scores_gemma":[0.9851849,0.00012564825,0.013930287,0.000024535912,0.0000135277705,0.000019202742,0.0000049128994,0.000006415315,0.000690539],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975735,0.00005872977,0.000012291402,0.00003859498,0.000112885915,0.000020229043],"domain_scores_gemma":[0.9997427,0.00012572952,0.000044902896,0.000020115303,0.000057825902,0.00000876868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033021945,0.00023879202,0.00025565494,0.00015400407,0.00013121097,0.00023986037,0.00043160372,0.00031192275,0.0002773939],"category_scores_gemma":[0.0007295596,0.00015083353,0.00020847381,0.0001354722,0.00041302227,0.00020570908,0.0003288362,0.0003256413,0.00005662069],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048261223,0.00010559014,0.0013222181,0.00031458103,0.000086865686,0.0005462974,0.00057542545,0.5855964,0.26484716,0.0139853805,0.0006663727,0.13147111],"study_design_scores_gemma":[0.000019936666,0.0002488268,0.0003776278,0.0000061381174,0.000012163479,0.00006392663,0.000013186572,0.98955256,0.008293631,0.0008492231,0.0005539696,0.000008837794],"about_ca_topic_score_codex":0.0016954674,"about_ca_topic_score_gemma":0.0011367119,"teacher_disagreement_score":0.0016954674,"about_ca_system_score_codex":0.00016310815,"about_ca_system_score_gemma":0.00018732047,"threshold_uncertainty_score":0.003371179},"labels":[],"label_agreement":null},{"id":"W2164310043","doi":"10.5539/mer.v2n1p29","title":"Influence of Hydraulic and Interference-fit Tool Holders on Tool Wear and Hole Quality in the Drilling of Al-Si Cylinder Heads","year":2012,"lang":"en","type":"article","venue":"Mechanical Engineering Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Drilling; Roundness (object); Mechanical engineering; Materials science; Tool wear; Surface roughness; Honing; Cylinder; Grinding; Surface finish; Interference (communication); Lubricant; Scanning electron microscope; Engineering drawing; Metallurgy; Composite material; Engineering","score_opus":0.058047215408994685,"score_gpt":0.3484536195892148,"score_spread":0.2904064041802201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164310043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971928,0.0002780723,0.0023506235,0.00000845825,0.000008690317,0.000009004945,0.000021914691,0.000025145837,0.00010529802],"genre_scores_gemma":[0.9976884,0.000069745176,0.0020440724,0.0000072270223,0.000005147915,0.0000038275834,0.000025330759,0.000011827559,0.0001443871],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99897397,0.0001869717,0.000094060655,0.00011830128,0.00049749546,0.00012911689],"domain_scores_gemma":[0.99579537,0.0021269,0.0009209907,0.00040872555,0.0006126678,0.0001354678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000917327,0.00033631286,0.00034419366,0.000288555,0.00019433336,0.00035334748,0.00031587027,0.00032312737,0.00042476208],"category_scores_gemma":[0.004536063,0.00028432757,0.00020906699,0.00016806633,0.00040097957,0.00036833057,0.00032280284,0.00018275113,0.000084312785],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012019131,0.00004725801,0.009669066,0.0002516595,0.000035020574,0.00027290874,0.00027023468,0.0017738087,0.97020257,0.000039614348,0.000058008067,0.016178008],"study_design_scores_gemma":[0.000040133396,0.0031301847,0.075188726,0.000014063287,0.00008857259,0.00074239465,0.00025180998,0.005673616,0.91387606,0.000028062123,0.0009252813,0.00004120709],"about_ca_topic_score_codex":0.0007011743,"about_ca_topic_score_gemma":0.0013916933,"teacher_disagreement_score":0.000917327,"about_ca_system_score_codex":0.0001901515,"about_ca_system_score_gemma":0.00018967454,"threshold_uncertainty_score":0.0048513412},"labels":[],"label_agreement":null},{"id":"W2165649889","doi":"10.1177/0954405414534827","title":"Milling burr formation, modeling and control: A review","year":2014,"lang":"en","type":"review","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Mechanical engineering; Residual stress; Manufacturing engineering; Process (computing); Surface finish; Quality (philosophy); Chip formation; Enhanced Data Rates for GSM Evolution; Engineering; Process engineering; Engineering drawing; Computer science; Tool wear; Materials science; Metallurgy","score_opus":0.012512175571418949,"score_gpt":0.2354059493207114,"score_spread":0.22289377374929245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165649889","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00059820653,0.99140793,0.006349141,0.00010460832,0.00013329428,0.000012184403,0.00003374009,0.00004971087,0.0013111449],"genre_scores_gemma":[0.00503529,0.98874414,0.0050801495,0.000057687717,0.00020721849,0.000021392143,0.000087012944,0.000011698107,0.0007554249],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996044,0.000042727574,0.000059049304,0.00008814446,0.00018115724,0.000024548905],"domain_scores_gemma":[0.99916863,0.00043488597,0.00012692691,0.000036626832,0.00020457622,0.000028317141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085859746,0.0014148686,0.0020409545,0.0022811508,0.00029755136,0.0014911586,0.0017826266,0.0013530647,0.002245455],"category_scores_gemma":[0.0012038334,0.0007808078,0.0009307496,0.0034490004,0.00051628257,0.0018518734,0.00057693414,0.00102504,0.0015246731],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006980452,0.00019515851,0.00048706343,0.023502342,0.0001345923,0.00016763911,0.00008345978,0.012443663,0.005279164,0.005931305,0.010797023,0.9409087],"study_design_scores_gemma":[0.000034346627,0.0006213907,0.0022069938,0.005765694,0.00052011915,0.0014540531,0.00016050151,0.015339983,0.007836246,0.0074011837,0.9584954,0.00016405404],"about_ca_topic_score_codex":0.0017501117,"about_ca_topic_score_gemma":0.0013857484,"teacher_disagreement_score":0.0022811508,"about_ca_system_score_codex":0.0004550295,"about_ca_system_score_gemma":0.0011424555,"threshold_uncertainty_score":0.0075117946},"labels":[],"label_agreement":null},{"id":"W2170265315","doi":"10.1179/030192304225018055","title":"Inclusion engineering of steel to prevent chemical tool wear","year":2004,"lang":"en","type":"article","venue":"Ironmaking & Steelmaking Processes Products and Applications","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Shear (geology); Softening; Shear zone; Materials science; Chip formation; Shear stress; Mechanics; Critical resolved shear stress; Dissolution; Metallurgy; Shear flow; Composite material; Shear rate; Geology; Engineering; Tool wear; Viscosity; Physics","score_opus":0.0056817078176337864,"score_gpt":0.2217078469411743,"score_spread":0.21602613912354052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170265315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.573528,0.0030636443,0.3348478,0.0005021966,0.0005480081,0.0002423848,0.0004066573,0.002047742,0.0848136],"genre_scores_gemma":[0.9173904,0.00076797453,0.056059264,0.00011447907,0.00002205431,0.00004856654,0.00024771615,0.00011388809,0.02523555],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996081,0.000028739056,0.0000159135,0.000038383605,0.00025586179,0.000052963613],"domain_scores_gemma":[0.9997003,0.0000216203,0.000049526705,0.000032559925,0.00017068155,0.000025318957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028688033,0.0005511122,0.000375573,0.00067153317,0.00047599358,0.0005030929,0.00066891266,0.00051368197,0.0021146284],"category_scores_gemma":[0.00045494345,0.00023656036,0.00036998815,0.000353941,0.0003314233,0.00030428445,0.00046606307,0.0003095817,0.0010193833],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001162576,0.00009571109,0.0012944618,0.0004597437,0.000031875123,0.00049622974,0.00019101615,0.03585011,0.89136535,0.0145173855,0.0022416601,0.053340234],"study_design_scores_gemma":[0.00007333648,0.0023548775,0.0073551093,0.00010369933,0.00010813816,0.00077451346,0.00018123795,0.2050117,0.6528147,0.007712684,0.123457424,0.00005252931],"about_ca_topic_score_codex":0.0022924042,"about_ca_topic_score_gemma":0.0056539113,"teacher_disagreement_score":0.0022924042,"about_ca_system_score_codex":0.0006190517,"about_ca_system_score_gemma":0.0006448089,"threshold_uncertainty_score":0.0070741177},"labels":[],"label_agreement":null},{"id":"W2170559401","doi":"10.1007/s00170-013-5310-5","title":"Force modeling and applications of inclined ball end milling of micro-dimpled surfaces","year":2013,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dimple; Materials science; Machining; Mechanical engineering; Ball (mathematics); Tribology; Fabrication; Molding (decorative); Surface micromachining; Engineering drawing; Composite material; Engineering; Metallurgy; Geometry","score_opus":0.005038171572938468,"score_gpt":0.22740552834970398,"score_spread":0.22236735677676553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170559401","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33619937,0.0006934561,0.6403176,0.00022789468,0.00011980561,0.0001001255,0.00009579039,0.0003916309,0.021854267],"genre_scores_gemma":[0.9702538,0.00020826796,0.02539495,0.000016016096,0.000011959143,0.000022685594,0.000040622497,0.000027131067,0.0040244632],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997937,0.00002402025,0.000007949152,0.000028242375,0.000120155564,0.00002589623],"domain_scores_gemma":[0.9997751,0.000077743985,0.000032562053,0.00003676069,0.00006138206,0.000016478729],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022030053,0.00038213158,0.000432428,0.0004164274,0.0004254429,0.0007611724,0.0010357862,0.0010873257,0.0016635957],"category_scores_gemma":[0.0006543707,0.0002769035,0.00043657067,0.00036963774,0.0005005181,0.00051668653,0.00042341606,0.00046976443,0.00028556748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006151703,0.0000617456,0.00076578854,0.000051315645,0.00001141484,0.0001561828,0.000084961204,0.949423,0.024016436,0.0038012606,0.0001798512,0.021386517],"study_design_scores_gemma":[0.0000019905222,0.00000926119,0.00017937686,0.0000013793626,9.1105983e-7,0.000009870546,0.000005897188,0.99836284,0.0010399497,0.00020668749,0.00017965231,0.0000021892615],"about_ca_topic_score_codex":0.005683622,"about_ca_topic_score_gemma":0.004675474,"teacher_disagreement_score":0.005683622,"about_ca_system_score_codex":0.00034639097,"about_ca_system_score_gemma":0.0005348562,"threshold_uncertainty_score":0.0113011},"labels":[],"label_agreement":null},{"id":"W2171495133","doi":"10.1115/1.4001251","title":"Analytical Chatter Stability of Milling With Rotating Cutter Dynamics at Process Damping Speeds","year":2010,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vibration; Control theory (sociology); Stability (learning theory); Time domain; Modal; LTI system theory; Nyquist stability criterion; Process (computing); Engineering; Mechanics; Mathematics; Mathematical analysis; Materials science; Physics; Computer science; Linear system; Acoustics","score_opus":0.005753431954724911,"score_gpt":0.2192288856239194,"score_spread":0.2134754536691945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171495133","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1749909,0.0004121884,0.81882644,0.00011344406,0.000023288567,0.000032024134,0.00004047527,0.00028811774,0.005273122],"genre_scores_gemma":[0.98392975,0.00011412836,0.013905318,0.000009729326,0.000006297254,0.000024328661,0.000020867295,0.000035146248,0.0019545127],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983513,0.00004713419,0.000005265924,0.00002451283,0.00007338041,0.000014468681],"domain_scores_gemma":[0.999188,0.00050682924,0.000078233665,0.000052371248,0.00015246405,0.000022115382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006674382,0.00040621473,0.00035710834,0.0003543301,0.00025174374,0.00049089297,0.0006367942,0.00042968066,0.0014233155],"category_scores_gemma":[0.002028693,0.0002246086,0.000390414,0.00014176089,0.00061799586,0.00046853907,0.00026545697,0.00047860737,0.00020724368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000114717266,0.00002436769,0.0011223658,0.00011404076,0.000023568722,0.00017942411,0.00027124677,0.9462593,0.022129813,0.017173236,0.0003652894,0.012222571],"study_design_scores_gemma":[9.634473e-7,0.000004624812,0.000067008106,0.0000014215316,8.349743e-7,0.0000045560905,0.0000029076755,0.99911064,0.00048653645,0.00028357128,0.00003542659,0.0000013910499],"about_ca_topic_score_codex":0.004121858,"about_ca_topic_score_gemma":0.002046957,"teacher_disagreement_score":0.004121858,"about_ca_system_score_codex":0.00059659884,"about_ca_system_score_gemma":0.0003796443,"threshold_uncertainty_score":0.008195758},"labels":[],"label_agreement":null},{"id":"W2172350318","doi":"10.1115/1.4032086","title":"An Accurate and Efficient Approach to Three-Dimensional Geometric Modeling of Undeformed Chips for the Geometric and the Physical Simulations of Three-Axis Milling of Complex Parts","year":2015,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Machining; Geometric modeling; Process (computing); Mechanical engineering; Geometric shape; Computer science; Work (physics); Engineering drawing; Geometry; Engineering; Mathematics","score_opus":0.044460910393810484,"score_gpt":0.2639391312460929,"score_spread":0.21947822085228244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172350318","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017653684,0.000045471734,0.9971775,0.000016295557,0.000007680875,0.000010570049,0.000031828476,0.0001742749,0.0007709404],"genre_scores_gemma":[0.1567281,0.00044458345,0.8400621,0.000058049103,0.000020593632,0.0001534827,0.00031052265,0.00022509242,0.0019974792],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994684,0.00006956497,0.000032330943,0.000056312812,0.00034200185,0.00003145611],"domain_scores_gemma":[0.9995888,0.000083584884,0.000052204923,0.00015372968,0.00010876912,0.000012958498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038701965,0.0006546021,0.0007156275,0.0006571202,0.00041312506,0.0011747293,0.0017998685,0.00090303714,0.0016627517],"category_scores_gemma":[0.0010056137,0.0006888342,0.00085436105,0.0006541394,0.00067964755,0.0011775836,0.0009959423,0.0011437061,0.00093331555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015958998,0.0000264996,0.00049745094,0.000095516494,0.000017481307,0.00012220847,0.00012000989,0.8874161,0.015235251,0.04859477,0.0010100934,0.046848584],"study_design_scores_gemma":[0.0000027367735,0.000011024529,0.00009656545,0.0000058048277,0.0000038102405,0.000054760014,0.000011214984,0.9878543,0.003303688,0.0046291333,0.0040172557,0.000009722101],"about_ca_topic_score_codex":0.002502863,"about_ca_topic_score_gemma":0.003058151,"teacher_disagreement_score":0.002502863,"about_ca_system_score_codex":0.0005390656,"about_ca_system_score_gemma":0.00093813345,"threshold_uncertainty_score":0.0055624843},"labels":[],"label_agreement":null},{"id":"W2173926673","doi":"10.1121/1.4934114","title":"Studying of the noise sources in a pneumatic nail-gun process","year":2015,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Noise (video); Acoustics; Nail (fastener); Accelerometer; Noise reduction; Process (computing); Vibration; Computer science; Automotive engineering; Engineering; Mechanical engineering; Physics","score_opus":0.014372897029105138,"score_gpt":0.25061274674969464,"score_spread":0.2362398497205895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2173926673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9772561,0.00017562648,0.021769328,0.00001522062,0.000009738745,0.000017003227,0.000030070256,0.000037331425,0.0006895692],"genre_scores_gemma":[0.9955869,0.00007745477,0.0036436587,0.0000058338464,0.0000032756889,0.000006431894,0.000034543096,0.000007296615,0.0006345815],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99978715,0.000024823614,0.000008222199,0.000056354787,0.000104891646,0.00001862207],"domain_scores_gemma":[0.9995945,0.00018761135,0.000058172074,0.0000250676,0.00011703807,0.000017612281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028371153,0.00022370541,0.00029878767,0.00031153433,0.00019631418,0.00021524023,0.00027130148,0.00030212308,0.0007183802],"category_scores_gemma":[0.0005943723,0.00013987675,0.0002256273,0.0002795993,0.00025154292,0.0003112321,0.00019082773,0.00019274378,0.00013482657],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052111945,0.00017170706,0.009291638,0.00022232518,0.0000236567,0.00045727496,0.00033860703,0.010283282,0.9470058,0.0002516369,0.00007051616,0.0313623],"study_design_scores_gemma":[0.000057811576,0.0027397939,0.17703713,0.000043563625,0.00011843187,0.00084761536,0.0010091085,0.12001252,0.6954839,0.00058753265,0.0019881602,0.00007438737],"about_ca_topic_score_codex":0.00090502435,"about_ca_topic_score_gemma":0.0011111753,"teacher_disagreement_score":0.00090502435,"about_ca_system_score_codex":0.00017729116,"about_ca_system_score_gemma":0.0001779349,"threshold_uncertainty_score":0.0024032593},"labels":[],"label_agreement":null},{"id":"W2173960222","doi":"10.1115/1.4032090","title":"An Accurate and Efficient Approach to Undeformed Chip Geometry in Face-Hobbing and Its Application in Cutting Force Prediction","year":2015,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Hobbing; Bevel; Face (sociological concept); Enhanced Data Rates for GSM Evolution; Chip; Geometry; Mechanical engineering; Process (computing); Machining; Kinematics; Computer science; Materials science; Structural engineering; Engineering; Mathematics; Artificial intelligence; Physics; Classical mechanics","score_opus":0.032432079563784175,"score_gpt":0.26699830946634945,"score_spread":0.23456622990256526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2173960222","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01416782,0.000066805944,0.9842858,0.000015798707,0.000009427758,0.000022890725,0.000041129228,0.00021404504,0.0011762608],"genre_scores_gemma":[0.60900086,0.0004267558,0.38742882,0.000037463025,0.000022252358,0.00011460482,0.00023131004,0.00019782854,0.0025400564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998073,0.000024985382,0.000009280287,0.000034958233,0.00010373006,0.000019768833],"domain_scores_gemma":[0.9996126,0.00013208418,0.000060722028,0.00006757398,0.00011370602,0.000013297948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025421602,0.0007292048,0.00066987827,0.0005306319,0.00028160203,0.00056919374,0.0010990074,0.0010635306,0.0016649305],"category_scores_gemma":[0.0009896227,0.00057218736,0.0005329016,0.00039224944,0.0004991014,0.00059460883,0.00040685185,0.00073995686,0.00059042365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011766602,0.000026590596,0.0008604888,0.000066466884,0.0000068113254,0.00014313265,0.0000627483,0.9428338,0.012948642,0.0034321202,0.00032142713,0.03928612],"study_design_scores_gemma":[7.7218516e-7,0.0000064219016,0.00017048426,0.0000033003755,0.0000011290394,0.000026715163,0.000006043079,0.99781656,0.0013616952,0.00038934793,0.00021369552,0.000003822818],"about_ca_topic_score_codex":0.004400184,"about_ca_topic_score_gemma":0.0048236265,"teacher_disagreement_score":0.004400184,"about_ca_system_score_codex":0.00037448294,"about_ca_system_score_gemma":0.0009702053,"threshold_uncertainty_score":0.008749187},"labels":[],"label_agreement":null},{"id":"W2176185364","doi":"10.1177/0954405415599946","title":"Minimal quantity cooling lubrication in turning of Ti6Al4V: Influence on surface roughness, cutting force and tool wear","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"National Research Foundation","keywords":"Machinability; Lubrication; Coolant; Machining; Materials science; Surface roughness; Tool wear; Titanium alloy; Surface finish; Metallurgy; Cutting fluid; Cutting tool; Mechanical engineering; Composite material; Alloy; Engineering","score_opus":0.009984223438474594,"score_gpt":0.21787647209689626,"score_spread":0.20789224865842165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2176185364","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99889046,0.00038902613,0.0005299403,0.000008902052,0.000006740365,0.0000035347937,0.000011782949,0.00001199109,0.00014763963],"genre_scores_gemma":[0.99935657,0.00011445424,0.000348795,0.0000036151769,0.0000019794616,0.0000018446037,0.000013333089,0.000005184496,0.00015415138],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997589,0.000046486886,0.00001759124,0.000029870445,0.00009325915,0.00005383766],"domain_scores_gemma":[0.9996136,0.00015957834,0.0000911996,0.000023945553,0.000083612555,0.000028118484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002578493,0.00019435413,0.0003010638,0.00027307263,0.00017146493,0.00032768206,0.00023636645,0.00022651427,0.0005596664],"category_scores_gemma":[0.00066143356,0.00012905116,0.0001869579,0.00016862767,0.00028090243,0.0002464945,0.00016329116,0.00016529966,0.00008581543],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00124585,0.000064394546,0.002290913,0.00025946126,0.000018514613,0.000111922025,0.00012330951,0.0014374033,0.9848295,0.00007669624,0.00006100539,0.009480943],"study_design_scores_gemma":[0.000023134955,0.002397756,0.010372359,0.000012028795,0.00004675284,0.00014012984,0.00012523324,0.0063727885,0.9796225,0.000029187591,0.0008442532,0.000014071471],"about_ca_topic_score_codex":0.0009104316,"about_ca_topic_score_gemma":0.0018375848,"teacher_disagreement_score":0.0009104316,"about_ca_system_score_codex":0.00019111925,"about_ca_system_score_gemma":0.0001232457,"threshold_uncertainty_score":0.0018722415},"labels":[],"label_agreement":null},{"id":"W2184368175","doi":"","title":"Experimental Investigation of Cutting Fluid Influence on Drilled Aluminum Part Quality","year":2012,"lang":"en","type":"article","venue":"Espace ÉTS (ETS)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Mist; Drilling; Factorial experiment; Cutting fluid; Metallurgy; Petroleum engineering; Design of experiments; Aluminium; Mechanical engineering; Quality (philosophy); Materials science; Engineering; Mathematics; Statistics","score_opus":0.01723735515752712,"score_gpt":0.2802452024278234,"score_spread":0.2630078472702963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184368175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99476826,0.00027682062,0.00459381,0.000008472689,0.000011094873,0.000036606467,0.00008049057,0.000026747633,0.00019767485],"genre_scores_gemma":[0.99345607,0.00021972258,0.005813941,0.000008840913,0.0000055791606,0.000028626266,0.00007644131,0.000015815833,0.00037494654],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99928635,0.00012648723,0.00007126839,0.000120556346,0.00031420687,0.000081122394],"domain_scores_gemma":[0.99776983,0.0010712221,0.0004533522,0.00017653123,0.00046103567,0.000068168694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006775166,0.0004991219,0.000576217,0.0002579695,0.00025957936,0.00030474228,0.00032393486,0.0005398657,0.0012703564],"category_scores_gemma":[0.0019110505,0.0002631821,0.00035970594,0.00026525432,0.00045487125,0.00038425782,0.00028222936,0.000446202,0.00014173386],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000557762,0.000089053814,0.0007425509,0.00017767951,0.000012696601,0.000058090955,0.000083977575,0.00066789915,0.99480975,0.000016805063,0.000011699446,0.0027720372],"study_design_scores_gemma":[0.000025059555,0.003220945,0.004872553,0.000004914934,0.00003704512,0.00006761693,0.00005429532,0.0011650537,0.9902018,0.0000152080165,0.00031861017,0.000016846521],"about_ca_topic_score_codex":0.0004987481,"about_ca_topic_score_gemma":0.0007691082,"teacher_disagreement_score":0.0012703564,"about_ca_system_score_codex":0.00024520693,"about_ca_system_score_gemma":0.00023510668,"threshold_uncertainty_score":0.0042497516},"labels":[],"label_agreement":null},{"id":"W2189341647","doi":"10.11575/prism/25669","title":"Development of an Optical System for High Precision Multi-Axis Force Measurements","year":2015,"lang":"en","type":"dissertation","venue":"PRISM (University of Calgary)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Optics; Computer science; Physics","score_opus":0.022763924905765225,"score_gpt":0.2392342538588917,"score_spread":0.21647032895312646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2189341647","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0469992,0.0014327485,0.9283074,0.00076060416,0.0007874014,0.0014386346,0.0006241053,0.0040298244,0.015620006],"genre_scores_gemma":[0.109854825,0.00072850345,0.88081676,0.0003045056,0.00008913337,0.0006751114,0.0003507031,0.00013681142,0.0070435936],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99839514,0.00007440741,0.000058923786,0.00023832408,0.0011481361,0.000085068365],"domain_scores_gemma":[0.99850625,0.00020310863,0.0001518652,0.00017600332,0.00087380596,0.000088891495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015589893,0.00051797135,0.00056050316,0.0008881887,0.00067427434,0.0008957654,0.0013158257,0.0010159928,0.00391305],"category_scores_gemma":[0.0014513534,0.00064325694,0.000293372,0.00093623594,0.0004955891,0.0013890371,0.0007263712,0.0011368922,0.001523684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011080925,0.00020876603,0.0010757043,0.0004541598,0.000026675198,0.000104557315,0.00012739164,0.0019886608,0.8225997,0.009799861,0.0041877828,0.15931594],"study_design_scores_gemma":[0.00011554404,0.0008993479,0.0056025516,0.00010709532,0.000054530024,0.00081648567,0.00007462048,0.039053302,0.85296685,0.0013920708,0.09877846,0.00013917906],"about_ca_topic_score_codex":0.0015199764,"about_ca_topic_score_gemma":0.0030241478,"teacher_disagreement_score":0.00391305,"about_ca_system_score_codex":0.0011713521,"about_ca_system_score_gemma":0.0025939494,"threshold_uncertainty_score":0.013090432},"labels":[],"label_agreement":null},{"id":"W2194460072","doi":"10.1007/s00170-015-8001-6","title":"Machining strategy development and parameter selection in 5-axis milling based on process simulations","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Pratt and Whitney Canada","keywords":"Machining; Mechanical engineering; Surface roughness; Machine tool; Engineering; Deflection (physics); Process (computing); Computer science; Materials science","score_opus":0.015398603761546835,"score_gpt":0.27153759110345504,"score_spread":0.2561389873419082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2194460072","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5820329,0.00051382295,0.39723694,0.00016191404,0.00005231902,0.00023210261,0.00018633914,0.0007285735,0.01885503],"genre_scores_gemma":[0.961953,0.000105765685,0.036773454,0.000016004757,0.000003580092,0.00007995262,0.00007662565,0.000051430434,0.0009402003],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984455,0.000045043827,0.000010423735,0.000020727759,0.000055694476,0.000023647588],"domain_scores_gemma":[0.99931836,0.00046007667,0.00006600335,0.000034112072,0.00010456347,0.00001683685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055382546,0.00058800937,0.000639707,0.00056301086,0.00039313312,0.0007451845,0.0006555127,0.0008819237,0.0017525327],"category_scores_gemma":[0.0013091081,0.00048942934,0.0005276755,0.0004451957,0.00027303022,0.0006124294,0.00031671367,0.00041373118,0.00019373579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003562142,0.000035852216,0.0005031538,0.00003295241,0.000007336748,0.000024202347,0.000026638885,0.9911567,0.0018107119,0.00055171346,0.000059283568,0.0057558115],"study_design_scores_gemma":[0.0000034528002,0.000011149805,0.00010182396,0.0000017732859,0.0000026049088,0.000002380076,0.00000418628,0.9992198,0.00050658995,0.00007659478,0.00006777106,0.0000018246501],"about_ca_topic_score_codex":0.0063704816,"about_ca_topic_score_gemma":0.0054133506,"teacher_disagreement_score":0.0063704816,"about_ca_system_score_codex":0.0005774929,"about_ca_system_score_gemma":0.0007815902,"threshold_uncertainty_score":0.0126668215},"labels":[],"label_agreement":null},{"id":"W2198770372","doi":"10.1016/b978-1-78242-307-2.00009-9","title":"Machining and drilling processes in composites manufacture","year":2015,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Machining; Materials science; Characterization (materials science); Composite number; Drilling; Mechanical engineering; Composite material; Engineering; Metallurgy; Nanotechnology","score_opus":0.012929221672122735,"score_gpt":0.2271992732596177,"score_spread":0.21427005158749496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2198770372","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008031768,0.19305214,0.20148224,0.0010279745,0.0029113682,0.00009148441,0.00021534083,0.0007263381,0.59246135],"genre_scores_gemma":[0.06204383,0.117929146,0.09630977,0.0002912897,0.0012834923,0.00010647605,0.00035844164,0.00033199246,0.72134554],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99977213,0.000021235479,0.000009942746,0.00003436372,0.00014996636,0.000012512264],"domain_scores_gemma":[0.9999231,0.000037455437,0.000005343926,0.000011234991,0.00001855999,0.0000042190445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019409781,0.0009570865,0.0006458283,0.00082271826,0.00036200738,0.0012706497,0.00087539305,0.0010618845,0.017456276],"category_scores_gemma":[0.00025717655,0.0004796208,0.00042624425,0.0015678521,0.00067234004,0.001557568,0.00071549666,0.0012922751,0.005862308],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005554074,0.000097698634,0.00015650701,0.0014930252,0.00001746739,0.00012684142,0.00017173841,0.022181652,0.015219488,0.13064654,0.032567404,0.7972661],"study_design_scores_gemma":[0.000013375182,0.00010567556,0.0011905872,0.00066099147,0.000024224892,0.00042089325,0.00010435996,0.022322942,0.009415585,0.10699626,0.8587104,0.00003472969],"about_ca_topic_score_codex":0.001048276,"about_ca_topic_score_gemma":0.00240582,"teacher_disagreement_score":0.017456276,"about_ca_system_score_codex":0.0005677406,"about_ca_system_score_gemma":0.00045607303,"threshold_uncertainty_score":0.058396995},"labels":[],"label_agreement":null},{"id":"W2198954693","doi":"10.1155/2016/4390185","title":"Effects of Machine Tool Spindle Decay on the Stability Lobe Diagram: An Analytical-Experimental Study","year":2015,"lang":"en","type":"article","venue":"Shock and Vibration","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machine tool; Natural frequency; Vibration; Machining; Stiffness; Stability (learning theory); Finite element method; Modal analysis; Engineering; Structural engineering; Boundary (topology); Modal; Diagram; Control theory (sociology); Mechanical engineering; Computer science; Acoustics; Physics; Mathematical analysis; Materials science; Mathematics","score_opus":0.020997155910658725,"score_gpt":0.27656552287185177,"score_spread":0.25556836696119306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2198954693","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98141104,0.00016534755,0.017201612,0.000031917032,0.000014275487,0.00004165276,0.00011031784,0.00015552415,0.00086828653],"genre_scores_gemma":[0.99813384,0.000036637608,0.0014550452,0.000006079591,0.000001703015,0.000013697918,0.00003568573,0.000016112761,0.00030118643],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991371,0.000121381476,0.00005853269,0.00017428763,0.0003868529,0.000121865036],"domain_scores_gemma":[0.9957949,0.0021335848,0.00052731717,0.00052961434,0.0008862105,0.00012846514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012495404,0.00039439887,0.0005192804,0.0004359037,0.0003651978,0.00037650004,0.0005345973,0.0005452998,0.0020246482],"category_scores_gemma":[0.004442361,0.0003080316,0.00032327647,0.00043842406,0.00083145016,0.0004609821,0.0004981072,0.00062910054,0.00035101522],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00209157,0.0005259282,0.006346883,0.00043517112,0.000017249538,0.00042839232,0.0010506584,0.013497272,0.9457925,0.0005204448,0.00029984754,0.028994141],"study_design_scores_gemma":[0.000062846586,0.0052110893,0.033890486,0.000054456865,0.000036342193,0.00044811386,0.00043733852,0.10815949,0.84938234,0.0002672247,0.0019849357,0.00006533053],"about_ca_topic_score_codex":0.0006703882,"about_ca_topic_score_gemma":0.00083301717,"teacher_disagreement_score":0.0020246482,"about_ca_system_score_codex":0.00032682501,"about_ca_system_score_gemma":0.00020793761,"threshold_uncertainty_score":0.006773114},"labels":[],"label_agreement":null},{"id":"W2204137982","doi":"","title":"Solid modeller-based geometric simulation for form grinding processes","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Grinding; MODELLER; Geometric modeling; Mechanical engineering; Engineering drawing; Computer science; Engineering; Physics","score_opus":0.02193459790836867,"score_gpt":0.3130790783211765,"score_spread":0.2911444804128078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2204137982","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029950507,0.000085854124,0.95419466,0.00009361832,0.00005502797,0.00012732261,0.000542035,0.0034200149,0.011530966],"genre_scores_gemma":[0.46335995,0.00037754784,0.5198832,0.00006642416,0.000025179374,0.0006683333,0.0018966103,0.001411137,0.012311564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997198,0.000057675767,0.000014451885,0.000027121432,0.00016026363,0.000020659361],"domain_scores_gemma":[0.9996532,0.00016574332,0.000024209145,0.000052760162,0.00008900684,0.000015093453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003959311,0.00063036656,0.0006285992,0.00038888288,0.00039059977,0.0005789693,0.0011758808,0.00076217117,0.009250193],"category_scores_gemma":[0.0009361895,0.00038264392,0.000734282,0.00037496377,0.00036959985,0.0006138263,0.0004813119,0.0007140141,0.0013824491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040114643,0.000030329194,0.00037044316,0.00006465238,0.000017010687,0.00006464732,0.00007155172,0.96318924,0.007651041,0.014203484,0.0012089574,0.013088569],"study_design_scores_gemma":[0.000012457594,0.000014556753,0.00005485834,0.0000036985068,0.0000032550897,0.000018247378,0.0000049572454,0.99097764,0.0035377583,0.001093895,0.004273167,0.0000054706434],"about_ca_topic_score_codex":0.003925593,"about_ca_topic_score_gemma":0.003919045,"teacher_disagreement_score":0.009250193,"about_ca_system_score_codex":0.0006082843,"about_ca_system_score_gemma":0.0009881152,"threshold_uncertainty_score":0.030945003},"labels":[],"label_agreement":null},{"id":"W2204467167","doi":"10.4271/2000-01-1694","title":"Increasing Productivity in 5-Axis Milling of IBR's Using Force Modeling and Control","year":2000,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Pratt and Whitney Canada","keywords":"Productivity; Control (management); Computer science; Control theory (sociology); Artificial intelligence; Economics","score_opus":0.009323163272128248,"score_gpt":0.23152519997740942,"score_spread":0.22220203670528116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2204467167","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39731795,0.0010167139,0.5894717,0.00024632414,0.00004255801,0.000072966424,0.00011003708,0.0013818147,0.010339852],"genre_scores_gemma":[0.9276753,0.0004483568,0.06948544,0.000021625145,0.000010373514,0.000025642832,0.00011435339,0.00005656311,0.0021623247],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975485,0.000048045942,0.000015216542,0.000039497627,0.000117211785,0.00002524037],"domain_scores_gemma":[0.9997627,0.00008797835,0.000053704076,0.000035865323,0.0000504634,0.000009330883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064150355,0.00058693177,0.0003585216,0.00033361668,0.00022417813,0.0005385746,0.00039576815,0.00037048108,0.0013701617],"category_scores_gemma":[0.00078913174,0.00019540919,0.00031559603,0.00040757796,0.00020739173,0.00048779152,0.00026671324,0.00020697805,0.00041291284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040811393,0.00021183316,0.003158854,0.0002967917,0.000025243658,0.00012022754,0.00014152181,0.52260864,0.15271291,0.0028521216,0.0012470922,0.31621668],"study_design_scores_gemma":[0.00002610153,0.00024437092,0.0024253642,0.000011291486,0.000013767742,0.000036189547,0.00002126983,0.9676002,0.027415635,0.0006386769,0.0015556348,0.000011595879],"about_ca_topic_score_codex":0.003380482,"about_ca_topic_score_gemma":0.0035912967,"teacher_disagreement_score":0.003380482,"about_ca_system_score_codex":0.0003790254,"about_ca_system_score_gemma":0.00033397248,"threshold_uncertainty_score":0.006721616},"labels":[],"label_agreement":null},{"id":"W2205198338","doi":"10.1016/j.promfg.2015.09.059","title":"Investigation of Boring Bar Dynamics for Chatter Suppression","year":2015,"lang":"en","type":"article","venue":"Procedia Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Qassim University","keywords":"Natural frequency; Bar (unit); Cantilever; Vibration; Engineering; Finite element method; Modal analysis; Structural engineering; Modal; Stiffness; Frequency response; Machining; Actuator; Mechanical engineering; Acoustics; Materials science; Geology; Physics","score_opus":0.022241249111069176,"score_gpt":0.23373791607547711,"score_spread":0.21149666696440794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2205198338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52619416,0.00040859624,0.46845832,0.00009252845,0.00003239933,0.00006592529,0.00003688718,0.0004401013,0.0042710463],"genre_scores_gemma":[0.98302644,0.00007122638,0.016214892,0.000005180359,0.0000029368991,0.000015157265,0.000013343076,0.000011824173,0.00063902047],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99984217,0.000027710354,0.000006384526,0.000029648036,0.00008291052,0.000011091548],"domain_scores_gemma":[0.9993243,0.00038458803,0.00007693041,0.000048319456,0.00014211606,0.000023750203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003331825,0.00027162192,0.0002782211,0.00024917693,0.0001643062,0.0002081308,0.00031418056,0.00028426768,0.0010538719],"category_scores_gemma":[0.0009398149,0.000121544326,0.00020460656,0.0001203307,0.0002649043,0.00025995285,0.0002073567,0.00024072616,0.00013205444],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039224455,0.00010228486,0.0036370675,0.0005286272,0.000039509385,0.00034467588,0.0008820513,0.08284988,0.8261713,0.004876758,0.0003186214,0.079857],"study_design_scores_gemma":[0.000009302357,0.00015867827,0.0022158502,0.000011903242,0.000010195676,0.00008863857,0.000046148776,0.93001646,0.06664088,0.00028855697,0.00050200504,0.0000115266475],"about_ca_topic_score_codex":0.0006615739,"about_ca_topic_score_gemma":0.000586901,"teacher_disagreement_score":0.0010538719,"about_ca_system_score_codex":0.00014362055,"about_ca_system_score_gemma":0.00017196429,"threshold_uncertainty_score":0.0035255551},"labels":[],"label_agreement":null},{"id":"W2224136207","doi":"10.1016/j.jcde.2015.12.001","title":"Cutter-workpiece engagement determination for general milling using triangle mesh modeling","year":2015,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Milling cutter; Process (computing); Intersection (aeronautics); Tool path; Mechanical engineering; Engineering; Polygon mesh; Engineering drawing; Path (computing); Series (stratigraphy); Cutter location; Geometry; Boundary (topology); Structural engineering; Computer science; Mathematics; Mathematical analysis","score_opus":0.06579461531457148,"score_gpt":0.2805356526886614,"score_spread":0.2147410373740899,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2224136207","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04835505,0.00007386277,0.94675785,0.000032846627,0.000013514868,0.000058519883,0.00008118601,0.00032024155,0.0043070097],"genre_scores_gemma":[0.6979287,0.00011230075,0.29955724,0.000017204544,0.000007800504,0.00009895406,0.00027358177,0.00016263982,0.0018414267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995813,0.000087842665,0.00002858685,0.00006502326,0.00019886722,0.00003834562],"domain_scores_gemma":[0.99925166,0.000409148,0.00006751891,0.00009702087,0.00015185298,0.000022728307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005907045,0.0005628011,0.000641032,0.00073975587,0.00027680927,0.00078522286,0.0009503953,0.000770106,0.0026169815],"category_scores_gemma":[0.001739314,0.00024325606,0.00071004895,0.00055744767,0.00033760894,0.0006298468,0.0007520209,0.000506416,0.00034060157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000098465374,0.00007250909,0.0024851908,0.00018025417,0.000022400123,0.00021294154,0.0001261649,0.9056173,0.015436693,0.009543045,0.00052863563,0.065676436],"study_design_scores_gemma":[0.0000022380789,0.000009428021,0.00012316745,0.000003042832,0.0000017638293,0.000012771718,0.000008767549,0.9975224,0.0012715049,0.00070154504,0.0003409989,0.0000024589842],"about_ca_topic_score_codex":0.0040137307,"about_ca_topic_score_gemma":0.0032036921,"teacher_disagreement_score":0.0040137307,"about_ca_system_score_codex":0.00048725551,"about_ca_system_score_gemma":0.0005931539,"threshold_uncertainty_score":0.008754671},"labels":[],"label_agreement":null},{"id":"W2226437371","doi":"10.3390/s16010070","title":"Design and Analysis of a Sensor System for Cutting Force Measurement in Machining Processes","year":2016,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Changsha Science and Technology Project; State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body; Natural Science Foundation of Hunan Province; National Natural Science Foundation of China","keywords":"Machining; Calibration; Finite element method; Mechanical engineering; Coupling (piping); Machine tool; Component (thermodynamics); Automation; Kinematics; Engineering; System of measurement; Structural engineering; Physics","score_opus":0.021591741134154043,"score_gpt":0.23352843524359418,"score_spread":0.21193669410944013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2226437371","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07698501,0.00052815763,0.9180911,0.0001585871,0.00005757114,0.00021789702,0.00007265718,0.00067723583,0.0032116924],"genre_scores_gemma":[0.7827536,0.00035573135,0.21357048,0.00008495055,0.00003225328,0.00019275659,0.00010933936,0.00003152925,0.002869416],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99951434,0.000051839965,0.00002111141,0.00009230578,0.0002919233,0.000028544508],"domain_scores_gemma":[0.9997453,0.000053001808,0.000047882506,0.000025699734,0.00011258836,0.000015434278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039925936,0.00037893598,0.00041170107,0.00024981992,0.00022613835,0.0003753475,0.00076192786,0.00061157136,0.0010492636],"category_scores_gemma":[0.00041729547,0.00024808245,0.00025663988,0.00018329667,0.00024705048,0.00053842657,0.00022172778,0.00026991373,0.0002702701],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029342165,0.00011404159,0.0022595155,0.00055531936,0.0000743289,0.00025335304,0.00017253235,0.078189306,0.796884,0.006811846,0.00090296404,0.11348945],"study_design_scores_gemma":[0.00004838775,0.0011407671,0.0065711546,0.000029181727,0.000074812946,0.0004496791,0.00006347331,0.6072965,0.3701601,0.00088042766,0.013235205,0.000050287334],"about_ca_topic_score_codex":0.00069086335,"about_ca_topic_score_gemma":0.00080747704,"teacher_disagreement_score":0.0010492636,"about_ca_system_score_codex":0.000428385,"about_ca_system_score_gemma":0.0006928579,"threshold_uncertainty_score":0.0035101175},"labels":[],"label_agreement":null},{"id":"W2233388212","doi":"10.5267/j.ijiec.2015.10.004","title":"Analysis of surface roughness and cutting force during turning of Ti6Al4V ELI in dry environment","year":2015,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Surface roughness; Metallurgy; Mechanical engineering; Surface finish; Materials science; Engineering; Composite material","score_opus":0.016777873710895213,"score_gpt":0.24810574344433164,"score_spread":0.23132786973343644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2233388212","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99603516,0.0003155254,0.0030413992,0.000016012378,0.00001029236,0.0000069516177,0.000073141615,0.000026330505,0.00047509154],"genre_scores_gemma":[0.99699867,0.00014538762,0.0020830007,0.000010116588,0.000003687201,0.000007056006,0.00015648769,0.000013290346,0.0005822391],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996086,0.000024080708,0.000012343651,0.00005473089,0.00023171544,0.00006845904],"domain_scores_gemma":[0.999691,0.00010290663,0.00006065409,0.000023136281,0.000103288316,0.000018939261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023571654,0.00019614767,0.0003635729,0.00036959,0.00019419464,0.00025952962,0.0001967253,0.00031176695,0.000618952],"category_scores_gemma":[0.00039190878,0.0001715246,0.00044851564,0.00022822534,0.0002071194,0.00017823119,0.0001182233,0.00030371983,0.00014764236],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022148337,0.000026419539,0.0026929602,0.00009472667,0.00001182838,0.000094236326,0.0001218151,0.0008270319,0.9888758,0.000027907789,0.0000649034,0.0069409213],"study_design_scores_gemma":[0.000015951113,0.0014766881,0.10858191,0.000011265151,0.000070918206,0.00036421884,0.00040526147,0.011345394,0.87624115,0.00007021067,0.0013687643,0.000048208676],"about_ca_topic_score_codex":0.0010511837,"about_ca_topic_score_gemma":0.0022645548,"teacher_disagreement_score":0.0010511837,"about_ca_system_score_codex":0.00018487973,"about_ca_system_score_gemma":0.00009122889,"threshold_uncertainty_score":0.002090156},"labels":[],"label_agreement":null},{"id":"W2243483411","doi":"10.1139/tcsme-2007-0020","title":"EFFECT OF WHEEL WEAR ON CONTACT LENGTH, UNCUT CHIP THICKNESS AND FORCES FOR A DEFORMABLE GRINDING WHEEL AND WORKPIECE","year":2007,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Grinding; Materials science; Enhanced Data Rates for GSM Evolution; Chip; Chip formation; Grinding wheel; Normal force; Composite material; Contact area; Dynamometer; Work (physics); Volume (thermodynamics); Mechanics; Mechanical engineering; Machining; Tool wear; Metallurgy; Engineering; Physics; Electrical engineering","score_opus":0.004922504940285437,"score_gpt":0.21046057614773686,"score_spread":0.20553807120745143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2243483411","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978313,0.0002301667,0.0017622283,0.0000066478337,0.000010479407,0.0000083359855,0.00002469744,0.000020154463,0.00010609485],"genre_scores_gemma":[0.99704,0.00009884933,0.0023608168,0.000011298947,0.0000034237228,0.0000067045257,0.000046989062,0.0000134942375,0.00041834588],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99933064,0.000053802076,0.000048020887,0.0001280789,0.00033734334,0.000102113205],"domain_scores_gemma":[0.9972133,0.0014864618,0.00039150898,0.00036982863,0.00042174698,0.000117202944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061765435,0.00033313615,0.00048634975,0.00036436386,0.00032995606,0.00032441606,0.00040404926,0.00038702795,0.0010792849],"category_scores_gemma":[0.0024535402,0.00027829723,0.00039670433,0.00020186827,0.00037186104,0.00032584532,0.00027183772,0.00027224855,0.00013607994],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009032401,0.00010942649,0.010199408,0.000233774,0.000036413127,0.00021159416,0.000298786,0.0018600675,0.96455806,0.00003322638,0.00005751054,0.021498486],"study_design_scores_gemma":[0.00003390767,0.0023008704,0.20160905,0.000020944648,0.00008315612,0.00030970707,0.00043907666,0.014052015,0.77982116,0.00005409457,0.001223996,0.00005193489],"about_ca_topic_score_codex":0.0023579698,"about_ca_topic_score_gemma":0.0068341973,"teacher_disagreement_score":0.0023579698,"about_ca_system_score_codex":0.00037321256,"about_ca_system_score_gemma":0.00024203844,"threshold_uncertainty_score":0.0046884418},"labels":[],"label_agreement":null},{"id":"W2243697171","doi":"10.4028/www.scientific.net/amr.1136.3","title":"Deep Profiled Slot Grinding on a Nickel-Based Alloy with Electroplated CBN Wheels","year":2016,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Grinding; Materials science; Electroplating; Grinding wheel; Broaching; Metallurgy; Alloy; Boron nitride; Grind; Head (geology); Mechanical engineering; Composite material; Engineering; Layer (electronics); Geology","score_opus":0.01937899942515432,"score_gpt":0.2987370439967735,"score_spread":0.27935804457161917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2243697171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96286434,0.00044843517,0.033217136,0.0000224798,0.00004926729,0.000054639702,0.00012624821,0.00033570966,0.0028818322],"genre_scores_gemma":[0.92745274,0.00018801712,0.067669585,0.000013096395,0.00000479869,0.000018895966,0.00017364413,0.000057418918,0.0044218767],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997999,0.000006307128,0.000009012024,0.000034380442,0.00012739151,0.000022904169],"domain_scores_gemma":[0.99982613,0.000019397932,0.00004458341,0.000035715435,0.00005460296,0.000019563968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018182141,0.00019385165,0.00025167776,0.00022874014,0.00012066723,0.00017199841,0.00032981831,0.00016485121,0.00052966626],"category_scores_gemma":[0.00024491208,0.00021700497,0.00012518105,0.00017478465,0.00019778701,0.00012946245,0.00017350145,0.00027979238,0.00033299896],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003586915,0.000009001724,0.00037929424,0.00003507321,0.0000013969164,0.000044981454,0.00003171421,0.00040187925,0.99346113,0.00008742739,0.00005879026,0.005453366],"study_design_scores_gemma":[0.000015449286,0.00048640883,0.020439092,0.000011575129,0.000009725935,0.00034695963,0.00004111202,0.0060348953,0.96553546,0.000061159015,0.00700205,0.000016099224],"about_ca_topic_score_codex":0.0016448159,"about_ca_topic_score_gemma":0.009817721,"teacher_disagreement_score":0.0016448159,"about_ca_system_score_codex":0.0003192547,"about_ca_system_score_gemma":0.00031025475,"threshold_uncertainty_score":0.0032704473},"labels":[],"label_agreement":null},{"id":"W2258115337","doi":"10.1139/tcsme-2005-0023","title":"DEVELOPMENT OF AN EXPERIMENTAL TECHNIQUE TO MODEL DEFLECTIONS IN SURFACE GRINDING","year":2005,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Grinding; Mechanical engineering; Nonlinear system; Backlash; Materials science; Machine tool; Power (physics); Surface integrity; Mechanics; Structural engineering; Machining; Engineering; Physics","score_opus":0.013566248176411388,"score_gpt":0.2444353349566518,"score_spread":0.2308690867802404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2258115337","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1477926,0.00014541732,0.84618723,0.000117027215,0.00011821104,0.00051595573,0.00037242743,0.00135462,0.0033964196],"genre_scores_gemma":[0.6844112,0.00025438538,0.31256124,0.0000635733,0.000024997438,0.0008610187,0.00035130733,0.00012900934,0.0013432568],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990055,0.00010982364,0.00005220726,0.00020964937,0.00055620074,0.00006675379],"domain_scores_gemma":[0.9975923,0.00092561526,0.000266057,0.00058924855,0.0005725813,0.00005417166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014323723,0.0005756066,0.00033381395,0.00040811647,0.000524153,0.0005157676,0.0013297949,0.000891103,0.0022186316],"category_scores_gemma":[0.00379091,0.00043336395,0.00033816314,0.0004559161,0.0007065227,0.0009090521,0.0006017479,0.0012524882,0.0004953296],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023665186,0.00049542944,0.0042441483,0.00027946354,0.000025238218,0.00014813886,0.00027793628,0.08597213,0.82590216,0.0064160735,0.00048795485,0.07551477],"study_design_scores_gemma":[0.00010515472,0.0014930962,0.0069099255,0.00003052645,0.00003069618,0.0001475754,0.00008469039,0.43800482,0.544002,0.0026293572,0.0064924257,0.00006971147],"about_ca_topic_score_codex":0.0019071348,"about_ca_topic_score_gemma":0.0021384503,"teacher_disagreement_score":0.0022186316,"about_ca_system_score_codex":0.00063103985,"about_ca_system_score_gemma":0.0008167649,"threshold_uncertainty_score":0.007575214},"labels":[],"label_agreement":null},{"id":"W2258557027","doi":"10.4271/2004-01-1245","title":"High-Performance Machining Automation","year":2004,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Automation; Machining; Computer science; Manufacturing engineering; Engineering; Mechanical engineering","score_opus":0.006343955684572088,"score_gpt":0.22286732091417216,"score_spread":0.21652336522960008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2258557027","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013859542,0.0022718436,0.7018595,0.00046983053,0.00048255268,0.0003603783,0.0011433329,0.031240663,0.24831244],"genre_scores_gemma":[0.3675388,0.002425299,0.4094127,0.00049564784,0.00044317057,0.00031772896,0.0062438366,0.0014123261,0.21171045],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99860615,0.000100871155,0.000060815313,0.00019580864,0.0009175306,0.00011879986],"domain_scores_gemma":[0.9992779,0.00010839755,0.000032712396,0.00025242014,0.00029581145,0.00003271555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052459637,0.000702402,0.0004157771,0.0010598525,0.00049082533,0.0015307283,0.0013621314,0.0006632841,0.03378743],"category_scores_gemma":[0.000735241,0.00028311412,0.00036200535,0.0013460976,0.0003076656,0.0010568892,0.0009824005,0.0007457482,0.019900113],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013594258,0.00011404145,0.0011157241,0.0003648956,0.00002793339,0.00017637703,0.000113531656,0.007118333,0.080286756,0.02073409,0.062596925,0.8272155],"study_design_scores_gemma":[0.000086281485,0.00032797313,0.0050163167,0.00009345184,0.000030765812,0.0010122391,0.000059435602,0.11096823,0.11943806,0.0122167375,0.75067765,0.00007292627],"about_ca_topic_score_codex":0.0015999221,"about_ca_topic_score_gemma":0.0015368996,"teacher_disagreement_score":0.03378743,"about_ca_system_score_codex":0.0005000565,"about_ca_system_score_gemma":0.0006209817,"threshold_uncertainty_score":0.113030195},"labels":[],"label_agreement":null},{"id":"W2260356148","doi":"10.1007/978-1-4471-4993-4_55","title":"Gearbox Fault Diagnosis Using Two-Dimensional Wavelet Transform","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Thresholding; Noise reduction; SIGNAL (programming language); Wavelet; Kurtosis; Vibration; Pattern recognition (psychology); Computer science; Wavelet transform; Artificial intelligence; Matrix (chemical analysis); Noise (video); Algorithm; Fault (geology); Mathematics; Acoustics; Materials science; Physics; Statistics; Image (mathematics); Geology","score_opus":0.009814248638526675,"score_gpt":0.2198842915211154,"score_spread":0.21007004288258874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2260356148","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09295723,0.0006089333,0.903686,0.00010372099,0.00010049417,0.000031605974,0.00009806638,0.00059800694,0.001816007],"genre_scores_gemma":[0.82463276,0.00081653195,0.17200832,0.000054394382,0.0000679432,0.00004143876,0.00025358502,0.00004867351,0.002076374],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999811,0.000020888252,0.000017479006,0.000037291713,0.00009249852,0.00002084014],"domain_scores_gemma":[0.99971145,0.00013495373,0.000035421297,0.000037081183,0.000068355235,0.000012672021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024039453,0.0006112817,0.000681817,0.00081528904,0.00014105959,0.0005974356,0.0003871407,0.0006939502,0.0010407001],"category_scores_gemma":[0.0010551377,0.00023136809,0.00043430168,0.0005543935,0.0002154016,0.0009722118,0.00044518933,0.00039821898,0.00040282993],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006478684,0.00016773453,0.0032651955,0.0004016952,0.000095975236,0.00057596597,0.0001102621,0.05903676,0.17597745,0.0033599548,0.0016858489,0.7546753],"study_design_scores_gemma":[0.000033609776,0.00015942687,0.0043271324,0.000029442053,0.00006243734,0.0005309216,0.000056227404,0.9571596,0.033463318,0.0031260976,0.0010296239,0.000022132486],"about_ca_topic_score_codex":0.0002934632,"about_ca_topic_score_gemma":0.00032617102,"teacher_disagreement_score":0.0010407001,"about_ca_system_score_codex":0.00010540946,"about_ca_system_score_gemma":0.00016325692,"threshold_uncertainty_score":0.0034815073},"labels":[],"label_agreement":null},{"id":"W2263601196","doi":"","title":"Calculation of Friction Coefficient And Downhole Weight On Bit With Finite Element Analysis of Drillstring","year":2012,"lang":"en","type":"article","venue":"46th U.S. Rock Mechanics/Geomechanics Symposium","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Bit (key); Finite element method; Friction coefficient; Geology; Mechanics; Materials science; Structural engineering; Engineering; Physics; Computer science; Composite material","score_opus":0.006254606044371454,"score_gpt":0.20654517897029673,"score_spread":0.20029057292592528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2263601196","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.557599,0.00023560863,0.43244478,0.00011033743,0.000047026948,0.000052601175,0.0002597993,0.0007490977,0.0085016955],"genre_scores_gemma":[0.97585607,0.00005528692,0.021975832,0.000009463394,0.0000034210234,0.000027847876,0.00011709757,0.000076753386,0.0018783262],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998784,0.000021384352,0.000008541388,0.000016249982,0.000058531437,0.000016827436],"domain_scores_gemma":[0.99967337,0.00011865154,0.000027536644,0.000040458526,0.00012292883,0.000017081853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021185081,0.00038825112,0.000544827,0.00065861613,0.00025665504,0.0004154401,0.00063334603,0.0006363992,0.002529643],"category_scores_gemma":[0.0010860318,0.00037197417,0.00038056416,0.0003583427,0.00023959298,0.0006164963,0.00030849478,0.0002671184,0.00048245915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019465065,0.000058517897,0.0050282087,0.00014848856,0.000029802575,0.00013549208,0.000103494975,0.9227026,0.02789153,0.0039922986,0.0006970904,0.03901781],"study_design_scores_gemma":[0.0000046374457,0.00001832668,0.0007573051,0.000005127177,0.000004494629,0.00001439846,0.000011907249,0.9958417,0.0028371415,0.00024415518,0.00025555005,0.0000053528584],"about_ca_topic_score_codex":0.00378307,"about_ca_topic_score_gemma":0.0040307413,"teacher_disagreement_score":0.00378307,"about_ca_system_score_codex":0.00030649808,"about_ca_system_score_gemma":0.0005198246,"threshold_uncertainty_score":0.008462548},"labels":[],"label_agreement":null},{"id":"W2264213598","doi":"10.1177/0954405415608601","title":"Optimum end milling tool path and machining parameters for micro Laval nozzle manufacturing","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Nozzle; Machining; Surface roughness; Mechanical engineering; Thrust; Surface finish; Materials science; Tool path; Cutting tool; Engineering; Composite material","score_opus":0.011604522816565757,"score_gpt":0.2087076963173076,"score_spread":0.19710317350074183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2264213598","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72733,0.0021190583,0.26705116,0.00014306106,0.000040394883,0.00013174211,0.00013210648,0.0004201607,0.0026322682],"genre_scores_gemma":[0.92999923,0.0002646336,0.069407575,0.000010920004,0.00000618905,0.000034494045,0.000046822013,0.000028614952,0.00020143345],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99934226,0.000094573224,0.000045638117,0.00011768155,0.00032844002,0.00007144189],"domain_scores_gemma":[0.9987863,0.00040284736,0.00043857994,0.00011414874,0.00022685171,0.000031237887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078142004,0.0004581096,0.00041411593,0.0005479249,0.00025916615,0.00071606383,0.0005335087,0.0005997785,0.00045029886],"category_scores_gemma":[0.0017745052,0.0003655921,0.00038549115,0.00037561616,0.00029406758,0.0007802983,0.00034529663,0.00031156818,0.00014290295],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005499653,0.00021648046,0.008948178,0.00075955596,0.000051694795,0.0005046856,0.00030564467,0.121695966,0.7751049,0.002930605,0.0008014855,0.08813094],"study_design_scores_gemma":[0.00022907795,0.0022137994,0.01553469,0.000100730926,0.00014223855,0.000989622,0.00024780148,0.36390293,0.6071561,0.0024736903,0.006828154,0.0001811261],"about_ca_topic_score_codex":0.0003491832,"about_ca_topic_score_gemma":0.000785979,"teacher_disagreement_score":0.00078142004,"about_ca_system_score_codex":0.00037460096,"about_ca_system_score_gemma":0.00059303484,"threshold_uncertainty_score":0.004132569},"labels":[],"label_agreement":null},{"id":"W2265717904","doi":"10.1115/1.4032585","title":"Stability of Milling Operations With Asymmetric Cutter Dynamics in Rotating Coordinates","year":2016,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dynamics (music); Stability (learning theory); Rotation (mathematics); Principal axis theorem; Mechanical engineering; Control theory (sociology); System dynamics; Physics; Computer science; Mechanics; Engineering; Geometry; Mathematics; Acoustics","score_opus":0.005303498213052689,"score_gpt":0.20042276310309745,"score_spread":0.19511926489004477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2265717904","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77350473,0.00016927761,0.22108588,0.00010688553,0.000014375991,0.00002813413,0.000062233026,0.00016709787,0.0048614386],"genre_scores_gemma":[0.9979261,0.000030413405,0.001575089,0.0000023997125,0.0000016884842,0.000008274994,0.000016390803,0.0000066292314,0.00043300618],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987936,0.000025843774,0.000005707643,0.000026318206,0.000044513086,0.000018337378],"domain_scores_gemma":[0.9997645,0.00008185168,0.00007391384,0.00002347144,0.00004529691,0.000011025818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026642173,0.0004444185,0.0003035123,0.00026449544,0.00024740314,0.00044528887,0.0002949276,0.0003625873,0.00056502246],"category_scores_gemma":[0.00054191553,0.00012434956,0.00043714125,0.00012575615,0.00062174705,0.0002957619,0.0002915629,0.0002868921,0.00014062955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026427023,0.000053561747,0.003459244,0.00006140996,0.00003754721,0.0002293129,0.00023031294,0.893509,0.078495175,0.010167525,0.0003163184,0.013176403],"study_design_scores_gemma":[0.0000039994384,0.000023588127,0.00046475916,0.0000012820625,0.00000252878,0.000017431219,0.000010924117,0.9964283,0.002499598,0.0004913854,0.00005291369,0.0000032941716],"about_ca_topic_score_codex":0.0023351915,"about_ca_topic_score_gemma":0.0010952116,"teacher_disagreement_score":0.0023351915,"about_ca_system_score_codex":0.00042495184,"about_ca_system_score_gemma":0.0003827417,"threshold_uncertainty_score":0.004643202},"labels":[],"label_agreement":null},{"id":"W2267846767","doi":"","title":"A comparison of the distortion of machined parts resulting from residual stresses within workpieces","year":2011,"lang":"en","type":"article","venue":"Espace ÉTS (ETS)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Residual stress; Machining; Distortion (music); Materials science; Surface integrity; Aerospace; Residual; Mechanical engineering; Structural engineering; Composite material; Metallurgy; Engineering; Computer science","score_opus":0.022950980944820443,"score_gpt":0.26374512749790774,"score_spread":0.24079414655308728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2267846767","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952513,0.0002316996,0.0032494972,0.0000072515136,0.000009259238,0.000010213095,0.00010028657,0.000034878674,0.0011056673],"genre_scores_gemma":[0.99735475,0.000071159266,0.0018283335,0.0000041433404,0.0000031623608,0.0000055885116,0.00017877993,0.000012447691,0.0005415812],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994721,0.00003647946,0.000035613008,0.00007112668,0.0003411031,0.000043596618],"domain_scores_gemma":[0.9980216,0.00072847895,0.00030876143,0.0003802027,0.0004739643,0.00008699412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035033753,0.00027847983,0.0003073317,0.0005939498,0.00017253931,0.00027244253,0.00039697293,0.0004119217,0.0018570732],"category_scores_gemma":[0.0014522943,0.0002319397,0.00032486144,0.00053671974,0.0004891864,0.00030099662,0.00017364165,0.0002700486,0.00024680636],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015181003,0.00008553161,0.0112981815,0.00021691556,0.000047750604,0.00028120418,0.00023682431,0.009652099,0.9474841,0.00025994788,0.00007460441,0.02884479],"study_design_scores_gemma":[0.000040151393,0.0024051443,0.35761636,0.000018354302,0.00006147702,0.0010297073,0.00019538883,0.015841827,0.62104255,0.00013992337,0.0015600733,0.00004913],"about_ca_topic_score_codex":0.0005912782,"about_ca_topic_score_gemma":0.0007988632,"teacher_disagreement_score":0.0018570732,"about_ca_system_score_codex":0.00025954522,"about_ca_system_score_gemma":0.00012971355,"threshold_uncertainty_score":0.0062125325},"labels":[],"label_agreement":null},{"id":"W2270704710","doi":"10.1139/tcsme-2010-0018","title":"INVESTIGATION OF SINGLE-POINT DRESSING OVERLAP RATIO AND DIAMOND-ROLL DRESSING INTERFERENCE ANGLE ON SURFACE ROUGHNESS IN GRINDING","year":2010,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Diamond; Materials science; Surface roughness; Surface finish; Diamond grinding; Interference (communication); Composite material; Diamond tool; Point (geometry); Single point; Inverse; Diamond turning; Geometry; Mechanics; Grinding wheel; Mathematics; Engineering; Computer simulation; Physics","score_opus":0.01401728513823588,"score_gpt":0.20879493949492575,"score_spread":0.19477765435668987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2270704710","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9780472,0.00052835944,0.020692425,0.000016701371,0.000009263437,0.000013039096,0.00002228754,0.00006814234,0.0006026165],"genre_scores_gemma":[0.9962631,0.000111860936,0.0035064358,0.0000040156706,0.0000017994334,0.0000031665968,0.000011501792,0.00001090432,0.000087325],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986512,0.00016889362,0.000039485945,0.00018325364,0.00083790603,0.00011923256],"domain_scores_gemma":[0.99610955,0.00264904,0.0005163501,0.00030206816,0.0003530972,0.00006985483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090236583,0.00037304914,0.00051055715,0.00031031837,0.00020730474,0.00044774715,0.0004071541,0.00041590098,0.0004214266],"category_scores_gemma":[0.0036557333,0.00033582252,0.0004812635,0.0003062171,0.00035312842,0.00047308387,0.00035066868,0.00034294903,0.00012974559],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005390938,0.00018123371,0.01188732,0.00033715108,0.00007567261,0.00023733558,0.00022217186,0.062584735,0.88226765,0.0003539669,0.00012820962,0.041185476],"study_design_scores_gemma":[0.000031963085,0.0013656525,0.03595393,0.000024997098,0.00009583482,0.0003828037,0.00016992597,0.26769814,0.69306135,0.00020703717,0.000939421,0.00006888355],"about_ca_topic_score_codex":0.0008553443,"about_ca_topic_score_gemma":0.0015366443,"teacher_disagreement_score":0.00090236583,"about_ca_system_score_codex":0.0003418012,"about_ca_system_score_gemma":0.00020325693,"threshold_uncertainty_score":0.004772246},"labels":[],"label_agreement":null},{"id":"W2271634029","doi":"10.4271/2007-01-0886","title":"Machining Error Correction at Batch Processing","year":2007,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; National Research Council Canada","funders":"AUTO21 Network of Centres of Excellence","keywords":"Machining; Computer science; Engineering; Mechanical engineering","score_opus":0.009775649750654983,"score_gpt":0.25532408505261145,"score_spread":0.24554843530195647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2271634029","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05348509,0.0002217427,0.9304338,0.00012779073,0.0002213742,0.00011031737,0.000188308,0.006346728,0.008864766],"genre_scores_gemma":[0.5239497,0.00012541059,0.45296174,0.00007012637,0.00006145679,0.00010557317,0.00046914766,0.00059106224,0.021665806],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991497,0.000071151895,0.000037184185,0.00019006527,0.0004998344,0.00005210332],"domain_scores_gemma":[0.9984641,0.0003460586,0.000096038006,0.00043368814,0.0006345161,0.000025558784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006366734,0.00052358204,0.00043047874,0.0006071048,0.0005027108,0.00078179984,0.0012243015,0.00040481458,0.0049868603],"category_scores_gemma":[0.0019555758,0.00020467232,0.00025090578,0.00063473673,0.00032890833,0.00072412885,0.00047059965,0.0008852278,0.0014733395],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072839163,0.00013000109,0.0017820727,0.00022284525,0.000022585997,0.00014626622,0.00023170272,0.045395013,0.26841778,0.0056521273,0.007128637,0.67014253],"study_design_scores_gemma":[0.000046089197,0.00025603827,0.003956402,0.000020870975,0.000021506525,0.00019344651,0.00004710659,0.45365572,0.5164248,0.0016344778,0.023695564,0.000048004727],"about_ca_topic_score_codex":0.00451398,"about_ca_topic_score_gemma":0.0043036155,"teacher_disagreement_score":0.0049868603,"about_ca_system_score_codex":0.0006304372,"about_ca_system_score_gemma":0.0009870614,"threshold_uncertainty_score":0.016682684},"labels":[],"label_agreement":null},{"id":"W2277343738","doi":"","title":"High-speed drilling of thick woven carbon fiber reinforced epoxy laminates","year":2015,"lang":"en","type":"article","venue":"Canadian aeronautics and space journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Aerospace; Epoxy; Drilling; Materials science; Composite laminates; Composite material; Composite number; Fiber; Durability; Carbon fiber composite; Marine industry; Structural engineering; Engineering; Aerospace engineering; Environmental science","score_opus":0.009995776759157048,"score_gpt":0.2006373325977383,"score_spread":0.19064155583858125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2277343738","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92421633,0.0018530973,0.066806875,0.00008875766,0.000101953796,0.00004561369,0.00008103148,0.00034062503,0.006465768],"genre_scores_gemma":[0.94498944,0.00040445686,0.05245943,0.000010166075,0.000011524573,0.000010812158,0.00004814557,0.000028483822,0.0020375913],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998865,0.000011817002,0.0000063047332,0.000015282452,0.000062053274,0.000018004212],"domain_scores_gemma":[0.99978584,0.000045254048,0.0000826299,0.000029041363,0.00004392963,0.000013314935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020075019,0.00024342518,0.0001660695,0.00024780352,0.00012538975,0.00017337444,0.00015935907,0.00024380285,0.0007136981],"category_scores_gemma":[0.0002820994,0.000171853,0.00010881055,0.00012850067,0.00019389103,0.0004428732,0.00019176363,0.00024795215,0.0002402222],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015140403,0.00002215089,0.0005166896,0.00024658028,0.0000050166227,0.00017660086,0.00008940611,0.004528039,0.9626481,0.0012095227,0.00032001932,0.030086473],"study_design_scores_gemma":[0.00002989542,0.00044539673,0.0031176398,0.000028691284,0.0000055488354,0.00043179543,0.00006404959,0.020913186,0.9693918,0.00039754796,0.0051569357,0.00001748192],"about_ca_topic_score_codex":0.00019968362,"about_ca_topic_score_gemma":0.00047395958,"teacher_disagreement_score":0.0007136981,"about_ca_system_score_codex":0.00008221444,"about_ca_system_score_gemma":0.0001377153,"threshold_uncertainty_score":0.0023875833},"labels":[],"label_agreement":null},{"id":"W2281903804","doi":"10.1139/tcsme-2003-0011","title":"ANALYSIS OF WHEEL WEAR USING FORCE DATA IN SURFACE GRINDING","year":2003,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Materials science; Abrasive; Grinding wheel; Cracking; Surface roughness; Metallurgy; Surface grinding; Composite material; Mechanical engineering; Engineering","score_opus":0.02085388871086057,"score_gpt":0.2408223631025024,"score_spread":0.21996847439164183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2281903804","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.982064,0.00026234638,0.016052794,0.00001817162,0.000013890184,0.000034628087,0.0004373839,0.00019699214,0.00091969146],"genre_scores_gemma":[0.9927834,0.000121381556,0.006181831,0.0000054355096,0.000004585997,0.000013214494,0.00039658832,0.000018616807,0.00047478202],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994599,0.000037601036,0.00002438688,0.00006704119,0.00034962007,0.00006146087],"domain_scores_gemma":[0.99784064,0.0008872438,0.00032028058,0.00017822662,0.00068757875,0.00008595944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045521435,0.000342345,0.00042442107,0.002283772,0.00025162735,0.00036003807,0.00035142372,0.0004838232,0.00070396543],"category_scores_gemma":[0.0025941778,0.0002025958,0.00029567734,0.0012800052,0.00024504078,0.00031847256,0.00021666715,0.00029269702,0.00031068455],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017345146,0.00042120338,0.28301403,0.0005672626,0.00014470695,0.0011393019,0.0012582409,0.030990707,0.36922505,0.0004750739,0.0009739345,0.31005594],"study_design_scores_gemma":[0.000022788694,0.00080014166,0.7236517,0.000041505908,0.00004679425,0.0010031536,0.0003590672,0.15899137,0.11222272,0.00040734623,0.002350164,0.00010337783],"about_ca_topic_score_codex":0.0049180933,"about_ca_topic_score_gemma":0.00772002,"teacher_disagreement_score":0.0049180933,"about_ca_system_score_codex":0.00029743536,"about_ca_system_score_gemma":0.00017599897,"threshold_uncertainty_score":0.009778917},"labels":[],"label_agreement":null},{"id":"W2283914286","doi":"10.1007/s11665-016-1950-6","title":"An Hybrid Approach Based on Machining and Dynamic Tests Data for the Identification of Material Constitutive Equations","year":2016,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Constitutive equation; Materials science; Inverse; Computation; Work (physics); Sensitivity (control systems); Finite element method; Inverse problem; Material properties; Identification (biology); Experimental data; Applied mathematics; Mechanical engineering; Computer science; Structural engineering; Algorithm; Mathematical analysis; Mathematics; Metallurgy; Composite material; Engineering; Statistics; Geometry","score_opus":0.014078801160641401,"score_gpt":0.24738010166025157,"score_spread":0.23330130049961018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2283914286","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020280048,0.000108092165,0.97752666,0.000029408919,0.000016784414,0.000055233668,0.000097677446,0.0003941854,0.0014918597],"genre_scores_gemma":[0.62985873,0.00035808247,0.36447838,0.000065988155,0.00005851632,0.00044745347,0.0007122539,0.00024477474,0.0037758537],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996258,0.000095652664,0.000029566972,0.00007673984,0.00014448095,0.000027794307],"domain_scores_gemma":[0.99916744,0.0004295683,0.000067386376,0.00009006224,0.00021998992,0.000025505224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048394824,0.0009614185,0.0010619749,0.0016485528,0.00045100506,0.0010129199,0.0012520577,0.0013704122,0.0034025882],"category_scores_gemma":[0.0015310629,0.00070650823,0.000847049,0.0009308547,0.0003961737,0.0012127981,0.00087630644,0.0010598353,0.0011836834],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002121998,0.00035373445,0.0027717445,0.00039840714,0.00014465221,0.00025064146,0.0001903589,0.7011021,0.07401537,0.010986089,0.00096379686,0.2086109],"study_design_scores_gemma":[0.0000069455878,0.000024806091,0.00037435954,0.00000640702,0.000010783903,0.000024676057,0.000012394691,0.99670035,0.0016302415,0.0008716855,0.00032624023,0.000011066771],"about_ca_topic_score_codex":0.003391946,"about_ca_topic_score_gemma":0.005155212,"teacher_disagreement_score":0.0034025882,"about_ca_system_score_codex":0.00032592143,"about_ca_system_score_gemma":0.00084054365,"threshold_uncertainty_score":0.011382818},"labels":[],"label_agreement":null},{"id":"W2285095447","doi":"10.1115/1.4032757","title":"Micro Flat End Milling Simulation Model With Instantaneous Plowing Area Prediction","year":2016,"lang":"en","type":"article","venue":"Journal of Micro and Nano-Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; Thermo Fisher Scientific (Canada)","funders":"","keywords":"Shearing (physics); Chip; Enhanced Data Rates for GSM Evolution; End milling; Chip formation; Miniaturization; Materials science; RADIUS; Machining; Mechanical engineering; Computer science; Tool wear; Composite material; Engineering","score_opus":0.008027891903721728,"score_gpt":0.1982001649652113,"score_spread":0.1901722730614896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2285095447","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29753053,0.00081507204,0.66050416,0.0004540015,0.00014664826,0.0002815044,0.0017635619,0.0017794647,0.03672499],"genre_scores_gemma":[0.91597617,0.00043610675,0.06872551,0.00007337129,0.000015589221,0.00049876916,0.0009158398,0.000120976874,0.013237576],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988747,0.000017722983,0.0000065833774,0.000025078773,0.00003999711,0.000023092942],"domain_scores_gemma":[0.9996228,0.00018749789,0.000048171678,0.000022488708,0.00009598125,0.000023042003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024474564,0.0005611077,0.0007272575,0.00046125855,0.00047750009,0.00080449786,0.0011872369,0.0013604311,0.0042724926],"category_scores_gemma":[0.00067633775,0.0004681259,0.00085480814,0.00046437435,0.00037998756,0.00045396874,0.00045210292,0.00062417216,0.0004923459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013613961,0.000007600325,0.00025051646,0.000013565645,0.0000035958512,0.000021502823,0.00000776495,0.9979742,0.0004585504,0.0003401764,0.00006072115,0.00084826455],"study_design_scores_gemma":[0.0000029336165,0.000004094428,0.0000479519,0.0000010752384,0.0000013807281,0.000002488197,0.0000017156519,0.99962854,0.00013209334,0.000072453004,0.0001040667,0.000001228796],"about_ca_topic_score_codex":0.018099513,"about_ca_topic_score_gemma":0.010061651,"teacher_disagreement_score":0.018099513,"about_ca_system_score_codex":0.0006132082,"about_ca_system_score_gemma":0.0010154872,"threshold_uncertainty_score":0.03598833},"labels":[],"label_agreement":null},{"id":"W2286336740","doi":"10.1007/s00170-015-8325-2","title":"Tool wear monitoring and replacement for tubesheet drilling","year":2016,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hitachi (Canada); University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Tool wear; Machining; Machine tool; Drilling; Process (computing); Engineering; Mechanical engineering; Duplex (building); Reduction (mathematics); Computer science","score_opus":0.006208704864434346,"score_gpt":0.24132588552490566,"score_spread":0.23511718066047133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2286336740","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9497904,0.0012782281,0.045713075,0.00006875283,0.00013403107,0.0000755128,0.00035765147,0.0010056838,0.0015765582],"genre_scores_gemma":[0.98869705,0.00013622329,0.009942449,0.0000135489,0.000009583578,0.00001074215,0.00011170447,0.000041765798,0.0010369975],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99939156,0.00006588505,0.000042185613,0.000081065424,0.000380977,0.00003830158],"domain_scores_gemma":[0.99823964,0.00055331195,0.0003164575,0.00025405144,0.0005591475,0.000077433964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043309588,0.00040901633,0.00045984038,0.0010157765,0.00033451992,0.00057170924,0.0007288911,0.00074530457,0.001153682],"category_scores_gemma":[0.0025937979,0.00034314735,0.00024550897,0.0004518358,0.0001968756,0.0006514197,0.0003345349,0.00035616977,0.00027263403],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037236563,0.00024634195,0.08117226,0.0004952301,0.000060023103,0.00065366476,0.00048112887,0.008842423,0.5238246,0.0002748209,0.0016117344,0.37861425],"study_design_scores_gemma":[0.00006092944,0.002849166,0.2188481,0.00010156568,0.00014882591,0.0029089956,0.0004972283,0.19635656,0.5699341,0.00044619018,0.0077218525,0.00012641343],"about_ca_topic_score_codex":0.0009195962,"about_ca_topic_score_gemma":0.002172086,"teacher_disagreement_score":0.001153682,"about_ca_system_score_codex":0.00018389623,"about_ca_system_score_gemma":0.0003316294,"threshold_uncertainty_score":0.0038594604},"labels":[],"label_agreement":null},{"id":"W2288138006","doi":"10.5539/jmsr.v5n2p100","title":"Influence of Process Parameters on the Surface Roughness during turning operation of High Strength Steel","year":2016,"lang":"en","type":"article","venue":"Journal of Materials Science Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Materials science; Surface roughness; Machining; High strength steel; Surface finish; Process (computing); Barrel (horology); Mechanical engineering; Metallurgy; Composite material; Computer science; Engineering","score_opus":0.0275108314492844,"score_gpt":0.3294611884589616,"score_spread":0.3019503570096772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2288138006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998887,0.00016037068,0.00061449816,0.00000469287,0.000006229898,0.000006357281,0.000029851255,0.000013211002,0.00027779397],"genre_scores_gemma":[0.99946386,0.000059804737,0.00026489707,0.0000031345212,0.0000015426057,0.0000023540665,0.00003890637,0.000006208069,0.00015930706],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964845,0.000049333787,0.000020999656,0.000053936288,0.00014773702,0.000079586796],"domain_scores_gemma":[0.99916613,0.00035471798,0.00015778939,0.00006935284,0.00020814002,0.000043867753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002894996,0.00027728817,0.0003150597,0.00022156232,0.00021344078,0.00036402518,0.00014922985,0.00035605129,0.0010011108],"category_scores_gemma":[0.0007560577,0.00024291882,0.0003344794,0.00018599047,0.00023376553,0.00024490972,0.00012865578,0.00028349363,0.00020310874],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008093316,0.00007135096,0.005915713,0.00012156599,0.000021000023,0.00021857288,0.00014525572,0.0026906151,0.9834225,0.000027447555,0.000063609914,0.0064929496],"study_design_scores_gemma":[0.000021585054,0.0029959066,0.09496681,0.00001207826,0.00008683418,0.00024003093,0.0004450867,0.0068639573,0.8936244,0.000044513574,0.0006596298,0.000039134902],"about_ca_topic_score_codex":0.0007622532,"about_ca_topic_score_gemma":0.0016072125,"teacher_disagreement_score":0.0010011108,"about_ca_system_score_codex":0.00015267047,"about_ca_system_score_gemma":0.00011436249,"threshold_uncertainty_score":0.0033490658},"labels":[],"label_agreement":null},{"id":"W2291436247","doi":"10.1139/tcsme-2010-0024","title":"FUZZY TAGUCHI DEDUCTION OPTIMIZATION ON MULTI-ATTRIBUTE CNC TURNING","year":2010,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Council","keywords":"TOPSIS; Taguchi methods; Ideal solution; Orthogonal array; Numerical control; Machining; Benchmark (surveying); Fuzzy logic; Similarity (geometry); Preference; Ideal (ethics); Computer science; Mathematics; Mathematical optimization; Engineering; Artificial intelligence; Mechanical engineering; Statistics; Operations research","score_opus":0.009087746676520651,"score_gpt":0.2109017885349232,"score_spread":0.20181404185840254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2291436247","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17473206,0.00014920082,0.82203144,0.00004184638,0.000020660966,0.00010739545,0.000016200189,0.000116691335,0.0027845781],"genre_scores_gemma":[0.8226024,0.000072362556,0.17635679,0.000019382214,0.0000059012937,0.00008217946,0.000036079753,0.000013831805,0.0008110883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982792,0.0004667936,0.00006654222,0.00017611911,0.00090328546,0.00010809895],"domain_scores_gemma":[0.9992078,0.00038926647,0.000092587135,0.000055112483,0.00023371406,0.000021629583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017082853,0.000601671,0.0007672993,0.0007686837,0.00042819846,0.0008296864,0.0005460792,0.00046588894,0.00049658876],"category_scores_gemma":[0.0019853057,0.00032082302,0.0006554124,0.0007241716,0.0005955708,0.00040532218,0.0003508096,0.00051130203,0.00008999812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023729297,0.00016559687,0.0015994745,0.00023648376,0.000047241483,0.000108171385,0.00022643949,0.78266907,0.049169187,0.006265082,0.00033704008,0.15893891],"study_design_scores_gemma":[0.00002599971,0.0003192557,0.00086329307,0.000010173295,0.000027938424,0.000040611263,0.00003188776,0.9843598,0.01207867,0.0016341325,0.0005913609,0.00001680867],"about_ca_topic_score_codex":0.002751351,"about_ca_topic_score_gemma":0.002949274,"teacher_disagreement_score":0.002751351,"about_ca_system_score_codex":0.00074459426,"about_ca_system_score_gemma":0.0009125067,"threshold_uncertainty_score":0.009034395},"labels":[],"label_agreement":null},{"id":"W2293772896","doi":"10.1139/tcsme-2008-0008","title":"COMPARISON OF CONVENTIONAL, COHERENT-JET AND HIGH-PRESSURE COOLANT DELIVERY SYSTEMS FOR PROFILE GRINDING","year":2008,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Coolant; Grinding; Jet (fluid); Mechanical engineering; Materials science; Volumetric flow rate; Mechanics; Flow (mathematics); Physics; Engineering","score_opus":0.017933022850232537,"score_gpt":0.23001885608952966,"score_spread":0.2120858332392971,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293772896","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8915107,0.006339241,0.09943353,0.00015789349,0.00016751986,0.00023117475,0.00009802596,0.0005195116,0.0015423612],"genre_scores_gemma":[0.9274507,0.001736152,0.067978494,0.00009333021,0.0000658975,0.00010256194,0.00015494028,0.00011773979,0.0023001833],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99827445,0.00021881056,0.000102905564,0.00020159809,0.0011268575,0.00007530836],"domain_scores_gemma":[0.99806184,0.00061759277,0.0003710456,0.00019786607,0.00065920776,0.0000923639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015315054,0.0003110645,0.0003521095,0.0005786598,0.0003091313,0.0006807061,0.00073780783,0.00038609194,0.0010371375],"category_scores_gemma":[0.003140442,0.00028851235,0.00022729939,0.0003220227,0.00037370564,0.00074341806,0.00043491376,0.00040663662,0.00026842576],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013032209,0.00025299616,0.0037254533,0.00085063133,0.00005571853,0.00010667451,0.00030789117,0.0018686106,0.8818296,0.00048447825,0.00047676841,0.108738005],"study_design_scores_gemma":[0.00025873614,0.004331499,0.028352719,0.00007872216,0.00018687909,0.00085262547,0.00014971943,0.01583265,0.94166183,0.00011936378,0.008081392,0.00009382052],"about_ca_topic_score_codex":0.0006939989,"about_ca_topic_score_gemma":0.0017250683,"teacher_disagreement_score":0.0015315054,"about_ca_system_score_codex":0.0005187404,"about_ca_system_score_gemma":0.00050660095,"threshold_uncertainty_score":0.008099496},"labels":[],"label_agreement":null},{"id":"W2299948121","doi":"10.4271/2016-01-0499","title":"Using Neural Networks to Examine the Sensitivity of Composite Material Mechanical Properties to Processing Parameters","year":2016,"lang":"en","type":"article","venue":"SAE International Journal of Materials and Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Composite number; Artificial neural network; Materials science; Sensitivity (control systems); Composite material; Materials processing; Computer science; Engineering; Process engineering; Artificial intelligence; Electronic engineering","score_opus":0.02089040918940083,"score_gpt":0.2466323832493497,"score_spread":0.22574197405994886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2299948121","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9212588,0.00028574024,0.075616896,0.00017669341,0.000030932133,0.00009454452,0.00017651655,0.00030254244,0.0020572895],"genre_scores_gemma":[0.9905608,0.00007342298,0.008560745,0.00002109649,0.0000049172413,0.000058811813,0.00011923673,0.00001405238,0.0005868735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955803,0.00015143695,0.000028704419,0.000105162646,0.00008620064,0.00007051168],"domain_scores_gemma":[0.9963415,0.00294691,0.00032851164,0.0001014304,0.00024579855,0.000035818382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001645177,0.0012343081,0.00051751384,0.00096740614,0.00025273842,0.0008190047,0.0006197589,0.0012726579,0.0010021563],"category_scores_gemma":[0.0072452542,0.00060621434,0.0006679269,0.0006094249,0.00045963173,0.00091330137,0.00043338316,0.00096906023,0.00011650667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019163883,0.00013051544,0.004152122,0.00005105519,0.00009191889,0.000034681867,0.00002174411,0.9816598,0.0041486286,0.00017971067,0.00004930764,0.009288895],"study_design_scores_gemma":[0.000003844695,0.00006402891,0.0015512309,0.0000026946275,0.000011649747,0.000006440391,0.0000061972264,0.9964365,0.0017572152,0.00012820217,0.000025033627,0.0000069625876],"about_ca_topic_score_codex":0.014043813,"about_ca_topic_score_gemma":0.0090428,"teacher_disagreement_score":0.014043813,"about_ca_system_score_codex":0.0010309367,"about_ca_system_score_gemma":0.00051104254,"threshold_uncertainty_score":0.02792412},"labels":[],"label_agreement":null},{"id":"W2304786101","doi":"10.1016/j.cirpj.2016.02.005","title":"Receptance coupling based algorithm for the identification of contact parameters at holder–tool interface","year":2016,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Interface (matter); Coupling (piping); Frequency response; Machine tool; Stability (learning theory); Substructure; Engineering; Position (finance); Vibration; Control theory (sociology); Algorithm; Computer science; Mechanical engineering; Structural engineering; Acoustics; Artificial intelligence; Physics","score_opus":0.00877426307148852,"score_gpt":0.2386599152504525,"score_spread":0.22988565217896398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2304786101","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005502907,0.000056353954,0.99347275,0.000016529097,0.000013928829,0.000023219818,0.000009432198,0.00023261632,0.00067208253],"genre_scores_gemma":[0.32912534,0.00017603657,0.66310036,0.000112141366,0.000033482724,0.0003221,0.00017434114,0.00012347627,0.0068327007],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996693,0.000084818974,0.000020570735,0.000071180075,0.00012433018,0.000029777555],"domain_scores_gemma":[0.9994735,0.00024322447,0.00004049421,0.000051930183,0.0001737491,0.00001717225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006706831,0.0007071253,0.00070177234,0.0005345089,0.00046292582,0.00067862176,0.0011241875,0.0012998539,0.0040207496],"category_scores_gemma":[0.0016914061,0.00029688884,0.0005588772,0.00037226753,0.0003199845,0.0006959046,0.0008234968,0.000930461,0.0011701543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055294094,0.00021155186,0.0013115593,0.0002925886,0.00012648587,0.00018527507,0.00029777538,0.31911814,0.09361167,0.013992229,0.0023245453,0.5679752],"study_design_scores_gemma":[0.000013659519,0.00007319894,0.0003024493,0.000009028046,0.000010234421,0.00004657189,0.000012931302,0.99264365,0.005069045,0.0009206153,0.00088948384,0.0000092094015],"about_ca_topic_score_codex":0.002170364,"about_ca_topic_score_gemma":0.002264989,"teacher_disagreement_score":0.0040207496,"about_ca_system_score_codex":0.000288216,"about_ca_system_score_gemma":0.00074633333,"threshold_uncertainty_score":0.013450742},"labels":[],"label_agreement":null},{"id":"W2313380927","doi":"10.1016/j.procir.2016.01.045","title":"A Novel Technique to Achieve Sustainable Machining System","year":2016,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Lubricant; Surface roughness; Mechanical engineering; Surface finish; Process engineering; Metalworking; Cutting fluid; Process (computing); Manufacturing engineering; Environmental pollution; Tool wear; Materials science; Engineering; Computer science; Environmental science; Composite material","score_opus":0.004569730936166919,"score_gpt":0.20178372079744453,"score_spread":0.1972139898612776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2313380927","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33012176,0.0031348364,0.63052016,0.0005389599,0.00022475315,0.00027018748,0.00016664702,0.0018179597,0.033204827],"genre_scores_gemma":[0.783024,0.00088431296,0.20749347,0.00012623338,0.00004369754,0.00013951043,0.00012508652,0.00006711266,0.008096615],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997291,0.00001568354,0.0000110856945,0.000056399476,0.00016289734,0.000024837113],"domain_scores_gemma":[0.99992645,0.000008575605,0.000015951453,0.00001535434,0.000025571599,0.00000797589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015332931,0.0002501114,0.0002622748,0.00028812038,0.00030599502,0.00039082306,0.000497099,0.00043154575,0.001496196],"category_scores_gemma":[0.00014932478,0.00015964729,0.00020587939,0.00023057136,0.0003128797,0.0006430449,0.0005234016,0.00037872148,0.000631115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038792237,0.000028410795,0.0002781258,0.00016204982,0.000007606028,0.0001331461,0.00010171173,0.0019619255,0.95210975,0.005404364,0.00043497773,0.03933909],"study_design_scores_gemma":[0.000046587425,0.0011371667,0.0023991058,0.000024991306,0.00002914219,0.0015113788,0.00013672438,0.0679907,0.8504419,0.0044532875,0.07177433,0.00005471523],"about_ca_topic_score_codex":0.00017870887,"about_ca_topic_score_gemma":0.00031080423,"teacher_disagreement_score":0.001496196,"about_ca_system_score_codex":0.00018404254,"about_ca_system_score_gemma":0.0003196214,"threshold_uncertainty_score":0.0050053},"labels":[],"label_agreement":null},{"id":"W2314141016","doi":"10.1109/idam.2014.6912701","title":"A study on modeling and grinding for twist drill flank","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Grinding; Flank; Drill; Conical surface; Machining; Point (geometry); Drilling; Kinematics; Computer science; Mechanical engineering; Engineering drawing; Geology; Engineering; Geometry; Mathematics; Physics","score_opus":0.0178345096121142,"score_gpt":0.2591932326107967,"score_spread":0.2413587229986825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314141016","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04095506,0.0022031853,0.9405607,0.00018154172,0.00007107873,0.00003852065,0.00009411545,0.0001551438,0.015740652],"genre_scores_gemma":[0.8306341,0.0042177085,0.15329383,0.00005152494,0.0000638823,0.00008409343,0.00022525719,0.0001217756,0.011307772],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996431,0.0000486653,0.000014709452,0.00007221097,0.00019872216,0.000022596358],"domain_scores_gemma":[0.99980456,0.000057298737,0.000038563172,0.000028498362,0.00006406154,0.000007083886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004022984,0.000525526,0.00048753704,0.00046106827,0.0003562098,0.00076845847,0.000935647,0.00051541626,0.0017068734],"category_scores_gemma":[0.00081361155,0.0003697972,0.0008309773,0.0006118833,0.0003762645,0.0011692947,0.00023334399,0.0005348256,0.00030892008],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034555498,0.000040645602,0.003093473,0.00046328406,0.000022457982,0.00033975558,0.00021463458,0.8405429,0.023017826,0.06602845,0.001161953,0.06504003],"study_design_scores_gemma":[0.000002463488,0.000042557323,0.00085987715,0.000020923717,0.000010103162,0.00016080108,0.000027053378,0.98554915,0.002533171,0.0063623814,0.00442063,0.000010938988],"about_ca_topic_score_codex":0.0082261795,"about_ca_topic_score_gemma":0.005949659,"teacher_disagreement_score":0.0082261795,"about_ca_system_score_codex":0.0005698479,"about_ca_system_score_gemma":0.0007384978,"threshold_uncertainty_score":0.016356587},"labels":[],"label_agreement":null},{"id":"W2315238182","doi":"10.1115/imece2005-81080","title":"Analytical and Numerical Investigation of the Strain Rate Field in the Secondary Shear Zone","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Shear rate; Shear stress; Shear (geology); Strain rate; Shear zone; Constitutive equation; Shear flow; Mechanics; Critical resolved shear stress; Chip formation; Simple shear; Materials science; Shear velocity; Flow stress; Pure shear; Geotechnical engineering; Geology; Composite material; Finite element method; Structural engineering; Machining; Rheology; Physics; Engineering; Metallurgy","score_opus":0.007804204487353628,"score_gpt":0.22471791656507664,"score_spread":0.216913712077723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315238182","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28868368,0.0007069635,0.69776636,0.00017728284,0.00004836808,0.0000821154,0.00011451295,0.0003786177,0.01204211],"genre_scores_gemma":[0.9084361,0.0003534627,0.089194335,0.000013822137,0.0000151394715,0.0000557995,0.000046084515,0.000024975248,0.0018603071],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985003,0.000028652295,0.0000069403795,0.00003001856,0.000066693974,0.000017560658],"domain_scores_gemma":[0.9995136,0.0002463357,0.00008450494,0.000043185817,0.000093122966,0.000019153229],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006157162,0.000398537,0.00045619067,0.0005718436,0.00021636719,0.0004702602,0.0004933792,0.0006782199,0.00066888274],"category_scores_gemma":[0.0011135951,0.00025033852,0.00035628778,0.00048287457,0.00086804054,0.00043861617,0.0002697699,0.0004036381,0.00013597668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000109577326,0.00011030003,0.0020160424,0.00017397436,0.00001272579,0.00017330387,0.0001637327,0.8901298,0.064999714,0.021273194,0.00022792774,0.020609727],"study_design_scores_gemma":[0.0000041413455,0.000020376232,0.00022946797,0.000003502855,0.0000014571189,0.000022780288,0.0000076761235,0.99547595,0.0036033292,0.00042561762,0.00020145978,0.000004380456],"about_ca_topic_score_codex":0.0013116378,"about_ca_topic_score_gemma":0.0008886729,"teacher_disagreement_score":0.0013116378,"about_ca_system_score_codex":0.00036516035,"about_ca_system_score_gemma":0.000675312,"threshold_uncertainty_score":0.0032562613},"labels":[],"label_agreement":null},{"id":"W2315242785","doi":"10.1504/ijmmm.2016.075469","title":"Experimental investigation on part quality and metallic particle emission when milling 6061-T6 aluminium alloy","year":2016,"lang":"en","type":"article","venue":"International Journal of Machining and Machinability of Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Materials science; Metallurgy; Aluminium; Alloy; Particle size; Aluminium alloy; Coating; Particle (ecology); Insert (composites); Quality (philosophy); RADIUS; Surface roughness; Composite material; Engineering","score_opus":0.03429381289650232,"score_gpt":0.29984027461576435,"score_spread":0.26554646171926205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315242785","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984493,0.00004382215,0.0012299982,0.0000039433917,0.0000028670459,0.000013722164,0.000053065578,0.000009746537,0.00019348408],"genre_scores_gemma":[0.99809664,0.000053919623,0.0013065559,0.0000049252576,0.00000331269,0.000014885278,0.000072171555,0.000007432188,0.00044013202],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999419,0.000090652255,0.000038183807,0.00013687467,0.00023521658,0.000080159865],"domain_scores_gemma":[0.9986308,0.00070416695,0.00023223463,0.0001251076,0.00025742978,0.00005021588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005372352,0.00034484663,0.00046457382,0.00024397772,0.00037473667,0.0002317507,0.00028510284,0.00042863522,0.0014233007],"category_scores_gemma":[0.001148633,0.0002085442,0.0003764907,0.00035798879,0.00045252094,0.00023258457,0.00019163877,0.00031848438,0.00015977064],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008883482,0.00023016028,0.003060546,0.000113444716,0.000019237095,0.00010406658,0.00023828917,0.0009271149,0.9915598,0.000029233173,0.000024660741,0.0028051205],"study_design_scores_gemma":[0.000038959723,0.0061242087,0.044493433,0.0000044392245,0.00005058113,0.00013618174,0.00022730415,0.0027561502,0.9457717,0.000034849574,0.00033999802,0.0000222022],"about_ca_topic_score_codex":0.00062853296,"about_ca_topic_score_gemma":0.0009522847,"teacher_disagreement_score":0.0014233007,"about_ca_system_score_codex":0.00018639542,"about_ca_system_score_gemma":0.00011682973,"threshold_uncertainty_score":0.004761398},"labels":[],"label_agreement":null},{"id":"W2316087454","doi":"10.1115/imece2004-60395","title":"Adaptive Control and Monitoring Using the Spindle Integrated Force Sensor System","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Kalman filter; Breakage; Machine tool; Engineering; Vibration; Tool wear; Trajectory; Control engineering; Mechanical engineering; Computer science; Acoustics; Artificial intelligence","score_opus":0.011095449120073575,"score_gpt":0.2225805769432285,"score_spread":0.21148512782315493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2316087454","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28979942,0.00039746796,0.7020038,0.00020352201,0.00009097017,0.00009757432,0.0001016853,0.0015921075,0.005713507],"genre_scores_gemma":[0.9497788,0.00010726108,0.04795348,0.000042376545,0.000025704341,0.000042857995,0.000054707896,0.000010468393,0.001984354],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997296,0.000030701154,0.000011653445,0.000055744127,0.00015452645,0.000017656977],"domain_scores_gemma":[0.99962807,0.00011016396,0.000058707617,0.000043513115,0.00014556572,0.000013926499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002641809,0.0002723898,0.00023301072,0.00026365425,0.00014050918,0.00032648465,0.00035762516,0.00034234222,0.00076712057],"category_scores_gemma":[0.0007941517,0.00011246433,0.000094510455,0.0002163148,0.0001727866,0.00029937734,0.00017823307,0.00024349318,0.0001528186],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072687224,0.00019835247,0.0068955594,0.00018863154,0.00005346186,0.00027020066,0.00023582249,0.09529254,0.45173633,0.0027678325,0.0017742132,0.43986022],"study_design_scores_gemma":[0.00008722946,0.0007526323,0.012708793,0.000022393406,0.000042870604,0.00034472824,0.00003654158,0.8737568,0.10516929,0.0008330407,0.0062049367,0.000040729596],"about_ca_topic_score_codex":0.0022079863,"about_ca_topic_score_gemma":0.0021671227,"teacher_disagreement_score":0.0022079863,"about_ca_system_score_codex":0.00018308689,"about_ca_system_score_gemma":0.0001803436,"threshold_uncertainty_score":0.0043902993},"labels":[],"label_agreement":null},{"id":"W2318273350","doi":"10.1115/detc2004-57211","title":"Global Stiffness Improvement for Tricept Machine Tools Family","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Stiffness; Machine tool; Computer science; Direct stiffness method; Structural engineering; Mechanical engineering; Engineering; Stiffness matrix","score_opus":0.011753747465982737,"score_gpt":0.2459445725111581,"score_spread":0.23419082504517535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2318273350","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27434167,0.00073161855,0.7004859,0.00010260518,0.000084916464,0.00003605599,0.00009406633,0.0005751366,0.023548149],"genre_scores_gemma":[0.92476416,0.00018175493,0.069737345,0.00002639735,0.000013897525,0.000031906577,0.00010689888,0.000050144754,0.0050875247],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998147,0.000019585377,0.0000076986835,0.00003288384,0.000106407366,0.000018647534],"domain_scores_gemma":[0.99982363,0.000032959106,0.000041755822,0.000040279647,0.00004967383,0.000011751484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012767126,0.00036457286,0.00020949163,0.00034335142,0.0001341025,0.0003149759,0.0005021512,0.00025422472,0.00307576],"category_scores_gemma":[0.00032341984,0.00012035376,0.00028036142,0.00021226208,0.0002715243,0.00063678325,0.00041205995,0.0002392307,0.0005781532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038755624,0.00006715074,0.0032343976,0.00055937417,0.00006811602,0.0005860011,0.00020706776,0.10954885,0.4921266,0.033084396,0.0023399096,0.35779062],"study_design_scores_gemma":[0.00010621394,0.0021166904,0.009631262,0.00010558324,0.00012076467,0.0029707653,0.00022195993,0.7043847,0.21403469,0.018456083,0.04774423,0.00010713503],"about_ca_topic_score_codex":0.00018107402,"about_ca_topic_score_gemma":0.00043650434,"teacher_disagreement_score":0.00307576,"about_ca_system_score_codex":0.00018209503,"about_ca_system_score_gemma":0.0001656583,"threshold_uncertainty_score":0.010289431},"labels":[],"label_agreement":null},{"id":"W2318820379","doi":"10.2493/jspe.70.433","title":"Effects of Laval Nozzle on Precision Micro Cutting of Thin Metal Plate by Pulsed YAG Laser","year":2004,"lang":"en","type":"article","venue":"Seimitsu kougakkaishi rombunshuu/Seimitsu kougakkaishi/Seimitsu Kougakkaishi rombunshuu","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nozzle; Dross; Mechanical engineering; Mechanics; Materials science; Cylinder; Mach number; Flow (mathematics); Laser cutting; Machining; Laser; Engineering; Metallurgy; Optics; Physics","score_opus":0.00502649676955371,"score_gpt":0.2111031830754095,"score_spread":0.2060766863058558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2318820379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99170893,0.0021205537,0.0048783924,0.000035828325,0.000023284474,0.000009486882,0.000019200817,0.00007252245,0.0011318845],"genre_scores_gemma":[0.99698156,0.0004910924,0.0021732135,0.000015465033,0.0000067546266,0.000005096992,0.000009993922,0.000009962794,0.0003068091],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997062,0.000034705576,0.000014433976,0.000049592123,0.00015257427,0.000042509106],"domain_scores_gemma":[0.9996722,0.00013714915,0.00009924412,0.000020696674,0.000054344277,0.00001634033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024406053,0.00022837512,0.00023032965,0.00018207003,0.00018785939,0.00028345335,0.00021584137,0.000266145,0.0005262937],"category_scores_gemma":[0.00037378693,0.00018150323,0.00023398652,0.00012606304,0.00033427542,0.00029949355,0.00028639418,0.00021726437,0.000076825294],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016135184,0.00001603704,0.001047609,0.00014022835,0.000011419021,0.00029464287,0.000084054045,0.0008013922,0.9891567,0.00017408548,0.00006914229,0.008043224],"study_design_scores_gemma":[0.00002861464,0.00061116065,0.007676789,0.000012027095,0.00003652337,0.00030584403,0.00006591867,0.0065996572,0.98347706,0.00006405119,0.0010990647,0.000023268818],"about_ca_topic_score_codex":0.0004972817,"about_ca_topic_score_gemma":0.0004347712,"teacher_disagreement_score":0.0005262937,"about_ca_system_score_codex":0.00019064386,"about_ca_system_score_gemma":0.00013733683,"threshold_uncertainty_score":0.001760602},"labels":[],"label_agreement":null},{"id":"W2319648114","doi":"10.3183/npprj-2014-29-01-p031-040","title":"Critical discussion of light scattering and microscopy techniques for CNC particle sizing","year":2014,"lang":"en","type":"article","venue":"Nordic Pulp & Paper Research Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"FPInnovations","funders":"Natural Resources Canada; ArboraNano","keywords":"Sizing; Particle (ecology); Microscopy; Materials science; Light scattering; Optics; Nanotechnology; Composite material; Scattering; Chemistry; Physics; Geology","score_opus":0.022189721413338394,"score_gpt":0.3684730961165018,"score_spread":0.3462833747031634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2319648114","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00843902,0.16396707,0.733162,0.030524358,0.033589493,0.0010697205,0.0004409421,0.0009960484,0.027811388],"genre_scores_gemma":[0.0943444,0.15085992,0.6759053,0.013852727,0.012606316,0.002404001,0.0005013549,0.000907572,0.04861845],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99433655,0.0018480083,0.00040052997,0.00042352715,0.002825113,0.00016627673],"domain_scores_gemma":[0.99302316,0.004423848,0.00036746814,0.000547281,0.0015292944,0.0001089828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009983929,0.0013105391,0.0009493116,0.002478564,0.001499832,0.0016758499,0.0026965933,0.002128725,0.004148536],"category_scores_gemma":[0.008772531,0.0008619505,0.0010424718,0.0011693013,0.0030366643,0.0023481515,0.0011209949,0.0048553385,0.0020292888],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003282889,0.0003428025,0.0014335754,0.007261378,0.00014602505,0.0014855032,0.0009163527,0.007964359,0.2327089,0.28941283,0.08446081,0.37353924],"study_design_scores_gemma":[0.000022170792,0.00029686975,0.0021742594,0.0009899358,0.00003768197,0.0016908653,0.00018473978,0.010108122,0.14069198,0.06547037,0.7781795,0.00015345524],"about_ca_topic_score_codex":0.0017615152,"about_ca_topic_score_gemma":0.002077036,"teacher_disagreement_score":0.009983929,"about_ca_system_score_codex":0.0030433394,"about_ca_system_score_gemma":0.0015123262,"threshold_uncertainty_score":0.052800655},"labels":[],"label_agreement":null},{"id":"W2320937148","doi":"10.1115/imece2003-42369","title":"Identification of Spindle Integrated Force Sensor’s Transfer Function for Modular End Mills","year":2003,"lang":"en","type":"article","venue":"Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Modular design; Transfer function; End mill; Mill; Coupling (piping); Function (biology); Control theory (sociology); Calibration; Engineering; Mechanical engineering; Control engineering; Computer science; Physics; Electrical engineering; Machining; Artificial intelligence","score_opus":0.007220761757520943,"score_gpt":0.2056163342474358,"score_spread":0.19839557248991485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2320937148","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10326731,0.00011360849,0.89528275,0.00004018442,0.000009374703,0.000027596203,0.000025968156,0.0004487689,0.00078444567],"genre_scores_gemma":[0.9497645,0.00007764261,0.049225315,0.000013333904,0.0000072953685,0.000027053671,0.000042583284,0.000024006336,0.00081820396],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997831,0.000049875027,0.0000069768907,0.000053074476,0.00008957741,0.000017346669],"domain_scores_gemma":[0.9995851,0.00020226515,0.00007235546,0.000052460156,0.00007766577,0.00001013557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036678376,0.00061035174,0.0003460678,0.00022341893,0.000178684,0.00037726658,0.00062406034,0.00077240536,0.0009123563],"category_scores_gemma":[0.0011229197,0.00025533972,0.00024073305,0.00013987807,0.00023346438,0.00043812682,0.0002316228,0.00042673334,0.0003280675],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004756801,0.00016082854,0.0054249484,0.00032388058,0.000082095794,0.00052418263,0.00031887356,0.27114028,0.5155732,0.006400457,0.0006445909,0.19893087],"study_design_scores_gemma":[0.000020664975,0.00022854537,0.0037279185,0.00001316115,0.000013498645,0.00029109247,0.000023068025,0.9341902,0.05946116,0.0011567131,0.0008562466,0.000017677123],"about_ca_topic_score_codex":0.00064466486,"about_ca_topic_score_gemma":0.0006020218,"teacher_disagreement_score":0.0009123563,"about_ca_system_score_codex":0.00028690713,"about_ca_system_score_gemma":0.00024803233,"threshold_uncertainty_score":0.003052175},"labels":[],"label_agreement":null},{"id":"W2321245006","doi":"10.1080/20550340.2015.1117747","title":"A simplified damage prediction framework for milling of unidirectional carbon fiber-reinforced plastics","year":2015,"lang":"en","type":"article","venue":"Advanced Manufacturing Polymer & Composites Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Delamination (geology); Materials science; Composite material; Fiber; Machining; Metallurgy; Geology","score_opus":0.014513408799826932,"score_gpt":0.24942172464019383,"score_spread":0.2349083158403669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2321245006","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012078059,0.0002267253,0.98651147,0.00003370906,0.000013468965,0.00004106457,0.00007140272,0.00028709648,0.00073706714],"genre_scores_gemma":[0.7388692,0.0011388743,0.25542307,0.000054995075,0.000078905236,0.00032508565,0.00033524077,0.00013899372,0.0036356843],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964035,0.000045055247,0.000019728659,0.00008329778,0.00016931261,0.000042225583],"domain_scores_gemma":[0.9996605,0.00013420967,0.00006771875,0.00002718653,0.00009152147,0.000018876368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006056348,0.0011637227,0.0009503536,0.0010455482,0.00034765474,0.0007516626,0.0015157358,0.0009484799,0.0014002682],"category_scores_gemma":[0.0009879189,0.00048227294,0.0008619944,0.0003998158,0.00052177405,0.0007352816,0.0006371084,0.00077433727,0.00039898843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010521963,0.00001696879,0.00035816562,0.0000497262,0.000014202233,0.00006702115,0.00001890494,0.9809014,0.0052022985,0.0020976283,0.00012206673,0.0111410795],"study_design_scores_gemma":[0.000001131487,0.000011914589,0.00014799711,0.0000031505401,0.0000030490105,0.000012588947,0.0000026960695,0.99852836,0.00043873358,0.00071826385,0.00012746255,0.0000045881507],"about_ca_topic_score_codex":0.008067003,"about_ca_topic_score_gemma":0.005493994,"teacher_disagreement_score":0.008067003,"about_ca_system_score_codex":0.0007175468,"about_ca_system_score_gemma":0.00082172325,"threshold_uncertainty_score":0.016040087},"labels":[],"label_agreement":null},{"id":"W2322755478","doi":"10.1115/imece2004-59445","title":"A Model for Orthogonal Machining of Metal Matrix Composite Using Finite Element Method","year":2004,"lang":"en","type":"article","venue":"Applied Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Finite element method; Aluminium; Materials science; Machining; Metal matrix composite; Composite number; Composite material; Matrix (chemical analysis); Aluminium oxide; Stress (linguistics); Structural engineering; Metallurgy; Engineering","score_opus":0.023337651582467412,"score_gpt":0.2914533675639964,"score_spread":0.268115715981529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2322755478","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008093083,0.0001853262,0.9863369,0.000081270446,0.000039361406,0.000039890692,0.00009190582,0.00023392645,0.0048982967],"genre_scores_gemma":[0.47501695,0.0009005869,0.49548355,0.00014254234,0.000047999725,0.0007150585,0.00046274316,0.00021151606,0.027018981],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998447,0.000036443744,0.0000075681924,0.00002366961,0.000074345444,0.000013357589],"domain_scores_gemma":[0.9999006,0.000036567562,0.00001328042,0.000012483464,0.00003010187,0.0000069896987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026647028,0.0004317134,0.00047397878,0.00033495965,0.0003510087,0.00049970055,0.00122421,0.0015659998,0.0030679244],"category_scores_gemma":[0.00036553148,0.0003666144,0.00065753143,0.00032877823,0.000354273,0.0005829306,0.00038039332,0.0007278992,0.0009581635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002239143,0.000026713551,0.00021983894,0.00008467459,0.000014097326,0.00007814103,0.000056486293,0.9615611,0.008826304,0.017580794,0.0004342785,0.01109507],"study_design_scores_gemma":[0.000003793419,0.000012707979,0.000055061093,0.000005550154,0.0000026936436,0.00003241712,0.0000068994045,0.99553704,0.00071500323,0.0012767449,0.002347589,0.0000045688207],"about_ca_topic_score_codex":0.0036673897,"about_ca_topic_score_gemma":0.0028222895,"teacher_disagreement_score":0.0036673897,"about_ca_system_score_codex":0.00032081935,"about_ca_system_score_gemma":0.0006740135,"threshold_uncertainty_score":0.010263205},"labels":[],"label_agreement":null},{"id":"W2326405972","doi":"10.1515/msr-2015-0034","title":"Design and Analysis of a Micromechanical Three-Component Force Sensor for Characterizing and Quantifying Surface Roughness","year":2015,"lang":"en","type":"article","venue":"Measurement Science Review","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Changsha Science and Technology Project; Specialized Research Fund for the Doctoral Program of Higher Education of China; Natural Science Foundation of Hunan Province; National Natural Science Foundation of China","keywords":"Materials science; Surface micromachining; Surface roughness; Sensitivity (control systems); Surface finish; Microelectromechanical systems; Coupling (piping); Nanometre; Component (thermodynamics); Compensation (psychology); Beam (structure); Acoustics; Electronic engineering; Mechanical engineering; Composite material; Structural engineering; Optoelectronics; Engineering; Fabrication","score_opus":0.16073330373539158,"score_gpt":0.3221838806290909,"score_spread":0.16145057689369935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2326405972","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.092711285,0.0006507285,0.9027432,0.0003321182,0.00006216545,0.0003787801,0.00013256069,0.0007405927,0.0022484052],"genre_scores_gemma":[0.7109429,0.0004596616,0.28617415,0.00009544891,0.00002643959,0.00028811203,0.00012530427,0.000028131837,0.0018598416],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994498,0.000054894685,0.000020005755,0.0001304182,0.00031482612,0.000030060906],"domain_scores_gemma":[0.9996408,0.00012069289,0.000056996603,0.000038064143,0.00012664741,0.000016800284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004651541,0.00051278376,0.0006841544,0.00031370763,0.00028445557,0.00057577423,0.00082753884,0.0009786143,0.00067927496],"category_scores_gemma":[0.0005711934,0.0003459984,0.00039430245,0.00028224388,0.0003326956,0.0005189387,0.00023565044,0.00036831532,0.00026863237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001501062,0.00009429111,0.002734781,0.0004385314,0.00007656556,0.0003373373,0.00013486267,0.05048414,0.88571644,0.0044555753,0.0009164427,0.054460943],"study_design_scores_gemma":[0.000048176687,0.00093873945,0.0062045148,0.000018246457,0.00006553067,0.00045297254,0.000051151204,0.75017744,0.2364129,0.000680139,0.0048911828,0.00005900649],"about_ca_topic_score_codex":0.0015141389,"about_ca_topic_score_gemma":0.0016313088,"teacher_disagreement_score":0.0015141389,"about_ca_system_score_codex":0.0006771045,"about_ca_system_score_gemma":0.00081844704,"threshold_uncertainty_score":0.0049127936},"labels":[],"label_agreement":null},{"id":"W2328831662","doi":"10.1007/s10845-016-1209-y","title":"A sensor fusion and support vector machine based approach for recognition of complex machining conditions","year":2016,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Natural Science Foundation of China","keywords":"Machining; Support vector machine; SIGNAL (programming language); Sensor fusion; Pattern recognition (psychology); Acceleration; Artificial intelligence; Condition monitoring; Engineering; Feature extraction; Tool wear; Machine tool; Vibration; Process (computing); Computer science; Mechanical engineering; Acoustics","score_opus":0.030544155812079567,"score_gpt":0.2603750140233659,"score_spread":0.22983085821128632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328831662","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033948157,0.0004990486,0.9633053,0.00009917136,0.00012280856,0.0000485057,0.00008961403,0.0007858032,0.001101554],"genre_scores_gemma":[0.7054368,0.0005295945,0.29056635,0.00012574402,0.00008815033,0.0001255548,0.0002644322,0.00004298858,0.0028203924],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996044,0.00005470697,0.000027627331,0.00007909466,0.00018982762,0.000044306136],"domain_scores_gemma":[0.999647,0.000077685174,0.00003901513,0.00003522361,0.00018317344,0.000017892418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004779543,0.0006409578,0.00081096013,0.0006980081,0.0002722356,0.0006419582,0.00072952907,0.0008667665,0.0013293099],"category_scores_gemma":[0.000855308,0.00033210206,0.0004748561,0.00076393376,0.00025658752,0.00096750015,0.0005886685,0.0007680316,0.00056815386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046381252,0.00030381896,0.0014470808,0.0001929326,0.0000989527,0.00013700659,0.00008962339,0.0638458,0.13175336,0.0026034939,0.0023626979,0.7967015],"study_design_scores_gemma":[0.0000124623975,0.0002164007,0.0018025802,0.000010223932,0.000030444353,0.00011731106,0.000028881865,0.96902496,0.026294563,0.001273999,0.0011613148,0.000026719843],"about_ca_topic_score_codex":0.0012879819,"about_ca_topic_score_gemma":0.001538347,"teacher_disagreement_score":0.0013293099,"about_ca_system_score_codex":0.00022091641,"about_ca_system_score_gemma":0.0004732948,"threshold_uncertainty_score":0.0044469833},"labels":[],"label_agreement":null},{"id":"W2330125078","doi":"10.3183/npprj-2011-26-01-p014-020","title":"Mechanical Pulping: Force-based characterization of refining intensity","year":2011,"lang":"en","type":"article","venue":"Nordic Pulp & Paper Research Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Refining (metallurgy); Industrial chemistry; Characterization (materials science); Materials science; Intensity (physics); Pulp and paper industry; Process engineering; Composite material; Engineering; Metallurgy; Nanotechnology; Biochemical engineering","score_opus":0.07527268932836945,"score_gpt":0.31280213221225284,"score_spread":0.2375294428838834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2330125078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97351766,0.00056191627,0.020443825,0.00003672557,0.000013855665,0.000046784593,0.00040671768,0.00016668403,0.0048058177],"genre_scores_gemma":[0.9937447,0.00015111275,0.0042799786,0.000014244571,0.000006447025,0.000016066757,0.00015732538,0.000028884222,0.0016013739],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995914,0.000021295316,0.000015500076,0.00007484407,0.00025661063,0.000040366227],"domain_scores_gemma":[0.9995442,0.00015085253,0.00006809378,0.000043278542,0.00016904627,0.000024513201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032165297,0.00025955116,0.00022158536,0.0007011002,0.00028947587,0.0003383308,0.0005348486,0.00042304353,0.0033618435],"category_scores_gemma":[0.0007818566,0.00023637166,0.00019362479,0.0006936656,0.00034040515,0.0004585808,0.0002520795,0.00030129406,0.00054499734],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004483621,0.0000450884,0.007441535,0.0000879011,0.000012638319,0.000028784016,0.00010891645,0.00079107145,0.96823555,0.00010787147,0.00010888696,0.022583343],"study_design_scores_gemma":[0.00001648898,0.00030729256,0.08040809,0.000009070743,0.00003347029,0.00015625759,0.00007142344,0.008233075,0.90955675,0.00006690742,0.001119383,0.000021754893],"about_ca_topic_score_codex":0.002420102,"about_ca_topic_score_gemma":0.0040063546,"teacher_disagreement_score":0.0033618435,"about_ca_system_score_codex":0.00026825332,"about_ca_system_score_gemma":0.00021253042,"threshold_uncertainty_score":0.011246502},"labels":[],"label_agreement":null},{"id":"W2335211085","doi":"","title":"Stress and Strain Distributions during Machining of Ti-6Al-4V at Ambient and Cryogenic Temperatures","year":2014,"lang":"en","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Materials science; Strain (injury); Metallurgy; Stress (linguistics); Cryogenic temperature; Composite material; Forensic engineering; Engineering; Medicine","score_opus":0.0053520656653797405,"score_gpt":0.18699106822718117,"score_spread":0.18163900256180143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2335211085","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990785,0.0000666867,0.0003799007,0.0000063176035,0.000002714546,0.000004672301,0.00011525714,0.000018786128,0.00032700054],"genre_scores_gemma":[0.99873,0.000039216702,0.0005526759,0.000004002924,0.0000029066118,0.000008114642,0.00015407882,0.000013232198,0.0004958776],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998037,0.000014769706,0.000008992072,0.00004986692,0.00007541984,0.000047330537],"domain_scores_gemma":[0.999554,0.00012227929,0.00010794816,0.000054284916,0.00012755637,0.000033971475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022593165,0.0002336109,0.00036755452,0.00031619595,0.00031114608,0.00033888718,0.00045352906,0.0002690681,0.001165938],"category_scores_gemma":[0.00043982617,0.00024934803,0.00014916823,0.0003823021,0.00045475984,0.00025842348,0.000119848475,0.00031398205,0.00013880055],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043456853,0.00003429741,0.0022918528,0.000054429267,0.000010788826,0.00012447013,0.00028762533,0.0010119707,0.99342114,0.000093733295,0.000064445296,0.0021705676],"study_design_scores_gemma":[0.000026584246,0.0009920233,0.09620619,0.000012624055,0.00002584558,0.00016493168,0.00033347314,0.010338949,0.890689,0.00009099849,0.00109126,0.00002816653],"about_ca_topic_score_codex":0.001465701,"about_ca_topic_score_gemma":0.0025310428,"teacher_disagreement_score":0.001465701,"about_ca_system_score_codex":0.00037585184,"about_ca_system_score_gemma":0.00016753816,"threshold_uncertainty_score":0.0039004087},"labels":[],"label_agreement":null},{"id":"W2335481389","doi":"10.1109/idam.2014.6912718","title":"A study on tool wear monitoring using time-frequency transformation techniques","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Short-time Fourier transform; Time–frequency analysis; Fault (geology); Transformation (genetics); SIGNAL (programming language); Computer science; Fourier transform; Hilbert–Huang transform; Signal processing; Wavelet transform; Continuous wavelet transform; Instantaneous phase; Fault detection and isolation; Principal component analysis; Artificial intelligence; Pattern recognition (psychology); Wavelet; Electronic engineering; Engineering; Discrete wavelet transform; Fourier analysis; Digital signal processing; Mathematics; Computer vision","score_opus":0.01386737463835182,"score_gpt":0.26355556045452994,"score_spread":0.2496881858161781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2335481389","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38777328,0.008866123,0.5967559,0.00023362908,0.00016735775,0.00013615435,0.000079188525,0.00046085005,0.005527554],"genre_scores_gemma":[0.8835923,0.003982975,0.10815536,0.000065557055,0.0001254119,0.00005625051,0.00010481814,0.00005122322,0.0038660483],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99930835,0.00015666694,0.000032325057,0.0001373683,0.000343988,0.000021337315],"domain_scores_gemma":[0.99847823,0.0007695707,0.00010585609,0.00016782292,0.00045156846,0.000026915735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005302841,0.0003458043,0.0003224202,0.00072391867,0.0001458374,0.0004442116,0.00040619946,0.00049277244,0.00066314504],"category_scores_gemma":[0.0018305411,0.00012070891,0.00029895123,0.0011138694,0.00028407315,0.0007183706,0.00013711373,0.00027084252,0.00020192005],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003072599,0.00013847426,0.004768627,0.00058058323,0.00005837281,0.00021069686,0.00045826889,0.007024177,0.3450359,0.0019312832,0.00040869022,0.6390776],"study_design_scores_gemma":[0.00006441185,0.0045170407,0.05696936,0.00017391765,0.00026260418,0.00365087,0.0006446645,0.28485033,0.61241066,0.0020610958,0.03425827,0.0001367421],"about_ca_topic_score_codex":0.00042756682,"about_ca_topic_score_gemma":0.00029238773,"teacher_disagreement_score":0.00072391867,"about_ca_system_score_codex":0.00014303655,"about_ca_system_score_gemma":0.00018646795,"threshold_uncertainty_score":0.0028044581},"labels":[],"label_agreement":null},{"id":"W2335684409","doi":"10.1515/secm-2013-0188","title":"Effect of cutting tool lead angle on machining forces and surface finish of CFRP laminates","year":2015,"lang":"en","type":"article","venue":"Science and Engineering of Composite Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Materials science; Machining; Surface roughness; Delamination (geology); Composite material; Surface finish; Surface integrity; Mold; Mechanical engineering; Metallurgy; Engineering","score_opus":0.00564370517679174,"score_gpt":0.22849411823595264,"score_spread":0.2228504130591609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2335684409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982059,0.0002914686,0.0010330424,0.000005810814,0.000011851153,0.0000044526755,0.000021687916,0.000031988227,0.0003937484],"genre_scores_gemma":[0.99913293,0.00008110027,0.00056893536,0.0000034459642,0.0000021760031,0.0000023784578,0.000017363582,0.000012356523,0.00017943273],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99966085,0.000046144887,0.000025971927,0.000058733403,0.00012264345,0.00008562203],"domain_scores_gemma":[0.99790704,0.0012562602,0.00039278617,0.00010249743,0.00024150049,0.000099879224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038860718,0.0005373053,0.0003526786,0.0004216858,0.00017633963,0.0004927698,0.0001462153,0.000316101,0.0010309201],"category_scores_gemma":[0.0012842561,0.00031990034,0.00022689665,0.00030533058,0.0002407854,0.00024799188,0.00013571722,0.00029469177,0.0001548481],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017396504,0.00013596755,0.004168572,0.00013674753,0.00002408536,0.0001856373,0.0001326652,0.0077734827,0.97133845,0.000084686726,0.00006809035,0.014211929],"study_design_scores_gemma":[0.000037333277,0.0016189695,0.026119875,0.000013355714,0.000036952068,0.00007675062,0.00007558356,0.009715868,0.96176386,0.00003365917,0.00048320662,0.000024614774],"about_ca_topic_score_codex":0.00049262354,"about_ca_topic_score_gemma":0.0006947867,"teacher_disagreement_score":0.0010309201,"about_ca_system_score_codex":0.00016852416,"about_ca_system_score_gemma":0.00013941748,"threshold_uncertainty_score":0.0034487844},"labels":[],"label_agreement":null},{"id":"W2335752704","doi":"10.3182/20140824-6-za-1003.02515","title":"A Novel Local Time-Frequency Domain Feature Extraction Method for Tool Condition Monitoring Using S-Transform and Genetic Algorithm","year":2014,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Frequency domain; Time domain; Fault (geology); SIGNAL (programming language); Time–frequency analysis; Algorithm; Feature (linguistics); Signal processing; Computation; Condition monitoring; Computer science; Feature extraction; Correlation coefficient; Fault detection and isolation; Genetic algorithm; Engineering; Artificial intelligence; Electronic engineering; Digital signal processing; Computer vision; Machine learning","score_opus":0.006853979121837998,"score_gpt":0.26289760298905823,"score_spread":0.25604362386722024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2335752704","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009980635,0.00009960495,0.9888075,0.000026950012,0.000018363544,0.00001782298,0.000021690123,0.00051491096,0.00051247765],"genre_scores_gemma":[0.22291097,0.0001526741,0.77350676,0.00006481555,0.000030421807,0.00008929587,0.00015413795,0.000085826614,0.0030050715],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975365,0.000024173276,0.000013735688,0.000065855515,0.00012706021,0.000015598542],"domain_scores_gemma":[0.99978596,0.00005876098,0.00003561672,0.000020209472,0.00008994935,0.000009423038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024091516,0.000535753,0.0007259283,0.0008267971,0.00024766935,0.00042347139,0.0007113951,0.0005414774,0.0010117409],"category_scores_gemma":[0.00043324206,0.00022640306,0.00053486973,0.0008134887,0.00023844461,0.000656978,0.00031356205,0.00039574527,0.00040523446],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001293611,0.00011691137,0.0009730353,0.000100156205,0.00006780606,0.00007750625,0.000049164028,0.05651489,0.15653527,0.002113206,0.0013463816,0.7819764],"study_design_scores_gemma":[0.000019522506,0.00010802239,0.0015975076,0.0000069529888,0.000035240486,0.00014951525,0.000014922755,0.96241915,0.033159778,0.00079335686,0.0016716961,0.000024204151],"about_ca_topic_score_codex":0.0021273042,"about_ca_topic_score_gemma":0.0026530027,"teacher_disagreement_score":0.0021273042,"about_ca_system_score_codex":0.00026905866,"about_ca_system_score_gemma":0.00045800806,"threshold_uncertainty_score":0.0042298436},"labels":[],"label_agreement":null},{"id":"W2339563741","doi":"10.1007/978-3-319-17683-3_1","title":"Review of Recent Advances on Reactionless Mechanisms and Parallel Robots","year":2015,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Cognitive science; Psychology","score_opus":0.034257423424929406,"score_gpt":0.27576785528021347,"score_spread":0.24151043185528406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2339563741","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006597594,0.9180528,0.026725374,0.0009604832,0.0034725724,0.00002942974,0.000121864636,0.0003101526,0.04966757],"genre_scores_gemma":[0.0056352606,0.909264,0.019411957,0.0011109188,0.003082806,0.00006026161,0.00044632988,0.00013730193,0.060851082],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996948,0.000025513138,0.000020051866,0.00006162759,0.00017180532,0.000026170874],"domain_scores_gemma":[0.99973816,0.000112023015,0.000025419333,0.000020953126,0.00008172286,0.000021688855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038513835,0.0009461611,0.0010545332,0.0017803616,0.00036364814,0.0013117646,0.0014315465,0.0009227238,0.02004818],"category_scores_gemma":[0.00069360575,0.00058145006,0.00055018853,0.0032266162,0.0005747651,0.0026883716,0.0010700683,0.0012533624,0.011711654],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000559977,0.00006580616,0.00006672335,0.005647389,0.000045482633,0.00006806467,0.000053422224,0.00313908,0.0058032847,0.033163633,0.122004084,0.829887],"study_design_scores_gemma":[0.000005936055,0.000038973005,0.00012556525,0.0004984693,0.000021265982,0.0001885637,0.0000143009065,0.0007034915,0.00061621016,0.012799981,0.9849717,0.000015553242],"about_ca_topic_score_codex":0.00039080088,"about_ca_topic_score_gemma":0.0010374824,"teacher_disagreement_score":0.02004818,"about_ca_system_score_codex":0.00048309003,"about_ca_system_score_gemma":0.00083405484,"threshold_uncertainty_score":0.0670678},"labels":[],"label_agreement":null},{"id":"W2341114807","doi":"10.3390/lubricants4020010","title":"Influence of Workpiece Material on Tool Wear Performance and Tribofilm Formation in Machining Hardened Steel","year":2016,"lang":"en","type":"article","venue":"Lubricants","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Machining; Metallurgy; Scanning electron microscope; Ceramic; Tool wear; Hardened steel; Carbide; Tribology; X-ray photoelectron spectroscopy; Composite material","score_opus":0.005706718111887447,"score_gpt":0.20268272031244738,"score_spread":0.19697600220055994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2341114807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992249,0.00030268508,0.0003114555,0.000004216014,0.0000026313714,0.000004838563,0.000016495047,0.000009105079,0.00012358869],"genre_scores_gemma":[0.9992193,0.000081660975,0.00044728132,0.000004264963,0.0000016390745,0.0000028726217,0.00003232819,0.000007494093,0.00020315619],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99951136,0.000069715265,0.00004279774,0.00006688422,0.00021168773,0.0000974854],"domain_scores_gemma":[0.9993876,0.00022918721,0.0001457788,0.000060606315,0.00012078562,0.000055917775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003465287,0.00029244486,0.00039230572,0.0004831359,0.00025104865,0.00047551238,0.00028171935,0.00042219844,0.00059616595],"category_scores_gemma":[0.0010351973,0.00022795917,0.0002797217,0.00026624755,0.00023264579,0.00024273778,0.000185824,0.0002557337,0.00015813149],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024526694,0.00002028882,0.0008529686,0.00006935273,0.00000836807,0.00008336524,0.00008714823,0.0002577273,0.9964515,0.000006852811,0.000008457252,0.0019086478],"study_design_scores_gemma":[0.000014486064,0.0013109599,0.025054218,0.000007657718,0.000023287455,0.00018736451,0.000104803796,0.0012559255,0.97167486,0.000011237068,0.00034214594,0.000013087032],"about_ca_topic_score_codex":0.00079233974,"about_ca_topic_score_gemma":0.0013336996,"teacher_disagreement_score":0.00079233974,"about_ca_system_score_codex":0.00020594515,"about_ca_system_score_gemma":0.00011615612,"threshold_uncertainty_score":0.0019943714},"labels":[],"label_agreement":null},{"id":"W2344521202","doi":"10.5267/j.esm.2016.3.001","title":"Influence of machining parameters on surface roughness and dry friction","year":2016,"lang":"en","type":"article","venue":"Engineering Solid Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Surface roughness; Materials science; Surface finish; Metallurgy; Dry friction; Mechanical engineering; Composite material; Engineering","score_opus":0.005151262777766415,"score_gpt":0.2060734523360243,"score_spread":0.20092218955825789,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2344521202","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969614,0.00057271007,0.0017556628,0.00000949512,0.000007735277,0.000012901015,0.000064745866,0.000028588189,0.00058676867],"genre_scores_gemma":[0.9988017,0.000117412026,0.0008679215,0.0000035506418,0.0000018510068,0.0000057335646,0.000045101588,0.0000084383055,0.00014828124],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994955,0.000065354245,0.000049193102,0.0001155946,0.00019674502,0.00007763726],"domain_scores_gemma":[0.99858546,0.00080745446,0.00019461352,0.00019119948,0.00017878898,0.000042475705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046216854,0.000364206,0.00048633906,0.0004161498,0.00018660598,0.00046231417,0.0002526676,0.00039838263,0.0008890527],"category_scores_gemma":[0.0019975682,0.00028547194,0.00021404056,0.00041516815,0.00038309745,0.00038770595,0.00022575918,0.00026853735,0.00016357322],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050172105,0.000044247623,0.006782326,0.00027070596,0.0000353168,0.0002350405,0.0001395885,0.0078016613,0.97119695,0.00008651606,0.00007879232,0.012827081],"study_design_scores_gemma":[0.000040438368,0.0014710773,0.12678432,0.000026495454,0.000078298646,0.00044275733,0.00027826976,0.022854839,0.8458873,0.0001434172,0.0019270956,0.0000657467],"about_ca_topic_score_codex":0.00059294305,"about_ca_topic_score_gemma":0.0011400236,"teacher_disagreement_score":0.0008890527,"about_ca_system_score_codex":0.00016054275,"about_ca_system_score_gemma":0.00010683386,"threshold_uncertainty_score":0.0029742122},"labels":[],"label_agreement":null},{"id":"W2369283953","doi":"","title":"Workpiece's Eccentricity Effect on Processing Accuracy of Turning Process","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Eccentricity (behavior); Process (computing); Surface (topology); Basis (linear algebra); Mechanical engineering; Position (finance); Engineering drawing; Foundation (evidence); Computer science; Engineering; Geometry; Mathematics; Economics; Political science; Law","score_opus":0.008633038824252799,"score_gpt":0.24280035587156018,"score_spread":0.2341673170473074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2369283953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96455795,0.00051955075,0.031837136,0.0000830674,0.000028450344,0.000005774633,0.000020896301,0.00013704528,0.002810267],"genre_scores_gemma":[0.9983677,0.00006629134,0.0012897548,0.0000067783467,0.0000047202307,0.0000011919245,0.000010136075,0.000017859807,0.0002354869],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99920493,0.00013291782,0.000040246356,0.00018379379,0.00030327798,0.00013486852],"domain_scores_gemma":[0.9918651,0.005571124,0.00074685155,0.0006534096,0.0010476126,0.000115983974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008835134,0.00022242886,0.00024144472,0.0003190509,0.00022871069,0.00041971853,0.00025430764,0.0004000146,0.001324953],"category_scores_gemma":[0.008868513,0.00019826792,0.00014592921,0.0002724529,0.00046105,0.00048676645,0.0003647898,0.000356905,0.00029726358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004796372,0.000088241875,0.0409441,0.0003701153,0.00007082838,0.0009969098,0.001304814,0.19278844,0.58252954,0.002921895,0.00062043715,0.17256838],"study_design_scores_gemma":[0.000122009595,0.0017052109,0.14876203,0.00008692516,0.00018614411,0.0017422003,0.00038526393,0.3221573,0.52010095,0.0021470976,0.0024827004,0.00012219638],"about_ca_topic_score_codex":0.00054273306,"about_ca_topic_score_gemma":0.00039862175,"teacher_disagreement_score":0.001324953,"about_ca_system_score_codex":0.00018569047,"about_ca_system_score_gemma":0.00015754919,"threshold_uncertainty_score":0.0046725273},"labels":[],"label_agreement":null},{"id":"W2396464542","doi":"10.1016/j.cirp.2016.04.049","title":"A new hybrid oscillatory orbital process for drilling of composites using superabrasive diamond tools","year":2016,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Diamond; Drilling; Materials science; Surface roughness; Tool wear; Diamond tool; Kinematics; Surface finish; Composite material; Process (computing); Carbide; Mechanical engineering; Diamond turning; Computer science; Machining; Metallurgy; Engineering; Physics","score_opus":0.04620706745006996,"score_gpt":0.3009709757511466,"score_spread":0.25476390830107665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2396464542","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76800257,0.001073657,0.2248335,0.00006219402,0.00010672598,0.00006617861,0.000094913805,0.0004522459,0.0053079417],"genre_scores_gemma":[0.8645818,0.0002702355,0.1327146,0.000016329692,0.000015071361,0.000035820725,0.000076021606,0.000040048577,0.0022499522],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979454,0.000010875495,0.000010200771,0.00003285584,0.00012798619,0.000023484865],"domain_scores_gemma":[0.99985754,0.000030465584,0.000032983873,0.000032599473,0.000029841502,0.000016594175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019594803,0.00025947273,0.00028631883,0.000510857,0.00023169811,0.00041048895,0.0005422384,0.00031965523,0.0009384405],"category_scores_gemma":[0.00018705452,0.00019025216,0.00022828391,0.0004269799,0.00034431246,0.00058547047,0.00059713726,0.00036407565,0.0001634114],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026912638,0.00006675005,0.0007900403,0.00018095813,0.000010893487,0.00012194352,0.000096851596,0.0034991058,0.94384557,0.0021068556,0.0002250536,0.048786763],"study_design_scores_gemma":[0.00013619522,0.0017344764,0.006544647,0.000024080107,0.000057778616,0.0010036249,0.00014661334,0.10598313,0.8675527,0.0015831039,0.015155529,0.00007810121],"about_ca_topic_score_codex":0.00042401973,"about_ca_topic_score_gemma":0.0014661086,"teacher_disagreement_score":0.0009384405,"about_ca_system_score_codex":0.00016889817,"about_ca_system_score_gemma":0.0003169345,"threshold_uncertainty_score":0.0031394362},"labels":[],"label_agreement":null},{"id":"W2397675892","doi":"10.1007/s00170-016-8931-7","title":"Finite strip modeling of the varying dynamics of thin-walled pocket structures during machining","year":2016,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Finite element method; Machining; Vibration; Stiffness; Mechanical engineering; Engineering; Structural engineering; System dynamics; Span (engineering); Computer science; Acoustics; Physics","score_opus":0.00569406720322228,"score_gpt":0.22007918313391647,"score_spread":0.2143851159306942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2397675892","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6979965,0.00038161263,0.28632346,0.00018290548,0.00007138392,0.000036140435,0.00014298318,0.00028178951,0.014583249],"genre_scores_gemma":[0.9940183,0.00006923091,0.0041361335,0.000008021247,0.000004065451,0.000009520108,0.000031552237,0.000021541602,0.0017016832],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999392,0.000016549619,0.0000022689167,0.000011059975,0.000017377195,0.00001348982],"domain_scores_gemma":[0.999811,0.000094154195,0.000026011277,0.000024299621,0.00002723412,0.000017407378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016959566,0.0003204351,0.00031754965,0.00018840937,0.00021470505,0.000485083,0.0006448418,0.0007198375,0.0011515887],"category_scores_gemma":[0.0005974791,0.0003237083,0.0002689681,0.00021673038,0.00057711924,0.0004876774,0.00027710578,0.00037967673,0.00015851222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055554316,0.000024589948,0.00071427604,0.000021292379,0.000009022735,0.0001174406,0.000060584367,0.98204136,0.011347069,0.0023912378,0.00014258178,0.0030750472],"study_design_scores_gemma":[0.0000020111374,0.000007725876,0.00021388223,9.752047e-7,0.0000011778346,0.000008482552,0.0000065559775,0.99915326,0.0003479593,0.00017885686,0.00007717167,0.0000018363447],"about_ca_topic_score_codex":0.00228505,"about_ca_topic_score_gemma":0.0019497576,"teacher_disagreement_score":0.00228505,"about_ca_system_score_codex":0.00026483132,"about_ca_system_score_gemma":0.00034279583,"threshold_uncertainty_score":0.004543543},"labels":[],"label_agreement":null},{"id":"W2402791433","doi":"","title":"Deformation Optimization of Plate Heat Exchangers","year":2016,"lang":"en","type":"article","venue":"Lund University Publications Student Papers (Lund University)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Deformation (meteorology); Heat exchanger; Plate heat exchanger; Materials science; Mechanical engineering; Engineering; Composite material","score_opus":0.0062766402711465445,"score_gpt":0.18416232207083952,"score_spread":0.17788568179969297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402791433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7277376,0.00072155887,0.24439293,0.00022758383,0.00009570846,0.00016534385,0.0001791743,0.00049887324,0.025981266],"genre_scores_gemma":[0.97440004,0.00023498775,0.021035952,0.000013373278,0.0000057715674,0.000045400746,0.000111483794,0.00006085973,0.0040920945],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981445,0.00003977267,0.000007944072,0.000034796,0.00006449071,0.00003852606],"domain_scores_gemma":[0.99985266,0.00006462049,0.00002039624,0.000022704835,0.000029305394,0.000010260217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000310929,0.00055450393,0.00049046334,0.00031328265,0.00028105886,0.0007023802,0.00048698063,0.00051533984,0.0026459908],"category_scores_gemma":[0.00057832676,0.00032458495,0.00053424074,0.00026665095,0.00039304484,0.00039590453,0.00038883134,0.0003805442,0.00043622626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010608534,0.000060783186,0.0006009192,0.000079190315,0.000012356382,0.000053863456,0.000034146622,0.94499797,0.036511417,0.0029225906,0.000254756,0.014365944],"study_design_scores_gemma":[0.000019181225,0.0002010947,0.00095343735,0.0000064953115,0.0000105547815,0.000028888444,0.0000264031,0.97467935,0.022055766,0.00081989105,0.0011880468,0.000010799271],"about_ca_topic_score_codex":0.0010767371,"about_ca_topic_score_gemma":0.0009920727,"teacher_disagreement_score":0.0026459908,"about_ca_system_score_codex":0.0006078589,"about_ca_system_score_gemma":0.00042517955,"threshold_uncertainty_score":0.008851767},"labels":[],"label_agreement":null},{"id":"W2409911107","doi":"10.1016/j.cirp.2016.04.040","title":"Chip geometry and cutting forces in gear shaping","year":2016,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hobbing; Machining; Chip; Kinematics; Rake; Engineering; Mechanical engineering; Process (computing); Geometry; Rake angle; Mechanism (biology); Structural engineering; Computer science; Physics; Mathematics; Classical mechanics","score_opus":0.029320492078417717,"score_gpt":0.2725203499523446,"score_spread":0.24319985787392687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2409911107","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7917954,0.0015144001,0.13134739,0.0006908482,0.00019771571,0.000036781432,0.000073251365,0.00012714748,0.07421707],"genre_scores_gemma":[0.99148023,0.00021260558,0.0031581207,0.000026216343,0.000023248997,0.0000065591817,0.000012716506,0.000038569095,0.0050417962],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998024,0.000061955216,0.000003339839,0.000023316245,0.00007481642,0.000034159464],"domain_scores_gemma":[0.999539,0.00029213578,0.00005363203,0.000026569334,0.000065191016,0.000023449502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033777248,0.0003440741,0.00029100417,0.00044575942,0.0003486709,0.0005818462,0.00051056955,0.00080528745,0.0036772857],"category_scores_gemma":[0.0018403691,0.00034750643,0.00020206065,0.00025079743,0.0009048665,0.0004789636,0.0005230199,0.00038544834,0.00040503114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014944412,0.000053166295,0.0017062814,0.000047299578,0.000011330028,0.00023113491,0.00008856002,0.9104418,0.013666644,0.04399366,0.00083116407,0.028779568],"study_design_scores_gemma":[0.000021988155,0.00013553495,0.005500351,0.000014383211,0.000017558328,0.00015245145,0.00010301794,0.96509695,0.004945163,0.022297071,0.0016904741,0.000025122234],"about_ca_topic_score_codex":0.0022437314,"about_ca_topic_score_gemma":0.0048789307,"teacher_disagreement_score":0.0036772857,"about_ca_system_score_codex":0.0004548389,"about_ca_system_score_gemma":0.0003599222,"threshold_uncertainty_score":0.012301743},"labels":[],"label_agreement":null},{"id":"W2412758731","doi":"10.7736/kspe.2016.33.6.447","title":"3-Axis Milling Algorithm Development for Carbon Fiber Reinforced Polymer (CFRP) Composites","year":2016,"lang":"en","type":"article","venue":"Journal of the Korean Society for Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Composite material; Materials science; Carbon fiber reinforced polymer; Polymer; Composite number","score_opus":0.007626137611308358,"score_gpt":0.21368074731504355,"score_spread":0.20605460970373518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2412758731","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013928171,0.000112834474,0.9820458,0.000044735792,0.000028955557,0.00005468441,0.000048994487,0.0012653354,0.0024703734],"genre_scores_gemma":[0.18005969,0.00023211562,0.815717,0.0000524031,0.000013616794,0.00026470897,0.00024650776,0.000461334,0.0029527475],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998074,0.00003240202,0.00001260273,0.000028095037,0.000100777084,0.000018667914],"domain_scores_gemma":[0.999706,0.000088448825,0.000031471962,0.000024038376,0.00013592043,0.000014046489],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041690248,0.0005569198,0.00037608392,0.00039257357,0.00041063357,0.0005723215,0.0008562856,0.00056196784,0.0031856862],"category_scores_gemma":[0.0007521319,0.00035516,0.0005031204,0.00030792708,0.00019890052,0.00043891312,0.00041394285,0.0005607749,0.0007164546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105444145,0.00008078009,0.002252025,0.00014883629,0.000038144422,0.00016911472,0.00017334489,0.7951908,0.017188232,0.009073113,0.0031178182,0.17246236],"study_design_scores_gemma":[0.000007933387,0.000016062955,0.000103854014,0.0000039749466,0.0000023723724,0.000018740657,0.000007759631,0.995488,0.0022342165,0.00038926894,0.0017245426,0.0000033204071],"about_ca_topic_score_codex":0.0045648376,"about_ca_topic_score_gemma":0.004561954,"teacher_disagreement_score":0.0045648376,"about_ca_system_score_codex":0.00042572647,"about_ca_system_score_gemma":0.0010040753,"threshold_uncertainty_score":0.010657191},"labels":[],"label_agreement":null},{"id":"W2423489173","doi":"10.1007/s00170-016-9023-4","title":"Influence of friction models on FE simulation results of orthogonal cutting process","year":2016,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Sandvik Coromant; Chalmers Tekniska Högskola; VINNOVA","keywords":"Chip formation; Finite element method; Chip; Reliability (semiconductor); Constitutive equation; Cemented carbide; Materials science; Deformation (meteorology); Process (computing); Carbide; Code (set theory); Mechanical engineering; Structural engineering; Engineering; Computer science; Tool wear; Metallurgy; Composite material; Machining; Physics","score_opus":0.00833387695583919,"score_gpt":0.2601992286707393,"score_spread":0.2518653517149001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2423489173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9358467,0.0007109798,0.047247853,0.00016969861,0.00011339521,0.000037854985,0.00035758136,0.0006283884,0.014887612],"genre_scores_gemma":[0.99769294,0.00007600708,0.0015274958,0.000010055182,0.0000035602864,0.000007684243,0.00008269223,0.00005437652,0.00054526184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965334,0.00008887098,0.000024261613,0.000040373692,0.00012123659,0.00007193628],"domain_scores_gemma":[0.9979961,0.0013048598,0.00017031796,0.00013709455,0.0003474748,0.00004416197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047404994,0.0006945626,0.00059074815,0.00076542026,0.00048230487,0.0007713943,0.00053465005,0.0012570939,0.0022915243],"category_scores_gemma":[0.0039779544,0.0003576122,0.0005787155,0.0006064403,0.00037007494,0.00065808155,0.00025774408,0.00038962223,0.00033428625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032363998,0.000094697265,0.002184623,0.00010232801,0.000019179945,0.00014713721,0.00007665227,0.9782235,0.010523489,0.0008135835,0.00041634205,0.0070747337],"study_design_scores_gemma":[0.000010066187,0.000052075255,0.0013237401,0.000012373476,0.000015832107,0.000028305454,0.000024653682,0.9915672,0.0064945878,0.00010456359,0.00035690505,0.000009615634],"about_ca_topic_score_codex":0.006461181,"about_ca_topic_score_gemma":0.0044848938,"teacher_disagreement_score":0.006461181,"about_ca_system_score_codex":0.00045017718,"about_ca_system_score_gemma":0.0003948759,"threshold_uncertainty_score":0.0128471255},"labels":[],"label_agreement":null},{"id":"W2428908028","doi":"10.5267/j.dsl.2016.3.001","title":"Multi-attribute decision making parametric optimization and modeling in hard turning using ceramic insert through grey relational analysis: A case study","year":2016,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":131,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Kalinga Institute of Industrial Technology","keywords":"Insert (composites); Grey relational analysis; Parametric statistics; Engineering drawing; Ceramic; Manufacturing engineering; Engineering; Computer science; Data mining; Materials science; Industrial engineering; Mechanical engineering; Mathematics; Statistics; Metallurgy","score_opus":0.07554028635422036,"score_gpt":0.3398083294877464,"score_spread":0.26426804313352603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2428908028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.834883,0.00023627855,0.16090691,0.0001648784,0.00001242226,0.0001362816,0.00009518362,0.0000480602,0.0035169462],"genre_scores_gemma":[0.9760208,0.00009190427,0.02296205,0.000006320088,0.0000031143425,0.00004430016,0.000026745029,0.0000048239976,0.0008399573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939907,0.00028490814,0.000029198525,0.00007101101,0.00013077474,0.00008505887],"domain_scores_gemma":[0.9987979,0.0009337979,0.00009361331,0.000047377485,0.00008237948,0.000044980756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013907063,0.00056863955,0.00073040096,0.0005250953,0.0005695164,0.0012335095,0.00080123224,0.0011254546,0.0012404096],"category_scores_gemma":[0.0012711532,0.00032214244,0.0011886541,0.0005864478,0.000580825,0.00045674478,0.00052899495,0.00066591235,0.00007628318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014800315,0.00017953852,0.0022098597,0.00011709509,0.000039573133,0.00075381796,0.00020270208,0.9765756,0.0050610392,0.0026340003,0.00012028566,0.011958533],"study_design_scores_gemma":[0.000008264322,0.0001463917,0.00077088067,0.000004974102,0.0000170196,0.000049657487,0.00011508093,0.9959104,0.0019541457,0.0008422493,0.00016995278,0.000010915045],"about_ca_topic_score_codex":0.004545279,"about_ca_topic_score_gemma":0.0048206523,"teacher_disagreement_score":0.004545279,"about_ca_system_score_codex":0.000799651,"about_ca_system_score_gemma":0.0006886609,"threshold_uncertainty_score":0.009037614},"labels":[],"label_agreement":null},{"id":"W24572273","doi":"10.1023/a:1015203721926","title":"The effects of nonlinearity in turning operation","year":2002,"lang":"en","type":"article","venue":"Journal of Engineering Mathematics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Hopf bifurcation; Nonlinear system; Bifurcation; Bifurcation theory; Mathematical analysis; Ode; Turning point; Ordinary differential equation; Computation; Differential equation; Steady state (chemistry); Function (biology); Control theory (sociology); Physics; Period (music)","score_opus":0.004762632387128869,"score_gpt":0.19736641706789151,"score_spread":0.19260378468076264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W24572273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93619233,0.00082235533,0.035570957,0.00077346864,0.00015222993,0.00001734985,0.000055430213,0.00013503646,0.026280785],"genre_scores_gemma":[0.9980014,0.000117016025,0.0003256486,0.000014454242,0.000015418556,0.000002461411,0.000007043461,0.000021637905,0.0014949167],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999777,0.00006143501,0.0000077259965,0.000020099562,0.000068280686,0.00006545314],"domain_scores_gemma":[0.99706787,0.0021993567,0.0001976826,0.00013140286,0.00025440188,0.00014934465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042518138,0.000343663,0.000589774,0.00033614427,0.0005245563,0.00069316966,0.00037297636,0.00081373175,0.0032108221],"category_scores_gemma":[0.00468771,0.00036614214,0.00034520333,0.00021885407,0.0010597995,0.0012408952,0.0007100076,0.00075098925,0.00032213755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015591122,0.00030185044,0.006246943,0.00021037139,0.000053892552,0.0016660811,0.00042063664,0.8233763,0.086250946,0.0507152,0.001298694,0.027899979],"study_design_scores_gemma":[0.000019816105,0.00013323272,0.0063014682,0.000014257223,0.00002338859,0.00034465585,0.0001277296,0.97180647,0.008811098,0.011969746,0.0003837408,0.0000643675],"about_ca_topic_score_codex":0.0016362921,"about_ca_topic_score_gemma":0.0015254319,"teacher_disagreement_score":0.0032108221,"about_ca_system_score_codex":0.00037892713,"about_ca_system_score_gemma":0.00033982703,"threshold_uncertainty_score":0.010741234},"labels":[],"label_agreement":null},{"id":"W2461178960","doi":"10.1115/1.4033933","title":"Feedrate Optimization for Computer Numerically Controlled Machine Tools Using Modeled and Measured Process Constraints","year":2016,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus","funders":"","keywords":"Process (computing); Acceleration; Machine tool; Table (database); Computer science; Task (project management); Point (geometry); Control engineering; Numerical control; Process control; Control theory (sociology); Engineering; Control (management); Mechanical engineering; Mathematics; Machining; Artificial intelligence","score_opus":0.01302235253479839,"score_gpt":0.23150641182042883,"score_spread":0.21848405928563044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2461178960","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13675046,0.00025882822,0.857855,0.00010890121,0.000025909678,0.000074871255,0.000043704345,0.00026180004,0.0046205367],"genre_scores_gemma":[0.92703766,0.00008165472,0.072179265,0.000011286338,0.000004932578,0.000053157106,0.00003607415,0.000030318,0.00056576246],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996594,0.0000835664,0.000019229308,0.00006749856,0.00013617087,0.000034122055],"domain_scores_gemma":[0.99927384,0.00044723347,0.00012548016,0.00003981437,0.000098513796,0.000015210874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096185185,0.00056711945,0.0005752537,0.0003121313,0.0002907748,0.001187871,0.0004603544,0.00053113315,0.0005615333],"category_scores_gemma":[0.0021681592,0.00039304222,0.0003514572,0.0003576596,0.0005522852,0.0006889113,0.0004361672,0.00063809095,0.000085466876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009140647,0.000039214916,0.0004102125,0.00008647483,0.000008806027,0.000019005658,0.00003620784,0.9627198,0.014578609,0.004134225,0.00010643527,0.017769588],"study_design_scores_gemma":[0.000007814367,0.000027308814,0.00009992207,0.000003148681,0.000001954475,0.0000031820437,0.0000028726595,0.99644035,0.003019255,0.00026068432,0.00013083678,0.000002679792],"about_ca_topic_score_codex":0.0052061197,"about_ca_topic_score_gemma":0.0042915116,"teacher_disagreement_score":0.0052061197,"about_ca_system_score_codex":0.00098665,"about_ca_system_score_gemma":0.0014818425,"threshold_uncertainty_score":0.010351598},"labels":[],"label_agreement":null},{"id":"W2469209261","doi":"10.1115/1.4033992","title":"Machining Setting Optimization for Formate® Face-Hobbing of Bevel Gears With the Cutting Force and Tool Wear Constraints","year":2016,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Hobbing; Machining; Face (sociological concept); Enhanced Data Rates for GSM Evolution; Bevel; Bevel gear; Mechanical engineering; Tool wear; Engineering; Cutting tool; Structural engineering; Engineering drawing","score_opus":0.011136422168738527,"score_gpt":0.21895619997354088,"score_spread":0.20781977780480235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2469209261","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32234764,0.0003835377,0.66990495,0.0000835367,0.000022665947,0.00026494733,0.0000588906,0.0002751911,0.0066587073],"genre_scores_gemma":[0.8511904,0.00010473963,0.14684913,0.000020549987,0.0000046066407,0.0001204068,0.0000626332,0.000048810612,0.001598861],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996706,0.00009977932,0.000014470868,0.00006259228,0.000101974976,0.00005061394],"domain_scores_gemma":[0.9995432,0.00027130728,0.00006443529,0.000032931926,0.000059839433,0.00002834989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008126256,0.00090061617,0.0009796917,0.0005545317,0.00036596452,0.0008250912,0.0006890298,0.0009328959,0.0017360697],"category_scores_gemma":[0.0015542014,0.00054879114,0.0005766703,0.00026871974,0.0003895938,0.00045198464,0.0005718313,0.00065281993,0.00021272177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015717234,0.00020081189,0.0015317812,0.00032762825,0.000039658902,0.0002203225,0.00014808436,0.9023206,0.027563674,0.0019948597,0.0003592465,0.06513611],"study_design_scores_gemma":[0.000028689468,0.00035748063,0.0012531285,0.000016394228,0.000019333007,0.0000921049,0.00008007694,0.9900725,0.006281446,0.0012214481,0.0005614991,0.000015984322],"about_ca_topic_score_codex":0.0014026352,"about_ca_topic_score_gemma":0.0020741867,"teacher_disagreement_score":0.0017360697,"about_ca_system_score_codex":0.00041516617,"about_ca_system_score_gemma":0.00060139067,"threshold_uncertainty_score":0.0058077574},"labels":[],"label_agreement":null},{"id":"W2503310396","doi":"10.17219/dmp/62196","title":"Flexural Properties of Chairside CAD/CAM Materials","year":2016,"lang":"en","type":"article","venue":"Dental and Medical Problems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Flexural strength; Flexural modulus; Nanoceramic; Significant difference; Composite material; Materials science; Crown (dentistry); Three point flexural test; Bending; CEREC; Ceramic; Medicine","score_opus":0.00896413857065599,"score_gpt":0.20135079095487107,"score_spread":0.1923866523842151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2503310396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9283232,0.011908053,0.020445822,0.00018111695,0.00026620715,0.00012180112,0.0016296508,0.00053953676,0.036584593],"genre_scores_gemma":[0.9816735,0.0007729673,0.006869474,0.00010493619,0.000031055217,0.00004363117,0.0007338243,0.00006952905,0.009701106],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964714,0.000016794304,0.000026066258,0.000049125083,0.00023016352,0.000030734187],"domain_scores_gemma":[0.99942255,0.00013190614,0.0001266857,0.000086530585,0.00018234407,0.000050101364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003779889,0.0005414408,0.00019226929,0.0009962944,0.00019126965,0.0003556903,0.00035612597,0.00045940312,0.010209305],"category_scores_gemma":[0.00096571125,0.00023727847,0.00020637663,0.0004873603,0.00019441696,0.00039581757,0.00021969223,0.0004845287,0.0022601385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016815997,0.000067090405,0.002280257,0.0004150459,0.000009790269,0.00022419715,0.000103041864,0.0013065556,0.91712576,0.00068192725,0.0009413639,0.07667685],"study_design_scores_gemma":[0.000014763627,0.0011085168,0.059460495,0.00007448719,0.000052728938,0.0016612513,0.00017725573,0.0046606185,0.9009756,0.00028532246,0.031461947,0.000067051355],"about_ca_topic_score_codex":0.0003187216,"about_ca_topic_score_gemma":0.000759045,"teacher_disagreement_score":0.010209305,"about_ca_system_score_codex":0.0001451212,"about_ca_system_score_gemma":0.00015536649,"threshold_uncertainty_score":0.03415346},"labels":[],"label_agreement":null},{"id":"W2505714040","doi":"10.1016/j.cirp.2016.06.004","title":"Chatter suppression techniques in metal cutting","year":2016,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":705,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"European Research Council","keywords":"Machining; Process (computing); Machine tool; Vibration; Reduction (mathematics); Mechanical engineering; Cutting tool; Computer science; Engineering; Control engineering; Mathematics; Acoustics; Physics","score_opus":0.01736030723831586,"score_gpt":0.274973025427861,"score_spread":0.2576127181895451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2505714040","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.044361893,0.0017703284,0.9439556,0.00011203346,0.00015027965,0.000035862588,0.000019481517,0.0003702907,0.00922427],"genre_scores_gemma":[0.62721354,0.0019339599,0.3469159,0.00015866556,0.00022361755,0.000114039285,0.000080131285,0.00028899664,0.023071114],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996785,0.00010495859,0.000011372408,0.000034648427,0.00013832144,0.000032221586],"domain_scores_gemma":[0.9991454,0.0005233619,0.00006976002,0.00008556465,0.0001334623,0.000042408992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056040677,0.00066027755,0.0005224033,0.00071622315,0.00044468738,0.0003511588,0.00088363624,0.0005854649,0.0029792872],"category_scores_gemma":[0.0017087059,0.0002982583,0.0004036843,0.00053779385,0.0007668629,0.0006106377,0.00070771883,0.0008886419,0.00077981956],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015079111,0.00027407557,0.0010177809,0.0006196593,0.00011014352,0.0006394669,0.00085685315,0.13984469,0.24298063,0.13483907,0.0048658983,0.4724438],"study_design_scores_gemma":[0.000076753335,0.00039257956,0.00077748817,0.00006058731,0.000058506008,0.00062367925,0.00015454186,0.8986615,0.054559905,0.036455292,0.008133733,0.000045448396],"about_ca_topic_score_codex":0.00066047045,"about_ca_topic_score_gemma":0.0013221287,"teacher_disagreement_score":0.0029792872,"about_ca_system_score_codex":0.00016428663,"about_ca_system_score_gemma":0.00028006354,"threshold_uncertainty_score":0.0099666715},"labels":[],"label_agreement":null},{"id":"W2509648798","doi":"10.1016/j.mineng.2016.08.014","title":"Investigating grinding media differences in microstructure, hardness, abrasion and fracture toughness","year":2016,"lang":"en","type":"article","venue":"Minerals Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hatch (Canada); Metso (Canada); McGill University","funders":"","keywords":"Grinding; Abrasion (mechanical); Microstructure; Materials science; Metallurgy; Toughness; Fracture toughness; Composite material","score_opus":0.008914679383860565,"score_gpt":0.19939385740803742,"score_spread":0.19047917802417685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509648798","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974802,0.00025732158,0.0011895592,0.000014440826,0.000009808115,0.000018745168,0.00016863976,0.000028559372,0.0008327918],"genre_scores_gemma":[0.9950094,0.00022550605,0.0030323865,0.00002421449,0.0000073796236,0.000021881895,0.00019533126,0.00003249813,0.001451313],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999783,0.00001700755,0.00001540348,0.00007161218,0.00008150275,0.000031490807],"domain_scores_gemma":[0.9993074,0.00023753097,0.0001532507,0.000058358935,0.00019710328,0.0000463138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040624765,0.00029696076,0.00026372264,0.0003790626,0.0001911464,0.0003812296,0.00027680554,0.0003472314,0.0018585834],"category_scores_gemma":[0.0008359884,0.0001870103,0.0002501939,0.00038314273,0.0003125717,0.0004965748,0.00021172158,0.00043540826,0.00021224748],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031941026,0.000048298247,0.0010393708,0.00003233093,0.000007598515,0.000027932363,0.000027026414,0.00014667356,0.99649185,0.000030897205,0.000016315504,0.0018123679],"study_design_scores_gemma":[0.00001547936,0.0007363428,0.038775593,0.0000044074536,0.000043566102,0.00007000759,0.00008829025,0.0015962315,0.9580337,0.000053884247,0.00057108916,0.000011485338],"about_ca_topic_score_codex":0.0018672921,"about_ca_topic_score_gemma":0.0035780563,"teacher_disagreement_score":0.0018672921,"about_ca_system_score_codex":0.00033924892,"about_ca_system_score_gemma":0.00019662123,"threshold_uncertainty_score":0.006217599},"labels":[],"label_agreement":null},{"id":"W2522525191","doi":"10.1007/s00170-016-9423-5","title":"Chip volume and cutting force calculations in 5-axis CNC machining of free-form surfaces using flat-end mills","year":2016,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Ministry of Trade, Industry and Energy","keywords":"Machining; Chip; Mechanical engineering; Machine tool; Chip formation; Numerical control; End mill; Rotation (mathematics); Process (computing); Volume (thermodynamics); Engineering; Orientation (vector space); Geometry; Engineering drawing; Computer science; Tool wear; Mathematics; Physics","score_opus":0.00744533275213994,"score_gpt":0.2403335980640139,"score_spread":0.23288826531187395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2522525191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9388235,0.00027568036,0.04740074,0.000061663966,0.000028964589,0.000041600877,0.00021220201,0.00033374576,0.0128218215],"genre_scores_gemma":[0.9906267,0.000033713404,0.007958291,0.0000058848123,0.0000026121215,0.000014073593,0.00007337935,0.000043035674,0.0012423522],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997626,0.000028204218,0.000008165572,0.000023840244,0.00014101114,0.00003616268],"domain_scores_gemma":[0.9991228,0.00054328394,0.00005483686,0.000048769234,0.00020983843,0.00002055582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048907794,0.00039569056,0.00041219057,0.0005511687,0.0004726496,0.0005704179,0.0010010431,0.0007830186,0.0021573624],"category_scores_gemma":[0.0010995175,0.0003451227,0.00035993732,0.0005063185,0.00032541598,0.00044569952,0.00027987963,0.00032318343,0.00021964489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016562571,0.000052905365,0.0023810866,0.00008716026,0.000013285948,0.00010985563,0.000098213975,0.9667427,0.011010528,0.001458945,0.00047884637,0.017400904],"study_design_scores_gemma":[0.0000055095325,0.00003352686,0.0018065294,0.0000023598081,0.0000029154583,0.000011179698,0.000018997784,0.99438816,0.0034463063,0.00010611524,0.00017290546,0.0000055072633],"about_ca_topic_score_codex":0.014121889,"about_ca_topic_score_gemma":0.019378362,"teacher_disagreement_score":0.014121889,"about_ca_system_score_codex":0.0006961036,"about_ca_system_score_gemma":0.00078064564,"threshold_uncertainty_score":0.02807939},"labels":[],"label_agreement":null},{"id":"W2522911262","doi":"","title":"Optimization of cold heading preform dies using fem analysis and a multi-criteria taguchi approach","year":2005,"lang":"en","type":"article","venue":"Wire journal international","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Heading (navigation); Taguchi methods; Finite element method; Materials science; Mechanical engineering; Structural engineering; Engineering drawing; Composite material; Engineering; Aerospace engineering","score_opus":0.019432051512074233,"score_gpt":0.2857272863696277,"score_spread":0.26629523485755346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2522911262","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7122705,0.0006176408,0.27949417,0.000053426924,0.000057282003,0.000108160086,0.00012646642,0.00035153254,0.0069207535],"genre_scores_gemma":[0.93093276,0.00019988437,0.06622325,0.000015401922,0.0000073605156,0.000050074563,0.00011215834,0.00006174544,0.002397446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983215,0.000019255978,0.0000067197116,0.000017511311,0.00009156075,0.000032816493],"domain_scores_gemma":[0.9996468,0.0001336939,0.00007569657,0.00002791278,0.00009666903,0.000019295197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047506025,0.00074124656,0.00075495796,0.0005949039,0.0003486897,0.0006826252,0.00045735322,0.0005414692,0.0012450092],"category_scores_gemma":[0.00054458505,0.0004406922,0.00052191626,0.00043150646,0.00027611342,0.000357274,0.00026100312,0.00042324216,0.00016371334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018695625,0.000105432315,0.0013887124,0.00016029632,0.00003259777,0.00012587706,0.00006560266,0.7954581,0.1516404,0.0015620943,0.00033393106,0.048940014],"study_design_scores_gemma":[0.00003610023,0.0009820383,0.0042899046,0.000026495429,0.00006904173,0.000091579685,0.000101292935,0.90371317,0.08838684,0.00086914125,0.001404469,0.000029973617],"about_ca_topic_score_codex":0.0012760995,"about_ca_topic_score_gemma":0.003747106,"teacher_disagreement_score":0.0012760995,"about_ca_system_score_codex":0.0006051825,"about_ca_system_score_gemma":0.00061368244,"threshold_uncertainty_score":0.0043908954},"labels":[],"label_agreement":null},{"id":"W2525505283","doi":"10.1007/s00170-016-9465-8","title":"An investigation into the behavior of the cutting forces in precision turning","year":2016,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Flank; RADIUS; Mechanical engineering; Chip; Chip formation; Component (thermodynamics); Sensitivity (control systems); Cutting tool; Engineering; Structural engineering; Mechanics; Computer science; Tool wear; Physics","score_opus":0.005358263811539326,"score_gpt":0.24818897786163918,"score_spread":0.24283071405009984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2525505283","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9851608,0.0006034437,0.006533924,0.000094170144,0.000019430252,0.000021370548,0.000039751354,0.000093267176,0.007433901],"genre_scores_gemma":[0.99876714,0.00011199002,0.0005443927,0.000006092413,0.0000023734185,0.0000027626588,0.0000182471,0.000008412622,0.0005385722],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999001,0.000012725012,0.0000028103202,0.000011072333,0.000042828062,0.000030432933],"domain_scores_gemma":[0.9991628,0.0006332844,0.00005864136,0.000027541693,0.00009095458,0.000026849864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016196733,0.0001933077,0.0002826451,0.00045106804,0.00035040703,0.00041002492,0.00025598396,0.00046064146,0.0016095801],"category_scores_gemma":[0.0016423638,0.00021399485,0.00027531743,0.00031293847,0.0003647474,0.00024309073,0.00013844775,0.00038214176,0.00013956007],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019117639,0.00037944564,0.014354712,0.00044325215,0.000094132665,0.001297584,0.0008485185,0.2269786,0.6630544,0.010288942,0.0010423557,0.07930631],"study_design_scores_gemma":[0.000058784473,0.0011081867,0.05956468,0.00004743965,0.000044519504,0.00079808576,0.000401452,0.80489826,0.12779683,0.002612541,0.0025981662,0.00007109382],"about_ca_topic_score_codex":0.0018254946,"about_ca_topic_score_gemma":0.0018187534,"teacher_disagreement_score":0.0018254946,"about_ca_system_score_codex":0.00020644,"about_ca_system_score_gemma":0.00020573496,"threshold_uncertainty_score":0.005384624},"labels":[],"label_agreement":null},{"id":"W2527473472","doi":"10.1117/12.2249389","title":"Simulation and optimization of physical phenomena when engine block machining: case study","year":2016,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Narodowe Centrum Badań i Rozwoju","keywords":"Machining; Finite element method; Block (permutation group theory); Mechanical engineering; Stress (linguistics); Computer science; Software; Process (computing); Structural engineering; Engineering; Mathematics","score_opus":0.011044698453481069,"score_gpt":0.2420837628560554,"score_spread":0.23103906440257432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527473472","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9325275,0.00045522166,0.054235622,0.00019437596,0.000031470532,0.00011420683,0.00030245798,0.0002645939,0.011874539],"genre_scores_gemma":[0.98500466,0.00014492981,0.012765238,0.000008632422,0.0000059334006,0.000054028173,0.00009039357,0.000020531947,0.0019054681],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985087,0.000041948908,0.0000072912403,0.00002018066,0.000045171317,0.00003449761],"domain_scores_gemma":[0.9993316,0.00044752492,0.000047449295,0.00005114249,0.00008272392,0.000039716553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039381522,0.00048553196,0.00047429535,0.00042121176,0.0003212809,0.00057951064,0.0005753107,0.0012343057,0.0022919571],"category_scores_gemma":[0.0008670073,0.0002818333,0.0004748289,0.00040277388,0.00032316803,0.00027754682,0.00031503718,0.00039635712,0.0001509459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009592331,0.00014278118,0.0020598024,0.000110840854,0.000015113818,0.00034764965,0.00005977654,0.9850235,0.0038137832,0.0009793456,0.00022385389,0.007127671],"study_design_scores_gemma":[0.00001439414,0.00010817876,0.000874465,0.000003886668,0.000008906638,0.000046964433,0.000033512988,0.99590945,0.0024306276,0.00017725833,0.00038700536,0.000005339487],"about_ca_topic_score_codex":0.0054131374,"about_ca_topic_score_gemma":0.0047890404,"teacher_disagreement_score":0.0054131374,"about_ca_system_score_codex":0.00030367554,"about_ca_system_score_gemma":0.00038410327,"threshold_uncertainty_score":0.010763288},"labels":[],"label_agreement":null},{"id":"W2528880305","doi":"10.1016/j.precisioneng.2016.09.021","title":"Modeling dynamics and stability of variable pitch and helix milling tools for development of a design method to maximize chatter stability","year":2016,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Pratt and Whitney Canada","keywords":"Stability (learning theory); Machinability; Variable (mathematics); Discretization; Focus (optics); Machine tool; Computer science; Control theory (sociology); Machining; Engineering; Mechanical engineering; Mathematics; Artificial intelligence; Machine learning","score_opus":0.03839781086723889,"score_gpt":0.26268586780348485,"score_spread":0.22428805693624596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2528880305","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027153257,0.00012501953,0.9696372,0.000044908415,0.000013372142,0.000031456577,0.00001501198,0.000076046446,0.0029037115],"genre_scores_gemma":[0.89552706,0.00025736247,0.09921465,0.000025894018,0.0000128617185,0.000150346,0.00003709483,0.000049484093,0.004725292],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987805,0.000033818058,0.000005877707,0.000022604232,0.000047907775,0.000011792923],"domain_scores_gemma":[0.9997106,0.0001649206,0.000045280776,0.000015573316,0.000054347198,0.000009271412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055875786,0.0005195905,0.00043916964,0.0003293335,0.0003861308,0.0005350755,0.00068095984,0.00069586054,0.0017933232],"category_scores_gemma":[0.00096900016,0.00039454718,0.0005323112,0.00023846734,0.00038185393,0.00066605955,0.00038440418,0.0005217593,0.00025754288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022068956,0.000017534001,0.00022092785,0.000053471118,0.0000103707935,0.000024098885,0.00006327908,0.9765237,0.009671586,0.0059351875,0.000108295906,0.0073494827],"study_design_scores_gemma":[0.0000019388826,0.00000915925,0.000032927182,0.0000022947202,0.0000021348712,0.00000345632,0.000003607142,0.9985171,0.00086273585,0.00042246754,0.00014055103,0.0000016544066],"about_ca_topic_score_codex":0.0031721068,"about_ca_topic_score_gemma":0.0036920689,"teacher_disagreement_score":0.0031721068,"about_ca_system_score_codex":0.00046146882,"about_ca_system_score_gemma":0.000681651,"threshold_uncertainty_score":0.0063072443},"labels":[],"label_agreement":null},{"id":"W2531848545","doi":"10.82308/23711","title":"Optimization of minimum quantity cooling / lubrication machining of composites through flow visualization","year":2013,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Mitacs","keywords":"Machining; Nozzle; Lubrication; Mechanical engineering; Materials science; Flow (mathematics); Lubricant; Engineering drawing; Mechanics; Engineering","score_opus":0.013223911798224956,"score_gpt":0.23739815189950966,"score_spread":0.2241742401012847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2531848545","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8652922,0.0004843567,0.13047472,0.00007179053,0.000022858354,0.00006609643,0.00007886481,0.00066373544,0.0028452754],"genre_scores_gemma":[0.94008136,0.00013603014,0.059354592,0.000004482563,0.0000026183488,0.000024266848,0.000042991644,0.00004474749,0.0003089176],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99984634,0.000023242805,0.0000074977374,0.000025004472,0.00007018004,0.000027636284],"domain_scores_gemma":[0.9997291,0.00010813276,0.00006378014,0.000025430669,0.000053476633,0.000020107243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004110595,0.00043966726,0.00032853667,0.00041842076,0.00025202543,0.00056694,0.00037185696,0.00030920884,0.00068851985],"category_scores_gemma":[0.0006993545,0.0002250474,0.00025446748,0.00024108266,0.00022484387,0.0003489742,0.00025129577,0.0002569616,0.00011054664],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003605288,0.00015450588,0.002115689,0.00026149204,0.000011901768,0.00011611875,0.00017253694,0.10781428,0.82250834,0.0010516398,0.0002089651,0.06522405],"study_design_scores_gemma":[0.00003908228,0.00066337903,0.004296877,0.000016449978,0.000020130654,0.000093245166,0.00008122539,0.5884227,0.40401822,0.00039478746,0.0019168673,0.000037035545],"about_ca_topic_score_codex":0.0011497763,"about_ca_topic_score_gemma":0.0017367913,"teacher_disagreement_score":0.0011497763,"about_ca_system_score_codex":0.00031933724,"about_ca_system_score_gemma":0.00047082079,"threshold_uncertainty_score":0.0023169518},"labels":[],"label_agreement":null},{"id":"W2532904964","doi":"10.1080/16864360.2016.1240454","title":"Optimal tool orientation generation and chip volume/cutting force predictions for 5-axis CNC machining of curved surfaces using flat-end mills","year":2016,"lang":"en","type":"article","venue":"Computer-Aided Design and Applications","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Machining; Chip; Orientation (vector space); End milling; Volume (thermodynamics); Mechanical engineering; Chip formation; Geometry; Numerical control; Engineering drawing; Materials science; Engineering; Tool wear; Mathematics; Physics","score_opus":0.025283428049759343,"score_gpt":0.2551242458259869,"score_spread":0.22984081777622759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2532904964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7079621,0.00029947463,0.2849251,0.00012110606,0.000038974744,0.00011068427,0.00024769298,0.0007357965,0.0055591203],"genre_scores_gemma":[0.98068124,0.000037859423,0.018487765,0.000007358644,0.0000028023378,0.000017655264,0.00009432961,0.0000320133,0.00063892506],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998559,0.000024784087,0.000006354727,0.000030129328,0.00006189493,0.000020955315],"domain_scores_gemma":[0.99949634,0.00030100305,0.00004882168,0.00002618595,0.000112407564,0.000015207603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000528594,0.0005265172,0.0003693547,0.0004710015,0.00026763894,0.0005117184,0.0004642814,0.0007468937,0.0014833566],"category_scores_gemma":[0.0011639744,0.00036940858,0.00033222968,0.00031137696,0.00027822613,0.00027426294,0.00018797675,0.00032717575,0.00018034154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014584936,0.000056010827,0.0016113629,0.000049776885,0.000007736829,0.000051994077,0.00003604036,0.96860415,0.0060828673,0.0005229837,0.00030828232,0.022522902],"study_design_scores_gemma":[0.0000026055552,0.0000113817805,0.00036421436,0.0000010095038,0.0000010780086,0.000002669385,0.0000033818092,0.9985435,0.0009878691,0.000048919737,0.00003153331,0.0000017946031],"about_ca_topic_score_codex":0.014923052,"about_ca_topic_score_gemma":0.014943029,"teacher_disagreement_score":0.014923052,"about_ca_system_score_codex":0.0005970949,"about_ca_system_score_gemma":0.00086561596,"threshold_uncertainty_score":0.029672384},"labels":[],"label_agreement":null},{"id":"W2534261471","doi":"10.1007/978-3-319-32180-6_26","title":"Force Sensing for Micro/Meso Milling","year":2016,"lang":"en","type":"book-chapter","venue":"Microsystems and nanosystems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Miniaturization; Mechanical engineering; Piezoelectricity; Automotive industry; Process (computing); Tool wear; Materials science; Engineering; Computer science; Machining; Nanotechnology; Aerospace engineering; Composite material","score_opus":0.007746923356859808,"score_gpt":0.19526868826889576,"score_spread":0.18752176491203595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2534261471","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012391214,0.14978257,0.5079371,0.0019778078,0.0038682295,0.0001946673,0.00071586313,0.0031717177,0.3199608],"genre_scores_gemma":[0.12826449,0.05974479,0.26631066,0.0012027752,0.0012711604,0.00019842363,0.00074212387,0.00069430546,0.5415713],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99969745,0.000012959758,0.000008513121,0.00006625453,0.00019623587,0.000018682531],"domain_scores_gemma":[0.99991965,0.000031847016,0.0000071009963,0.000014472651,0.000022621974,0.000004171161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015887221,0.0009281818,0.0005641913,0.000615366,0.00028331907,0.0009235417,0.001071891,0.0009817755,0.015239516],"category_scores_gemma":[0.00028668865,0.0004370754,0.00025833576,0.00067317963,0.0006510408,0.0017847201,0.0007193519,0.00116344,0.0053494764],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000626157,0.000055461056,0.00008398851,0.0011025725,0.000018584798,0.00010339309,0.00012690961,0.0027243255,0.19035763,0.07060538,0.041638583,0.69312054],"study_design_scores_gemma":[0.00001605038,0.00014393184,0.00059820066,0.00035201665,0.000020478887,0.0008252263,0.000075312295,0.026732907,0.18320286,0.05808583,0.7298726,0.0000745979],"about_ca_topic_score_codex":0.00030928108,"about_ca_topic_score_gemma":0.0006921646,"teacher_disagreement_score":0.015239516,"about_ca_system_score_codex":0.00046276656,"about_ca_system_score_gemma":0.0002105648,"threshold_uncertainty_score":0.050981224},"labels":[],"label_agreement":null},{"id":"W2547344027","doi":"10.1109/ccece.2016.7726783","title":"Machine learning for quality prediction in abrasion-resistant material manufacturing process","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Process (computing); Computer science; Abrasion (mechanical); Quality (philosophy); Support vector machine; Product (mathematics); Machine learning; Manufacturing engineering; Process engineering; Artificial intelligence; Engineering; Mechanical engineering; Mathematics","score_opus":0.012359573906714055,"score_gpt":0.26514354322578587,"score_spread":0.2527839693190718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2547344027","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26060662,0.0009035987,0.736171,0.00021038343,0.000043525844,0.000057675683,0.00013787864,0.0010915949,0.00077774824],"genre_scores_gemma":[0.95650095,0.0001758744,0.042702794,0.000022948334,0.000014311878,0.000044082506,0.00016437804,0.000021172571,0.00035352513],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995403,0.000115690775,0.000034527835,0.000102391416,0.00016143109,0.000045647255],"domain_scores_gemma":[0.9987692,0.0007053279,0.00016056924,0.0000867073,0.00025084396,0.000027286682],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009864151,0.0005894821,0.000762336,0.00071487774,0.00027212582,0.00057430915,0.0006961498,0.00071485323,0.0005071962],"category_scores_gemma":[0.0035291757,0.0002679844,0.00052941137,0.0006616492,0.00032839229,0.00061167224,0.00036272022,0.00089073664,0.00017152067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016353407,0.0001477589,0.004747334,0.000095858864,0.00004097657,0.0000753745,0.00004381821,0.86550754,0.005958493,0.0011026881,0.00048066437,0.12163592],"study_design_scores_gemma":[0.0000012677889,0.000012561433,0.00026951512,0.0000011199662,0.0000012217977,0.0000033337283,0.0000014952528,0.9988386,0.00061033317,0.00022938289,0.00002977387,0.0000013501349],"about_ca_topic_score_codex":0.0050812666,"about_ca_topic_score_gemma":0.0022510353,"teacher_disagreement_score":0.0050812666,"about_ca_system_score_codex":0.0005492514,"about_ca_system_score_gemma":0.0005460318,"threshold_uncertainty_score":0.0101034045},"labels":[],"label_agreement":null},{"id":"W2549279743","doi":"10.1177/1687814016671620","title":"Tool wear in disk milling grooving of titanium alloy","year":2016,"lang":"en","type":"article","venue":"Advances in Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Materials science; Tool wear; Delamination (geology); Enhanced Data Rates for GSM Evolution; Titanium alloy; Machining; Metallurgy; Scanning electron microscope; Grinding; Alloy; Composite material; Computer science","score_opus":0.0032271601683301543,"score_gpt":0.20493204937697465,"score_spread":0.2017048892086445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2549279743","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99731344,0.0005195403,0.0017768649,0.00001130953,0.000008651394,0.000010367633,0.00001964941,0.000026642629,0.00031346755],"genre_scores_gemma":[0.99807906,0.00012746414,0.0012525175,0.00001073,0.0000029636526,0.0000046416103,0.00003438227,0.000007110694,0.00048114167],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99957615,0.000038704155,0.000021062397,0.00008693084,0.0002134683,0.00006371871],"domain_scores_gemma":[0.9994972,0.00016092551,0.00008595856,0.00007176349,0.00016417257,0.00002006232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028634066,0.0002436244,0.00032178577,0.00031880793,0.0002874753,0.00025477845,0.00033264296,0.00032951127,0.00041787824],"category_scores_gemma":[0.00086086954,0.00019592467,0.00026716627,0.00023079525,0.000264291,0.0002782569,0.00018908642,0.00018029685,0.0000743904],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001550843,0.000024531093,0.0028356411,0.00014233941,0.000011643553,0.00022947532,0.00021457672,0.0008355013,0.98446923,0.00006126773,0.00006041959,0.010960281],"study_design_scores_gemma":[0.000018580344,0.0012639207,0.03479934,0.000011268668,0.000033661694,0.0005328163,0.0001994248,0.009959917,0.9517271,0.000115503775,0.0013070281,0.000031360807],"about_ca_topic_score_codex":0.0007921163,"about_ca_topic_score_gemma":0.0014059873,"teacher_disagreement_score":0.0007921163,"about_ca_system_score_codex":0.00019985429,"about_ca_system_score_gemma":0.00008971133,"threshold_uncertainty_score":0.0015750527},"labels":[],"label_agreement":null},{"id":"W2552083027","doi":"10.3390/s16111926","title":"Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining","year":2016,"lang":"en","type":"review","venue":"Sensors","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Changsha Science and Technology Project; State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body; Natural Science Foundation of Hunan Province; National Natural Science Foundation of China","keywords":"Machinability; Machining; Component (thermodynamics); Tool wear; Machine tool; Cutting tool; Mechanical engineering; Numerical control; Field (mathematics); Engineering; Computer science","score_opus":0.2700676315064661,"score_gpt":0.47101407950940205,"score_spread":0.20094644800293593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2552083027","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001207058,0.96499246,0.025463738,0.0006026752,0.00060501375,0.00004523656,0.000041819065,0.000053907166,0.006988025],"genre_scores_gemma":[0.01389767,0.95361936,0.025792079,0.00051861146,0.00056158175,0.000110284884,0.000095095005,0.000020849497,0.0053845043],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991731,0.00009976342,0.000067900386,0.00020100901,0.00040887168,0.000049287948],"domain_scores_gemma":[0.99917823,0.0003834034,0.00008862413,0.000055318375,0.00026416074,0.000030188265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011897518,0.0011071728,0.0010127616,0.0028181472,0.0003864808,0.0014336469,0.0015971413,0.0018369019,0.003619501],"category_scores_gemma":[0.0010652285,0.00062637054,0.00088821654,0.002987964,0.0011240082,0.0024879812,0.0009958892,0.002243058,0.002211298],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065013366,0.00017068535,0.000462226,0.017322255,0.00008856374,0.000261827,0.0001944368,0.0021598113,0.026230002,0.037020475,0.0070489417,0.9089757],"study_design_scores_gemma":[0.000013933953,0.00033825892,0.001601782,0.0029314088,0.00011993235,0.0020569828,0.00017036202,0.0032707762,0.022359999,0.015575663,0.95146143,0.00009953139],"about_ca_topic_score_codex":0.0006375475,"about_ca_topic_score_gemma":0.00066046574,"teacher_disagreement_score":0.003619501,"about_ca_system_score_codex":0.0007228468,"about_ca_system_score_gemma":0.0012077643,"threshold_uncertainty_score":0.012108386},"labels":[],"label_agreement":null},{"id":"W2553954891","doi":"10.1007/s00170-016-9757-z","title":"A spline-based method for stability analysis of milling processes","year":2016,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"National Institute for Materials Science; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Floquet theory; Collocation method; Mathematics; Stability (learning theory); Chebyshev filter; Spline (mechanical); Control theory (sociology); B-spline; Applied mathematics; Mathematical analysis; Computer science; Differential equation; Engineering; Nonlinear system; Ordinary differential equation; Structural engineering; Physics","score_opus":0.011209262371383642,"score_gpt":0.2813953592525026,"score_spread":0.27018609688111894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2553954891","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050340057,0.00012348096,0.9942123,0.000016332544,0.000028215316,0.0000122426645,0.000018825878,0.00015648971,0.00039803164],"genre_scores_gemma":[0.3873261,0.0006340546,0.6050888,0.00004390232,0.0001331884,0.00020032558,0.00026970022,0.00037008632,0.0059338203],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99962544,0.00013529405,0.000018893914,0.00004843747,0.00014631273,0.000025560708],"domain_scores_gemma":[0.9992555,0.0004238639,0.00004964854,0.00005039217,0.00018934143,0.00003127256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010200051,0.0005420584,0.0008097825,0.00074357854,0.00040914214,0.00056615216,0.0010342785,0.0009372168,0.0023228233],"category_scores_gemma":[0.0018629425,0.00040917526,0.0010890913,0.0008464294,0.00041023936,0.0005701323,0.0006109387,0.0012258388,0.00062204344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027923138,0.0001577904,0.0006954083,0.00029955184,0.00010416287,0.00006875297,0.00009094194,0.7316373,0.025875522,0.013930302,0.0010998074,0.2257612],"study_design_scores_gemma":[0.0000032421003,0.000012345878,0.00007267211,0.0000032653475,0.000004218012,0.000005104335,0.0000017102142,0.998396,0.0006165012,0.0005425862,0.00033799847,0.0000044843373],"about_ca_topic_score_codex":0.0029532532,"about_ca_topic_score_gemma":0.0026584272,"teacher_disagreement_score":0.0029532532,"about_ca_system_score_codex":0.00031202566,"about_ca_system_score_gemma":0.0007744867,"threshold_uncertainty_score":0.007770598},"labels":[],"label_agreement":null},{"id":"W2554710874","doi":"10.1016/j.promfg.2016.08.030","title":"Numerical Simulation of Chip Ploughing Volume and Forces in 5-axis CNC Micro-milling Using Flat-end Mills","year":2016,"lang":"en","type":"article","venue":"Procedia Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; Ministry of Trade, Industry and Energy","keywords":"Chip formation; Chip; Plough; Shearing (physics); Perpendicular; Volume (thermodynamics); Materials science; Machining; End mill; Mechanical engineering; Engineering drawing; Composite material; Geometry; Engineering; Tool wear; Mathematics; Electrical engineering; Physics","score_opus":0.011649129044376233,"score_gpt":0.23532640705448352,"score_spread":0.22367727801010728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2554710874","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87051415,0.00035842965,0.10860939,0.0002438678,0.0000630785,0.00012225207,0.0003525286,0.00046004276,0.019276217],"genre_scores_gemma":[0.98157376,0.00007386045,0.016034413,0.000021684555,0.000003333979,0.00006247728,0.0000861768,0.000021750044,0.0021226115],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998599,0.000021203548,0.000006170372,0.000021308553,0.000056402554,0.000034977114],"domain_scores_gemma":[0.9995876,0.00020832635,0.000071266695,0.00002912907,0.00007636451,0.000027266258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030459353,0.0003505151,0.0004128625,0.0002731229,0.0004468861,0.000601858,0.0007203594,0.001008936,0.0016864626],"category_scores_gemma":[0.00064702536,0.0003273227,0.00042269763,0.00034784453,0.0005128234,0.00030890005,0.00031625657,0.00031308585,0.00013171905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029328332,0.000024152981,0.00078969606,0.000027334041,0.000005957185,0.00007489838,0.000033604327,0.9935189,0.0031922678,0.0006830569,0.000108120796,0.0015125914],"study_design_scores_gemma":[0.000005453416,0.000011789605,0.00025943218,0.0000016198492,9.851603e-7,0.0000055028218,0.0000059989925,0.9991584,0.00040303246,0.000062802894,0.00008257615,0.0000024530007],"about_ca_topic_score_codex":0.015588066,"about_ca_topic_score_gemma":0.009081071,"teacher_disagreement_score":0.015588066,"about_ca_system_score_codex":0.0008912465,"about_ca_system_score_gemma":0.0008868492,"threshold_uncertainty_score":0.030994713},"labels":[],"label_agreement":null},{"id":"W2554848325","doi":"10.1016/j.promfg.2016.08.009","title":"Development of Multi-degrees of Freedom Optical Table Dynamometer","year":2016,"lang":"en","type":"article","venue":"Procedia Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Dynamometer; Strain gauge; Piezoelectricity; Vibration; Transducer; Acoustics; Amplifier; Force transducer; Machining; Mechanical engineering; Piezoelectric sensor; Engineering; Sensitivity (control systems); Bandwidth (computing); Structural engineering; Electronic engineering; Electrical engineering; Physics","score_opus":0.014742730099483525,"score_gpt":0.2247820486505855,"score_spread":0.21003931855110197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2554848325","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14585787,0.0019073877,0.8348371,0.00057603465,0.00069173233,0.00083518407,0.0009644375,0.0029660468,0.0113643175],"genre_scores_gemma":[0.5722627,0.0009976883,0.41396248,0.0002824843,0.000098185854,0.0005574891,0.00057234033,0.000071977694,0.011194685],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990013,0.000073504176,0.0000506188,0.00019551977,0.00061688555,0.00006213252],"domain_scores_gemma":[0.9994468,0.00014218243,0.000075307405,0.0000553694,0.00023391738,0.000046434987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006781733,0.00044236772,0.00064353686,0.00082356186,0.00029383806,0.00059934444,0.001252387,0.00073259306,0.00216405],"category_scores_gemma":[0.0007394465,0.000462091,0.0002836342,0.00056662096,0.0002483847,0.0008064989,0.0005441453,0.00045625374,0.00051087403],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037715244,0.00016188054,0.0049353475,0.00074879464,0.000057380275,0.0003191506,0.0002443428,0.005588014,0.74958146,0.0054488755,0.00402024,0.22851743],"study_design_scores_gemma":[0.00025501027,0.0017728539,0.03156815,0.00017359172,0.00014293203,0.0035456484,0.00025906364,0.24443439,0.6177957,0.0017619897,0.09787572,0.000414926],"about_ca_topic_score_codex":0.0010255099,"about_ca_topic_score_gemma":0.001553122,"teacher_disagreement_score":0.00216405,"about_ca_system_score_codex":0.00050904974,"about_ca_system_score_gemma":0.0009655134,"threshold_uncertainty_score":0.0072394013},"labels":[],"label_agreement":null},{"id":"W2555275373","doi":"","title":"Design and Analysis of a Collision Detector for Hybrid Robotic Machine Tools","year":2015,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Capacitive sensing; Detector; Collision; Capacitor; Collision detection; Capacitance; Computer science; Robot end effector; Fixture; Proximity sensor; Electrical engineering; Engineering; Robot; Simulation; Electronic engineering; Artificial intelligence; Mechanical engineering; Voltage; Physics","score_opus":0.2399899140660205,"score_gpt":0.49811882593934337,"score_spread":0.2581289118733229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2555275373","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053988054,0.0008426158,0.94052297,0.00021174461,0.00007572687,0.00021427634,0.000084181695,0.00087644666,0.003183997],"genre_scores_gemma":[0.7790635,0.00043182695,0.21612819,0.00015129581,0.000043889442,0.00019332675,0.00008161734,0.000046692807,0.0038595372],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999003,0.000109890316,0.00002583058,0.00019397376,0.0006065262,0.00006081535],"domain_scores_gemma":[0.99938345,0.00017114209,0.00013917219,0.0000530309,0.00022130797,0.00003182053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047159204,0.00049324357,0.00076688995,0.0004556617,0.00029221355,0.00089046854,0.0017907438,0.0010702804,0.0010894488],"category_scores_gemma":[0.0008509556,0.00036607304,0.00047760794,0.00041057487,0.00041712745,0.00067945814,0.00044709592,0.00035707973,0.0003952853],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035933554,0.00013626827,0.0025514022,0.00074531575,0.00021032343,0.0008227646,0.0003044835,0.07238487,0.8192336,0.01063853,0.0019642336,0.09064889],"study_design_scores_gemma":[0.00008041796,0.0018028425,0.0034013751,0.000046993617,0.000093467956,0.0012848739,0.00010058556,0.6564019,0.3124018,0.0014397001,0.022846777,0.00009927311],"about_ca_topic_score_codex":0.00078154367,"about_ca_topic_score_gemma":0.00060889736,"teacher_disagreement_score":0.0017907438,"about_ca_system_score_codex":0.0010328542,"about_ca_system_score_gemma":0.0007030496,"threshold_uncertainty_score":0.007493973},"labels":[],"label_agreement":null},{"id":"W2555452324","doi":"","title":"Calibration of Machine Tools Using on Machine Probing of an Indigenous Artefact","year":2016,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec","keywords":"Humanities; Physics; Art","score_opus":0.010842601542590155,"score_gpt":0.23490319746530097,"score_spread":0.22406059592271083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2555452324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68221676,0.00026343128,0.31440967,0.000024264618,0.000028366641,0.00011069277,0.0000776196,0.00041717524,0.0024520925],"genre_scores_gemma":[0.9413683,0.00006808184,0.058021042,0.000009467723,0.000006336483,0.000030197394,0.00006187493,0.000049313883,0.0003854007],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99784505,0.0003968867,0.00007259787,0.00047836523,0.001128717,0.00007835162],"domain_scores_gemma":[0.997733,0.00057764945,0.0004155902,0.00085845846,0.00038920363,0.000026081681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012484363,0.0005457053,0.00042666355,0.0006887357,0.00026659505,0.0006856341,0.0007328092,0.00058819575,0.00048711314],"category_scores_gemma":[0.003959005,0.00024239457,0.00031345623,0.0007401702,0.00070621044,0.00048049158,0.0006006363,0.00028726624,0.00019730859],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032297327,0.00012744703,0.034208898,0.00025994531,0.00009946469,0.00017255821,0.0010123599,0.043966178,0.6878152,0.0010323476,0.0002563674,0.23072623],"study_design_scores_gemma":[0.000039159317,0.0015201718,0.2482264,0.000061381696,0.00012288282,0.0009528164,0.0005558376,0.19405118,0.54146445,0.0020633345,0.010828861,0.00011352648],"about_ca_topic_score_codex":0.0011472251,"about_ca_topic_score_gemma":0.0030335574,"teacher_disagreement_score":0.0012484363,"about_ca_system_score_codex":0.00046242037,"about_ca_system_score_gemma":0.00036477362,"threshold_uncertainty_score":0.0066024065},"labels":[],"label_agreement":null},{"id":"W2555829298","doi":"10.6000/1929-5995.2016.05.03.2","title":"A Review of Backup Mechanism for Reducing Delamination when Drilling Composite Laminates","year":2016,"lang":"en","type":"review","venue":"Journal of Research Updates in Polymer Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Council","keywords":"Delamination (geology); Materials science; Composite laminates; Drill; Composite material; Composite number; Drilling; Backup; Mechanism (biology); Fiber pull-out; Mechanical engineering; Metallurgy; Geology; Engineering","score_opus":0.051999577353773266,"score_gpt":0.41751262155864965,"score_spread":0.3655130442048764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2555829298","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00040603254,0.99732864,0.0004732537,0.00010395102,0.0001683211,0.000010357108,0.000032356038,0.000015068555,0.0014620908],"genre_scores_gemma":[0.0016251061,0.99659073,0.0007393037,0.000074003554,0.00010692366,0.00001344911,0.000045160952,0.0000038308835,0.00080151],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997539,0.000026514543,0.00004563559,0.00005530998,0.00009914439,0.000019478537],"domain_scores_gemma":[0.99966395,0.0001442941,0.000070186776,0.000011421489,0.00008766948,0.000022434067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050653354,0.0009862224,0.0011873682,0.0033537897,0.0003228496,0.0007841476,0.0009037976,0.0009653589,0.004766345],"category_scores_gemma":[0.00075274246,0.00046767274,0.00075680745,0.0022531506,0.00033512292,0.0013425715,0.00045807794,0.0008992553,0.0019983249],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008207896,0.00016435662,0.00020262998,0.052447878,0.000113744165,0.0002261307,0.00008177144,0.00081247865,0.007547701,0.0036246653,0.015504638,0.91919184],"study_design_scores_gemma":[0.000015997919,0.00031655538,0.0010005294,0.005293018,0.00018603014,0.0013504708,0.00006241888,0.00024404554,0.004323357,0.0012525986,0.9859159,0.000039154307],"about_ca_topic_score_codex":0.00089440215,"about_ca_topic_score_gemma":0.0011960133,"teacher_disagreement_score":0.004766345,"about_ca_system_score_codex":0.00029774915,"about_ca_system_score_gemma":0.00074248057,"threshold_uncertainty_score":0.015945017},"labels":[],"label_agreement":null},{"id":"W2556469306","doi":"10.1139/tcsme-2008-0035","title":"MULTI-PARAMETER ANN MODEL FOR FLAT-END MILLING","year":2008,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Surface roughness; Machining; Process (computing); End milling; Factorial experiment; Surface finish; Design of experiments; Set (abstract data type); Response surface methodology; Mechanical engineering; Computer science; Engineering; Machine learning; Materials science; Mathematics; Statistics","score_opus":0.023647061560586637,"score_gpt":0.22093051914868128,"score_spread":0.19728345758809465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2556469306","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15039836,0.00097310025,0.83353317,0.00029445,0.000114593626,0.00009669659,0.00049028714,0.0010609403,0.013038407],"genre_scores_gemma":[0.9480893,0.00035641147,0.04033895,0.00005585682,0.00002177332,0.00026439113,0.000376829,0.00004025948,0.010456247],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984443,0.00003575671,0.000010176521,0.000047416048,0.00004177004,0.000020527908],"domain_scores_gemma":[0.9997242,0.00014207832,0.000029395951,0.000016383232,0.00007973361,0.000008158976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036500357,0.0006489565,0.0006512282,0.0003324261,0.000320312,0.00070642075,0.00079471717,0.0011266994,0.0023301467],"category_scores_gemma":[0.0008749353,0.00039438513,0.0005178398,0.0003372007,0.00024894945,0.0005798866,0.0003492451,0.00080990366,0.0005194328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018086868,0.000009303027,0.00015181836,0.000012164333,0.000008412996,0.000018667255,0.0000047035505,0.9953446,0.00041369424,0.00019963188,0.00009138193,0.003727588],"study_design_scores_gemma":[8.939554e-7,0.0000038012222,0.000058546742,0.0000011213867,0.0000010881506,0.000001689851,6.2701116e-7,0.9996916,0.000081280145,0.00010813716,0.000050004714,0.0000012592806],"about_ca_topic_score_codex":0.008921033,"about_ca_topic_score_gemma":0.0075758826,"teacher_disagreement_score":0.008921033,"about_ca_system_score_codex":0.0006267187,"about_ca_system_score_gemma":0.00055973814,"threshold_uncertainty_score":0.017738223},"labels":[],"label_agreement":null},{"id":"W2560406185","doi":"10.1115/1.4035421","title":"A Generic and Efficient Approach to Determining Locations and Orientations of Complex Standard and Worn Wheels for Cutter Flute Grinding Using Characteristics of Virtual Grinding Curves","year":2016,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Flute; Grinding; Machining; Kinematics; Rake; Parametric statistics; Grinding wheel; Orientation (vector space); Engineering; Computer science; Mechanical engineering; Engineering drawing; Acoustics; Geometry; Mathematics; Physics","score_opus":0.020229311161469605,"score_gpt":0.24833505204385734,"score_spread":0.22810574088238772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2560406185","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049644886,0.000052030566,0.9933113,0.000013484862,0.000010432007,0.000035030687,0.00003624713,0.00071167666,0.00086537184],"genre_scores_gemma":[0.13725579,0.00025568763,0.86010027,0.000019104142,0.000013130722,0.00008530153,0.00037173496,0.00029475897,0.0016041065],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99939513,0.000043278033,0.000029329523,0.00013631453,0.00033773226,0.000058255562],"domain_scores_gemma":[0.99958926,0.00006131356,0.000053481905,0.00009917326,0.00017168744,0.000025080284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032813003,0.0011001361,0.00088478846,0.0014331281,0.00035424193,0.0012171153,0.0015662786,0.0006735781,0.0027420619],"category_scores_gemma":[0.001232793,0.0005757087,0.001024731,0.0009896443,0.000489205,0.0009183406,0.0011333947,0.0010036167,0.0009382295],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010322446,0.00008881024,0.0032181507,0.00043056245,0.00005099573,0.0003030376,0.0005423829,0.19612195,0.12351143,0.02638229,0.0036623152,0.6455848],"study_design_scores_gemma":[0.000020081803,0.00007240941,0.0016790149,0.00003104546,0.000026433814,0.00043947797,0.00013801962,0.953152,0.027360955,0.00505511,0.01195368,0.0000716393],"about_ca_topic_score_codex":0.004895098,"about_ca_topic_score_gemma":0.0066182916,"teacher_disagreement_score":0.004895098,"about_ca_system_score_codex":0.0005934833,"about_ca_system_score_gemma":0.0011724555,"threshold_uncertainty_score":0.0097332},"labels":[],"label_agreement":null},{"id":"W2564610014","doi":"","title":"Design of a Three-Component Force Sensor for Meso-Milling Applications","year":2015,"lang":"en","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Component (thermodynamics); Mechanical engineering; Engineering; Computer science; Physics","score_opus":0.019460612926726708,"score_gpt":0.25133294239436954,"score_spread":0.23187232946764283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2564610014","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13848022,0.00076106505,0.8496735,0.0005402128,0.00019753406,0.00042507175,0.00025276703,0.0013294016,0.00834012],"genre_scores_gemma":[0.5387974,0.0006522937,0.45269847,0.0001888243,0.00003489256,0.0002575714,0.0001876109,0.000057245215,0.007125788],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999798,0.000013013776,0.00000783448,0.000051785195,0.00011139721,0.000017862723],"domain_scores_gemma":[0.9998684,0.000020748943,0.000020121593,0.000009694886,0.000066328386,0.000014732523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018691849,0.00035772557,0.00035542066,0.00023140186,0.00021780301,0.00048247984,0.00061402464,0.00054250157,0.001135813],"category_scores_gemma":[0.00019359436,0.0002637224,0.0002015423,0.000207059,0.00015635761,0.0004089606,0.00023254311,0.00037355,0.00066192297],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006938493,0.00004441283,0.00051107816,0.00014484386,0.00001309923,0.00010474524,0.0000880821,0.0057770126,0.9495001,0.0028237987,0.0011766985,0.03974684],"study_design_scores_gemma":[0.000030367564,0.00048544983,0.0018784789,0.000022040284,0.000030025853,0.0004871254,0.00007090712,0.16618192,0.8092738,0.0006621462,0.020840254,0.000037542875],"about_ca_topic_score_codex":0.00037408722,"about_ca_topic_score_gemma":0.0007146761,"teacher_disagreement_score":0.001135813,"about_ca_system_score_codex":0.00034032323,"about_ca_system_score_gemma":0.0006481622,"threshold_uncertainty_score":0.0037997365},"labels":[],"label_agreement":null},{"id":"W2567095457","doi":"10.1007/s00170-016-9776-9","title":"On modeling the deformations and tool-workpiece interactions during machining metal matrix composites","year":2016,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Institute of Population and Public Health; King Saud University","keywords":"Machining; Finite element method; Mechanical engineering; Transient (computer programming); Process (computing); Materials science; Deformation (meteorology); Matrix (chemical analysis); Structural engineering; Computer science; Engineering; Composite material","score_opus":0.005361141910256787,"score_gpt":0.2425842650429698,"score_spread":0.237223123132713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2567095457","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5755615,0.0013781079,0.38633597,0.0005479947,0.00019201486,0.0001933496,0.0002468062,0.0004303539,0.035113886],"genre_scores_gemma":[0.971283,0.00042700552,0.021251865,0.000046465884,0.000032559907,0.00007183721,0.000085465465,0.00015994042,0.006641857],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981195,0.000044475124,0.00000829574,0.000035075678,0.00005817879,0.000042025596],"domain_scores_gemma":[0.99949825,0.0003380549,0.000057795445,0.00003401954,0.000043315493,0.00002852911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004522587,0.00073398126,0.0007960363,0.0004303304,0.00071196957,0.0010145119,0.0011536288,0.0022764131,0.0024044437],"category_scores_gemma":[0.0012277008,0.00071688415,0.0007593836,0.00050773023,0.000977762,0.0007306646,0.0006514113,0.0008180638,0.0003212016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027270582,0.000029436913,0.00029096086,0.000030421403,0.000006968155,0.000052733078,0.000047016638,0.99183273,0.0035542694,0.0010626486,0.00007421359,0.0029912626],"study_design_scores_gemma":[0.0000024825363,0.000010764484,0.00014453563,0.0000019955924,0.0000020033262,0.00000688542,0.000009958093,0.9989642,0.0005196308,0.00019098927,0.00014320748,0.0000033913097],"about_ca_topic_score_codex":0.017552363,"about_ca_topic_score_gemma":0.015070951,"teacher_disagreement_score":0.017552363,"about_ca_system_score_codex":0.00060389494,"about_ca_system_score_gemma":0.0010006045,"threshold_uncertainty_score":0.034900427},"labels":[],"label_agreement":null},{"id":"W2569186366","doi":"10.1109/iecon.2016.7793371","title":"Identification of frequency response functions of a flexible robot as tool-holder for robotic grinding process","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hydro-Québec; École de Technologie Supérieure","funders":"","keywords":"Frequency response; Grinding; Autoregressive model; Control theory (sociology); Acceleration; System identification; Robot; Identification (biology); Vibration; Process (computing); Engineering; Control engineering; Computer science; Displacement (psychology); Artificial intelligence; Mathematics; Acoustics; Data modeling; Mechanical engineering; Physics","score_opus":0.015182669628123174,"score_gpt":0.27593073342857,"score_spread":0.2607480638004468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2569186366","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72444874,0.00017839756,0.27308124,0.00010526993,0.000018045337,0.000056366225,0.00008299557,0.00065059814,0.0013782938],"genre_scores_gemma":[0.9876751,0.000039218114,0.011722824,0.000005145823,0.0000014303654,0.000015490052,0.00003254634,0.0000100159605,0.0004982222],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998535,0.000032060838,0.000004866336,0.000030453988,0.000059623228,0.000019439409],"domain_scores_gemma":[0.9996791,0.00017446984,0.000047019716,0.00003204754,0.000053256037,0.000014050827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004798513,0.00041564766,0.0003233098,0.0003051487,0.00019119818,0.00022122287,0.00035300254,0.0005313461,0.00087293464],"category_scores_gemma":[0.00087014766,0.00014451347,0.00030254707,0.00014431022,0.00023245376,0.00026916384,0.00016414977,0.0002924733,0.00023341276],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009101979,0.00020103322,0.00880946,0.00042849348,0.000054807846,0.00056966796,0.0004054835,0.2942385,0.5628224,0.0011111033,0.00047336143,0.12997553],"study_design_scores_gemma":[0.00001798961,0.00053516886,0.017285682,0.000014173756,0.000022364726,0.00015786481,0.00010113451,0.9073875,0.07350418,0.00036625084,0.0005795502,0.000028128858],"about_ca_topic_score_codex":0.0019820405,"about_ca_topic_score_gemma":0.0017801939,"teacher_disagreement_score":0.0019820405,"about_ca_system_score_codex":0.00019108427,"about_ca_system_score_gemma":0.0002559664,"threshold_uncertainty_score":0.0039409995},"labels":[],"label_agreement":null},{"id":"W2572218965","doi":"10.1038/srep40007","title":"Thermal grill conditioning: Effect on contact heat evoked potentials","year":2017,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Universität Zürich; Eidgenössische Technische Hochschule Zürich; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Michael Smith Health Research BC; National Science Foundation","keywords":"Conditioning; Thermal; Neuroscience; Thermodynamics; Psychology; Physics","score_opus":0.008112377484554761,"score_gpt":0.2507897229417714,"score_spread":0.24267734545721661,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2572218965","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985911,0.00019950127,0.0005842836,0.000014838044,0.0000074656564,0.00004089198,0.000031573993,0.000013477442,0.00051682873],"genre_scores_gemma":[0.9992176,0.00007058413,0.00039312357,0.000020547679,0.0000071389977,0.00003053303,0.000034172645,0.000004000584,0.00022225741],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998566,0.00002946856,0.0000073186466,0.00004389471,0.000029846284,0.00003291304],"domain_scores_gemma":[0.9997824,0.00006657559,0.000038459995,0.000026927537,0.000021147522,0.00006448434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030179287,0.00053354405,0.0004060674,0.000112251546,0.00012779927,0.00012977677,0.00012202823,0.00024461056,0.0026916463],"category_scores_gemma":[0.0007804199,0.00010903293,0.00012702474,0.00009653501,0.0005432625,0.0001721656,0.00021854589,0.0003267714,0.000117075084],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0063343616,0.00033316645,0.002724583,0.00013011832,0.000014127962,0.00019837743,0.0001313525,0.00007032926,0.9810549,0.00004886893,0.00003758194,0.0089222565],"study_design_scores_gemma":[0.0005501324,0.03532162,0.4404637,0.00002215463,0.00011263052,0.002199468,0.00016462848,0.0010634,0.5188578,0.00024219185,0.000978699,0.000023639688],"about_ca_topic_score_codex":0.0004570771,"about_ca_topic_score_gemma":0.00046737012,"teacher_disagreement_score":0.0026916463,"about_ca_system_score_codex":0.00009698658,"about_ca_system_score_gemma":0.00013722909,"threshold_uncertainty_score":0.009004474},"labels":[],"label_agreement":null},{"id":"W2586082970","doi":"10.1115/imece2016-65748","title":"Tool Pre-Failure Monitoring in Intermittent Cutting Operations","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"","keywords":"Breakage; Acoustic emission; Machining; Tool wear; Machine tool; Cutting tool; Catastrophic failure; SIGNAL (programming language); Process (computing); Computer science; Work (physics); Condition monitoring; Mechanical engineering; Engineering; Materials science","score_opus":0.006209653146823696,"score_gpt":0.23375293333238567,"score_spread":0.22754328018556197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586082970","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9866328,0.00026368327,0.0124770235,0.000013126478,0.000009747786,0.00001585043,0.000070549526,0.00013920013,0.00037791912],"genre_scores_gemma":[0.99669266,0.0000605629,0.0029523068,0.000008900671,0.000004905728,0.000012295536,0.000040707688,0.000008187961,0.00021944316],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999706,0.000024123508,0.000011091402,0.00007201421,0.00014956096,0.000037252605],"domain_scores_gemma":[0.99923885,0.00028820767,0.00021086287,0.00007459141,0.00015117881,0.000036316567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023740859,0.00029742037,0.0003015323,0.0006602596,0.00012473743,0.00022174195,0.0004993375,0.00047038298,0.00072237325],"category_scores_gemma":[0.0008683913,0.00014777039,0.00013497178,0.0003080234,0.0002544767,0.00040996278,0.00027209573,0.00030512805,0.00012196438],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006700247,0.00015105511,0.017669525,0.0002760043,0.000023622122,0.00034321297,0.0002729881,0.0028071555,0.91445345,0.00008138064,0.00018050607,0.063071035],"study_design_scores_gemma":[0.000035646215,0.0034961903,0.25371155,0.000044823246,0.000077093035,0.0012996702,0.00038284936,0.063564666,0.67532873,0.00041811253,0.0015734817,0.000067173925],"about_ca_topic_score_codex":0.00032670257,"about_ca_topic_score_gemma":0.00042645415,"teacher_disagreement_score":0.00072237325,"about_ca_system_score_codex":0.00009985678,"about_ca_system_score_gemma":0.000072832176,"threshold_uncertainty_score":0.0024166107},"labels":[],"label_agreement":null},{"id":"W2586582129","doi":"10.1115/imece2016-67039","title":"Investigation of Drilling of CFRP-Aluminum Stacks Under Different Cooling Modes","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Materials science; Drilling; Composite material; Delamination (geology); Lubrication; Drill; Stack (abstract data type); Dynamometer; Tool wear; Composite number; Thrust; Aluminium; Machining; Mechanical engineering; Metallurgy; Geology","score_opus":0.0163460330795621,"score_gpt":0.21740114502214555,"score_spread":0.20105511194258346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586582129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976629,0.00018489565,0.0019075297,0.000010767238,0.000008095225,0.0000144201285,0.000039127197,0.000028282371,0.00014406804],"genre_scores_gemma":[0.99536246,0.00013562912,0.004057168,0.000008545415,0.0000038229273,0.000014110711,0.000058782913,0.000016949767,0.00034258352],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995963,0.00006195562,0.000038131042,0.000073673546,0.00014907766,0.00008089049],"domain_scores_gemma":[0.9989268,0.0003486229,0.00029855708,0.00008424361,0.000291353,0.000050319704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004757543,0.00036515898,0.00028783703,0.0003021752,0.00020770656,0.0002644629,0.00023708511,0.00037604396,0.00058821565],"category_scores_gemma":[0.0013646452,0.00024826513,0.00021274794,0.00016200749,0.00037805917,0.00044773048,0.00025627555,0.00024373313,0.000099428056],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017849059,0.000014561859,0.0011828326,0.00010843671,0.000005482289,0.00010053367,0.00019100074,0.0004093717,0.99489874,0.000025557247,0.00002089141,0.002864166],"study_design_scores_gemma":[0.000008569215,0.0012202988,0.015121374,0.000015663618,0.000026745223,0.00024673878,0.0003057351,0.0026427582,0.97951436,0.000029603838,0.0008484976,0.000019704241],"about_ca_topic_score_codex":0.0005438907,"about_ca_topic_score_gemma":0.0009656082,"teacher_disagreement_score":0.00058821565,"about_ca_system_score_codex":0.0001065681,"about_ca_system_score_gemma":0.00014553138,"threshold_uncertainty_score":0.0025160313},"labels":[],"label_agreement":null},{"id":"W2587288256","doi":"10.1115/imece2016-67064","title":"Analysis and Optimization of Robotized Grinding of Titanium High Pressure Compressor Blades","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"AV&R (Canada); National Research Council Canada","funders":"","keywords":"Vibration; Natural frequency; Gas compressor; Grinding; Grinding wheel; Mechanical engineering; Engineering; Aerospace; Actuator; Process (computing); Robot; Rotational speed; Grind; Acoustics; Computer science; Artificial intelligence; Aerospace engineering; Physics","score_opus":0.004945808780461672,"score_gpt":0.2049536235592116,"score_spread":0.20000781477874993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587288256","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.929825,0.00027124202,0.06771294,0.000026778798,0.000008278851,0.000043763015,0.00009775653,0.00013158869,0.0018825822],"genre_scores_gemma":[0.98370564,0.00007393008,0.015418113,0.000003290116,0.0000012906994,0.00002088486,0.00007862315,0.00002320209,0.0006750993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997507,0.000027233826,0.0000075707576,0.000031831918,0.00015638676,0.000026312911],"domain_scores_gemma":[0.9997042,0.00013090803,0.000044700828,0.000018700517,0.00009333696,0.000008221046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003476221,0.00033180742,0.00045479473,0.00036188163,0.00016409469,0.00036603955,0.00026940825,0.0003505016,0.00082704495],"category_scores_gemma":[0.0006923635,0.00020574397,0.00041494815,0.00025955215,0.00024373544,0.00015193361,0.00009244943,0.00018541375,0.00011919123],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025807237,0.0000925827,0.0026996084,0.0003405409,0.00004486991,0.00022817244,0.00008527303,0.62434775,0.33190733,0.00046515424,0.00020348903,0.03932721],"study_design_scores_gemma":[0.000021140091,0.0007235312,0.018786902,0.000007562436,0.000026416245,0.0000740287,0.00006526608,0.8880871,0.09112654,0.0001842173,0.00087592873,0.000021371647],"about_ca_topic_score_codex":0.004328737,"about_ca_topic_score_gemma":0.005203396,"teacher_disagreement_score":0.004328737,"about_ca_system_score_codex":0.0005589542,"about_ca_system_score_gemma":0.00048638173,"threshold_uncertainty_score":0.0086070895},"labels":[],"label_agreement":null},{"id":"W2589741380","doi":"","title":"Delamination Studies in Drilling of GFRP Composites by using Taguchi Method","year":2013,"lang":"en","type":"article","venue":"Mechanical Engineering Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Delamination (geology); Fibre-reinforced plastic; Drilling; Taguchi methods; Materials science; Orthogonal array; Composite number; Composite material; Drill; Machining; Glass fiber; Composite laminates; Fiber pull-out; Structural engineering; Engineering; Geology; Metallurgy","score_opus":0.07742232413375418,"score_gpt":0.4034607656444386,"score_spread":0.32603844151068445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2589741380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93249285,0.0018473871,0.06475602,0.000025170735,0.000034107194,0.00007614347,0.000048423564,0.000077674085,0.00064216665],"genre_scores_gemma":[0.9060146,0.0012377722,0.09195469,0.000017669787,0.0000064497335,0.00005503899,0.00004274309,0.0000125620945,0.00065838534],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994923,0.00009797789,0.000064653905,0.00005863105,0.0002327979,0.00005357452],"domain_scores_gemma":[0.99926513,0.00030500878,0.00019041728,0.000040453502,0.00016847686,0.000030459181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007178597,0.0004680623,0.0005347945,0.00059267913,0.00020971346,0.00021609402,0.00033840133,0.00029504768,0.00034104462],"category_scores_gemma":[0.0006549316,0.00029442302,0.0003307759,0.00047126893,0.000266874,0.0002807929,0.00019992061,0.0003986282,0.00008628619],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011801465,0.000049623584,0.00045436824,0.00013545345,0.000005883964,0.00005250535,0.00015265298,0.0009643634,0.99131644,0.00005974592,0.000008431243,0.0066824825],"study_design_scores_gemma":[0.000011197172,0.001634955,0.003421693,0.000014965007,0.000034322147,0.0002093383,0.0001643648,0.007798157,0.98599106,0.0000625622,0.00063657714,0.000020884565],"about_ca_topic_score_codex":0.00048838055,"about_ca_topic_score_gemma":0.001413058,"teacher_disagreement_score":0.0007178597,"about_ca_system_score_codex":0.00015609126,"about_ca_system_score_gemma":0.00019224914,"threshold_uncertainty_score":0.0037964582},"labels":[],"label_agreement":null},{"id":"W2594455465","doi":"10.1115/1.4036124","title":"Frequency Domain Updating of Thin-Walled Workpiece Dynamics Using Reduced Order Substructuring Method in Machining","year":2017,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Substructure; Machining; Frequency response; Frequency domain; Finite element method; Reduction (mathematics); Equations of motion; Structural engineering; Kinematics; Engineering; Mechanical engineering; Algorithm; Computer science; Mathematical analysis; Mathematics; Geometry; Physics; Classical mechanics","score_opus":0.00947820301805254,"score_gpt":0.2653936053099361,"score_spread":0.2559154022918836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594455465","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06383635,0.0001575609,0.9341233,0.00004871411,0.000022645956,0.000024089948,0.000028317625,0.00035190574,0.0014072156],"genre_scores_gemma":[0.7339686,0.00027985102,0.26238704,0.000030444597,0.000022265374,0.00007533285,0.00012805362,0.00013505,0.0029733677],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999188,0.000018206432,0.0000042072816,0.000011188667,0.000040553266,0.000007122972],"domain_scores_gemma":[0.9998135,0.00009193405,0.000025589374,0.000028154001,0.000034189765,0.0000066673574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019866836,0.00035945143,0.0004040589,0.00024257999,0.00018434339,0.0002912523,0.00065158674,0.00051342987,0.00078535563],"category_scores_gemma":[0.00058326626,0.00030428934,0.0004742601,0.00017194248,0.0002598161,0.00036933814,0.0001877559,0.00047955336,0.00023966057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027952427,0.000025378238,0.000519157,0.000041379066,0.000015419611,0.000053756477,0.000057340272,0.9457539,0.011964526,0.0018128856,0.00018562221,0.039542627],"study_design_scores_gemma":[0.0000010072929,0.000005143382,0.000052189687,7.0153857e-7,9.033234e-7,0.0000030825454,9.604939e-7,0.99923706,0.0005017102,0.000089170346,0.00010680326,0.0000011872693],"about_ca_topic_score_codex":0.0058787665,"about_ca_topic_score_gemma":0.0048632617,"teacher_disagreement_score":0.0058787665,"about_ca_system_score_codex":0.00029657967,"about_ca_system_score_gemma":0.0004536423,"threshold_uncertainty_score":0.0116891265},"labels":[],"label_agreement":null},{"id":"W2597052691","doi":"10.1109/tase.2017.2667709","title":"Adaptive Neural-Network-Based Active Control of Regenerative Chatter in Micromilling","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Automation Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Control theory (sociology); Actuator; Compensation (psychology); Controller (irrigation); Artificial neural network; Control engineering; Engineering; Adaptive control; Process (computing); Vibration; Control system; Computer science; Active vibration control; Vibration control; Control (management); Artificial intelligence","score_opus":0.011505801750720449,"score_gpt":0.2320656223770998,"score_spread":0.22055982062637935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2597052691","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07210623,0.00081420067,0.92272437,0.00013097381,0.00009780229,0.00003919166,0.000009816761,0.00017641218,0.003901023],"genre_scores_gemma":[0.9777223,0.00017769026,0.020397665,0.000038752263,0.000019284425,0.000040671242,0.000007206421,0.0000075080357,0.0015890214],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998572,0.000027371088,0.000010362623,0.00003428886,0.00004994998,0.000020814528],"domain_scores_gemma":[0.99979085,0.00009688584,0.000041352505,0.0000089826135,0.000053810843,0.0000081369835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042206887,0.00049670826,0.00034182757,0.00015712103,0.00024393886,0.00034753128,0.00079570676,0.00046979755,0.00062751124],"category_scores_gemma":[0.0005485174,0.00018611713,0.00020428767,0.00014893715,0.00048518262,0.0004758058,0.0004397597,0.00044989126,0.00006411476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018397215,0.00007642633,0.00041041026,0.00023919917,0.00004164646,0.00019250004,0.00017759016,0.8389855,0.057426218,0.010044568,0.00038774573,0.09183414],"study_design_scores_gemma":[0.000007526178,0.00005669353,0.000072479495,0.0000040630935,0.0000055308415,0.0000127554795,0.0000050040044,0.9969042,0.0022937737,0.00038407638,0.00024992754,0.0000040160867],"about_ca_topic_score_codex":0.0028650465,"about_ca_topic_score_gemma":0.0032439416,"teacher_disagreement_score":0.0028650465,"about_ca_system_score_codex":0.00031692875,"about_ca_system_score_gemma":0.00037112902,"threshold_uncertainty_score":0.0056967735},"labels":[],"label_agreement":null},{"id":"W2601890323","doi":"10.1088/1361-6439/aa6552","title":"Effects of dimensional size and surface roughness on service performance for a micro Laval nozzle","year":2017,"lang":"en","type":"article","venue":"Journal of Micromechanics and Microengineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Nozzle; Surface roughness; Machining; Mechanical engineering; Materials science; Thrust; Surface finish; Engineering; Composite material","score_opus":0.004309327692496441,"score_gpt":0.20229035011259353,"score_spread":0.19798102242009707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2601890323","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970074,0.00036787582,0.0022037171,0.000020074967,0.000010489825,0.0000050302756,0.000027286362,0.00005465155,0.00030356285],"genre_scores_gemma":[0.9991405,0.00007014715,0.00063584035,0.000006389502,0.000002358414,0.0000017566607,0.000022020258,0.000010000549,0.000111017434],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995252,0.000039700994,0.000033901302,0.000059326052,0.000253769,0.00008807],"domain_scores_gemma":[0.9983777,0.0007209058,0.0003248977,0.00011514214,0.0003725482,0.000088812856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043417333,0.00022395978,0.0003085495,0.00024327992,0.00018710108,0.00040402156,0.00022299562,0.0004103262,0.00060423266],"category_scores_gemma":[0.0015972165,0.00018757676,0.0003570246,0.00019005472,0.00021979069,0.0004129713,0.00020105303,0.000245468,0.00014659992],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002795713,0.000033495824,0.0043808054,0.00007472244,0.000012891322,0.00013624906,0.000073238254,0.0036423632,0.98296803,0.00005526174,0.000074144686,0.008269245],"study_design_scores_gemma":[0.000022759832,0.0021997374,0.03665909,0.000007655529,0.00004670727,0.00032879174,0.00014765366,0.025968747,0.9338949,0.000037522794,0.00063244585,0.000054079737],"about_ca_topic_score_codex":0.00080532854,"about_ca_topic_score_gemma":0.00077349547,"teacher_disagreement_score":0.00080532854,"about_ca_system_score_codex":0.00026359042,"about_ca_system_score_gemma":0.00015695451,"threshold_uncertainty_score":0.0022961497},"labels":[],"label_agreement":null},{"id":"W2604319339","doi":"10.1007/s00170-017-0339-5","title":"Effect of MQL and dry processes on the particle emission and part quality during milling of aluminum alloys","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal; Université du Québec à Trois-Rivières","funders":"","keywords":"Lubrication; Machining; Lubricant; Materials science; Mist; Coolant; Metallurgy; Surface roughness; Cutting fluid; Surface finish; Particle (ecology); Mechanical engineering; Composite material; Engineering","score_opus":0.008705581776670971,"score_gpt":0.27435037052279704,"score_spread":0.26564478874612607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604319339","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987789,0.0003708309,0.00063393736,0.000018628765,0.000009877277,0.000004407175,0.00003148022,0.00002046715,0.00013149988],"genre_scores_gemma":[0.9990177,0.000097872165,0.00041101343,0.000014876738,0.000005175354,0.0000036316267,0.000034000623,0.00001573432,0.0003999906],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997359,0.00003848521,0.000017171564,0.00006769112,0.00008914707,0.0000516567],"domain_scores_gemma":[0.9993012,0.00032281282,0.0001395126,0.000063437226,0.00013438718,0.00003871912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043761716,0.00025649532,0.00045607393,0.00018296942,0.000391045,0.00053536246,0.0002808221,0.00033785024,0.0008566464],"category_scores_gemma":[0.00082389516,0.00025100843,0.00038064143,0.0001597746,0.00044122813,0.00041111966,0.00025736002,0.0004305491,0.00016316136],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014895868,0.000066908746,0.0017141966,0.00010271965,0.000029209397,0.00009407003,0.00021959802,0.00060297985,0.9906465,0.000042851134,0.00006929994,0.004922061],"study_design_scores_gemma":[0.000028473132,0.00095718296,0.017009107,0.0000057702487,0.00004078833,0.00006556736,0.00010003931,0.0022443063,0.9790373,0.000022893886,0.00046920046,0.000019389176],"about_ca_topic_score_codex":0.0014052002,"about_ca_topic_score_gemma":0.0022333781,"teacher_disagreement_score":0.0014052002,"about_ca_system_score_codex":0.0004346359,"about_ca_system_score_gemma":0.000215493,"threshold_uncertainty_score":0.003153503},"labels":[],"label_agreement":null},{"id":"W2604455451","doi":"10.23977/jemm.2017.21003","title":"Effect of bearing preload on the dynamic characteristics of the spindle-bearing system","year":2017,"lang":"en","type":"article","venue":"Journal of Engineering Mechanics and Machinery","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science and Technology Major Project","keywords":"Preload; Bearing (navigation); Machine tool; Engineering; Finite element method; Machining; Mechanical engineering; Structural engineering; Stiffness; Computer science","score_opus":0.003949416732833069,"score_gpt":0.20631876520157702,"score_spread":0.20236934846874394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604455451","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9885384,0.00056348555,0.008584937,0.000046099314,0.000043084758,0.00001456697,0.00007012393,0.00018899942,0.0019503034],"genre_scores_gemma":[0.9991906,0.0000678342,0.00043613216,0.000008291906,0.000003026862,0.0000034697057,0.00003215958,0.000014183567,0.00024442014],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99974245,0.00003340437,0.000020661031,0.000057375553,0.00009617912,0.0000499746],"domain_scores_gemma":[0.9982445,0.0009430129,0.00025352725,0.00013651905,0.00034266576,0.00007981842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032821795,0.00022888543,0.00022622052,0.00028998108,0.00020948944,0.00025122822,0.00019122698,0.00023365881,0.0013403575],"category_scores_gemma":[0.0021743122,0.00014729056,0.00014803835,0.00014979154,0.00022900723,0.0003343637,0.00018924443,0.00019438453,0.00024111276],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011908747,0.000074505406,0.005228134,0.00034636518,0.000024211697,0.0004947387,0.00026962243,0.019617796,0.94448936,0.0002506011,0.00025694454,0.02775688],"study_design_scores_gemma":[0.00005914216,0.0022460937,0.06362027,0.00004539805,0.00008923873,0.000662411,0.00024735666,0.06485039,0.864038,0.0001524381,0.003921544,0.00006772068],"about_ca_topic_score_codex":0.00064627104,"about_ca_topic_score_gemma":0.00053518923,"teacher_disagreement_score":0.0013403575,"about_ca_system_score_codex":0.00014602554,"about_ca_system_score_gemma":0.00017464971,"threshold_uncertainty_score":0.004483938},"labels":[],"label_agreement":null},{"id":"W2616915511","doi":"10.1007/s00170-017-0460-5","title":"To characterize and optimize the surface quality attributes in slot milling operation","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Polytechnique Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Surface roughness; Quality (philosophy); Machining; Minification; Surface (topology); Mechanical engineering; Surface finish; Selection (genetic algorithm); Engineering drawing; Reliability engineering; Engineering; Mathematical optimization; Process engineering; Computer science; Mathematics; Materials science; Geometry; Machine learning; Composite material","score_opus":0.019982342273332922,"score_gpt":0.2876602424137024,"score_spread":0.2676779001403695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2616915511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97006446,0.00030526044,0.028445885,0.000043169097,0.000014680179,0.000024068891,0.0001244858,0.0001197794,0.00085814064],"genre_scores_gemma":[0.9895132,0.000103116254,0.009777155,0.000011836591,0.0000060230263,0.000010141613,0.0001124038,0.0000371238,0.00042904323],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99976,0.000016338741,0.000008669506,0.00004889509,0.00013435737,0.00003179444],"domain_scores_gemma":[0.9994184,0.00014853304,0.00017453916,0.00006517556,0.00017177402,0.00002155023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032072517,0.00033654715,0.00036318804,0.00022212282,0.00018384434,0.0006633527,0.0002747115,0.00033329087,0.00068843516],"category_scores_gemma":[0.00064102496,0.00015308111,0.00023124857,0.0004946702,0.0002423123,0.000574947,0.00016044344,0.00034543066,0.00023002438],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024189996,0.0000825349,0.0039426824,0.00010948476,0.000014601671,0.000021563434,0.000030942792,0.008630364,0.968933,0.00018967924,0.00013116437,0.017672127],"study_design_scores_gemma":[0.000020840547,0.0012978516,0.024649467,0.000003794455,0.00003251281,0.00007228273,0.00007980957,0.074337445,0.8980578,0.00029145475,0.0011345936,0.000022135006],"about_ca_topic_score_codex":0.00050079677,"about_ca_topic_score_gemma":0.0010178714,"teacher_disagreement_score":0.00068843516,"about_ca_system_score_codex":0.00029275115,"about_ca_system_score_gemma":0.00030189764,"threshold_uncertainty_score":0.0023030639},"labels":[],"label_agreement":null},{"id":"W2617276643","doi":"10.4236/wjm.2017.75013","title":"Artificial Neural Networks Based Integrated Predictive Modelling of Quality Characteristics in CNC Turning of Cantilever Bars","year":2017,"lang":"en","type":"article","venue":"World Journal of Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cégep de Rimouski; Université du Québec à Rimouski","funders":"","keywords":"Artificial neural network; Cantilever; Machining; Sensitivity (control systems); Process (computing); Computer science; Surface roughness; Quality (philosophy); Predictive modelling; Numerical control; Engineering; Artificial intelligence; Machine learning; Mechanical engineering; Structural engineering; Electronic engineering; Materials science","score_opus":0.029856719022463733,"score_gpt":0.26471742127033066,"score_spread":0.23486070224786693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2617276643","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3748621,0.0004676245,0.61869454,0.00016241183,0.000044344044,0.00006735864,0.00008870946,0.000444601,0.0051683253],"genre_scores_gemma":[0.9921462,0.00008702812,0.0069847414,0.000012021286,0.000004309073,0.00004183571,0.00003177998,0.000008471747,0.0006836396],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987125,0.000030219835,0.0000063179027,0.000024079109,0.000051527048,0.000016571677],"domain_scores_gemma":[0.99972206,0.00014538766,0.000039234066,0.000013531183,0.000073811454,0.0000060454627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003933297,0.00042206445,0.00040454316,0.0002695223,0.0002105092,0.0004884986,0.0005472124,0.00058771967,0.00048173376],"category_scores_gemma":[0.0007952982,0.00030032845,0.0003750081,0.0002576834,0.0003839131,0.0003377031,0.00023787668,0.00052920374,0.00007742765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016272283,0.000009121422,0.0002909444,0.0000094457655,0.0000045418283,0.000017053222,0.000008685514,0.9947196,0.0010162934,0.0002110723,0.000027790833,0.0036691811],"study_design_scores_gemma":[5.043795e-7,0.0000047636045,0.00008445648,5.16501e-7,7.8548936e-7,9.820874e-7,7.820174e-7,0.9997199,0.00013877868,0.000037880505,0.000010004574,6.8513884e-7],"about_ca_topic_score_codex":0.013268062,"about_ca_topic_score_gemma":0.008788907,"teacher_disagreement_score":0.013268062,"about_ca_system_score_codex":0.0005043843,"about_ca_system_score_gemma":0.00046964464,"threshold_uncertainty_score":0.026381671},"labels":[],"label_agreement":null},{"id":"W2618548267","doi":"10.5267/j.ijiec.2017.4.004","title":"Modelling and analysis of tool wear and surface roughness in hard turning of AISI D2 steel using response surface methodology","year":2017,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Cooperative Research Facility Center, Toyohashi University of Technology; National Institute of Technology Srinagar","keywords":"Surface roughness; Response surface methodology; Metallurgy; Materials science; Surface (topology); Surface finish; Tool wear; Tool steel; Mechanical engineering; Engineering; Composite material; Mathematics; Machining; Statistics; Geometry","score_opus":0.08965173629967446,"score_gpt":0.33443333782079404,"score_spread":0.24478160152111958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618548267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.838018,0.00034681286,0.15987909,0.000042133037,0.000011493776,0.00006275105,0.0001001719,0.0002545189,0.0012851458],"genre_scores_gemma":[0.99163496,0.000085803855,0.0077992342,0.000003696995,0.0000020543073,0.000025758693,0.000045730078,0.000009961564,0.00039296123],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997309,0.00008229687,0.0000141186365,0.00003565132,0.000106229134,0.000030893338],"domain_scores_gemma":[0.9995772,0.00027023247,0.00004637059,0.00003764786,0.000061180064,0.000007469865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005047794,0.00042963316,0.00046442042,0.00035240065,0.000106991174,0.00042274702,0.00036265593,0.0005913506,0.0003384965],"category_scores_gemma":[0.00072252954,0.00022031629,0.0008067199,0.00026375457,0.00019437174,0.00020232362,0.00013067892,0.00026467026,0.00011329723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021326833,0.00012461595,0.0043686805,0.00036102073,0.00007021022,0.00019681404,0.00016175624,0.82388526,0.1430916,0.0003653021,0.0001015505,0.027059872],"study_design_scores_gemma":[0.000009219244,0.00032142055,0.0053843963,0.0000038878316,0.00001753957,0.000054238222,0.000038481423,0.9742587,0.019525481,0.00015737649,0.0002131614,0.000016096688],"about_ca_topic_score_codex":0.0025675176,"about_ca_topic_score_gemma":0.0017324004,"teacher_disagreement_score":0.0025675176,"about_ca_system_score_codex":0.00018750166,"about_ca_system_score_gemma":0.00021522873,"threshold_uncertainty_score":0.0051051974},"labels":[],"label_agreement":null},{"id":"W2618817885","doi":"10.1016/j.ijmachtools.2018.03.001","title":"Mechanics and dynamics of orbital drilling operations","year":2018,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Academia Sinica; National Science Council","keywords":"Position (finance); Drilling; Chip; Stability (learning theory); Path (computing); Process (computing); Intersection (aeronautics); Orbital motion; Surface (topology); Machine tool; Orbital mechanics; Computer science; Geometry; Mechanics; Mechanical engineering; Engineering; Physics; Classical mechanics; Aerospace engineering; Mathematics","score_opus":0.0059012282084648995,"score_gpt":0.2381717863916151,"score_spread":0.2322705581831502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618817885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90312654,0.0006220249,0.057493214,0.0013005188,0.00010370384,0.000038740505,0.00021693177,0.00006094632,0.037037425],"genre_scores_gemma":[0.99544877,0.0001630288,0.00080527365,0.000013610691,0.000018345954,0.000009720381,0.000025782703,0.000008805046,0.00350658],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99992204,0.000016013892,0.0000031469683,0.000011372488,0.000029789115,0.000017686485],"domain_scores_gemma":[0.99977523,0.0001099761,0.00004648481,0.000008738636,0.000031959575,0.000027618984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013977315,0.00018147207,0.000280336,0.0004958237,0.00042494695,0.00085784105,0.00038373104,0.0004789328,0.0035930495],"category_scores_gemma":[0.0009114979,0.00030486693,0.00022593555,0.000322152,0.0006874701,0.0007766825,0.000621801,0.0004316089,0.00027889857],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015790215,0.00014416216,0.009936423,0.00006306429,0.000027814216,0.00046862342,0.00027957495,0.8696543,0.0075261253,0.091962256,0.0014293126,0.018350424],"study_design_scores_gemma":[0.00000932578,0.000022383185,0.0052104,0.000005345303,0.000003952472,0.00006418902,0.00010537721,0.9849027,0.0002401923,0.008790785,0.0006329881,0.000012366959],"about_ca_topic_score_codex":0.0059676897,"about_ca_topic_score_gemma":0.0045859185,"teacher_disagreement_score":0.0059676897,"about_ca_system_score_codex":0.00031480571,"about_ca_system_score_gemma":0.0005503419,"threshold_uncertainty_score":0.012019992},"labels":[],"label_agreement":null},{"id":"W2618836458","doi":"10.11159/icmie17.110","title":"Optimization of Carbonitrided AISI 1022 Self-drilling Tapping Screw Process Parameters Using Taguchi Approach","year":2017,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Tapping; Taguchi methods; Materials science; Process (computing); Drilling; Computer science; Mechanical engineering; Metallurgy; Composite material; Engineering","score_opus":0.010464945355616803,"score_gpt":0.22316263462576055,"score_spread":0.21269768927014376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618836458","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7829154,0.0046415688,0.20781308,0.00011748109,0.00008003335,0.00049396756,0.00026149966,0.00034645505,0.003330458],"genre_scores_gemma":[0.80747855,0.0024992363,0.18788984,0.0000577332,0.000013005694,0.00027944215,0.00028262302,0.000053738484,0.0014458256],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99917066,0.00013049673,0.00009743023,0.00012541946,0.0004025801,0.00007339426],"domain_scores_gemma":[0.9996222,0.00010456645,0.00011968314,0.00001967982,0.00011737397,0.00001646859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007455752,0.0010147667,0.0007726339,0.0007695224,0.00019467814,0.0007881742,0.0005576831,0.00061402674,0.00047512137],"category_scores_gemma":[0.00064572337,0.00040812112,0.0005961114,0.0009980263,0.00024146521,0.00040557786,0.0002182042,0.0004173826,0.00017029146],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013409804,0.00010986687,0.0005040161,0.00046207273,0.00002613455,0.00007588565,0.000057941954,0.01010123,0.97187716,0.0001702213,0.00006098601,0.016420372],"study_design_scores_gemma":[0.00003502546,0.00095548166,0.0023648872,0.000023635965,0.000095782634,0.00010396234,0.00007064185,0.04090685,0.95361024,0.00011026964,0.0016758787,0.00004729535],"about_ca_topic_score_codex":0.0014104493,"about_ca_topic_score_gemma":0.0043517393,"teacher_disagreement_score":0.0014104493,"about_ca_system_score_codex":0.00048715033,"about_ca_system_score_gemma":0.00060039246,"threshold_uncertainty_score":0.003943026},"labels":[],"label_agreement":null},{"id":"W2619500242","doi":"10.1115/1.4036834","title":"A Reliable and Efficient Approach to Numerically Controlled Programming Optimization for Multiple Largest Tools Cutting Blisks Patch by Patch in the Blisks' Four-Axis Rough Machining","year":2017,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Numerical control; Mechanical engineering; Cutter location; Turbine blade; Machine tool; Engineering drawing; Computer science; Structural engineering; Engineering; Turbine","score_opus":0.01460644154481518,"score_gpt":0.23923803311545186,"score_spread":0.22463159157063667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619500242","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0041647824,0.00026102862,0.9914961,0.0001580871,0.00007699232,0.00007589972,0.00004726949,0.000481052,0.0032388282],"genre_scores_gemma":[0.17311873,0.0003135381,0.81723326,0.0002607729,0.0001231656,0.0007892449,0.00033825467,0.0006481329,0.007174957],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914765,0.00029110213,0.00003354662,0.00014265113,0.00026701493,0.00011791644],"domain_scores_gemma":[0.9973579,0.0019299623,0.00013019577,0.000086788394,0.00039527565,0.00009985093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018824688,0.0020473357,0.0023872035,0.0008586715,0.0007917692,0.0014701008,0.0019890592,0.0018457507,0.0061460007],"category_scores_gemma":[0.0047625666,0.0010791976,0.0015733212,0.0008984195,0.0011478645,0.00090885593,0.002095891,0.003437323,0.0011267365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053126183,0.000060622093,0.00022054405,0.00011351715,0.000036171496,0.00007119313,0.000046666137,0.9607103,0.0009581847,0.009365317,0.0013811209,0.02698325],"study_design_scores_gemma":[0.0000105672125,0.00001355601,0.000023965384,0.000005797543,0.0000030035753,0.0000043855193,0.000007679033,0.9973815,0.00010921576,0.001923551,0.0005134696,0.0000033429872],"about_ca_topic_score_codex":0.011532139,"about_ca_topic_score_gemma":0.009341652,"teacher_disagreement_score":0.011532139,"about_ca_system_score_codex":0.0010326495,"about_ca_system_score_gemma":0.0029802208,"threshold_uncertainty_score":0.022930026},"labels":[],"label_agreement":null},{"id":"W2692066856","doi":"10.1177/0263092317712017","title":"Additive manufacturing for minimizing vibration damages in the water-stop tray of washing machines","year":2017,"lang":"en","type":"article","venue":"Journal of low frequency noise, vibration and active control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tray; Vibration; Accelerometer; Hammer; Impulse (physics); Engineering; Structural engineering; Acoustics; Mechanical engineering; Computer science; Physics","score_opus":0.00831843062902088,"score_gpt":0.24190733797319341,"score_spread":0.23358890734417254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2692066856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86055434,0.0041110865,0.13192163,0.000050840044,0.000061070976,0.00006342165,0.00006199226,0.00014876503,0.0030269115],"genre_scores_gemma":[0.9584517,0.0007945732,0.038930584,0.000015200669,0.000011573073,0.000022886206,0.00003669706,0.000016498314,0.0017203897],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997011,0.000033229822,0.000010250436,0.000036101883,0.00018620653,0.000033170614],"domain_scores_gemma":[0.9997856,0.00004923583,0.00007142855,0.000020922052,0.00006331068,0.000009614644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002777917,0.0004545037,0.00025424195,0.0004960811,0.00018698392,0.0003697454,0.00039802634,0.0003287729,0.00091147405],"category_scores_gemma":[0.00037546328,0.00014851411,0.00025424728,0.00031526524,0.00021524681,0.00031192126,0.0002703469,0.00018155688,0.00022614955],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012297297,0.000036804908,0.0007918637,0.0002815464,0.000014280282,0.000082574144,0.000052392603,0.0054946975,0.96155095,0.0003262299,0.00009154737,0.03115403],"study_design_scores_gemma":[0.000014907277,0.0016975572,0.011599686,0.000038203085,0.00010461124,0.00024120882,0.00015649841,0.020843873,0.9601418,0.00024342797,0.0048972378,0.000021040541],"about_ca_topic_score_codex":0.00033000892,"about_ca_topic_score_gemma":0.0011528521,"teacher_disagreement_score":0.00091147405,"about_ca_system_score_codex":0.00015649051,"about_ca_system_score_gemma":0.0002130114,"threshold_uncertainty_score":0.0030491948},"labels":[],"label_agreement":null},{"id":"W270266920","doi":"","title":"Proceedings of the Third International Meeting on Thermal Manikin Testing, 3IMM, at the National Institute for Working Life, October 12-13, 1999","year":2000,"lang":"en","type":"article","venue":"Gothenburg University Publications Electronic Archive (Gothenburg University)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Working life; Epistemology; Philosophy","score_opus":0.012633696584874699,"score_gpt":0.18966531387066987,"score_spread":0.17703161728579517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W270266920","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027890544,0.065825894,0.18577403,0.032148983,0.09852386,0.003485924,0.0032134103,0.005296287,0.5778411],"genre_scores_gemma":[0.02024837,0.016796447,0.021807497,0.0020498373,0.0047849147,0.0011415919,0.0022058855,0.0011730597,0.92979246],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99789894,0.00046857697,0.00015333199,0.0004599727,0.000808424,0.0002107105],"domain_scores_gemma":[0.99748886,0.00028343056,0.000083063824,0.00016987817,0.0014167934,0.00055789953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003925737,0.0026755382,0.0013939596,0.0011615942,0.0015461147,0.0032853398,0.0024117976,0.0027635652,0.18087621],"category_scores_gemma":[0.0027079426,0.0009796806,0.00087406486,0.00045181552,0.0011336862,0.00227619,0.0033010023,0.003243248,0.10966643],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009858072,0.0006583606,0.0019803583,0.00050382863,0.00005241995,0.0005143582,0.00052722567,0.00047077908,0.01698248,0.0012793948,0.6264521,0.34959295],"study_design_scores_gemma":[0.000064108164,0.00053063495,0.0036983292,0.0004743944,0.000030464838,0.00063571945,0.00036641106,0.0008947482,0.0029495384,0.001077836,0.9892285,0.000049301645],"about_ca_topic_score_codex":0.0021436857,"about_ca_topic_score_gemma":0.006000924,"teacher_disagreement_score":0.18087621,"about_ca_system_score_codex":0.0010520312,"about_ca_system_score_gemma":0.0017393047,"threshold_uncertainty_score":0.6050912},"labels":[],"label_agreement":null},{"id":"W2730445750","doi":"10.1007/s12541-017-0108-2","title":"Numerical simulation of chip ploughing volume in micro ball-end mill machining","year":2017,"lang":"en","type":"article","venue":"International Journal of Precision Engineering and Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Chip formation; Plough; Machining; Chip; Shearing (physics); Ball (mathematics); Mechanical engineering; Volume (thermodynamics); Engineering; Geotechnical engineering; Geometry; Mathematics; Tool wear; Physics","score_opus":0.008789696086179357,"score_gpt":0.2596046489494254,"score_spread":0.25081495286324607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2730445750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8809613,0.00052478723,0.094518214,0.00032493036,0.0001092611,0.00008897252,0.00023641103,0.0005546789,0.02268148],"genre_scores_gemma":[0.99000996,0.000060775918,0.008130484,0.000020091566,0.000005595265,0.000025171143,0.00003798714,0.000026424705,0.0016834973],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981636,0.000029161478,0.00000685657,0.000026123633,0.000076956174,0.000044459244],"domain_scores_gemma":[0.9988777,0.00071334804,0.000116625684,0.00006946354,0.00016243405,0.0000604576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032824549,0.00032381754,0.0006290175,0.00040164316,0.0005532609,0.00076841994,0.0010355563,0.0014572255,0.0024657103],"category_scores_gemma":[0.0015193144,0.00043899388,0.00041008784,0.00041490598,0.0006362267,0.0005073422,0.0003733928,0.0005011556,0.00017853004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006170018,0.000051498228,0.00081301795,0.00004235854,0.000010589827,0.00006742074,0.00004538708,0.9899715,0.005129005,0.0010578588,0.00013787372,0.0026116108],"study_design_scores_gemma":[0.0000065749987,0.000019519723,0.00022488706,0.0000014307292,0.0000016788815,0.0000055322653,0.000006295334,0.99887973,0.0006868539,0.00008126713,0.00008306867,0.0000031279335],"about_ca_topic_score_codex":0.008274943,"about_ca_topic_score_gemma":0.006224917,"teacher_disagreement_score":0.008274943,"about_ca_system_score_codex":0.0007845661,"about_ca_system_score_gemma":0.0008235517,"threshold_uncertainty_score":0.016453564},"labels":[],"label_agreement":null},{"id":"W2731306824","doi":"10.1115/1.4037183","title":"Grinding of Chromium Carbide Coatings Using Electroplated Diamond Wheels","year":2017,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Grinding; Materials science; Surface roughness; Grind; Metallurgy; Electroplating; Diamond; Chromium; Machining; Surface finish; Diamond grinding; Grinding wheel; Carbide; Composite material; Layer (electronics)","score_opus":0.009325017244890016,"score_gpt":0.23412351002966683,"score_spread":0.22479849278477682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2731306824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.985045,0.0006199156,0.013042228,0.000018334433,0.00003104776,0.00006135386,0.000059822272,0.00008484963,0.0010374107],"genre_scores_gemma":[0.96889305,0.0005082928,0.028411908,0.000024853438,0.000006942141,0.000022295013,0.00011096996,0.00005533805,0.0019663952],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992988,0.000028123895,0.000027177315,0.00014165319,0.00038708712,0.00011716982],"domain_scores_gemma":[0.99952435,0.00014688454,0.00008714621,0.000080871716,0.0001264298,0.0000343422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004083669,0.00040073675,0.00060398306,0.0004000968,0.0002667926,0.00032203097,0.0006038446,0.0004376247,0.0009893742],"category_scores_gemma":[0.00066469214,0.00031541134,0.00047563371,0.00022641968,0.00037627167,0.00024601063,0.0003490589,0.00050203776,0.00022983212],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037780614,0.000010489596,0.00016959295,0.000053431497,0.0000033995125,0.00003994502,0.000039444607,0.0002170861,0.99715686,0.000031593536,0.000013466326,0.002226853],"study_design_scores_gemma":[0.000010593366,0.00033232538,0.0042080134,0.0000057837815,0.000006965005,0.00009405169,0.00003486055,0.0022522951,0.99204165,0.000019163585,0.0009840806,0.000010094455],"about_ca_topic_score_codex":0.0025793898,"about_ca_topic_score_gemma":0.006858988,"teacher_disagreement_score":0.0025793898,"about_ca_system_score_codex":0.00042128324,"about_ca_system_score_gemma":0.00030500037,"threshold_uncertainty_score":0.0051287413},"labels":[],"label_agreement":null},{"id":"W2732826855","doi":"10.4050/f-0073-2017-12086","title":"Wear Sensors for Pitch Control Bearing Condition Based Maintenance","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell Helicopter Textron (Canada)","funders":"","keywords":"Bearing (navigation); Control (management); Automotive engineering; Computer science; Environmental science; Engineering; Artificial intelligence","score_opus":0.008476746970321485,"score_gpt":0.24871727978228875,"score_spread":0.24024053281196725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2732826855","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3525023,0.008868985,0.60204834,0.0008077147,0.0012737941,0.0006938582,0.0025284837,0.013114325,0.018162252],"genre_scores_gemma":[0.8520526,0.00094497093,0.13344808,0.0002661985,0.00011567154,0.00014296094,0.00076818676,0.00013263794,0.01212867],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999188,0.00007986217,0.00003294023,0.000084706044,0.00057466945,0.00003967106],"domain_scores_gemma":[0.9988979,0.0002945144,0.00016681662,0.0001475318,0.00045369813,0.00003956012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004939502,0.00041859853,0.0004989014,0.0006224441,0.00021643343,0.00050450925,0.0008647837,0.00054096204,0.0037516265],"category_scores_gemma":[0.0014811384,0.00028697064,0.00019106349,0.00037802244,0.00015192144,0.00087893684,0.00029639958,0.00048923696,0.00075012987],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070506835,0.00019644221,0.006662415,0.00063207315,0.000044073746,0.00023030282,0.00017038362,0.004013914,0.6583858,0.0012867505,0.0074967686,0.32017595],"study_design_scores_gemma":[0.00015210483,0.001944764,0.038519114,0.00012866847,0.00010537539,0.0019853702,0.00019975904,0.12510964,0.77510166,0.0015245038,0.055096805,0.00013225547],"about_ca_topic_score_codex":0.00068559585,"about_ca_topic_score_gemma":0.0013807965,"teacher_disagreement_score":0.0037516265,"about_ca_system_score_codex":0.0003527554,"about_ca_system_score_gemma":0.0002527283,"threshold_uncertainty_score":0.012550473},"labels":[],"label_agreement":null},{"id":"W2736149070","doi":"10.1080/10910344.2017.1336177","title":"Cutting tool wear detection using multiclass logical analysis of data","year":2017,"lang":"en","type":"article","venue":"Machining Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Machining; Tool wear; Artificial neural network; Machine tool; Computer science; Pattern recognition (psychology); Artificial intelligence; Class (philosophy); Numerical control; Machine learning; Data mining; Engineering; Mechanical engineering","score_opus":0.03828601625148307,"score_gpt":0.32596354674180367,"score_spread":0.2876775304903206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736149070","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10884671,0.00042613092,0.88790506,0.00008105974,0.000058679878,0.00014602627,0.0003079324,0.000768037,0.0014604585],"genre_scores_gemma":[0.6811292,0.00028425452,0.31674463,0.00005269585,0.000049094146,0.00019506404,0.00051350665,0.000051274816,0.0009801746],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880624,0.00017960822,0.000112643946,0.00026800396,0.00056541414,0.000068010355],"domain_scores_gemma":[0.99777704,0.00089250976,0.0004690003,0.00025327757,0.0005483352,0.0000597875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077176077,0.00051660824,0.0006036205,0.0031409555,0.00035272838,0.0009987555,0.0004916694,0.00036702966,0.00082909095],"category_scores_gemma":[0.0032610819,0.00016536587,0.000508919,0.0014108911,0.00038382784,0.0010449318,0.00050435687,0.00037727322,0.00029661867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004445189,0.00027646078,0.03300569,0.0004550764,0.00017136005,0.00018633735,0.00033125657,0.016208382,0.083473064,0.0023658301,0.00094037195,0.8621417],"study_design_scores_gemma":[0.000051076822,0.0007048605,0.057269957,0.00009254121,0.00013995897,0.0010032415,0.0004600548,0.8424681,0.082148045,0.0060880324,0.009442382,0.00013169262],"about_ca_topic_score_codex":0.0010590894,"about_ca_topic_score_gemma":0.001452674,"teacher_disagreement_score":0.0031409555,"about_ca_system_score_codex":0.0003764792,"about_ca_system_score_gemma":0.0005012199,"threshold_uncertainty_score":0.0040814877},"labels":[],"label_agreement":null},{"id":"W2737642985","doi":"","title":"The Role of Natural Vibrations In Penetration Mechanism of a Single PDC Cutter","year":2012,"lang":"en","type":"article","venue":"46th U.S. Rock Mechanics/Geomechanics Symposium","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Mechanism (biology); Vibration; Penetration (warfare); Natural (archaeology); Acoustics; Geology; Computer science; Engineering; Physics; Operations research","score_opus":0.005790607662359756,"score_gpt":0.20099699294893905,"score_spread":0.1952063852865793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2737642985","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95241094,0.00025726546,0.038785387,0.0001468223,0.000035364475,0.000019617739,0.000028547509,0.000114818475,0.008201275],"genre_scores_gemma":[0.99880755,0.000017760765,0.00070790126,0.0000042861775,0.0000014199109,0.0000017729634,0.00000322709,0.000004075785,0.00045207594],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999161,0.000010502434,0.0000028078043,0.000019090827,0.000030996987,0.000020433434],"domain_scores_gemma":[0.9997608,0.00010480949,0.000030697192,0.000024264913,0.00004896597,0.000030350155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001652612,0.00017083825,0.00015093942,0.0001918351,0.00028582517,0.00030232908,0.00040128187,0.0004469834,0.0028432722],"category_scores_gemma":[0.00050800445,0.00018736853,0.00011123779,0.000069229754,0.0004976936,0.00048141126,0.0002922311,0.00020718656,0.00023514054],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011066258,0.0001583001,0.011542165,0.00030853663,0.00004092491,0.0021402496,0.00080799987,0.09983534,0.7921686,0.022041624,0.0011271414,0.06872245],"study_design_scores_gemma":[0.00005759554,0.0005428864,0.026546061,0.000030878367,0.000023481996,0.001472923,0.00051216077,0.89289993,0.07021051,0.0058539426,0.0017881743,0.000061450846],"about_ca_topic_score_codex":0.0004658856,"about_ca_topic_score_gemma":0.0004800471,"teacher_disagreement_score":0.0028432722,"about_ca_system_score_codex":0.00020160033,"about_ca_system_score_gemma":0.00020320421,"threshold_uncertainty_score":0.00951165},"labels":[],"label_agreement":null},{"id":"W2743423608","doi":"10.1115/1.4037553","title":"A Novel Generalized Approach for Real-Time Tool Condition Monitoring","year":2017,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"","keywords":"Computer science; Process (computing); Sensitivity (control systems); Generalization; Machine tool; Cutting tool; Quality (philosophy); Artificial intelligence; Machine learning; Reliability engineering; Data mining; Pattern recognition (psychology); Engineering; Mathematics; Electronic engineering","score_opus":0.013909502567532758,"score_gpt":0.25331424274928344,"score_spread":0.23940474018175067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2743423608","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009629034,0.00020418072,0.9887256,0.00003338255,0.00003575057,0.0000390961,0.000054868193,0.00066947256,0.0006085905],"genre_scores_gemma":[0.38506466,0.0004101226,0.6102567,0.00014489659,0.00011772048,0.00018471241,0.0003012067,0.00013175923,0.003388273],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99942243,0.0000786532,0.000023962102,0.000214498,0.00021914387,0.000041393876],"domain_scores_gemma":[0.99968565,0.00008128245,0.00004921983,0.000066716224,0.000102110134,0.0000150351825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033217837,0.00079135504,0.000609709,0.0007634029,0.00018487991,0.000579128,0.0009837445,0.0005762022,0.0013450306],"category_scores_gemma":[0.000849433,0.00023510758,0.0005472398,0.00082790165,0.0003373792,0.0007756977,0.00065365667,0.0005500703,0.0006249999],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029772113,0.000110019864,0.0014054957,0.000251305,0.00009391365,0.0002383781,0.000166097,0.045947723,0.23288238,0.00464201,0.001499723,0.71246535],"study_design_scores_gemma":[0.000021544478,0.00031092516,0.003332826,0.0000198746,0.00006229763,0.00046259616,0.000047396432,0.9601685,0.025118642,0.0037826495,0.0066254963,0.00004736331],"about_ca_topic_score_codex":0.0010090504,"about_ca_topic_score_gemma":0.0014879871,"teacher_disagreement_score":0.0013450306,"about_ca_system_score_codex":0.0002317527,"about_ca_system_score_gemma":0.00031665753,"threshold_uncertainty_score":0.0044996142},"labels":[],"label_agreement":null},{"id":"W2749178540","doi":"10.1007/s00170-017-0975-9","title":"A numerical and experimental study to investigate convective heat transfer and associated cutting temperature distribution in single point turning","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Heat transfer coefficient; Convective heat transfer; Heat transfer; Computational fluid dynamics; Convection; Machining; Materials science; Coolant; Mechanics; Mechanical engineering; NTU method; Engineering; Micro heat exchanger; Physics","score_opus":0.006845416746663272,"score_gpt":0.2530293175572921,"score_spread":0.2461839008106288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749178540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943956,0.00007634582,0.004065363,0.000016939199,0.000020993119,0.000037197482,0.0000687331,0.00004587786,0.0012728722],"genre_scores_gemma":[0.99701333,0.00003899492,0.0025059483,0.000005013342,0.0000041674825,0.000020866108,0.000044536868,0.000006029422,0.00036109044],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971074,0.000031856212,0.000009949164,0.000050324434,0.00015176923,0.00004538143],"domain_scores_gemma":[0.9991222,0.00040732892,0.00008395305,0.00014527894,0.000193601,0.000047629343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040853024,0.000268924,0.00047389587,0.00033686237,0.0008307829,0.00032266992,0.0005207349,0.000521594,0.0012477683],"category_scores_gemma":[0.0008553928,0.00023984941,0.00028401034,0.00039608855,0.00072007696,0.00034232784,0.00027830678,0.00039812844,0.00015326223],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007815533,0.0008098189,0.004970199,0.00020979409,0.00001638635,0.00017104369,0.0004006364,0.010133981,0.9700509,0.000669372,0.00017372945,0.011612551],"study_design_scores_gemma":[0.00018071997,0.005736079,0.051837184,0.000021276954,0.00006885323,0.00068852084,0.0006605074,0.10879579,0.8296278,0.00043699195,0.0018637931,0.00008251962],"about_ca_topic_score_codex":0.0009502161,"about_ca_topic_score_gemma":0.0013216969,"teacher_disagreement_score":0.0012477683,"about_ca_system_score_codex":0.00028710716,"about_ca_system_score_gemma":0.0002797809,"threshold_uncertainty_score":0.004174173},"labels":[],"label_agreement":null},{"id":"W274954981","doi":"10.1177/0021998315587131","title":"Experimental investigation of the cutting temperature and surface quality during milling of unidirectional carbon fiber reinforced plastic","year":2015,"lang":"en","type":"article","venue":"Journal of Composite Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Materials science; Composite material; Machinability; Machining; Surface roughness; Fiber; Tool wear; Composite number; Thermal; Surface finish; Fibre-reinforced plastic; Surface integrity; Metallurgy","score_opus":0.012540147763605718,"score_gpt":0.239747144198054,"score_spread":0.2272069964344483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W274954981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986015,0.0000523459,0.0010972642,0.000003740823,0.0000028394757,0.000011178605,0.00005707913,0.0000110788105,0.00016295089],"genre_scores_gemma":[0.9968168,0.000065815846,0.0027525353,0.000003908281,0.0000024708695,0.000016251275,0.00006228597,0.0000104442925,0.00026952502],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996488,0.000029961157,0.000027333721,0.00007949701,0.00015374375,0.00006071409],"domain_scores_gemma":[0.9990282,0.00033916696,0.00023808138,0.000105877945,0.00025024946,0.000038523856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039396336,0.00035021032,0.0003766379,0.00023516227,0.00035224867,0.00022256272,0.00028190555,0.00037083443,0.00081991724],"category_scores_gemma":[0.0007293181,0.0002489556,0.0002923395,0.00029984038,0.00033731054,0.00022721574,0.00017213835,0.00038336724,0.00010413108],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022198643,0.00007180562,0.0013564273,0.000080038284,0.0000063760353,0.00006447833,0.00016263626,0.00063603243,0.9949773,0.00002609148,0.00002247693,0.0023742274],"study_design_scores_gemma":[0.0000116456695,0.0009464879,0.01448945,0.000004437151,0.000015161362,0.000064776235,0.00007158692,0.0027964101,0.9813436,0.000015549469,0.00022822032,0.000012495195],"about_ca_topic_score_codex":0.0005608797,"about_ca_topic_score_gemma":0.0010574567,"teacher_disagreement_score":0.00081991724,"about_ca_system_score_codex":0.00019330253,"about_ca_system_score_gemma":0.0001459082,"threshold_uncertainty_score":0.0027428865},"labels":[],"label_agreement":null},{"id":"W2754116814","doi":"10.1007/s00170-017-1032-4","title":"Finite element analysis and response surface method for robust multi-performance optimization of radial turning of hard 300M steel","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; École de Technologie Supérieure; Concordia University","funders":"","keywords":"Machining; Finite element method; Residual stress; Weighting; Engineering; Residual; Response surface methodology; Sequential quadratic programming; Structural engineering; Mechanical engineering; Design of experiments; Thrust; Mathematical optimization; Computer science; Quadratic programming; Algorithm; Materials science; Mathematics","score_opus":0.01470871776643502,"score_gpt":0.2831267101666853,"score_spread":0.26841799240025027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754116814","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1648213,0.00040729245,0.8241447,0.0002838219,0.000091391674,0.00009362144,0.000100600475,0.00049629476,0.009560997],"genre_scores_gemma":[0.9080039,0.00016035726,0.086725615,0.00006229409,0.000030593368,0.00017796527,0.00016043328,0.00016756903,0.0045112465],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958545,0.00016604342,0.000015504136,0.00003815311,0.00015086953,0.00004404935],"domain_scores_gemma":[0.9992036,0.00047890394,0.000065805536,0.00004994471,0.00017285808,0.00002896583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009947906,0.0007485011,0.0013751693,0.0007814178,0.0004287858,0.0006875841,0.0009547226,0.001540688,0.002376363],"category_scores_gemma":[0.0016699042,0.00074234506,0.0011119281,0.00036803223,0.0007177927,0.00045174704,0.0006920759,0.0008283597,0.00035699975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047214035,0.000036428206,0.00015503653,0.00003892531,0.000017542317,0.000027136693,0.000023876442,0.98907757,0.003914308,0.0011096258,0.00014265523,0.0054096533],"study_design_scores_gemma":[0.0000028188354,0.000014848574,0.000053328513,0.0000012838665,0.000001634201,0.0000025432123,0.0000043269138,0.9994523,0.00029177355,0.00010143453,0.0000717054,0.0000020489674],"about_ca_topic_score_codex":0.0053681773,"about_ca_topic_score_gemma":0.0038173487,"teacher_disagreement_score":0.0053681773,"about_ca_system_score_codex":0.00044415996,"about_ca_system_score_gemma":0.0010108487,"threshold_uncertainty_score":0.010673881},"labels":[],"label_agreement":null},{"id":"W2756521887","doi":"10.1016/j.jmapro.2017.09.011","title":"Effects of atomization-based cutting fluid sprays in milling of carbon fiber reinforced polymer composite","year":2017,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; University of Victoria","funders":"","keywords":"Materials science; Machining; Composite material; Delamination (geology); Composite number; Surface roughness; Tool wear; Surface integrity; Surface finish; Micrometer; Fiber; Metallurgy; Mechanical engineering","score_opus":0.005505801421853322,"score_gpt":0.22131563028126122,"score_spread":0.2158098288594079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756521887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99875915,0.0003576192,0.0004482323,0.000012200431,0.000015005871,0.000008208365,0.0000149230555,0.000017086784,0.00036758167],"genre_scores_gemma":[0.99871933,0.00022119886,0.00064012664,0.000012016393,0.0000068618674,0.0000041713265,0.000017759756,0.000009270666,0.00036917703],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998294,0.000019857627,0.000011645741,0.000028504695,0.00006259403,0.0000479001],"domain_scores_gemma":[0.9997154,0.000103409904,0.00006847256,0.00001561685,0.00006236971,0.00003469398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020124926,0.00028993963,0.00029082084,0.00019046507,0.00024386402,0.00031547,0.00022106327,0.00028854646,0.0017249237],"category_scores_gemma":[0.0003620476,0.0001912392,0.0002835828,0.000120207755,0.00030044845,0.00039811706,0.00022394484,0.0004300421,0.00012309747],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064594374,0.000066694854,0.00019829789,0.00005929299,0.000008339469,0.00003648378,0.000047087346,0.0002945812,0.9956441,0.0000513304,0.00003281388,0.002915125],"study_design_scores_gemma":[0.000021499593,0.0004597686,0.0015470166,0.0000029936048,0.00001293703,0.000014770241,0.000029046036,0.0016347747,0.9960521,0.000009208227,0.00021061779,0.0000052779455],"about_ca_topic_score_codex":0.0011029537,"about_ca_topic_score_gemma":0.002332701,"teacher_disagreement_score":0.0017249237,"about_ca_system_score_codex":0.0003184695,"about_ca_system_score_gemma":0.00030277704,"threshold_uncertainty_score":0.005770445},"labels":[],"label_agreement":null},{"id":"W2757988126","doi":"10.1177/1350650117733921","title":"Study of tribofilms generation at different cutting speeds in dry machining hardened AISI T1 and AISI D2 steel","year":2017,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Materials science; Metallurgy; Ceramic; Lubrication; Carbide; Scanning electron microscope; Optical microscope; Tool steel; Tribology; Composite material","score_opus":0.02116364165831756,"score_gpt":0.24868271797510869,"score_spread":0.22751907631679114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2757988126","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980433,0.00026662953,0.001348481,0.000009315191,0.0000041288786,0.000008901087,0.000077407516,0.000027100907,0.0002146783],"genre_scores_gemma":[0.99753535,0.000109434375,0.0018209899,0.000009004758,0.000002559761,0.000011869866,0.00012956795,0.000015765636,0.00036544804],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997024,0.000036787373,0.000025865877,0.00007315177,0.00010279089,0.000058957405],"domain_scores_gemma":[0.9991221,0.00032533167,0.000185897,0.0000661722,0.0002444526,0.000056082867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029282767,0.00034663477,0.00041954254,0.00059686496,0.00026808179,0.00038913393,0.0003490928,0.00060886866,0.00080769096],"category_scores_gemma":[0.0009313697,0.00029342738,0.0002768676,0.00050147244,0.00035264803,0.0003526391,0.00011769329,0.000458877,0.00015663965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043437709,0.000028081275,0.001759708,0.000103008875,0.00001376688,0.00011471082,0.00018559517,0.0005892932,0.99271977,0.00003776666,0.000034318826,0.0039795544],"study_design_scores_gemma":[0.00003558527,0.0008353095,0.046610314,0.0000108366785,0.00003789485,0.00023466737,0.00021608573,0.0051829326,0.9458183,0.00004899573,0.0009401973,0.000028898854],"about_ca_topic_score_codex":0.00095195597,"about_ca_topic_score_gemma":0.0011537739,"teacher_disagreement_score":0.00095195597,"about_ca_system_score_codex":0.00024071606,"about_ca_system_score_gemma":0.00012165842,"threshold_uncertainty_score":0.0027020574},"labels":[],"label_agreement":null},{"id":"W2759085868","doi":"10.1007/s00170-017-1088-1","title":"Coolant strategy influence on tool life and surface roughness when machining ADI","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University; University of Guelph","funders":"","keywords":"Machinability; Austempering; Materials science; Microstructure; Machining; Austenite; Ferrite (magnet); Metallurgy; Coolant; Surface roughness; Carbide; Tool wear; Composite material; Mechanical engineering; Bainite","score_opus":0.008959068563510888,"score_gpt":0.2539939620169222,"score_spread":0.2450348934534113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2759085868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99818414,0.00021125087,0.00087611505,0.000008506016,0.000009162947,0.0000040896743,0.000029062276,0.000026845855,0.0006508132],"genre_scores_gemma":[0.99938774,0.000032525044,0.00025339652,0.00000210806,0.0000015282121,0.0000019443298,0.000024251372,0.000009182985,0.0002872969],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981433,0.000017403318,0.000009686479,0.00005256826,0.00005547101,0.000050658113],"domain_scores_gemma":[0.9992791,0.00033966263,0.00009450269,0.00004525312,0.0001980086,0.00004351294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028236312,0.0002372269,0.00031631987,0.00041446247,0.00030702946,0.0006826805,0.0003201429,0.00035884164,0.001737887],"category_scores_gemma":[0.0009765676,0.0001795802,0.00027563656,0.0002968849,0.00021172722,0.00043352527,0.00016313024,0.00023293078,0.00024014938],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031647277,0.00025377094,0.03012132,0.00037737872,0.00009420595,0.000611348,0.0003187776,0.034214985,0.8903537,0.00047165545,0.0005202101,0.039497975],"study_design_scores_gemma":[0.00006169819,0.0041319,0.19104663,0.000027617625,0.0002822852,0.0005474251,0.0008712947,0.18545096,0.61469746,0.00043659398,0.002345568,0.00010057426],"about_ca_topic_score_codex":0.0011921495,"about_ca_topic_score_gemma":0.0019961835,"teacher_disagreement_score":0.001737887,"about_ca_system_score_codex":0.00030028351,"about_ca_system_score_gemma":0.00021446915,"threshold_uncertainty_score":0.005813837},"labels":[],"label_agreement":null},{"id":"W2759297652","doi":"10.1115/1.4038000","title":"Time-Domain Modeling of Varying Dynamic Characteristics in Thin-Wall Machining Using Perturbation and Reduced-Order Substructuring Methods","year":2017,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":81,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Perturbation (astronomy); Machining; Stiffness; Frequency domain; Time domain; Eigenvalues and eigenvectors; Rayleigh quotient; Algorithm; Computer science; Mathematical analysis; Mathematics; Control theory (sociology); Structural engineering; Engineering; Physics; Mechanical engineering","score_opus":0.01287627847781674,"score_gpt":0.2771429759062842,"score_spread":0.2642666974284674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2759297652","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060178246,0.00012907742,0.93686783,0.000059221205,0.000025064404,0.000033693155,0.0000343556,0.0002614243,0.0024111043],"genre_scores_gemma":[0.8928213,0.00030153184,0.10243943,0.00003151255,0.000016083743,0.00009257603,0.000098928125,0.00008457221,0.0041140765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999907,0.00002365263,0.000003883424,0.000014711722,0.000042074753,0.000008564192],"domain_scores_gemma":[0.999835,0.00007912392,0.000027933003,0.000019565614,0.000030347197,0.000007940493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019042459,0.00038745193,0.00032628488,0.00020935445,0.00017286124,0.00040357694,0.00063706614,0.0005037798,0.0007426582],"category_scores_gemma":[0.00045323995,0.00026277342,0.00039279967,0.0002009279,0.00037973752,0.00047266379,0.000263453,0.0004691558,0.00017699001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015597745,0.000010842268,0.00020309188,0.000017368546,0.000006512919,0.000041726253,0.000027629385,0.9860563,0.006754553,0.0018046355,0.00006752742,0.004994164],"study_design_scores_gemma":[6.025261e-7,0.0000027226374,0.000025374711,3.7612745e-7,4.7639784e-7,0.0000025388497,9.585561e-7,0.9994691,0.00030378954,0.00012374061,0.000069488764,7.8099475e-7],"about_ca_topic_score_codex":0.0033516244,"about_ca_topic_score_gemma":0.0017251783,"teacher_disagreement_score":0.0033516244,"about_ca_system_score_codex":0.00030140323,"about_ca_system_score_gemma":0.0003415097,"threshold_uncertainty_score":0.0066642165},"labels":[],"label_agreement":null},{"id":"W2761478393","doi":"10.1007/s12541-017-0162-9","title":"A parametric and accurate CAD model of flat end mills based on its grinding operations","year":2017,"lang":"en","type":"article","venue":"International Journal of Precision Engineering and Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"CAD; End mill; Rake angle; Grinding; Rake; Parametric statistics; Parametric model; Machining; Representation (politics); Enhanced Data Rates for GSM Evolution; Mechanical engineering; Engineering; Grinding wheel; Mill; Engineering drawing; Parametric design; Helix angle; Process (computing); Computer science; Mathematics","score_opus":0.022001842614790698,"score_gpt":0.2772178622069038,"score_spread":0.2552160195921131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2761478393","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15947932,0.00090421084,0.74305445,0.00045690883,0.00020899936,0.00029721815,0.0033521098,0.0023807269,0.08986608],"genre_scores_gemma":[0.8982209,0.00076391076,0.077545725,0.000055561984,0.000029992028,0.00020394773,0.001345697,0.00017118738,0.021663053],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998141,0.000022507345,0.000010341257,0.000037705224,0.00009929892,0.000016105138],"domain_scores_gemma":[0.9998529,0.000045898596,0.000024866498,0.000028728417,0.00004129241,0.0000063321004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015397895,0.00057231006,0.0005219081,0.0004454859,0.00032773518,0.0009275873,0.0012542635,0.0011448817,0.0087871],"category_scores_gemma":[0.0003418512,0.0005208689,0.0006427269,0.0007109362,0.0003904378,0.0006058147,0.00026648602,0.0004898779,0.0012213559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053380874,0.00003561757,0.00041992756,0.00007562701,0.000007858218,0.00018694851,0.00005816086,0.9725568,0.0053610425,0.0045773746,0.00068961206,0.015977552],"study_design_scores_gemma":[0.000013847412,0.00005444528,0.0010139544,0.000009386676,0.000008867205,0.0001332016,0.00002130624,0.99193245,0.0015552683,0.0010764911,0.0041611553,0.000019584922],"about_ca_topic_score_codex":0.007972728,"about_ca_topic_score_gemma":0.007162236,"teacher_disagreement_score":0.0087871,"about_ca_system_score_codex":0.0003927143,"about_ca_system_score_gemma":0.0008548277,"threshold_uncertainty_score":0.02939576},"labels":[],"label_agreement":null},{"id":"W2765115781","doi":"10.1007/s00170-017-1202-4","title":"A new mathematical method of modeling parts in virtual CNC lathing and its application on accurate tool path generation","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Science Basic Research Program of Shaanxi Province; National Natural Science Foundation of China","keywords":"Machining; Enhanced Data Rates for GSM Evolution; Path (computing); Numerical control; Tool path; Engineering drawing; Dimension (graph theory); Engineering; Surface roughness; Mechanical engineering; Machine tool; Surface finish; Computer science; Computer vision; Mathematics; Materials science","score_opus":0.017677109680898286,"score_gpt":0.29845689874677955,"score_spread":0.28077978906588125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765115781","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007981778,0.00008662431,0.9979018,0.00001926938,0.000039042516,0.000014532605,0.00001229486,0.00005713888,0.0010711529],"genre_scores_gemma":[0.19290929,0.0008165926,0.7971198,0.000097326316,0.00008704861,0.00027903653,0.00013023714,0.0002840875,0.008276517],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961805,0.00008284184,0.000019915096,0.00006973548,0.00019021785,0.000019237723],"domain_scores_gemma":[0.9997141,0.00011226223,0.000032728047,0.000039316004,0.00008839371,0.000013143365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006361673,0.0009821919,0.0007389495,0.0011389126,0.0005928642,0.00082255725,0.0016238681,0.0011740386,0.0026357598],"category_scores_gemma":[0.0010825957,0.0005295673,0.0009832995,0.0011579683,0.0008297327,0.0014832279,0.0007644413,0.0012349124,0.0005982646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026607056,0.000038870192,0.0002615575,0.00017302344,0.000023518003,0.000110936664,0.00011878748,0.82867277,0.011714611,0.10102089,0.0012218697,0.056616552],"study_design_scores_gemma":[0.0000017589706,0.000007773246,0.000027008127,0.0000042354277,0.0000034384298,0.000025919,0.000003385264,0.99505156,0.00057029526,0.002730607,0.001568615,0.0000054014813],"about_ca_topic_score_codex":0.0036232737,"about_ca_topic_score_gemma":0.003429371,"teacher_disagreement_score":0.0036232737,"about_ca_system_score_codex":0.0006449494,"about_ca_system_score_gemma":0.0010083421,"threshold_uncertainty_score":0.008817434},"labels":[],"label_agreement":null},{"id":"W2765605542","doi":"10.1115/1.4038206","title":"Design for Manufacturing of Variable Microgeometry Cutting Tools","year":2017,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Ontario Tech University","funders":"","keywords":"Machining; Enhanced Data Rates for GSM Evolution; Mechanical engineering; Materials science; Wedge (geometry); Surface roughness; Surface integrity; Process (computing); Cutting tool; Engineering drawing; Computer science; Engineering; Composite material; Geometry; Artificial intelligence; Mathematics","score_opus":0.017841938934663317,"score_gpt":0.2417072887833386,"score_spread":0.2238653498486753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765605542","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051318083,0.00035966662,0.94376034,0.00005928608,0.00004855963,0.000230399,0.000069348156,0.000591416,0.0035628723],"genre_scores_gemma":[0.54038465,0.00019491532,0.45762125,0.000035621717,0.000015573512,0.00021645096,0.00007786987,0.00004795401,0.0014056929],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99947137,0.0000530886,0.00003841087,0.00013277943,0.0002461271,0.00005830464],"domain_scores_gemma":[0.99948955,0.00007283856,0.00020277653,0.00008100181,0.00012653468,0.000027292901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042650496,0.00056236086,0.0003937212,0.00041249464,0.00024857518,0.0007504234,0.0012153654,0.0006713847,0.0010098635],"category_scores_gemma":[0.0007170444,0.0003467883,0.00038086635,0.0002399704,0.00032275514,0.0003495054,0.00046342227,0.00035614904,0.00035217463],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026234624,0.000093428665,0.002476152,0.0009144514,0.000052320043,0.00043116976,0.0002708996,0.15148336,0.6513212,0.013265356,0.001182132,0.17824726],"study_design_scores_gemma":[0.00011858783,0.0019106123,0.007813519,0.00010477331,0.00009460968,0.0012265322,0.00011466501,0.68444806,0.26859325,0.0037784765,0.031691547,0.000105328734],"about_ca_topic_score_codex":0.00039542248,"about_ca_topic_score_gemma":0.0004634581,"teacher_disagreement_score":0.0012153654,"about_ca_system_score_codex":0.0003708413,"about_ca_system_score_gemma":0.00054599665,"threshold_uncertainty_score":0.003378272},"labels":[],"label_agreement":null},{"id":"W2766281943","doi":"10.3390/ma10111230","title":"Effect of Built-Up Edge Formation during Stable State of Wear in AISI 304 Stainless Steel on Machining Performance and Surface Integrity of the Machined Part","year":2017,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Surface integrity; Machining; Enhanced Data Rates for GSM Evolution; Surface roughness; Metallurgy; Scanning electron microscope; Tool wear; Surface finish; Cutting tool; Chip formation; Residual stress; Composite material; Engineering","score_opus":0.008747601790091014,"score_gpt":0.24421486522030977,"score_spread":0.23546726343021876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766281943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99954695,0.00017008913,0.00015343282,0.0000054866177,0.0000045151232,0.000003560296,0.000024060742,0.000007554612,0.00008429607],"genre_scores_gemma":[0.99949074,0.00007048072,0.00021394141,0.0000056101876,0.0000016401189,0.0000029233706,0.00003728282,0.000004218238,0.00017311003],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995369,0.00005700883,0.0000519053,0.00006619765,0.00019036302,0.00009757736],"domain_scores_gemma":[0.9991793,0.00027808204,0.00014640903,0.00007488731,0.00024143694,0.000079855614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029086907,0.00030736218,0.0003784091,0.00028246976,0.0002729875,0.00028671985,0.00024400865,0.00042561957,0.0007561186],"category_scores_gemma":[0.0007878045,0.00021975089,0.0003696647,0.0002483622,0.00024190282,0.00025790534,0.00019949635,0.00033275905,0.000118812335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064912677,0.00005550403,0.003017046,0.000107747604,0.00001864166,0.00019782996,0.00021979505,0.0004399214,0.9917509,0.000015283478,0.000030908206,0.0034971654],"study_design_scores_gemma":[0.000014832489,0.0027245323,0.04346095,0.000008778595,0.000034461285,0.00015031788,0.00025167147,0.0019030361,0.95104694,0.00001834001,0.00036439585,0.000021693231],"about_ca_topic_score_codex":0.0010030632,"about_ca_topic_score_gemma":0.002043777,"teacher_disagreement_score":0.0010030632,"about_ca_system_score_codex":0.00019752016,"about_ca_system_score_gemma":0.00014751614,"threshold_uncertainty_score":0.0025294423},"labels":[],"label_agreement":null},{"id":"W2766591297","doi":"10.1515/amm-2017-0269","title":"Impact of Cutting Forces and Chip Microstructure in High Speed Machining of Carbon Fiber – Epoxy Composite Tube","year":2017,"lang":"en","type":"article","venue":"Archives of Metallurgy and Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"All India Council for Technical Education","keywords":"Machinability; Machining; Microstructure; Materials science; Thrust; Composite material; Chip formation; Composite number; Drilling; Fiber; Carbon fiber reinforced polymer; Tool wear; Metallurgy; Mechanical engineering; Engineering","score_opus":0.006072818455447663,"score_gpt":0.24298482448728068,"score_spread":0.23691200603183302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766591297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992994,0.000092672046,0.00035869103,0.000004047316,0.0000026271691,0.0000026056484,0.000014845171,0.0000097418215,0.00021527732],"genre_scores_gemma":[0.99920315,0.00003289279,0.000557405,0.0000028772472,8.138622e-7,0.0000016388809,0.000013128783,0.0000036865115,0.00018436242],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999838,0.000020456817,0.000008904346,0.000028366638,0.00007115183,0.000033054897],"domain_scores_gemma":[0.99944526,0.00021446362,0.0001551648,0.00003282301,0.00012479667,0.000027539447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002455986,0.00020717036,0.00016097933,0.000246621,0.00015316157,0.00022881365,0.00014459575,0.000262997,0.00096318714],"category_scores_gemma":[0.00044210994,0.00020094974,0.00014973585,0.0001574783,0.0001897375,0.00020432624,0.0000851328,0.00017893495,0.00009302237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037271148,0.00004290417,0.0030384162,0.00007026334,0.000012071268,0.00011651989,0.000061026472,0.002950793,0.98788214,0.00004578131,0.00004987404,0.0053574797],"study_design_scores_gemma":[0.000015541542,0.0014550562,0.08528638,0.000009647533,0.000024480982,0.00017434849,0.00011138856,0.011238614,0.9011194,0.000034684104,0.0005142506,0.000016215328],"about_ca_topic_score_codex":0.00075506594,"about_ca_topic_score_gemma":0.0018803136,"teacher_disagreement_score":0.00096318714,"about_ca_system_score_codex":0.00023638971,"about_ca_system_score_gemma":0.00012178308,"threshold_uncertainty_score":0.0032221675},"labels":[],"label_agreement":null},{"id":"W2767610102","doi":"10.1007/s00170-017-1288-8","title":"Mechanical deburring and edge-finishing processes for aluminum parts—a review","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Aerospace; Enhanced Data Rates for GSM Evolution; Flexibility (engineering); Automotive industry; Mechanical engineering; Work (physics); Process (computing); Manufacturing engineering; Engineering; Abrasion (mechanical); Quality (philosophy); Machining; Computer science","score_opus":0.013377730898568621,"score_gpt":0.2819617390660659,"score_spread":0.2685840081674973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767610102","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00046974767,0.9986077,0.00044186445,0.000040809522,0.00008003425,0.0000048439247,0.000007748656,0.0000044952703,0.0003426914],"genre_scores_gemma":[0.0031152074,0.9951131,0.00090223993,0.000093745206,0.00018146382,0.000008278277,0.000032750933,0.000004012807,0.0005492803],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995214,0.000038590653,0.00007780567,0.0001331872,0.00019554749,0.00003346885],"domain_scores_gemma":[0.9987833,0.0006498307,0.00022321736,0.00003786545,0.00026661967,0.000039181978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011801308,0.001195761,0.0016085667,0.002638874,0.00031549166,0.0012402235,0.0014962364,0.0015053842,0.001948943],"category_scores_gemma":[0.0013235367,0.00062594446,0.00078304997,0.0030841746,0.0007180651,0.0017352931,0.0006377821,0.0010426393,0.00096368004],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015807699,0.00021509483,0.0003819068,0.031939737,0.00022047406,0.00017252873,0.00007488444,0.0012948203,0.011714025,0.0016175556,0.0054834303,0.9467275],"study_design_scores_gemma":[0.00008294512,0.0011120038,0.0042489814,0.006164284,0.00096189755,0.0025355497,0.00020764231,0.0016865905,0.020477682,0.002486846,0.9598863,0.00014917197],"about_ca_topic_score_codex":0.0009541238,"about_ca_topic_score_gemma":0.0016692494,"teacher_disagreement_score":0.002638874,"about_ca_system_score_codex":0.00034326204,"about_ca_system_score_gemma":0.0009343005,"threshold_uncertainty_score":0.0065199137},"labels":[],"label_agreement":null},{"id":"W2768494850","doi":"10.1007/s00170-017-1307-9","title":"Principal component idealizations of the dominant modes of variability in the mechanics of the cutting process in metal turning","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Héroux-Devtek; Mitacs; Consortium de Recherche et d’innovation en Aérospatiale au Québec; Pratt and Whitney Canada","keywords":"Component (thermodynamics); Principal component analysis; Process (computing); Engineering; Principal (computer security); Mechanical engineering; Computer science; Physics; Artificial intelligence; Quantum mechanics","score_opus":0.008784083119690046,"score_gpt":0.2677905583021267,"score_spread":0.2590064751824367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2768494850","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1155725,0.0004073831,0.8761958,0.00032341824,0.0000605282,0.000053493794,0.00019057152,0.00018260092,0.007013641],"genre_scores_gemma":[0.95564437,0.000557722,0.039167274,0.000046736823,0.00008106008,0.00011417314,0.000259719,0.00014247996,0.0039863135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992392,0.00024567838,0.000031221276,0.00011896057,0.00024801743,0.00011691449],"domain_scores_gemma":[0.99826896,0.00093572796,0.00019580097,0.00019820218,0.00030500942,0.00009632116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016384864,0.00080455,0.00046778802,0.0010183724,0.00059192465,0.0013508416,0.00073935377,0.0005708386,0.0024091983],"category_scores_gemma":[0.0053067557,0.0004615372,0.0009475283,0.00075377326,0.0015962351,0.0013765955,0.00078457175,0.0011554918,0.0004223088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024962254,0.000105628715,0.0033473358,0.00014267895,0.00008610252,0.00016331286,0.0004097928,0.65579367,0.0065617897,0.2829261,0.0020059466,0.048207983],"study_design_scores_gemma":[0.000007732876,0.0000323709,0.0028813176,0.000012319552,0.000014083197,0.00005327915,0.000080768215,0.9016468,0.0006234851,0.093834914,0.00078115443,0.000031873955],"about_ca_topic_score_codex":0.0021197412,"about_ca_topic_score_gemma":0.001830852,"teacher_disagreement_score":0.0024091983,"about_ca_system_score_codex":0.0005353594,"about_ca_system_score_gemma":0.001092409,"threshold_uncertainty_score":0.008665264},"labels":[],"label_agreement":null},{"id":"W2769304450","doi":"10.1115/1.4038573","title":"Dynamics of Multipoint Thread Turning—Part II: Application to Thin-Walled Oil Pipes","year":2017,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant","keywords":"Threading (protein sequence); Thread (computing); Vibration; Shell (structure); Structural engineering; Discretization; Materials science; Mechanics; Engineering; Mechanical engineering; Acoustics; Physics; Mathematics","score_opus":0.00603457819706182,"score_gpt":0.2264902641853788,"score_spread":0.22045568598831697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2769304450","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48318425,0.0003166837,0.5108052,0.0001091395,0.000034805886,0.00005578012,0.000054789365,0.00025814344,0.0051812474],"genre_scores_gemma":[0.9908063,0.00012911658,0.0073930025,0.000006096811,0.000004401909,0.000022862529,0.000013144594,0.000014087774,0.0016109541],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99996066,0.000007670718,0.0000021981166,0.000008723786,0.000013860499,0.0000069545313],"domain_scores_gemma":[0.99988914,0.00004295796,0.0000280841,0.0000123092095,0.000018980665,0.000008487092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000119314485,0.0003217431,0.00039551881,0.00017732447,0.0002014639,0.00036120418,0.00033859123,0.00051617756,0.0011482264],"category_scores_gemma":[0.0003578521,0.00015910505,0.00035321948,0.00011163818,0.00041331336,0.000296166,0.00047591803,0.00031065405,0.000089570545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005536254,0.00002201397,0.0010267498,0.00006539347,0.00000904054,0.00022034858,0.00015534836,0.94845086,0.034914214,0.0039114472,0.00009641007,0.011072787],"study_design_scores_gemma":[0.000002394055,0.000022417098,0.00017868934,0.000002361294,0.0000012224989,0.000016399214,0.000010152106,0.998245,0.001118819,0.00028814544,0.000111708374,0.0000026003631],"about_ca_topic_score_codex":0.0024143322,"about_ca_topic_score_gemma":0.00096538325,"teacher_disagreement_score":0.0024143322,"about_ca_system_score_codex":0.0002357091,"about_ca_system_score_gemma":0.0002556625,"threshold_uncertainty_score":0.004800558},"labels":[],"label_agreement":null},{"id":"W2769556769","doi":"10.1115/1.4038570","title":"Dynamics of Multipoint Thread Turning—Part I: General Formulation","year":2017,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vibration; Thread (computing); Discretization; Chip; Torque; Modal; Control theory (sociology); Machine tool; Mechanical engineering; Engineering; Computer science; Acoustics; Mathematics; Mathematical analysis; Materials science; Physics","score_opus":0.008710026454687957,"score_gpt":0.23313559997341013,"score_spread":0.22442557351872217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2769556769","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029860903,0.0013030437,0.93949795,0.0004617451,0.0001417428,0.00012713186,0.00031861736,0.00015113848,0.02813774],"genre_scores_gemma":[0.8942965,0.0024282956,0.06416228,0.00029071883,0.00020337063,0.00064325565,0.0003423575,0.00014454914,0.037488684],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983835,0.000022534483,0.0000075780895,0.000049305338,0.00006242076,0.000019724457],"domain_scores_gemma":[0.99985325,0.00004132489,0.00003815558,0.000014718466,0.000041903026,0.000010529915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033694785,0.0007275465,0.00064140995,0.0004558016,0.00032683968,0.0010715659,0.0009162692,0.001400759,0.0046986598],"category_scores_gemma":[0.000522479,0.0003516925,0.0008111723,0.0003174398,0.0008376007,0.0011156189,0.0009716001,0.00091595756,0.0008160959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003701101,0.000043841144,0.00081401126,0.00020347943,0.000016201853,0.00022207918,0.00021183831,0.88043493,0.011878397,0.090456314,0.00140067,0.014281241],"study_design_scores_gemma":[0.0000070186006,0.00003060977,0.000357084,0.000013295094,0.0000038211115,0.00004866739,0.00003357712,0.98597974,0.0005650725,0.0107159335,0.0022354303,0.0000098814035],"about_ca_topic_score_codex":0.004244732,"about_ca_topic_score_gemma":0.0020958758,"teacher_disagreement_score":0.0046986598,"about_ca_system_score_codex":0.0006728525,"about_ca_system_score_gemma":0.00070204725,"threshold_uncertainty_score":0.01571858},"labels":[],"label_agreement":null},{"id":"W2769685469","doi":"10.1115/1.4038434","title":"Output-Only Modal Analysis of Micromilling Systems","year":2017,"lang":"en","type":"article","venue":"Journal of Micro and Nano-Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Laser Doppler vibrometer; Frequency response; Impulse response; Hammer; Modal testing; Modal analysis; Acoustics; Modal; Vibration; Structural engineering; Stiffness; Natural frequency; Engineering; Operational Modal Analysis; Materials science; Mathematics; Physics; Laser; Optics; Mathematical analysis","score_opus":0.009730594580594176,"score_gpt":0.23129449555365839,"score_spread":0.22156390097306422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2769685469","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029867908,0.000093281764,0.9656244,0.000038295682,0.000008806504,0.000027329257,0.00009948408,0.000213078,0.0040273997],"genre_scores_gemma":[0.87403077,0.00026082437,0.118134074,0.00004152463,0.0000344676,0.000118693126,0.00025697422,0.00010588507,0.0070168343],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997514,0.000051444964,0.000008156927,0.0000400736,0.00011817451,0.000030778545],"domain_scores_gemma":[0.9997137,0.00014196658,0.00003378707,0.000024902547,0.00007755171,0.000007919853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026931684,0.0005496455,0.00025739413,0.0003474576,0.00023067645,0.0005083571,0.00035630222,0.00030758994,0.003909925],"category_scores_gemma":[0.0009001413,0.00012367422,0.0003285376,0.00019857065,0.00023178851,0.0006275728,0.0004776246,0.0003945081,0.00046380857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015720249,0.00010084687,0.0021580278,0.0003591116,0.000058953974,0.00022943635,0.0004851515,0.5035283,0.19645575,0.06455546,0.0016366113,0.23027512],"study_design_scores_gemma":[0.00000301277,0.000032190597,0.0006665917,0.0000068862832,0.0000049979135,0.00004180446,0.000026782067,0.9867596,0.005784171,0.0052902545,0.001373398,0.0000103758675],"about_ca_topic_score_codex":0.0012559096,"about_ca_topic_score_gemma":0.0013149375,"teacher_disagreement_score":0.003909925,"about_ca_system_score_codex":0.0002581211,"about_ca_system_score_gemma":0.0002340345,"threshold_uncertainty_score":0.013079941},"labels":[],"label_agreement":null},{"id":"W2772710346","doi":"10.3390/fib5040046","title":"Influence of Cutting Temperature on the Tensile Strength of a Carbon Fiber-Reinforced Polymer","year":2017,"lang":"en","type":"article","venue":"Fibers","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; École de Technologie Supérieure","funders":"","keywords":"Materials science; Composite material; Epoxy; Abrasive; Ultimate tensile strength; Trimming; Delamination (geology); Tool wear; Carbon fibers; Diamond; Composite number; Machining; Metallurgy; Mechanical engineering","score_opus":0.00610230210827553,"score_gpt":0.2192968517199465,"score_spread":0.21319454961167097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2772710346","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977581,0.00065000803,0.0010172345,0.000013059633,0.000016996753,0.0000076547785,0.00005105106,0.000024156427,0.00046177808],"genre_scores_gemma":[0.99831235,0.00020074222,0.00090373855,0.000008339567,0.000004427983,0.0000054028337,0.000056152596,0.000014067433,0.0004948897],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996389,0.00003783584,0.000028557217,0.00005815347,0.00017879318,0.00005769415],"domain_scores_gemma":[0.9986866,0.0005052117,0.00028982954,0.00008546292,0.00033887094,0.00009406301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035386172,0.0003568228,0.0002085935,0.0003368635,0.00013932073,0.00027761667,0.00014577081,0.00030404635,0.001162607],"category_scores_gemma":[0.0008995707,0.00025844242,0.00029142702,0.00018880304,0.00018090161,0.00019635088,0.00012394943,0.00036838255,0.000283744],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017629233,0.00003429219,0.001157326,0.00006615043,0.000017093316,0.00007407141,0.000041985862,0.00038181397,0.9946518,0.000010387989,0.000021983864,0.0033667407],"study_design_scores_gemma":[0.0000049724035,0.0011714685,0.021033136,0.000011437875,0.000033927783,0.00011855193,0.000054678894,0.001587988,0.9755613,0.000012490755,0.00039954312,0.000010447958],"about_ca_topic_score_codex":0.00029353373,"about_ca_topic_score_gemma":0.00064026203,"teacher_disagreement_score":0.001162607,"about_ca_system_score_codex":0.00009504151,"about_ca_system_score_gemma":0.000104481995,"threshold_uncertainty_score":0.0038893223},"labels":[],"label_agreement":null},{"id":"W2774855789","doi":"10.1016/j.csite.2017.12.002","title":"Case study of laser hardening process applied to 4340 steel cylindrical specimens using simulation and experimental validation","year":2017,"lang":"en","type":"article","venue":"Case Studies in Thermal Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Multiphysics; Finite element method; Discretization; Materials science; Hardening (computing); Finite difference method; Boundary value problem; Experimental data; Mechanics; Finite difference; Mechanical engineering; Computer science; Structural engineering; Composite material; Mathematics; Engineering; Mathematical analysis; Physics; Layer (electronics)","score_opus":0.057074731897837294,"score_gpt":0.35722374061189166,"score_spread":0.30014900871405437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2774855789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9714788,0.00014046428,0.025957845,0.00003980216,0.000016042832,0.000086898435,0.00016484484,0.00020415965,0.0019111122],"genre_scores_gemma":[0.9891872,0.000059789825,0.009899746,0.0000044465655,0.0000018699945,0.00003511572,0.00005956928,0.00001503022,0.00073723774],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99968815,0.000056855595,0.000018904959,0.000055531596,0.00014127657,0.000039318358],"domain_scores_gemma":[0.99926513,0.00031093974,0.00007905311,0.00015148256,0.0001670947,0.000026161648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068896875,0.00059721037,0.00049812667,0.00040224704,0.0004926419,0.00037365578,0.0008852215,0.0013561983,0.0010413408],"category_scores_gemma":[0.0009008157,0.00025914342,0.00054004014,0.000441787,0.00058073096,0.00031221192,0.00028345035,0.0003548307,0.00022119378],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039943028,0.00032138222,0.007696405,0.00050155906,0.00003522317,0.0023107443,0.00052491453,0.80658954,0.1581703,0.0015796644,0.00050562323,0.021365197],"study_design_scores_gemma":[0.00003850955,0.0009826503,0.007168424,0.000020147998,0.000031199965,0.0004916706,0.000292814,0.84184194,0.1468066,0.0003060249,0.0019749992,0.0000451099],"about_ca_topic_score_codex":0.0036903871,"about_ca_topic_score_gemma":0.0053491793,"teacher_disagreement_score":0.0036903871,"about_ca_system_score_codex":0.00047933785,"about_ca_system_score_gemma":0.0004816568,"threshold_uncertainty_score":0.0073378086},"labels":[],"label_agreement":null},{"id":"W2775710086","doi":"10.1007/s00170-017-1353-3","title":"A new approach to generating trochoidal tool paths for effective corner machining","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Machining; Tool path; Enhanced Data Rates for GSM Evolution; Path (computing); Mechanical engineering; Engineering; Cutting tool; Machine tool; Moment (physics); Computer science; Engineering drawing; Physics","score_opus":0.008185045876668358,"score_gpt":0.26149325101026144,"score_spread":0.2533082051335931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2775710086","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006438848,0.000044771274,0.98872757,0.000037750982,0.00003953448,0.00005159554,0.000030422474,0.00037788035,0.0042515653],"genre_scores_gemma":[0.13544025,0.000094713825,0.85979915,0.00004403426,0.000017461345,0.00010987834,0.0001125012,0.00019978613,0.0041821613],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971384,0.000024192124,0.000010967414,0.000052899806,0.00017074197,0.00002728877],"domain_scores_gemma":[0.9997706,0.0000516679,0.000019044664,0.00005889921,0.00008708452,0.000012699967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002192392,0.0006256418,0.00044091046,0.00071900897,0.00053851557,0.00073905755,0.0012320786,0.00090608303,0.005023051],"category_scores_gemma":[0.00063279516,0.0004784965,0.00069769396,0.0005049974,0.0005039825,0.00066385866,0.0010867325,0.0010703717,0.0008797072],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013266977,0.00024424115,0.0007517394,0.00032172858,0.000060836413,0.00020339573,0.00029364583,0.41036913,0.13346122,0.08215591,0.0040560053,0.36794943],"study_design_scores_gemma":[0.000023271805,0.000103000624,0.00015128161,0.000017204811,0.000015012744,0.000111762405,0.000031089898,0.9631869,0.016224971,0.011851327,0.008264684,0.000019409266],"about_ca_topic_score_codex":0.0011425267,"about_ca_topic_score_gemma":0.003406947,"teacher_disagreement_score":0.005023051,"about_ca_system_score_codex":0.00036249295,"about_ca_system_score_gemma":0.0007961004,"threshold_uncertainty_score":0.016803801},"labels":[],"label_agreement":null},{"id":"W2781491255","doi":"10.15517/ri.v28i1.29257","title":"Desarrollo de un Modelo Virtual para el Conformado de Aceros Inoxidables","year":2017,"lang":"es","type":"article","venue":"Ingeniería","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bombardier (Canada)","funders":"","keywords":"Physics; Humanities; Philosophy","score_opus":0.015244080539142809,"score_gpt":0.2831466444161674,"score_spread":0.26790256387702455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781491255","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11687034,0.00036857446,0.86739886,0.00023300755,0.00018470811,0.000106148684,0.00023830988,0.0013872887,0.013212711],"genre_scores_gemma":[0.8378793,0.00060579414,0.14448613,0.00008553571,0.000028548593,0.000245679,0.00028032975,0.00036151893,0.016027266],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933296,0.00010711362,0.000028247485,0.0001031054,0.00037240182,0.000056131415],"domain_scores_gemma":[0.9994904,0.00016129008,0.000055737804,0.00008608161,0.00017733687,0.000029159477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074037473,0.00084750314,0.00066412915,0.00050158694,0.0005089517,0.00178022,0.001035878,0.0009871837,0.004365007],"category_scores_gemma":[0.0015044041,0.0006800386,0.0010741476,0.0003289513,0.00069236517,0.0013717833,0.00082319503,0.0008743136,0.0008123806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018230961,0.00006536492,0.0016901251,0.00017362343,0.000034157452,0.00012361699,0.00027976153,0.9062543,0.04194105,0.016963713,0.00052732864,0.031764645],"study_design_scores_gemma":[0.0000139518925,0.00012953616,0.00072825776,0.00003216983,0.00002417225,0.00005166547,0.00007564891,0.97297204,0.01609503,0.0030102422,0.006838264,0.000029014445],"about_ca_topic_score_codex":0.007843337,"about_ca_topic_score_gemma":0.0045481515,"teacher_disagreement_score":0.007843337,"about_ca_system_score_codex":0.0009205092,"about_ca_system_score_gemma":0.0013955436,"threshold_uncertainty_score":0.0155953765},"labels":[],"label_agreement":null},{"id":"W2781536165","doi":"10.2514/6.2018-1899","title":"ICME Approach to Compression Strength after Impact Modeling","year":2018,"lang":"en","type":"article","venue":"2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Compression (physics); Computer science; Materials science; Composite material","score_opus":0.010022208228101638,"score_gpt":0.24318041005133736,"score_spread":0.23315820182323574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781536165","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008516409,0.00025614,0.91413206,0.00023356803,0.000200945,0.00012755873,0.00043605175,0.0007769002,0.0753204],"genre_scores_gemma":[0.69720703,0.0008292176,0.18883125,0.00073548727,0.0004220291,0.0009516352,0.0012175738,0.0018944704,0.10791132],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996076,0.0000635988,0.0000142599065,0.000047209014,0.00020874417,0.000058549194],"domain_scores_gemma":[0.99941266,0.00018574086,0.00004282527,0.0001203268,0.00020601327,0.000032505202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054359116,0.00089239964,0.0010454805,0.001390834,0.0008682093,0.0012347368,0.0033598694,0.0022399153,0.017597158],"category_scores_gemma":[0.0020046895,0.0007164914,0.0011971126,0.0009303594,0.0007102607,0.0014562233,0.0012829126,0.0018712583,0.0027761275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021943537,0.00005312912,0.00018351925,0.000054083095,0.000032241285,0.000113019596,0.000038712722,0.92641705,0.0017716167,0.05679327,0.0017598504,0.012761645],"study_design_scores_gemma":[0.0000028259406,0.0000065870154,0.000045264234,0.0000051684724,0.000003751873,0.000010690528,0.0000050920758,0.9947679,0.00034750736,0.002598143,0.0022031118,0.0000039720567],"about_ca_topic_score_codex":0.013795223,"about_ca_topic_score_gemma":0.010707372,"teacher_disagreement_score":0.017597158,"about_ca_system_score_codex":0.0009972696,"about_ca_system_score_gemma":0.0013213432,"threshold_uncertainty_score":0.05886841},"labels":[],"label_agreement":null},{"id":"W2782608328","doi":"10.1177/0021998317752501","title":"Stress analysis of a carbon fiber-reinforced epoxy plate with a hole undergoing tension: A comparison of finite element analysis, strain gages, and infrared thermography","year":2018,"lang":"en","type":"article","venue":"Journal of Composite Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Victoria Hospital; Toronto Metropolitan University","funders":"","keywords":"Thermography; Materials science; Strain gauge; Composite material; Epoxy; Finite element method; Stress (linguistics); Infrared; von Mises yield criterion; Ultimate tensile strength; Tension (geology); Composite number; Structural engineering; Optics","score_opus":0.008532731484246762,"score_gpt":0.24509790458302477,"score_spread":0.236565173098778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782608328","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96008277,0.00020049572,0.038505156,0.00003544414,0.000028264734,0.000033718203,0.00006649333,0.00020693135,0.00084071286],"genre_scores_gemma":[0.97159404,0.00016157574,0.027078155,0.00001745454,0.0000095688965,0.00003611987,0.00008557645,0.000029715193,0.0009877373],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996451,0.000026539306,0.000023211018,0.00006482847,0.00021810111,0.00002221398],"domain_scores_gemma":[0.9993274,0.00025574505,0.000104441635,0.00009027549,0.00018882508,0.000033272634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051213754,0.00064657815,0.00040209503,0.00087573426,0.00023765773,0.0004440391,0.0007901577,0.0005813124,0.00093949394],"category_scores_gemma":[0.00071727607,0.00038428878,0.0004151982,0.00037989704,0.00063868536,0.0004898623,0.00025430764,0.00029034127,0.0001963286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002019367,0.00011180543,0.0054572383,0.00017246259,0.000026096599,0.00022753296,0.00025332038,0.019249687,0.94543815,0.00035121402,0.0000900364,0.028420482],"study_design_scores_gemma":[0.000022908773,0.0008620903,0.036882717,0.000045554065,0.000078279554,0.0005299734,0.00044090257,0.33890343,0.6206258,0.00028221612,0.0012339338,0.000092187925],"about_ca_topic_score_codex":0.00090704445,"about_ca_topic_score_gemma":0.0017333159,"teacher_disagreement_score":0.00093949394,"about_ca_system_score_codex":0.0002995649,"about_ca_system_score_gemma":0.000371602,"threshold_uncertainty_score":0.0031428933},"labels":[],"label_agreement":null},{"id":"W2782753569","doi":"10.1115/imece2017-70689","title":"A Design of Experiment to Study the Effects of Cutting Speed and Feed on the Generated Drilling Thrust and Torque in Aluminum Alloys","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; U.S. Department of Energy","keywords":"Thrust; Drilling; Torque; Dynamometer; Drill; Machining; Mechanical engineering; Structural engineering; Engineering; Physics","score_opus":0.020873091846691106,"score_gpt":0.26677939955041674,"score_spread":0.24590630770372562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782753569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81239736,0.0006012359,0.121011555,0.00017783079,0.00093542243,0.057366,0.0014828005,0.00056709,0.00546073],"genre_scores_gemma":[0.44495752,0.00059367134,0.3734862,0.00045110993,0.00016431547,0.17185083,0.00071757723,0.00014640242,0.007632344],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.98778266,0.0048509594,0.0015801747,0.0021946442,0.0026890342,0.0009025675],"domain_scores_gemma":[0.98213184,0.0114814285,0.0021297398,0.0013946856,0.0024400733,0.00042216593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011974918,0.0016619791,0.002170691,0.0007841024,0.0010776633,0.0015155633,0.0020423993,0.0018991847,0.0061089993],"category_scores_gemma":[0.012664436,0.0009294713,0.001183685,0.0006749208,0.0011338751,0.00077562046,0.0010450104,0.0016746512,0.00066714536],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.06860249,0.056718186,0.01446776,0.011775272,0.00095074775,0.0007917127,0.0043922067,0.024721544,0.6462589,0.010154979,0.0023236158,0.15884265],"study_design_scores_gemma":[0.016653894,0.61099964,0.04951862,0.000611233,0.0015853617,0.00036956204,0.001578118,0.05242737,0.22401272,0.004896334,0.036823776,0.0005233954],"about_ca_topic_score_codex":0.00063242466,"about_ca_topic_score_gemma":0.00076045824,"teacher_disagreement_score":0.011974918,"about_ca_system_score_codex":0.00092962716,"about_ca_system_score_gemma":0.0021387332,"threshold_uncertainty_score":0.06333017},"labels":[],"label_agreement":null},{"id":"W2784203964","doi":"10.1007/s00170-017-1527-z","title":"Performance evaluation of Ti–6Al–4V machining using nano-cutting fluids under minimum quantity lubrication","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":148,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machinability; Materials science; Lubrication; Machining; Titanium alloy; Metallurgy; Cutting fluid; Nano-; Titanium; Tool wear; Composite material; Alloy","score_opus":0.021045469332367457,"score_gpt":0.2958149494505334,"score_spread":0.27476948011816593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2784203964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99590343,0.00042407843,0.0023662222,0.00003862267,0.000021236829,0.000007701342,0.000036214053,0.000082392435,0.0011201733],"genre_scores_gemma":[0.9980792,0.00006717844,0.001261144,0.0000045815623,0.0000026393861,0.0000024550902,0.000030876967,0.000008213689,0.0005437353],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971837,0.000025881143,0.00001544806,0.000041790667,0.00015753384,0.00004090684],"domain_scores_gemma":[0.9994986,0.0001342509,0.00009743191,0.000038620332,0.00019996385,0.00003107282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000286789,0.000295091,0.00035053148,0.00028501722,0.00032109994,0.00037627076,0.0005332647,0.0004927525,0.0010478701],"category_scores_gemma":[0.00062108884,0.0001392704,0.00020700706,0.00021115085,0.00022631802,0.00042659076,0.00018579797,0.00014788189,0.00018696679],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015823393,0.000097246266,0.0015082855,0.00030139094,0.00002535367,0.000108042805,0.00011565154,0.016617872,0.9618495,0.00021602369,0.00018870874,0.017389588],"study_design_scores_gemma":[0.000036603207,0.0028512862,0.00686091,0.000009153333,0.000038594382,0.00011848462,0.00010423615,0.096864514,0.8917076,0.00008069092,0.0012999179,0.000028123439],"about_ca_topic_score_codex":0.0013785812,"about_ca_topic_score_gemma":0.0017459323,"teacher_disagreement_score":0.0013785812,"about_ca_system_score_codex":0.00031317605,"about_ca_system_score_gemma":0.00030506056,"threshold_uncertainty_score":0.003505528},"labels":[],"label_agreement":null},{"id":"W2785158842","doi":"10.1115/1.4039107","title":"Finite Strip Modeling of the Varying Dynamics of Shell-Like Structures During Machining Processes","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Finite element method; Machining; Vibration; Shell (structure); Structural engineering; Displacement (psychology); Natural frequency; Boundary value problem; Frequency response; Engineering; Mathematical analysis; Acoustics; Mathematics; Mechanical engineering; Physics","score_opus":0.006456915397935823,"score_gpt":0.2056831137471872,"score_spread":0.19922619834925137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785158842","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3640425,0.00018889914,0.6300799,0.00005896594,0.000021753513,0.000039485,0.00010902574,0.00039065556,0.0050687906],"genre_scores_gemma":[0.96379095,0.00009072084,0.034383036,0.000007419789,0.000004004203,0.00003359983,0.00006327371,0.000027568545,0.0015992866],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999416,0.000019544723,0.000003336299,0.000009033713,0.000019373474,0.0000071033196],"domain_scores_gemma":[0.99982125,0.00009548587,0.00002496958,0.000025532188,0.000024813167,0.00000805674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021390874,0.00027956386,0.0002707062,0.00018455618,0.00014874554,0.00027562628,0.00053811533,0.0005462398,0.0007884233],"category_scores_gemma":[0.0004182772,0.00017122818,0.0002752416,0.00018598957,0.00032653354,0.00029148787,0.00018282606,0.0002251472,0.00014860874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000310462,0.000017405491,0.00089295796,0.00003354091,0.00000698715,0.000085662956,0.00006391181,0.9689239,0.02096894,0.0016917995,0.000084644766,0.007199297],"study_design_scores_gemma":[0.0000011827278,0.000009727802,0.0001660502,0.000001224564,7.933072e-7,0.000009991147,0.000004918389,0.9985372,0.0010204269,0.00012385465,0.0001234491,0.0000013016211],"about_ca_topic_score_codex":0.001671752,"about_ca_topic_score_gemma":0.0011762097,"teacher_disagreement_score":0.001671752,"about_ca_system_score_codex":0.0001780503,"about_ca_system_score_gemma":0.00032913228,"threshold_uncertainty_score":0.0033239722},"labels":[],"label_agreement":null},{"id":"W2785885926","doi":"10.6000/1929-5995.2017.06.04.4","title":"A Review Study on the Traditional Machining of Composite Materials","year":2017,"lang":"en","type":"review","venue":"Journal of Research Updates in Polymer Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Materials science; Delamination (geology); Composite number; Composite material; Homogeneous; Mechanical engineering; Engineering; Metallurgy","score_opus":0.3047601532153148,"score_gpt":0.49647506434800254,"score_spread":0.19171491113268774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785885926","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023639669,0.9977702,0.00016973449,0.000143944,0.00017786426,0.00000842451,0.000033411357,0.000006403837,0.001453599],"genre_scores_gemma":[0.0007925475,0.99815613,0.0002725702,0.00008809939,0.0001273718,0.0000075157773,0.00003600211,0.000001555191,0.0005182621],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99967146,0.000040427134,0.00006371937,0.00006903539,0.00013215016,0.000023197557],"domain_scores_gemma":[0.9991634,0.00046796937,0.00013365361,0.000020430052,0.00017581959,0.00003880242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005345591,0.0008496087,0.0011691689,0.0038565723,0.00034303076,0.0012497349,0.0008483176,0.0008763874,0.0060812766],"category_scores_gemma":[0.0011978978,0.00034821214,0.000798526,0.00429757,0.00037956217,0.0015956773,0.00049833895,0.00097032683,0.0017740306],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008118471,0.00012419702,0.00036621775,0.10760114,0.00015250237,0.00037310383,0.00018051096,0.0005217732,0.0031728498,0.00412945,0.02715879,0.8561383],"study_design_scores_gemma":[0.000007801323,0.00011613937,0.001257388,0.012198773,0.00020988128,0.0014303934,0.00009980409,0.00007593976,0.0008768909,0.00088433124,0.98282284,0.000019856392],"about_ca_topic_score_codex":0.0011786186,"about_ca_topic_score_gemma":0.0017639273,"teacher_disagreement_score":0.0060812766,"about_ca_system_score_codex":0.00044117027,"about_ca_system_score_gemma":0.0018042953,"threshold_uncertainty_score":0.0203439},"labels":[],"label_agreement":null},{"id":"W2786226702","doi":"10.21535/ijrm.v4i1.971","title":"Characterization and Optimization of Machinability and Environmental Impact of Machining of Ti-6Al-4V with Minimum Quantity Lubrication","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Mechatronics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Lubrication; Machining; Nozzle; Machinability; Materials science; Surface roughness; Surface finish; Metallurgy; Titanium alloy; Mechanical engineering; Composite material; Engineering; Alloy","score_opus":0.006422662117234992,"score_gpt":0.24793936851921416,"score_spread":0.24151670640197917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2786226702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977545,0.0002724637,0.0016138875,0.000013333811,0.000003845451,0.000008567365,0.000048700407,0.000019846526,0.00026486427],"genre_scores_gemma":[0.9973224,0.0001385572,0.0020781043,0.0000047001895,0.000001873106,0.0000068783665,0.00009075761,0.000017514762,0.00033923818],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996032,0.000039475595,0.000022958287,0.000042509106,0.00024854302,0.0000432285],"domain_scores_gemma":[0.99958426,0.00011259105,0.00011452716,0.000036918747,0.00013278834,0.000018991463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003158757,0.00020168972,0.00031528447,0.0003538344,0.00017180417,0.00036892714,0.00033631895,0.00032230528,0.00043953068],"category_scores_gemma":[0.000825477,0.00013860651,0.00021479576,0.00026400643,0.00031941486,0.00031657933,0.00018972791,0.00019657904,0.00008671925],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014106158,0.000019116846,0.0012293108,0.000117103526,0.000007155088,0.000052723935,0.00006604681,0.0012050096,0.9939606,0.000047037145,0.000022759217,0.0031321128],"study_design_scores_gemma":[0.000008519101,0.0008154564,0.008731788,0.0000055001983,0.000017271304,0.00007976237,0.00009297488,0.0061474447,0.9832101,0.000038840873,0.0008396781,0.000012585674],"about_ca_topic_score_codex":0.00047498892,"about_ca_topic_score_gemma":0.0010390135,"teacher_disagreement_score":0.00047498892,"about_ca_system_score_codex":0.0002432922,"about_ca_system_score_gemma":0.00014410644,"threshold_uncertainty_score":0.0017651916},"labels":[],"label_agreement":null},{"id":"W2789646893","doi":"10.5604/01.3001.0010.8811","title":"INTELLIGENT MACHINING: REAL-TIME TOOL CONDITION MONITORING AND INTELLIGENT ADAPTIVE CONTROL SYSTEMS","year":2018,"lang":"en","type":"article","venue":"Journal of Machine Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"","keywords":"Machining; Machine tool; Process (computing); Reliability (semiconductor); Engineering; Controller (irrigation); Computer science; Condition monitoring; Manufacturing engineering; Control engineering; Reliability engineering; Mechanical engineering","score_opus":0.007663274685495045,"score_gpt":0.23367233802729975,"score_spread":0.2260090633418047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789646893","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010612372,0.026649686,0.9417419,0.0013174302,0.0006727921,0.00009233259,0.00011785992,0.003218076,0.0155775985],"genre_scores_gemma":[0.7265573,0.02689384,0.22048415,0.0011699414,0.0020962476,0.00022546394,0.0006925446,0.00022242637,0.021658028],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99942195,0.00008236761,0.000029641116,0.00014974637,0.00027986712,0.000036448837],"domain_scores_gemma":[0.9996407,0.00010781533,0.00007583412,0.00005124156,0.00010372296,0.000020793792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004117488,0.00064514886,0.0005292552,0.0005327607,0.00016004831,0.0011560984,0.0009472074,0.0009825279,0.0017843473],"category_scores_gemma":[0.0008488509,0.00021121105,0.00023811315,0.00078918133,0.0005149203,0.0014617085,0.00056756934,0.0008554148,0.00075598934],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020655053,0.00011302707,0.0012728455,0.00069422735,0.000073428615,0.00022083074,0.00015205365,0.049117636,0.038611487,0.02669184,0.010320412,0.8725257],"study_design_scores_gemma":[0.000068559966,0.0006075609,0.00589071,0.0002444955,0.00010499398,0.0009093914,0.000118101605,0.7436993,0.026580548,0.05849509,0.16313684,0.00014431744],"about_ca_topic_score_codex":0.0008884845,"about_ca_topic_score_gemma":0.0005172594,"teacher_disagreement_score":0.0017843473,"about_ca_system_score_codex":0.0003189499,"about_ca_system_score_gemma":0.00028556504,"threshold_uncertainty_score":0.005969286},"labels":[],"label_agreement":null},{"id":"W2790474171","doi":"10.5267/j.esm.2018.2.002","title":"Experimental investigation on friction drilling of titanium alloy","year":2018,"lang":"en","type":"article","venue":"Engineering Solid Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Universiti Putra Malaysia","keywords":"Materials science; Drilling; Alloy; Titanium alloy; Metallurgy; Titanium; Composite material","score_opus":0.011296164332873088,"score_gpt":0.2249505256154733,"score_spread":0.2136543612826002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790474171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99216664,0.0003568243,0.0053556073,0.00003379,0.00003882405,0.000041448573,0.00016101163,0.000058117792,0.0017878832],"genre_scores_gemma":[0.99263436,0.00020649479,0.0055452543,0.000013174813,0.0000055711976,0.000025823656,0.00011451984,0.000014596768,0.0014402586],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99947864,0.00003602005,0.000032550593,0.00010228838,0.00026917344,0.00008140517],"domain_scores_gemma":[0.9992499,0.00017877338,0.00011158901,0.00013077295,0.00030353645,0.00002545013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043178294,0.00032024912,0.0003803973,0.00039866677,0.00040366928,0.00022755635,0.00045968086,0.0005736579,0.0015993675],"category_scores_gemma":[0.0009171409,0.00020971647,0.0002754038,0.000361643,0.00037105384,0.0003800622,0.00025569834,0.00024698218,0.00021338381],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033433014,0.0001201739,0.0014513328,0.0002916946,0.000008206093,0.00025912866,0.000320498,0.0013468476,0.98876137,0.0002778852,0.00015916568,0.0066693733],"study_design_scores_gemma":[0.000045038454,0.003323004,0.014240939,0.000030244251,0.000040130217,0.00048729512,0.00037446237,0.008916624,0.96709836,0.00016712317,0.005230779,0.00004599092],"about_ca_topic_score_codex":0.000717084,"about_ca_topic_score_gemma":0.0011938204,"teacher_disagreement_score":0.0015993675,"about_ca_system_score_codex":0.0001867619,"about_ca_system_score_gemma":0.0001854806,"threshold_uncertainty_score":0.005350411},"labels":[],"label_agreement":null},{"id":"W2792119840","doi":"10.1007/s00170-018-1801-8","title":"Application of high-angle helical-grooved vitrified wheels to cylindrical plunge grinding","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Materials science; Roundness (object); Surface roughness; Grinding wheel; Groove (engineering); Specific energy; Composite material; Mechanical engineering; Metallurgy; Engineering; Physics","score_opus":0.005848043791015142,"score_gpt":0.2479244562923072,"score_spread":0.24207641250129205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792119840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91661316,0.00074854697,0.07887202,0.00006095317,0.00009963156,0.00007185588,0.000069949776,0.00028167132,0.003182147],"genre_scores_gemma":[0.97215706,0.00017389526,0.02622009,0.000009106759,0.0000045921543,0.0000122861375,0.000036889483,0.000019463396,0.001366603],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998179,0.000013069805,0.000010930526,0.000032314438,0.00008595884,0.000039887367],"domain_scores_gemma":[0.99980885,0.00003680533,0.000043250715,0.00004790569,0.00004153942,0.000021617183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029616372,0.00022562126,0.00029766883,0.00024315844,0.00021427496,0.00037060716,0.0003749607,0.00029784485,0.0009582275],"category_scores_gemma":[0.00039989545,0.00022025536,0.00025964176,0.00022570947,0.0004104954,0.0002740815,0.00039928654,0.00027971156,0.00022218424],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009130792,0.00003634781,0.00071876246,0.00008694948,0.000004423258,0.00007259375,0.00006699222,0.002422953,0.9799294,0.0014547316,0.00010311032,0.015012397],"study_design_scores_gemma":[0.000036997826,0.00055926933,0.005355861,0.000010589161,0.00001247425,0.00018051956,0.000062707026,0.022413217,0.9654025,0.00029485775,0.0056420243,0.00002911052],"about_ca_topic_score_codex":0.0008080047,"about_ca_topic_score_gemma":0.0018777845,"teacher_disagreement_score":0.0009582275,"about_ca_system_score_codex":0.0003202714,"about_ca_system_score_gemma":0.00048051408,"threshold_uncertainty_score":0.0032055974},"labels":[],"label_agreement":null},{"id":"W2792608712","doi":"10.1115/1.4039651","title":"Virtual Model of Gear Shaping—Part II: Elastic Deformations and Virtual Gear Metrology","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Deflection (physics); Machining; Stiffness; Spur gear; Engineering; Structural engineering; Non-circular gear; Spiral bevel gear; Mechanical engineering; Optics; Physics","score_opus":0.012205159474529659,"score_gpt":0.2192297829995064,"score_spread":0.20702462352497675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792608712","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04509521,0.00019146626,0.94806737,0.000101941456,0.00005332649,0.000037145684,0.000049054943,0.00037366507,0.0060308985],"genre_scores_gemma":[0.9385746,0.00024567408,0.055565465,0.000039467566,0.000017433409,0.0000624484,0.00006422173,0.000064265405,0.0053664637],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957174,0.00006476716,0.000016379421,0.00006676004,0.00024801714,0.000032432523],"domain_scores_gemma":[0.99961746,0.00010678514,0.00005744974,0.0001396526,0.000057412497,0.000021200369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040346058,0.00042025337,0.00051154016,0.00030500648,0.00024044885,0.00081124605,0.0011287825,0.000730225,0.0015661878],"category_scores_gemma":[0.0010818482,0.00037232714,0.00056301814,0.00029161433,0.00092135766,0.0009969472,0.0008179215,0.00053719594,0.00034613218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024902249,0.000016862776,0.00051847537,0.000022888493,0.000006622635,0.00008730052,0.00003691288,0.9688296,0.007776512,0.009506502,0.00014296728,0.013030374],"study_design_scores_gemma":[0.0000019935517,0.000017229575,0.00019102481,0.000002569581,0.0000013776148,0.000047710044,0.000005586001,0.9954731,0.0015640762,0.0019266182,0.0007629084,0.0000058486876],"about_ca_topic_score_codex":0.0018211883,"about_ca_topic_score_gemma":0.0011059754,"teacher_disagreement_score":0.0018211883,"about_ca_system_score_codex":0.0005192328,"about_ca_system_score_gemma":0.0006751344,"threshold_uncertainty_score":0.0052394867},"labels":[],"label_agreement":null},{"id":"W2792792092","doi":"10.1007/s00170-018-1759-6","title":"A comprehensive review of finite element modeling of orthogonal machining process: chip formation and surface integrity predictions","year":2018,"lang":"en","type":"review","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":90,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; École de Technologie Supérieure; Concordia University","funders":"","keywords":"Machining; Surface integrity; Finite element method; Mechanical engineering; Chip formation; Residual stress; Process (computing); Deformation (meteorology); Engineering; Tool wear; Structural engineering; Materials science; Computer science; Metallurgy; Composite material","score_opus":0.026400144899099306,"score_gpt":0.3136996331841867,"score_spread":0.2872994882850874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792792092","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023251146,0.93023354,0.061018843,0.00048053963,0.000508537,0.000039376315,0.00042892713,0.00024245547,0.004722615],"genre_scores_gemma":[0.017969627,0.9512886,0.026856374,0.00027478495,0.0005662562,0.000075645825,0.0006325562,0.00008606625,0.0022502034],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995067,0.00006875491,0.000067988374,0.00009965854,0.0002353676,0.000021513119],"domain_scores_gemma":[0.9988427,0.00061398005,0.00011852525,0.0000667298,0.00033741203,0.000020675438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008787765,0.0014661868,0.0021422163,0.0019430574,0.00026384715,0.0011685025,0.0025822425,0.0016760317,0.0027411648],"category_scores_gemma":[0.002239863,0.0008674353,0.0010355213,0.0028290893,0.00036353237,0.0014361768,0.00061019737,0.0009054065,0.001713332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057230205,0.00013175237,0.00085126224,0.019853825,0.00022151678,0.00009539882,0.000060431066,0.05989579,0.0049033617,0.008859928,0.015917983,0.88915145],"study_design_scores_gemma":[0.000049867598,0.0003517127,0.0035213793,0.009928515,0.00088109745,0.0011657976,0.0001733014,0.15013741,0.012912711,0.019495485,0.8011349,0.00024778562],"about_ca_topic_score_codex":0.0020465117,"about_ca_topic_score_gemma":0.0024089164,"teacher_disagreement_score":0.0027411648,"about_ca_system_score_codex":0.00040907695,"about_ca_system_score_gemma":0.0013147114,"threshold_uncertainty_score":0.009170115},"labels":[],"label_agreement":null},{"id":"W2793014541","doi":"10.5267/j.dsl.2017.11.003","title":"ANN and RSM approach for modelling and multi objective optimization of abrasive water jet machining process","year":2018,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Process (computing); Abrasive; Jet (fluid); Mechanical engineering; Materials science; Process engineering; Water jet; Manufacturing engineering; Response surface methodology; Engineering; Engineering drawing; Computer science; Aerospace engineering; Machine learning","score_opus":0.019030710907757497,"score_gpt":0.2816141547958688,"score_spread":0.26258344388811133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793014541","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.079633616,0.0017934504,0.8995562,0.0004065367,0.00011419129,0.00013146659,0.00028375912,0.0007358607,0.017344942],"genre_scores_gemma":[0.8984562,0.0008389435,0.091635525,0.00011709876,0.000054655768,0.0005066099,0.00039279115,0.000084299485,0.007913965],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999632,0.00014139399,0.0000251801,0.000064290434,0.00008934786,0.000047732283],"domain_scores_gemma":[0.99956125,0.0002704483,0.00005021533,0.000016343456,0.000089463545,0.000012296165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070013705,0.0012221925,0.0011120181,0.0007966821,0.00037849785,0.0010921552,0.0010112927,0.0015940116,0.002579255],"category_scores_gemma":[0.0009944689,0.00070921873,0.0013179906,0.0006536056,0.00037436158,0.0005154155,0.0005735554,0.0011436908,0.00036647217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008580054,0.000007830145,0.000106354324,0.000023377786,0.000016090626,0.000019949375,0.0000059812637,0.9960299,0.00022223358,0.00044834526,0.00006805417,0.0030431908],"study_design_scores_gemma":[0.0000012338539,0.000006438917,0.0000385785,0.000003320957,0.0000029617959,0.0000020694283,0.0000019153802,0.9995554,0.00006889479,0.00022041224,0.00009725763,0.000001552947],"about_ca_topic_score_codex":0.012118456,"about_ca_topic_score_gemma":0.007842495,"teacher_disagreement_score":0.012118456,"about_ca_system_score_codex":0.00072414364,"about_ca_system_score_gemma":0.0009401189,"threshold_uncertainty_score":0.024095833},"labels":[],"label_agreement":null},{"id":"W2793138710","doi":"10.21535/ijrm.v4i1.972","title":"Numerical and Experimental Investigation of Thermal Damage in Drilling of CFRP Composites","year":2017,"lang":"en","type":"article","venue":"International Journal of Robotics and Mechatronics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Materials science; Composite material; Drilling; Machining; Thermal; Carbon fiber reinforced polymer; Finite element method; Anisotropy; Aerospace; Thermal conduction; Fibre-reinforced plastic; Structural engineering; Composite number; Engineering; Metallurgy","score_opus":0.009810811255651244,"score_gpt":0.2602952837609856,"score_spread":0.25048447250533434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793138710","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9815896,0.00021677451,0.014492039,0.00006535092,0.000029948036,0.000028834658,0.00012619348,0.00014795303,0.0033031555],"genre_scores_gemma":[0.9937219,0.000048856913,0.005825344,0.0000049809105,0.0000022308664,0.000015684263,0.000034019846,0.000007718558,0.0003393076],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997769,0.000030001796,0.000014386373,0.000036267636,0.00010032801,0.000042020318],"domain_scores_gemma":[0.9989347,0.00054872123,0.00017998954,0.00011513751,0.00017225064,0.00004936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005213666,0.00042678582,0.00050061755,0.0005149235,0.00045722246,0.00034407096,0.0005042146,0.0010565172,0.0009722993],"category_scores_gemma":[0.0012775151,0.00024909,0.00037483618,0.0004313222,0.00090007094,0.0004092952,0.00032502317,0.00046728013,0.00008650988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002724095,0.00030799495,0.0068278615,0.0002670823,0.000020315592,0.0003734848,0.00026528098,0.8849825,0.09592667,0.0015745118,0.00032900245,0.008852766],"study_design_scores_gemma":[0.000014123288,0.00019619551,0.0030501082,0.000009992967,0.000008565897,0.000075362324,0.00005243336,0.98002166,0.01615388,0.00019273664,0.00020966545,0.000015360978],"about_ca_topic_score_codex":0.0017179921,"about_ca_topic_score_gemma":0.0016852433,"teacher_disagreement_score":0.0017179921,"about_ca_system_score_codex":0.0002954536,"about_ca_system_score_gemma":0.00027793687,"threshold_uncertainty_score":0.0034159422},"labels":[],"label_agreement":null},{"id":"W2793298284","doi":"10.1007/s00170-018-1825-0","title":"Effects of nano-cutting fluids on tool performance and chip morphology during machining Inconel 718","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":215,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Institute of Population and Public Health; Natural Sciences and Engineering Research Council of Canada; King Saud University","keywords":"Inconel; Coolant; Machinability; Machining; Materials science; Nano-; Cutting fluid; Tool wear; Lubricant; Chip formation; Metallurgy; Carbon nanotube; Composite material; Mechanical engineering; Engineering; Alloy","score_opus":0.002831449527119069,"score_gpt":0.21102510711315842,"score_spread":0.20819365758603936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793298284","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989698,0.00023389874,0.0004115497,0.000017225793,0.000013219382,0.0000034196978,0.000020312726,0.000013135572,0.0003175382],"genre_scores_gemma":[0.9989863,0.00008097314,0.00044000582,0.000009697304,0.000003834318,0.000002962123,0.000022060576,0.000011739402,0.00044242167],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99972206,0.00004055058,0.000017753579,0.000048605692,0.000084637104,0.00008637065],"domain_scores_gemma":[0.9991074,0.0005172878,0.00012188884,0.00004226107,0.00015482743,0.00005628555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032539642,0.00026973724,0.00031613538,0.00021340151,0.00037968796,0.0006914285,0.00026976733,0.00039045978,0.0015605903],"category_scores_gemma":[0.0011791448,0.0002465091,0.00020373658,0.00021012098,0.00049639185,0.00067151233,0.0002874161,0.0003712833,0.00020908256],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013543543,0.000098445336,0.0011787355,0.000073049814,0.00001379327,0.00015357768,0.00023802368,0.0016467015,0.987778,0.000076625234,0.00007157898,0.0073170126],"study_design_scores_gemma":[0.00001884184,0.0005743426,0.004555121,0.0000063520934,0.000015720712,0.00004689548,0.00013700576,0.0046709757,0.9894476,0.000031238378,0.00047860676,0.000017328475],"about_ca_topic_score_codex":0.0011929071,"about_ca_topic_score_gemma":0.002437005,"teacher_disagreement_score":0.0015605903,"about_ca_system_score_codex":0.0003748117,"about_ca_system_score_gemma":0.00034645898,"threshold_uncertainty_score":0.005220711},"labels":[],"label_agreement":null},{"id":"W2793747910","doi":"10.1115/1.4039646","title":"Virtual Model of Gear Shaping—Part I: Kinematics, Cutter–Workpiece Engagement, and Cutting Forces","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Hobbing; Kinematics; Machining; Engineering; Spiral bevel gear; Dynamometer; Mechanical engineering; Enhanced Data Rates for GSM Evolution; Structural engineering; Discretization; Geometry; Physics; Mathematics; Mathematical analysis; Classical mechanics","score_opus":0.021116782978339445,"score_gpt":0.2385176330903061,"score_spread":0.21740085011196666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793747910","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04547274,0.00021973508,0.94282573,0.00006944088,0.00004146947,0.000038204085,0.00015516307,0.00043196586,0.010745515],"genre_scores_gemma":[0.89523154,0.00054668396,0.0874863,0.00005323083,0.000025797886,0.00020506888,0.00036619714,0.00012515408,0.015959926],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986875,0.00001588597,0.000005498978,0.000028730545,0.000065116874,0.000016005602],"domain_scores_gemma":[0.99988735,0.000027659882,0.000017302213,0.000035951238,0.000021263848,0.00001057424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001305987,0.00045587093,0.0005233712,0.0002573588,0.00024276298,0.0008482178,0.0009430804,0.0007572792,0.002836341],"category_scores_gemma":[0.00031301632,0.00037221677,0.0005737298,0.0002456115,0.0006475633,0.0006329498,0.0005343783,0.00049799064,0.0007021229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015497564,0.000012927218,0.00026488517,0.00002068273,0.000004301803,0.00004541251,0.000023714743,0.9809918,0.005061952,0.0062143807,0.00015764232,0.0071867555],"study_design_scores_gemma":[0.0000027937738,0.000012845037,0.00014719753,0.0000023014975,0.0000017352843,0.000025728164,0.000004974654,0.99638665,0.0010732083,0.0011984063,0.001140498,0.000003589169],"about_ca_topic_score_codex":0.002899727,"about_ca_topic_score_gemma":0.0016773104,"teacher_disagreement_score":0.002899727,"about_ca_system_score_codex":0.0004233271,"about_ca_system_score_gemma":0.0008893209,"threshold_uncertainty_score":0.009488523},"labels":[],"label_agreement":null},{"id":"W2793925587","doi":"10.1007/s00170-018-1687-5","title":"A hybrid experimental and simulation approach to evaluate the calibration of tool wear rate models in machining","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Calibration; Tungsten carbide; Machining; Tool wear; Materials science; Range (aeronautics); Strain rate; Empirical modelling; Hardening (computing); Finite element method; Mechanical engineering; Computer science; Structural engineering; Metallurgy; Mathematics; Composite material; Engineering; Simulation; Statistics","score_opus":0.01266367387609895,"score_gpt":0.273655135706088,"score_spread":0.26099146182998906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793925587","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8347517,0.00032992652,0.15698723,0.00010233551,0.00009123243,0.00022252294,0.0005040008,0.0010997688,0.005911186],"genre_scores_gemma":[0.98388463,0.00004457348,0.0154851265,0.000010103919,0.00000426356,0.00008042569,0.00013478177,0.00002865015,0.00032761888],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926656,0.0002352027,0.00006056015,0.00010154808,0.00026874826,0.000067418776],"domain_scores_gemma":[0.9955254,0.0026161096,0.00034020786,0.0007119415,0.000747495,0.000058686102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019165073,0.00080935436,0.0006176941,0.0008161382,0.00042371868,0.0007184312,0.0013326748,0.0015395561,0.0017288161],"category_scores_gemma":[0.004452736,0.00045349536,0.00050609634,0.00074621703,0.00046284922,0.000800034,0.00045984017,0.0007071479,0.00019737444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005217459,0.0011979418,0.0056366134,0.0002496436,0.00008047323,0.0000736893,0.0001155364,0.9160993,0.04830571,0.0015699699,0.0004314987,0.025717814],"study_design_scores_gemma":[0.000032676468,0.00047119995,0.0014310032,0.0000071347713,0.000014056763,0.000027416547,0.000026757398,0.9780341,0.0194855,0.00015709676,0.0002965311,0.0000164996],"about_ca_topic_score_codex":0.0035491078,"about_ca_topic_score_gemma":0.0035130535,"teacher_disagreement_score":0.0035491078,"about_ca_system_score_codex":0.00073509174,"about_ca_system_score_gemma":0.00063248794,"threshold_uncertainty_score":0.010135591},"labels":[],"label_agreement":null},{"id":"W2795259548","doi":"10.1139/tcsme-2013-0034","title":"OPTIMIZATION OF AN ULTRATHIN CENTRIFUGAL FAN BASED ON THE TAGUCHI METHOD WITH FUZZY LOGICS","year":2013,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Centrifugal fan; Taguchi methods; Impeller; Orthogonal array; Volume (thermodynamics); Computational fluid dynamics; Flow (mathematics); Fuzzy logic; Mechanical engineering; Design of experiments; Noise (video); Engineering; Inlet; Computer science; Materials science; Mathematics; Aerospace engineering; Physics; Geometry; Statistics; Composite material","score_opus":0.007513829801637116,"score_gpt":0.2004249139639226,"score_spread":0.19291108416228547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795259548","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028011624,0.00017519917,0.9705898,0.000021302001,0.000014389125,0.000047991067,0.0000075606276,0.00006763186,0.0010644172],"genre_scores_gemma":[0.472634,0.00026506104,0.52587885,0.0000355712,0.000014740415,0.00016003018,0.000022793916,0.000020718857,0.00096817437],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993674,0.0001567934,0.0000329733,0.00007882112,0.00032214346,0.00004190352],"domain_scores_gemma":[0.99959034,0.00020555884,0.00006811758,0.000017749631,0.00010451785,0.000013643238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012159912,0.0008330942,0.0006829919,0.00063108467,0.00031076244,0.00069649145,0.0005618085,0.00043962602,0.0005440141],"category_scores_gemma":[0.00096448965,0.00034316798,0.00060421973,0.00038430563,0.000514302,0.00041982558,0.00031972348,0.00043299785,0.00009390023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001840291,0.00012208974,0.0010224049,0.00040080925,0.00007012201,0.00008253099,0.00015345647,0.66479534,0.14244594,0.008142232,0.00032348727,0.18225755],"study_design_scores_gemma":[0.000021921927,0.0002261982,0.00030329084,0.000018239602,0.00003354616,0.000037075108,0.000018810064,0.9728861,0.02422427,0.0010122657,0.0011984769,0.000019797597],"about_ca_topic_score_codex":0.0014591286,"about_ca_topic_score_gemma":0.0024139727,"teacher_disagreement_score":0.0014591286,"about_ca_system_score_codex":0.000673966,"about_ca_system_score_gemma":0.0009260442,"threshold_uncertainty_score":0.0064308643},"labels":[],"label_agreement":null},{"id":"W2795269312","doi":"10.1007/s00170-018-1948-3","title":"An experimental investigation of the influence of cutting parameters on workpiece internal temperature during Al2024-T3 milling","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Polytechnique Montréal; Bombardier (Canada)","funders":"","keywords":"Industrial and production engineering; Materials science; Mechanical engineering; Metallurgy; Engineering","score_opus":0.00466055661507564,"score_gpt":0.23808936986888268,"score_spread":0.23342881325380704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795269312","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976432,0.0001266547,0.0014714716,0.000015768243,0.0000143710395,0.000015135679,0.00010214027,0.00004138372,0.0005698152],"genre_scores_gemma":[0.9988613,0.000040599953,0.0006905168,0.000006994377,0.0000037452344,0.000009221912,0.000048853006,0.000015996018,0.00032289542],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997271,0.000024309447,0.000016619677,0.000079799785,0.00009353095,0.00005872441],"domain_scores_gemma":[0.99911624,0.0004329627,0.00013383401,0.00011767435,0.00016475089,0.00003456938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031683964,0.00041003234,0.0004198548,0.00017807611,0.0005211922,0.00035701794,0.00046908692,0.00056020194,0.0020850652],"category_scores_gemma":[0.0007903957,0.0002525291,0.00027293782,0.00033485942,0.0005019052,0.00038595614,0.00019311316,0.0003681777,0.00023790235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015235044,0.00013081482,0.0012705554,0.00013692422,0.000010515504,0.00009140242,0.00022197902,0.000853607,0.99120694,0.000049057016,0.000097954864,0.0044068843],"study_design_scores_gemma":[0.000041445728,0.0015338053,0.015198219,0.000008088854,0.00002601907,0.00008222149,0.00015283492,0.004139308,0.97812325,0.000035101115,0.000638283,0.000021475653],"about_ca_topic_score_codex":0.00072721695,"about_ca_topic_score_gemma":0.0013030618,"teacher_disagreement_score":0.0020850652,"about_ca_system_score_codex":0.0002612202,"about_ca_system_score_gemma":0.0002464313,"threshold_uncertainty_score":0.0069752336},"labels":[],"label_agreement":null},{"id":"W2796045839","doi":"10.1007/s40430-018-1156-y","title":"Multi-objective optimization of parameters in turning of N-155 iron-nickel-base superalloy using gray relational analysis","year":2018,"lang":"en","type":"article","venue":"Journal of the Brazilian Society of Mechanical Sciences and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Materials science; Surface roughness; Enhanced Data Rates for GSM Evolution; Superalloy; Scanning electron microscope; Volume (thermodynamics); Process (computing); Surface finish; Metallurgy; Mechanical engineering; Composite material; Computer science; Engineering; Artificial intelligence; Microstructure","score_opus":0.0159260989754674,"score_gpt":0.2491490203134485,"score_spread":0.2332229213379811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2796045839","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82738143,0.00076163624,0.16127741,0.0001531723,0.000045707282,0.000081331586,0.00012727648,0.00023203308,0.009939963],"genre_scores_gemma":[0.98985136,0.000066847395,0.009391559,0.000011393089,0.0000031868974,0.000021499633,0.000044038086,0.000020225601,0.00058990455],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998486,0.000045792814,0.0000071390923,0.000024695311,0.000043050706,0.000030653522],"domain_scores_gemma":[0.9996519,0.00022506669,0.00003790069,0.0000126808145,0.00005502782,0.000017336255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073316577,0.00064138946,0.00097407255,0.00079620513,0.00045970298,0.001006893,0.0005288235,0.0008947891,0.0010535697],"category_scores_gemma":[0.00082574994,0.0004652991,0.0008918832,0.00049031444,0.00045967693,0.0004353047,0.00032876257,0.0003754114,0.000080735495],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046670662,0.000033417313,0.0003422277,0.000041568575,0.0000202834,0.000039105405,0.00001795266,0.99295276,0.0022183326,0.00044764948,0.00006974457,0.003770423],"study_design_scores_gemma":[0.000004437847,0.000046035166,0.00034418135,0.0000030682602,0.000011001157,0.0000047274434,0.000015192301,0.9986725,0.00070757134,0.00013068391,0.00005789686,0.0000027767999],"about_ca_topic_score_codex":0.009625053,"about_ca_topic_score_gemma":0.00960092,"teacher_disagreement_score":0.009625053,"about_ca_system_score_codex":0.0008068575,"about_ca_system_score_gemma":0.0006924424,"threshold_uncertainty_score":0.019138038},"labels":[],"label_agreement":null},{"id":"W2796234849","doi":"10.1139/tcsme-2017-1027","title":"INVESTIGATION OF SURFACE INTEGRITY DURING TURNING INCONEL 718","year":2017,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Vikram Sarabhai Space Centre","keywords":"Surface integrity; Inconel; Residual stress; Machining; Surface roughness; Materials science; Lubrication; Carbide; Surface finish; Residual; Work (physics); Mechanical engineering; Metallurgy; Composite material; Computer science; Engineering; Alloy","score_opus":0.014953044789264281,"score_gpt":0.21637684245353933,"score_spread":0.20142379766427504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2796234849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987588,0.00014369277,0.00047859558,0.000008696083,0.0000053364415,0.000006054089,0.000039937444,0.000018813425,0.0005400226],"genre_scores_gemma":[0.9986461,0.00007133598,0.00047684752,0.000009934617,0.0000018737346,0.000004435504,0.00009471062,0.000010206033,0.0006845818],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996381,0.000025416643,0.0000117186855,0.000045844426,0.00020283337,0.00007620576],"domain_scores_gemma":[0.9994997,0.00009597895,0.000081980914,0.000047192396,0.00024753544,0.000027548562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020240714,0.00018924318,0.0002775757,0.00033386424,0.00031325698,0.00037179832,0.00022726861,0.0003776487,0.0010802504],"category_scores_gemma":[0.0005337417,0.00018964741,0.00021347518,0.0002652409,0.00027100084,0.00024847445,0.00017373935,0.00036186972,0.00019788492],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002924656,0.000041594765,0.0050340397,0.00008370686,0.00001236861,0.00030416454,0.00041223536,0.00044522967,0.98503333,0.00004028793,0.00011836043,0.008182165],"study_design_scores_gemma":[0.000012560822,0.0025725374,0.1491975,0.000024291689,0.000058619255,0.0007662469,0.0013982522,0.0050524934,0.8385515,0.00006998118,0.0022569282,0.0000390063],"about_ca_topic_score_codex":0.0013960127,"about_ca_topic_score_gemma":0.0026674315,"teacher_disagreement_score":0.0013960127,"about_ca_system_score_codex":0.00015823767,"about_ca_system_score_gemma":0.00011740219,"threshold_uncertainty_score":0.00361377},"labels":[],"label_agreement":null},{"id":"W2799277207","doi":"10.1139/tcsme-2017-0045","title":"Experimental investigation on hole quality in drilling of composite pipes","year":2018,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Drilling; Composite number; Materials science; Aluminium; Scanning electron microscope; Quality (philosophy); Process (computing); Central composite design; Composite material; Mechanical engineering; Response surface methodology; Engineering; Metallurgy; Computer science; Physics","score_opus":0.01931925356486422,"score_gpt":0.24614461371806887,"score_spread":0.22682536015320465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799277207","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919791,0.0001315736,0.007408661,0.0000102192225,0.000008453293,0.00005097891,0.00009428681,0.000051635987,0.00026516063],"genre_scores_gemma":[0.9895738,0.00013051776,0.00977531,0.000006061225,0.000003923395,0.000028101413,0.00007934797,0.000013224686,0.00038980975],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990877,0.0001568995,0.0000823063,0.00016869034,0.00041771473,0.000086743974],"domain_scores_gemma":[0.9951509,0.0020707103,0.000893076,0.0004987669,0.0012580946,0.00012843106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012492988,0.0005012302,0.0004685728,0.00037196654,0.0002790119,0.00025651095,0.00039972414,0.00061966944,0.001010003],"category_scores_gemma":[0.0027773436,0.00035713523,0.00031400958,0.0004048547,0.00062549807,0.00040421166,0.00037438943,0.00047652813,0.000109390654],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008404351,0.0004079645,0.0035562501,0.00046773494,0.000016253316,0.0002124196,0.00047183363,0.009102485,0.9770125,0.00014204686,0.00006743754,0.0077025685],"study_design_scores_gemma":[0.00006856028,0.009806923,0.017983371,0.000022331533,0.00004367934,0.00024938356,0.00027995557,0.016887525,0.95364994,0.00009881939,0.00086591067,0.000043679676],"about_ca_topic_score_codex":0.0005388118,"about_ca_topic_score_gemma":0.00082147744,"teacher_disagreement_score":0.0012492988,"about_ca_system_score_codex":0.00017009884,"about_ca_system_score_gemma":0.00023294277,"threshold_uncertainty_score":0.006606996},"labels":[],"label_agreement":null},{"id":"W2799710991","doi":"10.1016/j.cirp.2018.04.065","title":"A novel approach for real-time prediction and prevention of tool chipping in intermittent turning machining","year":2018,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Machine tool; SIGNAL (programming language); Cutting tool; Signal processing; Engineering; Computer science; Mechanical engineering; Control engineering; Digital signal processing; Electronic engineering","score_opus":0.026146442724572984,"score_gpt":0.27970262641896476,"score_spread":0.25355618369439176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799710991","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09977208,0.00034361426,0.89756095,0.00006782695,0.00010789111,0.000046063135,0.000051720825,0.0008257658,0.0012241793],"genre_scores_gemma":[0.86009586,0.00014556109,0.13816644,0.000048568763,0.000048824702,0.000059102407,0.0000687264,0.000038169208,0.0013287038],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998362,0.000020734486,0.00000781739,0.000052365354,0.0000574313,0.000025323487],"domain_scores_gemma":[0.9997638,0.00008829667,0.000038158316,0.000024185145,0.00006900971,0.000016555809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023711383,0.0005685683,0.00067471113,0.00046260929,0.00024140283,0.00044649027,0.0007245302,0.0006452894,0.00064250024],"category_scores_gemma":[0.00046943224,0.00027338107,0.00038551286,0.00026057693,0.00024238438,0.00033639465,0.00038142808,0.00041123826,0.00013165438],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006228365,0.0005345684,0.0061330893,0.0002446422,0.00014395261,0.00027995717,0.0001357671,0.47826573,0.11491922,0.0027465404,0.0011777481,0.39479592],"study_design_scores_gemma":[0.000005335582,0.00006701366,0.0005839614,0.0000022047134,0.000010216583,0.000019991678,0.0000048255306,0.99582666,0.0031225085,0.00018000559,0.00017160569,0.0000055817054],"about_ca_topic_score_codex":0.002227284,"about_ca_topic_score_gemma":0.0033340713,"teacher_disagreement_score":0.002227284,"about_ca_system_score_codex":0.00022110184,"about_ca_system_score_gemma":0.0004138353,"threshold_uncertainty_score":0.0044286847},"labels":[],"label_agreement":null},{"id":"W2799711417","doi":"10.1016/j.ijmachtools.2018.04.007","title":"On-line chatter detection in milling using drive motor current commands extracted from CNC","year":2018,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":174,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Engineering; Frequency response; Transfer function; Numerical control; Torque; Control theory (sociology); Digital control; Controller (irrigation); Vibration; Noise (video); Bandwidth (computing); Line (geometry); Control engineering; Computer science; Machining; Acoustics; Electronic engineering; Mechanical engineering; Control (management); Electrical engineering","score_opus":0.018026341214185636,"score_gpt":0.2845923449828631,"score_spread":0.2665660037686775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799711417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9124307,0.000791239,0.07885187,0.00010644335,0.00015204515,0.00008240262,0.0005997148,0.0015006074,0.005484847],"genre_scores_gemma":[0.9893,0.0000867768,0.009009581,0.000026226286,0.000017733126,0.000013510672,0.00017771566,0.000043565007,0.0013250299],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99963605,0.000029033634,0.00001599797,0.0000534163,0.00021878222,0.000046679612],"domain_scores_gemma":[0.99907243,0.00030270356,0.00012443334,0.000060852297,0.000379389,0.00006013199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022403774,0.00051925535,0.0004690279,0.0012079852,0.00022305707,0.000423929,0.00045036303,0.0005033195,0.0015231885],"category_scores_gemma":[0.0011196785,0.00015454422,0.00011143716,0.0007316578,0.00019528682,0.00032905387,0.00024645528,0.00030963868,0.00048735118],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037348194,0.00036755067,0.033805545,0.00063001306,0.00006756402,0.0015031742,0.0005824374,0.020358277,0.4082016,0.0005196213,0.0040290835,0.52620023],"study_design_scores_gemma":[0.0000820999,0.0007311039,0.18290937,0.000113876304,0.000085574895,0.0010588799,0.00037399048,0.61520904,0.19301926,0.0003688748,0.005966194,0.00008169719],"about_ca_topic_score_codex":0.003357387,"about_ca_topic_score_gemma":0.006961066,"teacher_disagreement_score":0.003357387,"about_ca_system_score_codex":0.0002385524,"about_ca_system_score_gemma":0.00030875372,"threshold_uncertainty_score":0.0066756606},"labels":[],"label_agreement":null},{"id":"W2799829979","doi":"10.1139/tcsme-2003-0012","title":"FINITE ELEMENT MODELING AND STABILITY ANALYSIS OF CHATTER IN END MILLING MACHINING","year":2003,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Finite element method; Timoshenko beam theory; Machining; Stability (learning theory); Structural engineering; Beam (structure); End milling; Point (geometry); Engineering; Mechanical engineering; Mathematics; Computer science; Geometry","score_opus":0.012045845327244531,"score_gpt":0.2080359325441187,"score_spread":0.19599008721687416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799829979","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.100935966,0.00017838825,0.8967583,0.000043147036,0.0000137552215,0.000019212008,0.00001577462,0.0001388787,0.0018965432],"genre_scores_gemma":[0.9249267,0.0001474766,0.07185198,0.000021542122,0.000008004338,0.000048858783,0.00003454741,0.000044530698,0.0029162923],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979466,0.000058399582,0.0000085549855,0.000026000334,0.000095809155,0.000016543265],"domain_scores_gemma":[0.99916744,0.00050954806,0.00008416737,0.000062429994,0.00015384804,0.000022554244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061041716,0.00038587832,0.00044489175,0.00036068802,0.0002703982,0.00042142966,0.000898863,0.0008008578,0.0008658713],"category_scores_gemma":[0.0012723877,0.000317471,0.00050135347,0.000111516034,0.00068651553,0.0005216539,0.00038493593,0.00057144696,0.00023958314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010730964,0.0000332799,0.0010963076,0.00008838945,0.000023167579,0.0002133989,0.00030562532,0.9397621,0.03562677,0.010492595,0.00013924776,0.012111856],"study_design_scores_gemma":[0.0000018248533,0.00001216327,0.00010466476,0.0000029796288,0.0000017860826,0.000015915417,0.0000069923694,0.99743915,0.0017845513,0.00050721754,0.00012017603,0.000002630035],"about_ca_topic_score_codex":0.0016397062,"about_ca_topic_score_gemma":0.0011589929,"teacher_disagreement_score":0.0016397062,"about_ca_system_score_codex":0.00031016188,"about_ca_system_score_gemma":0.00029902934,"threshold_uncertainty_score":0.003260374},"labels":[],"label_agreement":null},{"id":"W2799872363","doi":"10.1139/tcsme-2015-0023","title":"SURFACE ROUGHNESS AND CUTTING FORCES IN TURNING OF TOOL STEEL WITH MIXED CERAMIC AND CUBIC BORON NITRIDE CUTTING TOOLS","year":2015,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Süleyman Demirel Üniversitesi","keywords":"Boron nitride; Ceramic; Materials science; Machining; Surface roughness; Metallurgy; Cutting tool; Hardened steel; Surface finish; Tool wear; Composite material; Mechanical engineering; Engineering","score_opus":0.011666943271744267,"score_gpt":0.20612004362751937,"score_spread":0.1944531003557751,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799872363","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985501,0.00013203794,0.0010213475,0.000004088767,0.000005179082,0.000004680562,0.00002567743,0.000010914625,0.00024586698],"genre_scores_gemma":[0.99882525,0.000033147277,0.0008420493,0.0000048490983,0.0000012820055,0.0000030100177,0.000046093523,0.0000071127265,0.00023720002],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99899775,0.00007660055,0.00004400356,0.00011535537,0.00061742426,0.00014890799],"domain_scores_gemma":[0.9988953,0.00041879812,0.0002117044,0.000073513416,0.00032504628,0.00007555431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005157322,0.00029833193,0.00038770557,0.00048701567,0.0001764439,0.00037956526,0.00021967736,0.00036939903,0.0005317674],"category_scores_gemma":[0.0012259708,0.00027171077,0.00045143586,0.00030821963,0.00034910394,0.00018751704,0.00020076378,0.00031963724,0.000114526396],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047320165,0.000038906524,0.0036188709,0.00006365666,0.000023984454,0.00008556959,0.0001088591,0.0014589475,0.9880008,0.000028968627,0.00004558117,0.006052604],"study_design_scores_gemma":[0.00004803446,0.0034813143,0.30060256,0.000018153958,0.00011777206,0.00034440486,0.0005092821,0.016780019,0.6769348,0.00010003433,0.0009869327,0.000076798824],"about_ca_topic_score_codex":0.0024907212,"about_ca_topic_score_gemma":0.005053104,"teacher_disagreement_score":0.0024907212,"about_ca_system_score_codex":0.00036558794,"about_ca_system_score_gemma":0.00015586193,"threshold_uncertainty_score":0.0049524307},"labels":[],"label_agreement":null},{"id":"W2799874369","doi":"10.1139/tcsme-2004-0031","title":"A MULTI-LAYER NEURO-FUZZY NETWORK FOR TOOL-PIECE COLLISIONS DETECTION IN CAD/CAM","year":2004,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Espace pour la vie","funders":"","keywords":"CAD; Machining; Collision; Computer science; Artificial neural network; Collision detection; Point (geometry); Quality (philosophy); Fuzzy logic; State (computer science); Layer (electronics); Engineering drawing; Engineering; Artificial intelligence; Mechanical engineering; Algorithm; Mathematics","score_opus":0.012175072612331788,"score_gpt":0.21870838211779045,"score_spread":0.20653330950545867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799874369","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.096734665,0.0010600215,0.8987549,0.0002964475,0.000091069676,0.000065499444,0.000055625405,0.000618597,0.0023231816],"genre_scores_gemma":[0.8633364,0.00025357032,0.13344747,0.00010345343,0.000030413687,0.00009220207,0.000060204973,0.000016403526,0.0026599476],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997639,0.000051454,0.00001754358,0.00006601107,0.000061152336,0.000039974093],"domain_scores_gemma":[0.9996866,0.00013610821,0.00002383186,0.0000149197285,0.00012230052,0.000016312306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008939604,0.00048011233,0.00047566314,0.0003525389,0.00043571135,0.0006428595,0.0011183199,0.0011286862,0.0012360375],"category_scores_gemma":[0.0013603366,0.0003893783,0.00042339796,0.00024920923,0.00031370437,0.00074190984,0.00036058747,0.0006387557,0.00028958241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035414452,0.00012896926,0.001559147,0.00010262871,0.000075871365,0.0001304171,0.00008429167,0.7824069,0.011186386,0.0021672514,0.0009077956,0.20089622],"study_design_scores_gemma":[0.0000048199418,0.000022873925,0.000110262416,0.0000038946514,0.0000065335134,0.00000887925,0.0000032192236,0.9986083,0.00088603626,0.00023850003,0.000103431616,0.000003373103],"about_ca_topic_score_codex":0.012072305,"about_ca_topic_score_gemma":0.010524711,"teacher_disagreement_score":0.012072305,"about_ca_system_score_codex":0.00094252656,"about_ca_system_score_gemma":0.0007082131,"threshold_uncertainty_score":0.024004042},"labels":[],"label_agreement":null},{"id":"W2799954502","doi":"10.1139/tcsme-2005-0029","title":"THE USE OF FUZZY LOGIC IN THE TAGUCHI METHOD FOR THE DETERMINATION OF THE TOLERANCE OF A SIX-BAR HINGE MECHANISM","year":2005,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Science Council","keywords":"Taguchi methods; Fuzzy logic; Hinge; Bar (unit); Mechanism (biology); Control theory (sociology); Mathematics; Four-bar linkage; Computer science; Engineering; Statistics; Structural engineering; Control (management); Artificial intelligence; Physics","score_opus":0.02059658187855917,"score_gpt":0.24477974592423254,"score_spread":0.22418316404567337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799954502","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029186694,0.00029014496,0.96961445,0.000034421522,0.000025799072,0.00004546684,0.00000903383,0.00011662144,0.0006774459],"genre_scores_gemma":[0.4863548,0.00031892088,0.51250863,0.000052778178,0.000017811897,0.00010292285,0.000019142133,0.000021715488,0.0006033055],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793977,0.0005174123,0.0001617491,0.00022097815,0.0010709516,0.00008908422],"domain_scores_gemma":[0.99845564,0.0008168659,0.00023494392,0.0000988973,0.00036103718,0.00003267482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002441017,0.00064250914,0.0006300972,0.0012523851,0.0004696218,0.00087505736,0.00089711795,0.00070489926,0.00039684254],"category_scores_gemma":[0.0035002287,0.00041899277,0.0007303266,0.00060401525,0.00088554714,0.0006659695,0.00035426542,0.000834291,0.00017183251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005764213,0.00013558433,0.003292576,0.00076219434,0.00012197313,0.0002694825,0.0006018219,0.14057428,0.4955406,0.012425788,0.00029744627,0.34540194],"study_design_scores_gemma":[0.00006123436,0.0014305704,0.0029631567,0.000104972794,0.00015970015,0.0005591346,0.00016419451,0.67824495,0.30336928,0.007938977,0.0048031574,0.00020070659],"about_ca_topic_score_codex":0.0012259667,"about_ca_topic_score_gemma":0.0015702606,"teacher_disagreement_score":0.002441017,"about_ca_system_score_codex":0.00066966476,"about_ca_system_score_gemma":0.00058966834,"threshold_uncertainty_score":0.012909472},"labels":[],"label_agreement":null},{"id":"W2800053427","doi":"10.1139/tcsme-2015-0053","title":"A GENERAL CAD/CAM MODEL FOR APT-LIKE ROTARY MILLING CUTTERS","year":2015,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"CAD; Groove (engineering); Envelope (radar); Machining; Milling cutter; Enhanced Data Rates for GSM Evolution; Kinematics; Mechanical engineering; Machine tool; Engineering; Differential (mechanical device); Inverse; Computer science; Engineering drawing; Geometry; Mathematics; Physics; Aerospace engineering; Classical mechanics; Artificial intelligence","score_opus":0.01843049660541493,"score_gpt":0.2151491176058416,"score_spread":0.19671862100042667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800053427","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0056137177,0.00021873225,0.9799794,0.0001103387,0.00006975333,0.0001213316,0.00039185263,0.00062033086,0.012874621],"genre_scores_gemma":[0.32103643,0.0013096564,0.64190376,0.00020255944,0.00007900957,0.00094836135,0.0016164464,0.00027856667,0.032625254],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997712,0.000016802685,0.000015149344,0.000046529152,0.00013607599,0.000014305217],"domain_scores_gemma":[0.9998896,0.000018879036,0.000019509665,0.000021303822,0.00004439094,0.000006299392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023425708,0.0005465397,0.00046253897,0.000500138,0.0003287848,0.00079644413,0.001621651,0.0010708409,0.0059159915],"category_scores_gemma":[0.0003614305,0.00041302072,0.0006524219,0.000395112,0.0003928774,0.0006332033,0.0004021092,0.00077923905,0.0019714208],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052534844,0.00004311239,0.00070477306,0.00028975154,0.000014501234,0.00035762586,0.00016683665,0.8357421,0.039511215,0.060882177,0.0035932234,0.058642186],"study_design_scores_gemma":[0.000014805227,0.000035995083,0.00034724368,0.000023575081,0.000007998423,0.00017475852,0.000018076296,0.9624237,0.0036655334,0.0031242159,0.030147264,0.000016809545],"about_ca_topic_score_codex":0.004832195,"about_ca_topic_score_gemma":0.0041426676,"teacher_disagreement_score":0.0059159915,"about_ca_system_score_codex":0.0005081049,"about_ca_system_score_gemma":0.0008329282,"threshold_uncertainty_score":0.019791007},"labels":[],"label_agreement":null},{"id":"W2800288016","doi":"10.3390/jmmp2020027","title":"New Observations on High-Speed Machining of Hardened AISI 4340 Steel Using Alumina-Based Ceramic Tools","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Ceramic; Materials science; Machining; Scanning electron microscope; Metallurgy; Hardened steel; High-speed steel; Tool wear; X-ray photoelectron spectroscopy; Composite material; Chemical engineering; Engineering","score_opus":0.03095900700924285,"score_gpt":0.25960078598645303,"score_spread":0.2286417789772102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800288016","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949411,0.00079784886,0.003028186,0.000025216432,0.000015966094,0.000012265036,0.00007839101,0.000064674285,0.001036367],"genre_scores_gemma":[0.9965166,0.00026452454,0.0022349695,0.000018464278,0.0000063257166,0.000005155224,0.00008002378,0.0000086474,0.00086540746],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998173,0.000009854204,0.000009069188,0.000030389841,0.00010497567,0.000028434413],"domain_scores_gemma":[0.9997913,0.000045354278,0.000054456283,0.000024796696,0.00006690959,0.000017231854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001585618,0.00030768616,0.00020016245,0.0004998456,0.00023063598,0.0002322309,0.0003020865,0.0005652089,0.0011645373],"category_scores_gemma":[0.00023777579,0.00022388677,0.00027318875,0.00032583508,0.00036887525,0.00031794043,0.00015296935,0.00044899923,0.00017831585],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000072001814,0.000009477796,0.00034653876,0.000060337083,0.0000039309275,0.00013497379,0.00006895937,0.00006485248,0.99775773,0.000028531485,0.000029174018,0.0014235594],"study_design_scores_gemma":[0.0000103838065,0.00043527342,0.025363566,0.0000067062592,0.000019002924,0.000702822,0.00022211637,0.00088914105,0.97058064,0.000057106743,0.0016983422,0.000015009716],"about_ca_topic_score_codex":0.0005145783,"about_ca_topic_score_gemma":0.0008797709,"teacher_disagreement_score":0.0011645373,"about_ca_system_score_codex":0.00011102193,"about_ca_system_score_gemma":0.00007428442,"threshold_uncertainty_score":0.0038957},"labels":[],"label_agreement":null},{"id":"W2800480907","doi":"10.1139/tcsme-2015-0031","title":"DESIGN, FABRICATION, AND PREDICTIVE MODEL OF A 1-DOF TRANSLATIONAL FLEXIBLE BEARING FOR HIGH PRECISION MECHANISM","year":2015,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Bearing (navigation); Computer science; Multivariable calculus; Taguchi methods; Radial basis function; Actuator; Linear regression; Design of experiments; Control theory (sociology); Artificial intelligence; Control engineering; Machine learning; Engineering; Mathematics; Statistics","score_opus":0.024444664971919886,"score_gpt":0.2218567873860341,"score_spread":0.1974121224141142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800480907","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10038787,0.0008759764,0.8896986,0.00027791108,0.00008856157,0.00017340487,0.00020136776,0.0009967111,0.0072995145],"genre_scores_gemma":[0.93340534,0.0007232927,0.060587294,0.000036146288,0.000017491628,0.0003934449,0.00017367536,0.000046682253,0.0046166233],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998198,0.000025027763,0.000009253828,0.000044162243,0.00007996558,0.000021771264],"domain_scores_gemma":[0.99982077,0.000055374167,0.00004799287,0.000014472048,0.000052504663,0.000008839476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005595245,0.000684794,0.0007474141,0.0003845363,0.00051411276,0.00086741755,0.0009467937,0.0010673928,0.0017350982],"category_scores_gemma":[0.0004811103,0.0006853385,0.00089065474,0.00033295454,0.00042843688,0.0004927353,0.00044018877,0.0006849983,0.00041947214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032638014,0.000023474226,0.0006093863,0.0001120242,0.00001760326,0.000106653,0.00004299057,0.97588295,0.010599246,0.0007254836,0.00020234534,0.011645209],"study_design_scores_gemma":[0.000005624752,0.000047919028,0.00027541933,0.0000032978724,0.000008505717,0.000011696333,0.000006077707,0.9980444,0.0012121242,0.000082636994,0.00029785102,0.0000044542144],"about_ca_topic_score_codex":0.010441464,"about_ca_topic_score_gemma":0.009103023,"teacher_disagreement_score":0.010441464,"about_ca_system_score_codex":0.0005723968,"about_ca_system_score_gemma":0.0014860852,"threshold_uncertainty_score":0.02076137},"labels":[],"label_agreement":null},{"id":"W2800754150","doi":"10.1063/1.5029586","title":"Design and development of solid carbide step drill K34 for machining of CFRP and GFRP composite laminates","year":2018,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell Helicopter Textron (Canada)","funders":"","keywords":"Fibre-reinforced plastic; Delamination (geology); Drill; Materials science; Drilling; Machining; Composite material; Composite laminates; Breakage; Composite number; Thrust; Glass fiber; Mechanical engineering; Metallurgy; Engineering; Geology","score_opus":0.02092870793187958,"score_gpt":0.2558431669864828,"score_spread":0.2349144590546032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800754150","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5092735,0.0012654811,0.47804374,0.0000995113,0.000068143694,0.00080621266,0.0002048377,0.0013213183,0.008917296],"genre_scores_gemma":[0.7132334,0.0004071715,0.28375995,0.00001877449,0.0000074979125,0.00023825694,0.00013754632,0.00005558047,0.002141719],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995277,0.000043470256,0.00003475502,0.00008764885,0.00025516868,0.000051159845],"domain_scores_gemma":[0.99946946,0.0000669086,0.00018089611,0.000040572053,0.00020776723,0.000034421333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004201198,0.0005919027,0.0003380919,0.00048652102,0.00016538416,0.00039511896,0.00064802665,0.00048645565,0.00052192697],"category_scores_gemma":[0.0005049699,0.00044160135,0.00040041504,0.00021359533,0.00024295703,0.00026356603,0.00017446147,0.0002465709,0.0002067536],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026245243,0.00010999021,0.0029973995,0.0010136373,0.00004171351,0.00037407456,0.00020343205,0.06439072,0.83608514,0.0015674187,0.0004905371,0.092463434],"study_design_scores_gemma":[0.0001540934,0.006567981,0.024587944,0.000094214636,0.00014694584,0.0019053771,0.00019321653,0.1695011,0.7697911,0.00066644285,0.02629205,0.000099525765],"about_ca_topic_score_codex":0.0010599575,"about_ca_topic_score_gemma":0.001884624,"teacher_disagreement_score":0.0010599575,"about_ca_system_score_codex":0.00036223713,"about_ca_system_score_gemma":0.0010536305,"threshold_uncertainty_score":0.0026282072},"labels":[],"label_agreement":null},{"id":"W2800754747","doi":"10.1007/s00170-018-2028-4","title":"On machining of Ti-6Al-4V using multi-walled carbon nanotubes-based nano-fluid under minimum quantity lubrication","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":97,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machinability; Materials science; Machining; Surface roughness; Nanofluid; Cutting fluid; Lubrication; Thermal conductivity; Composite material; Carbon nanotube; Nano-; Tool wear; Metallurgy; Nanoparticle; Nanotechnology","score_opus":0.015428188756209741,"score_gpt":0.2775517146071619,"score_spread":0.26212352585095217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800754747","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99202347,0.00053230673,0.0036520106,0.000078249504,0.000059744754,0.000013284901,0.000053821506,0.00007112113,0.0035159613],"genre_scores_gemma":[0.9934141,0.0001470013,0.0047283177,0.0000075221415,0.00000546719,0.000004029789,0.000045756322,0.000013073736,0.0016348758],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998896,0.0000071344643,0.0000041095236,0.000015525,0.0000678509,0.000015818194],"domain_scores_gemma":[0.99990916,0.000026389642,0.000019411314,0.000009645159,0.000029918472,0.000005455739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010770998,0.00015919065,0.0002027558,0.0002589125,0.0003162695,0.00020031864,0.00037616247,0.0003194024,0.0012149973],"category_scores_gemma":[0.00024798597,0.00009575225,0.00017678594,0.00015062398,0.00019684857,0.0002541472,0.00015396369,0.00015527643,0.00014763787],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020333537,0.000024350624,0.00044658824,0.00019675544,0.000008781931,0.00012922884,0.00008251548,0.0074783755,0.9814015,0.00073737814,0.0002293717,0.009061879],"study_design_scores_gemma":[0.000013769838,0.00043537276,0.0031030737,0.000010252627,0.000014121785,0.00009478355,0.000058023856,0.053718142,0.9391475,0.0002916845,0.0030990636,0.000014217783],"about_ca_topic_score_codex":0.0015994962,"about_ca_topic_score_gemma":0.003477117,"teacher_disagreement_score":0.0015994962,"about_ca_system_score_codex":0.00028910517,"about_ca_system_score_gemma":0.00027085,"threshold_uncertainty_score":0.0040646195},"labels":[],"label_agreement":null},{"id":"W2800812102","doi":"10.1139/tcsme-2014-0023","title":"AN EXPERIMENTAL STUDY ON FRICTION DRILLING OF ST12 STEEL","year":2014,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Türkiye Bilimler Akademisi","keywords":"Drilling; Tungsten carbide; Materials science; Torque; Thrust; Composite material; Rotational speed; Metallurgy; Mechanical engineering; Engineering","score_opus":0.010000866819112277,"score_gpt":0.2281728832277082,"score_spread":0.21817201640859593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800812102","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966016,0.00022077108,0.0024872278,0.000012861685,0.00001000075,0.00002438969,0.00009292368,0.000023425897,0.0005267576],"genre_scores_gemma":[0.9948908,0.0001519729,0.0039864383,0.00000738018,0.0000035889998,0.0000147876435,0.00011810743,0.000012836069,0.00081412523],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994149,0.00007313869,0.000051778785,0.00008948449,0.00028302128,0.000087589164],"domain_scores_gemma":[0.99873835,0.0004304646,0.00021109155,0.00016201816,0.00040062686,0.00005751911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054898683,0.0004278359,0.0007057347,0.00041197197,0.0005382759,0.00025808858,0.00045446228,0.0005957315,0.0015750051],"category_scores_gemma":[0.0015996082,0.0002874756,0.00040538362,0.0005851146,0.00045431097,0.0003518746,0.00025188588,0.000304171,0.0002443325],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011156226,0.00015066781,0.0018201829,0.00029269172,0.000011663582,0.00023535156,0.00027116737,0.0021583033,0.9876544,0.000116052026,0.00007701128,0.006096837],"study_design_scores_gemma":[0.000098760465,0.007138765,0.019167222,0.000026389662,0.000039082446,0.00063253276,0.00028046474,0.008407462,0.9609503,0.00007743662,0.0031424512,0.00003920452],"about_ca_topic_score_codex":0.001538407,"about_ca_topic_score_gemma":0.0020952327,"teacher_disagreement_score":0.0015750051,"about_ca_system_score_codex":0.0002153326,"about_ca_system_score_gemma":0.00027778296,"threshold_uncertainty_score":0.005268872},"labels":[],"label_agreement":null},{"id":"W2801280090","doi":"10.1139/tcsme-2016-0001","title":"COMPARISON OF EXPERIMENTALLY MEASURED AND SIMULATED WORKPIECE AND GRINDING WHEEL TOPOGRAPHY USING A NEW DRESSING MODEL","year":2016,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Grinding; Grinding wheel; Materials science; Enhanced Data Rates for GSM Evolution; Surface grinding; Surface roughness; Surface (topology); Surface finish; Composite material; Mechanical engineering; Computer science; Geometry; Engineering; Mathematics","score_opus":0.02790367057407705,"score_gpt":0.2645639176365197,"score_spread":0.23666024706244265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801280090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8516658,0.00011785951,0.14413786,0.000057969533,0.000029127239,0.00009177648,0.0002754853,0.00070704176,0.0029170886],"genre_scores_gemma":[0.98013395,0.00009075871,0.019040994,0.0000066181337,0.0000014333043,0.000030427072,0.00013913595,0.00003044861,0.0005262049],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997342,0.00002584256,0.000016429445,0.00004446535,0.00015059083,0.000028385992],"domain_scores_gemma":[0.9994074,0.00023440234,0.0000481731,0.00014880647,0.00014090099,0.000020363159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042063135,0.0003943017,0.00033876637,0.00032148958,0.00018265288,0.0005870767,0.000803025,0.00069791835,0.001093697],"category_scores_gemma":[0.0014102637,0.00030694375,0.00039410157,0.0002718691,0.0003593771,0.0004119694,0.00027739842,0.00041757204,0.00023285039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018672735,0.00019987293,0.00846199,0.00016138528,0.000023572931,0.00021322533,0.00024195561,0.81776977,0.14314537,0.00066188606,0.00029816545,0.028636135],"study_design_scores_gemma":[0.000014188668,0.00011914507,0.004436624,0.0000056652325,0.0000073890187,0.000047706617,0.000044575045,0.9720139,0.022801315,0.000096429394,0.00039550042,0.000017672233],"about_ca_topic_score_codex":0.0048833475,"about_ca_topic_score_gemma":0.007952197,"teacher_disagreement_score":0.0048833475,"about_ca_system_score_codex":0.00056064985,"about_ca_system_score_gemma":0.00051833387,"threshold_uncertainty_score":0.009709835},"labels":[],"label_agreement":null},{"id":"W2801929927","doi":"10.1139/tcsme-2016-0072","title":"OPTIMAL PREDICTION AND DESIGN OF SURFACE ROUGHNESS FOR CNC TURNING OF AL7075-T6 BY USING THE TAGUCHI HYBRID QPSO ALGORITHM","year":2016,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Science and Technology, Taiwan","keywords":"Taguchi methods; Particle swarm optimization; Surface roughness; Machining; Orthogonal array; Numerical control; Response surface methodology; Mechanical engineering; Engineering; Algorithm; Mathematical optimization; Computer science; Materials science; Mathematics; Composite material; Machine learning","score_opus":0.010198755452585322,"score_gpt":0.20539997609645705,"score_spread":0.19520122064387171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801929927","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23411152,0.00028148183,0.76189333,0.000096560274,0.000028333623,0.00010268089,0.00003910827,0.0003572325,0.0030897195],"genre_scores_gemma":[0.9108071,0.00012339774,0.088214844,0.000032844004,0.0000068575196,0.000097761644,0.000065450855,0.000025505784,0.0006263195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998161,0.000030401314,0.000009020613,0.000033540775,0.00008403932,0.00002690737],"domain_scores_gemma":[0.99981016,0.00007008787,0.000031395317,0.000012611204,0.00006348194,0.000012250599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043493742,0.0005711358,0.00054715376,0.00046247547,0.00023467332,0.00054474024,0.0005841756,0.00068447297,0.00052690704],"category_scores_gemma":[0.000608905,0.0004049566,0.000837232,0.00025239625,0.00030407566,0.0002375279,0.00021460619,0.00043196348,0.00012786557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007581274,0.00007814458,0.0012689563,0.00010792286,0.00003059348,0.000054374257,0.0000480753,0.92001355,0.03655916,0.000803898,0.00022369131,0.04073581],"study_design_scores_gemma":[0.000007560128,0.000049765924,0.0003177787,0.0000021441065,0.000007796393,0.0000066109546,0.0000068150866,0.9969797,0.0024204247,0.000099466226,0.00009820171,0.0000038010648],"about_ca_topic_score_codex":0.0051440774,"about_ca_topic_score_gemma":0.004477572,"teacher_disagreement_score":0.0051440774,"about_ca_system_score_codex":0.00039883307,"about_ca_system_score_gemma":0.00089067343,"threshold_uncertainty_score":0.010228276},"labels":[],"label_agreement":null},{"id":"W2802074912","doi":"10.1007/s00170-018-2098-3","title":"Improving the performance of profile grinding wheels with helical grooves","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Groove (engineering); Grinding wheel; Materials science; Mechanical engineering; Geometry; Engineering drawing; Composite material; Metallurgy; Engineering; Mathematics","score_opus":0.004123549579156796,"score_gpt":0.21485671433152542,"score_spread":0.21073316475236864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802074912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97467774,0.00031114518,0.02346974,0.000024142268,0.000028280892,0.000012507023,0.000034928504,0.00028308432,0.001158393],"genre_scores_gemma":[0.9924452,0.0000708366,0.0068614744,0.000005632023,0.0000028199875,0.0000033929168,0.00003330373,0.000018997713,0.00055825483],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997688,0.00001721918,0.0000072721286,0.00003422696,0.00011397219,0.000058531667],"domain_scores_gemma":[0.99960095,0.00007686589,0.00007697203,0.00006426784,0.00013733386,0.000043734464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002813082,0.0004693488,0.0004938015,0.00029599492,0.00022943341,0.000391465,0.0006234985,0.00045782168,0.0011152395],"category_scores_gemma":[0.000538455,0.00021104014,0.00033353083,0.00032763332,0.00022641473,0.00031565982,0.00025480762,0.0002614594,0.00041726785],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006491868,0.00016956916,0.003919416,0.00012658715,0.000026387092,0.000080507445,0.000049439008,0.038775776,0.9148043,0.00056176947,0.0003464706,0.040490605],"study_design_scores_gemma":[0.000056016637,0.0018601128,0.0161486,0.00001375231,0.00005237972,0.00014371652,0.00007061663,0.31898227,0.6603938,0.00029452177,0.0019358186,0.00004844564],"about_ca_topic_score_codex":0.0015190402,"about_ca_topic_score_gemma":0.002786075,"teacher_disagreement_score":0.0015190402,"about_ca_system_score_codex":0.00026931323,"about_ca_system_score_gemma":0.00035046967,"threshold_uncertainty_score":0.0037308335},"labels":[],"label_agreement":null},{"id":"W2802252123","doi":"10.1139/tcsme-2002-0011","title":"ENHANCED MODELING AND OPTIMIZATION OF MILLING USING A HYBRID TECHNIQUE","year":2002,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Particle swarm optimization; Artificial neural network; Fractional factorial design; Design of experiments; Computer science; Process (computing); Factorial experiment; Orthogonal array; Algorithm; Taguchi methods; Mathematics; Artificial intelligence; Machine learning; Statistics","score_opus":0.012923571319275672,"score_gpt":0.20056478325572516,"score_spread":0.18764121193644948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802252123","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04517091,0.00024791082,0.94955915,0.00005145086,0.000017697455,0.000029701492,0.00004246245,0.00025594266,0.00462473],"genre_scores_gemma":[0.8448714,0.00040619736,0.1495475,0.000041551746,0.000016538976,0.00016359976,0.00009783215,0.000045144876,0.004810297],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998166,0.000045760702,0.00000834698,0.00003838019,0.000076182085,0.0000147358205],"domain_scores_gemma":[0.9997999,0.000108993976,0.000029900999,0.00002350085,0.000032761993,0.000004941507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035638936,0.0004583852,0.0005082432,0.0002526782,0.0001598095,0.00067133794,0.00058631646,0.00060912466,0.0009403255],"category_scores_gemma":[0.00041330725,0.00031391738,0.00065617304,0.00031035533,0.0003137896,0.0005686737,0.00038672664,0.00046224013,0.00019922435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016340819,0.000013350349,0.00016324938,0.000023680122,0.000014955788,0.000015921662,0.000010737685,0.9875814,0.002961323,0.0008660961,0.000041128245,0.008291849],"study_design_scores_gemma":[0.0000013929782,0.0000141977725,0.00006735078,0.0000011857778,0.0000021985295,0.0000041007675,0.0000011471502,0.99915504,0.0004254328,0.00017861293,0.00014799766,0.0000013598434],"about_ca_topic_score_codex":0.002578897,"about_ca_topic_score_gemma":0.0028558427,"teacher_disagreement_score":0.002578897,"about_ca_system_score_codex":0.00035345156,"about_ca_system_score_gemma":0.00039427538,"threshold_uncertainty_score":0.0051277876},"labels":[],"label_agreement":null},{"id":"W2802354832","doi":"10.1139/tcsme-2016-0008","title":"MULTI-OBJECTIVE OPTIMIZATION OF TURNING PARAMETERS USING THE COMBINED MOORA AND ENTROPY METHOD","year":2016,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Surface roughness; Mechanical engineering; RADIUS; Materials science; Surface finish; Entropy (arrow of time); Mathematics; Engineering; Structural engineering; Engineering drawing; Computer science; Composite material; Physics; Thermodynamics","score_opus":0.012610990286933337,"score_gpt":0.2333641788007099,"score_spread":0.22075318851377657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802354832","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.115103714,0.00040935018,0.8817121,0.0000345714,0.000019216555,0.000087785236,0.000027791193,0.00019080081,0.0024146882],"genre_scores_gemma":[0.79384565,0.00019845371,0.2045797,0.000024010094,0.000019523717,0.00026307147,0.00007391963,0.000060995593,0.0009348288],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950266,0.00017310251,0.00002769368,0.00005698916,0.0001958516,0.00004376475],"domain_scores_gemma":[0.999519,0.00030144537,0.00006052192,0.000017545704,0.00008778402,0.000013622127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009478195,0.001031995,0.0010092513,0.0013647896,0.00026728804,0.0005559222,0.00038964936,0.0005022084,0.0006238362],"category_scores_gemma":[0.0010306872,0.00040714594,0.0011422554,0.0005722296,0.00034575636,0.0004411381,0.0005262052,0.00031163145,0.00008536262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013315478,0.00009145888,0.0013916519,0.00020222361,0.00015964621,0.00004730321,0.000060698225,0.8970472,0.02104082,0.0018153375,0.00014489656,0.07786565],"study_design_scores_gemma":[0.000013573458,0.00012601767,0.000796942,0.0000065038457,0.000023254459,0.000014872538,0.000010196848,0.99489695,0.0036033322,0.00031427818,0.00018418796,0.000009888914],"about_ca_topic_score_codex":0.001273733,"about_ca_topic_score_gemma":0.0015921512,"teacher_disagreement_score":0.0013647896,"about_ca_system_score_codex":0.00030365554,"about_ca_system_score_gemma":0.00045029816,"threshold_uncertainty_score":0.005012572},"labels":[],"label_agreement":null},{"id":"W2802510146","doi":"10.1139/tcsme-2012-0002","title":"SLIP-LINE MODELING OF MACHINING AND DETERMINE THE INFLUENCE OF RAKE ANGLE ON THE CUTTING FORCE","year":2012,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Rake angle; Thrust; Rake; Slip (aerodynamics); Machining; Structural engineering; Mechanics; Mechanical engineering; Materials science; Engineering; Physics","score_opus":0.012591922418950314,"score_gpt":0.2085609452719478,"score_spread":0.19596902285299747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802510146","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36625072,0.00083868107,0.6254631,0.000051920197,0.000034951976,0.00007257366,0.00011543556,0.0004795742,0.0066929474],"genre_scores_gemma":[0.96201175,0.00037888502,0.034403026,0.000011207218,0.000005722586,0.00004777892,0.000082020866,0.000051660496,0.0030078848],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974316,0.00003364719,0.000014963179,0.000045038658,0.00013403875,0.000029101448],"domain_scores_gemma":[0.9995427,0.00020840322,0.00009952213,0.000052381845,0.000085303196,0.000011718775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038888768,0.0005740892,0.00043910774,0.00035732763,0.00019381006,0.00055649,0.00053902116,0.00061809074,0.001520541],"category_scores_gemma":[0.0010928644,0.00034257647,0.00039406793,0.00031346848,0.00021302747,0.00067171716,0.000199006,0.0003243567,0.0005347614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016902227,0.000060720136,0.0021697124,0.00014261894,0.0000205563,0.00010715825,0.00011867594,0.9049278,0.06132852,0.0009554792,0.00017050981,0.029829303],"study_design_scores_gemma":[0.0000036979968,0.000073754825,0.00070444366,0.000004062001,0.000006666756,0.00002592465,0.000008992103,0.9901816,0.008437095,0.0000985928,0.000450281,0.0000048393845],"about_ca_topic_score_codex":0.0035920115,"about_ca_topic_score_gemma":0.0038683673,"teacher_disagreement_score":0.0035920115,"about_ca_system_score_codex":0.00029704487,"about_ca_system_score_gemma":0.0004579197,"threshold_uncertainty_score":0.007142186},"labels":[],"label_agreement":null},{"id":"W2803133548","doi":"10.1139/tcsme-2017-1043","title":"OPTIMIZATION OF HIGH SPEED CNC END MILLING PROCESS OF BSL 168 ALUMINIUM COMPOSITE FOR AERONAUTICAL APPLICATIONS","year":2017,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Aluminium; Box–Behnken design; Response surface methodology; Surface roughness; Composite number; Process (computing); Materials science; Design of experiments; Machining; Mechanical engineering; End milling; Central composite design; Engineering drawing; Process engineering; Computer science; Composite material; Engineering; Metallurgy; Mathematics; Statistics; Machine learning","score_opus":0.009813985723392113,"score_gpt":0.23168628552986625,"score_spread":0.22187229980647413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803133548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85754263,0.0005919599,0.13875751,0.000044985198,0.000011294474,0.0000768145,0.000098787474,0.00013946912,0.0027365924],"genre_scores_gemma":[0.96525705,0.0002224322,0.033786837,0.000006962686,0.0000017151383,0.00004224466,0.000072080846,0.000013815218,0.0005968316],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996184,0.00007066298,0.000014147171,0.00005927085,0.00021145414,0.000025996644],"domain_scores_gemma":[0.99979883,0.000077163095,0.00005792392,0.000016215547,0.00004417446,0.000005694983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005393236,0.00048026448,0.00029429534,0.00027997972,0.0001818658,0.00038513614,0.00025483652,0.00028056145,0.0005056474],"category_scores_gemma":[0.00044571699,0.00015682107,0.0004398834,0.00021559722,0.0001949763,0.00023874806,0.00012382209,0.00025410962,0.00013781854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024259975,0.00018410178,0.0025159605,0.00046995253,0.00003579048,0.000059962127,0.00006480312,0.42561817,0.53843194,0.00060094916,0.00012648257,0.03164919],"study_design_scores_gemma":[0.00002871657,0.0018842174,0.010042408,0.00001869336,0.000059443642,0.000112731934,0.00009245315,0.53469425,0.45040798,0.0006416731,0.0019761773,0.00004121874],"about_ca_topic_score_codex":0.001314364,"about_ca_topic_score_gemma":0.0030512952,"teacher_disagreement_score":0.001314364,"about_ca_system_score_codex":0.00041362515,"about_ca_system_score_gemma":0.00044502428,"threshold_uncertainty_score":0.0030010939},"labels":[],"label_agreement":null},{"id":"W2803451113","doi":"10.1139/tcsme-2017-0048","title":"Design of grinding wheel profile for new micro drill flute","year":2018,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Flute; Drill; Grinding; Grinding wheel; Mechanical engineering; Engineering; Structural engineering; Acoustics; Physics","score_opus":0.014039011276525286,"score_gpt":0.21543243584621968,"score_spread":0.2013934245696944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803451113","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04207709,0.00024513784,0.95286846,0.0000840605,0.00005587133,0.00018145522,0.000072690185,0.00034868537,0.004066583],"genre_scores_gemma":[0.69649285,0.00035640266,0.29941964,0.000032429143,0.00001673278,0.00030316127,0.0001560243,0.000094770796,0.0031279123],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99939775,0.000047843176,0.000032793287,0.00010237456,0.0003464324,0.00007286696],"domain_scores_gemma":[0.99950516,0.00006367045,0.000086183754,0.000046304984,0.000255537,0.000043117012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057384354,0.00062584365,0.00072825473,0.00081226055,0.000264695,0.00080323545,0.0010230746,0.0008036324,0.001771921],"category_scores_gemma":[0.0009786036,0.0005184663,0.0005607658,0.00034130464,0.00038046675,0.00062374515,0.0005598278,0.00047109154,0.0006579107],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046730074,0.00019916233,0.00512324,0.0012866013,0.000049740225,0.0005599924,0.00040413707,0.2573276,0.51765186,0.017458051,0.002746772,0.19672555],"study_design_scores_gemma":[0.00014621342,0.00059738365,0.0051012044,0.000072856536,0.00006775877,0.00074448617,0.0001350234,0.8761633,0.0995372,0.0020809271,0.015242002,0.000111552006],"about_ca_topic_score_codex":0.0017925637,"about_ca_topic_score_gemma":0.0027275742,"teacher_disagreement_score":0.0017925637,"about_ca_system_score_codex":0.0006194563,"about_ca_system_score_gemma":0.0015731638,"threshold_uncertainty_score":0.005927682},"labels":[],"label_agreement":null},{"id":"W2803676952","doi":"10.1051/matecconf/201816518004","title":"Influence of surface residual stresses on the fatigue life and crack propagation behavior of turned Inconel 718 super-alloy","year":2018,"lang":"en","type":"article","venue":"MATEC Web of Conferences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure","funders":"Héroux-Devtek; Natural Sciences and Engineering Research Council of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec","keywords":"Inconel; Materials science; Residual stress; Surface roughness; Surface finish; Composite material; Alloy; Ultimate tensile strength; Fatigue limit; Bending","score_opus":0.022360365520780367,"score_gpt":0.2555942350363938,"score_spread":0.23323386951561342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803676952","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99956614,0.00013743076,0.00013182334,0.0000024422836,0.0000012170547,0.0000010118163,0.000023954146,0.000008791705,0.00012720842],"genre_scores_gemma":[0.999597,0.00005178911,0.00014798196,0.0000019366455,6.0213785e-7,0.0000010941244,0.000039300343,0.000003959606,0.00015629489],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983287,0.000014133037,0.0000127629255,0.000027360402,0.000071546936,0.000041326803],"domain_scores_gemma":[0.99966824,0.00010481967,0.000068550864,0.000037449674,0.00009156513,0.00002942165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012247903,0.00023651324,0.00024417133,0.00031832897,0.00011450107,0.00018817796,0.00014335566,0.00019951347,0.0007250517],"category_scores_gemma":[0.00038964843,0.00013885323,0.00019172046,0.00019624233,0.00017382932,0.0001313111,0.00009700813,0.00013795514,0.000103298946],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030709343,0.000013196587,0.0033115938,0.000051087733,0.000011991098,0.00015924597,0.0000637761,0.0017761083,0.98930734,0.00001801796,0.00002650058,0.004954035],"study_design_scores_gemma":[0.000011947149,0.002087558,0.11010244,0.000009296129,0.000056114885,0.00031858028,0.00017293422,0.009853509,0.8765837,0.00003433189,0.0007438861,0.000025653486],"about_ca_topic_score_codex":0.0016252262,"about_ca_topic_score_gemma":0.0034332843,"teacher_disagreement_score":0.0016252262,"about_ca_system_score_codex":0.0001452271,"about_ca_system_score_gemma":0.000095555224,"threshold_uncertainty_score":0.003231585},"labels":[],"label_agreement":null},{"id":"W2804017919","doi":"10.1115/gt2013-94400","title":"Modeling of Abradable Coating Removal in Aircraft Engines Through Delay Differential Equations","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Materials science; Turbomachinery; Vibration; Machining; Coating; Turbine; Stability (learning theory); Instability; Turbine blade; Computer science; Mechanical engineering; Mechanics; Composite material; Acoustics; Physics; Engineering; Metallurgy","score_opus":0.014049314506130187,"score_gpt":0.2340172795635463,"score_spread":0.21996796505741611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804017919","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09869086,0.0010913846,0.87955755,0.0004060312,0.000116100244,0.00011799819,0.0003014493,0.0003185289,0.019400047],"genre_scores_gemma":[0.94437176,0.0010625629,0.032691218,0.00009281181,0.000041609514,0.00027228327,0.00021054715,0.000092715905,0.021164438],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998492,0.00003183615,0.000008393288,0.000029590901,0.000052275227,0.000028635119],"domain_scores_gemma":[0.99978083,0.00010201404,0.000043530305,0.000009395361,0.000047075562,0.000017221326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034208238,0.0008268811,0.00069595734,0.00049472274,0.00047055364,0.0009506439,0.0012014827,0.0015068077,0.0017892716],"category_scores_gemma":[0.00070710236,0.0004411318,0.0006922602,0.00033200806,0.00075636146,0.0007133601,0.0007475516,0.00076163927,0.00028552554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020736052,0.000017066626,0.00043734314,0.000049768918,0.000010216434,0.000111202666,0.000063608626,0.9842987,0.0034918385,0.009236454,0.00015852167,0.0021046062],"study_design_scores_gemma":[0.000002952325,0.000005870201,0.0000498636,0.0000022573486,0.00000214692,0.0000074788873,0.000004909557,0.9986737,0.00023707355,0.0007182824,0.00029271498,0.0000027477731],"about_ca_topic_score_codex":0.01687033,"about_ca_topic_score_gemma":0.0077205165,"teacher_disagreement_score":0.01687033,"about_ca_system_score_codex":0.0009760309,"about_ca_system_score_gemma":0.0011609232,"threshold_uncertainty_score":0.033544242},"labels":[],"label_agreement":null},{"id":"W2805011532","doi":"10.5267/j.ijiec.2017.11.002","title":"Experimental investigation on hard turning using mixed ceramic insert under accelerated cooling environment","year":2018,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Kalinga Institute of Industrial Technology","keywords":"Materials science; Coolant; Machining; Tool wear; Abrasion (mechanical); Metallurgy; Insert (composites); Brittleness; Ceramic; Surface roughness; Heat generation; Chip formation; Composite material; Cutting tool; Mechanical engineering; Engineering","score_opus":0.06748438687173858,"score_gpt":0.28256221509417995,"score_spread":0.21507782822244137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805011532","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99617696,0.00020292644,0.0021460683,0.000014657582,0.000021706757,0.000031465115,0.00011684378,0.000043537424,0.0012456944],"genre_scores_gemma":[0.9952466,0.00020893605,0.0029553748,0.000009772627,0.000010611648,0.000026543485,0.000103407954,0.000019402041,0.0014194526],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99955875,0.00003768093,0.000017736313,0.000087751265,0.00018759748,0.00011055055],"domain_scores_gemma":[0.9993968,0.000160453,0.00007887713,0.00009222533,0.00022750944,0.00004414659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034081738,0.0003343592,0.0004237581,0.0003311097,0.0003330323,0.00031032547,0.00039607345,0.00038252267,0.00224971],"category_scores_gemma":[0.00051239855,0.00021638906,0.00030694812,0.00031609405,0.0003208071,0.0002168114,0.0002096437,0.00048457138,0.00031948063],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004725012,0.00019037804,0.0010574632,0.0002560268,0.000009786574,0.00019044812,0.00021519315,0.0011527697,0.9913147,0.00009187469,0.00011137997,0.00493747],"study_design_scores_gemma":[0.000038273123,0.004860053,0.013554303,0.000016098711,0.000045093577,0.00025043543,0.00025618103,0.0032978982,0.9746227,0.000055977896,0.0029713965,0.000031683874],"about_ca_topic_score_codex":0.0007932709,"about_ca_topic_score_gemma":0.0015125731,"teacher_disagreement_score":0.00224971,"about_ca_system_score_codex":0.00014411083,"about_ca_system_score_gemma":0.0002031647,"threshold_uncertainty_score":0.00752604},"labels":[],"label_agreement":null},{"id":"W2806352440","doi":"","title":"Feasibility Study on Resonance Enhanced Drilling Technology","year":2017,"lang":"en","type":"article","venue":"Advances in petroleum exploration and development","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Drilling; Drill bit; Drill; Resonance (particle physics); Measurement while drilling; Excitation; Modal analysis; Drilling fluid; Realization (probability); Petroleum engineering; Drill pipe; Vibration; Engineering; Acoustics; Geology; Mechanical engineering; Physics; Electrical engineering","score_opus":0.025606374890427275,"score_gpt":0.3014389124102491,"score_spread":0.27583253751982184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806352440","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18210587,0.0018445967,0.7810862,0.0013670815,0.00024927838,0.00034834308,0.000084383966,0.0005436584,0.032370687],"genre_scores_gemma":[0.8182144,0.0012086296,0.17575146,0.00013497511,0.000042722775,0.00015182623,0.0000711315,0.00003400798,0.0043908707],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989114,0.00020698237,0.000055867145,0.00012404719,0.00061244087,0.000089306945],"domain_scores_gemma":[0.9992848,0.00025015263,0.00008083221,0.00008113332,0.0002630902,0.00003987576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010334492,0.0003807616,0.00036534667,0.0004630556,0.0003900483,0.000651529,0.0006291449,0.0009067687,0.0025052284],"category_scores_gemma":[0.0015478309,0.00024050318,0.0005666121,0.00022729745,0.00059723004,0.0019923844,0.0007225881,0.00052856957,0.0005883612],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072134513,0.00023818639,0.004071028,0.001286044,0.000054241737,0.0020737743,0.00066550623,0.033267133,0.7729943,0.055359256,0.002361349,0.12690784],"study_design_scores_gemma":[0.00033875112,0.0047034314,0.004034645,0.00029436676,0.00023388218,0.005938674,0.0010303111,0.353424,0.55061483,0.01725976,0.061870042,0.00025729762],"about_ca_topic_score_codex":0.00036845665,"about_ca_topic_score_gemma":0.00027114997,"teacher_disagreement_score":0.0025052284,"about_ca_system_score_codex":0.00024524762,"about_ca_system_score_gemma":0.0007699237,"threshold_uncertainty_score":0.00838089},"labels":[],"label_agreement":null},{"id":"W2806583313","doi":"10.5267/j.ijdns.2017.1.008","title":"Optimization of turning parameters of Aluminum 6351 T6 using Taguchi decision making technique","year":2017,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taguchi methods; Aluminium; Materials science; Computer science; Manufacturing engineering; Process engineering; Engineering; Metallurgy; Composite material","score_opus":0.031905687410211714,"score_gpt":0.34554598631875383,"score_spread":0.3136402989085421,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806583313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7570721,0.0038236976,0.22840506,0.0001713736,0.00012581499,0.00034255048,0.00021954118,0.00025467455,0.009585189],"genre_scores_gemma":[0.9090711,0.0011088923,0.08865147,0.00003560129,0.0000105893205,0.00011468741,0.00008731168,0.000022824885,0.00089756533],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948525,0.00009736504,0.000054117692,0.00006401684,0.00022677095,0.00007253622],"domain_scores_gemma":[0.9996319,0.00015624713,0.00009538152,0.000019069992,0.00008081788,0.0000166597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082883344,0.00056796387,0.00082432776,0.0009024479,0.00023339227,0.00086220633,0.00045375156,0.0005765373,0.00081902475],"category_scores_gemma":[0.0007952535,0.0003422773,0.00076392206,0.00074597285,0.00026309054,0.00025077138,0.00018370626,0.0003757779,0.000221252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083071104,0.0003212113,0.002767337,0.0015038963,0.00006453418,0.000312133,0.00021190676,0.15375751,0.74345016,0.0012624405,0.00047168287,0.09504643],"study_design_scores_gemma":[0.00015559969,0.005004581,0.0080712475,0.00014700502,0.00031900595,0.0002556074,0.0002561094,0.3282788,0.6518297,0.0010822985,0.004459692,0.00014033832],"about_ca_topic_score_codex":0.0009817824,"about_ca_topic_score_gemma":0.0018051569,"teacher_disagreement_score":0.0009817824,"about_ca_system_score_codex":0.00028921105,"about_ca_system_score_gemma":0.00045743887,"threshold_uncertainty_score":0.0043833256},"labels":[],"label_agreement":null},{"id":"W2807513785","doi":"10.1007/s12008-018-0491-7","title":"Hybrid nano-fluid-minimum quantity lubrication strategy for machining austempered ductile iron (ADI)","year":2018,"lang":"en","type":"article","venue":"International Journal on Interactive Design and Manufacturing (IJIDeM)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; University of Ontario Institute of Technology","keywords":"Coolant; Machinability; Lubrication; Materials science; Cutting fluid; Nanofluid; Machining; Tool wear; Toughness; Metallurgy; Composite material; Mechanical engineering; Nanoparticle; Engineering","score_opus":0.026081701081201423,"score_gpt":0.2988178068054263,"score_spread":0.27273610572422485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807513785","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37236547,0.0012072835,0.6113632,0.00022410511,0.00012626065,0.00007413165,0.000050519266,0.0003561714,0.014232787],"genre_scores_gemma":[0.9685316,0.00009931357,0.028718377,0.000023446464,0.0000074685117,0.000021997155,0.00002043224,0.000013651026,0.0025637527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999368,0.000007210778,0.000003343963,0.000012955668,0.000027719929,0.000011850382],"domain_scores_gemma":[0.99993837,0.000016077489,0.00001256408,0.0000053526787,0.000019942216,0.000007785235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010833214,0.00032758992,0.0004519056,0.000235132,0.0002872249,0.00040535576,0.00054358493,0.0004533542,0.0013310652],"category_scores_gemma":[0.00016584955,0.00016005793,0.00022851626,0.00014297315,0.00021541762,0.0003757544,0.0003950391,0.0001953468,0.00016419517],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043532753,0.00025658385,0.0009932843,0.00043016634,0.00005712147,0.00029446985,0.00012825064,0.64227575,0.25458398,0.013092648,0.0011160758,0.08633636],"study_design_scores_gemma":[0.000014429422,0.00016741527,0.00016167363,0.0000034103143,0.000007439228,0.00003278887,0.000014627106,0.98697543,0.010954262,0.00083263696,0.0008301786,0.0000057945826],"about_ca_topic_score_codex":0.0012013157,"about_ca_topic_score_gemma":0.0020491953,"teacher_disagreement_score":0.0013310652,"about_ca_system_score_codex":0.0002479394,"about_ca_system_score_gemma":0.00038192183,"threshold_uncertainty_score":0.0044528246},"labels":[],"label_agreement":null},{"id":"W2808132978","doi":"10.1007/s12008-018-0495-3","title":"Non-contact auxiliary fixture for machining stability improvement of thin flexible workpieces using eddy currents","year":2018,"lang":"en","type":"article","venue":"International Journal on Interactive Design and Manufacturing (IJIDeM)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fixture; Clamping; Machining; Mechanical engineering; Aerospace; Vibration; Eddy current; Engineering; Materials science; Structural engineering; Acoustics; Electrical engineering","score_opus":0.02715303478821594,"score_gpt":0.31065664565759943,"score_spread":0.28350361086938347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808132978","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6995689,0.00035448247,0.29687977,0.00003975412,0.00004089158,0.000025816622,0.000023267166,0.00033193378,0.002735181],"genre_scores_gemma":[0.97479904,0.000042860338,0.024128702,0.000007770376,0.0000069947296,0.000009904542,0.000016655735,0.000016914555,0.0009712815],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99992573,0.000008009179,0.0000036368763,0.000019335346,0.0000341414,0.000009114968],"domain_scores_gemma":[0.9998016,0.000055469296,0.00004319418,0.000045656743,0.000043311655,0.000010909414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014592253,0.00029364848,0.0002454495,0.0002455614,0.00024683506,0.00025978536,0.0008093713,0.0002918157,0.0011818125],"category_scores_gemma":[0.00024886327,0.0001401491,0.00023855534,0.00014886289,0.00021012919,0.00036021776,0.000323496,0.00020936404,0.000136808],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047974623,0.00010170644,0.0011568672,0.00015159766,0.00004067224,0.00012888057,0.00016082087,0.022238452,0.9159839,0.0021998477,0.00033989266,0.057017624],"study_design_scores_gemma":[0.00011033826,0.0019249916,0.0111792395,0.000030675732,0.00014032038,0.00046120823,0.00009402578,0.4219617,0.5584904,0.00089668157,0.0046716733,0.00003873489],"about_ca_topic_score_codex":0.00015721904,"about_ca_topic_score_gemma":0.00038567165,"teacher_disagreement_score":0.0011818125,"about_ca_system_score_codex":0.00013096222,"about_ca_system_score_gemma":0.00013921941,"threshold_uncertainty_score":0.003953576},"labels":[],"label_agreement":null},{"id":"W2809024381","doi":"10.1007/s00170-018-2341-y","title":"Application of acoustic emissions in machining processes: analysis and critical review","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":116,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Acoustic emission; Tool wear; Enhanced Data Rates for GSM Evolution; Cutting tool; Breakage; Chip formation; Mechanical engineering; Machine tool; Vibration; Process (computing); Chip; Engineering; Computer science; Materials science; Acoustics; Artificial intelligence","score_opus":0.006456967466785659,"score_gpt":0.28597521977846446,"score_spread":0.2795182523116788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809024381","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011632424,0.9941888,0.0022071295,0.0009871317,0.0005388621,0.000018212264,0.000013683717,0.0000066723464,0.00087630807],"genre_scores_gemma":[0.008952523,0.98791856,0.0014160025,0.00043783273,0.0008575693,0.000022080425,0.000019818604,0.000004782524,0.00037097337],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982874,0.0003231697,0.00026971236,0.00028300463,0.0007496832,0.000087035296],"domain_scores_gemma":[0.9864042,0.008668521,0.00078600843,0.0002893601,0.0037245427,0.00012749576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044756383,0.0009098341,0.001481726,0.0023840023,0.00040737985,0.0019993817,0.0016838802,0.0024685957,0.001288469],"category_scores_gemma":[0.007876993,0.0004993561,0.00078897376,0.0020734575,0.0013294973,0.0027990644,0.0008974719,0.0016684795,0.00062616495],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025271453,0.00015404435,0.0011658643,0.031003313,0.0002674342,0.00041311327,0.00027131735,0.0026803256,0.01146578,0.008561204,0.008140251,0.9356247],"study_design_scores_gemma":[0.00004943235,0.00093493215,0.0074300542,0.017821122,0.0009784368,0.003087147,0.0010264354,0.0040401723,0.034434907,0.016733555,0.91319585,0.00026796167],"about_ca_topic_score_codex":0.0011735858,"about_ca_topic_score_gemma":0.0012695555,"teacher_disagreement_score":0.0044756383,"about_ca_system_score_codex":0.0011405086,"about_ca_system_score_gemma":0.0030881735,"threshold_uncertainty_score":0.02366972},"labels":[],"label_agreement":null},{"id":"W2809121007","doi":"10.1016/j.jclepro.2018.06.190","title":"An extensive review of the water consumption and cutting fluid based sustainability concerns in the metal cutting sector","year":2018,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":128,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Machining; Lubrication; Cutting fluid; Mechanical engineering; Sustainability; Environmentally friendly; Grinding; Heat generation; Drilling; Metalworking; Process engineering; Engineering; Environmental science","score_opus":0.014500834782431546,"score_gpt":0.2830304512337723,"score_spread":0.26852961645134077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809121007","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021044184,0.99088776,0.0010220711,0.0013321642,0.00045768652,0.0000066506423,0.00009504594,0.0000067731726,0.00408747],"genre_scores_gemma":[0.007882532,0.989474,0.0005332003,0.00042686707,0.0003902912,0.0000061278456,0.00006996921,0.000004861905,0.0012122235],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99945706,0.00011408801,0.000074831594,0.00009911571,0.00021046647,0.000044499036],"domain_scores_gemma":[0.99841833,0.0009865798,0.00023354498,0.000030536925,0.00029515507,0.000035888486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008601815,0.0005839977,0.00078992394,0.0020847258,0.00024187076,0.0015051307,0.000556919,0.0011269855,0.0029827112],"category_scores_gemma":[0.0015565673,0.0002374242,0.00049142994,0.0042718756,0.0004316439,0.0016788433,0.00057803775,0.00084165053,0.0005079185],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013786404,0.00013696624,0.0015294069,0.054599855,0.0001900741,0.0003039366,0.00030722047,0.0024992384,0.008331884,0.019296035,0.03840041,0.8742672],"study_design_scores_gemma":[0.000005065108,0.0001664474,0.0055101984,0.013028021,0.00020094206,0.00044565834,0.00054192275,0.00057104137,0.0037786765,0.004840661,0.97086257,0.000048862228],"about_ca_topic_score_codex":0.0023132819,"about_ca_topic_score_gemma":0.0052255215,"teacher_disagreement_score":0.0029827112,"about_ca_system_score_codex":0.0007412095,"about_ca_system_score_gemma":0.0019019165,"threshold_uncertainty_score":0.009978116},"labels":[],"label_agreement":null},{"id":"W2809860803","doi":"10.1115/1.4040726","title":"Dynamics and Stability of Turn-Milling Operations With Varying Time Delay in Discrete Time Domain","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Kinematics; Time domain; Cartesian coordinate system; Stability (learning theory); Mechanism (biology); Machine tool; Mechanical engineering; Vibration; Process (computing); Chip; Turn (biochemistry); Control theory (sociology); Machining; Engineering; Computer science; Geometry; Acoustics; Mathematics; Physics; Classical mechanics; Artificial intelligence","score_opus":0.003594667589623027,"score_gpt":0.19893293286322916,"score_spread":0.19533826527360615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809860803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64741945,0.00035840433,0.34773004,0.00014304189,0.000018775758,0.000027067379,0.000081988495,0.00018284051,0.004038362],"genre_scores_gemma":[0.9966703,0.0000712127,0.002463687,0.0000049024848,0.000001663862,0.00001060577,0.000021592874,0.000007449264,0.0007485238],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99992085,0.000013386166,0.0000033805527,0.000021122916,0.000028626904,0.000012721066],"domain_scores_gemma":[0.9996232,0.00020081343,0.00008766726,0.000020122377,0.000052269388,0.000015880356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021543691,0.00030180524,0.0002738321,0.00021457204,0.00019528496,0.00046261592,0.00026739613,0.00037578322,0.0006157846],"category_scores_gemma":[0.0006892469,0.00015504089,0.00030333005,0.00012005241,0.0006201326,0.0003125908,0.00024186222,0.0003954074,0.00008921422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018832917,0.000039920473,0.0026936855,0.0000718461,0.000032589793,0.0002501675,0.00026244647,0.9377473,0.039844315,0.011579786,0.0001878035,0.007101771],"study_design_scores_gemma":[0.0000037373838,0.000018609968,0.00042924494,0.0000017398028,0.0000026446778,0.00001599858,0.000010124638,0.9977586,0.0012721905,0.0004181373,0.00006560367,0.0000033386489],"about_ca_topic_score_codex":0.003569369,"about_ca_topic_score_gemma":0.0017111615,"teacher_disagreement_score":0.003569369,"about_ca_system_score_codex":0.00046136108,"about_ca_system_score_gemma":0.00033823552,"threshold_uncertainty_score":0.0070971847},"labels":[],"label_agreement":null},{"id":"W2810853631","doi":"10.1016/j.procir.2018.03.201","title":"Benchmarking of Pattern Recognition Techniques for Online Tool Wear Detection","year":2018,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Benchmarking; Linear discriminant analysis; Robustness (evolution); Pattern recognition (psychology); Computer science; Artificial intelligence; Reliability (semiconductor); Machine learning; Tool wear; Data mining; Engineering; Machining","score_opus":0.012801645457264765,"score_gpt":0.24428617857377752,"score_spread":0.23148453311651276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810853631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73696274,0.0012570695,0.2541463,0.00014815699,0.00011225052,0.00015631909,0.00053822447,0.004359415,0.0023195772],"genre_scores_gemma":[0.91540116,0.00017019061,0.082986064,0.00002618419,0.0000147900055,0.00006933467,0.0005118943,0.000050464998,0.0007698601],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998629,0.00032672097,0.00013330061,0.00032540003,0.0004945842,0.00009098682],"domain_scores_gemma":[0.9964265,0.0017472073,0.000300695,0.0004739678,0.0010012196,0.00005047264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014865396,0.0007502257,0.0005497199,0.0013243342,0.00017709383,0.00065253535,0.0009495156,0.0006693256,0.0010996809],"category_scores_gemma":[0.0042176805,0.00016346408,0.0003536189,0.00097201404,0.00018432687,0.0006891454,0.0003723749,0.00035180734,0.0005193346],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010883866,0.00069545134,0.008996472,0.00031341292,0.0001786732,0.00010821803,0.000053210242,0.12495035,0.0730465,0.00037488263,0.0017237128,0.78847075],"study_design_scores_gemma":[0.000048289396,0.0009655044,0.014368936,0.000014893251,0.000041361185,0.00014180379,0.000038021022,0.90348226,0.07948643,0.00031167976,0.0010786692,0.000022109763],"about_ca_topic_score_codex":0.0015779035,"about_ca_topic_score_gemma":0.0012581893,"teacher_disagreement_score":0.0015779035,"about_ca_system_score_codex":0.00040835654,"about_ca_system_score_gemma":0.0003271433,"threshold_uncertainty_score":0.007861674},"labels":[],"label_agreement":null},{"id":"W2810945665","doi":"10.1139/tcsme-2017-1009","title":"PREDICTION AND INVESTIGATION OF SURFACE ROUGHNESS WHILE TURNING SG IRON WITH CUBIC BORON NITRIDE (CBN) AND TUNGSTEN CARBIDE INSERTS","year":2017,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Materials science; Boron nitride; Tungsten carbide; Surface roughness; Metallurgy; Cast iron; Carbide; Graphite; Drilling; Tin; Surface finish; Composite material","score_opus":0.01032498351269568,"score_gpt":0.18785558793636223,"score_spread":0.17753060442366655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810945665","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914056,0.000077628036,0.007947212,0.000011532909,0.0000064797555,0.000009981006,0.000046758734,0.00008887172,0.00040589008],"genre_scores_gemma":[0.99723357,0.000035298846,0.0024861174,0.0000021795374,8.6459704e-7,0.0000036064305,0.000057260775,0.000006806766,0.00017422471],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998202,0.000016500986,0.0000071012987,0.0000384094,0.000083153216,0.000034619414],"domain_scores_gemma":[0.99943036,0.00028674118,0.00008811457,0.000047292473,0.0001225912,0.000024845964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024282899,0.00030861277,0.00036270605,0.00024192192,0.0001384179,0.00041735495,0.00021929419,0.00051439635,0.00033061323],"category_scores_gemma":[0.0007186719,0.0002509314,0.0004004923,0.0001459498,0.00018853374,0.00018621422,0.00011103218,0.0002164976,0.00015036855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008163299,0.00026259696,0.031692397,0.00024685668,0.000047883386,0.00022435289,0.00022287441,0.2006223,0.7186826,0.00013269203,0.00030837406,0.04674077],"study_design_scores_gemma":[0.000015493313,0.0012418316,0.061104003,0.000009773831,0.000046656853,0.000103723636,0.00023457217,0.7198609,0.21681057,0.00006149954,0.000465258,0.00004578577],"about_ca_topic_score_codex":0.0032079206,"about_ca_topic_score_gemma":0.0051508215,"teacher_disagreement_score":0.0032079206,"about_ca_system_score_codex":0.0002363428,"about_ca_system_score_gemma":0.00019760134,"threshold_uncertainty_score":0.006378472},"labels":[],"label_agreement":null},{"id":"W2823756350","doi":"10.1007/s00170-018-2389-8","title":"A thermal model for hard precision turning","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Thermal; Industrial and production engineering; Mechanical engineering; Materials science; Engineering; Engineering drawing; Computer science; Physics; Thermodynamics","score_opus":0.010711149565246816,"score_gpt":0.2604620903983339,"score_spread":0.24975094083308708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2823756350","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13842,0.0030951062,0.7119431,0.0014161802,0.0007062608,0.00020934966,0.0008268179,0.0007274516,0.14265579],"genre_scores_gemma":[0.93412805,0.0010335657,0.016311085,0.00020721923,0.00010972581,0.0002022708,0.000315982,0.00025993495,0.047432233],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998628,0.000025995612,0.000005305509,0.000027395607,0.000043181582,0.000035233836],"domain_scores_gemma":[0.99980587,0.00009454341,0.000019135328,0.00001668136,0.000044741628,0.000019026565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024985088,0.000751841,0.0010727032,0.000555821,0.0007343139,0.0011828939,0.0013476606,0.0021026284,0.0075247907],"category_scores_gemma":[0.0008263415,0.00069231895,0.0011800645,0.000534445,0.00080363353,0.0010471451,0.0006625923,0.001212418,0.001004951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009117439,0.000007957858,0.000038788952,0.00002122097,0.000004172075,0.00003090028,0.000012989823,0.9917983,0.00068940327,0.0062179244,0.00021797065,0.00095129205],"study_design_scores_gemma":[0.0000065517265,0.000006823563,0.00005653349,0.0000033420524,0.0000035367955,0.000009049896,0.0000057468274,0.9968194,0.00011294224,0.002533369,0.00043847164,0.0000042245974],"about_ca_topic_score_codex":0.012338877,"about_ca_topic_score_gemma":0.008763782,"teacher_disagreement_score":0.012338877,"about_ca_system_score_codex":0.00086330913,"about_ca_system_score_gemma":0.0010178757,"threshold_uncertainty_score":0.025172949},"labels":[],"label_agreement":null},{"id":"W2883855374","doi":"10.20944/preprints201807.0447.v1","title":"A Neuro-Fuzzy Approach Based Tool Condition Monitoring in AISI H13 Milling","year":2018,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Tool wear; Downtime; Machining; Machine tool; Process (computing); Cutting tool; Engineering; Condition monitoring; Fault (geology); Manufacturing engineering; Mechanical engineering; Computer science; Reliability engineering","score_opus":0.07007629479751548,"score_gpt":0.3170383130535252,"score_spread":0.24696201825600972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883855374","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4847544,0.0007238657,0.5072238,0.00018257256,0.00005068315,0.00015174852,0.00013417569,0.00054716796,0.0062315757],"genre_scores_gemma":[0.9850535,0.00007938273,0.014119283,0.000012202038,0.0000051008865,0.000022490656,0.000025199224,0.000004195471,0.0006786902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982697,0.000024428733,0.000013857814,0.000048236732,0.00006470276,0.00002181802],"domain_scores_gemma":[0.9998665,0.00003899293,0.000023397151,0.000008040769,0.000052432006,0.000010639628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003410898,0.00035593114,0.0004635259,0.0003180141,0.00034614388,0.00060137064,0.0004909603,0.0005240309,0.0006942839],"category_scores_gemma":[0.00037328873,0.00023179734,0.0002999839,0.00029269676,0.00022443713,0.00023859969,0.00024104565,0.00031729153,0.0001033969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066132116,0.00027669335,0.0056106574,0.00024340599,0.00009031214,0.00042762718,0.00023238325,0.7334418,0.042306375,0.0016120336,0.00088650064,0.21421087],"study_design_scores_gemma":[0.000008230194,0.00007559625,0.0015279682,0.000004838932,0.000011648982,0.000018458712,0.000020111154,0.9954602,0.0024589598,0.00022294153,0.00018392439,0.0000071852082],"about_ca_topic_score_codex":0.009249646,"about_ca_topic_score_gemma":0.008424226,"teacher_disagreement_score":0.009249646,"about_ca_system_score_codex":0.00050962117,"about_ca_system_score_gemma":0.00045489336,"threshold_uncertainty_score":0.01839161},"labels":[],"label_agreement":null},{"id":"W2884449204","doi":"10.1007/s00170-018-2410-2","title":"Low-frequency vibration-assisted drilling of hybrid CFRP/Ti6Al4V stacked material","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"McMaster University","keywords":"Machinability; Drilling; Delamination (geology); Machining; Materials science; Tool wear; Vibration; Titanium alloy; Aerospace; Carbon fiber reinforced polymer; Fibre-reinforced plastic; Surface roughness; Chip formation; Mechanical engineering; Composite material; Alloy; Metallurgy; Acoustics; Engineering; Aerospace engineering","score_opus":0.0052884988698650715,"score_gpt":0.2311107246327934,"score_spread":0.22582222576292832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884449204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918868,0.00030637105,0.0057490994,0.000030247715,0.000052255094,0.0000058990677,0.000093662275,0.00013650465,0.0017391169],"genre_scores_gemma":[0.9940388,0.00004224382,0.0052418984,0.0000062795225,0.0000032413207,0.0000035233963,0.000044717963,0.000008054327,0.00061137276],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99988174,0.000007707641,0.0000047805147,0.000022872624,0.000057299498,0.00002557531],"domain_scores_gemma":[0.9998865,0.000022241902,0.00002968534,0.000016496811,0.00003425329,0.000010796095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012128186,0.00023572259,0.00018654832,0.00025596542,0.00016871854,0.00021483898,0.00036693187,0.0004064921,0.0011733655],"category_scores_gemma":[0.00016746916,0.00014639653,0.00018441759,0.00019126273,0.00020705721,0.0003211024,0.0002014518,0.00017078628,0.00018652769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026119463,0.000015862337,0.0004217466,0.00010576592,0.0000065361614,0.00011062092,0.000044562606,0.0030559646,0.9880711,0.00027674844,0.00018799098,0.00744196],"study_design_scores_gemma":[0.000027910055,0.000900552,0.008047223,0.000015166911,0.000022374787,0.00034975784,0.00018841111,0.039513666,0.94798183,0.00018069588,0.0027349729,0.000037412017],"about_ca_topic_score_codex":0.00040227943,"about_ca_topic_score_gemma":0.0010606146,"teacher_disagreement_score":0.0011733655,"about_ca_system_score_codex":0.0001077519,"about_ca_system_score_gemma":0.00018071783,"threshold_uncertainty_score":0.0039253235},"labels":[],"label_agreement":null},{"id":"W2884557444","doi":"10.1016/j.rcim.2018.07.004","title":"Chatter stability in robotic milling","year":2018,"lang":"en","type":"article","venue":"Robotics and Computer-Integrated Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":212,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Robot; Software portability; Aerospace; Stability (learning theory); Machine tool; Mechanical engineering; Coupling (piping); Process (computing); Engineering; Control theory (sociology); Control engineering; Computer science; Artificial intelligence","score_opus":0.011336249225704823,"score_gpt":0.2091190084869736,"score_spread":0.19778275926126876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884557444","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23697539,0.0018964368,0.73926675,0.0007658972,0.00029628462,0.000046184407,0.000063143576,0.00030190308,0.020387944],"genre_scores_gemma":[0.9810182,0.00025700062,0.008919983,0.00005378068,0.000055128872,0.000043313757,0.000029242838,0.00006037395,0.009563108],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99946815,0.00021427656,0.000024832738,0.00008321675,0.00015366965,0.00005592249],"domain_scores_gemma":[0.99520063,0.003461806,0.00040142375,0.00016265246,0.0005937778,0.00017968839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014955985,0.0006876152,0.0007531102,0.0009333227,0.00066871924,0.0011044409,0.0009586735,0.001163542,0.003628773],"category_scores_gemma":[0.0072534457,0.00040316087,0.00037877852,0.00040459045,0.0018503123,0.0013704657,0.0014044577,0.0011608851,0.0003453426],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012968641,0.00013442722,0.001914919,0.00047436505,0.00013286335,0.0005492803,0.0008486594,0.63268685,0.02390533,0.30389586,0.0022943458,0.03186611],"study_design_scores_gemma":[0.000013263474,0.00006947404,0.00036425944,0.000011868649,0.00000820316,0.000032798154,0.000049192404,0.96932375,0.001017721,0.028824413,0.00026891704,0.000016233538],"about_ca_topic_score_codex":0.0026532651,"about_ca_topic_score_gemma":0.0017806244,"teacher_disagreement_score":0.003628773,"about_ca_system_score_codex":0.0006252963,"about_ca_system_score_gemma":0.00043454889,"threshold_uncertainty_score":0.01213944},"labels":[],"label_agreement":null},{"id":"W2885127558","doi":"10.1007/978-3-319-95966-5_7","title":"Environmentally Conscious Machining","year":2018,"lang":"en","type":"book-chapter","venue":"Materials forming, machining and tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Machinability; Machining; Productivity; Materials science; Mechanical engineering; Process engineering; Metallurgy; Engineering","score_opus":0.006719902293511286,"score_gpt":0.1984004480470128,"score_spread":0.1916805457535015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885127558","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012194172,0.010011534,0.059189998,0.0012381248,0.00078115816,0.000030116948,0.00007879394,0.00044561588,0.9160304],"genre_scores_gemma":[0.19881009,0.011760025,0.026787162,0.001053079,0.00036226085,0.00005880127,0.00016775446,0.00033802024,0.7606629],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99965835,0.00003069862,0.00000587358,0.00005741835,0.0002158681,0.000031840515],"domain_scores_gemma":[0.9999368,0.000011982286,0.000006275835,0.000023540455,0.000015445085,0.00000581023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017580105,0.0005059311,0.00021763613,0.0003782102,0.0006180854,0.0012211517,0.00051920884,0.00072922045,0.0094625065],"category_scores_gemma":[0.00018879547,0.00024211875,0.00016443754,0.00032752496,0.0015721926,0.0011690625,0.0014468865,0.0013417329,0.0028670605],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022170236,0.00005248198,0.00016209354,0.00025452417,0.0000087525705,0.000099754034,0.0003678486,0.0015435251,0.024204796,0.78836054,0.022031857,0.1628918],"study_design_scores_gemma":[0.000003091462,0.000039002836,0.0006093366,0.00009734372,0.0000057887632,0.00030116318,0.00013996307,0.0010926038,0.020977303,0.13345784,0.8432613,0.000015248377],"about_ca_topic_score_codex":0.00037266916,"about_ca_topic_score_gemma":0.0015058947,"teacher_disagreement_score":0.0094625065,"about_ca_system_score_codex":0.00065793947,"about_ca_system_score_gemma":0.00054956065,"threshold_uncertainty_score":0.031655252},"labels":[],"label_agreement":null},{"id":"W2885349258","doi":"10.1115/1.4040617","title":"On-Line Energy-Based Milling Chatter Detection","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Harmonics; Vibration; Acoustics; Frequency domain; Energy (signal processing); Microphone; Discrete frequency domain; Amplitude; Fourier transform; Accelerometer; Line (geometry); Nonlinear system; Kalman filter; Fast Fourier transform; Engineering; Computer science; Physics; Mathematics; Mathematical analysis; Algorithm; Optics; Artificial intelligence; Computer vision; Electrical engineering","score_opus":0.007116937571991898,"score_gpt":0.21065798633743518,"score_spread":0.2035410487654433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885349258","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22352138,0.00038113628,0.7704943,0.000067090215,0.00007694741,0.00010099703,0.00012678634,0.0013665361,0.003864887],"genre_scores_gemma":[0.8903038,0.00015457139,0.106027804,0.000046242905,0.00002648016,0.000052694642,0.000114988055,0.0000766318,0.0031967105],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99937004,0.00006304172,0.00003369403,0.00011252688,0.0003823687,0.000038225255],"domain_scores_gemma":[0.998221,0.0007602893,0.00029860286,0.00015844557,0.00051352085,0.000048265374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033273175,0.00055738655,0.0006396058,0.0010263836,0.0002201231,0.00048609803,0.000762433,0.0005171499,0.0015499294],"category_scores_gemma":[0.0016789137,0.00025270542,0.00021126121,0.00037691803,0.0003121798,0.0005471037,0.00047909466,0.00035215783,0.00042391187],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096954533,0.00033185762,0.010299405,0.0004966089,0.00007863977,0.0005084399,0.00047960947,0.032821074,0.31723836,0.0014466428,0.0014386721,0.63389117],"study_design_scores_gemma":[0.0000416798,0.00038850994,0.018530266,0.000041261726,0.00004253,0.00095504464,0.00013466548,0.80405086,0.17199686,0.0010433046,0.0027047538,0.00007026351],"about_ca_topic_score_codex":0.00078471156,"about_ca_topic_score_gemma":0.0015935648,"teacher_disagreement_score":0.0015499294,"about_ca_system_score_codex":0.00027421117,"about_ca_system_score_gemma":0.00021583971,"threshold_uncertainty_score":0.005185008},"labels":[],"label_agreement":null},{"id":"W2885534505","doi":"10.3390/jmmp2030050","title":"Towards Sustainable Machining of Inconel 718 Using Nano-Fluid Minimum Quantity Lubrication","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machinability; Inconel; Machining; Materials science; Lubrication; Tool wear; Metallurgy; Mechanical engineering; Composite material; Alloy; Engineering","score_opus":0.012376394626509841,"score_gpt":0.25606756354130683,"score_spread":0.243691168914797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885534505","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9810417,0.0028097704,0.013029781,0.000116936564,0.000016710124,0.000028968987,0.000058705493,0.00007908462,0.0028183206],"genre_scores_gemma":[0.9778137,0.0016496836,0.018241314,0.00003101686,0.000004478659,0.000021923528,0.0000968577,0.000020553416,0.0021205621],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998393,0.000015391983,0.0000096233525,0.000023209817,0.000086428496,0.000025989175],"domain_scores_gemma":[0.9999145,0.00001115143,0.000029273797,0.000005868981,0.00003137677,0.00000780947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017333213,0.0002262917,0.00021019472,0.00039370768,0.00018278093,0.00031304173,0.00029193924,0.00027377336,0.0005449529],"category_scores_gemma":[0.00016646934,0.000112540925,0.00025903794,0.00027907838,0.00015437207,0.00035389746,0.00023100748,0.00024638363,0.0002016507],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078257886,0.000043279604,0.0013258433,0.00029193197,0.000010016703,0.00020029949,0.00008288453,0.0023813706,0.97151875,0.00042045655,0.00012446441,0.023522442],"study_design_scores_gemma":[0.000012458408,0.0007795325,0.0051187095,0.000031600874,0.000024935012,0.00032237466,0.00014752141,0.0065347585,0.9780262,0.0003270319,0.008660795,0.000014123326],"about_ca_topic_score_codex":0.00061190926,"about_ca_topic_score_gemma":0.00246997,"teacher_disagreement_score":0.00061190926,"about_ca_system_score_codex":0.00017304975,"about_ca_system_score_gemma":0.00023131515,"threshold_uncertainty_score":0.0018230677},"labels":[],"label_agreement":null},{"id":"W2886374926","doi":"10.1007/s00170-018-2420-0","title":"Tool condition monitoring using spectral subtraction and convolutional neural networks in milling process","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":203,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Ames Research Center; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Tool wear; Artificial intelligence; Artificial neural network; Convolutional neural network; Engineering; Support vector machine; Machining; Wavelet; Downtime; Machine tool; Fault detection and isolation; Feature extraction; Computer science; Pattern recognition (psychology); Machine learning; Reliability engineering; Mechanical engineering; Actuator","score_opus":0.008125261086522183,"score_gpt":0.2699558143832492,"score_spread":0.26183055329672705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886374926","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7337923,0.00070303807,0.26067683,0.00012361688,0.00006258585,0.00003079877,0.00016577946,0.0011121933,0.0033329118],"genre_scores_gemma":[0.98337674,0.00013209578,0.015763333,0.000012987659,0.000008440864,0.0000058683454,0.00005040273,0.000016130713,0.0006339279],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998363,0.000017009073,0.00000818544,0.000052427524,0.00006956131,0.00001640089],"domain_scores_gemma":[0.9997961,0.000069081805,0.000035888213,0.000018055161,0.00007137475,0.000009517287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024835533,0.00036807626,0.00028707788,0.0004932532,0.00014955633,0.0003642088,0.00038760155,0.00035697556,0.0005084809],"category_scores_gemma":[0.00040845017,0.00019049631,0.00019478324,0.00045113298,0.0001739371,0.00049653265,0.00022174596,0.0002662125,0.00015314038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014059375,0.00042735887,0.020163296,0.00029333774,0.00011661228,0.00019613488,0.00012417742,0.14679837,0.30939624,0.0009885668,0.0011859537,0.51890403],"study_design_scores_gemma":[0.000008396426,0.000085584914,0.013450152,0.0000057105303,0.000033375578,0.00004804465,0.000020566686,0.92845595,0.057137534,0.00035880756,0.00038256877,0.000013315105],"about_ca_topic_score_codex":0.002437928,"about_ca_topic_score_gemma":0.004007401,"teacher_disagreement_score":0.002437928,"about_ca_system_score_codex":0.0002987472,"about_ca_system_score_gemma":0.00022997109,"threshold_uncertainty_score":0.0048475266},"labels":[],"label_agreement":null},{"id":"W2886726677","doi":"10.1115/1.4041072","title":"Effect of Cutting Speed on Chipping and Wear of the SiAlON Ceramic Tool in Dry Finish Turning of the Precipitation Hardenable IN100 Aerospace Superalloy","year":2018,"lang":"en","type":"article","venue":"Journal of Tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"McMaster University","keywords":"Sialon; Superalloy; Materials science; Tool wear; Enhanced Data Rates for GSM Evolution; Ceramic; Machining; Scanning electron microscope; Aerospace; Metallurgy; Inconel; Breakage; Cutting tool; Composite material; Alloy; Computer science; Engineering","score_opus":0.0037911982015220286,"score_gpt":0.22951448591154486,"score_spread":0.22572328771002284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886726677","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99925834,0.00028847836,0.00024965437,0.0000062434337,0.000007902337,0.0000040124464,0.000029170229,0.000013003352,0.00014322861],"genre_scores_gemma":[0.9988254,0.00018239021,0.00055046653,0.0000059401236,0.0000025130655,0.000003906637,0.000054632543,0.000013891292,0.00036095222],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99973685,0.00002228664,0.00002435066,0.00006152588,0.00009204122,0.00006306781],"domain_scores_gemma":[0.9992093,0.00033794908,0.00018009398,0.000066708286,0.00014321256,0.000062790285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002550108,0.00038644252,0.0003838289,0.00028349308,0.00016256643,0.00040256217,0.00028191175,0.00029452663,0.00074067886],"category_scores_gemma":[0.00079676183,0.0002485984,0.00025133244,0.00024550638,0.00019064077,0.00022326453,0.00014546422,0.0003143753,0.0001049356],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004787014,0.00003987632,0.0016280154,0.0001252713,0.000016152306,0.000110685614,0.00012674482,0.00035033867,0.99320686,0.000022008904,0.000034352335,0.0038610813],"study_design_scores_gemma":[0.000012812545,0.0012329752,0.017659675,0.0000077311215,0.00003911321,0.000087885295,0.00010248292,0.0015805736,0.97871816,0.000010635212,0.0005316607,0.000016236474],"about_ca_topic_score_codex":0.00061540736,"about_ca_topic_score_gemma":0.0013413777,"teacher_disagreement_score":0.00074067886,"about_ca_system_score_codex":0.00017292719,"about_ca_system_score_gemma":0.0001230571,"threshold_uncertainty_score":0.0024778247},"labels":[],"label_agreement":null},{"id":"W2888701353","doi":"10.1139/tcsme-2018-0066","title":"Burr edge occupancy: edge finishing index for milling machined parts","year":2018,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Enhanced Data Rates for GSM Evolution; Machining; Aerospace; Cutting tool; Mechanical engineering; Automotive industry; Sensitivity (control systems); Engineering drawing; Materials science; Engineering","score_opus":0.011609109808736187,"score_gpt":0.22294845313495398,"score_spread":0.2113393433262178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888701353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8367186,0.0014486975,0.15635803,0.000027244905,0.000035460525,0.00007587925,0.00031007544,0.0006951663,0.00433084],"genre_scores_gemma":[0.95976454,0.00016556583,0.03909806,0.0000069734797,0.000009327027,0.000022963543,0.0002751711,0.00004891331,0.00060850236],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987112,0.00013857533,0.0001207983,0.00013311976,0.0008280142,0.00006817272],"domain_scores_gemma":[0.99518317,0.002152884,0.0012091964,0.0004914394,0.00084506854,0.0001181773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010225134,0.00042960714,0.00046521748,0.0017827667,0.00020992511,0.00052885,0.00042408865,0.0003650533,0.0008148569],"category_scores_gemma":[0.004004447,0.00025222328,0.0002862178,0.0010847496,0.0004196735,0.0006557595,0.00044492868,0.0002567297,0.0002847451],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016034814,0.0002535591,0.09568969,0.0007833237,0.00013157282,0.0003490283,0.0005891671,0.04845007,0.49518996,0.0020149811,0.0011366287,0.35380858],"study_design_scores_gemma":[0.000043962034,0.0027500745,0.364374,0.000073661606,0.0001536347,0.0016307426,0.0004373578,0.16648826,0.45421353,0.0015049196,0.008086288,0.00024359372],"about_ca_topic_score_codex":0.00040814406,"about_ca_topic_score_gemma":0.00066977,"teacher_disagreement_score":0.0017827667,"about_ca_system_score_codex":0.00024376124,"about_ca_system_score_gemma":0.00018009651,"threshold_uncertainty_score":0.0054076314},"labels":[],"label_agreement":null},{"id":"W2889830624","doi":"10.1007/s00170-018-2669-3","title":"An investigation of the effect of a new tool treatment technique on the machinability of Inconel 718 during the turning process","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machinability; Inconel; Materials science; Machining; Tool wear; Metallurgy; Alloy; Cutting tool; Mechanical engineering; Engineering","score_opus":0.004542638465955541,"score_gpt":0.2518113572711131,"score_spread":0.24726871880515755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889830624","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979697,0.000682311,0.0007947376,0.00002011601,0.000023532266,0.000009671042,0.000031930806,0.000019558858,0.00044837737],"genre_scores_gemma":[0.9983608,0.0003172898,0.0007867947,0.000012376045,0.0000066340926,0.0000044878925,0.000030027037,0.0000110793735,0.00047049538],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99982244,0.00002172453,0.000012573075,0.00003682661,0.00006148458,0.00004499985],"domain_scores_gemma":[0.99956506,0.00018589963,0.000097387856,0.000040682757,0.00008841401,0.0000225972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019608223,0.00028909222,0.0003626044,0.00023943401,0.0003120557,0.00029635662,0.00023606603,0.00044339613,0.001229995],"category_scores_gemma":[0.0005678759,0.00019382226,0.0002932017,0.00028183515,0.00028009797,0.00028682617,0.00014251255,0.00029844604,0.00013552053],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004919275,0.000046073365,0.00078830734,0.00013766895,0.000016213857,0.0001373694,0.00007545895,0.00036307555,0.9923805,0.00003690269,0.00003715504,0.005489332],"study_design_scores_gemma":[0.00002534986,0.002023389,0.013486991,0.000008509429,0.00008089559,0.00018972078,0.00009550292,0.0016753438,0.98136526,0.000019335468,0.001012294,0.000017405648],"about_ca_topic_score_codex":0.0004982409,"about_ca_topic_score_gemma":0.001171125,"teacher_disagreement_score":0.001229995,"about_ca_system_score_codex":0.00012570042,"about_ca_system_score_gemma":0.00016666406,"threshold_uncertainty_score":0.004114747},"labels":[],"label_agreement":null},{"id":"W2890572629","doi":"","title":"Investigation of Minimum Quantity Lubrication Coolant Strategy for the machining of Austempered Ductile Iron (ADI)","year":2018,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Austempering; Coolant; Lubrication; Metallurgy; Machining; Materials science; Cast iron; Mechanical engineering; Composite material; Engineering; Microstructure; Bainite; Austenite","score_opus":0.02413416303809098,"score_gpt":0.23781304810356585,"score_spread":0.21367888506547486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890572629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9836828,0.0016211311,0.013404308,0.00006885961,0.000018085577,0.0000400992,0.000041950443,0.000063666324,0.001059125],"genre_scores_gemma":[0.9898874,0.00043978603,0.009145764,0.000008329388,0.0000025324873,0.000010519898,0.00003288423,0.000009014947,0.0004637168],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99984825,0.000014853593,0.000011395576,0.00002418834,0.00008502692,0.000016242211],"domain_scores_gemma":[0.9998017,0.000060166243,0.00005631317,0.0000118065145,0.000058481648,0.000011618696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026969198,0.00016421756,0.0002490012,0.00029084715,0.00016208876,0.00028789713,0.00033367268,0.00022252454,0.0003730614],"category_scores_gemma":[0.00045750279,0.00014489306,0.00018951565,0.00015055075,0.00018855117,0.00037820736,0.00015634851,0.0002422899,0.00007300456],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028532493,0.000128295,0.0034104711,0.000896048,0.00001697997,0.00023312832,0.00021476149,0.018505787,0.9423531,0.00086625724,0.0002016476,0.032888174],"study_design_scores_gemma":[0.000048067515,0.0036817002,0.007873124,0.000043775155,0.000049969156,0.00040186875,0.00017513586,0.1838604,0.79879135,0.0002834806,0.0047532376,0.000037788723],"about_ca_topic_score_codex":0.0009638485,"about_ca_topic_score_gemma":0.0017542077,"teacher_disagreement_score":0.0009638485,"about_ca_system_score_codex":0.0002671357,"about_ca_system_score_gemma":0.00024254227,"threshold_uncertainty_score":0.0019382238},"labels":[],"label_agreement":null},{"id":"W2890661285","doi":"10.3390/jmmp2030060","title":"Machine Tool Volumetric Error Features Extraction and Classification Using Principal Component Analysis and K-Means","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Principal component analysis; Artificial intelligence; Computer science; Pattern recognition (psychology); Feature extraction; Encoder; Machine tool; Feature (linguistics); Fault (geology); Component (thermodynamics); Data mining; Engineering","score_opus":0.017811734713443807,"score_gpt":0.277620969260491,"score_spread":0.2598092345470472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890661285","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053990554,0.00012591235,0.94352406,0.00006209144,0.00004033037,0.00009255022,0.00017389895,0.0013694593,0.00062113296],"genre_scores_gemma":[0.45951304,0.00020153464,0.5379404,0.00002334313,0.000031084317,0.00020032428,0.0006724472,0.0001893677,0.0012284551],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908316,0.00008152628,0.00008400591,0.00017119841,0.00050104805,0.00007910424],"domain_scores_gemma":[0.9986891,0.00035082948,0.0001835947,0.00014461398,0.0006051635,0.000026727765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006659809,0.0010811491,0.00075333443,0.0023038501,0.0004320549,0.0009313399,0.0005881248,0.00050125644,0.00088150665],"category_scores_gemma":[0.0031056628,0.00031242095,0.00073694525,0.0020429173,0.00043786876,0.0011136386,0.0004852393,0.0007503604,0.00039001746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002451221,0.00018377365,0.0075956685,0.00025930005,0.0000961452,0.00011553256,0.0002711896,0.060272697,0.060781855,0.0025091239,0.0022928314,0.8653767],"study_design_scores_gemma":[0.000021235512,0.00016065483,0.026229724,0.000030081776,0.00005266793,0.00018217588,0.00020900414,0.9027853,0.063303575,0.0029709914,0.0039502042,0.000104301704],"about_ca_topic_score_codex":0.0034717016,"about_ca_topic_score_gemma":0.002559231,"teacher_disagreement_score":0.0034717016,"about_ca_system_score_codex":0.00037419493,"about_ca_system_score_gemma":0.00068490335,"threshold_uncertainty_score":0.0069029927},"labels":[],"label_agreement":null},{"id":"W2891500756","doi":"10.1007/s00170-018-2675-5","title":"Some observations on flood and dry finish turning of the Ti-6Al-4V aerospace alloy with carbide and PCD tools","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Aerospace; Carbide; Alloy; Metallurgy; Flood myth; Materials science; Titanium alloy; Engineering; Aerospace engineering; History","score_opus":0.009200651050712091,"score_gpt":0.22224123276891378,"score_spread":0.21304058171820167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891500756","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99301744,0.00029316396,0.0015638401,0.00007851473,0.000041099778,0.000019758254,0.0004150673,0.000094525836,0.0044766264],"genre_scores_gemma":[0.99614906,0.00008144392,0.0006451657,0.000029785195,0.0000121682915,0.000007053652,0.00033351334,0.000028735141,0.0027131499],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981934,0.000009138629,0.0000050364065,0.00002753704,0.000086392734,0.000052631523],"domain_scores_gemma":[0.9996056,0.00014601681,0.000045019322,0.00006598953,0.000072151466,0.00006523952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016233191,0.0002078278,0.00032866164,0.00061533693,0.00087254914,0.000306152,0.00036484387,0.00077211385,0.002502025],"category_scores_gemma":[0.0004188318,0.00021210327,0.00036771942,0.00041806494,0.0007141464,0.00021861547,0.0004134375,0.0007498244,0.00027598732],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018096395,0.00007499735,0.009851379,0.00013002685,0.000045599863,0.0029541922,0.0013951828,0.0009127177,0.9756663,0.00025689154,0.00096401834,0.0059391786],"study_design_scores_gemma":[0.000063162894,0.0009324518,0.48711514,0.00003183389,0.00008979929,0.0024120957,0.0027160477,0.0027634169,0.49204502,0.00045259646,0.011292499,0.00008599357],"about_ca_topic_score_codex":0.0033653283,"about_ca_topic_score_gemma":0.0057732025,"teacher_disagreement_score":0.0033653283,"about_ca_system_score_codex":0.00026563444,"about_ca_system_score_gemma":0.00013459996,"threshold_uncertainty_score":0.008370101},"labels":[],"label_agreement":null},{"id":"W2895821744","doi":"10.3390/jmmp2040066","title":"Selection of Machining Parameters Using a Correlative Study of Cutting Tool Wear in High-Speed Turning of AISI 1045 Steel","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Universidad Autónoma de Nuevo León","keywords":"Machining; Insert (composites); Response surface methodology; Tool wear; Cutting tool; Mechanical engineering; High-speed steel; Carbide; Multi-objective optimization; Flank; Materials science; Computer science; Engineering; Metallurgy; Machine learning","score_opus":0.013360488131196249,"score_gpt":0.2548443324237998,"score_spread":0.24148384429260353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895821744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958484,0.000057016303,0.003846467,0.000004210962,0.000002088864,0.0000130588005,0.000011925376,0.000016446429,0.00020042999],"genre_scores_gemma":[0.998582,0.000019713618,0.0013199445,0.0000015088391,7.334758e-7,0.0000039896063,0.00001406219,0.0000014631493,0.00005671188],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996997,0.00007400554,0.000017403829,0.000046682097,0.00013424181,0.000028080252],"domain_scores_gemma":[0.99908984,0.00048519304,0.00015273517,0.000069286936,0.00018575987,0.000017191838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080152927,0.00029190723,0.00039924335,0.0006514871,0.0001744036,0.00031972988,0.00035428855,0.00054959813,0.00022278905],"category_scores_gemma":[0.0012104736,0.00018492715,0.00045709734,0.0003516372,0.00025681537,0.00021373222,0.00010680341,0.00021761225,0.000054823464],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009283861,0.0009436151,0.06022041,0.0007182565,0.00016973105,0.00067138637,0.0007748912,0.24419862,0.62923944,0.00048785392,0.00023920751,0.061408214],"study_design_scores_gemma":[0.00003830188,0.0036797589,0.1472427,0.000024562367,0.00011319915,0.00035624907,0.00045463056,0.6312042,0.2161749,0.00021784712,0.00041493258,0.00007870114],"about_ca_topic_score_codex":0.0011459735,"about_ca_topic_score_gemma":0.0017748913,"teacher_disagreement_score":0.0011459735,"about_ca_system_score_codex":0.00018602434,"about_ca_system_score_gemma":0.00017860222,"threshold_uncertainty_score":0.004238963},"labels":[],"label_agreement":null},{"id":"W2896493418","doi":"10.5267/j.ijdns.2018.9.002","title":"Multi-objective optimization of CNC turning parameters using genetic algorithm and performance evaluation of nanocomposite coated carbide inserts","year":2018,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Carbide; Nanocomposite; Materials science; Genetic algorithm; Composite material; Mathematics; Mathematical optimization","score_opus":0.03451331993890337,"score_gpt":0.3164829240242391,"score_spread":0.2819696040853357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896493418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8444981,0.001323825,0.14416988,0.00026586655,0.00006882824,0.00019281333,0.0001657972,0.00042154966,0.0088934135],"genre_scores_gemma":[0.97250587,0.00017907102,0.025500095,0.00004202691,0.000004817382,0.00012382436,0.00012952535,0.0000195817,0.0014952081],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997811,0.000053784457,0.000012321668,0.00004192542,0.000049006343,0.00006198102],"domain_scores_gemma":[0.9992473,0.00045757636,0.000095743555,0.000021584983,0.00014151358,0.000036307007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007968681,0.0011421987,0.0009832793,0.0011189508,0.00038265524,0.0010832739,0.000748896,0.0014225398,0.0009896862],"category_scores_gemma":[0.0011859636,0.0004246595,0.0009338386,0.00063151633,0.000426738,0.0002766573,0.00039263626,0.0006881842,0.00009750309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057313257,0.00008515577,0.0006300687,0.000055261673,0.000025633515,0.0000508776,0.000019637935,0.99086636,0.0018151724,0.00014198701,0.00009585814,0.0061566452],"study_design_scores_gemma":[0.000010356646,0.00008631176,0.0005004299,0.0000061823607,0.000011767445,0.0000054377647,0.000017803968,0.99824524,0.0009646117,0.00006304108,0.0000842254,0.00000452928],"about_ca_topic_score_codex":0.013869673,"about_ca_topic_score_gemma":0.008934311,"teacher_disagreement_score":0.013869673,"about_ca_system_score_codex":0.00089219766,"about_ca_system_score_gemma":0.00088995404,"threshold_uncertainty_score":0.027577877},"labels":[],"label_agreement":null},{"id":"W2896760709","doi":"10.2351/1.5061467","title":"Smart tools with embedded optical fiber sensors: Laser based layered manufacturing procedures","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Materials science; Fiber Bragg grating; Machining; Fabrication; Optical fiber; Laser; Fiber laser; Process (computing); Fiber optic sensor; Fiber; Grating; Computer science; Optics; Optoelectronics; Composite material","score_opus":0.00784724414413727,"score_gpt":0.21703100180611576,"score_spread":0.2091837576619785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896760709","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39227238,0.003368013,0.5968447,0.00022414171,0.00014445065,0.0001461584,0.00015267568,0.0014638013,0.005383658],"genre_scores_gemma":[0.5531331,0.0009810802,0.44334394,0.000115236864,0.000033546265,0.00008511648,0.00006969514,0.000039558538,0.0021986587],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995846,0.00003022806,0.000024994351,0.000062573876,0.0002682187,0.000029391818],"domain_scores_gemma":[0.9995735,0.000092343296,0.00018190246,0.000084157014,0.000046730634,0.000021350612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023062697,0.00040790468,0.00024642592,0.0004085614,0.00012100808,0.00038863273,0.00079592137,0.0005653606,0.00053501455],"category_scores_gemma":[0.0004511969,0.00030358523,0.00025848555,0.00022250692,0.00044300323,0.0009065903,0.0006038026,0.00037278977,0.00040429493],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029147113,0.000028862125,0.00027076105,0.000105818406,0.000011198314,0.000078958066,0.000036656773,0.0012885686,0.97553045,0.0013640772,0.00010836729,0.02114714],"study_design_scores_gemma":[0.000011063188,0.00023274937,0.000695019,0.000013077733,0.000019118354,0.0004259784,0.000014956049,0.015916495,0.97736883,0.00041439585,0.0048565282,0.000031851665],"about_ca_topic_score_codex":0.00018372238,"about_ca_topic_score_gemma":0.00043496973,"teacher_disagreement_score":0.00079592137,"about_ca_system_score_codex":0.00026215258,"about_ca_system_score_gemma":0.0002036218,"threshold_uncertainty_score":0.0019021034},"labels":[],"label_agreement":null},{"id":"W2897820198","doi":"10.1007/s00170-018-2651-0","title":"Tool wear characterization in high-speed milling of titanium metal matrix composites","year":2018,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Materials science; Machinability; Abrasive; Tool wear; Insert (composites); Abrasion (mechanical); Machining; Surface roughness; Carbide; Titanium carbide; Metallurgy; Composite material; Ceramic; Surface finish; Titanium","score_opus":0.0043951798218034,"score_gpt":0.23273181239689422,"score_spread":0.22833663257509082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897820198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997943,0.00025423573,0.0014310788,0.000008667619,0.000011550219,0.0000067023852,0.000045033597,0.000029388664,0.00027036783],"genre_scores_gemma":[0.99874973,0.000038903716,0.00070268894,0.000005460312,0.000002142473,0.0000037579027,0.000040184077,0.000009169005,0.00044796936],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99969995,0.000020224432,0.000016298403,0.000051759926,0.00017534972,0.000036432244],"domain_scores_gemma":[0.9991731,0.00028866346,0.00015673375,0.00009302113,0.00025620547,0.000032240947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029567452,0.00018343829,0.00026850819,0.0005019103,0.00027707385,0.00030533233,0.00029367508,0.0004092794,0.0008173687],"category_scores_gemma":[0.00057629636,0.00020799809,0.00025611607,0.00029916107,0.00025092062,0.00024413387,0.00011080131,0.00022045225,0.0001236214],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034795236,0.00002211569,0.002127318,0.000061245744,0.000008939236,0.00008333172,0.00014371952,0.00039291574,0.9900513,0.000024921697,0.000075295706,0.006660951],"study_design_scores_gemma":[0.000014581177,0.0008216024,0.07502849,0.000008432977,0.00002611723,0.00030970332,0.00022323098,0.005874192,0.91654813,0.000035951114,0.0010873512,0.00002222745],"about_ca_topic_score_codex":0.00089172303,"about_ca_topic_score_gemma":0.0023331884,"teacher_disagreement_score":0.00089172303,"about_ca_system_score_codex":0.00022430257,"about_ca_system_score_gemma":0.00015740069,"threshold_uncertainty_score":0.002734363},"labels":[],"label_agreement":null},{"id":"W2898887753","doi":"10.1007/s10845-018-1453-4","title":"Failure time prediction using adaptive logical analysis of survival curves and multiple machining signals","year":2018,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability (semiconductor); Degradation (telecommunications); Process (computing); Computer science; Parametric statistics; Machining; Reliability engineering; Survival analysis; Data mining; Exploit; Asset (computer security); Artificial intelligence; Machine learning; Engineering; Mathematics; Statistics","score_opus":0.02271936846115548,"score_gpt":0.25369947386013114,"score_spread":0.23098010539897568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898887753","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2456193,0.00018961415,0.7527557,0.00008497069,0.000029743409,0.000046145276,0.00010212326,0.00052310945,0.0006492392],"genre_scores_gemma":[0.9713875,0.00008523274,0.027923366,0.000012635391,0.000017850052,0.000039041603,0.000101669146,0.000020828025,0.00041194406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967015,0.00008061236,0.000027321741,0.000085121785,0.00009708668,0.000039708793],"domain_scores_gemma":[0.9958853,0.0026598363,0.00045023861,0.0002149293,0.00070083136,0.0000889624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011842054,0.0007247798,0.0006357527,0.0015037318,0.00025274855,0.00066869345,0.0008305625,0.00058416836,0.0010370412],"category_scores_gemma":[0.005205705,0.0002659791,0.00068261346,0.00071142596,0.000341855,0.0009196225,0.0005438365,0.0006391137,0.0002087089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003729997,0.000117654316,0.016861157,0.000095907686,0.00008606289,0.00010667894,0.00007742259,0.8526564,0.0053200833,0.0021754142,0.00032971177,0.12180054],"study_design_scores_gemma":[0.0000023355556,0.000024238283,0.0009001103,0.0000019277827,0.0000059514027,0.000009658716,0.0000036591719,0.99807894,0.00041903212,0.0005229392,0.00002779312,0.0000034286568],"about_ca_topic_score_codex":0.0022771962,"about_ca_topic_score_gemma":0.002027858,"teacher_disagreement_score":0.0022771962,"about_ca_system_score_codex":0.00047487626,"about_ca_system_score_gemma":0.0005689288,"threshold_uncertainty_score":0.0062627792},"labels":[],"label_agreement":null},{"id":"W2899347417","doi":"10.1115/detc2018-85253","title":"Cutting Tool Wear Estimation Using a Genetic Algorithm Based Long Short-Term Memory Neural Network","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial neural network; Computer science; Term (time); Long short term memory; Genetic algorithm; Set (abstract data type); Automation; Machine learning; Time series; Training set; Data mining; Artificial intelligence; Tool wear; Algorithm; Recurrent neural network; Engineering; Machining","score_opus":0.012305679160464296,"score_gpt":0.25348260200560296,"score_spread":0.24117692284513867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899347417","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3454678,0.00068842695,0.64883476,0.00032113199,0.00008364288,0.000083931176,0.000098076656,0.0012757537,0.0031465325],"genre_scores_gemma":[0.9118861,0.000121625206,0.08612336,0.0000873225,0.000013342415,0.00008128011,0.000104230356,0.000023895695,0.0015588647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998362,0.000031178675,0.000009310226,0.000057072422,0.00003601851,0.00003025609],"domain_scores_gemma":[0.9996314,0.00017659226,0.00004888829,0.000019564055,0.00011180486,0.000011837807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051923236,0.0006738706,0.000563778,0.0005911799,0.00027185716,0.0005477763,0.0008228163,0.0010024465,0.0006546149],"category_scores_gemma":[0.001290539,0.00029611262,0.00046711694,0.00043640737,0.00028609534,0.00058853725,0.0003300517,0.0006143736,0.00011798646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006510587,0.00009010283,0.0018471238,0.000026402891,0.000049094884,0.0000600141,0.00002742274,0.9057532,0.003535651,0.0005172372,0.00030833567,0.087720245],"study_design_scores_gemma":[0.0000025205113,0.000014609787,0.00016775598,0.0000013035924,0.0000040626323,0.0000043722735,0.0000018350529,0.99927336,0.00040940882,0.00009263721,0.00002641908,0.0000017298458],"about_ca_topic_score_codex":0.014659997,"about_ca_topic_score_gemma":0.013446403,"teacher_disagreement_score":0.014659997,"about_ca_system_score_codex":0.0007606913,"about_ca_system_score_gemma":0.0008774921,"threshold_uncertainty_score":0.029149354},"labels":[],"label_agreement":null},{"id":"W2900931479","doi":"10.25071/10315/35246","title":"The Effect Of Minimum Quantity Lubrication On The The Fsw Process Performance","year":2018,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lubrication; Process (computing); Materials science; Process engineering; Computer science; Composite material; Engineering; Operating system","score_opus":0.005041602825274434,"score_gpt":0.23083367724968382,"score_spread":0.22579207442440938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900931479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99705976,0.0008009295,0.0016181599,0.000028105256,0.000009118918,0.000008434071,0.000059616745,0.000045660727,0.00037013245],"genre_scores_gemma":[0.9981641,0.0002693722,0.0012598754,0.0000062629533,0.0000025047334,0.0000045028783,0.000052994394,0.00001300731,0.00022734219],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996124,0.00006218666,0.000048909187,0.000059893708,0.00015531985,0.00006137465],"domain_scores_gemma":[0.9991968,0.00034334877,0.00018894828,0.000041503143,0.00019088588,0.000038459104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043485654,0.00034425932,0.00050489965,0.0002908261,0.00021321482,0.00047818714,0.0003006407,0.000285793,0.00068989524],"category_scores_gemma":[0.0018086289,0.00016716667,0.00022331564,0.0003524594,0.0002303973,0.00048548498,0.00021122595,0.0001943684,0.00013673039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007939735,0.00004461314,0.0017995102,0.00029697918,0.000016832015,0.000091839276,0.00012586662,0.0017755668,0.9837895,0.00007240716,0.000045932404,0.011146954],"study_design_scores_gemma":[0.000013586857,0.00131171,0.007219729,0.000009492448,0.00003403522,0.00009618408,0.000062303625,0.0036053401,0.98679,0.000026137504,0.0008169061,0.000014636077],"about_ca_topic_score_codex":0.0016676775,"about_ca_topic_score_gemma":0.0020243158,"teacher_disagreement_score":0.0016676775,"about_ca_system_score_codex":0.00024850597,"about_ca_system_score_gemma":0.00032192323,"threshold_uncertainty_score":0.0033159256},"labels":[],"label_agreement":null},{"id":"W2900969869","doi":"10.1115/1.4042019","title":"Modification of Tool Orientation and Position to Compensate Tool and Part Deflections in Five-Axis Ball End Milling Operations","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Deflection (physics); Machine tool; Cutter location; Machining; Ball (mathematics); End milling; Tool path; Stiffness; Finite element method; Mechanical engineering; Computer science; Engineering; Structural engineering; Geometry; Mathematics; Optics","score_opus":0.010346439549420926,"score_gpt":0.2467961707859177,"score_spread":0.23644973123649676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900969869","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.111121304,0.00011486242,0.88761866,0.00001994514,0.000014090771,0.000023113147,0.000012286531,0.0004841541,0.0005915524],"genre_scores_gemma":[0.79501694,0.00008780786,0.20386155,0.000015400745,0.0000036917402,0.000019174802,0.00004148497,0.00005832191,0.0008955398],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998292,0.000025036923,0.0000065729873,0.000042928765,0.00007685793,0.000019438918],"domain_scores_gemma":[0.9998115,0.000044644956,0.000054430642,0.000041111685,0.000040352825,0.000007899821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022595041,0.00041196845,0.000346551,0.00014638284,0.00014033954,0.00027387202,0.00052049843,0.00035199572,0.00039609987],"category_scores_gemma":[0.0005144182,0.0002470034,0.00017189396,0.00016001184,0.00017391687,0.0002807616,0.0002581597,0.00035563213,0.00018614907],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024306176,0.0001492275,0.0054999064,0.00016752328,0.000024801688,0.00016231493,0.0001925107,0.30005118,0.28459483,0.0013334744,0.0004485828,0.4071325],"study_design_scores_gemma":[0.000031952884,0.00026709973,0.005231499,0.0000106864545,0.000019876526,0.00023016085,0.0000517183,0.9092268,0.08273755,0.00047977347,0.0016864632,0.000026520584],"about_ca_topic_score_codex":0.001412146,"about_ca_topic_score_gemma":0.002470802,"teacher_disagreement_score":0.001412146,"about_ca_system_score_codex":0.00013880068,"about_ca_system_score_gemma":0.00036382707,"threshold_uncertainty_score":0.0028078556},"labels":[],"label_agreement":null},{"id":"W2901510825","doi":"10.25071/10315/35212","title":"Multi-Objective Optimization During Machining Ti-6Al-4V Using Nano-Fluids","year":2018,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nano-; Machining; Materials science; Computer science; Metallurgy; Composite material","score_opus":0.009328373524144895,"score_gpt":0.2436107365202741,"score_spread":0.2342823629961292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901510825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5677397,0.0011745796,0.42440277,0.00021748434,0.000049063252,0.00023082724,0.00012587472,0.00025202017,0.0058076214],"genre_scores_gemma":[0.92417884,0.00023924549,0.073439896,0.000036184316,0.000005894384,0.00020088322,0.00007949629,0.000025785295,0.0017936425],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997688,0.00007105531,0.000011750435,0.000041913314,0.00006728638,0.000039073577],"domain_scores_gemma":[0.9995994,0.0002612864,0.000064978194,0.000010673521,0.000049879032,0.0000137389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007814439,0.00080188795,0.0007213342,0.00054527767,0.00027192093,0.0007674748,0.00061137,0.0008720443,0.00065227546],"category_scores_gemma":[0.00075702346,0.00038868346,0.00076697837,0.00038358348,0.00034043536,0.00034642612,0.00041426654,0.00049275317,0.00007700999],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024239942,0.000034234792,0.00030763514,0.00006228002,0.000018963272,0.000027642547,0.000016411173,0.99006236,0.0035283477,0.00031756677,0.00004059063,0.0055596703],"study_design_scores_gemma":[0.000005353534,0.000073899304,0.00020821637,0.0000038392436,0.0000072210114,0.000005165656,0.0000134530455,0.9978516,0.0014974618,0.00016447347,0.0001665491,0.0000027785557],"about_ca_topic_score_codex":0.0047106766,"about_ca_topic_score_gemma":0.0049365093,"teacher_disagreement_score":0.0047106766,"about_ca_system_score_codex":0.00072370144,"about_ca_system_score_gemma":0.0009001413,"threshold_uncertainty_score":0.009366512},"labels":[],"label_agreement":null},{"id":"W2901915193","doi":"10.25071/10315/35211","title":"The Effect Of Nanoparticle Concentration On Mql Performance When Machining Ti-6Al-4V Titanium Alloy","year":2018,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Titanium alloy; Materials science; Alloy; Machining; Nanoparticle; Titanium; Metallurgy; Nanotechnology","score_opus":0.004018622800212231,"score_gpt":0.2132904861433252,"score_spread":0.20927186334311296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901915193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982078,0.00052055815,0.0007530172,0.000031059753,0.000014849771,0.000009441871,0.00005027572,0.000025371586,0.0003875343],"genre_scores_gemma":[0.9969252,0.00031622621,0.0018210444,0.000015817162,0.0000072206394,0.000014182998,0.000059852562,0.000017569002,0.0008228315],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99970704,0.000042135634,0.000033005304,0.00006839113,0.00009632864,0.000053142863],"domain_scores_gemma":[0.9992644,0.00028693647,0.00018337736,0.0000309606,0.00020182862,0.000032559015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038339046,0.0003311296,0.00028069763,0.0002685169,0.00022228238,0.00041722946,0.00028163398,0.00041906323,0.00058668933],"category_scores_gemma":[0.0011710352,0.00025356293,0.00025994718,0.00017706038,0.00030225387,0.00041125002,0.00015306943,0.00027339303,0.00019641286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022417413,0.000021533599,0.00029371658,0.000071681316,0.0000055133078,0.000026344747,0.00005220684,0.00020749174,0.99722797,0.000012538989,0.000016901979,0.0018399834],"study_design_scores_gemma":[0.0000033783922,0.00061582774,0.0017491042,0.0000031944817,0.000018379451,0.00001857499,0.0000382701,0.0006563591,0.99663687,0.000006277534,0.0002471008,0.0000066503326],"about_ca_topic_score_codex":0.0011365538,"about_ca_topic_score_gemma":0.0023139887,"teacher_disagreement_score":0.0011365538,"about_ca_system_score_codex":0.00031837632,"about_ca_system_score_gemma":0.00014529344,"threshold_uncertainty_score":0.002309978},"labels":[],"label_agreement":null},{"id":"W2902290085","doi":"10.5539/mer.v8n2p10","title":"Influence of Water-Miscible Cutting Fluids on Tool Wear Behavior of Different Coated HSS Tools in Hobbing","year":2018,"lang":"en","type":"article","venue":"Mechanical Engineering Research","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cutting fluid; Materials science; Surface roughness; Hobbing; Tool wear; Coating; Metallurgy; Surface finish; Cutting tool; Flank; Composite material; Machining","score_opus":0.03338161427591096,"score_gpt":0.3164439955196165,"score_spread":0.28306238124370553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902290085","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998976,0.00025409053,0.0006155791,0.0000036167169,0.0000032658397,0.0000071055683,0.000023014602,0.0000119765045,0.000105544175],"genre_scores_gemma":[0.99804735,0.00017934002,0.0013801543,0.000006976318,0.0000023576856,0.000008297708,0.000045466066,0.000015487545,0.0003145835],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995073,0.000076346,0.00004498859,0.000072214316,0.00020806282,0.00009111097],"domain_scores_gemma":[0.9989862,0.0004194208,0.00021936557,0.00007577666,0.00021800952,0.000081210484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034492603,0.00046623076,0.00047548115,0.0004503583,0.00022097836,0.00045016623,0.00026560685,0.0003514207,0.0006643175],"category_scores_gemma":[0.0011452335,0.00024425192,0.000355838,0.00022008807,0.00034547134,0.0003435747,0.00025611676,0.00023600503,0.0001424692],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006535264,0.000040521216,0.0020625114,0.00017865725,0.000023596944,0.000110665176,0.00017603865,0.00078560744,0.9902941,0.00001540337,0.000012740041,0.0056466],"study_design_scores_gemma":[0.000011560658,0.0013202076,0.009896804,0.000011522925,0.000033512828,0.000087522334,0.0001997913,0.0021530802,0.9857347,0.00001754682,0.0005122868,0.00002149668],"about_ca_topic_score_codex":0.001158446,"about_ca_topic_score_gemma":0.0021919133,"teacher_disagreement_score":0.001158446,"about_ca_system_score_codex":0.0001744174,"about_ca_system_score_gemma":0.00018622239,"threshold_uncertainty_score":0.002303362},"labels":[],"label_agreement":null},{"id":"W2903963931","doi":"","title":"A New Way of Considering Insert Wear In the Drilling Rate Model For Roller Cone Bits","year":2011,"lang":"en","type":"article","venue":"45th U.S. Rock Mechanics / Geomechanics Symposium","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Insert (composites); Drilling; Cone (formal languages); Engineering drawing; Mechanical engineering; Engineering; Geology; Computer science; Algorithm","score_opus":0.02432666877483109,"score_gpt":0.220773129780704,"score_spread":0.19644646100587293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903963931","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010288523,0.00041474946,0.9857438,0.00017584146,0.0001081479,0.000030449206,0.000070637565,0.00018050376,0.0029873226],"genre_scores_gemma":[0.8096129,0.0015126524,0.16769372,0.00024053273,0.00018433089,0.0001938729,0.00019994624,0.00033963574,0.020022415],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995819,0.00011377834,0.000030863113,0.00006510049,0.00017134627,0.000037009893],"domain_scores_gemma":[0.9992894,0.00029873464,0.00006982738,0.00009364035,0.00022065408,0.000027806318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001095066,0.00093520805,0.0010110413,0.00070805824,0.0003286372,0.00133788,0.0019617258,0.0016369426,0.0022145882],"category_scores_gemma":[0.0029651003,0.0005296183,0.0011970932,0.0004982249,0.00054923387,0.0025665748,0.0007563471,0.0017661814,0.0006195649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004995631,0.00003921662,0.0005524552,0.00009071327,0.000027905262,0.00013000646,0.00006794,0.95605224,0.005284695,0.015665494,0.0007746489,0.02126474],"study_design_scores_gemma":[0.0000023230793,0.000012636297,0.00004174986,0.0000051132483,0.0000052366477,0.000015296586,0.0000031475533,0.9978824,0.00031838572,0.0012367221,0.00047122574,0.000005715791],"about_ca_topic_score_codex":0.0053740637,"about_ca_topic_score_gemma":0.0055322256,"teacher_disagreement_score":0.0053740637,"about_ca_system_score_codex":0.0003598764,"about_ca_system_score_gemma":0.00072950334,"threshold_uncertainty_score":0.010685563},"labels":[],"label_agreement":null},{"id":"W2905378739","doi":"10.1115/1.4042307","title":"A Hybrid Modeling Approach for Characterization and Simulation of Cryogenic Machining of Ti–6Al–4V Alloy","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Coolant; Machining; Materials science; Finite element method; Heat transfer; Computational fluid dynamics; Mechanical engineering; Heat transfer coefficient; Chip formation; Turbulence; Volume fraction; Cutting fluid; Tool wear; Jet (fluid); Titanium alloy; Alloy; Mechanics; Composite material; Metallurgy; Structural engineering; Engineering; Aerospace engineering","score_opus":0.011226500992012223,"score_gpt":0.2291813255841265,"score_spread":0.21795482459211427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905378739","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11842996,0.00057732663,0.8678494,0.00017016183,0.00007588525,0.0002126258,0.0004472467,0.001368633,0.010868786],"genre_scores_gemma":[0.7809837,0.00060323376,0.21107616,0.000070111004,0.000033645534,0.0006580443,0.0005810076,0.0002096944,0.005784553],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998192,0.000032452466,0.000010666545,0.000023350483,0.00008731603,0.000027061189],"domain_scores_gemma":[0.9997727,0.00009223169,0.00003197111,0.000026931411,0.000060690876,0.00001551614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003778902,0.00076217914,0.00072907243,0.00068187126,0.0005198749,0.0007900421,0.0013720243,0.0013857208,0.0016719509],"category_scores_gemma":[0.00048223705,0.00064136443,0.0010070979,0.00043338252,0.00036134955,0.0004891838,0.0004941746,0.00050844694,0.00029931628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021290274,0.000028276856,0.0005870788,0.000051583254,0.000019758076,0.00005974781,0.000044991455,0.9852865,0.007072813,0.0015178913,0.00015521646,0.0051548337],"study_design_scores_gemma":[0.0000027567967,0.000016037653,0.0001232916,0.0000030639587,0.0000036768524,0.000013520522,0.0000069673392,0.9983516,0.00080141483,0.00014635737,0.00052739755,0.000003898849],"about_ca_topic_score_codex":0.008390714,"about_ca_topic_score_gemma":0.0076110433,"teacher_disagreement_score":0.008390714,"about_ca_system_score_codex":0.0006780428,"about_ca_system_score_gemma":0.0011622361,"threshold_uncertainty_score":0.016683757},"labels":[],"label_agreement":null},{"id":"W2907135495","doi":"10.1177/1350650118822388","title":"Tool wear and chip formation during dry high speed turning of direct aged Inconel 718 aerospace superalloy using different ceramic tools","year":2019,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"McMaster University","keywords":"Inconel; Superalloy; Aerospace; Materials science; Ceramic; Metallurgy; Engineering; Alloy; Aerospace engineering","score_opus":0.008738841559056083,"score_gpt":0.20045535497461572,"score_spread":0.19171651341555965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907135495","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997013,0.00008648046,0.00012234163,0.0000018572789,0.000002072899,0.0000017793764,0.000024136492,0.000005908046,0.000054111428],"genre_scores_gemma":[0.9993167,0.000057912774,0.00030889362,0.0000033691472,0.0000015656638,0.0000029991977,0.00005355632,0.0000045608,0.000250433],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977297,0.000019639287,0.000018698684,0.000045096305,0.00009116223,0.000052466814],"domain_scores_gemma":[0.9996655,0.000084217354,0.00009960139,0.00004514731,0.00007518071,0.000030289462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001772709,0.00026699668,0.00028896052,0.0003621774,0.00015809381,0.00023159213,0.000248201,0.0002985795,0.0006578157],"category_scores_gemma":[0.00031836992,0.00019449001,0.00027317498,0.00019075132,0.00024407405,0.00019265467,0.00018929785,0.00019629979,0.000073088006],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022867645,0.000018997333,0.0014456656,0.000058975078,0.0000115538805,0.00017333277,0.00014112337,0.0002783158,0.9958584,0.0000128507945,0.000018430328,0.0017537095],"study_design_scores_gemma":[0.00001881125,0.0017585753,0.056733653,0.000009925073,0.00004265333,0.0003128688,0.00028278286,0.0029028438,0.93727654,0.000020407486,0.00061639235,0.00002460655],"about_ca_topic_score_codex":0.0009113077,"about_ca_topic_score_gemma":0.0014045734,"teacher_disagreement_score":0.0009113077,"about_ca_system_score_codex":0.00015528103,"about_ca_system_score_gemma":0.00008340531,"threshold_uncertainty_score":0.002200663},"labels":[],"label_agreement":null},{"id":"W2907241196","doi":"10.5267/j.msl.2018.12.004","title":"Applications of optimization techniques for parametric analysis of non-traditional machining processes: A Review","year":2018,"lang":"en","type":"review","venue":"Management Science Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Computer science; Industrial engineering; Parametric statistics; Manufacturing engineering; Engineering drawing; Mechanical engineering; Engineering; Mathematics; Statistics","score_opus":0.024964376248327206,"score_gpt":0.31867329165547775,"score_spread":0.29370891540715055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907241196","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00028285827,0.9930227,0.005008695,0.0001059668,0.0001198265,0.000010947854,0.000018656932,0.00002360647,0.001406745],"genre_scores_gemma":[0.0028939126,0.99140394,0.004754129,0.000052331965,0.00019994272,0.00002030018,0.000050260536,0.000011798033,0.0006133366],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993268,0.00010397776,0.00009244032,0.0001366066,0.00030786064,0.000032331387],"domain_scores_gemma":[0.9984092,0.000989463,0.00015694943,0.000064906395,0.00034145568,0.00003796348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013106414,0.0015852427,0.0020424547,0.0037788958,0.00029755762,0.0012154481,0.0015208379,0.0012706836,0.002991647],"category_scores_gemma":[0.0019136681,0.00073633104,0.0010963258,0.0059468644,0.00068345806,0.0016891236,0.0007807364,0.001460153,0.0018141433],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042936397,0.00012199905,0.00033796707,0.020652108,0.00018196035,0.00019526934,0.00009833096,0.004739148,0.0031419683,0.0074625975,0.008975317,0.9540505],"study_design_scores_gemma":[0.00003223484,0.0002859158,0.0023392823,0.006689015,0.00039424485,0.0017711654,0.00014924853,0.0056334944,0.0043416326,0.007819128,0.9704188,0.00012588582],"about_ca_topic_score_codex":0.0010901127,"about_ca_topic_score_gemma":0.0011208465,"teacher_disagreement_score":0.0037788958,"about_ca_system_score_codex":0.00047560874,"about_ca_system_score_gemma":0.0010010479,"threshold_uncertainty_score":0.010008037},"labels":[],"label_agreement":null},{"id":"W2909184105","doi":"10.1007/s00170-019-03294-0","title":"A model for machining with nano-additives based minimum quantity lubrication","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Coolant; Machining; Materials science; Lubrication; Inconel; Cutting fluid; Finite element method; Mechanical engineering; Heat transfer; Metallurgy; Lubricant; Superalloy; Composite material; Mechanics; Engineering; Structural engineering; Alloy","score_opus":0.008131845490449383,"score_gpt":0.2391688334064587,"score_spread":0.23103698791600932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909184105","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053780623,0.0016937566,0.89800376,0.0010258887,0.00032704478,0.00015780938,0.0004824842,0.0004839215,0.044044673],"genre_scores_gemma":[0.8880724,0.0011387917,0.060523923,0.0002136144,0.000100211524,0.00040904863,0.00032923964,0.00017596662,0.049036734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983263,0.000030869738,0.0000073118854,0.000040615058,0.00006280513,0.000025718993],"domain_scores_gemma":[0.99972004,0.00014130493,0.00004164409,0.000019551091,0.000057068617,0.000020467378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026067262,0.00069926423,0.0011562973,0.00051177817,0.00052790245,0.0010970811,0.0017795145,0.0026576575,0.004766216],"category_scores_gemma":[0.0008699939,0.0004250967,0.00075786904,0.00046192366,0.0007220973,0.0012005445,0.00068050704,0.0009798785,0.0008661927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004283908,0.00003716667,0.00012949204,0.00010639249,0.000012587472,0.0000676815,0.000029552128,0.9644496,0.0038957081,0.027328905,0.00053678185,0.003363331],"study_design_scores_gemma":[0.0000069284893,0.0000116616975,0.000027026355,0.0000027063586,0.0000027710294,0.000006686239,0.000002070609,0.9966827,0.0002643734,0.002451586,0.00053866685,0.000002927304],"about_ca_topic_score_codex":0.0069512003,"about_ca_topic_score_gemma":0.0042506796,"teacher_disagreement_score":0.0069512003,"about_ca_system_score_codex":0.00084497,"about_ca_system_score_gemma":0.0010738902,"threshold_uncertainty_score":0.0159446},"labels":[],"label_agreement":null},{"id":"W2911374908","doi":"10.1007/s00170-019-03314-z","title":"Comparison of between direct and peck drilling for large aspect ratio in Ti-6Al-4V alloy","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drilling; Machining; Thrust; Drill; Peck (Imperial); Surface roughness; Mechanical engineering; Surface finish; Materials science; Engineering; Composite material; Geometry","score_opus":0.009767149278269457,"score_gpt":0.2870941384855923,"score_spread":0.27732698920732285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911374908","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97476995,0.0019825909,0.016086748,0.000076305645,0.00009714659,0.00003788327,0.00021358895,0.00030453206,0.0064313062],"genre_scores_gemma":[0.9901606,0.00021082767,0.007988913,0.000010410666,0.000006105995,0.0000075253934,0.00008376226,0.0000264465,0.0015054859],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997135,0.000022613427,0.000014667818,0.000042735657,0.00017133223,0.00003515092],"domain_scores_gemma":[0.99938023,0.00019282577,0.00008472678,0.00005589358,0.00026422043,0.00002213295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028233943,0.0002429925,0.000372143,0.00028915616,0.000273682,0.00052831596,0.00045872942,0.0004416536,0.0021457186],"category_scores_gemma":[0.00081460766,0.00020479901,0.00027935926,0.00021021957,0.0002794762,0.0004970346,0.00031913604,0.00019944957,0.00031088246],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0053184694,0.00014413019,0.007665958,0.0015483696,0.00009048411,0.00048330353,0.0004133219,0.015507304,0.85088587,0.0019553674,0.0014804173,0.11450707],"study_design_scores_gemma":[0.0002823443,0.00606537,0.07181028,0.00009404258,0.0002623919,0.002403032,0.00082683045,0.09024387,0.8098935,0.00082528096,0.017156973,0.00013618037],"about_ca_topic_score_codex":0.001050591,"about_ca_topic_score_gemma":0.002980697,"teacher_disagreement_score":0.0021457186,"about_ca_system_score_codex":0.00024707522,"about_ca_system_score_gemma":0.00038930646,"threshold_uncertainty_score":0.0071781278},"labels":[],"label_agreement":null},{"id":"W2911386729","doi":"10.5539/mas.v13n2p275","title":"Optimal Performance of Caps’ Pressing Process Using Taguchi-Grey Method","year":2019,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taguchi methods; Grey relational analysis; Pressing; Quality (philosophy); Process (computing); Process capability; Computer science; Process engineering; Mathematics; Statistics; Operations management; Mechanical engineering; Work in process; Engineering; Physics","score_opus":0.011024998116411638,"score_gpt":0.2710968919054113,"score_spread":0.26007189378899964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911386729","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55283564,0.002219144,0.43915924,0.00011045386,0.00003737078,0.0001566232,0.000072800314,0.00031462873,0.0050941114],"genre_scores_gemma":[0.92432266,0.00063933176,0.07415998,0.000017688071,0.0000064622295,0.000042652264,0.00003863559,0.000035908724,0.00073661725],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99865353,0.00033749937,0.00007852189,0.0002053425,0.00061349204,0.00011158764],"domain_scores_gemma":[0.99956125,0.0002254469,0.00007956696,0.000032277785,0.00008767729,0.000013674795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015625495,0.0005761544,0.0007076076,0.0005684255,0.00025171373,0.0009666617,0.00054889946,0.0005697195,0.0007155014],"category_scores_gemma":[0.0013776236,0.0002826182,0.00058063905,0.0007061932,0.00039731822,0.00057942723,0.00029265208,0.00034689013,0.00028048095],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006424978,0.00013175048,0.0013850365,0.00072568096,0.00004793378,0.00014559797,0.00029944433,0.08453647,0.8397829,0.0024344025,0.0001846135,0.069683686],"study_design_scores_gemma":[0.000031139803,0.0012761392,0.0029623837,0.000025152596,0.00008886078,0.00012519553,0.000109760236,0.20085315,0.7919393,0.00075024,0.0017842777,0.000054356606],"about_ca_topic_score_codex":0.0010478352,"about_ca_topic_score_gemma":0.0016378438,"teacher_disagreement_score":0.0015625495,"about_ca_system_score_codex":0.000451681,"about_ca_system_score_gemma":0.00054448127,"threshold_uncertainty_score":0.008263648},"labels":[],"label_agreement":null},{"id":"W2912701984","doi":"10.1007/s12541-019-00021-3","title":"FE Modeling and Experimental Analysis of Residual Stresses in Vibration Assisted Turning of Ti6Al4V","year":2019,"lang":"en","type":"article","venue":"International Journal of Precision Engineering and Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Residual stress; Titanium alloy; Materials science; Machining; Finite element method; Aerospace; Perpendicular; Metallurgy; Vibration; Carbide; Durability; Alloy; Mechanical engineering; Structural engineering; Composite material; Engineering; Acoustics","score_opus":0.00738619666858391,"score_gpt":0.24716470967781293,"score_spread":0.239778513009229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912701984","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942644,0.00008347302,0.002837708,0.000025749228,0.000013700428,0.000010238957,0.000112017144,0.00014285353,0.0025097698],"genre_scores_gemma":[0.99887687,0.000012019847,0.0005025691,0.0000024412118,0.0000015913076,0.00000488386,0.000046728535,0.000007637037,0.0005452093],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981517,0.000017310536,0.000005906105,0.000020293033,0.000103849954,0.000037453],"domain_scores_gemma":[0.99972147,0.00009663459,0.000038476945,0.000037182974,0.00008910261,0.000017015298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021932868,0.0002622698,0.00029384423,0.00035939092,0.00034024962,0.00027219718,0.0006041543,0.0005361054,0.0021421798],"category_scores_gemma":[0.0003549094,0.00020003636,0.0002913645,0.0002471186,0.00044057626,0.00016045583,0.000116018535,0.0002399338,0.00021442356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018928639,0.00046764666,0.0067164325,0.00036085068,0.00004671659,0.0006061007,0.00060460577,0.22447342,0.7263817,0.0013237832,0.0014194098,0.035706323],"study_design_scores_gemma":[0.000058057216,0.001247434,0.056536313,0.000026072883,0.000045631474,0.0002293531,0.0003429393,0.76057297,0.17873076,0.000248044,0.0019132901,0.00004911517],"about_ca_topic_score_codex":0.0028027003,"about_ca_topic_score_gemma":0.0040501063,"teacher_disagreement_score":0.0028027003,"about_ca_system_score_codex":0.0002821812,"about_ca_system_score_gemma":0.00022603467,"threshold_uncertainty_score":0.007166326},"labels":[],"label_agreement":null},{"id":"W2914247164","doi":"10.1016/j.ijmachtools.2019.02.003","title":"CFD and experimental analysis of the coolant flow in cryogenic milling","year":2019,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Ministero dello Sviluppo Economico","keywords":"Coolant; Nozzle; Machining; Mechanical engineering; Computational fluid dynamics; Materials science; Liquid nitrogen; Volumetric flow rate; Injector; Nuclear engineering; Flow (mathematics); Mechanics; Engineering; Aerospace engineering; Chemistry","score_opus":0.004047789057548296,"score_gpt":0.22343982666169723,"score_spread":0.21939203760414894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914247164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98209804,0.0002634217,0.008277431,0.00013459321,0.000049494534,0.000038471353,0.00033715906,0.00021756795,0.008583678],"genre_scores_gemma":[0.9974341,0.000055890385,0.0015015806,0.0000075135645,0.000005334626,0.000010940714,0.00008117274,0.000016623486,0.0008869525],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998447,0.000024168608,0.0000072138278,0.000029698484,0.00005661402,0.000037560378],"domain_scores_gemma":[0.9993051,0.00045037756,0.000038216866,0.000053369095,0.00012724992,0.000025632962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036106838,0.00028476192,0.0006156781,0.0003920808,0.00084645726,0.00068006385,0.00059783517,0.00065892347,0.0032092733],"category_scores_gemma":[0.0010704726,0.00025847447,0.0003842536,0.00036797594,0.0009934144,0.00049806945,0.00029348137,0.00052308245,0.00028117278],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022976343,0.000706968,0.015002338,0.00045522326,0.00003823079,0.0006240429,0.00075256923,0.71306527,0.22950509,0.0065940237,0.0022048457,0.028753733],"study_design_scores_gemma":[0.00010773691,0.00031087347,0.012790799,0.000019073763,0.000021362192,0.00006872454,0.00013218886,0.90865684,0.07576511,0.00042630773,0.0016587771,0.000042238247],"about_ca_topic_score_codex":0.009848471,"about_ca_topic_score_gemma":0.005113198,"teacher_disagreement_score":0.009848471,"about_ca_system_score_codex":0.00094427716,"about_ca_system_score_gemma":0.00088017585,"threshold_uncertainty_score":0.019582331},"labels":[],"label_agreement":null},{"id":"W2921016714","doi":"10.1177/1063293x19832940","title":"Study on lightweight structural optimization design system for gantry machine tool","year":2019,"lang":"en","type":"article","venue":"Concurrent Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Gantry crane; Frame (networking); Machine tool; Parametric statistics; Engineering; Computer science; Structural engineering; Mechanical engineering","score_opus":0.011472946773542632,"score_gpt":0.22931708497419206,"score_spread":0.21784413820064943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921016714","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04491736,0.0001533414,0.9488608,0.000053965647,0.000020052572,0.00006541262,0.000029249451,0.00033370123,0.0055660997],"genre_scores_gemma":[0.73022074,0.00023941207,0.26538414,0.00003792669,0.000020514288,0.00021095264,0.00015505486,0.00012545018,0.0036057732],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994985,0.00007830382,0.000021186788,0.000070861926,0.000296117,0.000035038272],"domain_scores_gemma":[0.9997397,0.00006861012,0.00004285964,0.00003904819,0.00010031815,0.000009387372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005142552,0.0005168863,0.00047133185,0.000512973,0.00031080394,0.00042876377,0.00055816094,0.00040355232,0.002317728],"category_scores_gemma":[0.0006620955,0.00031596996,0.0006402297,0.0003349127,0.00024649498,0.00040314053,0.00034930452,0.00040091152,0.00034361874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009289151,0.00006605836,0.002359168,0.000275229,0.000037742186,0.000111458656,0.0001446621,0.7375102,0.10176125,0.010204459,0.0010545537,0.14638227],"study_design_scores_gemma":[0.000021917218,0.00019905932,0.0012228051,0.000014638969,0.000019283621,0.00008243932,0.000027264792,0.9776404,0.014529517,0.0014007856,0.0048249946,0.000016891632],"about_ca_topic_score_codex":0.002097492,"about_ca_topic_score_gemma":0.001908207,"teacher_disagreement_score":0.002317728,"about_ca_system_score_codex":0.00038780575,"about_ca_system_score_gemma":0.00078475755,"threshold_uncertainty_score":0.007753551},"labels":[],"label_agreement":null},{"id":"W2921962515","doi":"10.3390/jmmp3010023","title":"Chip Morphology and Delamination Characterization for Vibration-Assisted Drilling of Carbon Fiber-Reinforced Polymer","year":2019,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"National Research Council Canada","keywords":"Delamination (geology); Materials science; Carbon fiber reinforced polymer; Vibration; Drilling; Composite material; Aerospace; Fiber pull-out; Structural engineering; Acoustics; Engineering; Metallurgy; Aerospace engineering; Composite laminates; Geology","score_opus":0.006461028182840171,"score_gpt":0.21366821370257053,"score_spread":0.20720718551973036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921962515","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99286073,0.0002401844,0.0063365106,0.000007764375,0.000008196194,0.000013057945,0.00009093379,0.000042642456,0.00039995208],"genre_scores_gemma":[0.9938532,0.00015003169,0.005161025,0.000008320548,0.0000022623708,0.000016463551,0.000118114396,0.00001262858,0.0006779167],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987817,0.00000645082,0.0000059878644,0.000024422481,0.000069967355,0.0000149997495],"domain_scores_gemma":[0.99951804,0.00012345187,0.00012397926,0.00004016095,0.0001693912,0.000024876737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015761319,0.0001608627,0.00012736605,0.0003800912,0.00009483908,0.0001615164,0.00017030541,0.0002253613,0.0007407534],"category_scores_gemma":[0.00033538626,0.00015144054,0.00012322102,0.00017741749,0.00019204944,0.00014508757,0.00012121053,0.00015766281,0.0001339231],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004138772,0.000015224545,0.0011325272,0.00003712332,0.0000023243845,0.000060922983,0.000054813456,0.00036305905,0.994968,0.000026476044,0.000025778783,0.003272298],"study_design_scores_gemma":[0.0000067220167,0.00065763725,0.06670636,0.00001180498,0.000015951937,0.00034926686,0.0001503756,0.008495863,0.92256695,0.000026550695,0.000991963,0.000020561507],"about_ca_topic_score_codex":0.00034281268,"about_ca_topic_score_gemma":0.0009482879,"teacher_disagreement_score":0.0007407534,"about_ca_system_score_codex":0.00009379677,"about_ca_system_score_gemma":0.00007792303,"threshold_uncertainty_score":0.0024781227},"labels":[],"label_agreement":null},{"id":"W2922381206","doi":"10.1007/s00170-019-03526-3","title":"Acoustic emission monitoring of sawing process: artificial intelligence approach for optimal sensory feature selection","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Waviness; Adaptive neuro fuzzy inference system; Particle swarm optimization; Acoustic emission; Engineering; Feature selection; Vibration; Artificial intelligence; Wavelet; Pattern recognition (psychology); Computer science; Fuzzy logic; Acoustics; Algorithm; Fuzzy control system; Mechanical engineering","score_opus":0.010951109203367851,"score_gpt":0.27057248761636654,"score_spread":0.2596213784129987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922381206","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10744535,0.00033731622,0.89018124,0.00011494997,0.000023680084,0.000021950325,0.000032436117,0.00016442631,0.0016786396],"genre_scores_gemma":[0.92952806,0.0001882103,0.069158815,0.000030103365,0.000022205086,0.000034694393,0.000046739508,0.000014815352,0.0009763835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987614,0.000025553614,0.000008813013,0.000034648274,0.000037752114,0.000017064849],"domain_scores_gemma":[0.9998111,0.00010669232,0.00002231314,0.000010138404,0.000043470725,0.000006341511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029034403,0.00039539946,0.0004827929,0.00032822392,0.0001558707,0.00041822996,0.00044658198,0.00043614686,0.0005706621],"category_scores_gemma":[0.0006851393,0.00017892303,0.00048759978,0.00027899328,0.00019307726,0.00039892967,0.0002045108,0.00036087772,0.000084252424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032334717,0.00026486942,0.0025203484,0.00020660595,0.00012131452,0.0001700694,0.00010942612,0.51643866,0.096885055,0.0033076159,0.0007098356,0.37894288],"study_design_scores_gemma":[0.0000036131246,0.000034933364,0.0007012937,0.0000022532518,0.000008782258,0.000016350312,0.000006611241,0.99546283,0.0032052302,0.00047111337,0.00008380622,0.000003235925],"about_ca_topic_score_codex":0.0011937357,"about_ca_topic_score_gemma":0.0011171874,"teacher_disagreement_score":0.0011937357,"about_ca_system_score_codex":0.00015566914,"about_ca_system_score_gemma":0.00027495413,"threshold_uncertainty_score":0.0023736358},"labels":[],"label_agreement":null},{"id":"W2923843910","doi":"10.1115/1.4043310","title":"Analytical Modeling of Process Damping in Machining","year":2019,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Enhanced Data Rates for GSM Evolution; Vibration; Materials science; Waveform; Process (computing); Indentation; Mechanical engineering; Structural engineering; Mechanics; Acoustics; Engineering; Computer science; Physics; Composite material","score_opus":0.006857231567518949,"score_gpt":0.23225985597347473,"score_spread":0.2254026244059558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2923843910","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04267382,0.00064036663,0.9436478,0.00008560536,0.00004015397,0.00005368559,0.00004579329,0.0004055249,0.012407292],"genre_scores_gemma":[0.9560746,0.00070919946,0.03457709,0.000028915074,0.00002483744,0.00010139915,0.000057317186,0.00009651898,0.008330095],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974436,0.000036445363,0.000007966852,0.000036993464,0.00014511358,0.000029097127],"domain_scores_gemma":[0.9997707,0.0001000566,0.00003142295,0.000024292338,0.00006348629,0.0000100266125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029511997,0.0006370361,0.0004664428,0.00048091385,0.0003083904,0.0006478507,0.001084027,0.0010842625,0.0012516606],"category_scores_gemma":[0.0011116925,0.00039040134,0.0004447291,0.00034793175,0.0006178716,0.0007075881,0.00042585106,0.00052801793,0.0004969794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020679478,0.000024077153,0.00023814022,0.000057535544,0.000008175955,0.00013042452,0.00012667269,0.9674137,0.012347145,0.01046016,0.00018213072,0.008991066],"study_design_scores_gemma":[0.0000017271768,0.0000061608034,0.00004629508,0.0000021950393,0.0000011768365,0.000011299068,0.000003683351,0.99852836,0.0003903489,0.00072962634,0.0002773118,0.0000018841606],"about_ca_topic_score_codex":0.003141487,"about_ca_topic_score_gemma":0.0015912601,"teacher_disagreement_score":0.003141487,"about_ca_system_score_codex":0.000570742,"about_ca_system_score_gemma":0.00046782385,"threshold_uncertainty_score":0.006246388},"labels":[],"label_agreement":null},{"id":"W2926439648","doi":"10.1007/s00170-019-03608-2","title":"Surface and microstructure characterization of low-frequency vibration-assisted drilling of Ti6Al4V","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"","keywords":"Residual stress; Materials science; Drilling; Machining; Microstructure; Surface integrity; Tool wear; Deep hole drilling; Titanium alloy; Chip formation; Vibration; Composite material; Metallurgy; Acoustics; Alloy","score_opus":0.0032934189828169565,"score_gpt":0.20929392235730704,"score_spread":0.20600050337449008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2926439648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99644655,0.00019764988,0.001921515,0.000029646984,0.000019490772,0.000008945944,0.00018202352,0.000057196656,0.0011370316],"genre_scores_gemma":[0.9969195,0.000048634687,0.001717465,0.0000097595985,0.0000037439042,0.000007173466,0.00017819833,0.00001063979,0.001104925],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99982965,0.00000901401,0.0000065231457,0.000030029256,0.000101749,0.00002294532],"domain_scores_gemma":[0.99978083,0.000036323996,0.000040128893,0.000017804014,0.00011030664,0.00001457079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013952787,0.00015859658,0.00016957043,0.00040665234,0.00019888594,0.00023173743,0.0003221084,0.00045574576,0.001769561],"category_scores_gemma":[0.0002716196,0.00019269399,0.00018917008,0.00022870307,0.00027972358,0.0002531204,0.00013063956,0.00017273931,0.00018065237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013204482,0.000014032116,0.00096026686,0.000056613695,0.0000041510357,0.00004501296,0.000045913108,0.00037499194,0.9950837,0.000075162716,0.00011606311,0.0030920305],"study_design_scores_gemma":[0.000029199451,0.00082391634,0.088944726,0.0000112655325,0.000029793933,0.0003796804,0.00032190714,0.015861204,0.8902177,0.00013045117,0.003217078,0.000033016393],"about_ca_topic_score_codex":0.0013451582,"about_ca_topic_score_gemma":0.0026418727,"teacher_disagreement_score":0.001769561,"about_ca_system_score_codex":0.00017408044,"about_ca_system_score_gemma":0.00017926899,"threshold_uncertainty_score":0.005919814},"labels":[],"label_agreement":null},{"id":"W2940500086","doi":"10.1007/s00170-019-03517-4","title":"Prediction of critical thrust force generated at the onset of delamination in machining carbon reinforced composites","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Delamination (geology); Thrust; Enhanced Data Rates for GSM Evolution; Drilling; Materials science; Composite material; Machining; Structural engineering; Drill; Mechanical engineering; Geology; Engineering; Metallurgy","score_opus":0.006132371769811788,"score_gpt":0.23076804152515293,"score_spread":0.22463566975534113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2940500086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9887649,0.00011735881,0.009591148,0.000041047366,0.000014195914,0.0000140221,0.000034551074,0.00010959667,0.0013131725],"genre_scores_gemma":[0.99937576,0.000016303065,0.00045407302,0.0000011689867,0.0000010054257,0.000001748384,0.000011107413,0.0000028491042,0.00013602841],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99996126,0.000002663505,0.0000013011773,0.000008256037,0.000012925502,0.000013643383],"domain_scores_gemma":[0.99961686,0.00020732755,0.00005572976,0.000011533921,0.000072737465,0.000035798996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012880037,0.00040938242,0.00020088881,0.0004282309,0.0002768098,0.00034081624,0.00024584273,0.0005929202,0.00081674976],"category_scores_gemma":[0.00047156593,0.00021477182,0.00019040098,0.00012406046,0.0002712498,0.00019387457,0.00014795706,0.00037599594,0.00011982985],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085970043,0.00022608644,0.02689107,0.00016606082,0.000022085726,0.00097284757,0.00016649994,0.7355629,0.21083634,0.0014256557,0.0005173858,0.02235332],"study_design_scores_gemma":[0.000010380119,0.0001201789,0.011880092,0.0000054590682,0.0000044776993,0.00003732037,0.00002785175,0.96301067,0.024669724,0.00012465622,0.00010097086,0.000008226228],"about_ca_topic_score_codex":0.0069425893,"about_ca_topic_score_gemma":0.004772651,"teacher_disagreement_score":0.0069425893,"about_ca_system_score_codex":0.0005330886,"about_ca_system_score_gemma":0.00048599034,"threshold_uncertainty_score":0.013804376},"labels":[],"label_agreement":null},{"id":"W2940785958","doi":"10.1115/1.4043578","title":"A Two-Dimensional Transient Thermal Model for Coated Cutting Tools","year":2019,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Rake; Materials science; Chip; Tool wear; Finite element method; Chip formation; Cutting tool; Coating; Heat transfer; Machining; Transient (computer programming); Shear zone; Machine tool; Mechanical engineering; Composite material; Mechanics; Structural engineering; Metallurgy; Computer science; Geology; Engineering","score_opus":0.010302979733297014,"score_gpt":0.2233785937801878,"score_spread":0.21307561404689077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2940785958","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.091977775,0.00031204606,0.8870063,0.00024490533,0.00010192819,0.0001290275,0.00051586394,0.0008689018,0.018843245],"genre_scores_gemma":[0.94202244,0.00027448984,0.040838007,0.000060887738,0.000026574506,0.0003801516,0.0004151942,0.00015101541,0.015831338],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999846,0.000028233808,0.000007813553,0.00003660967,0.000055966528,0.000025222169],"domain_scores_gemma":[0.9997807,0.000089776884,0.000026315234,0.000021460055,0.00006244092,0.000019321134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023581677,0.00058299914,0.00065378187,0.00035349134,0.0004599809,0.0009599348,0.0013079876,0.0015668888,0.0028339645],"category_scores_gemma":[0.00070142833,0.0005610628,0.00088592945,0.00033708278,0.00067771494,0.0005405366,0.00048978126,0.00079870026,0.00053635205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020835283,0.000010626238,0.00013924467,0.000016136475,0.0000050324684,0.00003419286,0.000020147698,0.9943715,0.0025293238,0.001776662,0.00011625544,0.00096014346],"study_design_scores_gemma":[0.000003999077,0.000004572789,0.000050208546,0.0000012706765,0.0000015785905,0.000005371014,0.0000025372253,0.9992623,0.0002455121,0.00018776966,0.00023245862,0.0000024273397],"about_ca_topic_score_codex":0.013368903,"about_ca_topic_score_gemma":0.006086334,"teacher_disagreement_score":0.013368903,"about_ca_system_score_codex":0.00082228257,"about_ca_system_score_gemma":0.0010853983,"threshold_uncertainty_score":0.026582181},"labels":[],"label_agreement":null},{"id":"W2946736682","doi":"10.1016/j.ymssp.2019.04.057","title":"Estimation of vibration stability in turning using operational modal analysis","year":2019,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vibration; Modal; Machining; Engineering; Process (computing); Stability (learning theory); Modal analysis; Instability; Control theory (sociology); Machine tool; Computer science; Structural engineering; Control engineering; Mechanical engineering; Finite element method; Artificial intelligence; Acoustics; Machine learning","score_opus":0.013398774326855174,"score_gpt":0.24219551095649933,"score_spread":0.22879673662964414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946736682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8375917,0.00013599031,0.16104929,0.00002258022,0.000011258172,0.0000129733335,0.00003382643,0.00014437862,0.0009979592],"genre_scores_gemma":[0.9965017,0.000010587706,0.0033858859,0.0000013625536,0.0000018650791,0.0000023852883,0.000015081626,0.000004826481,0.00007624988],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998653,0.000036512505,0.0000061824453,0.000021859658,0.00004722848,0.000022914253],"domain_scores_gemma":[0.99939764,0.00037192335,0.000056283963,0.000029203551,0.000111773814,0.00003320447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000284378,0.0002631904,0.0003006112,0.0008589927,0.00022307069,0.00030796407,0.00023787397,0.00029045396,0.00054450333],"category_scores_gemma":[0.0011048912,0.00016155567,0.00021897785,0.00024517236,0.00028368208,0.00027034327,0.00034186605,0.00021509151,0.000085645384],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028235791,0.00019577253,0.047391392,0.00020467752,0.00016305869,0.00032774507,0.0004725215,0.34205967,0.34005356,0.003632881,0.00051041273,0.2621647],"study_design_scores_gemma":[0.000010467076,0.00015157861,0.020880532,0.0000074146774,0.000017836739,0.00007681755,0.00008598867,0.96356964,0.014362251,0.0007000076,0.00011997225,0.000017487293],"about_ca_topic_score_codex":0.0014017045,"about_ca_topic_score_gemma":0.001444253,"teacher_disagreement_score":0.0014017045,"about_ca_system_score_codex":0.00014920266,"about_ca_system_score_gemma":0.00012898583,"threshold_uncertainty_score":0.0027871132},"labels":[],"label_agreement":null},{"id":"W2946829374","doi":"10.1007/s00170-019-03863-3","title":"Hard turning multi-performance optimization for improving the surface integrity of 300M ultra-high strength steel","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; École de Technologie Supérieure; Polytechnique Montréal","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Héroux-Devtek; Mitacs; Consortium de Recherche et d’innovation en Aérospatiale au Québec; Pratt and Whitney Canada","keywords":"Surface integrity; Hardened steel; Surface roughness; Materials science; Taguchi methods; Context (archaeology); Mechanical engineering; Boron nitride; Response surface methodology; Machining; Composite material; Metallurgy; Engineering; Computer science","score_opus":0.0076577887770650005,"score_gpt":0.23121165136051314,"score_spread":0.22355386258344814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946829374","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91474193,0.00063939556,0.07398009,0.00011970256,0.00005206229,0.00002762709,0.000050922998,0.00032746463,0.010060779],"genre_scores_gemma":[0.994749,0.00003976967,0.0041422006,0.000008117335,0.0000033019255,0.0000070402193,0.000031987845,0.000021315755,0.0009973305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998079,0.000016452417,0.0000049728524,0.000029036992,0.00009507579,0.00004650389],"domain_scores_gemma":[0.9998498,0.00003385673,0.000029486662,0.000012594684,0.000060545648,0.000013776078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021400524,0.00055914145,0.00048523516,0.00044785388,0.00031474658,0.0007091873,0.0005380054,0.0005744012,0.0011516387],"category_scores_gemma":[0.00023332576,0.00028474128,0.00045388672,0.0002593743,0.00025377647,0.00027701678,0.00036816404,0.00033783863,0.00016496883],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039420874,0.0001555272,0.001701735,0.00016505651,0.00008254916,0.00016712626,0.000079631434,0.6570194,0.29461887,0.0013464964,0.0006032075,0.043666285],"study_design_scores_gemma":[0.000022443823,0.00056394853,0.003037337,0.0000048525485,0.000040807437,0.000042143776,0.00004044317,0.94013846,0.054943603,0.0003418476,0.00080640154,0.00001780789],"about_ca_topic_score_codex":0.0016593222,"about_ca_topic_score_gemma":0.0029816963,"teacher_disagreement_score":0.0016593222,"about_ca_system_score_codex":0.0005296246,"about_ca_system_score_gemma":0.00040112447,"threshold_uncertainty_score":0.0038526654},"labels":[],"label_agreement":null},{"id":"W2950738454","doi":"10.1139/tcsme-2019-0038","title":"Multiple performance characteristics optimization in end milling of thin-walled parts using desirability function","year":2019,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Flatness (cosmology); Surface roughness; Mechanical engineering; Surface finish; Materials science; Engineering drawing; Engineering; Composite material","score_opus":0.011819719576693276,"score_gpt":0.19123229208335657,"score_spread":0.1794125725066633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950738454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5366001,0.00040011102,0.45923844,0.0000511998,0.00001060629,0.00010273222,0.000019052271,0.00028750574,0.0032901706],"genre_scores_gemma":[0.914506,0.00011739834,0.08390157,0.000017125305,0.000004430879,0.00008150058,0.0000550205,0.00006524655,0.001251745],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994242,0.00018764898,0.000024498946,0.000087050015,0.0002252228,0.000051442606],"domain_scores_gemma":[0.9990067,0.000611818,0.0001283249,0.000043962722,0.00018276951,0.000026350539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014947727,0.0009793008,0.0007529158,0.0007859224,0.00025703755,0.00063054956,0.0005059111,0.0004895768,0.0005394264],"category_scores_gemma":[0.001817116,0.0003541317,0.000710624,0.00032804746,0.00027731012,0.0004489736,0.0003658923,0.00043643484,0.00015089597],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042732674,0.00036148482,0.0032660826,0.000191536,0.000097257245,0.00013053177,0.00015569094,0.7806685,0.097591,0.0016030922,0.00021039204,0.11529704],"study_design_scores_gemma":[0.00001987538,0.000706908,0.002889381,0.00000851168,0.00003245128,0.000046338344,0.000022756722,0.9763797,0.019063527,0.00039931826,0.00041267884,0.00001863421],"about_ca_topic_score_codex":0.0008908844,"about_ca_topic_score_gemma":0.00075647497,"teacher_disagreement_score":0.0014947727,"about_ca_system_score_codex":0.0004176893,"about_ca_system_score_gemma":0.0004042384,"threshold_uncertainty_score":0.007905245},"labels":[],"label_agreement":null},{"id":"W2950966453","doi":"10.1007/s11837-019-03584-8","title":"Nonlinearity of Material Loss Versus the Wearing Force","year":2019,"lang":"en","type":"article","venue":"JOM","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear system; Materials science; Composite material; Mechanics; Structural engineering; Forensic engineering; Physics; Engineering","score_opus":0.005739760477401325,"score_gpt":0.21781963120395662,"score_spread":0.2120798707265553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950966453","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74133545,0.00093857874,0.18593885,0.0016535623,0.0001598422,0.00008057985,0.0005767876,0.0011409782,0.06817531],"genre_scores_gemma":[0.984495,0.00018597457,0.0033841932,0.00007935044,0.000020050116,0.00003020835,0.00006527132,0.00012395573,0.011616048],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996209,0.000079884354,0.000011129916,0.00008319884,0.00012356212,0.00008131518],"domain_scores_gemma":[0.9975096,0.001615315,0.00030648135,0.00022051351,0.00026905493,0.00007897009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006631691,0.0004699673,0.00035895524,0.00046105767,0.0002233497,0.0005897692,0.0005808519,0.0010108198,0.0064038606],"category_scores_gemma":[0.0047461004,0.00028523145,0.0002550096,0.0003597766,0.0010603641,0.0014615804,0.00067105656,0.00067080493,0.0016306815],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013990301,0.00033460718,0.007887375,0.0009090277,0.00006160043,0.0009090138,0.0011809081,0.5246382,0.36877418,0.03527982,0.002499589,0.056126658],"study_design_scores_gemma":[0.00002064745,0.00026428082,0.011712944,0.0000951616,0.000027364205,0.0007946687,0.00023339564,0.8970993,0.08025759,0.006589345,0.002833134,0.00007206854],"about_ca_topic_score_codex":0.001047918,"about_ca_topic_score_gemma":0.0009885324,"teacher_disagreement_score":0.0064038606,"about_ca_system_score_codex":0.0005320756,"about_ca_system_score_gemma":0.0005047122,"threshold_uncertainty_score":0.021423042},"labels":[],"label_agreement":null},{"id":"W2952469025","doi":"10.1109/tmech.2019.2906904","title":"Development of a Three-Degree-of-Freedom Ultrasonic Vibration Tool Holder for Milling and Drilling","year":2019,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Vibration; Actuator; Acoustics; Ultrasonic sensor; Ultrasonic machining; Natural frequency; Metalworking; Piezoelectricity; Drilling; Amplitude; Materials science; Mechanical engineering; Engineering; Optics; Physics; Electrical engineering","score_opus":0.01876744279076912,"score_gpt":0.22688530347691468,"score_spread":0.20811786068614557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952469025","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15762444,0.0011074853,0.8362606,0.00018916959,0.00030131845,0.0003150993,0.000250658,0.0017897421,0.0021615243],"genre_scores_gemma":[0.32663786,0.0005198577,0.6693819,0.000087410976,0.00006426506,0.00021230652,0.0002982682,0.00010389917,0.002694229],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99939454,0.000025226796,0.000037825514,0.00009625923,0.0003937718,0.00005239886],"domain_scores_gemma":[0.99942315,0.00012350785,0.00013056456,0.00007664361,0.0001502627,0.00009591029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005583756,0.00041384815,0.00047294956,0.0003964911,0.00019908533,0.00029250066,0.0014915131,0.0006432082,0.0015105054],"category_scores_gemma":[0.00072215335,0.00038852476,0.00033269753,0.00019871136,0.00026376842,0.0006521555,0.0005302691,0.00065177307,0.00071481575],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004904484,0.00003668717,0.00059086335,0.00013890705,0.000006431302,0.00015780075,0.00004520636,0.0010336038,0.95728,0.0008552305,0.0003659401,0.03944026],"study_design_scores_gemma":[0.00009168654,0.0014149571,0.006054207,0.000039516788,0.000043737215,0.001661286,0.000056791243,0.055980265,0.90313745,0.00022917605,0.03119341,0.00009753645],"about_ca_topic_score_codex":0.00044888543,"about_ca_topic_score_gemma":0.000567926,"teacher_disagreement_score":0.0015105054,"about_ca_system_score_codex":0.00019079934,"about_ca_system_score_gemma":0.00047261897,"threshold_uncertainty_score":0.005053103},"labels":[],"label_agreement":null},{"id":"W2953956978","doi":"10.1007/s00170-019-04010-8","title":"Improving the cutting rate in turning operations of flexible stepped shafts with a linear parameter-varying controller using the electromagnetic actuator","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Actuator; Control theory (sociology); Controller (irrigation); Engineering; Vibration; Process (computing); Work (physics); Stability (learning theory); Range (aeronautics); Machine tool; Cutting tool; Mechanical engineering; Control engineering; Computer science; Control (management); Acoustics","score_opus":0.005967778737789144,"score_gpt":0.2368573968686888,"score_spread":0.23088961813089967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953956978","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9215678,0.00034097306,0.07681434,0.000033180644,0.000031638374,0.000023835659,0.000012682453,0.00014176738,0.0010337997],"genre_scores_gemma":[0.99303484,0.000038941194,0.006696975,0.000004318118,0.0000022660963,0.000003873162,0.0000055707883,0.00000521448,0.0002081606],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989986,0.000015838434,0.000006700929,0.000019964378,0.000045656878,0.000011984871],"domain_scores_gemma":[0.99973255,0.0001313582,0.000043421736,0.000021710648,0.000057121608,0.000013842201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023511227,0.0002046573,0.00016227078,0.00017643196,0.0001407205,0.00020175416,0.00027607314,0.00021890875,0.00035959334],"category_scores_gemma":[0.00048713453,0.00011292447,0.00014510528,0.00013876628,0.00015063002,0.00017361944,0.000109991975,0.00018505134,0.000057303216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006278909,0.00010553929,0.0021133348,0.00016503871,0.00002227326,0.00009915596,0.00009367471,0.02621048,0.8898496,0.0004602363,0.0001451791,0.080107614],"study_design_scores_gemma":[0.00006481934,0.0015501371,0.012985157,0.00001190838,0.000049586077,0.0002478699,0.00005014093,0.3787808,0.60485613,0.0002017739,0.0011656643,0.00003594527],"about_ca_topic_score_codex":0.00039681498,"about_ca_topic_score_gemma":0.0005092761,"teacher_disagreement_score":0.00039681498,"about_ca_system_score_codex":0.000093387935,"about_ca_system_score_gemma":0.00012854626,"threshold_uncertainty_score":0.0012434125},"labels":[],"label_agreement":null},{"id":"W2954115956","doi":"10.7176/isde/10-5-01","title":"Optimization the Parameters of Hotwire Cutting Process to Enhance the Properties of Polystyrene Foam","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Innovation, Science and Economic Development Canada","keywords":"Taguchi methods; Orthogonal array; Polystyrene; Design of experiments; Materials science; Process (computing); Expanded polystyrene; Composite material; Noise (video); Statistical analysis; Computer science; Mathematics; Statistics; Polymer; Artificial intelligence","score_opus":0.00607236893603968,"score_gpt":0.2259937629166587,"score_spread":0.21992139398061902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954115956","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9113792,0.00462605,0.08030824,0.00010879458,0.0000986613,0.00025549292,0.00017883065,0.00020240316,0.0028422098],"genre_scores_gemma":[0.9415634,0.0022622356,0.054739874,0.000038186754,0.000017741222,0.00015850476,0.00017896584,0.00006174858,0.0009793272],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99939215,0.00008855388,0.00006995669,0.00008985341,0.00029147926,0.00006801457],"domain_scores_gemma":[0.9994537,0.00014534172,0.00016542256,0.000036971567,0.00017349514,0.000025082792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093969534,0.0007416762,0.00052841264,0.0006543735,0.0002468619,0.00060717075,0.000416178,0.00044179545,0.0010119568],"category_scores_gemma":[0.0011937198,0.00022606009,0.00038151917,0.0005582304,0.00022500943,0.00061363744,0.00025321526,0.00048477814,0.00031253684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002831507,0.00027997233,0.0018255992,0.0007729329,0.000028745766,0.00010762359,0.000120332166,0.0034744272,0.96227664,0.00026842812,0.0001988985,0.030363321],"study_design_scores_gemma":[0.00002441721,0.001189073,0.0061866487,0.000045871864,0.000106914864,0.00012777132,0.00011053553,0.00797327,0.98126054,0.00013487377,0.0028061976,0.00003389425],"about_ca_topic_score_codex":0.00048775758,"about_ca_topic_score_gemma":0.0011419094,"teacher_disagreement_score":0.0010119568,"about_ca_system_score_codex":0.00025578783,"about_ca_system_score_gemma":0.00050371664,"threshold_uncertainty_score":0.0049696565},"labels":[],"label_agreement":null},{"id":"W2954713279","doi":"10.3390/ma12122034","title":"Machinability of Rene 65 Superalloy","year":2019,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machinability; Superalloy; Materials science; Machining; Metallurgy; Microstructure; Tool wear; Drilling","score_opus":0.0019520432179326382,"score_gpt":0.17546622192218844,"score_spread":0.1735141787042558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954713279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99883014,0.00025028698,0.0003592619,0.000005378362,0.0000023389055,0.000007506801,0.00007979635,0.000017286326,0.00044807247],"genre_scores_gemma":[0.9982299,0.00008424026,0.00067202974,0.000003501211,7.659285e-7,0.000004572502,0.00012849957,0.0000119534625,0.00086462527],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999522,0.000035672674,0.000046511606,0.00009529675,0.00024094574,0.000059674836],"domain_scores_gemma":[0.99947363,0.0001168971,0.00014740707,0.00006268734,0.0001651662,0.00003434098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040862837,0.00031916102,0.0002724246,0.00036359043,0.00014741322,0.00032860806,0.00030883556,0.00026305616,0.0010468758],"category_scores_gemma":[0.0007367616,0.00020457458,0.00023384267,0.0002654557,0.0003189414,0.0002766217,0.0002443453,0.00021806567,0.00016216902],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020215848,0.000022710685,0.0021320225,0.00010306169,0.000015119665,0.00011186953,0.00018521724,0.00039670194,0.9934675,0.00004343847,0.000024282104,0.003295957],"study_design_scores_gemma":[0.000008038576,0.0012372189,0.031274505,0.00000765776,0.00002945879,0.0001722711,0.00018098936,0.001072466,0.96482486,0.000012564805,0.0011650884,0.000014849953],"about_ca_topic_score_codex":0.0015912456,"about_ca_topic_score_gemma":0.003248431,"teacher_disagreement_score":0.0015912456,"about_ca_system_score_codex":0.00022371372,"about_ca_system_score_gemma":0.0001500842,"threshold_uncertainty_score":0.0035021305},"labels":[],"label_agreement":null},{"id":"W2955239364","doi":"10.1016/j.wear.2019.202949","title":"A novel method of assessing and predicting coated cutting tool wear during Inconel DA 718 turning","year":2019,"lang":"en","type":"article","venue":"Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Inconel; Coating; Tool wear; Superalloy; Metallurgy; Flank; Carbide; Alloy; Composite material; Machining","score_opus":0.007897708145165792,"score_gpt":0.2542125996521584,"score_spread":0.24631489150699262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955239364","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42798284,0.0007791821,0.564088,0.000040553077,0.00014683913,0.00017952235,0.00047583188,0.0024914502,0.0038157634],"genre_scores_gemma":[0.8673044,0.00020529433,0.12898143,0.000022861506,0.00002098476,0.00008136356,0.000217143,0.000060227852,0.0031063608],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996093,0.000029208986,0.00001623308,0.00007470465,0.0002444167,0.000026245512],"domain_scores_gemma":[0.9991737,0.0002130562,0.00009612798,0.000081751765,0.00040741538,0.000027945265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003192596,0.00065219495,0.00067186286,0.00112589,0.00035068474,0.0005677544,0.00055121916,0.00067668816,0.0007746325],"category_scores_gemma":[0.000669532,0.0003262824,0.00025418476,0.00060058245,0.00017812365,0.00032707752,0.00026558,0.0003707436,0.00025504266],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083191704,0.00041105424,0.034937598,0.0004869812,0.000149287,0.0002210512,0.00027803084,0.03480862,0.5350226,0.00045179846,0.0013695785,0.39103147],"study_design_scores_gemma":[0.000055201206,0.001126221,0.054215223,0.000033919918,0.000117359516,0.00076575973,0.00014338682,0.691349,0.24863304,0.0001791872,0.0032719062,0.000109735796],"about_ca_topic_score_codex":0.0026904778,"about_ca_topic_score_gemma":0.007937578,"teacher_disagreement_score":0.0026904778,"about_ca_system_score_codex":0.0002549131,"about_ca_system_score_gemma":0.0004446899,"threshold_uncertainty_score":0.0053496957},"labels":[],"label_agreement":null},{"id":"W2955306689","doi":"10.1109/lra.2019.2926666","title":"Intelligent Machining Monitoring Using Sound Signal Processed With the Wavelet Method and a Self-Organizing Neural Network","year":2019,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"SIGNAL (programming language); Wavelet; Computer science; Artificial neural network; Waviness; Artificial intelligence; Microphone; Pattern recognition (psychology); Acoustics; Engineering; Sound pressure","score_opus":0.010748041303294367,"score_gpt":0.23624830294129234,"score_spread":0.22550026163799797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955306689","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07082054,0.00022035942,0.927575,0.000045065455,0.00003948721,0.00006963704,0.00002649317,0.00045859316,0.000744783],"genre_scores_gemma":[0.69357955,0.00023543352,0.30484387,0.000043720567,0.000028993014,0.00017597576,0.000064681764,0.000019708847,0.0010080099],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997688,0.000038012713,0.000017878427,0.000058817604,0.00010036921,0.000016207545],"domain_scores_gemma":[0.9997495,0.000078685465,0.00004422657,0.0000213391,0.00009673006,0.000009474065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004415321,0.00042742115,0.000378908,0.0006054934,0.0001570126,0.0003718382,0.00046986385,0.00051140384,0.00028781258],"category_scores_gemma":[0.0007216195,0.00023903963,0.00038160646,0.00045881406,0.00024888891,0.0005674001,0.00025141562,0.0003373731,0.00008230418],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029369126,0.00028489158,0.0046337917,0.00037183403,0.00016002543,0.00025539176,0.00021584157,0.2745952,0.2041353,0.0035730365,0.0006226395,0.51085836],"study_design_scores_gemma":[0.000008721476,0.00015734098,0.0018453288,0.000007718742,0.00002127154,0.00005496243,0.000015309675,0.97702616,0.019842789,0.00062016613,0.00038516705,0.000015073443],"about_ca_topic_score_codex":0.0006417175,"about_ca_topic_score_gemma":0.0007898483,"teacher_disagreement_score":0.0006417175,"about_ca_system_score_codex":0.00021853107,"about_ca_system_score_gemma":0.00022713278,"threshold_uncertainty_score":0.0023350716},"labels":[],"label_agreement":null},{"id":"W2955540682","doi":"10.1016/j.procir.2019.04.235","title":"Effect of axial vibrations on regenerative chatter in robotic milling","year":2019,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vibration; Engineering; Mechanical engineering; Regenerative medicine; Materials science; Computer science; Control engineering; Structural engineering; Acoustics; Physics; Chemistry","score_opus":0.0037299365526223295,"score_gpt":0.2197567218520342,"score_spread":0.21602678529941188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955540682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73500663,0.00077353365,0.2577677,0.00015416105,0.00005555479,0.00003344032,0.00002384806,0.00032884144,0.005856312],"genre_scores_gemma":[0.9980556,0.000043915003,0.0015709576,0.000005998094,0.000003560246,0.0000039113247,0.000002338666,0.000006752604,0.00030706255],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995497,0.00017886948,0.000021559334,0.000046137513,0.00016283068,0.00004084124],"domain_scores_gemma":[0.9968664,0.0025027394,0.000295848,0.00011115418,0.00016726655,0.000056439407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009634661,0.00043306616,0.00036377576,0.00036044637,0.00033837243,0.00041311266,0.00041034733,0.0006768897,0.00093771884],"category_scores_gemma":[0.0032309946,0.00019677314,0.00028174435,0.00013643164,0.0010271501,0.00040500815,0.0005240783,0.0003949909,0.00009923502],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010413524,0.00009982958,0.0045328424,0.00045616328,0.00006842192,0.0018692763,0.0009522967,0.8340805,0.11906176,0.008377691,0.0002727317,0.029187117],"study_design_scores_gemma":[0.000012704068,0.0002132702,0.002081342,0.000021474383,0.000019749275,0.00020769224,0.00007498957,0.98396885,0.011989175,0.0012056475,0.00018637591,0.000018799761],"about_ca_topic_score_codex":0.0011633326,"about_ca_topic_score_gemma":0.00086323346,"teacher_disagreement_score":0.0011633326,"about_ca_system_score_codex":0.0002928455,"about_ca_system_score_gemma":0.00015895495,"threshold_uncertainty_score":0.0050953627},"labels":[],"label_agreement":null},{"id":"W2955724619","doi":"10.2495/safe-v9-n2-121-136","title":"Analytical models for machine tool motion behavior assessment bench mark subjected to great earthquake","year":2019,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Motion (physics); Engineering; Forensic engineering; Computer science; Artificial intelligence","score_opus":0.006121630008462713,"score_gpt":0.24651599361651524,"score_spread":0.24039436360805252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955724619","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24839613,0.00084589625,0.72888047,0.00026020684,0.000088382454,0.00015407163,0.00026905714,0.0007382997,0.020367416],"genre_scores_gemma":[0.9858607,0.00027804993,0.009123882,0.000014606976,0.000009543381,0.00008782342,0.00007180713,0.000026267797,0.0045274002],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988186,0.000027109434,0.0000066078405,0.000021799875,0.000044099623,0.000018515451],"domain_scores_gemma":[0.99973315,0.0001150047,0.000052776057,0.000020724166,0.00007061638,0.000007648478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026308527,0.00048070552,0.00033911242,0.000435544,0.0002226039,0.00048390627,0.0007022598,0.0009033375,0.0016776419],"category_scores_gemma":[0.00095399877,0.00023391981,0.00047690375,0.00023062149,0.0003473804,0.0003743682,0.00032640932,0.00039450303,0.0003591575],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002008,0.000021111924,0.0006422558,0.000052892152,0.000007777413,0.000098071905,0.000073711686,0.9837149,0.007567129,0.002621431,0.00019744074,0.004983137],"study_design_scores_gemma":[0.0000010658092,0.000011395279,0.00017948837,0.0000027429116,0.0000022281265,0.000007896765,0.000009153518,0.99891484,0.00043314014,0.00023355732,0.0002023845,0.0000021691699],"about_ca_topic_score_codex":0.0040233033,"about_ca_topic_score_gemma":0.0026141775,"teacher_disagreement_score":0.0040233033,"about_ca_system_score_codex":0.0003829355,"about_ca_system_score_gemma":0.0004156869,"threshold_uncertainty_score":0.007999778},"labels":[],"label_agreement":null},{"id":"W2956084971","doi":"10.3390/ma12132174","title":"Machinability of Luxury Vinyl Tiles during Plain Milling Using a Helical Cutter","year":2019,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Doctorate Fellowship Foundation of Nanjing Forestry University; National Natural Science Foundation of China","keywords":"Helix angle; Machinability; Surface roughness; Materials science; Machining; Surface finish; Diamond tool; Helix (gastropod); Drilling; Composite material; Geometry; Diamond cutting; Surface (topology); Diamond turning; Metallurgy; Geology; Mathematics","score_opus":0.004902285531222763,"score_gpt":0.2110386511459775,"score_spread":0.20613636561475474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2956084971","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99877506,0.000056752007,0.00092318037,0.0000039603137,0.0000023889522,0.000003980765,0.000018792787,0.000010906334,0.00020485303],"genre_scores_gemma":[0.99822885,0.000032283242,0.0012088541,0.0000029709122,0.0000010617123,0.000002693976,0.000027314214,0.0000058753867,0.00049014704],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998497,0.000014739906,0.000010193397,0.00003288549,0.000053075888,0.00003940024],"domain_scores_gemma":[0.9995944,0.00015028629,0.000108780514,0.00005462603,0.00005827646,0.000033593453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003332651,0.00019463453,0.00024605778,0.0001865407,0.00016193028,0.00030782376,0.00016495043,0.0002095074,0.0008661213],"category_scores_gemma":[0.0006814828,0.00018002713,0.00020843564,0.00019917951,0.00026577633,0.00020977367,0.00015026907,0.00018818083,0.00011125942],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029377823,0.000013691152,0.0010549955,0.000031683296,0.000004412763,0.00009104349,0.00007825182,0.0011311268,0.99504685,0.000031942727,0.000019232511,0.0022029385],"study_design_scores_gemma":[0.000024801344,0.00094539276,0.031035827,0.0000052206383,0.000016416874,0.00014244326,0.00015160823,0.008968547,0.95816946,0.000053215634,0.00046916975,0.000017877117],"about_ca_topic_score_codex":0.0006437396,"about_ca_topic_score_gemma":0.0010818683,"teacher_disagreement_score":0.0008661213,"about_ca_system_score_codex":0.00015154947,"about_ca_system_score_gemma":0.000095517506,"threshold_uncertainty_score":0.0028974414},"labels":[],"label_agreement":null},{"id":"W2962848625","doi":"10.3390/jmmp3030061","title":"Sustainability Assessment during Machining Ti-6Al-4V with Nano-Additives-Based Minimum Quantity Lubrication","year":2019,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; Ontario Tech University","funders":"","keywords":"Lubrication; Machining; Sustainability; Nanofluid; Process (computing); Materials science; Mechanical engineering; Tool wear; Process engineering; Manufacturing engineering; Metallurgy; Computer science; Engineering; Nanotechnology; Nanoparticle","score_opus":0.0038192399513501266,"score_gpt":0.23227526545888694,"score_spread":0.2284560255075368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2962848625","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9862818,0.0002868808,0.012710982,0.000021376774,0.0000034726615,0.000016889871,0.000024747147,0.000034514735,0.000619292],"genre_scores_gemma":[0.99650925,0.0000994724,0.0031807057,0.0000031237653,5.984819e-7,0.0000064855426,0.00002441317,0.000003936307,0.00017206346],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99968255,0.00006005366,0.000016469114,0.000037207992,0.00016107573,0.00004265738],"domain_scores_gemma":[0.9997408,0.00009013378,0.0000593513,0.000014483481,0.000082816696,0.000012398874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005836819,0.00024988377,0.00027482468,0.00039611742,0.0001728863,0.0004729263,0.00029120204,0.0003666862,0.00022412126],"category_scores_gemma":[0.00064919033,0.00013262825,0.00033149755,0.00020224799,0.0002940631,0.00042970423,0.0003716507,0.00017266998,0.000046174973],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006093915,0.00016563137,0.031872172,0.00065896334,0.000065346154,0.00034625985,0.000556082,0.15356818,0.7518666,0.0011532368,0.00011435471,0.05902381],"study_design_scores_gemma":[0.000017485336,0.0016754614,0.025377259,0.000029708914,0.00006502739,0.00019140776,0.00063684984,0.2774086,0.69162714,0.0013823534,0.0015474176,0.000041297753],"about_ca_topic_score_codex":0.0009692439,"about_ca_topic_score_gemma":0.0019830198,"teacher_disagreement_score":0.0009692439,"about_ca_system_score_codex":0.00041847062,"about_ca_system_score_gemma":0.00032488527,"threshold_uncertainty_score":0.0030868053},"labels":[],"label_agreement":null},{"id":"W2963004637","doi":"10.1007/s00170-019-04048-8","title":"Force coefficient prediction for drilling of UD-CFRP based on FEM simulation of orthogonal cutting","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"China National Funds for Distinguished Young Scientists; University of British Columbia; National Natural Science Foundation of China","keywords":"Thrust; Drilling; Torque; Finite element method; Rake angle; Machining; Fiber; Mechanical engineering; Orthogonal array; Matrix (chemical analysis); Structural engineering; Materials science; Engineering; Taguchi methods; Composite material; Physics","score_opus":0.005707186907208327,"score_gpt":0.2430299738690899,"score_spread":0.23732278696188155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963004637","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9106137,0.0003568943,0.07053021,0.0001144861,0.00006684,0.000045701792,0.00037910746,0.00066075,0.017232375],"genre_scores_gemma":[0.994107,0.000049528393,0.0050808373,0.000006502507,0.0000018505544,0.000009756281,0.00006258259,0.000017694907,0.0006642099],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989295,0.000012347891,0.000004284934,0.000016027221,0.000049429076,0.000024906229],"domain_scores_gemma":[0.9995995,0.00018455186,0.000044914497,0.000031260726,0.00012157821,0.000018174082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016949736,0.00033073177,0.00034654487,0.0004141102,0.00029170944,0.00032680974,0.00040524607,0.00077470444,0.0016594706],"category_scores_gemma":[0.00070130033,0.00024489014,0.0003595772,0.000370745,0.00031189003,0.00036329558,0.0002182839,0.00028174248,0.00020979467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018505433,0.000082821105,0.004918683,0.00016252542,0.000013938314,0.00024186698,0.00013428253,0.953629,0.022258064,0.0014265777,0.0009264377,0.01602074],"study_design_scores_gemma":[0.0000062369822,0.000034281005,0.0015744851,0.00000607435,0.0000036789215,0.000027232929,0.00002420616,0.99543566,0.0025116017,0.00008332131,0.0002860604,0.0000070801707],"about_ca_topic_score_codex":0.008805272,"about_ca_topic_score_gemma":0.006723903,"teacher_disagreement_score":0.008805272,"about_ca_system_score_codex":0.0002468381,"about_ca_system_score_gemma":0.0005122615,"threshold_uncertainty_score":0.01750803},"labels":[],"label_agreement":null},{"id":"W2963097579","doi":"","title":"Toward the quality prognostic of an aircraft engine workpiece in Inconel Alloy 625: case study and proposed system architecture","year":2019,"lang":"en","type":"preprint","venue":"Espace ÉTS (ETS)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Inconel 625; Architecture; Inconel; Alloy; Quality (philosophy); Computer science; Materials science; Metallurgy; Physics","score_opus":0.016327164887271407,"score_gpt":0.27359263186475047,"score_spread":0.25726546697747904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963097579","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35562325,0.00033063357,0.6333254,0.0005770511,0.000045760145,0.0002609266,0.00032794592,0.0056125484,0.003896466],"genre_scores_gemma":[0.9508064,0.000094865776,0.047024656,0.000027230923,0.000013418372,0.000034527533,0.00019133174,0.00002362786,0.0017840024],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999736,0.000037029436,0.00002350585,0.0000771172,0.00009135467,0.000034952405],"domain_scores_gemma":[0.9995745,0.000087667,0.000056772795,0.00005929662,0.00018645162,0.000035395748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069714186,0.0005964226,0.0006570516,0.00065666,0.0005318188,0.0011718079,0.0009377032,0.0009812836,0.0017340801],"category_scores_gemma":[0.0013380679,0.00021333378,0.00039368536,0.00046742804,0.00030834894,0.0005237255,0.0008439477,0.00035635196,0.00050011656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011961033,0.00031227389,0.023884444,0.00028591306,0.00009124461,0.0007800938,0.00046007193,0.56092626,0.08370497,0.0027552005,0.0019242223,0.3236793],"study_design_scores_gemma":[0.000023495315,0.00022001183,0.0045730993,0.000014806331,0.000035004643,0.00008336862,0.00007945157,0.9773094,0.016046368,0.0008286473,0.00077374035,0.00001261846],"about_ca_topic_score_codex":0.009195601,"about_ca_topic_score_gemma":0.006655665,"teacher_disagreement_score":0.009195601,"about_ca_system_score_codex":0.00065877876,"about_ca_system_score_gemma":0.0009968779,"threshold_uncertainty_score":0.018284142},"labels":[],"label_agreement":null},{"id":"W2963708853","doi":"","title":"ARX model for experimental vibration analysis of grinding process by flexible manipulator","year":2019,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Grinding; Vibration; Manipulator (device); Process (computing); Computer science; Control engineering; Control theory (sociology); Mechanical engineering; Engineering; Acoustics; Physics; Artificial intelligence; Robotic arm","score_opus":0.010241196748709809,"score_gpt":0.23848417550478887,"score_spread":0.22824297875607907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963708853","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035694145,0.0002909631,0.9602242,0.00007002567,0.000038651277,0.00005687799,0.000159896,0.0006213384,0.0028438848],"genre_scores_gemma":[0.9345473,0.0004098215,0.054636616,0.00004198217,0.000026747379,0.0003969517,0.00056157546,0.00010741543,0.009271472],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947685,0.00013756719,0.000024928435,0.00014646366,0.00017117965,0.000043069806],"domain_scores_gemma":[0.99956805,0.00025283557,0.00005819628,0.0000367358,0.00007562964,0.000008582757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007839499,0.0008775222,0.0005672962,0.0003154733,0.00023916022,0.000547663,0.0009091707,0.0011692179,0.0028769115],"category_scores_gemma":[0.0009985599,0.00030733203,0.0008589947,0.00031249394,0.00040515588,0.00043574334,0.00037235697,0.0010748969,0.00071968895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009934671,0.00006679352,0.0006015724,0.00017355199,0.000039357023,0.00013252602,0.00010766555,0.9600902,0.018500464,0.0033973448,0.00032246023,0.016468698],"study_design_scores_gemma":[0.000004109157,0.000042695294,0.00034573348,0.0000033017532,0.0000046277,0.000013099637,0.000006436418,0.9979219,0.0010670492,0.00029886627,0.00028739305,0.0000048841353],"about_ca_topic_score_codex":0.004693966,"about_ca_topic_score_gemma":0.0028359771,"teacher_disagreement_score":0.004693966,"about_ca_system_score_codex":0.00035511077,"about_ca_system_score_gemma":0.0004108448,"threshold_uncertainty_score":0.009624243},"labels":[],"label_agreement":null},{"id":"W2963904467","doi":"10.1007/s00170-019-04064-8","title":"Geometrical theory of cutting stock with torus end mills in five-axis CNC machining and its applications in machining simulation","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Aeronautical Science Foundation of China; National Natural Science Foundation of China","keywords":"Machining; Torus; Mechanical engineering; Numerical control; Engineering; Engineering drawing; Industrial and production engineering; Stock (firearms); Manufacturing engineering; Geometry; Mathematics","score_opus":0.0054912848581230725,"score_gpt":0.242741748798107,"score_spread":0.23725046393998392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963904467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.057596173,0.0004945137,0.89973265,0.0003439936,0.00016953042,0.000097723176,0.00015993626,0.00018921398,0.041216217],"genre_scores_gemma":[0.90512216,0.0005919778,0.07721803,0.00011540739,0.000067323985,0.00017914733,0.00018866699,0.00016308752,0.016354153],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965227,0.00008636577,0.000017932502,0.000059620947,0.00014766096,0.000036248042],"domain_scores_gemma":[0.9996277,0.00013662846,0.00006285996,0.000028118828,0.000115457835,0.000029173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056364044,0.0005582085,0.0007533335,0.0010924771,0.0008359135,0.0014345278,0.0017966443,0.0017118346,0.004561742],"category_scores_gemma":[0.0012530431,0.0006586572,0.0008420391,0.0010392324,0.0015172672,0.0013096874,0.00080009125,0.0007584344,0.00053478585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013636944,0.000018347417,0.00029029386,0.000029936498,0.000007483383,0.00007341703,0.000036251055,0.93553144,0.00092360046,0.060261827,0.00028125837,0.0025325676],"study_design_scores_gemma":[0.0000033963927,0.000009213177,0.000119894234,0.000003075137,0.0000025346656,0.000022176891,0.000010675006,0.99087673,0.00017142671,0.008342394,0.00043333377,0.000005186373],"about_ca_topic_score_codex":0.0067562344,"about_ca_topic_score_gemma":0.003908037,"teacher_disagreement_score":0.0067562344,"about_ca_system_score_codex":0.0011821509,"about_ca_system_score_gemma":0.0012176967,"threshold_uncertainty_score":0.015260577},"labels":[],"label_agreement":null},{"id":"W2964945510","doi":"10.18280/jesa.520211","title":"Prediction of Surface Roughness for CNC Turning of EN8 Steel Bar Using Artificial Neural Network Model","year":2019,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Surface roughness; Bar (unit); Surface (topology); Surface finish; Materials science; Mechanical engineering; Engineering; Computer science; Metallurgy; Artificial intelligence; Geology; Composite material; Mathematics; Geometry","score_opus":0.029239192087014955,"score_gpt":0.25342538576940943,"score_spread":0.22418619368239448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964945510","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8947093,0.00033609767,0.1010266,0.000091484406,0.00005319714,0.000043249547,0.00026002346,0.0004568095,0.0030233376],"genre_scores_gemma":[0.9935656,0.000077236065,0.0052497066,0.000009601936,0.000002538632,0.000023787377,0.00017800239,0.00000753143,0.0008859683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988127,0.00001727164,0.000009337465,0.00003374745,0.000037652742,0.000020728225],"domain_scores_gemma":[0.99975294,0.00012423212,0.000027898071,0.000012420991,0.000074881595,0.0000076320375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024311693,0.00048605775,0.00037626806,0.00040968577,0.00015131194,0.00036932863,0.00034329295,0.00063779793,0.00097231974],"category_scores_gemma":[0.0005924312,0.00021677234,0.0005457092,0.00022009686,0.00012965246,0.00020784326,0.00013551522,0.00037822122,0.00019837741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015271234,0.000092230526,0.0061794403,0.000091096386,0.000033104057,0.00009318262,0.00002727546,0.95419794,0.013816168,0.00009842864,0.00033018013,0.024888225],"study_design_scores_gemma":[0.0000017667824,0.00003200992,0.0021231507,0.000002303897,0.0000042240545,0.0000054722323,0.000005198303,0.99646133,0.0012995759,0.000024068593,0.00003745888,0.0000035195285],"about_ca_topic_score_codex":0.00978274,"about_ca_topic_score_gemma":0.009433255,"teacher_disagreement_score":0.00978274,"about_ca_system_score_codex":0.00036394832,"about_ca_system_score_gemma":0.00026643698,"threshold_uncertainty_score":0.019451559},"labels":[],"label_agreement":null},{"id":"W2966438060","doi":"10.3390/jmmp3030063","title":"An Investigation into Tool Wear and Hole Quality during Low-Frequency Vibration-Assisted Drilling of CFRP/Ti6Al4V Stack","year":2019,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"","keywords":"Drilling; Delamination (geology); Tool wear; Vibration; Machining; Chip formation; Thrust; Materials science; Mechanism (biology); Chip; Mechanical engineering; Stack (abstract data type); Aerospace; Deep hole drilling; Structural engineering; Engineering; Acoustics; Computer science; Geology; Aerospace engineering","score_opus":0.007426493945150559,"score_gpt":0.24259437681191906,"score_spread":0.2351678828667685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966438060","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983034,0.00016738981,0.0013587894,0.0000062129425,0.000004505508,0.0000067832516,0.00003354885,0.000018909981,0.00010033361],"genre_scores_gemma":[0.9988875,0.000054741082,0.0007494463,0.000004515369,0.0000018210849,0.0000034701154,0.00003712738,0.0000068149347,0.000254614],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996908,0.00003097765,0.00001889569,0.00005040306,0.0001645764,0.000044400953],"domain_scores_gemma":[0.99855834,0.0005037803,0.00033667337,0.00013510711,0.00041522912,0.000050879564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036813243,0.00022672278,0.00030441413,0.0002881102,0.00020772636,0.00023053463,0.0002420756,0.00037398507,0.0005697689],"category_scores_gemma":[0.0011629659,0.00019361298,0.000238521,0.00018540828,0.00029169247,0.0003307469,0.00015065199,0.00024225317,0.0000843822],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006603094,0.00007326021,0.006632441,0.00018976464,0.000021360864,0.00034786353,0.00046930576,0.0011742747,0.9756918,0.00003153302,0.00006621999,0.0146418875],"study_design_scores_gemma":[0.000024305931,0.0044948272,0.1050592,0.00002250183,0.00006710596,0.0008539201,0.0005965034,0.011631901,0.8762408,0.000054562483,0.0009058229,0.000048571383],"about_ca_topic_score_codex":0.0004931239,"about_ca_topic_score_gemma":0.0010549076,"teacher_disagreement_score":0.0005697689,"about_ca_system_score_codex":0.00010593526,"about_ca_system_score_gemma":0.000065753695,"threshold_uncertainty_score":0.0019469261},"labels":[],"label_agreement":null},{"id":"W2967780342","doi":"10.1007/s00170-019-04248-2","title":"Elimination of delamination and burr formation using high-frequency vibration-assisted drilling of hybrid CFRP/Ti6Al4V stacked material","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"","keywords":"Delamination (geology); Surface integrity; Drilling; Materials science; Residual stress; Thrust; Machining; Titanium alloy; Vibration; Chip formation; Structural engineering; Composite material; Tool wear; Mechanical engineering; Metallurgy; Alloy; Engineering; Acoustics; Geology","score_opus":0.004985302949327813,"score_gpt":0.21813682069333976,"score_spread":0.21315151774401195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967780342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98887664,0.00022462412,0.009946801,0.000012994439,0.000031808562,0.000005213247,0.000031098814,0.00011673445,0.0007540883],"genre_scores_gemma":[0.99323916,0.000037373313,0.006196423,0.000004834181,0.0000031408379,0.0000030344222,0.00002733651,0.000009246352,0.00047939908],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998883,0.0000064062656,0.000005907123,0.000020795651,0.00005291933,0.000025627725],"domain_scores_gemma":[0.9998018,0.000021733555,0.0000644779,0.000032664222,0.000059647384,0.00001977076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012394163,0.0003021346,0.00019204979,0.00024517562,0.00014505562,0.00018796725,0.00033932476,0.00029484942,0.0007663257],"category_scores_gemma":[0.00016991468,0.0001686338,0.00022327094,0.00012792509,0.00017872847,0.00027954974,0.0002405777,0.00020867189,0.00012023618],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013266235,0.000018740093,0.0003428666,0.00007065972,0.000008630853,0.00007558692,0.000034723573,0.0014960767,0.9905563,0.00015000305,0.000063007785,0.0070508164],"study_design_scores_gemma":[0.000017919303,0.0007690418,0.0063879937,0.000009270931,0.000031713433,0.0003236146,0.00007517827,0.01355291,0.97759193,0.00006631005,0.001154801,0.000019311356],"about_ca_topic_score_codex":0.00024471298,"about_ca_topic_score_gemma":0.0008332894,"teacher_disagreement_score":0.0007663257,"about_ca_system_score_codex":0.00006620955,"about_ca_system_score_gemma":0.0001819468,"threshold_uncertainty_score":0.0025636554},"labels":[],"label_agreement":null},{"id":"W2969633391","doi":"10.1007/s10010-019-00352-7","title":"Online estimate and compensation of the gear machining error based on electronic gearbox cross-coupling controller","year":2019,"lang":"en","type":"article","venue":"Forschung im Ingenieurwesen","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Environment and Climate Change Canada; National Natural Science Foundation of China","keywords":"Hobbing; Compensation (psychology); Machining; Controller (irrigation); Linkage (software); Non-circular gear; Coupling (piping); Process (computing); Computer science; Spiral bevel gear; Numerical control; Engineering; Control theory (sociology); Automotive engineering; Mechanical engineering; Control (management); Artificial intelligence","score_opus":0.006659618505482241,"score_gpt":0.259301601180154,"score_spread":0.25264198267467175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969633391","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09976063,0.00058936025,0.89502925,0.00009332142,0.00019751058,0.000074512245,0.000048588245,0.0010241546,0.0031826957],"genre_scores_gemma":[0.9117162,0.00019806263,0.084842734,0.00007751342,0.000053713997,0.00007143323,0.000104015344,0.000033218457,0.0029032321],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99958473,0.000032039625,0.000022892275,0.00012349627,0.00019950769,0.000037393373],"domain_scores_gemma":[0.9995546,0.00012640709,0.000053720654,0.00004960598,0.00019301783,0.000022584316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000419901,0.00065358414,0.0009054206,0.0005456429,0.0003453462,0.00068240886,0.0006146201,0.00062831107,0.0019017372],"category_scores_gemma":[0.0011768709,0.00032016027,0.00026521992,0.00025734972,0.00022537271,0.0006203649,0.0006321923,0.00056260265,0.0004095337],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010791244,0.00038479714,0.0054829745,0.00047531855,0.00018474789,0.0003082856,0.00022818193,0.21252637,0.16207017,0.003059669,0.002936995,0.6112634],"study_design_scores_gemma":[0.00004476402,0.00016572904,0.00404325,0.000016447799,0.000033913428,0.000101405276,0.000018130371,0.97697383,0.017277295,0.00037631652,0.0009264783,0.000022464586],"about_ca_topic_score_codex":0.002364706,"about_ca_topic_score_gemma":0.003449699,"teacher_disagreement_score":0.002364706,"about_ca_system_score_codex":0.00022810897,"about_ca_system_score_gemma":0.00058297947,"threshold_uncertainty_score":0.0063619614},"labels":[],"label_agreement":null},{"id":"W2969738331","doi":"10.1007/s00170-019-04210-2","title":"Influence of process parameters on the cutting performance of SiAlON ceramic tools during high-speed dry face milling of hardened Inconel 718","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Machinability; Inconel; Sialon; Superalloy; Tool wear; Ceramic; Enhanced Data Rates for GSM Evolution; Machining; Chip formation; Metallurgy; Cutting tool; Hardened steel; Composite material; Microstructure; Alloy; Engineering","score_opus":0.005475618901241777,"score_gpt":0.21844468929252103,"score_spread":0.21296907039127927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969738331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989397,0.00021621276,0.00045805605,0.000009265172,0.0000067698807,0.0000035240957,0.00003332538,0.000014652649,0.00031858752],"genre_scores_gemma":[0.999204,0.00006443794,0.00035929252,0.000004748046,0.0000023322775,0.0000021082633,0.00003560709,0.000011055173,0.00031654187],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977094,0.000023542118,0.000014628148,0.000048704354,0.000080251746,0.000061956045],"domain_scores_gemma":[0.9993017,0.0003818249,0.00012373606,0.000044154174,0.00011780972,0.000030726085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030995527,0.00026774794,0.00036387652,0.00019303198,0.00035538527,0.00048022124,0.0002499457,0.00036886137,0.0013486936],"category_scores_gemma":[0.00075582974,0.00022769242,0.00022209744,0.00023145592,0.00026787177,0.00038037973,0.00017724012,0.00032624352,0.00021824207],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013765526,0.0000539246,0.0013271277,0.0001479396,0.000019657879,0.0001470938,0.0002644022,0.0013989065,0.987773,0.000055881326,0.00010589849,0.007329637],"study_design_scores_gemma":[0.000031870026,0.0012591655,0.024270529,0.000010755391,0.00005320429,0.00011147787,0.00021654987,0.0050742407,0.96818113,0.000037977803,0.000721538,0.00003157166],"about_ca_topic_score_codex":0.00095553027,"about_ca_topic_score_gemma":0.0019779096,"teacher_disagreement_score":0.0013486936,"about_ca_system_score_codex":0.00021686267,"about_ca_system_score_gemma":0.00025497336,"threshold_uncertainty_score":0.004511893},"labels":[],"label_agreement":null},{"id":"W2971039213","doi":"","title":"Mechanistic cutting force model including the stress state induced by the chip flow contribution for cylindrical turning on Ti6Al4V alloy with two different nose radii","year":2016,"lang":"en","type":"preprint","venue":"SAM, the Arts et Métiers ParisTech open access repository (Paris Institute of Technology)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Safran Electronics (Canada)","funders":"Safran Aircraft Engines","keywords":"Titanium alloy; Alloy; Chip; Materials science; Stress (linguistics); Flow (mathematics); Mechanics; Mechanical engineering; Structural engineering; Metallurgy; Physics; Engineering; Electrical engineering","score_opus":0.0346262118481159,"score_gpt":0.33382071879689307,"score_spread":0.29919450694877714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971039213","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30129972,0.00091562414,0.6573228,0.0003526893,0.000110218236,0.0001196224,0.00037897984,0.0003327941,0.039167587],"genre_scores_gemma":[0.982563,0.00034948977,0.011098493,0.00003301144,0.000020623309,0.000078023295,0.00015553215,0.00003780264,0.005664087],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999151,0.000014334304,0.0000032189573,0.000012632727,0.000037510046,0.000017136766],"domain_scores_gemma":[0.9998815,0.000041572916,0.000024852581,0.000014622848,0.00002947486,0.000007916801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024924488,0.0004803698,0.00039454762,0.00039463447,0.0002086717,0.00039974492,0.0007919525,0.0011364628,0.0015989777],"category_scores_gemma":[0.00033841436,0.00023711383,0.0006645239,0.00020145446,0.00031881855,0.00033843712,0.00024163723,0.00034124168,0.00021204079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022211698,0.000031495754,0.00029690115,0.000047692014,0.0000089314335,0.00010357923,0.000025876068,0.97848445,0.010210349,0.0059338794,0.00019174936,0.0046427986],"study_design_scores_gemma":[0.0000029417486,0.000018944722,0.00025072595,0.0000019337238,0.000003486304,0.000022526849,0.0000037878133,0.99835455,0.0005777665,0.00050003035,0.00026005393,0.0000033579904],"about_ca_topic_score_codex":0.0018907747,"about_ca_topic_score_gemma":0.0024226785,"teacher_disagreement_score":0.0018907747,"about_ca_system_score_codex":0.00027637547,"about_ca_system_score_gemma":0.00042888435,"threshold_uncertainty_score":0.0053491592},"labels":[],"label_agreement":null},{"id":"W2971707246","doi":"10.3390/jmmp3030078","title":"Effect of Graphene on Machinability of Glass Fiber Reinforced Polymer (GFRP)","year":2019,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machinability; Materials science; Fibre-reinforced plastic; Composite material; Machining; Epoxy; Graphene; Surface roughness; Glass fiber; Surface finish; Diamond; Metallurgy; Nanotechnology","score_opus":0.003083603574130633,"score_gpt":0.21978508380317308,"score_spread":0.21670148022904245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971707246","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983621,0.00048797196,0.00037351126,0.00001637913,0.000013746217,0.000007475314,0.00005217488,0.000023230581,0.00066328177],"genre_scores_gemma":[0.9981359,0.00028510025,0.0009514795,0.000014218977,0.0000037790542,0.000005344121,0.00004134004,0.000013370085,0.0005494107],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99982053,0.00002704417,0.00001229905,0.00003695897,0.000069473426,0.00003376739],"domain_scores_gemma":[0.9996623,0.00011790878,0.000094416755,0.000034453824,0.00006259879,0.000028420027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015001038,0.00035788468,0.00013969307,0.00025008706,0.00013911286,0.00021046163,0.0001928493,0.00034077404,0.0010128533],"category_scores_gemma":[0.0004906763,0.00017135066,0.0002215995,0.00015653827,0.00014535566,0.00022739996,0.00016162546,0.00031967135,0.00013626716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014011476,0.00002337592,0.00020754851,0.00007644639,0.000011917264,0.000079283695,0.00004379363,0.00021615907,0.9972535,0.00002116821,0.000022829694,0.0019039075],"study_design_scores_gemma":[0.000003653283,0.00031715495,0.0030479457,0.0000054422185,0.000019442052,0.000035364745,0.00002043351,0.0005833536,0.99563307,0.000006065446,0.00032227786,0.000005665281],"about_ca_topic_score_codex":0.00037404263,"about_ca_topic_score_gemma":0.0012562297,"teacher_disagreement_score":0.0010128533,"about_ca_system_score_codex":0.000111409754,"about_ca_system_score_gemma":0.000048191625,"threshold_uncertainty_score":0.0033883452},"labels":[],"label_agreement":null},{"id":"W2974312079","doi":"10.1139/tcsme-2019-0051","title":"Tool wear morphology and life under various lubrication modes in turning stainless steel 316L","year":2019,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Lubrication; Machinability; Materials science; Machining; Metallurgy; Enhanced Data Rates for GSM Evolution; Tool wear; Mechanical engineering; Composite material; Engineering","score_opus":0.006656487138684549,"score_gpt":0.19558056318341843,"score_spread":0.18892407604473388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2974312079","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99927,0.0002384001,0.0002712569,0.0000047308677,0.000002726395,0.000003724927,0.000043312662,0.000012351384,0.00015339353],"genre_scores_gemma":[0.999252,0.00008045072,0.00026421048,0.0000042660754,0.0000014641938,0.0000036455965,0.000062178224,0.0000057803554,0.00032607073],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996599,0.000031512496,0.00002458764,0.000047452708,0.00016995429,0.000066705084],"domain_scores_gemma":[0.99948275,0.00010961184,0.00014451772,0.00004030764,0.00017627796,0.000046526908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023834029,0.0001806107,0.00026097574,0.0005376847,0.00019963506,0.00029248194,0.00021142887,0.00032251337,0.00063388405],"category_scores_gemma":[0.00072168285,0.00018283376,0.00020247781,0.0003239528,0.00033268926,0.0002688453,0.00017979297,0.00018091784,0.00014774827],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058150326,0.000031493997,0.005357148,0.00008390769,0.000010206492,0.00025277058,0.00044625005,0.0004608379,0.98752105,0.000032622702,0.00005735174,0.005164764],"study_design_scores_gemma":[0.000025440866,0.0027966679,0.17377439,0.000026730946,0.00004564083,0.0008684254,0.00090665504,0.005116166,0.8150152,0.000094644885,0.0012558192,0.00007422276],"about_ca_topic_score_codex":0.0012841773,"about_ca_topic_score_gemma":0.0020649778,"teacher_disagreement_score":0.0012841773,"about_ca_system_score_codex":0.00020034099,"about_ca_system_score_gemma":0.00010519739,"threshold_uncertainty_score":0.0025534034},"labels":[],"label_agreement":null},{"id":"W2975697703","doi":"10.1139/tcsme-2019-0110","title":"Initial tool wear behavior in high-speed turning of Inconel 718","year":2019,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Inconel; Superalloy; Materials science; Tool wear; Flank; Metallurgy; Mechanical engineering; Machining; Alloy; Engineering","score_opus":0.006853631882512544,"score_gpt":0.20918669379900476,"score_spread":0.20233306191649222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2975697703","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99929094,0.00016894203,0.00014737509,0.0000045688093,0.0000036396316,0.00000313446,0.00003887127,0.00001618479,0.00032631797],"genre_scores_gemma":[0.99931085,0.000039957693,0.00012611381,0.0000049310943,0.0000011141611,0.0000023375019,0.000050870007,0.0000037006191,0.00046009274],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971896,0.000017362321,0.00001169864,0.000044068685,0.00013100888,0.000076974145],"domain_scores_gemma":[0.99942243,0.00019348528,0.0000978657,0.000056815064,0.00018316845,0.000046304023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016881348,0.00019123628,0.00028798086,0.00057607837,0.0002482121,0.00023703945,0.00024473396,0.0003868254,0.0013856383],"category_scores_gemma":[0.00048347012,0.00017553539,0.00020470453,0.00028203326,0.0002627153,0.0001768257,0.0001432943,0.00021548048,0.00017343927],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011144788,0.000081183076,0.014946871,0.0002167024,0.000027934086,0.0011560868,0.00075113017,0.0015068841,0.96163243,0.000061272716,0.00032916135,0.01817587],"study_design_scores_gemma":[0.000029808914,0.0033028536,0.51800066,0.000055958866,0.000054027034,0.0014213941,0.0011396012,0.007963002,0.46541607,0.000083304156,0.0024669606,0.00006642143],"about_ca_topic_score_codex":0.0016900179,"about_ca_topic_score_gemma":0.0035167183,"teacher_disagreement_score":0.0016900179,"about_ca_system_score_codex":0.00013822995,"about_ca_system_score_gemma":0.000077709534,"threshold_uncertainty_score":0.0046353936},"labels":[],"label_agreement":null},{"id":"W2979826118","doi":"10.1115/1.4045129","title":"Effects of Ultrasonic Vibration Assistance on Chip Formation Mechanism in Cutting of Ti–6Al–4V","year":2019,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Chip; Vibration; Chip formation; Shear (geology); Shear stress; Ultrasonic sensor; Composite material; Finite element method; Mechanism (biology); Structural engineering; Acoustics; Engineering; Metallurgy; Machining; Tool wear","score_opus":0.002767490136388453,"score_gpt":0.18627678631781863,"score_spread":0.1835092961814302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979826118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961939,0.00016758818,0.0033321644,0.000013423359,0.000008221389,0.0000035261792,0.0000062981253,0.00002777663,0.0002471524],"genre_scores_gemma":[0.9986908,0.000039828803,0.0011402217,0.0000036937756,0.0000011911557,0.0000017227821,0.000005026741,0.0000035458115,0.000113935326],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999064,0.0000114573295,0.0000039768156,0.0000127525855,0.000034876914,0.000030514966],"domain_scores_gemma":[0.9997781,0.00010980831,0.00005292667,0.000018000987,0.000026366764,0.000014886669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001949856,0.0001679875,0.0001356687,0.00013219441,0.000114201095,0.00015719101,0.00019327307,0.00023008317,0.0006076632],"category_scores_gemma":[0.00037128135,0.00016758384,0.00016231892,0.0000660844,0.00025055127,0.00015572704,0.00018817042,0.00011689003,0.00006296391],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039448423,0.000031241187,0.0019914052,0.00009466845,0.00001417765,0.00011246789,0.00009387335,0.009651639,0.9801191,0.00019423371,0.000048561345,0.0072542056],"study_design_scores_gemma":[0.000035137993,0.00080373784,0.01473608,0.000010712048,0.000041487812,0.00014540133,0.000102630256,0.08557165,0.8973933,0.00011625606,0.0010206022,0.000022996375],"about_ca_topic_score_codex":0.00044792026,"about_ca_topic_score_gemma":0.0005876533,"teacher_disagreement_score":0.0006076632,"about_ca_system_score_codex":0.00012239335,"about_ca_system_score_gemma":0.00013412745,"threshold_uncertainty_score":0.002032876},"labels":[],"label_agreement":null},{"id":"W2982513810","doi":"10.1177/1077546319880376","title":"Experimental study of stability prediction for high-speed robotic milling of aluminum","year":2019,"lang":"en","type":"article","venue":"Journal of Vibration and Control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Vibration; Machining; Robot; Control theory (sociology); Modal; Stability (learning theory); Displacement (psychology); Engineering; Stiffness; Machine tool; Coupling (piping); Trajectory; Numerical control; Modal analysis; Control engineering; Computer science; Mechanical engineering; Structural engineering; Artificial intelligence; Acoustics; Control (management); Finite element method; Materials science","score_opus":0.008629291987899412,"score_gpt":0.22782134144199181,"score_spread":0.2191920494540924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982513810","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.982735,0.00010832736,0.016030546,0.000044166587,0.00001567375,0.000020990545,0.00003933071,0.00019685618,0.00080910715],"genre_scores_gemma":[0.99785787,0.000022756296,0.0018347418,0.0000031004524,0.0000019080105,0.0000080909485,0.000018176048,0.0000054428856,0.0002478898],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995704,0.000078425146,0.000020682766,0.000071625494,0.00021414955,0.0000446525],"domain_scores_gemma":[0.9983381,0.0007762605,0.00023764232,0.00021963299,0.00037792305,0.000050306553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072348246,0.0003724525,0.0002352621,0.00031419314,0.00036238946,0.00021106249,0.00065474905,0.0005826023,0.0013936708],"category_scores_gemma":[0.0016251118,0.0001960095,0.00021837986,0.00019026705,0.0004897425,0.00037738617,0.0003248481,0.0003568063,0.0001934694],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011870413,0.0003594528,0.0038732204,0.000412768,0.000025816062,0.00026893054,0.00067563367,0.037048303,0.92885524,0.0005447792,0.00029910723,0.026449725],"study_design_scores_gemma":[0.00008980613,0.0058485586,0.015396064,0.000026731897,0.00003822753,0.00013396193,0.00026444663,0.23768255,0.73902684,0.00036511023,0.0010714434,0.000056334142],"about_ca_topic_score_codex":0.00055477757,"about_ca_topic_score_gemma":0.0006666058,"teacher_disagreement_score":0.0013936708,"about_ca_system_score_codex":0.0001828482,"about_ca_system_score_gemma":0.0001938376,"threshold_uncertainty_score":0.004662335},"labels":[],"label_agreement":null},{"id":"W2984738609","doi":"10.1139/tcsme-2019-0215","title":"Machinability study of aircraft series aluminium alloys 7075-T6 and 7050-T7451","year":2019,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machinability; Machining; Materials science; Metallurgy; Aluminium; Toughness; Aluminium alloy; Lubrication; Corrosion; Alloy; Breakage; Residual stress; Composite material","score_opus":0.005130701439955906,"score_gpt":0.19382274482813963,"score_spread":0.18869204338818374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984738609","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973571,0.0008792415,0.00047073697,0.000012192684,0.000006129966,0.000011761406,0.0001065131,0.00001511125,0.0011411973],"genre_scores_gemma":[0.997012,0.00027366064,0.00095843937,0.000007883805,0.0000023002115,0.0000050070666,0.00020310063,0.000009496715,0.0015281261],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995596,0.000035623667,0.000035697194,0.00006796371,0.000256452,0.000044644265],"domain_scores_gemma":[0.99952793,0.0000841706,0.00010517002,0.00004836896,0.00020003227,0.000034217537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032683564,0.0003062971,0.00024469921,0.0010265753,0.00033850342,0.00028176772,0.00040079863,0.000385004,0.0012119949],"category_scores_gemma":[0.00058862363,0.00017235942,0.00030882144,0.00049821305,0.00025136,0.00020883352,0.00016831313,0.00020095434,0.000249975],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006011708,0.00005480322,0.007945746,0.0003176721,0.000051108476,0.00030626246,0.00033384253,0.0018147909,0.9757273,0.0001613642,0.00021476451,0.012471316],"study_design_scores_gemma":[0.00002896069,0.005031728,0.19453862,0.00004552621,0.00019212927,0.000783442,0.00063283753,0.007408749,0.7849618,0.00010014777,0.0062300046,0.00004611041],"about_ca_topic_score_codex":0.0038023766,"about_ca_topic_score_gemma":0.008808198,"teacher_disagreement_score":0.0038023766,"about_ca_system_score_codex":0.00034210033,"about_ca_system_score_gemma":0.00015364544,"threshold_uncertainty_score":0.0075604916},"labels":[],"label_agreement":null},{"id":"W298584975","doi":"10.1177/0954405415584960","title":"An investigation into the effect of nozzle shape and jet pressure in profile creepfeed grinding","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Nozzle; Body orifice; Grinding; Materials science; Jet (fluid); Surface roughness; Mechanical engineering; Conical surface; Inlet; Surface finish; Machining; Mechanics; Composite material; Engineering; Metallurgy; Physics","score_opus":0.006822069725925496,"score_gpt":0.21359102143069048,"score_spread":0.20676895170476497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W298584975","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904715,0.0006874375,0.007952591,0.0000310133,0.000022796203,0.00006554874,0.00006555011,0.00007279246,0.00063082355],"genre_scores_gemma":[0.99269617,0.00036328868,0.006459165,0.000025961599,0.000006655451,0.00001954313,0.00004388557,0.00003087365,0.00035451102],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988972,0.00020678133,0.000097753655,0.000171795,0.0005205264,0.00010597285],"domain_scores_gemma":[0.9946648,0.0033838807,0.00057657674,0.00038657736,0.0008756935,0.00011251319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014358766,0.0004074418,0.00045862186,0.00023882458,0.00036313594,0.00057467195,0.00047423862,0.0006054675,0.0006886448],"category_scores_gemma":[0.0060719196,0.00031027783,0.00025270422,0.00035033654,0.00041124685,0.0006187261,0.00031966012,0.00039094102,0.00016279492],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009257521,0.00021854679,0.0026520218,0.00026127606,0.000016118893,0.00016928169,0.00016411976,0.002474027,0.9716546,0.00006441676,0.0000557739,0.021344136],"study_design_scores_gemma":[0.000038745715,0.005056964,0.022313645,0.000021114918,0.000043022537,0.00027756373,0.00011750266,0.006408515,0.96495646,0.000036273654,0.00070444134,0.000025798177],"about_ca_topic_score_codex":0.0007625881,"about_ca_topic_score_gemma":0.0010844516,"teacher_disagreement_score":0.0014358766,"about_ca_system_score_codex":0.00022849493,"about_ca_system_score_gemma":0.00035090276,"threshold_uncertainty_score":0.007593751},"labels":[],"label_agreement":null},{"id":"W2986896780","doi":"10.1520/ssms20190020","title":"A Generalized Multisensor Real-Time Tool Condition–Monitoring Approach Using Deep Recurrent Neural Network","year":2019,"lang":"en","type":"article","venue":"Smart and Sustainable Manufacturing Systems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Process (computing); Recurrent neural network; Computer science; SIGNAL (programming language); Artificial intelligence; Tool wear; Artificial neural network; Deep learning; Condition monitoring; Feature extraction; Machine learning; Feature (linguistics); Pattern recognition (psychology); Control engineering; Engineering; Machining","score_opus":0.007857472582058433,"score_gpt":0.22122983373633215,"score_spread":0.21337236115427372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2986896780","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05915181,0.00042566078,0.9379429,0.0001423592,0.000034837616,0.00003274855,0.000047743062,0.00068232755,0.0015395152],"genre_scores_gemma":[0.92827123,0.00015085933,0.06972536,0.00006390869,0.000024331603,0.000043854234,0.00008523243,0.000031698248,0.0016034069],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976677,0.00004196815,0.000012615179,0.0000815823,0.00006807725,0.000028947432],"domain_scores_gemma":[0.999813,0.000047099446,0.000037822014,0.000024481425,0.00006465553,0.000013073706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004848209,0.00076877413,0.00043108995,0.0003715462,0.00016517108,0.00043977314,0.00092707353,0.0006223613,0.00082566065],"category_scores_gemma":[0.00060672965,0.0002831465,0.00065908174,0.00032560216,0.00028458712,0.00067343755,0.0004914164,0.00069650006,0.00020110155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001267071,0.000078292804,0.001353472,0.000107976084,0.000096748445,0.00018459366,0.00007731435,0.81068975,0.030665515,0.0020899547,0.00067871605,0.15385097],"study_design_scores_gemma":[0.0000010709626,0.000016266109,0.00014379775,0.0000018468751,0.000005850574,0.0000066299676,0.0000028412226,0.9983625,0.0011242181,0.0002605433,0.00007182983,0.0000025341335],"about_ca_topic_score_codex":0.00414711,"about_ca_topic_score_gemma":0.0042633973,"teacher_disagreement_score":0.00414711,"about_ca_system_score_codex":0.00047602467,"about_ca_system_score_gemma":0.00041738563,"threshold_uncertainty_score":0.008245945},"labels":[],"label_agreement":null},{"id":"W2988015520","doi":"10.1007/s00170-019-04406-6","title":"Investigation of the effect of speed ratio on workpiece surface topography and grinding power in cylindrical plunge grinding using grooved and non-grooved grinding wheels","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Gear ratio; Surface roughness; Rotational speed; Materials science; Grain size; Surface finish; Power (physics); Synchronization (alternating current); Geometry; Mechanical engineering; Composite material; Mathematics; Engineering; Physics; Topology (electrical circuits); Electrical engineering","score_opus":0.004810238809187374,"score_gpt":0.22140936830098454,"score_spread":0.21659912949179716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988015520","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971028,0.0003992071,0.002092746,0.000015555432,0.00001144861,0.000008356834,0.000024876765,0.000027249313,0.0003177804],"genre_scores_gemma":[0.99878055,0.00015055884,0.0008304343,0.0000039469614,0.0000035249593,0.0000029846435,0.000012996329,0.000009540581,0.00020542188],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997571,0.0000421224,0.000014789681,0.000056334076,0.0000894594,0.000040202747],"domain_scores_gemma":[0.998502,0.0009802607,0.00016657042,0.000079018886,0.00022607886,0.000046214194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000376406,0.00026573325,0.000351131,0.00021663264,0.00018113342,0.0002972293,0.0002894356,0.00032679667,0.0012109689],"category_scores_gemma":[0.0015174898,0.0003113345,0.00029027706,0.00028167423,0.00025042208,0.00046548585,0.00014187922,0.00023459502,0.00015659933],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013163709,0.00010787222,0.0038052062,0.00016710555,0.000024468762,0.00011781004,0.00011560292,0.0022038284,0.97793895,0.0000775451,0.0000787752,0.014046371],"study_design_scores_gemma":[0.000072907365,0.0021228143,0.05869026,0.000010767803,0.00011200327,0.00022561655,0.00019363988,0.023699384,0.91400915,0.000060973056,0.0007614051,0.000040991705],"about_ca_topic_score_codex":0.0007320522,"about_ca_topic_score_gemma":0.0012645586,"teacher_disagreement_score":0.0012109689,"about_ca_system_score_codex":0.0002006086,"about_ca_system_score_gemma":0.00018899883,"threshold_uncertainty_score":0.0040510297},"labels":[],"label_agreement":null},{"id":"W2988613083","doi":"10.1016/j.ifacol.2019.10.056","title":"A Review of Developments in the Fields of the Design of Smart Cutting Tools, Wear Monitoring, and Sensor Innovation","year":2019,"lang":"en","type":"review","venue":"IFAC-PapersOnLine","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Computer science; Manufacturing engineering; Engineering; Work (physics); Systems engineering; Data science; Mechanical engineering","score_opus":0.0789060811662014,"score_gpt":0.327274887217883,"score_spread":0.2483688060516816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988613083","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002728454,0.9947608,0.0009244879,0.00028011898,0.0004327278,0.000013752875,0.00006516363,0.000023276369,0.0032269245],"genre_scores_gemma":[0.001210553,0.99580526,0.0011006601,0.00019443773,0.00020927672,0.000012035409,0.000072628085,0.000004571948,0.0013906882],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99962056,0.000047378853,0.00006391088,0.0000667386,0.00016970855,0.000031687912],"domain_scores_gemma":[0.99914527,0.00040348017,0.00011438967,0.000030583942,0.00025100066,0.000055296663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007267908,0.00090780825,0.0010683576,0.0034631735,0.00030927872,0.0010981582,0.0008030996,0.00090834167,0.0070336685],"category_scores_gemma":[0.0011896119,0.00038560107,0.0005979568,0.003944335,0.00031246268,0.001427867,0.00049911195,0.0011553575,0.003377972],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006341145,0.00009337365,0.00018247186,0.047676194,0.000100955214,0.00019852027,0.00009677865,0.0006052013,0.0075756977,0.006198321,0.03726113,0.89994794],"study_design_scores_gemma":[0.0000058438764,0.00010480902,0.0006485674,0.0048313704,0.00012053289,0.0007616402,0.00005175332,0.00009770579,0.0014706034,0.0011824251,0.9907036,0.000021224878],"about_ca_topic_score_codex":0.00077561376,"about_ca_topic_score_gemma":0.0018757497,"teacher_disagreement_score":0.0070336685,"about_ca_system_score_codex":0.00054268906,"about_ca_system_score_gemma":0.0018098122,"threshold_uncertainty_score":0.023530006},"labels":[],"label_agreement":null},{"id":"W2988977240","doi":"10.1016/j.ifacol.2019.10.042","title":"Effects of Harmonic Vibrations of Cutting Speed on Cutting Force and Surface Quality in Al 7075-T6 Broaching","year":2019,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Broaching; Machining; Vibration; Mechanical engineering; Quality (philosophy); Phase (matter); Engineering; Materials science; Acoustics; Physics","score_opus":0.007084166760245924,"score_gpt":0.25673465869753853,"score_spread":0.2496504919372926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988977240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989304,0.00018527875,0.000619209,0.000007688684,0.000004247877,0.0000050017916,0.000010904317,0.00000775843,0.00022948011],"genre_scores_gemma":[0.99914443,0.00009000402,0.00046163847,0.000005472632,0.0000011717474,0.00000248137,0.0000122193,0.000003122503,0.00027948405],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997547,0.00002749915,0.0000125658935,0.00004144371,0.00011495664,0.000048815025],"domain_scores_gemma":[0.9992619,0.00035066315,0.00017497878,0.000038741684,0.00012610148,0.000047560334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030788247,0.00023081726,0.00022410654,0.00025108238,0.00018806227,0.00026822853,0.00022680427,0.00041908864,0.00088042795],"category_scores_gemma":[0.00069224444,0.00017541242,0.00019998943,0.00023168378,0.00035821274,0.00021593645,0.00017470219,0.00031767835,0.0000974096],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008029735,0.00008648699,0.0021423677,0.00011776383,0.000010840405,0.000118315314,0.0001067311,0.0028319345,0.98644084,0.00004787698,0.000034700774,0.0072592995],"study_design_scores_gemma":[0.000027040205,0.0022009227,0.032346606,0.000013125838,0.000031497584,0.00008877919,0.00024990615,0.009727305,0.9548138,0.000047713347,0.0004282084,0.000025079084],"about_ca_topic_score_codex":0.00076298026,"about_ca_topic_score_gemma":0.0014072211,"teacher_disagreement_score":0.00088042795,"about_ca_system_score_codex":0.00016001763,"about_ca_system_score_gemma":0.00009211739,"threshold_uncertainty_score":0.002945304},"labels":[],"label_agreement":null},{"id":"W2990344497","doi":"10.3390/ma12233974","title":"Machinability Study of Hardened 1045 Steel When Milling with Ceramic Cutting Inserts","year":2019,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cegep Edouard Montpetit; École de Technologie Supérieure","funders":"","keywords":"Machinability; Materials science; Machining; Ceramic; Sialon; Flank; Tool wear; Hardened steel; Enhanced Data Rates for GSM Evolution; Drilling; Brittleness; Abrasion (mechanical); Insert (composites); Composite material; Metallurgy; Cutting tool","score_opus":0.005356735719405771,"score_gpt":0.20088552462447404,"score_spread":0.19552878890506828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990344497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991597,0.000116801544,0.00051770377,0.000003185003,0.0000025381362,0.0000086412865,0.000040525032,0.0000066948896,0.00014421222],"genre_scores_gemma":[0.99691004,0.0001402024,0.0019386018,0.0000071147306,0.000002818081,0.000009993595,0.00010410079,0.0000087922,0.0008782279],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995003,0.000050375584,0.000050689505,0.00007562228,0.00027167777,0.0000514448],"domain_scores_gemma":[0.99918514,0.00022663239,0.00025056436,0.000057006382,0.00023539648,0.00004527852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003896007,0.0003166847,0.0003546393,0.00043867974,0.00019404119,0.00026279746,0.00032772144,0.0002934268,0.0010260106],"category_scores_gemma":[0.00079563394,0.0001863485,0.00040743558,0.0003896009,0.00020204081,0.00024046833,0.0001988943,0.00028877048,0.0001758874],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022710732,0.000033907716,0.0021566285,0.000100470126,0.000009244516,0.00006307607,0.00012834476,0.00021863391,0.9934169,0.000007176548,0.000012803516,0.003625657],"study_design_scores_gemma":[0.000010962969,0.0041097067,0.10533167,0.000011688754,0.00006589598,0.00019997025,0.00033402277,0.0017910311,0.8874009,0.00001542951,0.00069956615,0.000029020995],"about_ca_topic_score_codex":0.00080787647,"about_ca_topic_score_gemma":0.0024166119,"teacher_disagreement_score":0.0010260106,"about_ca_system_score_codex":0.00020036563,"about_ca_system_score_gemma":0.00010188396,"threshold_uncertainty_score":0.0034323335},"labels":[],"label_agreement":null},{"id":"W2991366373","doi":"10.1007/s00170-019-04550-z","title":"Environmentally conscious machining of Inconel 718: surface roughness, tool wear, and material removal rate assessment","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inconel; Machining; Surface roughness; Metallurgy; Materials science; Surface finish; Tool wear; Industrial and production engineering; Mechanical engineering; Composite material; Engineering; Alloy","score_opus":0.002969062364752998,"score_gpt":0.21849854090232804,"score_spread":0.21552947853757504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991366373","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983981,0.000037114707,0.00093347626,0.0000055803594,0.0000019452186,0.00000662137,0.0000619839,0.000018820016,0.00053641363],"genre_scores_gemma":[0.99758935,0.000030333198,0.0015630345,0.000004150078,7.878818e-7,0.0000047037893,0.00008577502,0.000007654249,0.0007141751],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995252,0.000036351506,0.000021220882,0.00005997181,0.0003159818,0.000041299114],"domain_scores_gemma":[0.9995554,0.00009847654,0.00007868115,0.000064884254,0.00018453842,0.000017966591],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004052445,0.00023566348,0.00028710635,0.0003711943,0.0003192894,0.00032786798,0.00042207332,0.00050823425,0.00074212695],"category_scores_gemma":[0.0006441395,0.00016536082,0.00020024761,0.00038163867,0.0002371699,0.00030120305,0.00025976804,0.00026211035,0.00012554947],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013972572,0.00035604832,0.06343657,0.00029447855,0.000070516835,0.00046790869,0.0003416133,0.026165938,0.8446735,0.00038352635,0.00049462076,0.061918046],"study_design_scores_gemma":[0.000043698365,0.003387675,0.29780716,0.000014810816,0.00008590817,0.00052052224,0.0004806218,0.07032402,0.6237776,0.00027767566,0.003197779,0.000082535335],"about_ca_topic_score_codex":0.0038957405,"about_ca_topic_score_gemma":0.011514254,"teacher_disagreement_score":0.0038957405,"about_ca_system_score_codex":0.00029023914,"about_ca_system_score_gemma":0.00025834932,"threshold_uncertainty_score":0.0077461004},"labels":[],"label_agreement":null},{"id":"W2992369099","doi":"10.1007/s00170-019-04627-9","title":"Effect of process parameters on chip formation during vibration-assisted drilling of Ti6Al4V","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McMaster University","funders":"","keywords":"Materials science; Drilling; Scanning electron microscope; Thrust; Titanium alloy; Vibration; Chip formation; Rake angle; Machining; Chip; Amplitude; Composite material; Structural engineering; Tool wear; Mechanical engineering; Metallurgy; Optics; Acoustics; Engineering; Alloy","score_opus":0.003576141554005121,"score_gpt":0.23486428030438988,"score_spread":0.23128813875038476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2992369099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989548,0.00019405152,0.0005150752,0.000017888675,0.000018141725,0.0000034729117,0.000023666054,0.000023351997,0.00024955068],"genre_scores_gemma":[0.99960214,0.000032275686,0.00021472118,0.000003991599,0.0000015038679,0.0000014511686,0.000011416383,0.000005003079,0.00012733618],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987376,0.000014404709,0.000007300494,0.000024615705,0.00003759494,0.000042384334],"domain_scores_gemma":[0.99951184,0.00024426635,0.00010355364,0.000029373286,0.00007957691,0.000031346288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020127208,0.00018559559,0.00019850343,0.000115688985,0.00019614243,0.000256846,0.00025599106,0.00027663462,0.00136748],"category_scores_gemma":[0.00071876094,0.00018259523,0.00013345997,0.00012566039,0.00026213433,0.00030888413,0.00017393992,0.00025941632,0.00012882064],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014163046,0.000056869547,0.001012981,0.00017322916,0.00001609657,0.00015334626,0.00017239047,0.0022977025,0.9888854,0.000099808785,0.00013884764,0.0055770795],"study_design_scores_gemma":[0.000028893679,0.0009399439,0.008915536,0.0000069418866,0.000024610328,0.000060042974,0.0001522251,0.007803683,0.9815616,0.000035323235,0.0004529004,0.000018344565],"about_ca_topic_score_codex":0.0005140334,"about_ca_topic_score_gemma":0.0012461012,"teacher_disagreement_score":0.00136748,"about_ca_system_score_codex":0.00015241462,"about_ca_system_score_gemma":0.00018765226,"threshold_uncertainty_score":0.0045746565},"labels":[],"label_agreement":null},{"id":"W2993797753","doi":"10.1016/j.wear.2019.203153","title":"Wear of form taps in threading of Al-Si alloy parts: Mechanisms and measurements","year":2019,"lang":"en","type":"article","venue":"Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Abrasion (mechanical); Machining; Rework; Scrap; Tool wear; Alloy; Threading (protein sequence); Automotive industry; Metallurgy; Mechanical engineering; Composite material; Computer science; Engineering","score_opus":0.011801894250243467,"score_gpt":0.22237969224635376,"score_spread":0.2105777979961103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2993797753","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99801874,0.0002109115,0.0013740795,0.000007382725,0.000010087015,0.000016645481,0.000096707015,0.000060848906,0.00020459446],"genre_scores_gemma":[0.99928516,0.000035522608,0.00038794958,0.0000034962225,0.0000032266264,0.000005002141,0.00003873682,0.000007780387,0.00023306951],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995011,0.000045703786,0.00003309611,0.000078305966,0.00027828966,0.00006341556],"domain_scores_gemma":[0.9976484,0.00078291487,0.00034672112,0.00036555433,0.00073075836,0.00012568424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000522736,0.00032128062,0.00048333046,0.00086525566,0.0004401953,0.00046533238,0.0005933789,0.00054955226,0.0009880804],"category_scores_gemma":[0.0019810703,0.00036107388,0.00036534248,0.00053577777,0.0006695253,0.0005643772,0.00039492315,0.0004105007,0.00017449509],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029223426,0.00024544663,0.03489576,0.00029838295,0.00006264661,0.00033264523,0.0016468902,0.0028613163,0.9213912,0.00023964382,0.00045311323,0.034650635],"study_design_scores_gemma":[0.00008674529,0.0040542795,0.21380487,0.00003394203,0.00008616542,0.0010231934,0.00086119457,0.033643924,0.7441787,0.00020438025,0.0019486437,0.000073939496],"about_ca_topic_score_codex":0.0011062161,"about_ca_topic_score_gemma":0.001219881,"teacher_disagreement_score":0.0011062161,"about_ca_system_score_codex":0.00042731685,"about_ca_system_score_gemma":0.00021434731,"threshold_uncertainty_score":0.0033054352},"labels":[],"label_agreement":null},{"id":"W2994636746","doi":"10.1007/s00170-019-04702-1","title":"Effect of edge preparation technologies on cutting edge properties and tool performance","year":2019,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Enhanced Data Rates for GSM Evolution; Materials science; Machining; Tungsten carbide; Abrasive; Residual stress; Composite material; Surface finish; Surface roughness; Drag; Metallurgy; Engineering","score_opus":0.004993031544287396,"score_gpt":0.2262342628000466,"score_spread":0.2212412312557592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2994636746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994776,0.0011430712,0.0025879582,0.000026401502,0.000045023513,0.00001164202,0.0000913387,0.00008241517,0.0012360159],"genre_scores_gemma":[0.9973636,0.00035356605,0.0015804672,0.000015617867,0.0000086277605,0.000006199267,0.00007148707,0.0000474038,0.0005529777],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997632,0.000026922706,0.000018124918,0.000059284182,0.000052227475,0.00008029024],"domain_scores_gemma":[0.9987779,0.0006451709,0.00026206623,0.00011785325,0.00012730584,0.00006965015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003295342,0.00048964494,0.00036562016,0.00032594815,0.00027715837,0.0006430651,0.00033755405,0.000559816,0.0024627575],"category_scores_gemma":[0.001348524,0.00034067643,0.0002912537,0.00047557201,0.00026076037,0.00082044554,0.00029790873,0.0005522883,0.00050939486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002054269,0.00020003271,0.001437034,0.00016961554,0.000024250665,0.00014254212,0.000048682778,0.002869483,0.9843699,0.00015559127,0.00009400861,0.008434588],"study_design_scores_gemma":[0.000020092035,0.0009838762,0.0037216435,0.00000880134,0.000048106027,0.000059837414,0.000039816085,0.002275979,0.99236506,0.000033935736,0.00043139103,0.000011368749],"about_ca_topic_score_codex":0.00025655865,"about_ca_topic_score_gemma":0.00043164057,"teacher_disagreement_score":0.0024627575,"about_ca_system_score_codex":0.00015186727,"about_ca_system_score_gemma":0.0002747775,"threshold_uncertainty_score":0.008238673},"labels":[],"label_agreement":null},{"id":"W2995159336","doi":"10.20964/2020.01.60","title":"Corrosion Behavior of AISI 1045 Carbon Steel in Metalworking Fluids Containing","year":2019,"lang":"en","type":"article","venue":"International Journal of Electrochemical Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Metalworking; Corrosion; Carbon steel; Metallurgy; Materials science","score_opus":0.005357317863368323,"score_gpt":0.2550824759366226,"score_spread":0.24972515807325427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995159336","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989398,0.0003036811,0.00029766653,0.00002128375,0.0000058943756,0.0000060993207,0.00008492528,0.00000833827,0.00033237136],"genre_scores_gemma":[0.998033,0.00025187852,0.0007594603,0.000011203374,0.000003538981,0.000005872464,0.00016540082,0.0000022794773,0.0007672786],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999808,0.000030324622,0.00001686201,0.000034343855,0.00007822878,0.000032346343],"domain_scores_gemma":[0.99986446,0.000016821648,0.000033124314,0.000006912953,0.0000652815,0.000013277155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001461258,0.00045396373,0.0001648987,0.00023260475,0.00018300135,0.00020105075,0.00022171595,0.00036537764,0.0005551393],"category_scores_gemma":[0.00025514164,0.00010092022,0.00022436715,0.00025272326,0.00012799732,0.0002248447,0.00011849666,0.00018695484,0.00012089771],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013503875,0.000018008925,0.0029428767,0.00007689969,0.00001326691,0.000099356854,0.000085910455,0.00018297123,0.994072,0.000025937798,0.000030263862,0.0023173545],"study_design_scores_gemma":[0.000003763168,0.0006929339,0.02716069,0.000010595343,0.000027622305,0.00013088726,0.00024819782,0.0017171392,0.96918184,0.000026098558,0.00078974495,0.000010481186],"about_ca_topic_score_codex":0.0045158635,"about_ca_topic_score_gemma":0.0051418813,"teacher_disagreement_score":0.0045158635,"about_ca_system_score_codex":0.00025017746,"about_ca_system_score_gemma":0.00018880772,"threshold_uncertainty_score":0.008979142},"labels":[],"label_agreement":null},{"id":"W2995479783","doi":"10.1016/j.measurement.2019.107370","title":"Kriging versus Bezier and regression methods for modeling and prediction of cutting force and surface roughness during high speed edge trimming of carbon fiber reinforced polymers","year":2019,"lang":"en","type":"article","venue":"Measurement","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Corporación Tecnológica de Andalucía; Bombardier","keywords":"Trimming; Kriging; Surface roughness; Materials science; Enhanced Data Rates for GSM Evolution; Surface finish; Surface (topology); Polymer; Composite material; Regression analysis; Bézier curve; Geometry; Mathematics; Mechanical engineering; Engineering; Computer science; Statistics; Artificial intelligence","score_opus":0.027349018226321214,"score_gpt":0.2753920600387506,"score_spread":0.2480430418124294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995479783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59432596,0.00054973207,0.4034592,0.00006533408,0.000028486382,0.000039278682,0.00010865078,0.0006571261,0.00076632673],"genre_scores_gemma":[0.93294305,0.00021795066,0.06582667,0.000008049173,0.0000035193518,0.000032446456,0.00007019438,0.00004468533,0.0008533914],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998041,0.00006577748,0.000013941856,0.000033960405,0.000056018274,0.000026189016],"domain_scores_gemma":[0.99942553,0.00038175774,0.00006694574,0.00003098335,0.00008317765,0.000011637041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006571756,0.00044101282,0.00042756586,0.00030611435,0.00029498327,0.00028050633,0.00042451275,0.00050709734,0.0003374162],"category_scores_gemma":[0.0012018237,0.00039266076,0.0004477156,0.00034193092,0.00020273493,0.0003697378,0.0001946657,0.0006707934,0.00009197416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023138504,0.000108881475,0.0023868175,0.00009158244,0.000032340497,0.000029366236,0.000082711565,0.9259257,0.016907059,0.00057342753,0.00013585946,0.053494893],"study_design_scores_gemma":[0.0000036803651,0.00004864756,0.0006466009,0.0000016749932,0.0000058931373,0.0000059104277,0.000006852163,0.9949994,0.004152373,0.000060776812,0.00006353708,0.0000047273365],"about_ca_topic_score_codex":0.028833918,"about_ca_topic_score_gemma":0.02726596,"teacher_disagreement_score":0.028833918,"about_ca_system_score_codex":0.0005009768,"about_ca_system_score_gemma":0.0008287529,"threshold_uncertainty_score":0.057332158},"labels":[],"label_agreement":null},{"id":"W2995871999","doi":"10.1016/j.cirpj.2019.11.006","title":"Chatter stability of synchronized elliptical vibration assisted milling","year":2019,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vibration; Actuator; Ultrasonic sensor; Materials science; Acoustics; Amplitude; Time domain; Chip; Mechanical engineering; Engineering; Physics; Optics; Computer science","score_opus":0.006629968285562995,"score_gpt":0.2136508044791858,"score_spread":0.2070208361936228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995871999","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5278034,0.00032900856,0.46156657,0.00010873514,0.000074323245,0.000023564067,0.000039366612,0.00015993293,0.009895075],"genre_scores_gemma":[0.99542326,0.000035223413,0.0028769863,0.00000797802,0.000006904684,0.000007471399,0.00001025752,0.000009088284,0.0016228548],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997985,0.000056454945,0.000008574533,0.00004127725,0.00007485508,0.00002039562],"domain_scores_gemma":[0.99932253,0.00035430572,0.00009983326,0.00005475709,0.00013815936,0.000030350768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038483742,0.00030928463,0.00034885076,0.00023007438,0.00019459277,0.00041986417,0.00036682692,0.000397218,0.0017019316],"category_scores_gemma":[0.001364056,0.0001553804,0.00018754671,0.0001487413,0.00048084807,0.00035767767,0.00048167058,0.00029522946,0.00015599158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023469874,0.00018847363,0.0037233194,0.0004226983,0.00018144908,0.0007656432,0.00095372973,0.5650108,0.24427919,0.09798458,0.0013320887,0.08281115],"study_design_scores_gemma":[0.000010703788,0.00010874229,0.000897139,0.0000051172915,0.0000071984878,0.000039383176,0.000024248488,0.9912429,0.0046707126,0.002783576,0.0001990872,0.000011246073],"about_ca_topic_score_codex":0.0006148501,"about_ca_topic_score_gemma":0.00044660692,"teacher_disagreement_score":0.0017019316,"about_ca_system_score_codex":0.00020583993,"about_ca_system_score_gemma":0.00016586995,"threshold_uncertainty_score":0.0056934953},"labels":[],"label_agreement":null},{"id":"W2997516628","doi":"10.4271/2020-01-0035","title":"Advances in Drilling with PCD (Polycrystalline Diamond)","year":2020,"lang":"en","type":"article","venue":"SAE International Journal of Advances and Current Practices in Mobility","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MD Precision (Canada)","funders":"","keywords":"Drilling; Polycrystalline diamond; Drill; Materials science; Diamond; Metallurgy; Composite material","score_opus":0.016394827029482344,"score_gpt":0.3194583870822549,"score_spread":0.3030635600527725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997516628","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1557405,0.16216063,0.5778262,0.002955872,0.0014370095,0.00040368916,0.00076107745,0.0012804096,0.09743459],"genre_scores_gemma":[0.4550094,0.054734435,0.46409166,0.00032283386,0.00032050686,0.00015682986,0.0008444432,0.00023905738,0.02428076],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987233,0.000092812705,0.000067036766,0.00023871525,0.0008206326,0.000057407768],"domain_scores_gemma":[0.99903995,0.000245307,0.0001341247,0.00015414618,0.0003802665,0.000046152127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001327028,0.0003823776,0.000327853,0.00085540983,0.00021442847,0.0008241412,0.0008287731,0.0005272168,0.0040520397],"category_scores_gemma":[0.0011054792,0.00039826983,0.00034137658,0.0011070631,0.0005297945,0.0010800101,0.0007643259,0.0008618125,0.0015838991],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015269002,0.00019933704,0.0022895914,0.0023568028,0.00004293131,0.00019356565,0.0002447647,0.0066314414,0.4014443,0.02262768,0.007255864,0.55656105],"study_design_scores_gemma":[0.000043592852,0.00094422634,0.0067446753,0.00026548823,0.00004391385,0.0019905798,0.00020053906,0.011527522,0.41231647,0.0048430315,0.5609907,0.00008924265],"about_ca_topic_score_codex":0.00092135504,"about_ca_topic_score_gemma":0.0017397602,"teacher_disagreement_score":0.0040520397,"about_ca_system_score_codex":0.0006981159,"about_ca_system_score_gemma":0.0006146002,"threshold_uncertainty_score":0.0135554075},"labels":[],"label_agreement":null},{"id":"W2998922510","doi":"10.1007/s00170-019-04759-y","title":"An applied explicit mathematical model of conical drill point geometry without flank rubbing","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"National Major Science and Technology Projects of China","keywords":"Flank; Rubbing; Drill; Conical surface; Point (geometry); Geometry; Drilling; Helix angle; Engineering; Structural engineering; Mathematics; Mechanical engineering","score_opus":0.011665545172445795,"score_gpt":0.24789263116792865,"score_spread":0.23622708599548284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998922510","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02270405,0.0007360905,0.9180185,0.0005249429,0.0002605604,0.000057399164,0.00023809267,0.00016249489,0.057297904],"genre_scores_gemma":[0.8558481,0.0010338378,0.09724676,0.00031297468,0.00018677255,0.00017006289,0.00027129077,0.00019922186,0.044730894],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997259,0.000055312652,0.000013128588,0.00005356609,0.00011646308,0.00003563265],"domain_scores_gemma":[0.99965596,0.000109278946,0.000053457425,0.00004321574,0.00011700666,0.000021028593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037528275,0.00060556096,0.0008177718,0.0006139954,0.00042016126,0.0015129087,0.0017429771,0.0020549705,0.0042458368],"category_scores_gemma":[0.0013878179,0.00052752293,0.00073375885,0.0007580052,0.0010559506,0.0016490403,0.00093935616,0.0011361777,0.0008662319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015006997,0.00003067085,0.00016907348,0.00007751548,0.000008383896,0.00014791967,0.000047058533,0.8490361,0.0027125317,0.14284647,0.00075073354,0.004158529],"study_design_scores_gemma":[0.000003648379,0.000005929273,0.000047885584,0.000004025913,0.0000023385503,0.000027250733,0.000006538417,0.9906289,0.00024420308,0.008179011,0.00084506685,0.000005180543],"about_ca_topic_score_codex":0.0048215375,"about_ca_topic_score_gemma":0.0031211001,"teacher_disagreement_score":0.0048215375,"about_ca_system_score_codex":0.0008213299,"about_ca_system_score_gemma":0.0011269061,"threshold_uncertainty_score":0.014203787},"labels":[],"label_agreement":null},{"id":"W2999227275","doi":"10.1007/s00170-019-04881-x","title":"Feasibility analysis of active chatter control for stationary and revolving bar boring operations based on magnitude of control forces using fractional order PDλ controller","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Bar (unit); Machining; Engineering; Controller (irrigation); Rigidity (electromagnetism); Process (computing); Structural engineering; Mechanical engineering; Computer science; Control (management); Artificial intelligence; Physics","score_opus":0.011552608098780622,"score_gpt":0.27461467319412697,"score_spread":0.26306206509534635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999227275","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08824217,0.00036690917,0.8992955,0.00013469762,0.000071316936,0.00013062937,0.000026476097,0.00020926358,0.011523073],"genre_scores_gemma":[0.9847669,0.0000846432,0.013710749,0.00001588401,0.000011868572,0.00005392393,0.000014227895,0.000012248626,0.0013296367],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941885,0.00012923377,0.000022953767,0.00011869884,0.0002398837,0.00007040713],"domain_scores_gemma":[0.9982603,0.0010502958,0.00014285948,0.000068953326,0.00044971492,0.000027927417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011675417,0.00082777935,0.00069790473,0.0004767585,0.00046939604,0.0012607126,0.00069856714,0.0008158603,0.0033981397],"category_scores_gemma":[0.0021118624,0.0003735249,0.0005686816,0.00028386575,0.000646935,0.0006797836,0.00042428923,0.0005326404,0.00018163343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022826334,0.00029753652,0.001999364,0.0016525575,0.00015384115,0.0007738279,0.0005717187,0.69542444,0.14951561,0.04187539,0.0013728074,0.104080275],"study_design_scores_gemma":[0.000031688174,0.00033553984,0.0007045404,0.000015064384,0.000026320275,0.000058799393,0.000035840694,0.99153954,0.0057081985,0.0011567223,0.00037289172,0.000014818065],"about_ca_topic_score_codex":0.0024474603,"about_ca_topic_score_gemma":0.0015681701,"teacher_disagreement_score":0.0033981397,"about_ca_system_score_codex":0.00044508537,"about_ca_system_score_gemma":0.00072484266,"threshold_uncertainty_score":0.011367917},"labels":[],"label_agreement":null},{"id":"W2999516701","doi":"10.1007/s00170-020-04933-7","title":"Investigation into the effect of wheel groove depth and width on grinding performance in creep-feed grinding","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Groove (engineering); Materials science; Grinding; Surface roughness; Coolant; Composite material; Surface finish; Volumetric flow rate; Mechanics; Mechanical engineering; Metallurgy; Engineering; Physics","score_opus":0.006640015326645284,"score_gpt":0.21975527653889482,"score_spread":0.21311526121224952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999516701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99759287,0.00025972226,0.0017293686,0.000016132004,0.000010490751,0.0000058693313,0.000037831356,0.000045666715,0.0003020141],"genre_scores_gemma":[0.998777,0.000092716924,0.0008017816,0.0000063917955,0.0000020911182,0.0000019752747,0.000027624028,0.000016776261,0.00027363235],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997279,0.00003129964,0.000022337255,0.00005798287,0.0001057497,0.000054760916],"domain_scores_gemma":[0.9982741,0.0008148101,0.0002800711,0.00013725573,0.00041086285,0.00008286896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005042852,0.00036001162,0.00044711295,0.00019856439,0.0002825519,0.0003499887,0.00042423725,0.0004271338,0.0007641321],"category_scores_gemma":[0.0015259889,0.00029781193,0.00026109346,0.00027126452,0.00026246396,0.0004584807,0.00016661052,0.0003244872,0.00022985031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008601884,0.00016294436,0.0033226516,0.00011045058,0.000018221312,0.000101878555,0.00008656279,0.0051419795,0.9782647,0.00003273955,0.000073543604,0.01182414],"study_design_scores_gemma":[0.000025288542,0.0025207796,0.03846239,0.000013632001,0.00007240022,0.00012783964,0.00013390364,0.019001717,0.93914276,0.00003343147,0.0004319409,0.000033886827],"about_ca_topic_score_codex":0.0012583811,"about_ca_topic_score_gemma":0.003293931,"teacher_disagreement_score":0.0012583811,"about_ca_system_score_codex":0.00025819737,"about_ca_system_score_gemma":0.00023691812,"threshold_uncertainty_score":0.0026669502},"labels":[],"label_agreement":null},{"id":"W3001018233","doi":"10.1016/j.jmapro.2019.09.036","title":"Incorporating dual BCC/FCC Zerilli-Armstrong and blue brittleness constitutive material models into Oxley’s machining shear zone theory","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Arts Research Board, McMaster University; American University of Beirut","keywords":"Materials science; Machining; Constitutive equation; Brittleness; Shear (geology); Composite material; Dual (grammatical number); Structural engineering; Metallurgy; Finite element method; Engineering","score_opus":0.011794246510658949,"score_gpt":0.21563165753854066,"score_spread":0.20383741102788172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3001018233","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.070998244,0.0016469934,0.8186726,0.00096940954,0.00065058185,0.00011007263,0.00021700886,0.00029113388,0.10644394],"genre_scores_gemma":[0.853538,0.0007973587,0.08748274,0.0004400045,0.00009834321,0.00012909748,0.00014458052,0.00023888117,0.057131033],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982965,0.000036149522,0.0000067090136,0.000023027349,0.000081620354,0.000022795826],"domain_scores_gemma":[0.9998634,0.000032120894,0.000014896362,0.000026255242,0.00005019153,0.000013093256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000367863,0.000785136,0.00068881083,0.0010085732,0.0004907287,0.0008283937,0.0016111158,0.0011950266,0.0035863058],"category_scores_gemma":[0.00059510407,0.00055087486,0.00060192513,0.0005941828,0.0009173834,0.0014967652,0.00067479856,0.0011551776,0.0007377259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000327901,0.000055399647,0.00027291686,0.00007699625,0.000016249283,0.00012438535,0.00008061754,0.702234,0.010264038,0.27360854,0.001544603,0.011689514],"study_design_scores_gemma":[0.0000061088363,0.000011059722,0.0001360009,0.000005799853,0.000004179908,0.000021777521,0.000012123328,0.97987515,0.0008770631,0.01722311,0.0018190475,0.00000868939],"about_ca_topic_score_codex":0.0061828904,"about_ca_topic_score_gemma":0.0097250035,"teacher_disagreement_score":0.0061828904,"about_ca_system_score_codex":0.00086292136,"about_ca_system_score_gemma":0.000664835,"threshold_uncertainty_score":0.012293756},"labels":[],"label_agreement":null},{"id":"W3001068130","doi":"10.1139/tcsme-2019-0254","title":"Multi-response optimization of CNC turning parameters of austenitic stainless steel 303 using Taguchi-based grey relational analysis","year":2020,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Grey relational analysis; Taguchi methods; Orthogonal array; Surface roughness; Machining; Process (computing); Mechanical engineering; Process variable; Design of experiments; Austenitic stainless steel; Materials science; Engineering drawing; Computer science; Engineering; Metallurgy; Mathematics; Composite material; Statistics","score_opus":0.024689999591191933,"score_gpt":0.22709202907106923,"score_spread":0.2024020294798773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3001068130","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49668616,0.0012941314,0.49803585,0.000068171124,0.000029971234,0.0002892476,0.00012430767,0.00028289715,0.0031893642],"genre_scores_gemma":[0.86481404,0.00048483978,0.13384058,0.000020692012,0.0000045451284,0.00015121263,0.00007855678,0.000044407323,0.00056116685],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984131,0.0003921578,0.00010708169,0.00016500842,0.00083959615,0.00008309767],"domain_scores_gemma":[0.99902475,0.0005274724,0.00016080435,0.00005424086,0.00021507392,0.000017643519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001957099,0.00066461513,0.00093534123,0.0010860943,0.00020008271,0.00074705447,0.0005200915,0.00047083967,0.00049765897],"category_scores_gemma":[0.0018084851,0.00033729992,0.0008766994,0.0010351929,0.00036482525,0.00031841212,0.00030561892,0.00043442918,0.0001659049],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003248358,0.00017142131,0.0016312902,0.0006075744,0.00005762065,0.000082450366,0.00019156432,0.16897385,0.76500916,0.00101032,0.0001504565,0.061789393],"study_design_scores_gemma":[0.00003515619,0.0012826059,0.007359432,0.000028310202,0.00011890452,0.00011076918,0.000095738105,0.5199209,0.46901217,0.0005516893,0.0013935927,0.00009077001],"about_ca_topic_score_codex":0.0013474957,"about_ca_topic_score_gemma":0.0031469618,"teacher_disagreement_score":0.001957099,"about_ca_system_score_codex":0.00066411495,"about_ca_system_score_gemma":0.0005638398,"threshold_uncertainty_score":0.010350287},"labels":[],"label_agreement":null},{"id":"W3001708567","doi":"10.1007/s00170-020-04945-3","title":"On the impacts of tool geometry and cutting conditions in straight turning of aluminum alloys 6061-T6: an experimentally validated numerical study","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; École de Technologie Supérieure","funders":"","keywords":"Machining; Rake angle; Enhanced Data Rates for GSM Evolution; Machinability; Materials science; Drilling; RADIUS; Cutting tool; Tool wear; Mechanical engineering; Chip formation; Aerospace; Aluminium; Metallurgy; Geometry; Engineering; Computer science; Mathematics","score_opus":0.009634149657183979,"score_gpt":0.2709497443738024,"score_spread":0.26131559471661847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3001708567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99593675,0.0001727312,0.0018075379,0.000021627722,0.000014434771,0.000012862167,0.00006981868,0.00004645722,0.0019176429],"genre_scores_gemma":[0.99936503,0.000043573495,0.0003845509,0.000004275311,0.000001761179,0.0000029345945,0.00002133291,0.00000529026,0.00017125127],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981743,0.000029121935,0.000007632043,0.000026146492,0.00006760651,0.00005210399],"domain_scores_gemma":[0.9986492,0.00093609287,0.00014086916,0.000080748585,0.00015611868,0.000037142454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029999876,0.00027929587,0.00045822095,0.0004007967,0.00041494556,0.0005128183,0.00045615976,0.0006978047,0.0021693108],"category_scores_gemma":[0.0015237927,0.00022159844,0.0003771222,0.00028081326,0.00074811885,0.00033301927,0.0002695822,0.00027203475,0.00023793182],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024473104,0.0007796093,0.009684853,0.00070371415,0.000066415974,0.0011716969,0.00041853433,0.5536371,0.40484694,0.0015944046,0.0008983626,0.023751168],"study_design_scores_gemma":[0.000125168,0.0021923673,0.03430272,0.000043122498,0.00010899277,0.00034876284,0.00051507103,0.83910424,0.1215079,0.0005885899,0.001063587,0.000099531724],"about_ca_topic_score_codex":0.0027714388,"about_ca_topic_score_gemma":0.0032613766,"teacher_disagreement_score":0.0027714388,"about_ca_system_score_codex":0.00022932274,"about_ca_system_score_gemma":0.0002871652,"threshold_uncertainty_score":0.0072570443},"labels":[],"label_agreement":null},{"id":"W3002067784","doi":"10.1016/j.wear.2020.203191","title":"Chip formation and tribological behavior in high-speed milling of IN718 with ceramic tools","year":2020,"lang":"en","type":"article","venue":"Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Machinability; Chip formation; Tool wear; Machining; Brittleness; Ceramic; Inconel; Sialon; Superalloy; Nanoindentation; Composite material; Tribology; Metallurgy; Mechanical engineering; Microstructure","score_opus":0.019086734048463495,"score_gpt":0.21656480805364253,"score_spread":0.19747807400517903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3002067784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99919444,0.00010134214,0.0003515881,0.000008076775,0.000008318772,0.0000029504972,0.000029219396,0.000017142258,0.00028699683],"genre_scores_gemma":[0.9988557,0.000028962924,0.00037237947,0.000004990578,0.0000018673181,0.0000030493293,0.000034631106,0.000005724968,0.00069259375],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998153,0.000015187886,0.000009878592,0.00003794414,0.000068522444,0.000053182586],"domain_scores_gemma":[0.9996674,0.00009559691,0.000078212855,0.000036024037,0.00009206028,0.000030647876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021744179,0.00015261474,0.00025332635,0.00025627605,0.000255201,0.00029776167,0.00040867415,0.00026927036,0.001333488],"category_scores_gemma":[0.00051906635,0.00020610409,0.0001420697,0.00020754937,0.0002447475,0.0002466525,0.00012768147,0.00017906552,0.00016482105],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047280864,0.000058429665,0.002300432,0.00008406893,0.000014723402,0.00013657556,0.00020732191,0.0011661041,0.99103737,0.00014779315,0.00025148856,0.0041227797],"study_design_scores_gemma":[0.000019005702,0.0004888503,0.021802966,0.0000046917544,0.00001646919,0.000090733585,0.00013569873,0.007093204,0.969468,0.000033469994,0.00083465385,0.000012168069],"about_ca_topic_score_codex":0.0010312329,"about_ca_topic_score_gemma":0.00226414,"teacher_disagreement_score":0.001333488,"about_ca_system_score_codex":0.00034748839,"about_ca_system_score_gemma":0.00019173876,"threshold_uncertainty_score":0.004460931},"labels":[],"label_agreement":null},{"id":"W3005007700","doi":"10.1088/1361-6501/ab7282","title":"A novel transformer-based neural network model for tool wear estimation","year":2020,"lang":"en","type":"article","venue":"Measurement Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":98,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Transformer; Artificial neural network; Feature (linguistics); Data mining; Raw data; Artificial intelligence; Engineering; Voltage","score_opus":0.03784379806808408,"score_gpt":0.23781849481379702,"score_spread":0.19997469674571294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005007700","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023735518,0.00046148774,0.9727633,0.00011516999,0.00006383054,0.000036278438,0.00012991745,0.0005339987,0.0021604665],"genre_scores_gemma":[0.93629086,0.00040908367,0.057709023,0.00009652511,0.00004152071,0.00013180778,0.00027618944,0.00004866723,0.0049963538],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997826,0.000034227527,0.000013373993,0.00007495812,0.000062388186,0.00003254084],"domain_scores_gemma":[0.9997814,0.00006810664,0.00002436917,0.00001630707,0.00010056565,0.000009238456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041357725,0.0006157221,0.00058442005,0.00054193725,0.00021088487,0.00059635635,0.0013748594,0.00063494913,0.0015984571],"category_scores_gemma":[0.0009278693,0.0003220485,0.0006269723,0.00056502194,0.0002984153,0.0008834069,0.00049368734,0.00074211205,0.00030122313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008223779,0.00004606892,0.00090864196,0.00006428772,0.00005725982,0.000054017073,0.000028137583,0.9206351,0.0046695215,0.002021203,0.0007758392,0.07065764],"study_design_scores_gemma":[0.0000012331326,0.0000045963834,0.00006157275,0.0000010969299,0.0000029119449,0.0000037905684,8.4445463e-7,0.99945706,0.0002020642,0.00020379451,0.00005976088,0.0000012645636],"about_ca_topic_score_codex":0.011456899,"about_ca_topic_score_gemma":0.008282397,"teacher_disagreement_score":0.011456899,"about_ca_system_score_codex":0.000686368,"about_ca_system_score_gemma":0.0005828292,"threshold_uncertainty_score":0.022780418},"labels":[],"label_agreement":null},{"id":"W3008869636","doi":"10.3390/jmmp4010016","title":"A Unique Methodology for Tool Life Prediction in Machining","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Rake; Flank; Machining; Tool wear; Face (sociological concept); von Mises yield criterion; Calibration; Finite element method; Computer science; Function (biology); Materials science; Mechanical engineering; Structural engineering; Mathematics; Engineering; Statistics","score_opus":0.03854059991764456,"score_gpt":0.2686314966079568,"score_spread":0.23009089669031227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008869636","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025292027,0.000108412605,0.99647397,0.000008933273,0.000015612019,0.000021697373,0.000020220068,0.0002520503,0.00056990917],"genre_scores_gemma":[0.26950654,0.00060689833,0.7260192,0.000053498585,0.000051216794,0.00030659852,0.00027441292,0.00017762049,0.0030039637],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996685,0.000043119,0.000018587301,0.00007000012,0.00018337015,0.000016384412],"domain_scores_gemma":[0.99960274,0.00013275078,0.000050264993,0.00007492991,0.0001284377,0.000010894147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041236903,0.00063907506,0.000529481,0.00074055215,0.0002696115,0.00039196087,0.0009723605,0.00073322444,0.0011339989],"category_scores_gemma":[0.001053604,0.00033954237,0.0006310293,0.0005253347,0.00028810994,0.00067587895,0.00039978474,0.00067260436,0.00048658065],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031067222,0.00008413867,0.002425085,0.0005209657,0.00008188971,0.000116511364,0.00020235202,0.52897507,0.060919587,0.02053352,0.0014651988,0.38464466],"study_design_scores_gemma":[0.000003816816,0.00006289809,0.00051577244,0.000018270937,0.000010733343,0.00011868096,0.00001676295,0.98199975,0.008344094,0.0029667893,0.00592669,0.00001564517],"about_ca_topic_score_codex":0.0010002881,"about_ca_topic_score_gemma":0.0010131944,"teacher_disagreement_score":0.0011339989,"about_ca_system_score_codex":0.00021915685,"about_ca_system_score_gemma":0.0004025326,"threshold_uncertainty_score":0.0037936568},"labels":[],"label_agreement":null},{"id":"W3009338247","doi":"10.3390/app10051746","title":"An Analytical Approach to Cutter Edge Temperature Prediction in Milling and Its Application to Trochoidal Milling","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Aeronautical Science Foundation of China; National Natural Science Foundation of China","keywords":"Enhanced Data Rates for GSM Evolution; Milling cutter; Machining; Mechanical engineering; Engineering; Tool path; Cutter location; Engineering drawing","score_opus":0.01543211551591437,"score_gpt":0.24789298199964913,"score_spread":0.23246086648373476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009338247","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015762592,0.000482404,0.97951585,0.00009132772,0.00003933684,0.000041205552,0.000023489707,0.00036925732,0.0036745362],"genre_scores_gemma":[0.7872776,0.0013992913,0.20625421,0.00010885409,0.00006558606,0.00016499282,0.00006795369,0.00018147376,0.0044800215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996661,0.000050955397,0.0000126330015,0.00007343416,0.00015568324,0.00004128265],"domain_scores_gemma":[0.9995241,0.000206456,0.000049283168,0.000032120588,0.00017635386,0.000011651827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004710435,0.0007474048,0.00084476115,0.00085658435,0.00060781057,0.00076912326,0.0009467323,0.0011206703,0.0009116755],"category_scores_gemma":[0.001387043,0.0005852342,0.0009597258,0.0006069995,0.000617491,0.0006025281,0.00044335893,0.0010379406,0.00042423763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025861216,0.000055251043,0.00049739983,0.00011744083,0.0000151699305,0.00013445115,0.000103592356,0.93549544,0.02013584,0.008154027,0.0005549462,0.034710634],"study_design_scores_gemma":[0.0000015378841,0.000010350256,0.00007084634,0.0000056774197,0.0000027080844,0.000015376017,0.000007189248,0.9971718,0.001510879,0.00082494615,0.00037287068,0.0000057939374],"about_ca_topic_score_codex":0.005709477,"about_ca_topic_score_gemma":0.004508459,"teacher_disagreement_score":0.005709477,"about_ca_system_score_codex":0.0008703666,"about_ca_system_score_gemma":0.0011654595,"threshold_uncertainty_score":0.011352479},"labels":[],"label_agreement":null},{"id":"W3010401191","doi":"10.4028/www.scientific.net/msf.980.136","title":"Characters of Deformation and Surface Quality and Cutter Wearing at High-Speed Cutting","year":2020,"lang":"en","type":"article","venue":"Materials science forum","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Materials science; Chip; Brittleness; Surface roughness; Chip formation; Deformation (meteorology); Metallurgy; Welding; Ceramic; Cutting tool; Surface finish; Composite material; Machining; Mechanical engineering; Tool wear; Engineering","score_opus":0.016101158841203424,"score_gpt":0.2437790806874949,"score_spread":0.2276779218462915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010401191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99838614,0.000049523806,0.0012433097,0.000005532549,0.0000034372433,0.0000040612867,0.00003648277,0.000017163613,0.0002543445],"genre_scores_gemma":[0.99924314,0.0000144254045,0.0004416913,0.0000031646098,8.82097e-7,0.0000017427736,0.000045794073,0.000005648574,0.00024363729],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99970394,0.000019266256,0.000011100988,0.000046706515,0.00017130101,0.000047676895],"domain_scores_gemma":[0.9993175,0.00019820232,0.0001745688,0.000096038086,0.00017070163,0.000043063596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021113093,0.00018940562,0.00016609752,0.0002930036,0.0001642943,0.00021831741,0.00023473844,0.00040088367,0.001241251],"category_scores_gemma":[0.0006544583,0.00014629855,0.00030835276,0.00018160726,0.00024340244,0.00024342355,0.00013529856,0.00028750297,0.00011370483],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005247147,0.000073755786,0.03459322,0.00012979997,0.000035071855,0.00031412658,0.00031264627,0.003124688,0.944325,0.00009734947,0.00011780622,0.016351752],"study_design_scores_gemma":[0.000018485794,0.001766799,0.4256102,0.000011191774,0.000047696387,0.00089096813,0.00046834827,0.011479958,0.55865467,0.00014938143,0.00085382565,0.00004836228],"about_ca_topic_score_codex":0.00056857994,"about_ca_topic_score_gemma":0.0009984471,"teacher_disagreement_score":0.001241251,"about_ca_system_score_codex":0.00014171452,"about_ca_system_score_gemma":0.00006975247,"threshold_uncertainty_score":0.0041523576},"labels":[],"label_agreement":null},{"id":"W3010959093","doi":"10.1109/icmimt49010.2020.9041189","title":"Machining/machinability of Rene 65 superalloy for aerospace applications","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machinability; Superalloy; Machining; Materials science; Metallurgy; Surface roughness; Ultimate tensile strength; Tool wear; Creep; Surface finish; Composite material; Alloy","score_opus":0.012278660086314149,"score_gpt":0.22484517168365337,"score_spread":0.21256651159733922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010959093","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944666,0.0010290773,0.0021886744,0.000022716751,0.000011214388,0.000032678134,0.00015545964,0.00006711657,0.0020264403],"genre_scores_gemma":[0.9947153,0.00021427425,0.003165719,0.0000073719702,0.0000019047461,0.000015046967,0.00017160241,0.000024715471,0.0016841162],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99952435,0.000034042267,0.00003339259,0.000071030816,0.00029313253,0.000044125707],"domain_scores_gemma":[0.9996667,0.00004311477,0.00011166293,0.000042847107,0.000105524414,0.000030196887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050171296,0.00028601516,0.00024809406,0.00036204018,0.0001885796,0.00036225858,0.00045745654,0.00022482178,0.0009712267],"category_scores_gemma":[0.0005515618,0.00014444777,0.00023495294,0.00024295518,0.0002539827,0.0003662193,0.00024576986,0.00022437828,0.00021848275],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001434662,0.000026666596,0.0010129397,0.00020562917,0.000010288972,0.00013193201,0.00010847755,0.00069234485,0.99135536,0.00014714291,0.00009424639,0.006071524],"study_design_scores_gemma":[0.000014765166,0.0010417775,0.016216379,0.000016614355,0.000032272364,0.00032722406,0.00012499436,0.0027899654,0.97372276,0.000031084546,0.005661266,0.00002100888],"about_ca_topic_score_codex":0.001656742,"about_ca_topic_score_gemma":0.004607258,"teacher_disagreement_score":0.001656742,"about_ca_system_score_codex":0.00031396886,"about_ca_system_score_gemma":0.00030397013,"threshold_uncertainty_score":0.0032942295},"labels":[],"label_agreement":null},{"id":"W3019375674","doi":"10.3390/jmmp4020033","title":"Effect of Rack and Pinion Feed Drive Control Parameters on Machine Tool Dynamics","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Rack; Machine tool; Controller (irrigation); Computer science; Pinion; Control engineering; Engineering; Control (management); Mechanical engineering; Artificial intelligence","score_opus":0.004253734105550943,"score_gpt":0.21256955949328304,"score_spread":0.2083158253877321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3019375674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96564084,0.00037573837,0.03113124,0.000084137966,0.000027684806,0.000042631807,0.000075115,0.00039737538,0.002225219],"genre_scores_gemma":[0.99882,0.000032376625,0.0009435092,0.00000694089,9.1896754e-7,0.000007584267,0.000010367196,0.000015237163,0.00016301841],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99933416,0.0001477072,0.00004232665,0.000163704,0.0002284117,0.00008374941],"domain_scores_gemma":[0.9962304,0.0027393785,0.00041770237,0.00033978414,0.00023305256,0.000039695078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008050389,0.00051564176,0.00046535052,0.00033916224,0.0003206527,0.00071306987,0.00045859368,0.0007439066,0.0010676576],"category_scores_gemma":[0.0052049267,0.00039062306,0.00026041426,0.00025575171,0.0005393989,0.00066935335,0.00038649703,0.00050287135,0.00017901995],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024830718,0.00041101006,0.014961128,0.00080217386,0.00010948812,0.0009882159,0.0009030062,0.6530034,0.26489466,0.00088180834,0.00033060627,0.06023148],"study_design_scores_gemma":[0.000102979815,0.0013389848,0.022360321,0.000064521584,0.00008313648,0.000343655,0.0002065315,0.72246915,0.25133458,0.0002584775,0.0013558947,0.00008177563],"about_ca_topic_score_codex":0.0015978668,"about_ca_topic_score_gemma":0.001431749,"teacher_disagreement_score":0.0015978668,"about_ca_system_score_codex":0.0002982401,"about_ca_system_score_gemma":0.0004035481,"threshold_uncertainty_score":0.0042575},"labels":[],"label_agreement":null},{"id":"W3019913886","doi":"10.3390/app10082870","title":"An Unsupervised Regularization and Dropout based Deep Neural Network and Its Application for Thermal Error Prediction","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Department of Education of Liaoning Province","keywords":"Computer science; Artificial neural network; Artificial intelligence; Heavy duty; Regularization (linguistics); Machine learning; Compensation (psychology); Dropout (neural networks); Engineering","score_opus":0.01411537615629635,"score_gpt":0.23322389218607065,"score_spread":0.2191085160297743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3019913886","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02828258,0.00048562148,0.968922,0.00022308709,0.00005740836,0.000028667891,0.00006806147,0.0006903113,0.0012423039],"genre_scores_gemma":[0.8451001,0.0006023663,0.14816204,0.00017790688,0.00007217893,0.00012987774,0.00032273322,0.00009054683,0.00534235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968815,0.000059099773,0.000019942836,0.00009111225,0.00010683293,0.00003494747],"domain_scores_gemma":[0.9995994,0.00012771177,0.000060964925,0.00004636525,0.0001464467,0.000019078921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084296515,0.00064386113,0.0005345357,0.00036631984,0.00032889203,0.00041781593,0.0010598849,0.00083674514,0.00069911394],"category_scores_gemma":[0.001458884,0.00035793826,0.000579704,0.00050705817,0.0004641272,0.00093607145,0.0007156146,0.0012607168,0.00017383596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013461521,0.000100270205,0.0016210215,0.00008564983,0.000059906117,0.0000899311,0.000062722305,0.85330904,0.0117153935,0.0049367836,0.0017795386,0.12610511],"study_design_scores_gemma":[9.3446323e-7,0.0000067421443,0.00007353316,0.0000012411614,0.0000019438144,0.0000033715303,8.193482e-7,0.9988788,0.0006955195,0.00024172621,0.00009342485,0.0000019599981],"about_ca_topic_score_codex":0.008008394,"about_ca_topic_score_gemma":0.006809489,"teacher_disagreement_score":0.008008394,"about_ca_system_score_codex":0.0008396255,"about_ca_system_score_gemma":0.0010572306,"threshold_uncertainty_score":0.01592356},"labels":[],"label_agreement":null},{"id":"W3021553200","doi":"10.1016/b0-12-227055-x/00486-7","title":"FLOUR | Roller Milling Operations","year":2003,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian International Grains Institute","funders":"","keywords":"Roller mill; Manufacturing engineering; Materials science; Engineering drawing; Business; Engineering; Metallurgy; Grinding","score_opus":0.01007935263061588,"score_gpt":0.2151754308980249,"score_spread":0.20509607826740903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021553200","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008234423,0.012885411,0.036073335,0.00064161344,0.0007552297,0.000054289663,0.0004962797,0.0011525936,0.93970686],"genre_scores_gemma":[0.03788243,0.012056573,0.016897205,0.00022283824,0.00024194122,0.00003181888,0.0007438582,0.00041884586,0.9315044],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998386,0.000009248805,0.0000070729884,0.000031911317,0.000100920166,0.000012228185],"domain_scores_gemma":[0.99996257,0.0000086217715,0.000004069057,0.000008513268,0.000012854184,0.0000033691808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012019709,0.0008541755,0.0005503417,0.0006579116,0.0003516613,0.0019691987,0.0006042856,0.0006375135,0.05348336],"category_scores_gemma":[0.00013137548,0.00032986456,0.00024450844,0.001209656,0.00029718026,0.0011318523,0.0005546139,0.00092837156,0.022254316],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089439134,0.000105249856,0.00012061238,0.0004688144,0.00000859946,0.0001609754,0.00009744898,0.0021067655,0.022399183,0.05617971,0.058859304,0.8594039],"study_design_scores_gemma":[0.0000098531655,0.00007108434,0.0006376789,0.00010751148,0.0000065286636,0.00025582025,0.000043478434,0.0016725209,0.00785045,0.013361404,0.97597265,0.000010978172],"about_ca_topic_score_codex":0.0010278176,"about_ca_topic_score_gemma":0.0023022154,"teacher_disagreement_score":0.05348336,"about_ca_system_score_codex":0.0003421362,"about_ca_system_score_gemma":0.000309752,"threshold_uncertainty_score":0.17891967},"labels":[],"label_agreement":null},{"id":"W3024077606","doi":"10.1016/j.cirp.2020.04.047","title":"In-process digital twin estimation for high-performance machine tools with coupled multibody dynamics","year":2020,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear system; Actuator; Multibody system; Machine tool; Torque; Control theory (sociology); Multivariable calculus; Vibration; Process (computing); Coupling (piping); Control engineering; Computer science; Engineering; Mechanical engineering; Control (management); Artificial intelligence; Acoustics; Physics","score_opus":0.016672947967387795,"score_gpt":0.2635223199056019,"score_spread":0.24684937193821407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3024077606","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.069767386,0.00022000003,0.92746395,0.000069828864,0.000052366882,0.000023845012,0.000051332223,0.00035986584,0.001991482],"genre_scores_gemma":[0.8932204,0.00013642876,0.10398887,0.000028502353,0.000021140022,0.000024622872,0.00012189769,0.00006718259,0.0023909025],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975413,0.000040999697,0.000010600092,0.000061425635,0.00010615261,0.000026638538],"domain_scores_gemma":[0.99965394,0.00012580928,0.000052616142,0.000048064554,0.00009974758,0.000019781037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041271097,0.00052448886,0.00051685626,0.0005205999,0.00033922965,0.00074815704,0.0006187821,0.0005158067,0.0015275104],"category_scores_gemma":[0.0012652845,0.0002977821,0.00033605023,0.0005365187,0.00026688343,0.0011096157,0.0008723214,0.0005877821,0.00037333445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008409676,0.00023514392,0.007987112,0.00033892464,0.00012185948,0.00015225798,0.00019152858,0.44012755,0.07407617,0.0058031436,0.001669748,0.46845552],"study_design_scores_gemma":[0.000004418713,0.000032714386,0.00085547357,0.0000045844486,0.00000822917,0.00001846601,0.000011518534,0.99202526,0.005955864,0.00058933033,0.0004887426,0.000005508163],"about_ca_topic_score_codex":0.0016879307,"about_ca_topic_score_gemma":0.0025746846,"teacher_disagreement_score":0.0016879307,"about_ca_system_score_codex":0.00029484916,"about_ca_system_score_gemma":0.00056485855,"threshold_uncertainty_score":0.005110085},"labels":[],"label_agreement":null},{"id":"W3024960686","doi":"10.1007/s00170-020-05430-7","title":"Numerical study of flow and heat transfer of minimum quantity lubrication based nanofluid in a turning process using Inconel alloy","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Kuwait Foundation for the Advancement of Sciences","keywords":"Nanofluid; Volume fraction; Materials science; Inconel; Lubrication; Heat transfer; Finite volume method; Flow (mathematics); Mechanical engineering; Finite element method; Volume (thermodynamics); Metallurgy; Alloy; Mechanics; Nanoparticle; Composite material; Engineering; Thermodynamics; Structural engineering; Nanotechnology","score_opus":0.012904751778151306,"score_gpt":0.2602859984163926,"score_spread":0.2473812466382413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3024960686","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98673147,0.0002373492,0.00647571,0.00016353566,0.000047681908,0.00002609125,0.000049367132,0.000055485696,0.0062132822],"genre_scores_gemma":[0.99801815,0.000044748347,0.0010874108,0.000008183641,0.0000037547993,0.0000068619097,0.000015581953,0.0000047179974,0.0008105723],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991536,0.000016183849,0.0000045916413,0.000014395694,0.000023590112,0.000025806921],"domain_scores_gemma":[0.9996326,0.00023176543,0.000040012856,0.000018178322,0.00005049587,0.00002687602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020562689,0.00025531417,0.0006683261,0.00039507187,0.00091591966,0.0006784186,0.00044783615,0.0010455014,0.0011778409],"category_scores_gemma":[0.00073198695,0.00023918394,0.00050732144,0.00030489833,0.00076385145,0.00043388846,0.00029237042,0.00042015465,0.000073686635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005044869,0.00028574275,0.00469868,0.00023449256,0.000044921053,0.0007080968,0.00027198656,0.91487545,0.066392586,0.005802703,0.00040442945,0.0057764496],"study_design_scores_gemma":[0.00003637216,0.00013959678,0.0011985581,0.0000048061024,0.000010014256,0.00003220444,0.00005399569,0.9928356,0.0052903346,0.00017904713,0.0002077617,0.000011798968],"about_ca_topic_score_codex":0.010241398,"about_ca_topic_score_gemma":0.0049396516,"teacher_disagreement_score":0.010241398,"about_ca_system_score_codex":0.000681563,"about_ca_system_score_gemma":0.00067204086,"threshold_uncertainty_score":0.02036357},"labels":[],"label_agreement":null},{"id":"W3025018393","doi":"10.1016/j.cirp.2020.04.040","title":"Physics-based approach for predicting dissolution‒diffusion tool wear in machining","year":2020,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"Nanoscience and Nanotechnology Area of Advance, Chalmers Tekniska Högskola; Chalmers Tekniska Högskola; National Research Centre","keywords":"Machining; Dissolution; Carbide; Materials science; Diffusion; Nonlinear system; Tool wear; Mechanical engineering; Metallurgy; Engineering; Thermodynamics; Physics; Chemical engineering","score_opus":0.03564816054881861,"score_gpt":0.2673305912183026,"score_spread":0.231682430669484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3025018393","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09467257,0.00035963717,0.90069795,0.000062582345,0.00004184074,0.00013687843,0.00007671831,0.0004587648,0.0034929705],"genre_scores_gemma":[0.91441417,0.00033597968,0.08324044,0.000025683592,0.000028841005,0.00018145086,0.0000794881,0.000041021915,0.0016528341],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990153,0.00001301943,0.000004586716,0.000011824508,0.00006056166,0.000008501616],"domain_scores_gemma":[0.9998118,0.00009446033,0.0000208248,0.000018772007,0.000044964072,0.000009203018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022220524,0.00051227305,0.00050657603,0.0005789241,0.00024260543,0.00042081182,0.0009353533,0.00077499985,0.00069015234],"category_scores_gemma":[0.00054382044,0.0003682377,0.0005661972,0.00029805247,0.0003528469,0.00040423672,0.00027881537,0.00049890525,0.00013223274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019305928,0.000051083,0.00096337567,0.000055035296,0.000022755514,0.000060758273,0.000025469539,0.96782506,0.015225122,0.0020900692,0.00009966651,0.013562261],"study_design_scores_gemma":[0.0000028729148,0.000020480024,0.00036279575,0.0000012615479,0.0000030037766,0.000013599612,0.0000022591935,0.9980421,0.0010750487,0.0003445984,0.00012873381,0.0000030940118],"about_ca_topic_score_codex":0.0027202426,"about_ca_topic_score_gemma":0.0022875858,"teacher_disagreement_score":0.0027202426,"about_ca_system_score_codex":0.00045588764,"about_ca_system_score_gemma":0.0005929224,"threshold_uncertainty_score":0.0054088235},"labels":[],"label_agreement":null},{"id":"W3033106265","doi":"10.21062/ujep/x.2013/a/1213-2489/mt/13/2/226","title":"Development and applications of a rotating turning tool","year":2013,"lang":"en","type":"article","venue":"MANUFACTURING TECHNOLOGY","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Durability; Machining; Bearing (navigation); Mechanical engineering; Engineering; Process (computing); Oscillation (cell signaling); Quality (philosophy); Chip; Computer science; Manufacturing engineering; Artificial intelligence; Physics; Electrical engineering","score_opus":0.004284936899805255,"score_gpt":0.19706909639055045,"score_spread":0.1927841594907452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033106265","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27842396,0.014681897,0.66361487,0.00034773743,0.00068813027,0.0004417645,0.00022888344,0.002214011,0.039358813],"genre_scores_gemma":[0.65842193,0.0042958925,0.3298738,0.000081269965,0.00012820226,0.00010974099,0.00024829604,0.00012050105,0.0067203585],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99924743,0.000066492576,0.00005046188,0.00013610085,0.0004219138,0.00007756065],"domain_scores_gemma":[0.9994773,0.0000803248,0.00007032837,0.000120757875,0.00018864335,0.000062744264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006631122,0.00044531966,0.0004300425,0.0010540175,0.0002470439,0.0006066166,0.00079522165,0.0006609011,0.0018513747],"category_scores_gemma":[0.0007573875,0.00027409956,0.00044280395,0.000740693,0.00036055723,0.00039919748,0.00038414815,0.00044343693,0.001150431],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015890907,0.00010630078,0.001182797,0.0005860209,0.000022818782,0.00039093994,0.00013864948,0.0059502632,0.7375329,0.010928402,0.0009520306,0.24204996],"study_design_scores_gemma":[0.00014534495,0.0053713312,0.0106080035,0.00016905133,0.00016561613,0.003632214,0.00012641621,0.04371791,0.7562457,0.0035906301,0.17608458,0.00014325393],"about_ca_topic_score_codex":0.00034541913,"about_ca_topic_score_gemma":0.0003139632,"teacher_disagreement_score":0.0018513747,"about_ca_system_score_codex":0.00019171937,"about_ca_system_score_gemma":0.00043312318,"threshold_uncertainty_score":0.006193459},"labels":[],"label_agreement":null},{"id":"W3034035625","doi":"10.1007/s00170-020-05505-5","title":"Intelligent wood machining monitoring using vibration signals combined with self-organizing maps for automatic feature selection","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Waviness; Artificial neural network; Adaptive neuro fuzzy inference system; Machining; Vibration; Self-organizing map; Artificial intelligence; Engineering; Feature selection; Feature (linguistics); Perceptron; Multilayer perceptron; Tool wear; Computer science; Process (computing); Pattern recognition (psychology); Fuzzy logic; Mechanical engineering; Fuzzy control system; Acoustics","score_opus":0.010635425203911933,"score_gpt":0.2435058600473431,"score_spread":0.23287043484343117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034035625","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24761234,0.00062737515,0.748775,0.00007953218,0.00009483725,0.00004500838,0.00015179046,0.0012041047,0.0014099507],"genre_scores_gemma":[0.88102674,0.00016077058,0.11753094,0.000032848857,0.000030673276,0.000038460286,0.00014532267,0.000034902263,0.0009993537],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998574,0.000017940922,0.0000072644966,0.00004020433,0.00005443413,0.000022716853],"domain_scores_gemma":[0.9998604,0.000058025627,0.00001856828,0.000010929634,0.000043462256,0.0000085045995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018268179,0.00039345876,0.00035090512,0.0007626216,0.00017206959,0.00030894275,0.00032734984,0.0003078103,0.00047333472],"category_scores_gemma":[0.00033090395,0.0001732796,0.00034559504,0.00056776736,0.00011635235,0.00043132878,0.0002348918,0.0002698355,0.00015179128],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046578687,0.00028856948,0.004402214,0.00015324962,0.000110379246,0.00015051787,0.00010941911,0.031411484,0.23836043,0.00059620687,0.0019434309,0.7220082],"study_design_scores_gemma":[0.000017669397,0.00016168036,0.0163098,0.000008199693,0.000056635974,0.000121322104,0.000048413298,0.92372733,0.057743095,0.0007991734,0.0009822635,0.000024371167],"about_ca_topic_score_codex":0.00082418125,"about_ca_topic_score_gemma":0.0014665653,"teacher_disagreement_score":0.00082418125,"about_ca_system_score_codex":0.00009918006,"about_ca_system_score_gemma":0.00015677174,"threshold_uncertainty_score":0.0016387105},"labels":[],"label_agreement":null},{"id":"W3034938008","doi":"10.1007/s11665-020-04880-0","title":"Characterization of Shear Band Formation and Microstructure Evolution during Orthogonal Cutting of Ti-5553: Part I—Shear Angle, Strain and Strain Rate","year":2020,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Materials science; Microstructure; Shear (geology); Strain (injury); Shear band; Composite material; Strain rate","score_opus":0.00503596761913132,"score_gpt":0.17671757064275886,"score_spread":0.17168160302362753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034938008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99908054,0.000089793786,0.0004634768,0.0000043183386,0.0000026596522,0.0000025152256,0.00006505326,0.000007683257,0.00028395324],"genre_scores_gemma":[0.9991425,0.00004169723,0.00035568012,0.000004210082,9.425928e-7,0.00000271616,0.000112431335,0.0000060785424,0.00033378482],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99991715,0.0000057132834,0.0000061060155,0.000020485944,0.00003097663,0.000019518522],"domain_scores_gemma":[0.9997837,0.000047202564,0.00007743291,0.000019158879,0.000053974305,0.000018461957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015248891,0.00013158032,0.00016170577,0.00019617817,0.00012751928,0.0001973099,0.00013597551,0.00017026176,0.0008643331],"category_scores_gemma":[0.00025005252,0.00014929844,0.00013905569,0.0002026157,0.0002064831,0.00016773796,0.00008227546,0.00013822904,0.00009970986],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002292711,0.000016814023,0.0029081814,0.000017690012,0.000005341995,0.00003743101,0.00005156772,0.00025733456,0.9941638,0.000039122755,0.00003221995,0.002241126],"study_design_scores_gemma":[0.0000064914707,0.00024244135,0.08380286,0.0000032682185,0.000020696061,0.00009354277,0.00007560089,0.0030023013,0.91226196,0.000015851327,0.0004664328,0.000008472354],"about_ca_topic_score_codex":0.0017790673,"about_ca_topic_score_gemma":0.002331587,"teacher_disagreement_score":0.0017790673,"about_ca_system_score_codex":0.00019751603,"about_ca_system_score_gemma":0.0001904531,"threshold_uncertainty_score":0.003537476},"labels":[],"label_agreement":null},{"id":"W3035770528","doi":"10.1007/s00170-020-05450-3","title":"Tribological mechanisms of nano-cutting fluid minimum quantity lubrication: a comparative performance analysis model","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Academy of Scientific Research and Technology","keywords":"Lubrication; Materials science; Nano-; Machining; Abrasive; Cutting fluid; Tribology; Inconel; Nanoparticle; Tool wear; Carbon nanotube; Composite material; Lubricity; Metallurgy; Nanotechnology; Alloy","score_opus":0.02048964018471095,"score_gpt":0.2625921888197439,"score_spread":0.24210254863503294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035770528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60638696,0.0033988631,0.31896657,0.00060557603,0.0001265197,0.00015261002,0.00019923202,0.00022409114,0.069939554],"genre_scores_gemma":[0.9939314,0.00025829414,0.0018978096,0.000011855,0.0000094364805,0.00001983348,0.000022496728,0.000010362483,0.0038384842],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989724,0.000016839955,0.0000042938914,0.000015165002,0.000041834155,0.000024664316],"domain_scores_gemma":[0.9997584,0.000102656166,0.000036987494,0.000021258065,0.00006927448,0.000011433717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002914681,0.00031665328,0.0005539427,0.00062353833,0.00039594172,0.0007514492,0.001005493,0.00076276256,0.0031297007],"category_scores_gemma":[0.00077987753,0.00020332845,0.00058187894,0.0003592034,0.00045432392,0.0011635709,0.000313716,0.00031213812,0.00032019173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015877088,0.00010265498,0.0007260155,0.00020147211,0.00003194005,0.00014536243,0.00012049407,0.89569056,0.028925011,0.056240898,0.0006996147,0.016957264],"study_design_scores_gemma":[0.0000060004895,0.000034269,0.0003720562,0.0000024573594,0.000007961466,0.000016598262,0.0000138901405,0.9955627,0.0013203559,0.0023388683,0.0003200954,0.0000048313973],"about_ca_topic_score_codex":0.0029197661,"about_ca_topic_score_gemma":0.0013584527,"teacher_disagreement_score":0.0031297007,"about_ca_system_score_codex":0.00055055233,"about_ca_system_score_gemma":0.0004969519,"threshold_uncertainty_score":0.010469854},"labels":[],"label_agreement":null},{"id":"W3035906653","doi":"10.1177/1350650120933420","title":"Investigation of the role of tribolayer formation in improving drilling performance of Ti-6Al-4V using minimum quantity of lubrication","year":2020,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Lubrication; Materials science; Drilling; Tribology; Drilling fluid; X-ray photoelectron spectroscopy; Alloy; Machining; Metallurgy; Composite material; Chemical engineering; Engineering","score_opus":0.016744503405828823,"score_gpt":0.20576513804954574,"score_spread":0.18902063464371693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035906653","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979213,0.0005323789,0.0012757838,0.000016572327,0.0000065308186,0.0000072530715,0.000016161666,0.000021579066,0.00020249486],"genre_scores_gemma":[0.99646616,0.00020852638,0.0029639273,0.000006210943,0.0000025942397,0.0000059872914,0.000030226116,0.000006560883,0.00030983496],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980766,0.000031410633,0.00001907751,0.000026690366,0.0000693641,0.000045852637],"domain_scores_gemma":[0.99979216,0.000040935465,0.000071319424,0.000014761762,0.000060295315,0.000020548694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022028897,0.00022583519,0.0002631776,0.00028941268,0.00010519398,0.00031488916,0.0004042386,0.0002924758,0.00037817794],"category_scores_gemma":[0.0005462806,0.00013728629,0.000157701,0.00015088214,0.00015913314,0.00034434136,0.00020375756,0.00016886194,0.00010240262],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078349054,0.000012700805,0.00035063116,0.000073348114,0.0000029750215,0.000030538715,0.000023721781,0.00021380001,0.9966673,0.000026660204,0.000008138289,0.0025119241],"study_design_scores_gemma":[0.0000060374914,0.00039915793,0.001721509,0.000003544117,0.000008039558,0.00005380603,0.000022252469,0.0018329686,0.9954432,0.0000099957015,0.00049439084,0.0000050126987],"about_ca_topic_score_codex":0.00039301283,"about_ca_topic_score_gemma":0.00085807807,"teacher_disagreement_score":0.0004042386,"about_ca_system_score_codex":0.00014496864,"about_ca_system_score_gemma":0.00012149462,"threshold_uncertainty_score":0.0012651682},"labels":[],"label_agreement":null},{"id":"W3037922707","doi":"10.3390/met10060835","title":"Tool Performance Optimization While Machining Aluminium-Based Metal Matrix Composite","year":2020,"lang":"en","type":"article","venue":"Metals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"King Abdulaziz City for Science and Technology","keywords":"Metal matrix composite; Machining; Solver; Materials science; Composite number; Design of experiments; Matrix (chemical analysis); Fractional factorial design; Aluminium; Volume fraction; Composite material; Factorial experiment; Mechanical engineering; Computer science; Mathematical optimization; Engineering; Metallurgy; Mathematics","score_opus":0.014978307380308743,"score_gpt":0.22855098769939491,"score_spread":0.21357268031908616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037922707","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91378087,0.00023653323,0.078625135,0.000045449295,0.000011186947,0.000052962692,0.000095126416,0.00041529545,0.006737379],"genre_scores_gemma":[0.97881925,0.000056736208,0.020228723,0.000004391991,0.0000011416291,0.00002223687,0.00005602288,0.000040230996,0.0007713107],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997625,0.00003217664,0.000009871017,0.000039817052,0.000106499574,0.000049069593],"domain_scores_gemma":[0.99966586,0.00013712316,0.000066915425,0.000033162865,0.00008293481,0.000013926681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056497136,0.0008308799,0.00042056458,0.00052972836,0.00029734266,0.0005689749,0.00035845133,0.0005118245,0.0007227279],"category_scores_gemma":[0.00069147296,0.0002281466,0.00027602943,0.00042129666,0.00022824931,0.00024022427,0.00025084743,0.00024975918,0.00018699176],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019487466,0.00011917121,0.00151919,0.0001659723,0.00001984526,0.00011298829,0.00009154609,0.8369013,0.12649037,0.0005961783,0.00020858049,0.03358002],"study_design_scores_gemma":[0.000023883713,0.0006951455,0.0027642606,0.000009830783,0.000023598255,0.000047834095,0.0000594463,0.86491567,0.13006987,0.0004088922,0.00096331123,0.000018249966],"about_ca_topic_score_codex":0.0012978914,"about_ca_topic_score_gemma":0.0026005742,"teacher_disagreement_score":0.0012978914,"about_ca_system_score_codex":0.00049394433,"about_ca_system_score_gemma":0.00050922565,"threshold_uncertainty_score":0.0035838485},"labels":[],"label_agreement":null},{"id":"W3039179452","doi":"10.1016/j.precisioneng.2020.07.001","title":"Measurement of high-frequency milling forces using piezoelectric dynamometers with dynamic compensation","year":2020,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dynamometer; Machining; Control theory (sociology); Kalman filter; System of measurement; Noise (video); Mechatronics; Piezoelectricity; Compensation (psychology); Computer science; Mechanical engineering; Engineering; Control engineering; Acoustics; Control (management); Physics; Artificial intelligence","score_opus":0.013435799567981823,"score_gpt":0.20645059061060242,"score_spread":0.1930147910426206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3039179452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6889969,0.0007086953,0.30417055,0.0003074951,0.00019029745,0.00017768113,0.00041205625,0.0004977785,0.0045386166],"genre_scores_gemma":[0.88226,0.00027138635,0.11522156,0.00009456569,0.000038683156,0.00008820478,0.0001518251,0.000035911027,0.0018377372],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99908626,0.00010797422,0.000045145254,0.00012109827,0.0005768164,0.00006275836],"domain_scores_gemma":[0.99880433,0.0006080749,0.00013263957,0.000120876284,0.0002837903,0.000050356066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072514254,0.00043753645,0.0003788009,0.000697136,0.00031929335,0.0004988584,0.00051705854,0.0007298058,0.0010350711],"category_scores_gemma":[0.0013892786,0.00038165157,0.00014709939,0.000764591,0.00038362006,0.000752556,0.00039513817,0.0004379124,0.00024210376],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028154298,0.00010528412,0.004572453,0.00014283943,0.000025816022,0.000047850688,0.00009189325,0.0014463604,0.93351066,0.0006338918,0.00047068443,0.05867067],"study_design_scores_gemma":[0.00020042776,0.00067063165,0.056814983,0.000025275252,0.000065517954,0.0009554641,0.00011793108,0.058752496,0.87583476,0.0009228835,0.0055452487,0.00009429763],"about_ca_topic_score_codex":0.0005705549,"about_ca_topic_score_gemma":0.001272533,"teacher_disagreement_score":0.0010350711,"about_ca_system_score_codex":0.00030204645,"about_ca_system_score_gemma":0.0004369783,"threshold_uncertainty_score":0.0038349032},"labels":[],"label_agreement":null},{"id":"W3039350","doi":"10.1007/978-3-642-28768-8_56","title":"Variable Drive Frequency Effect on Spindle Dynamic Behavior in High Speed Machining","year":2012,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Interference (communication); Vibration; Bearing (navigation); Transient (computer programming); Critical speed; Reliability (semiconductor); Engineering; Process (computing); Structural engineering; Rotational speed; Mechanical engineering; Acoustics; Control theory (sociology); Materials science; Computer science; Physics; Electrical engineering","score_opus":0.005780184934609708,"score_gpt":0.22175699257001413,"score_spread":0.21597680763540442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3039350","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8887338,0.01222087,0.061775792,0.00016162715,0.0002046952,0.000020486988,0.00014576723,0.0005025913,0.036234327],"genre_scores_gemma":[0.98770636,0.0017892879,0.0028928705,0.000015214646,0.000034468398,0.0000043705786,0.000060211776,0.00009232142,0.007404781],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991465,0.000009843318,0.0000023602008,0.00001636858,0.000048007314,0.000008720723],"domain_scores_gemma":[0.99971026,0.00021255268,0.000023388076,0.000020898024,0.000027980652,0.0000048814227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010622639,0.00020519445,0.00028348496,0.00018596262,0.00016940801,0.00031045298,0.00030093035,0.0003464912,0.00324464],"category_scores_gemma":[0.00057954184,0.00019932314,0.00019624364,0.00030534662,0.00023786648,0.0003180635,0.00012716351,0.00022536778,0.0002976819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014274629,0.00013729838,0.0023849623,0.0007070579,0.000067274894,0.00061908545,0.00043901216,0.09332526,0.6998226,0.007236873,0.0018518303,0.1919812],"study_design_scores_gemma":[0.0001473031,0.0030603858,0.073868275,0.000164021,0.0003155667,0.002542096,0.00028033293,0.35490516,0.5209434,0.009870247,0.033716157,0.00018707747],"about_ca_topic_score_codex":0.0002740627,"about_ca_topic_score_gemma":0.00047616241,"teacher_disagreement_score":0.00324464,"about_ca_system_score_codex":0.00013693042,"about_ca_system_score_gemma":0.000057917365,"threshold_uncertainty_score":0.010854423},"labels":[],"label_agreement":null},{"id":"W3039458171","doi":"10.1115/1.4047703","title":"Fractional Calculus-Based Energy Efficient Active Chatter Control of Milling Process Using Small Size Electromagnetic Actuators","year":2020,"lang":"en","type":"article","venue":"Journal of vibration and acoustics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Robustness (evolution); Actuator; Vibration; Optimal control; Controller (irrigation); Robust control; Engineering; Vibration control; Control engineering; Active vibration control; Control system; Computer science; Mathematics; Control (management); Mathematical optimization; Acoustics; Artificial intelligence","score_opus":0.007888068336155124,"score_gpt":0.21814300169571477,"score_spread":0.21025493335955964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3039458171","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08148928,0.00043723694,0.91301435,0.000102030834,0.00007789059,0.000037119054,0.000012225621,0.00024138551,0.0045884727],"genre_scores_gemma":[0.98303854,0.000083935665,0.01597728,0.00001559489,0.000010128924,0.000016727236,0.0000052111745,0.000007211743,0.0008453741],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998037,0.000035612054,0.000010809747,0.000034413642,0.00009635413,0.000019066412],"domain_scores_gemma":[0.9997774,0.00009263656,0.0000467087,0.000017367707,0.000057366346,0.000008596384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038568396,0.0003087911,0.00039011007,0.00021728696,0.00026576745,0.0005091643,0.00049326185,0.00025337152,0.00070831366],"category_scores_gemma":[0.00053221564,0.00014550153,0.00028791444,0.00016226585,0.00041043578,0.00022916603,0.00023628626,0.00025383284,0.00006752138],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042817259,0.000117263466,0.000510206,0.0003346424,0.000076790835,0.00017804992,0.00017886206,0.72733104,0.15373625,0.01380162,0.0006921838,0.102614895],"study_design_scores_gemma":[0.000012813694,0.00009226493,0.0001886343,0.000003965335,0.000010410527,0.00001655128,0.000004359681,0.99245024,0.0063383584,0.0005101716,0.00036656327,0.0000057817347],"about_ca_topic_score_codex":0.001827514,"about_ca_topic_score_gemma":0.0014731152,"teacher_disagreement_score":0.001827514,"about_ca_system_score_codex":0.00036888898,"about_ca_system_score_gemma":0.00034830463,"threshold_uncertainty_score":0.0036337972},"labels":[],"label_agreement":null},{"id":"W3040018037","doi":"10.1115/1.4047625","title":"General Cutting Dynamics Model for Five-Axis Ball-End Milling Operations","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Key Research and Development Program of China Stem Cell and Translational Research; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"End milling; Machine tool; Ball (mathematics); Vibration; Mechanical engineering; Numerical control; Engineering; Computer science; Machining; Geometry; Acoustics; Mathematics; Physics","score_opus":0.011360595010685247,"score_gpt":0.22410857101305046,"score_spread":0.2127479760023652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040018037","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09509535,0.00053643726,0.8835497,0.00021169313,0.000075203585,0.00015987438,0.0004972662,0.00050095934,0.01937354],"genre_scores_gemma":[0.9656993,0.00040413448,0.017288746,0.00006238145,0.000019212759,0.00030411032,0.0003588892,0.000053626267,0.015809622],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981874,0.000028290067,0.000008779641,0.00004796459,0.000071068,0.000025126363],"domain_scores_gemma":[0.99982786,0.000055066015,0.000038647206,0.000011864356,0.00005707265,0.000009419471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026346053,0.00076651,0.0007187116,0.00043403803,0.00037426004,0.00066968706,0.0013666201,0.0013917795,0.003589524],"category_scores_gemma":[0.00043548315,0.00035256564,0.0006983521,0.00031711612,0.0004826514,0.000629329,0.0005359754,0.00074275554,0.0007241909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021653952,0.000014235721,0.00031393796,0.00004268694,0.000009328394,0.000097504744,0.000049990358,0.99088985,0.0035372847,0.0019842593,0.00018365127,0.0028555903],"study_design_scores_gemma":[0.0000037943805,0.000010688267,0.00012293048,0.0000021892063,0.0000019322697,0.000012357337,0.000004381372,0.9991359,0.0001542754,0.00031761007,0.0002314725,0.00000242854],"about_ca_topic_score_codex":0.008493504,"about_ca_topic_score_gemma":0.0046254834,"teacher_disagreement_score":0.008493504,"about_ca_system_score_codex":0.00055224623,"about_ca_system_score_gemma":0.0005180293,"threshold_uncertainty_score":0.016888142},"labels":[],"label_agreement":null},{"id":"W3040456805","doi":"10.3390/s20133736","title":"Simultaneous Clamping and Cutting Force Measurements with Built-In Sensors","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Korea Institute of Machinery and Materials","keywords":"Clamping; Strain gauge; Machining; Lead zirconate titanate; Mechanical engineering; Piezoelectricity; Slippage; Materials science; Structural engineering; Engineering; Acoustics; Composite material; Electrical engineering; Physics","score_opus":0.01743247151018199,"score_gpt":0.2295628465806924,"score_spread":0.2121303750705104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040456805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50552744,0.0014022106,0.48678067,0.0001373736,0.00029435466,0.00021885816,0.0005046644,0.002123189,0.0030112078],"genre_scores_gemma":[0.73834884,0.00051544287,0.25759932,0.000119817814,0.00007744952,0.00021096577,0.00029752814,0.00009395151,0.0027366688],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980096,0.00013383757,0.000095528536,0.00037747205,0.001282261,0.00010132077],"domain_scores_gemma":[0.9988949,0.00032139104,0.00020596919,0.00018488173,0.00033357355,0.00005937012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087530253,0.0007402054,0.0009130047,0.0008772743,0.00027819324,0.00073088636,0.0011884351,0.0010545915,0.0009862027],"category_scores_gemma":[0.0016121046,0.00051871344,0.00032363698,0.0007873252,0.00034371935,0.0010291116,0.001070309,0.0006598224,0.00032361597],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001818232,0.00007648062,0.002699189,0.00014576892,0.000041456635,0.00006682825,0.00010148099,0.00081455533,0.9435789,0.00027056952,0.00025487805,0.051768165],"study_design_scores_gemma":[0.000046871806,0.0005296014,0.011179621,0.000019795865,0.00006349532,0.00050889666,0.00009985215,0.024075532,0.9603825,0.00024653383,0.0027842587,0.000062997584],"about_ca_topic_score_codex":0.000357543,"about_ca_topic_score_gemma":0.00088636513,"teacher_disagreement_score":0.0011884351,"about_ca_system_score_codex":0.00024954925,"about_ca_system_score_gemma":0.00032211083,"threshold_uncertainty_score":0.004629135},"labels":[],"label_agreement":null},{"id":"W3040483011","doi":"10.18280/mmep.070213","title":"Comparison of Regression Model with Multi-layer Perceptron Model While Optimising Cutting Force Using Genetic Algorithm","year":2020,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Perceptron; Computer science; Genetic algorithm; Regression analysis; Layer (electronics); Regression; Algorithm; Artificial intelligence; Machine learning; Artificial neural network; Mathematics; Statistics; Materials science","score_opus":0.07759055388590058,"score_gpt":0.27990939658002,"score_spread":0.20231884269411943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040483011","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40511674,0.002768869,0.5747482,0.0008948982,0.00020893372,0.00019726834,0.0002290947,0.0018053864,0.014030594],"genre_scores_gemma":[0.95131433,0.0006597349,0.043673784,0.000080062855,0.000023580924,0.0001522247,0.00022189114,0.000062229214,0.003812165],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994505,0.000187055,0.000044453573,0.00012240733,0.00011563085,0.000079951824],"domain_scores_gemma":[0.99907887,0.0005855398,0.00008595037,0.00003247613,0.00019280199,0.000024240917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001412863,0.0012755546,0.001177177,0.0008901937,0.00038525072,0.0011770462,0.0010529491,0.0014363854,0.0020496382],"category_scores_gemma":[0.001875831,0.00044079468,0.0011878856,0.0008353716,0.00030367033,0.00082227786,0.0003455135,0.00093965913,0.00040805226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011887885,0.00008333502,0.0013135313,0.000115965006,0.00007266475,0.000074597665,0.000051654406,0.9692383,0.0015475395,0.000445627,0.00030292402,0.02663498],"study_design_scores_gemma":[0.0000071701165,0.00006709208,0.0003497216,0.0000065638874,0.000013860451,0.000010037868,0.000009307099,0.9987392,0.0005245227,0.00013040777,0.00013625,0.00000596758],"about_ca_topic_score_codex":0.018511692,"about_ca_topic_score_gemma":0.0088135665,"teacher_disagreement_score":0.018511692,"about_ca_system_score_codex":0.0007450897,"about_ca_system_score_gemma":0.00091649225,"threshold_uncertainty_score":0.036807895},"labels":[],"label_agreement":null},{"id":"W3041393592","doi":"10.1177/0954405420937502","title":"On the impacts of cutting parameters on surface roughness, tool wear mode and size in slot milling of A356 metal matrix composites reinforced with silicon carbide elements","year":2020,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Materials science; Machinability; Silicon carbide; Composite material; Machining; Surface roughness; Ceramic; Metal matrix composite; Composite number; Abrasion (mechanical); Lubrication; Carbide; Tool wear; Metallurgy","score_opus":0.007206583587639739,"score_gpt":0.20890807429229594,"score_spread":0.2017014907046562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041393592","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993569,0.00020596093,0.0003042431,0.000003952589,0.000003151489,0.000003147146,0.00002650897,0.0000061163805,0.000090046335],"genre_scores_gemma":[0.9989396,0.00012046441,0.0006329455,0.0000045101942,0.0000017449314,0.000003284138,0.00004117765,0.000005326241,0.00025090398],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980646,0.000018081644,0.000021584296,0.00004369855,0.000082960156,0.000027238046],"domain_scores_gemma":[0.9991738,0.0003448627,0.00020001805,0.000042687832,0.0002010849,0.00003760214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022772606,0.00020008517,0.00025941982,0.00027256593,0.0001725895,0.00025420243,0.00015903923,0.00026387555,0.00052163604],"category_scores_gemma":[0.00057048694,0.00019331895,0.00032926758,0.00020883669,0.00016375331,0.00023955663,0.00013694359,0.0002667364,0.00012036707],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003762297,0.00006937665,0.004276047,0.00012325993,0.000017652948,0.00010590284,0.00014707277,0.0009305769,0.9876336,0.000011954029,0.000035522808,0.006272753],"study_design_scores_gemma":[0.000010026119,0.0035102055,0.10642443,0.000009946994,0.00006328212,0.00019595258,0.0003374903,0.005004448,0.88386303,0.000022839404,0.00052957074,0.00002876269],"about_ca_topic_score_codex":0.0006022083,"about_ca_topic_score_gemma":0.0019664948,"teacher_disagreement_score":0.0006022083,"about_ca_system_score_codex":0.00011326331,"about_ca_system_score_gemma":0.00006502383,"threshold_uncertainty_score":0.0017450452},"labels":[],"label_agreement":null},{"id":"W3042162832","doi":"10.1007/s12008-020-00662-z","title":"An integrated numerical study for using minimum quantity lubrication (MQL) when machining austempered ductile iron (ADI)","year":2020,"lang":"en","type":"article","venue":"International Journal on Interactive Design and Manufacturing (IJIDeM)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Machining; Coolant; Lubrication; Mechanical engineering; Materials science; Austempering; Cutting fluid; Heat transfer; Finite element method; Metallurgy; Engineering; Structural engineering; Mechanics; Microstructure","score_opus":0.04199758854316872,"score_gpt":0.3155288343709762,"score_spread":0.27353124582780747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042162832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7998291,0.0008116167,0.17969716,0.00020463928,0.00010121185,0.00014072581,0.00009780047,0.00019688395,0.018920733],"genre_scores_gemma":[0.97180444,0.00010716652,0.02667559,0.000015945083,0.000008310264,0.000025042493,0.000026690004,0.000025110938,0.0013116818],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998491,0.000029148614,0.000007908042,0.000023510436,0.00007108046,0.000019315252],"domain_scores_gemma":[0.9996283,0.00017406976,0.000054512035,0.000033049444,0.00009398682,0.000016049498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032491283,0.00023191649,0.00036365545,0.00031511497,0.00034721554,0.0006445791,0.00054485066,0.00059828145,0.0013082592],"category_scores_gemma":[0.0012956125,0.00018013739,0.0002918733,0.00024901662,0.00038389515,0.0004887408,0.0003281169,0.00026184734,0.000110829096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049469835,0.00057575956,0.0064992523,0.00053855963,0.00005366572,0.00028855843,0.00029237277,0.78988075,0.1443709,0.01265048,0.0005343073,0.043820772],"study_design_scores_gemma":[0.000012915934,0.00014954375,0.0005824917,0.000005518461,0.000010236695,0.000022805993,0.000023660623,0.9935103,0.00510146,0.00018413537,0.00039140275,0.0000055297874],"about_ca_topic_score_codex":0.002533325,"about_ca_topic_score_gemma":0.0021769528,"teacher_disagreement_score":0.002533325,"about_ca_system_score_codex":0.000341182,"about_ca_system_score_gemma":0.0004213883,"threshold_uncertainty_score":0.005037129},"labels":[],"label_agreement":null},{"id":"W3042305584","doi":"10.1007/s11771-020-4402-2","title":"Evaluation of surface roughness and optimization of cutting parameters in turning of AA2024 alloy under different cooling-lubrication conditions using RSM method","year":2020,"lang":"en","type":"article","venue":"Journal of Central South University","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Materials science; Surface roughness; Lubrication; Response surface methodology; Tool wear; Enhanced Data Rates for GSM Evolution; Metallurgy; Machining; Surface finish; Composite material; Mechanical engineering; Engineering; Computer science","score_opus":0.03562710494080325,"score_gpt":0.27188312912767,"score_spread":0.23625602418686675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042305584","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99413645,0.00030563085,0.004535317,0.0000199265,0.000013652574,0.000007946868,0.00006430371,0.000050711536,0.000866106],"genre_scores_gemma":[0.99574125,0.00008288794,0.003684309,0.0000037358113,0.0000022411032,0.000006095588,0.000053312713,0.00000776324,0.0004183027],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979013,0.00002051965,0.000013464984,0.00003397561,0.00011461216,0.00002730866],"domain_scores_gemma":[0.9997255,0.000092863855,0.000044693898,0.000023182422,0.00010292294,0.000010801997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002549364,0.00022972915,0.00035841102,0.00035131833,0.00023459435,0.00029736196,0.00024861807,0.00036307846,0.00058527605],"category_scores_gemma":[0.00036840257,0.00018677043,0.0003638404,0.00032726716,0.00017921397,0.00020643092,0.00009881247,0.00019688388,0.000086165404],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003921752,0.00006528765,0.0030218516,0.00021146923,0.000022294264,0.00011076999,0.00012573726,0.009740039,0.97106296,0.00021072637,0.0001519904,0.014884546],"study_design_scores_gemma":[0.000018784756,0.00082298275,0.034888748,0.000007914089,0.0000654845,0.000118656404,0.00018241508,0.07146694,0.8913753,0.00008890167,0.0009246534,0.000039158185],"about_ca_topic_score_codex":0.0013416562,"about_ca_topic_score_gemma":0.002550307,"teacher_disagreement_score":0.0013416562,"about_ca_system_score_codex":0.0001749891,"about_ca_system_score_gemma":0.00016415634,"threshold_uncertainty_score":0.0026676655},"labels":[],"label_agreement":null},{"id":"W3043266634","doi":"10.1139/tcsme-2020-0030","title":"Research on the relationship between turning temperature rising and turning vibration based on particle swarm optimization","year":2020,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Jiangsu Normal University; Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"Particle swarm optimization; Vibration; Acceleration; Engineering; Turning point; Control theory (sociology); Mathematics; Computer science; Acoustics; Artificial intelligence; Algorithm; Physics","score_opus":0.0421721151091124,"score_gpt":0.2660420950263486,"score_spread":0.22386997991723623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043266634","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.253035,0.0007149709,0.7430578,0.0002998486,0.000074827934,0.00008564327,0.000044881544,0.00024042212,0.0024465988],"genre_scores_gemma":[0.96502864,0.00054832676,0.03315037,0.000036273774,0.000029073395,0.00008451409,0.00008632263,0.000025490506,0.0010110191],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995284,0.0001034827,0.000028003082,0.00012632787,0.00015633693,0.000057467583],"domain_scores_gemma":[0.9990025,0.0006654238,0.00010331488,0.000026637354,0.0001711379,0.000030893803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011112182,0.0009459556,0.0010102893,0.0008486446,0.00035400124,0.0008448863,0.0006693706,0.0006889445,0.00049008644],"category_scores_gemma":[0.0026702706,0.0005849701,0.0007783192,0.00083050155,0.0004377559,0.0008860704,0.0003442132,0.00074137835,0.000069837595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042654472,0.00007253494,0.0068011275,0.000090616115,0.00010217727,0.000063911946,0.00007133551,0.9643784,0.0026452984,0.0017550361,0.00021039584,0.023766445],"study_design_scores_gemma":[0.0000023351633,0.000019547982,0.0010005531,0.0000022331851,0.000009175228,0.000004833917,0.0000074017676,0.99850345,0.00022055309,0.00018727133,0.00003944096,0.0000032231803],"about_ca_topic_score_codex":0.012694845,"about_ca_topic_score_gemma":0.0046285996,"teacher_disagreement_score":0.012694845,"about_ca_system_score_codex":0.00046134787,"about_ca_system_score_gemma":0.0009955101,"threshold_uncertainty_score":0.025241911},"labels":[],"label_agreement":null},{"id":"W3043735498","doi":"10.1115/1.4047391","title":"Chatter Stability of Machining Operations","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":169,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Science Foundation of Sri Lanka; Natural Sciences and Engineering Research Council of Canada; American Research Institute in Turkey","keywords":"Machining; Stability (learning theory); Engineering; Coupling (piping); Process (computing); Computer science; Mechanical engineering; Control theory (sociology); Artificial intelligence","score_opus":0.011859603919809406,"score_gpt":0.21216284039496885,"score_spread":0.20030323647515946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043735498","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.113626,0.0016635386,0.8599357,0.00029798507,0.00011383313,0.000046421286,0.00006267158,0.0003690602,0.023884844],"genre_scores_gemma":[0.9808781,0.0004275193,0.013437407,0.00004463077,0.000046199526,0.000033256725,0.000039316867,0.00003855839,0.005055015],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99932015,0.00012450918,0.000026960175,0.00013676524,0.00033659185,0.00005513414],"domain_scores_gemma":[0.9985983,0.0006794771,0.00022580933,0.00015353723,0.00030652015,0.000036376936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006625758,0.00045841356,0.00051402533,0.00048554008,0.00023638294,0.0009163513,0.0006524928,0.0003962965,0.0026300251],"category_scores_gemma":[0.0028076903,0.00014473908,0.00033054894,0.00022448676,0.0011062388,0.00084927963,0.00059563835,0.0007476581,0.00035608778],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035125762,0.00007406889,0.0024858192,0.0004956054,0.0000819227,0.0004798916,0.0008082127,0.43243748,0.07849744,0.4134952,0.0017127985,0.06908033],"study_design_scores_gemma":[0.000009086569,0.000099487566,0.00076711783,0.000026009202,0.000007613619,0.00013336581,0.000056820914,0.93145216,0.0072221886,0.058395717,0.0018129889,0.000017452561],"about_ca_topic_score_codex":0.0010545804,"about_ca_topic_score_gemma":0.00044106581,"teacher_disagreement_score":0.0026300251,"about_ca_system_score_codex":0.00059653143,"about_ca_system_score_gemma":0.000367623,"threshold_uncertainty_score":0.008798301},"labels":[],"label_agreement":null},{"id":"W3048247683","doi":"10.1115/1.4048001","title":"Online Chatter Detection for Milling Operations Using LSTM Neural Networks Assisted by Motor Current Signals of Ball Screw Drives","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Artificial neural network; Vibration; Ball screw; Deflection (physics); Ball (mathematics); Engineering; Machine tool; Control theory (sociology); Computer science; Mechanical engineering; Acoustics; Artificial intelligence; Control (management); Mathematics","score_opus":0.019464740175615225,"score_gpt":0.2504926280155255,"score_spread":0.2310278878399103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3048247683","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46367988,0.0012623256,0.5278409,0.00032023914,0.00025587864,0.000108365515,0.00013905983,0.0026865355,0.0037067828],"genre_scores_gemma":[0.98092127,0.00007306513,0.01819118,0.00003744082,0.000010477655,0.000032403663,0.000052477986,0.0000144519,0.00066718215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997186,0.000054232376,0.000023278122,0.00007003375,0.00009564768,0.000038169255],"domain_scores_gemma":[0.9993253,0.00032207856,0.00007245375,0.00003599749,0.00021662425,0.000027684806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006616867,0.00075536134,0.00045522608,0.0003942842,0.0002216107,0.0004589483,0.0006328117,0.00058694824,0.0010872466],"category_scores_gemma":[0.0015936345,0.00026852638,0.0003051019,0.00024511953,0.0002619185,0.00050139165,0.00030748558,0.00081127544,0.00021033346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012263686,0.00040828422,0.004556099,0.00039812404,0.0001400655,0.00021310206,0.00018750802,0.5025705,0.071994714,0.0008343956,0.0017556142,0.41571525],"study_design_scores_gemma":[0.0000036936924,0.000048528207,0.000385311,0.000003950441,0.0000062022573,0.000005974137,0.0000036097147,0.9952976,0.00410145,0.00006887974,0.000070861366,0.000003879737],"about_ca_topic_score_codex":0.0062659793,"about_ca_topic_score_gemma":0.006037916,"teacher_disagreement_score":0.0062659793,"about_ca_system_score_codex":0.00057028094,"about_ca_system_score_gemma":0.00041839547,"threshold_uncertainty_score":0.01245898},"labels":[],"label_agreement":null},{"id":"W3049740028","doi":"10.1007/s00170-020-05869-8","title":"Ultrafine particle emission during high-speed milling of hardened AISI 1045 steel","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Materials science; Enhanced Data Rates for GSM Evolution; Machining; Metallurgy; Hardened steel; Ceramic; Particle (ecology); Ultrafine particle; Particle size; Composite material; Engineering; Nanotechnology","score_opus":0.006934249915995447,"score_gpt":0.2196266543915005,"score_spread":0.21269240447550505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3049740028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988881,0.00010542504,0.00062566716,0.000010123529,0.0000063372336,0.0000043899413,0.00004127614,0.000011628498,0.00030705653],"genre_scores_gemma":[0.99856865,0.00004072628,0.00039288358,0.000008269597,0.0000034889943,0.0000029508942,0.00008473108,0.00000856334,0.0008898022],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979156,0.000019572808,0.000008412822,0.00004104098,0.000101089376,0.000038356542],"domain_scores_gemma":[0.9996313,0.00016758368,0.00006544646,0.000017138374,0.00009251682,0.000026089423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027648747,0.0002491045,0.0002818298,0.00040696724,0.00043110907,0.00035902436,0.00022998005,0.00045606846,0.0009387214],"category_scores_gemma":[0.0004298304,0.00016489098,0.0002828481,0.00023876947,0.00037538636,0.00027279655,0.00013313013,0.0003226296,0.00013789663],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008853838,0.000040026214,0.0026304943,0.000059286394,0.000019351059,0.00017353432,0.00019080567,0.0006142904,0.99240416,0.000043614687,0.000097159274,0.002841893],"study_design_scores_gemma":[0.000027226859,0.000558613,0.10169789,0.0000070372234,0.000023368812,0.00012327266,0.0001858052,0.0045903632,0.89202976,0.000038684913,0.00069583824,0.000022169628],"about_ca_topic_score_codex":0.0031466507,"about_ca_topic_score_gemma":0.004484187,"teacher_disagreement_score":0.0031466507,"about_ca_system_score_codex":0.0004869073,"about_ca_system_score_gemma":0.0001808528,"threshold_uncertainty_score":0.00625664},"labels":[],"label_agreement":null},{"id":"W3080976459","doi":"10.1177/0954405420949127","title":"Evaluating the sensitivity of acoustic emission signal features to the variation of cutting parameters in milling aluminum alloys: Part A: frequency domain analysis","year":2020,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Polytechnique Montréal; University of British Columbia","funders":"","keywords":"Acoustic emission; SIGNAL (programming language); Time domain; Acoustics; Signal processing; Frequency domain; Sensitivity (control systems); Materials science; Cutting tool; Chip formation; Machining; Computer science; Engineering; Electronic engineering; Tool wear; Physics; Telecommunications","score_opus":0.016176154854679707,"score_gpt":0.24464701829239266,"score_spread":0.22847086343771295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080976459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94360024,0.0010587646,0.054353643,0.00002439988,0.00001710857,0.000049082908,0.00010304525,0.00021368601,0.0005800816],"genre_scores_gemma":[0.98422664,0.00046273472,0.014688488,0.000018640776,0.000009323691,0.000037393376,0.0001813084,0.000030423455,0.00034504506],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99962544,0.000051189938,0.000025878886,0.000084860556,0.00018645704,0.000026102236],"domain_scores_gemma":[0.9981116,0.0013153998,0.00021307627,0.00010302733,0.00022851181,0.000028274106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079880795,0.00042068108,0.00034617423,0.0011409096,0.00011171145,0.00037396437,0.0003096236,0.00058252347,0.0005464293],"category_scores_gemma":[0.0024532953,0.00020182015,0.00035249707,0.0006225535,0.00033097147,0.00039544623,0.00022005259,0.00027335525,0.0001821485],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080393243,0.00019527138,0.016179334,0.0006897843,0.000107442545,0.00033176513,0.0003128282,0.028006587,0.81375396,0.00015884977,0.00013198228,0.13932821],"study_design_scores_gemma":[0.00003254035,0.0025883897,0.28061122,0.00007274099,0.00021983651,0.00101752,0.0005466496,0.15827805,0.55424166,0.00047605502,0.0017758094,0.00013949026],"about_ca_topic_score_codex":0.0005125131,"about_ca_topic_score_gemma":0.00044374185,"teacher_disagreement_score":0.0011409096,"about_ca_system_score_codex":0.000099391655,"about_ca_system_score_gemma":0.00009847486,"threshold_uncertainty_score":0.004224539},"labels":[],"label_agreement":null},{"id":"W3081900602","doi":"10.1115/1.4048267","title":"Minimizing Flute Engagement to Adjust Tool Orientation for Reducing Surface Errors in Five-Axis Ball End Milling Operations","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Industrial Technology Research Institute","keywords":"Machining; Ball (mathematics); End milling; Deflection (physics); Mechanical engineering; Cutting tool; Machine tool; Computer science; Engineering; Geometry; Mathematics; Optics","score_opus":0.01721835239572168,"score_gpt":0.24878334960358814,"score_spread":0.23156499720786647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081900602","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4705442,0.00017425232,0.52729493,0.000035752946,0.000009489583,0.000037478556,0.0000179082,0.00022893876,0.001657102],"genre_scores_gemma":[0.94778305,0.000035370962,0.05188386,0.000007428283,0.0000017468457,0.00001690475,0.00001759426,0.000025710771,0.00022833563],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997744,0.000042983844,0.000010815885,0.000036398735,0.000093494345,0.000041937943],"domain_scores_gemma":[0.9996662,0.00012822091,0.00008738163,0.000034778768,0.000064187014,0.000019220091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037176127,0.0005455857,0.00032836472,0.00030009518,0.00017436253,0.00042738733,0.00035588467,0.00039877777,0.0004338959],"category_scores_gemma":[0.00077493046,0.00019014064,0.00017693231,0.00018114016,0.00027475052,0.0003104879,0.00042877297,0.00031520965,0.00012273226],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003610996,0.00025338767,0.004310594,0.00014692397,0.000026260597,0.00011585381,0.00014558304,0.6061991,0.27227488,0.0015265231,0.00030586906,0.11433388],"study_design_scores_gemma":[0.000029513154,0.00048550498,0.0037872593,0.000012592603,0.000017945227,0.00006257929,0.00005425127,0.90731716,0.08686009,0.0006392856,0.0007113342,0.000022446664],"about_ca_topic_score_codex":0.0008301732,"about_ca_topic_score_gemma":0.0011689127,"teacher_disagreement_score":0.0008301732,"about_ca_system_score_codex":0.00020416733,"about_ca_system_score_gemma":0.00039619298,"threshold_uncertainty_score":0.0019660592},"labels":[],"label_agreement":null},{"id":"W3083570310","doi":"10.2316/j.2020.206-0449","title":"ROBUST ADAPTIVE CONTROL BASED ON MACHINE LEARNING AND NTSMC FOR WORKPIECE SURFACE-GRINDING ROBOT","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Grinding; Computer science; Robot; Surface grinding; Adaptive control; Surface (topology); Control (management); Artificial intelligence; Engineering; Mechanical engineering; Mathematics; Geometry","score_opus":0.018159177756974402,"score_gpt":0.23714800926386365,"score_spread":0.21898883150688925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083570310","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04302121,0.00040672562,0.9518576,0.00015478929,0.00010641861,0.00003791647,0.000022848062,0.0004943753,0.003898066],"genre_scores_gemma":[0.94839126,0.00012271934,0.048750434,0.000051970514,0.000041442057,0.000079184836,0.000038323724,0.000023316716,0.0025012444],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99969614,0.000047146423,0.00001679375,0.00008515567,0.000120708995,0.000034085188],"domain_scores_gemma":[0.9996897,0.00011463956,0.000048374983,0.000022576902,0.00011364019,0.000010988413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003979666,0.00039700148,0.00054530863,0.00020123506,0.00036390894,0.00038837883,0.0007588569,0.00045699129,0.0014012707],"category_scores_gemma":[0.0007063918,0.00021929815,0.0003489579,0.00020830292,0.00039890365,0.00035218956,0.00040773032,0.0005441401,0.00015004356],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021694884,0.00006765972,0.00061787,0.00018227888,0.00005584991,0.00009625706,0.00011387591,0.837653,0.02762419,0.0053578652,0.0010982424,0.1269161],"study_design_scores_gemma":[0.000006560205,0.000057135505,0.00016821655,0.0000027211618,0.000004632933,0.0000070148,0.0000028418544,0.9980065,0.0012228838,0.00026304924,0.00025487802,0.0000035765345],"about_ca_topic_score_codex":0.0092385495,"about_ca_topic_score_gemma":0.0077757337,"teacher_disagreement_score":0.0092385495,"about_ca_system_score_codex":0.00040901324,"about_ca_system_score_gemma":0.0007298875,"threshold_uncertainty_score":0.018369555},"labels":[],"label_agreement":null},{"id":"W3084173124","doi":"10.32393/csme.2020.1277","title":"An Oxley-based Force Model for Milling of Hardened Steel Using Indexable Milling Tools","year":2020,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering. Volume 3","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Materials science; Metallurgy; Engineering; Manufacturing engineering; Mechanical engineering","score_opus":0.028226679451036685,"score_gpt":0.2512100832130207,"score_spread":0.222983403761984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084173124","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043546516,0.0003646145,0.94155484,0.000081184044,0.0000657311,0.00008065657,0.0002152894,0.00032780445,0.013763353],"genre_scores_gemma":[0.8623804,0.00076929695,0.11365467,0.00008001891,0.00002666052,0.00020913086,0.000453835,0.000113860464,0.022312205],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998487,0.000012532941,0.0000071641916,0.000026876316,0.000091838796,0.0000128550255],"domain_scores_gemma":[0.99989665,0.00003197227,0.00002150233,0.000010429708,0.000034182172,0.00000527905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015291598,0.0005220496,0.00034292202,0.0003208591,0.00022276463,0.00048487846,0.00095133437,0.00052069145,0.0017303342],"category_scores_gemma":[0.00032918126,0.00019955286,0.00038373945,0.0002478699,0.00024482055,0.0005772166,0.0001883853,0.0004276659,0.00040214637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025973146,0.000025816456,0.0004453226,0.00007095887,0.0000109117,0.00010582656,0.00004013189,0.9563909,0.016913297,0.0060454602,0.0004308068,0.019494664],"study_design_scores_gemma":[0.0000047578424,0.000023010527,0.00024888274,0.0000026136295,0.0000034914708,0.000016234966,0.0000037789732,0.99729913,0.00097394665,0.00047779997,0.0009423669,0.0000040712594],"about_ca_topic_score_codex":0.014117403,"about_ca_topic_score_gemma":0.012324817,"teacher_disagreement_score":0.014117403,"about_ca_system_score_codex":0.00050260586,"about_ca_system_score_gemma":0.0007404199,"threshold_uncertainty_score":0.02807045},"labels":[],"label_agreement":null},{"id":"W3084290283","doi":"10.32393/csme.2020.113","title":"Development of a Kinematic Simulation Tool to Study Cylindrical Plunge Grinding","year":2020,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering. Volume 3","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Kinematics; Grinding; Computer science; Mechanical engineering; Engineering drawing; Engineering; Physics; Classical mechanics","score_opus":0.015207164584914359,"score_gpt":0.2533979431471987,"score_spread":0.23819077856228435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084290283","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028730733,0.0001015192,0.964669,0.000057141766,0.000047788824,0.00020978032,0.00022974366,0.0015585053,0.004395826],"genre_scores_gemma":[0.37587416,0.0005111052,0.61820006,0.000031103697,0.000026040483,0.0007354536,0.00070907094,0.00050857244,0.0034044022],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973935,0.0000365039,0.000015685107,0.00002667427,0.0001552081,0.000026617321],"domain_scores_gemma":[0.9994498,0.00023934679,0.00004664617,0.00006654322,0.00017107709,0.000026513659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006423928,0.000586769,0.0007296399,0.00043080136,0.00037759435,0.0005531025,0.0014094764,0.00082720496,0.002845248],"category_scores_gemma":[0.0013908454,0.0005049815,0.0005946576,0.0004537392,0.00029178202,0.00051425444,0.0005007588,0.00074777997,0.00053610775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003438437,0.000060222665,0.001227795,0.00010351127,0.000023704282,0.00012984622,0.000094290066,0.94606066,0.02236011,0.006501785,0.0005082744,0.022895496],"study_design_scores_gemma":[0.000013883918,0.000029983745,0.00016871447,0.0000060926704,0.0000039502806,0.000021707427,0.000008913121,0.99305564,0.003716534,0.00030596662,0.0026609944,0.000007668671],"about_ca_topic_score_codex":0.006053125,"about_ca_topic_score_gemma":0.004571377,"teacher_disagreement_score":0.006053125,"about_ca_system_score_codex":0.00044026325,"about_ca_system_score_gemma":0.001479883,"threshold_uncertainty_score":0.012035787},"labels":[],"label_agreement":null},{"id":"W3084321117","doi":"10.32393/csme.2020.1272","title":"3D Finite Element Simulation of Cutting Forces in Milling Hardened Steels","year":2020,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering. Volume 3","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Finite element method; Materials science; Mechanical engineering; Hardened steel; Metallurgy; Structural engineering; Engineering","score_opus":0.010116055152001107,"score_gpt":0.2286840631520815,"score_spread":0.2185680080000804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084321117","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38451305,0.0002002956,0.5972738,0.0001779856,0.000061434024,0.00010900335,0.000566503,0.0009046624,0.016193295],"genre_scores_gemma":[0.92964756,0.00014575155,0.06520178,0.0000401443,0.000006363495,0.00013589619,0.0002721868,0.00008367956,0.0044666165],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998666,0.000026292535,0.000007758292,0.000013997232,0.0000658644,0.000019476387],"domain_scores_gemma":[0.9997924,0.00009796535,0.000026153442,0.00002334801,0.000044084238,0.000016104805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002647798,0.00036756272,0.0004254038,0.00038478972,0.00032243866,0.0005243709,0.0006980507,0.0012144239,0.0020739262],"category_scores_gemma":[0.0006628335,0.00033294276,0.00048129517,0.00027715336,0.00044375792,0.00030788628,0.00039403263,0.00038404358,0.00038319317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002130425,0.000021799797,0.00068845577,0.000021332999,0.0000059274807,0.000052365165,0.000051938132,0.9892157,0.0051895333,0.0014399791,0.00009598729,0.0031957675],"study_design_scores_gemma":[0.0000030606948,0.000008804907,0.00020098788,0.000001963839,0.000001034443,0.000011054966,0.000006366485,0.998648,0.000693308,0.00014709511,0.0002754569,0.0000028658474],"about_ca_topic_score_codex":0.0073190047,"about_ca_topic_score_gemma":0.0057357857,"teacher_disagreement_score":0.0073190047,"about_ca_system_score_codex":0.00041797743,"about_ca_system_score_gemma":0.0006440596,"threshold_uncertainty_score":0.014552832},"labels":[],"label_agreement":null},{"id":"W3086383380","doi":"10.1007/s00170-020-06027-w","title":"Effect of turning environments and parameters on surface integrity of AA6061-T6: experimental analysis, predictive modeling, and multi-criteria optimization","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Surface integrity; Surface roughness; Response surface methodology; Machining; Residual stress; Central composite design; Residual; Lubrication; Design of experiments; Regression analysis; Mechanical engineering; Structural engineering; Engineering; Materials science; Composite material; Computer science; Mathematics; Algorithm; Statistics; Machine learning","score_opus":0.00898109875614018,"score_gpt":0.2635940265329377,"score_spread":0.2546129277767975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3086383380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981231,0.0001569073,0.0009938652,0.000015696949,0.0000136260205,0.0000044135068,0.00006651627,0.000030152647,0.0005955914],"genre_scores_gemma":[0.9993223,0.00004779059,0.00033657812,0.000003368697,0.0000010760156,0.0000017503876,0.00004277218,0.0000072692687,0.00023713773],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997316,0.000020764073,0.000013947375,0.000043624827,0.00011667307,0.00007339569],"domain_scores_gemma":[0.9995097,0.00019177857,0.000072887284,0.000057569352,0.00013236754,0.00003569834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003489572,0.00039217056,0.00047063548,0.0003542958,0.0003722954,0.0005418631,0.00032162535,0.000584945,0.0017805768],"category_scores_gemma":[0.0007857123,0.00018752222,0.00037721786,0.00040848332,0.00036594307,0.00040619713,0.00023929706,0.00039643663,0.00028406718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023742372,0.00025925157,0.0045701093,0.00019955648,0.000033435346,0.00025617282,0.0001329291,0.09231287,0.881553,0.0003898547,0.00034508854,0.017573463],"study_design_scores_gemma":[0.000021700565,0.0015024347,0.009532278,0.000009432675,0.00004802196,0.000075459786,0.00015566847,0.10877126,0.87910867,0.00013220917,0.0006066386,0.000036203794],"about_ca_topic_score_codex":0.0017825748,"about_ca_topic_score_gemma":0.0024468817,"teacher_disagreement_score":0.0017825748,"about_ca_system_score_codex":0.00026807692,"about_ca_system_score_gemma":0.00025371238,"threshold_uncertainty_score":0.00595659},"labels":[],"label_agreement":null},{"id":"W3087189602","doi":"10.1007/s00170-020-06049-4","title":"A smart tool wear prediction model in drilling of woven composites","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Drilling; Artificial neural network; Tool wear; Kriging; Support vector machine; Machine learning; Heuristic; Process (computing); Computer science; Artificial intelligence; Engineering; Structural engineering; Mechanical engineering; Machining","score_opus":0.007259926092976922,"score_gpt":0.21829636709294012,"score_spread":0.2110364409999632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087189602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66527873,0.0007042897,0.32889333,0.00014659954,0.00009230455,0.00005024627,0.00018801399,0.00068288116,0.003963633],"genre_scores_gemma":[0.99268496,0.000086805,0.0064185862,0.000009670124,0.0000052690802,0.000014329799,0.00004293419,0.000013526538,0.0007237397],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99993277,0.000010623331,0.0000046696077,0.000017445163,0.000020692356,0.000013829851],"domain_scores_gemma":[0.99970144,0.00015741026,0.000034996894,0.000020066842,0.00006752548,0.000018392817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023079327,0.0003640599,0.00063143176,0.0002655623,0.00022560943,0.0004914871,0.00058374787,0.000884681,0.00069016713],"category_scores_gemma":[0.0006128875,0.00037995644,0.00047255048,0.00023752495,0.0002474201,0.00040264986,0.00024896156,0.00040279632,0.00010463893],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003893552,0.000021050539,0.0006476493,0.000019349234,0.0000075862276,0.000038634545,0.000010906013,0.99287766,0.0016033187,0.00018348171,0.00007017174,0.0044812583],"study_design_scores_gemma":[0.0000010355157,0.0000059435824,0.00007816214,5.847266e-7,0.0000010006553,0.0000020148468,0.0000011352369,0.99974257,0.0001221026,0.000029892812,0.000014663936,8.8132344e-7],"about_ca_topic_score_codex":0.012998437,"about_ca_topic_score_gemma":0.008113277,"teacher_disagreement_score":0.012998437,"about_ca_system_score_codex":0.00021579854,"about_ca_system_score_gemma":0.0005274435,"threshold_uncertainty_score":0.025845528},"labels":[],"label_agreement":null},{"id":"W3088398675","doi":"10.1115/1.4048513","title":"Single Degree-of-Freedom Modeling of the Nonlinear Vibration Response of a Machining Robot","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Nonlinear system; Vibration; Revolute joint; Control theory (sociology); Stiffness; Engineering; Robot; Coupling (piping); Structural engineering; Mechanical engineering; Computer science; Acoustics; Physics; Constraint (computer-aided design); Artificial intelligence","score_opus":0.02215401895939584,"score_gpt":0.21990058477213206,"score_spread":0.19774656581273622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088398675","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43854576,0.00025029283,0.5540187,0.0001152056,0.00003425637,0.000081122525,0.00013066351,0.0004100555,0.0064140414],"genre_scores_gemma":[0.9923879,0.000060565806,0.00644158,0.000006824058,0.0000027697713,0.00003087042,0.000035648667,0.000007685032,0.0010261539],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987614,0.000025024829,0.0000068885324,0.000026454107,0.000047927013,0.000017476312],"domain_scores_gemma":[0.9998418,0.00006104046,0.00003393404,0.000023473478,0.000032465894,0.0000072482594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021162671,0.00042564998,0.00027006635,0.00021883028,0.0002304586,0.00027205137,0.0005204116,0.0006468953,0.0011542932],"category_scores_gemma":[0.0003896891,0.00018079676,0.00043254075,0.0001250986,0.00025063418,0.00022820185,0.00024076887,0.00035726157,0.00023834096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061938226,0.000045956647,0.0017403712,0.00007675239,0.000020268122,0.00012073258,0.0001340416,0.9480876,0.036523197,0.0010503847,0.00013955904,0.011999175],"study_design_scores_gemma":[0.000002053746,0.000027736918,0.00060727005,0.0000022274585,0.000002127784,0.000013368308,0.0000055639302,0.9980842,0.0010530142,0.00008078545,0.00011921692,0.0000025330066],"about_ca_topic_score_codex":0.0054531475,"about_ca_topic_score_gemma":0.003404563,"teacher_disagreement_score":0.0054531475,"about_ca_system_score_codex":0.000194854,"about_ca_system_score_gemma":0.00030461184,"threshold_uncertainty_score":0.0108428},"labels":[],"label_agreement":null},{"id":"W3090853371","doi":"10.1007/s00170-020-06144-6","title":"Prediction of cutting tool wear during a turning process using artificial intelligence techniques","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Queen's University","funders":"","keywords":"Adaptive neuro fuzzy inference system; Dynamometer; Tool wear; Process (computing); Flank; Engineering; Artificial neural network; Machining; Data acquisition; Cutting tool; Fuzzy logic; Mechanical engineering; Automotive engineering; Computer science; Artificial intelligence; Fuzzy control system","score_opus":0.019103149253947623,"score_gpt":0.2642311351922303,"score_spread":0.24512798593828267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090853371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9582643,0.00023235474,0.0404242,0.000029253315,0.00003630375,0.000020564345,0.000086585154,0.00019583516,0.00071061606],"genre_scores_gemma":[0.9975332,0.000038418915,0.002230657,0.0000022581642,0.0000028576242,0.000004164763,0.00004352026,0.0000041912276,0.00014075897],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991286,0.000009951223,0.0000073103593,0.000018768855,0.000033799246,0.000017307011],"domain_scores_gemma":[0.9992305,0.00048006186,0.000095860625,0.000036267946,0.00012312963,0.00003408189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020567336,0.00044222057,0.00046075258,0.0006936722,0.00024235272,0.00046016026,0.00027798722,0.0005425913,0.00037126898],"category_scores_gemma":[0.0007806356,0.00022841149,0.00040898245,0.00033666607,0.00017608456,0.00024662665,0.0001357532,0.0003844656,0.000085262225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001193251,0.00043129278,0.048033923,0.00021117069,0.00013216816,0.00062088214,0.00015162927,0.7912033,0.06418964,0.00029756222,0.00051240175,0.09302283],"study_design_scores_gemma":[0.0000051719912,0.00013947535,0.015157562,0.000003996209,0.000014776748,0.000048922182,0.00001958759,0.9799048,0.004518831,0.000115437855,0.00006254284,0.000009015065],"about_ca_topic_score_codex":0.0028644293,"about_ca_topic_score_gemma":0.0031884916,"teacher_disagreement_score":0.0028644293,"about_ca_system_score_codex":0.00019369791,"about_ca_system_score_gemma":0.00017950263,"threshold_uncertainty_score":0.005695522},"labels":[],"label_agreement":null},{"id":"W3090917381","doi":"10.1007/s00170-020-06130-y","title":"Sustainability assessment of cutting fluids for flooded approach through a comparative surface integrity evaluation of IN718","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Surface integrity; Machinability; Materials science; Lubrication; Machining; Superalloy; Cutting fluid; Surface roughness; Indentation hardness; Tool wear; Scanning electron microscope; Mineral oil; Metallurgy; Composite material; Microstructure","score_opus":0.045269735399531746,"score_gpt":0.35863161111099057,"score_spread":0.3133618757114588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090917381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98260385,0.00035021664,0.012400958,0.0000525997,0.000013796795,0.000052786836,0.00019979727,0.00004604914,0.00427993],"genre_scores_gemma":[0.9948388,0.00015481227,0.0039502606,0.000007693996,0.0000021659569,0.000022953518,0.00012600476,0.000010325025,0.00088699226],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988907,0.00013390312,0.000046602257,0.00010599915,0.0007247565,0.00009814478],"domain_scores_gemma":[0.9989208,0.00017565946,0.00016017283,0.00007544837,0.0006126254,0.000055230485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016469761,0.0004318381,0.0004476396,0.0021078535,0.00055175484,0.0017433164,0.00060167594,0.00090723066,0.0012884445],"category_scores_gemma":[0.001662868,0.00015690993,0.00065572665,0.0011690976,0.00059095514,0.0015874555,0.0010688814,0.00051720295,0.00019016385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020116775,0.0010764545,0.13513367,0.0010516649,0.00043670126,0.0010458927,0.0015786487,0.18782589,0.38403577,0.010978218,0.001397268,0.2734281],"study_design_scores_gemma":[0.0000903982,0.006148285,0.2000855,0.00020526315,0.00073541567,0.0006096525,0.0058043525,0.3412855,0.4195697,0.008626454,0.016651059,0.00018847919],"about_ca_topic_score_codex":0.0025210178,"about_ca_topic_score_gemma":0.0043715085,"teacher_disagreement_score":0.0025210178,"about_ca_system_score_codex":0.0010117915,"about_ca_system_score_gemma":0.0010186246,"threshold_uncertainty_score":0.008710146},"labels":[],"label_agreement":null},{"id":"W3092794716","doi":"10.3390/su12208462","title":"Environmental Analysis of Sustainable and Traditional Cooling and Lubrication Strategies during Machining Processes","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Lubrication; Vegetable oil; Machining; Molybdenum disulfide; Environmentally friendly; Environmental impact assessment; Environmental science; Materials science; Pulp and paper industry; Metallurgy; Composite material; Engineering; Food science; Chemistry","score_opus":0.006642739501711901,"score_gpt":0.2063200789425864,"score_spread":0.19967733944087449,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092794716","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98763895,0.0017273484,0.0038911235,0.00007867822,0.000016415668,0.000059441678,0.00048622486,0.0000367186,0.0060653156],"genre_scores_gemma":[0.996287,0.0009067908,0.0014238149,0.000021934953,0.0000035992812,0.00003340403,0.00025740475,0.00001202996,0.0010540764],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993486,0.00008430587,0.000025363765,0.00007148631,0.0003712401,0.00009900349],"domain_scores_gemma":[0.9996283,0.00010884565,0.000053253483,0.000015761047,0.00017922695,0.000014548963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058207806,0.00030578504,0.00027448504,0.000656366,0.00042470073,0.00078727346,0.00033261726,0.0005217521,0.0010473732],"category_scores_gemma":[0.00051362056,0.00013654474,0.00044647412,0.0004914398,0.00030883882,0.0006906425,0.00037658942,0.0003000889,0.000151644],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012966612,0.0004979442,0.0727214,0.0021510369,0.00017505878,0.0011253025,0.00069372216,0.06683728,0.7185242,0.004204846,0.0014223176,0.13035014],"study_design_scores_gemma":[0.000022793567,0.0020569938,0.11361917,0.0001214369,0.0001710638,0.00031429352,0.0015497254,0.059332833,0.80704874,0.0015348274,0.014156547,0.000071569106],"about_ca_topic_score_codex":0.004050331,"about_ca_topic_score_gemma":0.0060297404,"teacher_disagreement_score":0.004050331,"about_ca_system_score_codex":0.0010531382,"about_ca_system_score_gemma":0.0005311351,"threshold_uncertainty_score":0.008053541},"labels":[],"label_agreement":null},{"id":"W3093558803","doi":"10.1007/s00170-020-06254-1","title":"Tool wear monitoring system in belt grinding based on image-processing techniques","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Grinding; Tool wear; Abrasive; Machining; Image processing; Computer science; Artificial intelligence; Engineering; Mechanical engineering; Image (mathematics)","score_opus":0.007595307649401818,"score_gpt":0.24508189579702253,"score_spread":0.23748658814762072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093558803","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47970492,0.0016988324,0.5071028,0.00017336098,0.00023866445,0.00026477396,0.00060381676,0.005820882,0.0043919766],"genre_scores_gemma":[0.8315494,0.00043320764,0.16373919,0.00012162041,0.000065859545,0.00010279333,0.0003486285,0.00013493387,0.0035043752],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995938,0.000030179486,0.000018842069,0.0000875472,0.0002430506,0.000026548982],"domain_scores_gemma":[0.99945444,0.00012036764,0.00008343358,0.00006529431,0.00024640173,0.00003014358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003350325,0.0005665937,0.00062365097,0.00082653086,0.00027214398,0.00043933088,0.00089746545,0.0005796907,0.0019381791],"category_scores_gemma":[0.00055111357,0.00034448272,0.00026236687,0.00055872934,0.00017662856,0.0005833752,0.0003225684,0.0003631557,0.0004680808],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067246845,0.00018552686,0.0061491956,0.00032317743,0.0000453158,0.00016123329,0.00014696861,0.0017246029,0.7265851,0.00022294755,0.0017399333,0.2620435],"study_design_scores_gemma":[0.0001900261,0.0013021979,0.10349031,0.00006349097,0.0002941908,0.0017989811,0.00016084022,0.28325182,0.60032535,0.0005789081,0.008388968,0.00015490396],"about_ca_topic_score_codex":0.0008430262,"about_ca_topic_score_gemma":0.0019250197,"teacher_disagreement_score":0.0019381791,"about_ca_system_score_codex":0.00020852411,"about_ca_system_score_gemma":0.00033950323,"threshold_uncertainty_score":0.0064839125},"labels":[],"label_agreement":null},{"id":"W3093950640","doi":"10.1115/1.4048854","title":"Modeling the Dynamics of Five-Axis Machine Tool Using the Multibody Approach","year":2020,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multibody system; Machine tool; Vibration; Kinematics; Modal analysis; Finite element method; Control theory (sociology); Rigid body; Computer science; Modal; Degrees of freedom (physics and chemistry); Point (geometry); Engineering; Structural engineering; Mechanical engineering; Acoustics; Artificial intelligence; Physics; Mathematics","score_opus":0.01276198239766191,"score_gpt":0.22161526625484898,"score_spread":0.20885328385718707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093950640","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058952384,0.00021043513,0.9352941,0.00005014467,0.000020336392,0.000055939567,0.00007433276,0.00025249226,0.005089872],"genre_scores_gemma":[0.9387673,0.0003099174,0.056641694,0.00002539623,0.000014271844,0.00017281594,0.00010073652,0.00004906871,0.003918738],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998605,0.000034574947,0.0000086397895,0.000026171669,0.000051690346,0.00001840285],"domain_scores_gemma":[0.9998876,0.00003411569,0.000030900184,0.000015953663,0.000023021305,0.000008405778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002222777,0.00044540223,0.00042537213,0.00059904234,0.000336772,0.0005405214,0.00073186937,0.00078205846,0.0015992527],"category_scores_gemma":[0.0003199955,0.000352527,0.0006613006,0.00027895338,0.00042801112,0.00061364996,0.00046065598,0.00037128065,0.00039716467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012026488,0.000017007378,0.0004711701,0.000025912881,0.000013243616,0.00006908804,0.00004165074,0.985805,0.0054247947,0.003132572,0.000069377355,0.004918187],"study_design_scores_gemma":[0.0000016822315,0.000012411743,0.00013312243,0.0000030946699,0.000002116535,0.000009232601,0.0000052987025,0.9987771,0.00031663183,0.0003927127,0.0003445601,0.0000020634989],"about_ca_topic_score_codex":0.002742891,"about_ca_topic_score_gemma":0.0018543324,"teacher_disagreement_score":0.002742891,"about_ca_system_score_codex":0.00024871906,"about_ca_system_score_gemma":0.00037359007,"threshold_uncertainty_score":0.005453825},"labels":[],"label_agreement":null},{"id":"W3094137509","doi":"10.18280/i2m.190408","title":"Thermal Error Compensation of Spindle System of Computer Numerically Controlled Machine Tools Through Experiments and Modeling","year":2020,"lang":"en","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machine tool; Particle swarm optimization; Machining; Computer science; Artificial neural network; Compensation (psychology); Numerical control; Generalization; Backpropagation; Artificial intelligence; Grey relational analysis; Algorithm; Engineering; Mathematics; Mechanical engineering","score_opus":0.05068360985846526,"score_gpt":0.29304845302413285,"score_spread":0.2423648431656676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094137509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5518831,0.00078355364,0.4401813,0.0001949429,0.0000675487,0.00011975949,0.00010450191,0.0009318037,0.0057334485],"genre_scores_gemma":[0.9886658,0.00012074286,0.010644643,0.000006431287,0.0000036236486,0.000029985933,0.000023658426,0.000012070964,0.00049298524],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971765,0.00003551264,0.000016367227,0.00006249083,0.0001514002,0.000016684267],"domain_scores_gemma":[0.99966025,0.00012700947,0.000042353182,0.00004654516,0.00011835084,0.0000056114873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047334438,0.00035140727,0.00029237795,0.00028238952,0.00021282342,0.00037335185,0.00044856136,0.00043406925,0.00045847526],"category_scores_gemma":[0.0010636871,0.00015967652,0.00036380056,0.00022371052,0.0003150447,0.0005273857,0.00016033638,0.00027315388,0.00007082732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020704816,0.000108137116,0.0057639424,0.00047529943,0.000052211166,0.0001737157,0.00042925976,0.77726054,0.13841502,0.0032285491,0.0006341084,0.073252186],"study_design_scores_gemma":[0.000009113956,0.00010544055,0.0021416931,0.000007984397,0.0000133710555,0.000025460631,0.00001670007,0.97709376,0.019724812,0.00028125176,0.0005705114,0.000009940316],"about_ca_topic_score_codex":0.003907985,"about_ca_topic_score_gemma":0.0030234307,"teacher_disagreement_score":0.003907985,"about_ca_system_score_codex":0.00040689492,"about_ca_system_score_gemma":0.0003796038,"threshold_uncertainty_score":0.0077704787},"labels":[],"label_agreement":null},{"id":"W3094395907","doi":"10.37775/eis.2020.2.4","title":"On the sliding mode control for precision machining","year":2020,"lang":"en","type":"article","venue":"Mérnöki és Informatikai Megoldások","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Savaria (Canada)","funders":"Eusko Jaurlaritza","keywords":"Machining; Control theory (sociology); Robustness (evolution); Actuator; Miniaturization; Control engineering; Sliding mode control; Computer science; Mode (computer interface); Engineering; Mechanical engineering; Control (management); Nonlinear system; Physics; Artificial intelligence","score_opus":0.014182099740233274,"score_gpt":0.23391543562394693,"score_spread":0.21973333588371366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094395907","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023790158,0.03884972,0.8822848,0.0008410461,0.00128913,0.000075814,0.00006206352,0.00028215934,0.0525251],"genre_scores_gemma":[0.8623683,0.030297056,0.08043314,0.0005200036,0.00137641,0.00016849377,0.00012966672,0.00007142114,0.024635587],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99974257,0.000059317394,0.000012769893,0.000051848292,0.000118007134,0.000015491098],"domain_scores_gemma":[0.99989855,0.00004646612,0.0000087226945,0.000010633124,0.000030841227,0.000004719212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003358923,0.00046024384,0.00035685036,0.00029871732,0.00017919192,0.0006123462,0.00031956928,0.00047808667,0.0019823029],"category_scores_gemma":[0.00060583866,0.00009978329,0.00029060824,0.00041309002,0.0007293733,0.00060102827,0.00035341078,0.0009696392,0.00034247068],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027097878,0.00007872046,0.000625335,0.00073735294,0.0000738299,0.00028441317,0.00039803656,0.16975784,0.02969238,0.34666312,0.00503505,0.4463829],"study_design_scores_gemma":[0.000060680788,0.001303901,0.002593186,0.00035042837,0.00006916534,0.00038292378,0.00008155726,0.7005892,0.009245135,0.20187798,0.08336668,0.0000792735],"about_ca_topic_score_codex":0.0012752126,"about_ca_topic_score_gemma":0.00041067763,"teacher_disagreement_score":0.0019823029,"about_ca_system_score_codex":0.00029305133,"about_ca_system_score_gemma":0.00025734506,"threshold_uncertainty_score":0.006631434},"labels":[],"label_agreement":null},{"id":"W3096865813","doi":"10.3390/met10111459","title":"Experimental Characterization of Tool Wear Morphology and Cutting Force Profile in Dry and Wet Turning of Titanium Metal Matrix Composites (Ti-MMCs)","year":2020,"lang":"en","type":"article","venue":"Metals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Polytechnique Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Machinability; Materials science; Abrasion (mechanical); Lubrication; Machining; Composite material; Titanium; Tool wear; Metallurgy; Carbide; Titanium carbide; Tribology; Enhanced Data Rates for GSM Evolution; Titanium alloy; Alloy","score_opus":0.008664359551677488,"score_gpt":0.2386471335633843,"score_spread":0.2299827740117068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096865813","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99791616,0.00025108474,0.0012980681,0.0000076813685,0.000008040844,0.000012668314,0.00012150515,0.000029802026,0.00035492468],"genre_scores_gemma":[0.99716693,0.000116402734,0.0019699035,0.000009877431,0.0000036030922,0.000016566797,0.00012771568,0.000016857288,0.00057213474],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99969006,0.000017942897,0.000019099696,0.00006713072,0.0001549768,0.000050885814],"domain_scores_gemma":[0.99923754,0.00024224258,0.00015685885,0.00007677246,0.00024057046,0.000045985413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024597897,0.00023772253,0.0003140485,0.0004080443,0.00029663986,0.00022132817,0.0002348768,0.00045941363,0.00084688683],"category_scores_gemma":[0.00050480076,0.00020161648,0.00024435812,0.00031017372,0.0003331441,0.0001801075,0.0001635804,0.00029767453,0.00012059213],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018078518,0.00003937815,0.0022104841,0.00008961464,0.000006014701,0.00014799707,0.00032293945,0.0002628586,0.99270755,0.00002284331,0.000042728236,0.0039668027],"study_design_scores_gemma":[0.000010672346,0.0012030925,0.07273172,0.00001423158,0.000025446814,0.0003683582,0.00028350463,0.0025960316,0.9217744,0.000030206851,0.00093614316,0.000026206153],"about_ca_topic_score_codex":0.0009646487,"about_ca_topic_score_gemma":0.0022674731,"teacher_disagreement_score":0.0009646487,"about_ca_system_score_codex":0.00015542026,"about_ca_system_score_gemma":0.00011922555,"threshold_uncertainty_score":0.002833128},"labels":[],"label_agreement":null},{"id":"W3097491851","doi":"10.3390/ma13215011","title":"Machining of Titanium Metal Matrix Composites: Progress Overview","year":2020,"lang":"en","type":"review","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Polytechnique Montréal","funders":"","keywords":"Machining; Materials science; Tool wear; Grinding; Surface roughness; Chip formation; Adiabatic shear band; Titanium alloy; Metallurgy; Surface finish; Lubrication; Titanium; Composite material; Cutting tool; Shear (geology); Alloy","score_opus":0.0343419547927369,"score_gpt":0.3355540046326184,"score_spread":0.30121204983988153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3097491851","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0057908064,0.97537065,0.0080517,0.00035264352,0.0002925122,0.00005020887,0.00006027955,0.00010183283,0.009929338],"genre_scores_gemma":[0.020738382,0.96018475,0.013167068,0.00027254946,0.00058377185,0.000059024853,0.00025032446,0.000044424043,0.0046997233],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994735,0.00006647516,0.00005622166,0.00014235474,0.00018591806,0.000075525255],"domain_scores_gemma":[0.9993667,0.00019892392,0.00008629105,0.000039662456,0.00025676494,0.00005169271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015715514,0.0010396849,0.00078856194,0.0026491513,0.0004218889,0.0016603036,0.0010323382,0.0012517113,0.002639986],"category_scores_gemma":[0.00079636974,0.00082010444,0.00069385336,0.0027682737,0.00047040006,0.001858548,0.00080395455,0.0016867844,0.0017138395],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017396959,0.0004416997,0.0011600147,0.019022753,0.0001538775,0.00025918102,0.00041138128,0.003763372,0.034208734,0.009743958,0.009761727,0.9208993],"study_design_scores_gemma":[0.00002552329,0.001402952,0.0048263194,0.0031412095,0.0002204676,0.0019313822,0.00038255082,0.003984093,0.037312854,0.0032951473,0.9433696,0.00010782189],"about_ca_topic_score_codex":0.0019927314,"about_ca_topic_score_gemma":0.0015713456,"teacher_disagreement_score":0.0026491513,"about_ca_system_score_codex":0.0007611561,"about_ca_system_score_gemma":0.0013627368,"threshold_uncertainty_score":0.00883162},"labels":[],"label_agreement":null},{"id":"W3099548931","doi":"10.3390/ma13225236","title":"Numerical Modeling and Analysis of Ti6Al4V Alloy Chip for Biomedical Applications","year":2020,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"King Saud University","keywords":"Titanium alloy; Materials science; Machining; Chip; Shearing (physics); Chip formation; Flow stress; Mechanical engineering; Macro; Alloy; Structural engineering; Tool wear; Composite material; Metallurgy; Computer science; Engineering","score_opus":0.01637101307095152,"score_gpt":0.25738014946887994,"score_spread":0.24100913639792843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3099548931","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23692119,0.0012878616,0.7272722,0.000395599,0.0001547974,0.0001560664,0.00046126213,0.0008129149,0.032538187],"genre_scores_gemma":[0.8817841,0.00064803456,0.107353374,0.000058156103,0.000024934603,0.00022941812,0.00023672909,0.00010019517,0.00956505],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998741,0.000019302495,0.0000058951364,0.000013167301,0.000070666625,0.000016880213],"domain_scores_gemma":[0.99986136,0.00005036332,0.00002218453,0.000017803513,0.00003973586,0.00000861692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025738383,0.0003314906,0.0003377612,0.0003483214,0.0002736202,0.00059045095,0.0007229656,0.00076048,0.0015351139],"category_scores_gemma":[0.00049819454,0.00026675547,0.000395667,0.00028069093,0.00035906988,0.00021819815,0.00029831915,0.00021562373,0.00034516057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012943523,0.000011097641,0.00036379075,0.000043799693,0.000006864551,0.000058855912,0.000029585382,0.9788608,0.012478807,0.0029402163,0.00019667401,0.0049966117],"study_design_scores_gemma":[0.0000018650453,0.000010402021,0.00020736616,0.0000029760283,0.0000020952436,0.00001587311,0.000006222328,0.9975153,0.0011064723,0.00030734568,0.0008209985,0.000002990253],"about_ca_topic_score_codex":0.0036022642,"about_ca_topic_score_gemma":0.0028580558,"teacher_disagreement_score":0.0036022642,"about_ca_system_score_codex":0.00054624054,"about_ca_system_score_gemma":0.0009431855,"threshold_uncertainty_score":0.007162571},"labels":[],"label_agreement":null},{"id":"W3101228943","doi":"10.1007/s00170-020-06195-9","title":"Flooded drilling of Inconel 718 using graphene incorporating cutting fluid","year":2020,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Inconel; Drilling; Materials science; Cutting fluid; Graphene; Enhanced Data Rates for GSM Evolution; Superalloy; Drill; Composite material; Alloy; Deformation (meteorology); Metallurgy; Machining; Nanotechnology; Engineering","score_opus":0.012193489090678068,"score_gpt":0.23805599906226507,"score_spread":0.225862509971587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3101228943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99653685,0.00019216296,0.0012758655,0.00006184859,0.00003691313,0.000006379108,0.000073385876,0.00007183221,0.0017446459],"genre_scores_gemma":[0.995784,0.0000743928,0.002784952,0.000010925928,0.0000027902631,0.000004043345,0.00003137487,0.0000067156748,0.0013007829],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99989617,0.0000090522235,0.000005096768,0.000020423891,0.000046144483,0.000023122055],"domain_scores_gemma":[0.99989915,0.000025792111,0.000026132424,0.000016618387,0.000020827512,0.000011423032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000117340525,0.00019705026,0.00023487658,0.00026690835,0.00023882845,0.0002515168,0.0002699222,0.0005386796,0.0012796693],"category_scores_gemma":[0.00021728924,0.00014996476,0.00018843974,0.00021463199,0.00024927862,0.00043583615,0.00031360597,0.00026105987,0.00018131571],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004414294,0.000045545425,0.00067106774,0.00027961168,0.0000117793115,0.00044907915,0.00015668155,0.00481972,0.9813479,0.0005943298,0.0003683483,0.010814533],"study_design_scores_gemma":[0.000039053197,0.0009751334,0.003669045,0.000026635475,0.000020485404,0.00019669205,0.0002352776,0.017129384,0.97327685,0.00030203557,0.004078151,0.000051166237],"about_ca_topic_score_codex":0.0007282159,"about_ca_topic_score_gemma":0.0017817663,"teacher_disagreement_score":0.0012796693,"about_ca_system_score_codex":0.00016179137,"about_ca_system_score_gemma":0.00018621936,"threshold_uncertainty_score":0.0042809844},"labels":[],"label_agreement":null},{"id":"W3101934687","doi":"10.5267/j.esm.2020.5.005","title":"Methods of influence coefficients to evaluate stress and deviation distributions of parts under operating conditions - A review","year":2020,"lang":"en","type":"review","venue":"Engineering Solid Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Stress (linguistics); Materials science; Mechanics; Physics","score_opus":0.026367988992972387,"score_gpt":0.37737005659648304,"score_spread":0.35100206760351066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3101934687","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008055175,0.96167296,0.031586032,0.00019338045,0.00029451665,0.000058540387,0.00016819236,0.00009657239,0.0051243133],"genre_scores_gemma":[0.008617515,0.96428984,0.024310507,0.00014252501,0.00029985115,0.00010559678,0.00021377364,0.000059932143,0.001960389],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99852896,0.00022364501,0.00017304673,0.0002740318,0.0007552044,0.000045125405],"domain_scores_gemma":[0.99712986,0.0018341063,0.00024341991,0.00010974946,0.0006525929,0.00003032073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021012002,0.0017424736,0.002133859,0.00685379,0.00029376804,0.0014772515,0.0015993378,0.0010686085,0.0038285914],"category_scores_gemma":[0.0035228177,0.00076092687,0.0013420065,0.0059066657,0.0010305528,0.0020431245,0.0007133877,0.0012148075,0.001597863],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003283886,0.00008355298,0.00075761956,0.027437627,0.00020758023,0.00011612135,0.00013241054,0.0060824826,0.004119908,0.019570092,0.009993124,0.9314666],"study_design_scores_gemma":[0.000020985037,0.00025190102,0.00445998,0.009803337,0.000674579,0.0020168184,0.00020565996,0.009057522,0.00852104,0.016689181,0.9480351,0.00026392308],"about_ca_topic_score_codex":0.001905012,"about_ca_topic_score_gemma":0.0019824698,"teacher_disagreement_score":0.00685379,"about_ca_system_score_codex":0.00065175997,"about_ca_system_score_gemma":0.0013197063,"threshold_uncertainty_score":0.012807906},"labels":[],"label_agreement":null},{"id":"W3102515349","doi":"10.3390/ma13225092","title":"Evaluation of Self-Propelled Rotary Tool in the Machining of Hardened Steel Using Finite Element Models","year":2020,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Finite element method; Machining; Chip formation; Displacement (psychology); Mechanical engineering; Materials science; Hardened steel; Chip; Heat transfer; Tool wear; Heat flux; Structural engineering; Engineering; Mechanics; Metallurgy","score_opus":0.058506305818554497,"score_gpt":0.2704640585460748,"score_spread":0.21195775272752032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102515349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5971255,0.00035749772,0.39298782,0.00008734913,0.000027261562,0.00018377572,0.00016771953,0.00055124855,0.008511913],"genre_scores_gemma":[0.96292007,0.00012503356,0.03521369,0.000010287604,0.0000025987508,0.000102166174,0.00008243182,0.00003595236,0.001507731],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979097,0.00005652412,0.0000092058535,0.000020659214,0.0001039963,0.000018617611],"domain_scores_gemma":[0.9996259,0.00020741546,0.000043141798,0.000034621273,0.00007577734,0.000013039411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004526411,0.00049682544,0.0005125165,0.0003544605,0.00021573681,0.0005801392,0.0007047602,0.0011452112,0.0011976692],"category_scores_gemma":[0.0008481802,0.00033268926,0.000594035,0.00016546476,0.00028383112,0.00044955002,0.0002760534,0.00030723825,0.00023718324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003814393,0.000046571808,0.0005661261,0.000049198174,0.000011283629,0.000037047626,0.000044108863,0.9798458,0.01337335,0.00057657773,0.00004393196,0.005367775],"study_design_scores_gemma":[0.000003444076,0.000040045,0.00018684445,0.0000036208273,0.0000029652326,0.0000073940637,0.00000805164,0.9970696,0.002446154,0.000066106644,0.00016264072,0.0000031982775],"about_ca_topic_score_codex":0.0032199458,"about_ca_topic_score_gemma":0.0030534586,"teacher_disagreement_score":0.0032199458,"about_ca_system_score_codex":0.00045362962,"about_ca_system_score_gemma":0.00044813528,"threshold_uncertainty_score":0.0064023733},"labels":[],"label_agreement":null},{"id":"W3104564324","doi":"10.1115/detc2001/vib-21435","title":"Modeling and Chatter Suppression With Ultra-Precision in Dynamic Turning Metal Cutting Process","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Control theory (sociology); Displacement (psychology); Vibration; Machining; Controller (irrigation); Hysteresis; Process (computing); Machine tool; Computer science; Engineering; Mechanical engineering; Acoustics; Physics","score_opus":0.00537800669046827,"score_gpt":0.2388907421793894,"score_spread":0.23351273548892115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3104564324","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.109283045,0.0004072315,0.88763416,0.00009719528,0.000032518114,0.000021733287,0.000012973851,0.00024027907,0.0022708145],"genre_scores_gemma":[0.9915279,0.000090780195,0.007756545,0.000010558839,0.000006286706,0.000016609627,0.0000071373247,0.0000050148337,0.00057923264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971706,0.00006525948,0.000013382863,0.000051094736,0.00012399342,0.000029238698],"domain_scores_gemma":[0.99960774,0.0001716983,0.00007721716,0.00003785076,0.000095420066,0.000010098778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003731786,0.00038133064,0.00038712553,0.00021393773,0.00018517772,0.0004488255,0.00068650796,0.00049452024,0.0005037988],"category_scores_gemma":[0.0008010372,0.0002526505,0.00034301422,0.00013970892,0.00042736126,0.00042590674,0.00033780694,0.0004821403,0.00008156101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018411929,0.00004871999,0.0009024393,0.00015701618,0.00004832029,0.00029789557,0.00027474854,0.910074,0.051148824,0.009012211,0.0002090057,0.027642718],"study_design_scores_gemma":[0.0000065146055,0.000060564882,0.00018338264,0.0000031234592,0.0000067030364,0.000022429278,0.000005229728,0.997331,0.001791837,0.00042681352,0.00015902777,0.0000033939575],"about_ca_topic_score_codex":0.0032275794,"about_ca_topic_score_gemma":0.0016321237,"teacher_disagreement_score":0.0032275794,"about_ca_system_score_codex":0.00026322252,"about_ca_system_score_gemma":0.0002688043,"threshold_uncertainty_score":0.006417632},"labels":[],"label_agreement":null},{"id":"W3108160111","doi":"10.1088/1757-899x/973/1/012048","title":"Computational fluid dynamic model for machining using minimum quantity coolant","year":2020,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Coolant; Machining; Computational fluid dynamics; Mechanical engineering; Materials science; Heat transfer; Internal combustion engine cooling; Water cooling; Nuclear engineering; Mechanics; Environmental science; Engineering; Chemistry; Physics","score_opus":0.026590263969660622,"score_gpt":0.24980821858642377,"score_spread":0.22321795461676314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108160111","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28511238,0.0014802768,0.6548462,0.0012264595,0.00041936114,0.000513355,0.0014957252,0.000726426,0.054179836],"genre_scores_gemma":[0.95182717,0.00053874706,0.028059691,0.00011913801,0.00004708857,0.0007078419,0.00057812023,0.00007760647,0.018044641],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997377,0.00006385177,0.000011986471,0.000051967738,0.00008414203,0.000050330254],"domain_scores_gemma":[0.99958843,0.00021036711,0.000051710784,0.000016400094,0.00010907479,0.00002408679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033401034,0.0007840273,0.0010330688,0.0005999963,0.0008169366,0.0013866131,0.0011538826,0.002570554,0.0035531304],"category_scores_gemma":[0.0010835666,0.0005843833,0.0011227487,0.0004230703,0.0008398492,0.0006814,0.0006688212,0.0010027881,0.00040925914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021845584,0.000019215335,0.0003921248,0.000030238733,0.0000067663236,0.0000677361,0.000028484326,0.9956251,0.0012949064,0.001375811,0.00013580431,0.0010021126],"study_design_scores_gemma":[0.000004646435,0.000007660991,0.000081906044,0.0000025989775,0.000001594707,0.000005158574,0.00000515854,0.9993319,0.00016081559,0.00013918399,0.00025667765,0.0000026026335],"about_ca_topic_score_codex":0.02307584,"about_ca_topic_score_gemma":0.008142439,"teacher_disagreement_score":0.02307584,"about_ca_system_score_codex":0.0010588029,"about_ca_system_score_gemma":0.0016231278,"threshold_uncertainty_score":0.04588306},"labels":[],"label_agreement":null},{"id":"W3113986652","doi":"10.1177/1687814020984388","title":"Identifying optimal features for cutting tool condition monitoring using recurrent neural networks","year":2014,"lang":"en","type":"article","venue":"Advances in Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Prognostics; Artificial neural network; Feature selection; Artificial intelligence; Feature (linguistics); Computer science; Process (computing); Machine learning; Engineering; Condition monitoring; Pattern recognition (psychology); Tool wear; Population; Data mining; Machining","score_opus":0.010564283522245374,"score_gpt":0.284727559178274,"score_spread":0.27416327565602866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113986652","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.273352,0.00035820302,0.7247466,0.00009650076,0.000020754236,0.00005380026,0.00009553761,0.0005754201,0.00070118037],"genre_scores_gemma":[0.96163946,0.00006815708,0.037905734,0.000013163098,0.000008305782,0.000039003986,0.00009803431,0.000015722871,0.0002124001],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996582,0.00007190371,0.000033439417,0.00008963569,0.00009961482,0.000047155154],"domain_scores_gemma":[0.9992995,0.00032808445,0.00015939894,0.000049466595,0.00014485409,0.00001866238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009005196,0.000815629,0.0006787372,0.0009510303,0.00020387981,0.0005495182,0.00047759723,0.0006020367,0.0004149774],"category_scores_gemma":[0.002558206,0.00021218114,0.00051868847,0.00053816766,0.00026253477,0.0008187344,0.0003540841,0.0003784928,0.00012556156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003043753,0.00016912172,0.010848113,0.000114427705,0.00008990883,0.00026100953,0.00010954679,0.6749505,0.033399303,0.001352512,0.0005628442,0.27783835],"study_design_scores_gemma":[0.0000037744662,0.000045322526,0.0017613007,0.0000054801753,0.000014165533,0.000023003917,0.000010236861,0.99404573,0.003395608,0.00061692647,0.000070826514,0.000007578012],"about_ca_topic_score_codex":0.0017359921,"about_ca_topic_score_gemma":0.001679625,"teacher_disagreement_score":0.0017359921,"about_ca_system_score_codex":0.00035267658,"about_ca_system_score_gemma":0.0002983593,"threshold_uncertainty_score":0.0047624707},"labels":[],"label_agreement":null},{"id":"W3115868475","doi":"10.18280/rcma.305-607","title":"Prediction of Temperature During Machinability of Al2O3 Reinforced Al7075","year":2020,"lang":"en","type":"article","venue":"Revue des composites et des matériaux avancés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Materials science; Machining; Machinability; Composite material; Maximum temperature; Metallurgy; Thermodynamics","score_opus":0.033197353361533004,"score_gpt":0.2347897669819101,"score_spread":0.20159241362037708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3115868475","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99330103,0.00011075419,0.0059989146,0.000011616723,0.000007599341,0.0000091921875,0.00008882908,0.00009072692,0.00038135622],"genre_scores_gemma":[0.9987539,0.000049434584,0.0008501296,0.0000016856886,8.818788e-7,0.0000043039945,0.000062487656,0.000008623472,0.00026857786],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985194,0.000010995009,0.000007184837,0.00004331805,0.00006331916,0.000023312843],"domain_scores_gemma":[0.9997074,0.0001414732,0.000065318374,0.000015318818,0.000057750894,0.000012657583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019807293,0.00045103044,0.00025724474,0.00031845647,0.0001225295,0.00040206336,0.00029590123,0.0004433167,0.00038351747],"category_scores_gemma":[0.0005139217,0.00024757182,0.0004943412,0.00018920093,0.0001335208,0.00023937442,0.00011516024,0.00023569269,0.00016132228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001108608,0.0002253131,0.06601869,0.00031078458,0.00008491286,0.0004084666,0.00023740219,0.37752005,0.51718044,0.00012377604,0.00029749642,0.03648407],"study_design_scores_gemma":[0.000010703112,0.0007393431,0.06374966,0.000014397818,0.00006241513,0.00007971499,0.00011636775,0.73008704,0.20461656,0.00008215495,0.00040658074,0.000035039506],"about_ca_topic_score_codex":0.004052336,"about_ca_topic_score_gemma":0.0057072467,"teacher_disagreement_score":0.004052336,"about_ca_system_score_codex":0.00033710702,"about_ca_system_score_gemma":0.0001705056,"threshold_uncertainty_score":0.008057535},"labels":[],"label_agreement":null},{"id":"W3118692280","doi":"10.1007/s42452-020-03980-9","title":"Neuro-fuzzy based predictive model for cutting force in CNC turning process of Al–Si–Cu cast alloy using modifier elements","year":2021,"lang":"en","type":"article","venue":"SN Applied Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Adaptive neuro fuzzy inference system; Machining; Alloy; Materials science; Mechanical engineering; Process (computing); Fuzzy logic; Metallurgy; Control theory (sociology); Computer science; Fuzzy control system; Engineering; Artificial intelligence","score_opus":0.02650561579428809,"score_gpt":0.29028947662290866,"score_spread":0.2637838608286206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118692280","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.63098294,0.000675872,0.3562709,0.00022676075,0.00011490288,0.00010949336,0.00019190421,0.0004866768,0.010940553],"genre_scores_gemma":[0.99655354,0.00006412143,0.0022243536,0.000007495693,0.0000036715362,0.000030162735,0.000025196789,0.0000035861842,0.0010877921],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990726,0.000014105326,0.000004798034,0.00002139672,0.000037099024,0.000015366892],"domain_scores_gemma":[0.9998621,0.00005601468,0.000021767699,0.0000071797863,0.00004815073,0.0000047357203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002509534,0.0005284751,0.00046062542,0.0003204134,0.0003365987,0.000534363,0.0005345288,0.000694196,0.00085789413],"category_scores_gemma":[0.00037499255,0.00031578957,0.0004591849,0.00017325644,0.0002684749,0.00025706133,0.00016396158,0.0004645557,0.00012213195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053308642,0.000024121073,0.00058007153,0.00003559024,0.000015185965,0.00006985431,0.000025709312,0.98947734,0.0044627227,0.00031808784,0.000092784845,0.0048453235],"study_design_scores_gemma":[0.0000018030885,0.000014716935,0.00018858185,0.0000015485417,0.0000029689681,0.0000035992177,0.0000031427596,0.9992316,0.00046748892,0.000038134585,0.000044734996,0.0000016886321],"about_ca_topic_score_codex":0.022397354,"about_ca_topic_score_gemma":0.015565559,"teacher_disagreement_score":0.022397354,"about_ca_system_score_codex":0.0005602628,"about_ca_system_score_gemma":0.0005058687,"threshold_uncertainty_score":0.044533968},"labels":[],"label_agreement":null},{"id":"W3120374275","doi":"10.20965/ijat.2021.p0080","title":"Measurements of Non-Grinding Forces and Power","year":2021,"lang":"en","type":"article","venue":"International Journal of Automation Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Grinding; Grind; Dynamometer; Power (physics); Materials science; Grinding wheel; Mechanical engineering; Pulverizer; Mechanics; Composite material; Engineering; Physics","score_opus":0.007609436166155466,"score_gpt":0.26208259708399023,"score_spread":0.2544731609178348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120374275","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68030316,0.004300732,0.2740683,0.00020487123,0.0006704423,0.0012144338,0.0049492437,0.0020263055,0.032262538],"genre_scores_gemma":[0.79001325,0.0039352695,0.17443939,0.00021680478,0.00013245239,0.0011282929,0.0037667537,0.00079436816,0.025573462],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99683607,0.00010485737,0.00013567366,0.00041888864,0.0023668215,0.00013766308],"domain_scores_gemma":[0.99740404,0.0006233982,0.00028093133,0.0002942159,0.0012922126,0.00010510981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009222738,0.0013914906,0.00093518663,0.0021185018,0.0006356591,0.0007927517,0.0012108444,0.00064279826,0.0061807116],"category_scores_gemma":[0.0023386714,0.00050336536,0.0005319752,0.0016277746,0.00064826757,0.0011255693,0.0007505997,0.0010943725,0.0020120074],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017883953,0.00014840676,0.0028563708,0.00074119534,0.000037048267,0.00013508015,0.00025619997,0.0006502034,0.93956906,0.000748523,0.00091519783,0.05376386],"study_design_scores_gemma":[0.000025210684,0.00043054472,0.038783483,0.000054744956,0.000059976155,0.00022118025,0.00017377929,0.0075891013,0.9401058,0.00064886716,0.011840506,0.00006682878],"about_ca_topic_score_codex":0.00095377164,"about_ca_topic_score_gemma":0.002588441,"teacher_disagreement_score":0.0061807116,"about_ca_system_score_codex":0.00043526816,"about_ca_system_score_gemma":0.00060440635,"threshold_uncertainty_score":0.020676494},"labels":[],"label_agreement":null},{"id":"W3120640809","doi":"10.1007/s00170-020-06473-6","title":"Cutting tool temperature monitoring in circular sawing: measurement and multi-sensor feature fusion-based prediction","year":2021,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of British Columbia","funders":"","keywords":"Machining; Thermocouple; Rotational speed; Acoustic emission; Rotation (mathematics); Enhanced Data Rates for GSM Evolution; Mechanical engineering; Acoustics; Temperature measurement; Vibration; Process (computing); Cutting tool; Tool wear; Engineering; Computer science; Artificial intelligence; Electrical engineering","score_opus":0.010381353698757867,"score_gpt":0.23434034595965614,"score_spread":0.22395899226089827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120640809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73290515,0.0005707508,0.26474223,0.000115927076,0.00007083278,0.000020886715,0.00010068271,0.00042915464,0.0010443064],"genre_scores_gemma":[0.9928311,0.000068547975,0.006924239,0.000008269619,0.000006851539,0.0000033635692,0.000026186,0.0000066739567,0.00012470942],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998198,0.000017020802,0.0000072120797,0.000058445687,0.00007189216,0.000025609726],"domain_scores_gemma":[0.99972624,0.00011124493,0.00005578457,0.000023810066,0.00007063677,0.000012243848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023864477,0.0003186405,0.00043692667,0.00035779516,0.00016214102,0.00034494395,0.00041008627,0.00052277313,0.00025458398],"category_scores_gemma":[0.0004945976,0.00021908958,0.00030822871,0.0004746425,0.0002472529,0.00073207205,0.00024086691,0.00038950416,0.00010633869],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014706164,0.00044062253,0.032327786,0.00023007338,0.000102223035,0.0003021372,0.00022488953,0.1558679,0.51778543,0.0007502854,0.0009127025,0.28958532],"study_design_scores_gemma":[0.000009372905,0.0001138221,0.01657023,0.0000044647254,0.00002368121,0.00009452387,0.000026924095,0.9406706,0.042039916,0.0002525579,0.00017841649,0.00001548331],"about_ca_topic_score_codex":0.0013893335,"about_ca_topic_score_gemma":0.0019044608,"teacher_disagreement_score":0.0013893335,"about_ca_system_score_codex":0.00022695202,"about_ca_system_score_gemma":0.0002559791,"threshold_uncertainty_score":0.0027624965},"labels":[],"label_agreement":null},{"id":"W3120824260","doi":"10.1007/s40430-020-02719-2","title":"Influence of hole quality on fatigue life of drilled CFRP with the different ply orientation angle","year":2021,"lang":"en","type":"article","venue":"Journal of the Brazilian Society of Mechanical Sciences and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Drilling; Thrust; Surface roughness; Materials science; Composite material; Ultimate tensile strength; Deformation (meteorology); Surface finish; Structural engineering; Mechanical engineering; Metallurgy; Engineering","score_opus":0.013488817058855384,"score_gpt":0.25541520138376606,"score_spread":0.24192638432491068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120824260","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99723417,0.0005738649,0.0016055249,0.000014180765,0.000017105169,0.000006838209,0.00008618858,0.000034487908,0.00042777223],"genre_scores_gemma":[0.9993068,0.00007787492,0.00034139096,0.000005234324,0.0000023117716,0.0000033042422,0.000041218216,0.0000081596,0.00021373626],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995974,0.000035002264,0.000022198772,0.00009172618,0.00014988567,0.00010386833],"domain_scores_gemma":[0.9976648,0.0008279197,0.00043530634,0.00017932,0.000767192,0.00012542168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049918616,0.0003964493,0.00036845542,0.00038859327,0.00021421879,0.0003985697,0.00022843087,0.00067763973,0.0020900837],"category_scores_gemma":[0.0020878273,0.00028847056,0.00031016514,0.00032968092,0.0004156564,0.0005329148,0.0001727815,0.00033010394,0.00022621448],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023775327,0.0001041008,0.012681965,0.00035685397,0.000048094902,0.0003617713,0.00031324034,0.008188064,0.9551671,0.00019411159,0.00026521436,0.019941982],"study_design_scores_gemma":[0.00007246707,0.00500502,0.1584669,0.000056280463,0.000245019,0.00052996835,0.0007027508,0.014055962,0.8190214,0.00015498184,0.001617869,0.00007125117],"about_ca_topic_score_codex":0.00061614305,"about_ca_topic_score_gemma":0.0013554746,"teacher_disagreement_score":0.0020900837,"about_ca_system_score_codex":0.00019116116,"about_ca_system_score_gemma":0.00016496803,"threshold_uncertainty_score":0.006992042},"labels":[],"label_agreement":null},{"id":"W3121601982","doi":"10.1007/s42452-021-04197-0","title":"Optimization of process parameters for turning of titanium alloy (Grade II) in MQL environment using multi-CI algorithm","year":2021,"lang":"en","type":"article","venue":"SN Applied Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Machinability; Minification; Particle swarm optimization; Machining; Tool wear; Titanium alloy; Materials science; Algorithm; Lubrication; Metallurgy; Surface roughness; Computer science; Mechanical engineering; Alloy; Mathematical optimization; Engineering; Mathematics; Composite material","score_opus":0.02706870859685274,"score_gpt":0.2718731187792219,"score_spread":0.24480441018236915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121601982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50782806,0.0011518426,0.4756936,0.00037148138,0.00010447974,0.00025038994,0.000106219224,0.000852388,0.013641499],"genre_scores_gemma":[0.9441242,0.00011701025,0.054451063,0.000059124828,0.000006965953,0.00011140191,0.00008866544,0.000023893195,0.001017692],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997614,0.00004040294,0.00001403626,0.000044104192,0.000084554355,0.000055535456],"domain_scores_gemma":[0.9994765,0.00022141133,0.00008454525,0.000026472779,0.00015858965,0.000032468983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006909789,0.0008463395,0.00083367946,0.0010044173,0.00038382984,0.0009033026,0.00078813033,0.0010219077,0.0010398121],"category_scores_gemma":[0.001164174,0.000308381,0.00069653994,0.000543394,0.00037254748,0.00028812943,0.00046518003,0.0005036754,0.00013247531],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082744526,0.000090515015,0.0014189318,0.00010767597,0.00003593057,0.0000645737,0.000042842472,0.968883,0.00529765,0.00051272864,0.00024737444,0.023216084],"study_design_scores_gemma":[0.000012005322,0.00009475302,0.0004966363,0.0000053532017,0.000010275044,0.00000914387,0.000016017564,0.99798954,0.0010970505,0.00009968203,0.00016521913,0.000004372465],"about_ca_topic_score_codex":0.006848391,"about_ca_topic_score_gemma":0.005596218,"teacher_disagreement_score":0.006848391,"about_ca_system_score_codex":0.00068155915,"about_ca_system_score_gemma":0.0009452664,"threshold_uncertainty_score":0.013617039},"labels":[],"label_agreement":null},{"id":"W3125290567","doi":"10.3390/ma14030592","title":"Study of the Effects of Initial Cutting Conditions and Transition Period on Ultimate Tool Life when Machining Inconel 718","year":2021,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Inconel; Machining; Tool wear; Materials science; Cutting tool; Point (geometry); Flank; Mechanical engineering; Metallurgy; Mathematics; Engineering; Geometry; Alloy","score_opus":0.0076769755273318595,"score_gpt":0.25814767289175544,"score_spread":0.25047069736442357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125290567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99617803,0.0015506881,0.0015897494,0.000017268285,0.000019445257,0.000018026007,0.00008274355,0.00004530117,0.0004986999],"genre_scores_gemma":[0.9980756,0.00035155716,0.0011398194,0.000012857329,0.000003890759,0.000014536591,0.00007976057,0.000016990458,0.00030497563],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995426,0.00003546334,0.000034672772,0.00009556547,0.00018480798,0.00010697447],"domain_scores_gemma":[0.9989409,0.00047217341,0.00017340365,0.00007311201,0.0002714931,0.00006891044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047373527,0.00034161814,0.0003915344,0.0004542209,0.00022003498,0.00034469002,0.00032012427,0.0003773912,0.0008462754],"category_scores_gemma":[0.001373516,0.00018832443,0.00028776348,0.000344977,0.00022512746,0.00047734877,0.00018737066,0.00046249887,0.0001514157],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007730531,0.00011346181,0.0037853927,0.00043751774,0.000024514004,0.0002754104,0.00027801923,0.0014224096,0.9730493,0.00007236005,0.00014845011,0.01962026],"study_design_scores_gemma":[0.000016317419,0.0029646119,0.033304833,0.00003887782,0.00007008741,0.00020839143,0.0002647913,0.0041083987,0.95728564,0.000044678935,0.0016602669,0.000033183194],"about_ca_topic_score_codex":0.00059070083,"about_ca_topic_score_gemma":0.0009591285,"teacher_disagreement_score":0.0008462754,"about_ca_system_score_codex":0.00017560521,"about_ca_system_score_gemma":0.00019297052,"threshold_uncertainty_score":0.0028310418},"labels":[],"label_agreement":null},{"id":"W3125843953","doi":"10.1115/msec2020-8452","title":"Structural Nonlinearity of Robotic Machining Systems","year":2020,"lang":"en","type":"article","venue":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Machining; Vibration; Nonlinear system; Modal; Control theory (sociology); Frequency response; Robot; Modal analysis; Harmonic; Machine tool; Engineering; Amplitude; Computer science; Control engineering; Mechanical engineering; Structural engineering; Acoustics; Physics; Materials science; Artificial intelligence; Control (management); Optics","score_opus":0.021309006781386388,"score_gpt":0.25101661041520995,"score_spread":0.22970760363382356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125843953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6076443,0.00047599504,0.36659017,0.00039152268,0.00003292199,0.00006905877,0.00010967416,0.00041277407,0.024273554],"genre_scores_gemma":[0.99451655,0.00009237242,0.003590178,0.000014587769,0.000005366899,0.000025663176,0.000022081835,0.000009200321,0.00172409],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998105,0.000039602346,0.0000058836017,0.000036715042,0.000088858586,0.000018421579],"domain_scores_gemma":[0.99965155,0.00019647065,0.000058115176,0.000032838583,0.000053615466,0.000007382655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016736412,0.00024091032,0.00021962855,0.00023480918,0.00019829061,0.0002825581,0.00025646988,0.00038974354,0.0017736667],"category_scores_gemma":[0.0007724179,0.00017719163,0.00015007806,0.00011798365,0.00042467564,0.00037453577,0.00027394333,0.00030036425,0.000329207],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007865897,0.000054689914,0.003893586,0.00022972695,0.00003894054,0.0003498194,0.00033691825,0.8188958,0.1327451,0.016177047,0.0002889918,0.026910737],"study_design_scores_gemma":[0.0000026122702,0.000042696192,0.0027436817,0.000006354931,0.000002852436,0.00008908959,0.000028814846,0.99067736,0.0031687205,0.00257137,0.0006592168,0.000007240774],"about_ca_topic_score_codex":0.0014906533,"about_ca_topic_score_gemma":0.0010283897,"teacher_disagreement_score":0.0017736667,"about_ca_system_score_codex":0.00030281054,"about_ca_system_score_gemma":0.0002289018,"threshold_uncertainty_score":0.0059334636},"labels":[],"label_agreement":null},{"id":"W3129724101","doi":"10.21203/rs.3.rs-168821/v1","title":"The effect of MQL on tool wear progression in low-frequency vibration-assisted  drilling of CFRP/Ti6Al4V stack material","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada; McMaster University","funders":"National Research Council Canada","keywords":"Delamination (geology); Materials science; Drilling; Tool wear; Vibration; Stack (abstract data type); Machining; Titanium alloy; Composite material; Chip; Lubricant; Chip formation; Structural engineering; Metallurgy; Acoustics; Computer science; Geology; Engineering; Alloy","score_opus":0.0164827379750634,"score_gpt":0.35191141340243426,"score_spread":0.33542867542737087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129724101","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99887985,0.0003050398,0.000531419,0.000017216013,0.000008282104,0.000002834252,0.00003612934,0.000028571312,0.00019069163],"genre_scores_gemma":[0.9995161,0.000049622668,0.000216094,0.0000045823904,0.0000018606503,0.0000018954838,0.000013278416,0.0000062916906,0.00019012991],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997867,0.00003717452,0.000012826761,0.000042406682,0.00007735453,0.000043481272],"domain_scores_gemma":[0.99881375,0.00059556455,0.00022956733,0.000081686936,0.00022692159,0.00005251319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004599537,0.00020026937,0.0002505587,0.00022035681,0.0002447594,0.000329423,0.0003333223,0.00036669357,0.0013695277],"category_scores_gemma":[0.0013057167,0.00014716224,0.00018950463,0.00015852024,0.00036188544,0.00034048714,0.00023372787,0.00026771985,0.00017072866],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015441744,0.000060768063,0.0020158922,0.0002122333,0.000016888154,0.00012319171,0.00025618295,0.0026893753,0.9841851,0.000076707336,0.00009369169,0.008725792],"study_design_scores_gemma":[0.000035935092,0.002030301,0.025826456,0.000034061424,0.000041094896,0.00012843581,0.00024954084,0.0153039815,0.9556337,0.000050458435,0.0006339036,0.000032124055],"about_ca_topic_score_codex":0.0008010986,"about_ca_topic_score_gemma":0.001173564,"teacher_disagreement_score":0.0013695277,"about_ca_system_score_codex":0.00019144425,"about_ca_system_score_gemma":0.00012874966,"threshold_uncertainty_score":0.0045815706},"labels":[],"label_agreement":null},{"id":"W3130416032","doi":"10.1007/s00170-021-06777-1","title":"Substructure analysis of vibration-assisted drilling systems","year":2021,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Substructure; Actuator; Vibration; Finite element method; Piezoelectricity; Engineering; Mechanical engineering; Acoustics; Coupling (piping); Structural engineering; Mechanical impedance; Natural frequency; Electrical impedance; Electrical engineering; Physics","score_opus":0.005615439688275,"score_gpt":0.23091164939125622,"score_spread":0.22529620970298123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130416032","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41767007,0.0004984673,0.573614,0.000113544804,0.000031218475,0.00005092737,0.00007384993,0.00016745567,0.007780423],"genre_scores_gemma":[0.99082816,0.00006057272,0.007387478,0.0000068931067,0.0000040947634,0.00001202334,0.000028454942,0.000008302963,0.0016639668],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990845,0.000015944806,0.000003856422,0.00001174858,0.000049349394,0.000010647495],"domain_scores_gemma":[0.9998456,0.00007459622,0.000024106364,0.000012031458,0.000037562742,0.0000060717034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014686071,0.00021483016,0.00024762377,0.00024306338,0.00015605957,0.00025847496,0.00030968117,0.00035432653,0.0012394022],"category_scores_gemma":[0.00046439894,0.00013121823,0.00020624777,0.00018336308,0.00021550656,0.00029851633,0.00027120556,0.0002295343,0.00013522286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000857696,0.00003321558,0.0011237185,0.000069953254,0.000029630863,0.00006974981,0.00006347741,0.9290009,0.023914924,0.0045679575,0.00021779518,0.04082283],"study_design_scores_gemma":[0.0000010418681,0.000016831153,0.0005267257,0.0000010448452,0.0000013342444,0.000007303868,0.000003949746,0.9985525,0.0005157598,0.00028877458,0.000083140825,0.0000015929497],"about_ca_topic_score_codex":0.0021264802,"about_ca_topic_score_gemma":0.0017806429,"teacher_disagreement_score":0.0021264802,"about_ca_system_score_codex":0.00017918082,"about_ca_system_score_gemma":0.00023214325,"threshold_uncertainty_score":0.0042281747},"labels":[],"label_agreement":null},{"id":"W3131074662","doi":"10.21203/rs.3.rs-207947/v1","title":"Evaluation of Factors Affecting Delamination, Tensile Strength, Thrust Force and Surface Roughness in Drilling of GFRP","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Delamination (geology); Fibre-reinforced plastic; Materials science; Composite material; Drilling; Ultimate tensile strength; Thrust; Surface roughness; Surface finish; Machining; Metallurgy; Mechanical engineering; Engineering; Geology","score_opus":0.06142246103758482,"score_gpt":0.38123850808204207,"score_spread":0.31981604704445726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3131074662","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998262,0.00017610968,0.0014092993,0.0000049924083,0.0000022111758,0.000006819578,0.000028667637,0.000009029133,0.00010080505],"genre_scores_gemma":[0.9992507,0.000060112445,0.00057959836,0.0000012329039,0.0000010371383,0.000002761438,0.000031004674,0.0000021893304,0.000071199545],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999645,0.000062091676,0.000022997596,0.00006370857,0.0001638438,0.00004239234],"domain_scores_gemma":[0.99848735,0.0007750734,0.00028156146,0.000049328675,0.00036120397,0.000045403765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053369056,0.0002945814,0.0004553862,0.0004441028,0.0002663105,0.00045843,0.0001963988,0.00048058596,0.00024132204],"category_scores_gemma":[0.0014540199,0.00024209524,0.00034908467,0.00042832867,0.00029490454,0.0003570879,0.00014160632,0.00021255676,0.00006197953],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018091073,0.0002890787,0.07820845,0.00047192755,0.00013606025,0.00044899926,0.00018730886,0.051350623,0.83759737,0.00013433794,0.00013226594,0.029234502],"study_design_scores_gemma":[0.000031752432,0.0031261202,0.28993925,0.00001954795,0.00026226052,0.0004532463,0.00037810314,0.16086054,0.54431516,0.00014235108,0.00040840998,0.00006329612],"about_ca_topic_score_codex":0.0022427933,"about_ca_topic_score_gemma":0.0032232606,"teacher_disagreement_score":0.0022427933,"about_ca_system_score_codex":0.00024010474,"about_ca_system_score_gemma":0.0003231175,"threshold_uncertainty_score":0.0044595003},"labels":[],"label_agreement":null},{"id":"W3134090603","doi":"10.3390/ma14051161","title":"3D Finite Element Model on Drilling of CFRP with Numerical Optimization and Experimental Validation","year":2021,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Drill; Thrust; Drilling; Materials science; Finite element method; Fibre-reinforced plastic; Structural engineering; Composite material; Mechanical engineering; Engineering","score_opus":0.00964230191815396,"score_gpt":0.23108271792127913,"score_spread":0.22144041600312517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134090603","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31830332,0.0003629141,0.65573376,0.00028268495,0.0000963889,0.0003480083,0.0013922339,0.0015720454,0.021908637],"genre_scores_gemma":[0.80946404,0.0002164309,0.18286307,0.000058144295,0.000007913882,0.00057255797,0.0008281126,0.00010036744,0.005889329],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997613,0.000044791377,0.000015740146,0.00003052387,0.00012708022,0.0000206629],"domain_scores_gemma":[0.99956447,0.00018305336,0.000056231656,0.000050756906,0.00013280533,0.0000125863835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046351223,0.00056147046,0.0005182758,0.00039761185,0.00030156883,0.00049487955,0.00082350464,0.0013803501,0.003387178],"category_scores_gemma":[0.0009470631,0.00033299357,0.0005273754,0.0003722246,0.0004535068,0.00034757238,0.00036914402,0.00041746316,0.0005704981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004537346,0.000038899092,0.0005850544,0.00009657339,0.000004996541,0.0000705993,0.00006478797,0.9821254,0.007898804,0.0010203589,0.00025466396,0.007794468],"study_design_scores_gemma":[0.000008509884,0.000039449216,0.00027399953,0.000008996307,0.0000029190583,0.000021193538,0.000015917367,0.9957461,0.0026939434,0.00017396949,0.0010081158,0.000007022252],"about_ca_topic_score_codex":0.005170384,"about_ca_topic_score_gemma":0.004269329,"teacher_disagreement_score":0.005170384,"about_ca_system_score_codex":0.0003435657,"about_ca_system_score_gemma":0.00070815167,"threshold_uncertainty_score":0.01133126},"labels":[],"label_agreement":null},{"id":"W3134787538","doi":"10.1007/s40997-021-00425-5","title":"Machinability Study of AA6061 Under Various Heat Treatment Conditions","year":2021,"lang":"en","type":"article","venue":"Iranian Journal of Science and Technology Transactions of Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machinability; Lubrication; Materials science; Surface roughness; Enhanced Data Rates for GSM Evolution; Lubricant; Metallurgy; Drilling; Tool wear; Surface finish; Aluminium; Alloy; Composite material; Machining; Computer science","score_opus":0.007410709392923526,"score_gpt":0.23803406189821277,"score_spread":0.23062335250528926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134787538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99600583,0.0010075805,0.00057066255,0.000046111894,0.00005439889,0.000016434979,0.00012693893,0.00003686135,0.0021353355],"genre_scores_gemma":[0.9965335,0.00023342267,0.0005076325,0.000018981227,0.000009017953,0.000008451248,0.00011680938,0.000012013077,0.0025601515],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996762,0.000013891355,0.000024382902,0.000057091973,0.00018662892,0.000041784922],"domain_scores_gemma":[0.99960345,0.00009310096,0.00007322968,0.000042483985,0.0001594678,0.00002825777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021375278,0.0002524357,0.00033374105,0.0003873908,0.00045967975,0.00032285575,0.00020565552,0.00054444,0.003490652],"category_scores_gemma":[0.0005128882,0.00018601511,0.00030796084,0.0003627818,0.00024203223,0.00038938643,0.00015019071,0.0002980951,0.0003732501],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026410082,0.000044486078,0.0015299596,0.00009767975,0.000010747864,0.00017269287,0.00020133909,0.0006848105,0.98989105,0.00013327948,0.00017298727,0.0067969677],"study_design_scores_gemma":[0.000018098921,0.0010243084,0.026255863,0.000010297792,0.00003610608,0.00013750163,0.00020363132,0.0030426923,0.9667283,0.00006702131,0.0024540934,0.000022116654],"about_ca_topic_score_codex":0.00090365944,"about_ca_topic_score_gemma":0.0025553992,"teacher_disagreement_score":0.003490652,"about_ca_system_score_codex":0.00017474983,"about_ca_system_score_gemma":0.00015497542,"threshold_uncertainty_score":0.011677384},"labels":[],"label_agreement":null},{"id":"W3134833309","doi":"10.1007/978-3-662-62924-6_18","title":"Comparison of the Mechanical Properties of Adhesively Bonded and Mechanically Interlocked Steel/Fibre-Reinforced Thermoplastic Hybrids Produced Using One-Step Forming Process","year":2021,"lang":"en","type":"book-chapter","venue":"Zukunftstechnologien für den multifunktionalen Leichtbau","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Blank; Materials science; Interlocking; Thermoplastic; Composite material; Process (computing); Adhesive; Fuel efficiency; Fabrication; Forming processes; Process engineering; Mechanical engineering; Automotive engineering; Engineering; Computer science","score_opus":0.04389931806969927,"score_gpt":0.28221579577388045,"score_spread":0.23831647770418118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134833309","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99333173,0.0013117524,0.0013435258,0.000015565787,0.000025923277,0.0000073028045,0.0001747791,0.000057088597,0.003732338],"genre_scores_gemma":[0.98938096,0.00041386692,0.0019846144,0.000016552876,0.000007592369,0.000009906964,0.0003796587,0.00004502882,0.0077618514],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999895,0.000008509688,0.0000046902196,0.000020581834,0.000056164805,0.000015074861],"domain_scores_gemma":[0.9998665,0.000051417584,0.000028979794,0.000012620902,0.000028178569,0.000012326834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013587311,0.00015639563,0.00017297681,0.00029294132,0.00016110018,0.00021335715,0.00026402078,0.00029396472,0.002480321],"category_scores_gemma":[0.00016971861,0.00010848213,0.00023399165,0.00035032484,0.00014324607,0.00025596225,0.00011611859,0.00022931861,0.00043440686],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006966794,0.000009870749,0.00011716267,0.000038733473,0.0000053283648,0.000033904358,0.000024261846,0.0001944693,0.996461,0.000049809285,0.00004598867,0.0029498842],"study_design_scores_gemma":[0.000004929993,0.00041827405,0.008174692,0.0000065429754,0.00003079125,0.000115541596,0.000037818518,0.00084815687,0.9885948,0.00002860889,0.001730329,0.000009519146],"about_ca_topic_score_codex":0.00022767157,"about_ca_topic_score_gemma":0.0009644378,"teacher_disagreement_score":0.002480321,"about_ca_system_score_codex":0.000106858926,"about_ca_system_score_gemma":0.000069516864,"threshold_uncertainty_score":0.008297503},"labels":[],"label_agreement":null},{"id":"W3141262229","doi":"10.36897/jme/134244","title":"Tooling systems with integrated sensors enabling data based process optimization","year":2021,"lang":"en","type":"article","venue":"Journal of Machine Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"ATS Automation Tooling Systems (Canada)","funders":"Österreichische Forschungsförderungsgesellschaft; Technische Universität Wien; Machine Tool Technologies Research Foundation","keywords":"Process (computing); Manufacturing engineering; Systems engineering; Computer science; Engineering; Engineering drawing; Operating system","score_opus":0.010265284076265604,"score_gpt":0.22598811615145423,"score_spread":0.2157228320751886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3141262229","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029806215,0.0030148108,0.9539844,0.0002558183,0.0001809864,0.0002509773,0.0005542157,0.004909983,0.007042629],"genre_scores_gemma":[0.6821672,0.001686524,0.30984214,0.0002780123,0.00011842608,0.000319562,0.00083698705,0.00019314457,0.0045580906],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989611,0.0000977627,0.00008079662,0.00021885688,0.00058323884,0.000058269645],"domain_scores_gemma":[0.99928075,0.00022980546,0.000112178044,0.00018247041,0.0001690591,0.000025784788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006351095,0.0008727542,0.0008360971,0.0007614572,0.00024303606,0.0014743024,0.0018297274,0.0011469207,0.003162712],"category_scores_gemma":[0.0017191719,0.0005458681,0.00031543238,0.0009462234,0.00038242532,0.0014131643,0.0012101388,0.0009680949,0.0010249731],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007911491,0.00035727108,0.002544332,0.0014408933,0.00021977421,0.00040563385,0.0002938518,0.15565906,0.3132238,0.018953806,0.005408266,0.50070214],"study_design_scores_gemma":[0.00011505539,0.00077899283,0.0023686439,0.00013445399,0.00009852083,0.0004024999,0.00004258678,0.77655965,0.1657341,0.011784869,0.041872866,0.000107697866],"about_ca_topic_score_codex":0.00047226096,"about_ca_topic_score_gemma":0.00052879506,"teacher_disagreement_score":0.003162712,"about_ca_system_score_codex":0.0004149687,"about_ca_system_score_gemma":0.00041315067,"threshold_uncertainty_score":0.010580301},"labels":[],"label_agreement":null},{"id":"W3150978003","doi":"10.1016/j.wear.2021.203759","title":"Characterization and machining performance of a chipping resistant ultra-soft coating used for the machining of Inconel 718","year":2021,"lang":"en","type":"article","venue":"Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Inconel; Machinability; Machining; Coating; Residual stress; Superalloy; Metallurgy; Surface roughness; Surface finish; Deposition (geology); Microstructure; Composite material; Alloy","score_opus":0.009891204100300123,"score_gpt":0.21975928710524276,"score_spread":0.20986808300494264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3150978003","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99847156,0.00016399003,0.00085860904,0.000011899661,0.000008025249,0.000009232778,0.000056864927,0.000020686488,0.00039922554],"genre_scores_gemma":[0.9973851,0.00006854918,0.0011986811,0.000011154866,0.0000025452796,0.000005077379,0.00008349364,0.000016776736,0.0012286444],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996574,0.000029876985,0.000018947514,0.000059513317,0.00018805811,0.000046209025],"domain_scores_gemma":[0.9993278,0.00013811924,0.00010243341,0.00009573885,0.0002876536,0.000048183552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022620219,0.00024911374,0.0002721017,0.00032291672,0.0002997629,0.00031177112,0.00043021265,0.0005169587,0.0008563861],"category_scores_gemma":[0.000694692,0.00017085046,0.00020565571,0.000227403,0.00021137486,0.00019190097,0.00013036194,0.00021962186,0.00024298739],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013994068,0.000018608003,0.000586976,0.000037907437,0.0000068086765,0.000059297006,0.000046309247,0.00015999065,0.9968516,0.000014648303,0.000057740068,0.002020188],"study_design_scores_gemma":[0.0000132048035,0.0010346315,0.01561552,0.0000049416585,0.000027893904,0.00015579084,0.00006353054,0.003183144,0.9789149,0.000007084137,0.00096786214,0.000011452528],"about_ca_topic_score_codex":0.001269382,"about_ca_topic_score_gemma":0.0018381762,"teacher_disagreement_score":0.001269382,"about_ca_system_score_codex":0.00016697805,"about_ca_system_score_gemma":0.0001648267,"threshold_uncertainty_score":0.0028649569},"labels":[],"label_agreement":null},{"id":"W3152687773","doi":"10.1007/s11740-021-01040-8","title":"Predicting regenerative chatter in milling with hardware-in-the-loop simulation using a dexel-based cutting model","year":2021,"lang":"en","type":"article","venue":"Production Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universität Stuttgart; University of British Columbia; Alexander von Humboldt-Stiftung","keywords":"Machining; Machine tool; Process (computing); Computation; Vibration; Computer science; Cutting tool; Numerical control; Position (finance); Stability (learning theory); Loop (graph theory); Control engineering; Control theory (sociology); Engineering; Simulation; Mechanical engineering; Algorithm; Control (management); Artificial intelligence","score_opus":0.01775272651505402,"score_gpt":0.23714977444092408,"score_spread":0.21939704792587006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152687773","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.63615215,0.00013953426,0.35669097,0.00011534846,0.00003617226,0.00008370645,0.000107478554,0.00071286125,0.00596177],"genre_scores_gemma":[0.9896488,0.000028435416,0.009179454,0.00000968697,0.0000017612805,0.000035724384,0.000028965243,0.000016156186,0.0010508702],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989235,0.000030902454,0.0000050135695,0.000017356839,0.000037267157,0.00001710604],"domain_scores_gemma":[0.9994854,0.00034294845,0.00004794142,0.000041266212,0.000059958504,0.000022604536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038060968,0.00039973005,0.00052219373,0.00023712649,0.00022813659,0.0005409634,0.00059684314,0.00083522435,0.0011888676],"category_scores_gemma":[0.0008108489,0.00022041691,0.0003648505,0.0001324301,0.0004869839,0.00034383358,0.00034827905,0.00052415853,0.0001238972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030384805,0.000016937032,0.0003133619,0.0000135025675,0.0000039939937,0.000022847782,0.000019140552,0.99578285,0.0023122355,0.00028215762,0.000019728637,0.0011829131],"study_design_scores_gemma":[0.0000022516695,0.000007852768,0.0000328251,5.406336e-7,6.5519316e-7,0.0000012323502,0.0000011849542,0.99959475,0.00031401112,0.000023151333,0.000020876807,7.0616767e-7],"about_ca_topic_score_codex":0.006575291,"about_ca_topic_score_gemma":0.0033246786,"teacher_disagreement_score":0.006575291,"about_ca_system_score_codex":0.00041706106,"about_ca_system_score_gemma":0.0004763903,"threshold_uncertainty_score":0.01307404},"labels":[],"label_agreement":null},{"id":"W3152937796","doi":"","title":"Development and Calibration of a 3-component Force Sensor for Meso-milling","year":2015,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Calibration; Component (thermodynamics); Bandwidth (computing); Piezoelectricity; Engineering; Development (topology); Piezoelectric sensor; Electronic engineering; Computer science; Control engineering; Mechanical engineering; Electrical engineering; Physics; Telecommunications; Mathematics","score_opus":0.01943851981452284,"score_gpt":0.30250801712056785,"score_spread":0.283069497306045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152937796","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24099779,0.0012412256,0.7522427,0.00028351808,0.00018878182,0.00048741503,0.00016160832,0.0010070155,0.0033900184],"genre_scores_gemma":[0.4470084,0.0008199266,0.54808754,0.000102494305,0.000022431082,0.0002266935,0.00016561085,0.000077413475,0.0034895584],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99943584,0.000039463528,0.000017875405,0.00012083477,0.00035757356,0.00002845584],"domain_scores_gemma":[0.9996711,0.000070047194,0.000039744864,0.000036084002,0.00016092419,0.000022055057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006589317,0.00036348923,0.00037596293,0.00026491313,0.00021007471,0.00044054684,0.0006758383,0.00070725,0.0009152457],"category_scores_gemma":[0.00061603583,0.00025615096,0.00022186758,0.00021543817,0.0002921918,0.0005945162,0.0003409495,0.00064461725,0.00036676682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033433185,0.00003569267,0.00038596545,0.000110737834,0.000005783607,0.000049522612,0.00008765349,0.0012232116,0.96141285,0.00071578944,0.0002666389,0.035672687],"study_design_scores_gemma":[0.000015749865,0.000423428,0.0027955284,0.000018945568,0.000012503198,0.00037693954,0.00005412899,0.022018353,0.9654196,0.00024114145,0.008595131,0.000028477225],"about_ca_topic_score_codex":0.00027805957,"about_ca_topic_score_gemma":0.0004718515,"teacher_disagreement_score":0.0009152457,"about_ca_system_score_codex":0.00031557016,"about_ca_system_score_gemma":0.0005904051,"threshold_uncertainty_score":0.0034847856},"labels":[],"label_agreement":null},{"id":"W3154289000","doi":"10.1016/j.asoc.2021.107416","title":"Analysis, modeling, and multi-objective optimization of machining Inconel 718 with nano-additives based minimum quantity coolant","year":2021,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inconel; Materials science; Machining; Nanofluid; Lubrication; Coolant; Soft computing; Response surface methodology; Tool wear; Nanoparticle; Surface roughness; Energy consumption; Nano-; Computer science; Artificial neural network; Process engineering; Mechanical engineering; Composite material; Metallurgy; Nanotechnology; Machine learning; Engineering","score_opus":0.008877700037328781,"score_gpt":0.22537563848816983,"score_spread":0.21649793845084103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154289000","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7497886,0.0009400316,0.22691353,0.00050347944,0.00008948206,0.00009737783,0.00026374162,0.00026991946,0.021133896],"genre_scores_gemma":[0.9831457,0.00015862452,0.012641849,0.0000247841,0.0000085721595,0.00005744566,0.000071644754,0.00003493312,0.0038564177],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998337,0.00004200896,0.0000054727943,0.00002619094,0.00005233262,0.000040224542],"domain_scores_gemma":[0.9995035,0.00031838758,0.00006405355,0.000017738157,0.00007882193,0.000017363116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005821172,0.0006269801,0.00086212746,0.0004965573,0.00047783402,0.0010705772,0.00067598326,0.0011294531,0.0016530897],"category_scores_gemma":[0.00073280255,0.00052443985,0.0008821549,0.0003983429,0.0005032188,0.0004939943,0.0003545636,0.0006082078,0.00014587634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015307445,0.000014111794,0.0001464377,0.000018353174,0.0000050821986,0.000011173712,0.0000053867075,0.9980977,0.00052759744,0.00027991988,0.000033549037,0.0008453369],"study_design_scores_gemma":[0.0000016828216,0.0000112951875,0.000092539,7.837341e-7,0.0000020588395,0.0000011773257,0.000003173261,0.9995944,0.00020210275,0.00005026903,0.00003940938,0.0000010876403],"about_ca_topic_score_codex":0.017482681,"about_ca_topic_score_gemma":0.014724954,"teacher_disagreement_score":0.017482681,"about_ca_system_score_codex":0.0010633062,"about_ca_system_score_gemma":0.0013209437,"threshold_uncertainty_score":0.034761786},"labels":[],"label_agreement":null},{"id":"W3154788462","doi":"10.1016/j.cirp.2021.03.024","title":"Novel sensor-based tool wear monitoring approach for seamless implementation in high speed milling applications","year":2021,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"National Research Council Canada","keywords":"Tool wear; Machine tool; Vibration; Computer science; Condition monitoring; Cutting tool; Engineering; Control engineering; Mechanical engineering; Machining; Acoustics","score_opus":0.041653633743643025,"score_gpt":0.3243470128936295,"score_spread":0.2826933791499865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154788462","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20241731,0.0012887352,0.7856008,0.0002532412,0.00040634075,0.0001581628,0.00040846114,0.0035499535,0.0059170006],"genre_scores_gemma":[0.8257784,0.0002956388,0.16962941,0.00016015962,0.00006184233,0.00006432278,0.0001770501,0.00006530276,0.003767952],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99954754,0.00003130152,0.000017937584,0.000097594406,0.00027418838,0.000031418338],"domain_scores_gemma":[0.9996099,0.0000650167,0.000071000664,0.00006913326,0.00016661694,0.000018374934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024087654,0.00053654687,0.00044373234,0.0004302309,0.00016822858,0.00054611976,0.0011746136,0.00057524926,0.0014668168],"category_scores_gemma":[0.00046512415,0.00026212208,0.00020971666,0.00038956542,0.00018673732,0.0007671312,0.0004392214,0.00040361332,0.00044704284],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025248347,0.00015340747,0.0017794679,0.00020242934,0.000032343905,0.00013086858,0.00009224374,0.002766919,0.8395887,0.00086263986,0.00206536,0.15207303],"study_design_scores_gemma":[0.00003486893,0.0008341763,0.0071624643,0.000023568624,0.00005496188,0.0006472484,0.0000907591,0.2234963,0.75705415,0.00072090735,0.009806981,0.00007372522],"about_ca_topic_score_codex":0.00034530688,"about_ca_topic_score_gemma":0.001115341,"teacher_disagreement_score":0.0014668168,"about_ca_system_score_codex":0.00020431395,"about_ca_system_score_gemma":0.0002732737,"threshold_uncertainty_score":0.0049069524},"labels":[],"label_agreement":null},{"id":"W3155289338","doi":"10.3390/ma14082062","title":"Milling Performance of CFRP Composite and Atomised Vegetable Oil as a Function of Fiber Orientation","year":2021,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Materials science; Delamination (geology); Machining; Composite material; Surface integrity; Fiber; Composite number; Tool wear; Wet-milling; Metallurgy","score_opus":0.004846175388564436,"score_gpt":0.20155909523847085,"score_spread":0.1967129198499064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155289338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991015,0.00016739812,0.000444781,0.000004770634,0.0000034553693,0.000003421062,0.00004974562,0.000012041909,0.00021293314],"genre_scores_gemma":[0.9982387,0.00015294102,0.00089392945,0.000005436137,0.0000016406815,0.000003913655,0.00007524256,0.000008206178,0.00061998476],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998155,0.00001596041,0.000019867108,0.000033464334,0.00008124086,0.000033896213],"domain_scores_gemma":[0.9993374,0.0002563786,0.00022760115,0.00003760632,0.000100641264,0.000040301547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025809868,0.00030063812,0.00017404377,0.00020400231,0.00009297138,0.00022071534,0.00015012815,0.00026323457,0.00080979214],"category_scores_gemma":[0.00056543894,0.00013982953,0.00013846371,0.00026424666,0.00017606257,0.0002328395,0.00010548427,0.0002972049,0.00015769858],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032588292,0.00003301373,0.00045682967,0.000038354785,0.0000036417432,0.00003337486,0.0000486859,0.00034264335,0.9970113,0.00001561783,0.000013842887,0.0016766972],"study_design_scores_gemma":[0.000005984975,0.00072545226,0.0043834425,0.0000024862964,0.0000070015103,0.000028293585,0.000037093592,0.0011391811,0.993504,0.000006146973,0.00015558119,0.0000053117883],"about_ca_topic_score_codex":0.00061888,"about_ca_topic_score_gemma":0.0010762741,"teacher_disagreement_score":0.00080979214,"about_ca_system_score_codex":0.00013144201,"about_ca_system_score_gemma":0.00009019589,"threshold_uncertainty_score":0.002709031},"labels":[],"label_agreement":null},{"id":"W3156447535","doi":"10.1007/978-3-319-95966-5","title":"Machining Difficult-to-Cut Materials","year":2018,"lang":"en","type":"book","venue":"Materials forming, machining and tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Machining; Materials science; Metallurgy; Focus (optics); Ceramic; Titanium alloy; Titanium; Mechanical engineering; Engineering; Alloy","score_opus":0.006763369074373988,"score_gpt":0.22211781722955934,"score_spread":0.21535444815518534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3156447535","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018372472,0.06348503,0.45752707,0.000917093,0.0046525993,0.00036455374,0.0005423817,0.0028015822,0.45133716],"genre_scores_gemma":[0.068235114,0.027466957,0.3752579,0.0007063284,0.0010593546,0.00017411812,0.0017814909,0.0012797897,0.524039],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99962914,0.000011501483,0.000011609635,0.000056084908,0.00026988488,0.000021754971],"domain_scores_gemma":[0.9998467,0.000053976677,0.000014937695,0.000035087905,0.00003798074,0.000011312702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020626605,0.0010469521,0.0007815322,0.0008219457,0.00035116368,0.0009486886,0.0014199439,0.0006949214,0.023682768],"category_scores_gemma":[0.00041894562,0.0005275337,0.0004625163,0.00073892827,0.00050690136,0.0013453157,0.0011616134,0.0013176529,0.012436147],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000072039715,0.00006199093,0.00016712942,0.0022730508,0.000046055804,0.00021358754,0.00012642411,0.005183621,0.14583132,0.0250663,0.07320634,0.74775213],"study_design_scores_gemma":[0.00002602319,0.00018959006,0.0014156587,0.0003509059,0.000029164328,0.0022265927,0.000059637594,0.01452443,0.0724968,0.034768622,0.87387234,0.00004035766],"about_ca_topic_score_codex":0.00017665197,"about_ca_topic_score_gemma":0.00085032865,"teacher_disagreement_score":0.023682768,"about_ca_system_score_codex":0.00022352183,"about_ca_system_score_gemma":0.00027816938,"threshold_uncertainty_score":0.07922679},"labels":[],"label_agreement":null},{"id":"W3157749223","doi":"10.1016/j.precisioneng.2021.04.017","title":"Chatter suppression in micro-milling using shank-mounted Two-DOF tuned mass damper","year":2021,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Tuned mass damper; Vibration; Damper; Machining; Structural engineering; Frequency response; Modal; Natural frequency; Modal analysis; Stability (learning theory); Engineering; End mill; Coupling (piping); Mechanical engineering; Materials science; Acoustics; Computer science; Finite element method; Composite material; Physics","score_opus":0.01021115030071086,"score_gpt":0.2557951771705574,"score_spread":0.24558402686984654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157749223","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49377233,0.00062256947,0.5009013,0.000108887776,0.00008307962,0.00002827901,0.000016941722,0.0002852079,0.00418146],"genre_scores_gemma":[0.97554,0.00006256632,0.02326296,0.000011974394,0.000007692991,0.000011033697,0.0000052745027,0.000014899149,0.0010836142],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980074,0.000046460915,0.0000071014992,0.000034552115,0.00009140852,0.000019649668],"domain_scores_gemma":[0.999634,0.0001929143,0.000050849296,0.00003343242,0.00006655695,0.00002216912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028396837,0.0002586236,0.00039390722,0.00014101023,0.0002400489,0.00020147946,0.00048228554,0.0003845717,0.00074101775],"category_scores_gemma":[0.00045156083,0.0001836917,0.00015668207,0.0001349122,0.00041558588,0.00029424878,0.00038705504,0.00024903845,0.00010877133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014043978,0.00014229397,0.0017572324,0.00036181675,0.000045289748,0.00033170427,0.00063692837,0.08757457,0.81171834,0.0052932617,0.0005645133,0.09016965],"study_design_scores_gemma":[0.000040062652,0.0003822705,0.0013190256,0.000010610778,0.000013251753,0.00010277697,0.000046448098,0.937664,0.05931599,0.00043667588,0.0006516695,0.000017250348],"about_ca_topic_score_codex":0.00043190687,"about_ca_topic_score_gemma":0.0008319066,"teacher_disagreement_score":0.00074101775,"about_ca_system_score_codex":0.00011247934,"about_ca_system_score_gemma":0.00015330914,"threshold_uncertainty_score":0.0024788976},"labels":[],"label_agreement":null},{"id":"W3158121308","doi":"10.3390/jmmp5020042","title":"Machining Ti-6Al-4V Alloy Using Nano-Cutting Fluids: Investigation and Analysis","year":2021,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Materials science; Lubrication; Nanofluid; Surface roughness; Machining; Tool wear; Metallurgy; Inconel; Coolant; Cutting fluid; Surface finish; Composite material; Alloy; Nanoparticle; Mechanical engineering; Nanotechnology","score_opus":0.012264349339316572,"score_gpt":0.23773847472138954,"score_spread":0.22547412538207295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158121308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904454,0.0020636087,0.005941946,0.000055586497,0.000019802274,0.00003512811,0.00017531625,0.00006315846,0.0012000628],"genre_scores_gemma":[0.9883559,0.0012438152,0.008692662,0.000021817646,0.00000820509,0.000027061556,0.00018733458,0.000015724076,0.0014476087],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980575,0.000008634719,0.000010057609,0.000025971853,0.00012966522,0.000020004007],"domain_scores_gemma":[0.9998846,0.000020578089,0.00002993135,0.000005430124,0.000054380504,0.000005090317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020814827,0.00019753598,0.00022633378,0.00054609013,0.00020598934,0.00033107627,0.00032660575,0.00043125704,0.0005407216],"category_scores_gemma":[0.00018848375,0.00017216855,0.00028840426,0.00035296552,0.00023064061,0.00035142087,0.00015053037,0.00026246218,0.00015235592],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051237992,0.000021013497,0.0012410787,0.00025454073,0.0000066504886,0.00009681688,0.0001096326,0.00059369556,0.99199474,0.00012129565,0.00006726576,0.005442062],"study_design_scores_gemma":[0.000009795616,0.00048119688,0.012315504,0.000022148866,0.000025968466,0.00025766686,0.00033844128,0.015062471,0.96784556,0.00014870393,0.0034650639,0.000027437822],"about_ca_topic_score_codex":0.0012227072,"about_ca_topic_score_gemma":0.0026218027,"teacher_disagreement_score":0.0012227072,"about_ca_system_score_codex":0.00025465243,"about_ca_system_score_gemma":0.00014474751,"threshold_uncertainty_score":0.0024312139},"labels":[],"label_agreement":null},{"id":"W3159286787","doi":"10.18280/jesa.540206","title":"Multi Objective Study on Machining Characteristics of AISI H-11 Tool Steel Prepared by Different Processing Techniques","year":2021,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taguchi methods; Machining; Materials science; Surface roughness; Tool steel; Tool wear; Metallurgy; Response surface methodology; Surface finish; Orthogonal array; Mechanical engineering; Composite material; Computer science; Engineering","score_opus":0.014229941060344888,"score_gpt":0.2662147825715351,"score_spread":0.2519848415111902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3159286787","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99045265,0.00017056766,0.0086102905,0.000008415658,0.0000051789348,0.000017988106,0.00004844004,0.000016554868,0.0006699823],"genre_scores_gemma":[0.99365234,0.00009095961,0.005060474,0.0000060815705,0.000004249777,0.000014405907,0.00011778156,0.000007655524,0.0010460035],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99935764,0.000055481058,0.000032469703,0.00010115697,0.0003892155,0.00006395838],"domain_scores_gemma":[0.9988537,0.0003863384,0.0003087222,0.000039562634,0.00036040932,0.000051231553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007872892,0.0003502629,0.00038087193,0.00066511094,0.00014935697,0.00038623513,0.00018707717,0.00036532438,0.00085320056],"category_scores_gemma":[0.00053820387,0.00013125314,0.00035883187,0.000339186,0.00018077057,0.00021428558,0.00014023184,0.00014565076,0.00015182862],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070661143,0.00036177968,0.022937756,0.0007234114,0.00008939171,0.00018915962,0.00027929465,0.015910339,0.91011155,0.00014691443,0.0001754175,0.04836839],"study_design_scores_gemma":[0.00004324671,0.010888156,0.4401266,0.000038632134,0.00025866827,0.00057133177,0.0008507641,0.08186866,0.46292916,0.00024832424,0.0020581395,0.000118278935],"about_ca_topic_score_codex":0.00049173896,"about_ca_topic_score_gemma":0.0015699795,"teacher_disagreement_score":0.00085320056,"about_ca_system_score_codex":0.00017696217,"about_ca_system_score_gemma":0.00013491581,"threshold_uncertainty_score":0.004163623},"labels":[],"label_agreement":null},{"id":"W3163005782","doi":"10.3390/jcs5050137","title":"Temperature Study during the Edge Trimming of Carbon Fiber-Reinforced Plastic [0]8/Ti6Al4V Stack Material","year":2021,"lang":"en","type":"article","venue":"Journal of Composites Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; École de Technologie Supérieure","funders":"","keywords":"Materials science; Machinability; Rivet; Composite material; Titanium alloy; Machining; Fibre-reinforced plastic; Delamination (geology); Enhanced Data Rates for GSM Evolution; Drilling; Trimming; Thermal conductivity; Mechanical engineering; Alloy; Metallurgy; Computer science","score_opus":0.004484783904610715,"score_gpt":0.22098574970074786,"score_spread":0.21650096579613715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163005782","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963315,0.0006476025,0.0017248989,0.000023440238,0.000020288622,0.000012068613,0.00015631261,0.000061834304,0.0010220608],"genre_scores_gemma":[0.997563,0.0001670632,0.0010734332,0.00001705415,0.0000072897656,0.000011196187,0.00011503634,0.000033468354,0.0010125278],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977833,0.000015562106,0.00000812371,0.00006816035,0.00009464509,0.00003521352],"domain_scores_gemma":[0.99953127,0.00011296634,0.00012222848,0.000040012997,0.00016498067,0.000028443714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020234154,0.00027668313,0.0003431176,0.00030128084,0.0003163947,0.00026314773,0.00032835003,0.0003934923,0.0013809864],"category_scores_gemma":[0.0004026704,0.0002220081,0.00025773302,0.00028855773,0.00026332767,0.00035811387,0.00011664039,0.00041058153,0.00036216772],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005440085,0.00007672372,0.0048900433,0.0002470091,0.000016001297,0.0003364707,0.00051919976,0.0010670777,0.9834616,0.00007010126,0.00026174216,0.00850999],"study_design_scores_gemma":[0.000008834826,0.0013033507,0.081693575,0.000038890994,0.000058783102,0.00034354144,0.0006379007,0.007154025,0.9065345,0.000057802416,0.0021308595,0.000037949747],"about_ca_topic_score_codex":0.0006110846,"about_ca_topic_score_gemma":0.001379153,"teacher_disagreement_score":0.0013809864,"about_ca_system_score_codex":0.00018236366,"about_ca_system_score_gemma":0.00011159072,"threshold_uncertainty_score":0.004619837},"labels":[],"label_agreement":null},{"id":"W3163199723","doi":"10.21203/rs.3.rs-494087/v1","title":"Application of Mechanistic Force Models to Features of Arbitrary Geometry at Low Material Removal Rate","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Discretization; Machining; Chamfer (geometry); Nonlinear system; Exponential function; Enhanced Data Rates for GSM Evolution; Geometry; Mathematics; Mechanics; Computer science; Mechanical engineering; Mathematical analysis; Engineering; Artificial intelligence; Physics","score_opus":0.023817796640009003,"score_gpt":0.3195581035445573,"score_spread":0.29574030690454833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163199723","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38903645,0.00016488868,0.6064795,0.000066079534,0.000011263553,0.000051025996,0.00007867364,0.00031791313,0.0037941746],"genre_scores_gemma":[0.9733497,0.00007940688,0.025678001,0.0000061428877,0.0000019957306,0.000035468405,0.000032771928,0.000019368767,0.0007971736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998468,0.000024803086,0.000007257717,0.000025097539,0.00007790617,0.000017981087],"domain_scores_gemma":[0.9995635,0.00024888612,0.00008073571,0.00006205092,0.000034921522,0.00000979609],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003710627,0.00031509303,0.00032264346,0.00027255501,0.0001644145,0.00038897578,0.00082029385,0.00064633694,0.0008435803],"category_scores_gemma":[0.0009998732,0.0002889448,0.00048224785,0.0002030129,0.0004141116,0.0004269732,0.0002347776,0.00036598058,0.00015119497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012358154,0.000026401829,0.0007026043,0.000022051183,0.0000045699194,0.00003968047,0.00002243709,0.98258,0.009924955,0.0010441552,0.000027341675,0.005593557],"study_design_scores_gemma":[0.0000023837035,0.00001461675,0.00035539785,0.0000015697517,0.0000010953355,0.0000119092465,0.0000029587688,0.99757534,0.0017701557,0.00017756653,0.00008432958,0.000002730819],"about_ca_topic_score_codex":0.0024940763,"about_ca_topic_score_gemma":0.0022337225,"teacher_disagreement_score":0.0024940763,"about_ca_system_score_codex":0.0004957452,"about_ca_system_score_gemma":0.00040634602,"threshold_uncertainty_score":0.004959166},"labels":[],"label_agreement":null},{"id":"W3164031468","doi":"10.1115/1.4051286","title":"Transmissibility Enhanced Inverse Chatter Stability Solution","year":2021,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transmissibility (structural dynamics); Modal; Vibration; Control theory (sociology); Stability (learning theory); Natural frequency; Inverse; Modal testing; Modal analysis; Engineering; Mathematics; Computer science; Vibration isolation; Acoustics; Physics; Materials science; Geometry; Artificial intelligence","score_opus":0.00946559194133301,"score_gpt":0.21212658377423976,"score_spread":0.20266099183290676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164031468","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02111625,0.00008103216,0.9742138,0.000079223166,0.000021912436,0.000034284647,0.00002525329,0.00015069141,0.0042775394],"genre_scores_gemma":[0.8804846,0.00012400655,0.11173402,0.00006709682,0.0000314969,0.00015956837,0.00009334181,0.000059385333,0.0072464636],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965894,0.00009887966,0.00001760596,0.00007953073,0.00011845548,0.000026537777],"domain_scores_gemma":[0.9991242,0.00043746366,0.000094240124,0.000048533002,0.00027908664,0.000016482003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073118665,0.0008867338,0.00073167455,0.00049454643,0.00025098328,0.0006666092,0.000634672,0.0008356296,0.0025827633],"category_scores_gemma":[0.001951799,0.00031184097,0.0005061243,0.00018310835,0.00054167205,0.0004920391,0.00074289186,0.000757346,0.00034514724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007425655,0.000027213813,0.000647974,0.000114903254,0.00003586767,0.00007579721,0.0000812628,0.9592392,0.006950222,0.004918588,0.00034524009,0.027489481],"study_design_scores_gemma":[0.0000026310718,0.000012243004,0.000069270245,0.000004364353,0.0000026551593,0.000006280343,0.0000030846095,0.99870634,0.00064689346,0.0004258221,0.000118366974,0.000002091423],"about_ca_topic_score_codex":0.00341083,"about_ca_topic_score_gemma":0.0019624347,"teacher_disagreement_score":0.00341083,"about_ca_system_score_codex":0.00035772764,"about_ca_system_score_gemma":0.00058694044,"threshold_uncertainty_score":0.00864017},"labels":[],"label_agreement":null},{"id":"W3165366904","doi":"10.1016/j.cirp.2021.04.060","title":"Active control of high frequency chatter with machine tool feed drives in turning","year":2021,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of British Columbia; National Science Foundation","keywords":"Control theory (sociology); Vibration; Engineering; Modal; Controller (irrigation); Machine tool; Feed forward; Process (computing); Stability (learning theory); Control engineering; Filter (signal processing); Servo; Control (management); Mechanical engineering; Computer science; Acoustics; Materials science; Artificial intelligence","score_opus":0.007001771364977215,"score_gpt":0.22436268823479186,"score_spread":0.21736091686981465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165366904","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4389723,0.0008940639,0.549352,0.00012324622,0.00021842947,0.00003128003,0.00001531302,0.00020685753,0.010186486],"genre_scores_gemma":[0.99526924,0.00006354432,0.0035306476,0.000008767112,0.0000121208805,0.0000066374078,0.0000029976204,0.0000061502483,0.0011000109],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980396,0.00006020185,0.000009405925,0.000025338373,0.00007018583,0.00003095777],"domain_scores_gemma":[0.9994504,0.00034163776,0.00005638547,0.00002583234,0.000106482476,0.000019245468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003559483,0.00028218198,0.00035663234,0.00023011936,0.00023377557,0.0005615497,0.00047713632,0.00032509936,0.0010205879],"category_scores_gemma":[0.000849329,0.00014825915,0.00016697423,0.00015211756,0.00042701102,0.00026292002,0.00029284132,0.00032431402,0.0000950503],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026301504,0.0003409317,0.002368889,0.0008623852,0.00013165282,0.00073999446,0.0010818437,0.40655574,0.26518467,0.029956196,0.0015617611,0.2885857],"study_design_scores_gemma":[0.00004479181,0.0006456966,0.0017967552,0.000029144641,0.000030969146,0.00012781288,0.000077207755,0.972622,0.020236995,0.0027449825,0.001626118,0.000017610519],"about_ca_topic_score_codex":0.00086841075,"about_ca_topic_score_gemma":0.0013848455,"teacher_disagreement_score":0.0010205879,"about_ca_system_score_codex":0.00016091471,"about_ca_system_score_gemma":0.00012221467,"threshold_uncertainty_score":0.003414154},"labels":[],"label_agreement":null},{"id":"W3170637310","doi":"10.1007/s00170-021-07325-7","title":"A review on deep learning in machining and tool monitoring: methods, opportunities, and challenges","year":2021,"lang":"en","type":"review","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":299,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Artificial intelligence; Big data; Machining; Deep learning; Process (computing); Artificial neural network; Machine learning; Computer science; Smart manufacturing; Sensor fusion; Convolutional neural network; Machine tool; Redundancy (engineering); Engineering; Manufacturing engineering; Data mining; Reliability engineering","score_opus":0.06722737477220725,"score_gpt":0.3583259737242154,"score_spread":0.2910985989520081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170637310","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016458641,0.99738044,0.0013218278,0.0004108205,0.00019942458,0.000006025852,0.00004672728,0.000014060024,0.00045599512],"genre_scores_gemma":[0.0012381558,0.99675995,0.0011381871,0.00025308356,0.00023259985,0.000009428069,0.00006511735,0.000004899182,0.00029871197],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995728,0.000079906116,0.000071320515,0.000083440995,0.00016115392,0.000031358126],"domain_scores_gemma":[0.99811065,0.0012442683,0.0001669618,0.00004331674,0.0003708179,0.000063924155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014371928,0.0010897492,0.0016085651,0.002152065,0.00021285102,0.0013552939,0.001286529,0.0012662411,0.002851219],"category_scores_gemma":[0.003120253,0.00044478785,0.0008849419,0.0034291917,0.00045678354,0.0021309077,0.00090917555,0.0015960223,0.001170418],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007044562,0.000060199673,0.000269446,0.02185487,0.00019312199,0.00004787751,0.000025598601,0.0013478933,0.00087278447,0.003485145,0.018051319,0.9537213],"study_design_scores_gemma":[0.000042494357,0.00030615876,0.0017106424,0.018147111,0.000880625,0.00056705636,0.00007288216,0.003006189,0.0022666838,0.0093232775,0.96358925,0.000087763394],"about_ca_topic_score_codex":0.0021162843,"about_ca_topic_score_gemma":0.0031585041,"teacher_disagreement_score":0.002851219,"about_ca_system_score_codex":0.0007025556,"about_ca_system_score_gemma":0.0022402955,"threshold_uncertainty_score":0.009538293},"labels":[],"label_agreement":null},{"id":"W3171348149","doi":"10.1101/2021.06.11.21258244","title":"A row-generation approach for simultaneous multiple needle trajectory planning in radiofrequency ablation","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; University of Toronto","funders":"","keywords":"Pairwise comparison; Ellipse; Trajectory; Thermal ablation; Scalability; Computer science; Set (abstract data type); Radiofrequency ablation; Integer programming; Ablation; Algorithm; Mathematics; Artificial intelligence; Physics; Medicine","score_opus":0.028771896453061975,"score_gpt":0.2549334901087695,"score_spread":0.2261615936557075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171348149","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010080052,0.0000847363,0.98861235,0.000033080458,0.000014857387,0.000026519012,0.000054578075,0.0004697802,0.00062400603],"genre_scores_gemma":[0.27628276,0.000089961366,0.7212969,0.0000481081,0.000015739739,0.00011042235,0.00035714285,0.00029831642,0.001500628],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996904,0.00010204267,0.00001396285,0.00005691936,0.000094361625,0.000042342712],"domain_scores_gemma":[0.99939513,0.00029234897,0.00006350148,0.000093473594,0.00012222768,0.00003332087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050377764,0.00074050523,0.000591833,0.00052190333,0.00024656975,0.00055942667,0.00066449546,0.00067800406,0.0027556901],"category_scores_gemma":[0.0010568207,0.00054081745,0.0007989838,0.00053639035,0.00034608977,0.00046430377,0.0007861295,0.0006887951,0.0006634339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008653139,0.000043695258,0.000614487,0.00007900638,0.00003863072,0.000105192514,0.00008717871,0.899201,0.009166969,0.0034243371,0.0015573795,0.08559571],"study_design_scores_gemma":[0.0000032934975,0.000018287063,0.00005691828,0.0000032826727,0.0000042953784,0.000020692967,0.0000071199406,0.99712163,0.0013884959,0.0008891473,0.00048336494,0.0000034369846],"about_ca_topic_score_codex":0.0028088186,"about_ca_topic_score_gemma":0.0036167933,"teacher_disagreement_score":0.0028088186,"about_ca_system_score_codex":0.00039769107,"about_ca_system_score_gemma":0.0005165061,"threshold_uncertainty_score":0.009218752},"labels":[],"label_agreement":null},{"id":"W3171436672","doi":"10.1002/int.22493","title":"Digital‐twin assisted: Fault diagnosis using deep transfer learning for machining tool condition","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Automation; Cloud computing; Computer science; Process (computing); Fault (geology); Software deployment; Manufacturing engineering; Machining; Systems engineering; Engineering; Software engineering; Mechanical engineering","score_opus":0.02158188550714101,"score_gpt":0.28915211068924546,"score_spread":0.26757022518210444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171436672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14024328,0.0005418485,0.85318226,0.00027400686,0.00010996745,0.000057845577,0.00015629035,0.0030488614,0.0023856289],"genre_scores_gemma":[0.95581555,0.00009442006,0.042041425,0.00008303452,0.000021217553,0.000026516936,0.00015535987,0.000026734648,0.0017358436],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998104,0.000020001105,0.000009955357,0.000053466345,0.00006573037,0.00004045273],"domain_scores_gemma":[0.9997638,0.000066468536,0.00003711649,0.00003034133,0.00008435047,0.000018004213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002911676,0.0006289293,0.00037815544,0.0005994307,0.00021323556,0.000439788,0.0008119959,0.0007422072,0.0015285122],"category_scores_gemma":[0.00091749744,0.000159947,0.0003169505,0.00037462363,0.00029550318,0.0008531953,0.0006189363,0.0006731328,0.00032738945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004649058,0.00037575295,0.0075589223,0.00015010014,0.00008706662,0.0003316881,0.00011876785,0.28973916,0.030847639,0.0018240148,0.0032547982,0.66524714],"study_design_scores_gemma":[0.000004986025,0.00004678711,0.00085423107,0.0000036552883,0.0000073428337,0.000044042637,0.000010388726,0.9920413,0.005747517,0.0009317062,0.00030177436,0.0000062633244],"about_ca_topic_score_codex":0.0033142716,"about_ca_topic_score_gemma":0.0034615067,"teacher_disagreement_score":0.0033142716,"about_ca_system_score_codex":0.0005240081,"about_ca_system_score_gemma":0.0005010859,"threshold_uncertainty_score":0.006589949},"labels":[],"label_agreement":null},{"id":"W3173875301","doi":"10.18280/jesa.540309","title":"Remarkable Characteristics of a Novel Path Interval Determination in Filleted End Milling","year":2021,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Seikei University","keywords":"Interval (graph theory); Path (computing); Numerical control; Intersection (aeronautics); Boundary (topology); Tool path; Process (computing); Computer science; End milling; Mechanical engineering; Engineering drawing; Engineering; Mathematics; Machining; Mathematical analysis; Aerospace engineering","score_opus":0.01462528682206453,"score_gpt":0.24291348496829332,"score_spread":0.22828819814622878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3173875301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06620054,0.00026278401,0.9293942,0.000053164156,0.000039263647,0.00003757918,0.00003824285,0.0004586204,0.003515619],"genre_scores_gemma":[0.6668157,0.00016089523,0.3310665,0.000027707654,0.000021745374,0.000040165927,0.000113844,0.000073613905,0.0016798135],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991912,0.000094514035,0.000038347844,0.00018484471,0.00044257994,0.000048405534],"domain_scores_gemma":[0.9987931,0.0004514122,0.00021171605,0.00021182593,0.00028316962,0.000048730926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055469084,0.00039478045,0.00035392714,0.0007066971,0.0004237001,0.00070242636,0.00082645606,0.0005051223,0.001442096],"category_scores_gemma":[0.0021920665,0.00023209103,0.00032626747,0.0006724281,0.00051047344,0.0009239955,0.00076469814,0.00066196773,0.00023324146],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007436149,0.00013726756,0.0055788946,0.0004173144,0.000046387064,0.00068443635,0.000802344,0.1578075,0.2437442,0.043329183,0.0017876287,0.54492134],"study_design_scores_gemma":[0.00003837698,0.00051545806,0.0041424045,0.000029569805,0.00003288529,0.0010577259,0.00015506448,0.8511092,0.12110969,0.01178067,0.0099206865,0.000108191976],"about_ca_topic_score_codex":0.0004593692,"about_ca_topic_score_gemma":0.00041138995,"teacher_disagreement_score":0.001442096,"about_ca_system_score_codex":0.0002726317,"about_ca_system_score_gemma":0.00043216758,"threshold_uncertainty_score":0.0048243403},"labels":[],"label_agreement":null},{"id":"W3174718247","doi":"10.1088/1757-899x/1157/1/012081","title":"Parametric Shape Optimization of Stretch Webs in a Progressive Die Process using a Neural Network Surrogate Model","year":2021,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Forming Technologies (Canada)","funders":"","keywords":"Finite element method; Artificial neural network; Surrogate model; Parametric statistics; Process (computing); Computer science; Die (integrated circuit); Bending; Automation; Mechanical engineering; Artificial intelligence; Structural engineering; Engineering; Machine learning; Mathematics","score_opus":0.018674640370240667,"score_gpt":0.2484965873902292,"score_spread":0.22982194701998854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174718247","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.442476,0.00036798252,0.5402289,0.00035523938,0.000040066683,0.000108399814,0.00018772835,0.00024983464,0.015985869],"genre_scores_gemma":[0.9825562,0.00007955509,0.01459782,0.00002196644,0.0000037649056,0.00007186765,0.00007249876,0.000016864755,0.0025794958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998722,0.000046463258,0.000005764884,0.000020272759,0.000037972797,0.00001731357],"domain_scores_gemma":[0.9996346,0.00022152747,0.000042971977,0.000022494403,0.00006379491,0.000014576748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005849946,0.00043873762,0.00046909295,0.0003035771,0.00021325343,0.0005894984,0.000368668,0.00105415,0.0012507054],"category_scores_gemma":[0.0008315647,0.0002713447,0.00049361837,0.00028353577,0.00049103546,0.00036088473,0.00037093146,0.000483193,0.00013023359],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011053251,0.0000072466937,0.000099891186,0.0000062409367,0.0000021064438,0.000010126476,0.0000031169393,0.9982331,0.0004594473,0.00021744646,0.00001885914,0.00093132805],"study_design_scores_gemma":[9.790286e-7,0.000007450576,0.0000346911,8.449515e-7,5.286926e-7,0.0000012195009,8.951035e-7,0.9997553,0.00012344598,0.000050582712,0.000023329005,7.247808e-7],"about_ca_topic_score_codex":0.004229127,"about_ca_topic_score_gemma":0.0023160109,"teacher_disagreement_score":0.004229127,"about_ca_system_score_codex":0.00051256415,"about_ca_system_score_gemma":0.00056215265,"threshold_uncertainty_score":0.008409023},"labels":[],"label_agreement":null},{"id":"W3175173185","doi":"10.21203/rs.3.rs-617721/v1","title":"Study the Effects of Micro-Textured Cutting Tool on Surface Quality and Tool Wear when Machining Aluminium Alloy 7075-T6","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Materials science; Enhanced Data Rates for GSM Evolution; Machining; Aluminium; Metallurgy; Surface roughness; Tungsten carbide; Tool wear; Insert (composites); Rake; Lubrication; Surface finish; Cutting tool; Aluminium alloy; Alloy; Mechanical engineering; Composite material; Computer science; Engineering","score_opus":0.04490120334498755,"score_gpt":0.3775942843299947,"score_spread":0.33269308098500716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175173185","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99861515,0.0002706839,0.0009297491,0.00000714133,0.0000068542386,0.0000067995297,0.000018373461,0.00001231062,0.00013291767],"genre_scores_gemma":[0.9981834,0.00011723755,0.0014174251,0.000007141729,0.0000028256068,0.0000038312573,0.00001925909,0.000005557589,0.00024325245],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997392,0.000017510118,0.000015568905,0.000041481544,0.00015157249,0.000034617206],"domain_scores_gemma":[0.9993344,0.00019823214,0.000182384,0.000056748653,0.00020154634,0.000026589063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020446947,0.00020355795,0.00029191363,0.0002070659,0.00014530064,0.00032168243,0.0002212136,0.00032559194,0.0006210275],"category_scores_gemma":[0.00069844665,0.00016222034,0.00032085084,0.00018807284,0.00022155388,0.0002536669,0.00019374615,0.00022903825,0.0000986177],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026272645,0.000051320047,0.0044630985,0.00019675575,0.000017765087,0.00012255374,0.00015268024,0.0007556959,0.98561907,0.000022638058,0.000035938316,0.008299723],"study_design_scores_gemma":[0.000015018432,0.0023016492,0.054974727,0.000012823228,0.000053529213,0.00027920218,0.00031857745,0.0066026207,0.9346281,0.000027257987,0.00076050725,0.000026060181],"about_ca_topic_score_codex":0.0008591687,"about_ca_topic_score_gemma":0.0019694085,"teacher_disagreement_score":0.0008591687,"about_ca_system_score_codex":0.00017267295,"about_ca_system_score_gemma":0.000077886776,"threshold_uncertainty_score":0.00207752},"labels":[],"label_agreement":null},{"id":"W3175356714","doi":"10.1007/978-3-030-71438-3_10","title":"Drilling of Fibre Reinforced Polymers and Hybrid Stacked Materials","year":2021,"lang":"en","type":"book-chapter","venue":"Engineering materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Aerospace; Delamination (geology); Process (computing); Drilling; Machining; Mechanical engineering; Tool wear; Materials science; Engineering; Manufacturing engineering; Computer science; Aerospace engineering; Geology","score_opus":0.005356585227201861,"score_gpt":0.179981683697687,"score_spread":0.17462509847048513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175356714","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11299335,0.098151736,0.3193101,0.0005570495,0.0026182854,0.00013912724,0.00044372803,0.0013583737,0.4644283],"genre_scores_gemma":[0.32673246,0.03635893,0.20956723,0.00025105136,0.00038129246,0.00010905787,0.00046130255,0.00031278207,0.42582586],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99992526,0.0000045301276,0.000002181616,0.000012344876,0.000045120683,0.000010560461],"domain_scores_gemma":[0.99996555,0.000013104337,0.000004552398,0.000007283875,0.0000062752615,0.0000032437674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008376176,0.0004119818,0.00028950375,0.00047029532,0.00020946945,0.0005188746,0.00033675836,0.00040320895,0.005783632],"category_scores_gemma":[0.00013286127,0.00035376442,0.00024459916,0.00047730072,0.0002707702,0.0012014003,0.0005521428,0.00049647724,0.0014551579],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009842371,0.000056798206,0.0002297932,0.0011356701,0.000024732428,0.00043122875,0.00023214145,0.011005941,0.34334043,0.09502854,0.013752848,0.5346635],"study_design_scores_gemma":[0.0000137922925,0.00034249554,0.0019742723,0.00028129903,0.000025469819,0.0027521735,0.00020080159,0.020969408,0.25279713,0.043345895,0.677242,0.000055353783],"about_ca_topic_score_codex":0.0001944648,"about_ca_topic_score_gemma":0.0008567235,"teacher_disagreement_score":0.005783632,"about_ca_system_score_codex":0.00017646965,"about_ca_system_score_gemma":0.00015808703,"threshold_uncertainty_score":0.019348145},"labels":[],"label_agreement":null},{"id":"W3175450364","doi":"10.21203/rs.3.rs-286538/v1","title":"Towards Analysis and Optimization during Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machinability; Machining; Hardened steel; Materials science; Tool wear; Mechanical engineering; Surface roughness; Process (computing); Surface finish; Metallurgy; Computer science; Engineering; Composite material","score_opus":0.023290150554017057,"score_gpt":0.30605554019899317,"score_spread":0.2827653896449761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175450364","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8825483,0.0003058307,0.1133901,0.000051904048,0.000010844222,0.00011458704,0.00009713086,0.00021559373,0.0032657522],"genre_scores_gemma":[0.9771886,0.00010857975,0.021783601,0.0000065818676,0.0000012318396,0.000048949783,0.000078762285,0.000018953635,0.0007646435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977034,0.000040642288,0.00001408353,0.000040213636,0.00009594599,0.00003875415],"domain_scores_gemma":[0.99968266,0.0001617213,0.000053332107,0.000018444922,0.0000742323,0.000009544073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004945132,0.00062637747,0.0004934911,0.00062396936,0.00025315516,0.00075150974,0.00041115025,0.0006734822,0.00080985005],"category_scores_gemma":[0.0006543601,0.00032680103,0.0007765249,0.0004190712,0.00025239817,0.00024704554,0.00022178573,0.00027389606,0.00010536043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061384264,0.00010584465,0.0019362946,0.00018406546,0.000034198874,0.00010281127,0.000049672773,0.951729,0.030334655,0.00030198955,0.000053694017,0.015106385],"study_design_scores_gemma":[0.000009887503,0.0002465531,0.0019173224,0.0000066372068,0.000023561728,0.000015347796,0.00004867445,0.9857373,0.0114946775,0.00015828093,0.00033472723,0.000007039235],"about_ca_topic_score_codex":0.0055812593,"about_ca_topic_score_gemma":0.004575343,"teacher_disagreement_score":0.0055812593,"about_ca_system_score_codex":0.00053910183,"about_ca_system_score_gemma":0.0007234456,"threshold_uncertainty_score":0.01109755},"labels":[],"label_agreement":null},{"id":"W3177302046","doi":"10.1115/1.4051605","title":"Analytical Modeling of Shear Localization in Orthogonal Cutting Processes","year":2021,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Defence Research and Development Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Shear band; Adiabatic shear band; Shear (geology); Materials science; Shear stress; Simple shear; Shear rate; Rake; Finite element method; Critical resolved shear stress; Mechanics; Shear zone; Composite material; Structural engineering; Geology; Mechanical engineering; Rheology; Engineering; Physics","score_opus":0.00934558008906939,"score_gpt":0.2280528980525483,"score_spread":0.21870731796347892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177302046","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3475937,0.0004338562,0.63803613,0.00013993094,0.000039863695,0.000050044117,0.000074616306,0.00022906416,0.013402834],"genre_scores_gemma":[0.98460674,0.00015272122,0.0124167,0.000016094442,0.000007258382,0.00003384695,0.000021896813,0.000025423138,0.0027192768],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999869,0.000021476508,0.0000045552674,0.000020383779,0.000059097783,0.000025469177],"domain_scores_gemma":[0.9998449,0.000055711283,0.000038051443,0.00001674395,0.00003622351,0.0000083816385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002841173,0.00033005708,0.0003596893,0.00038902895,0.0002450646,0.00047113845,0.000570054,0.00061374175,0.0009090001],"category_scores_gemma":[0.0006725659,0.00031849288,0.0004191204,0.00023773,0.0006350124,0.0005063634,0.00034701862,0.00030193533,0.00023557812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023646793,0.000020662821,0.0003996574,0.000017689528,0.0000050587523,0.00006681092,0.00005128755,0.9728001,0.014088395,0.009696493,0.000068188776,0.0027618944],"study_design_scores_gemma":[0.0000016141768,0.000004834153,0.00006705387,9.655104e-7,9.2219295e-7,0.000005556234,0.0000029026658,0.99884653,0.00057645864,0.00040649367,0.00008518454,0.0000014822255],"about_ca_topic_score_codex":0.003443853,"about_ca_topic_score_gemma":0.0015291731,"teacher_disagreement_score":0.003443853,"about_ca_system_score_codex":0.00063300924,"about_ca_system_score_gemma":0.00060399686,"threshold_uncertainty_score":0.00684762},"labels":[],"label_agreement":null},{"id":"W3181851684","doi":"10.1016/j.cirpj.2021.06.019","title":"Experimental comparison of different automatically tuned control strategies for active vibration control","year":2021,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Bayerisches Staatsministerium für Wissenschaft, Forschung und Kunst; Bayerisches Staatsministerium für Bildung und Kultus, Wissenschaft und Kunst; University of Waterloo","keywords":"Controller (irrigation); Control theory (sociology); Vibration; Particle swarm optimization; Engineering; Control engineering; Vibration control; Mode (computer interface); Machine tool; Computer science; Control (management); Mechanical engineering; Artificial intelligence; Acoustics; Algorithm","score_opus":0.007682525848317643,"score_gpt":0.2654782178958026,"score_spread":0.257795692047485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3181851684","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9407183,0.0005090142,0.053338815,0.00004916553,0.00016544918,0.0001530911,0.00015936818,0.00038343758,0.004523354],"genre_scores_gemma":[0.9957014,0.000044323453,0.003605001,0.000011427256,0.0000053153944,0.000044783697,0.000035043147,0.00001810647,0.00053451135],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99957496,0.00006511904,0.000045810066,0.000080854676,0.00014401703,0.00008928518],"domain_scores_gemma":[0.99891007,0.00058150955,0.00010771413,0.000102023514,0.00025708118,0.000041526822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038661715,0.00048654262,0.00041759055,0.00048932695,0.00030676674,0.00046639502,0.0006871599,0.0007060476,0.0038828992],"category_scores_gemma":[0.0015070115,0.00024955353,0.00023386096,0.00021908434,0.00029716326,0.00036940418,0.0002567904,0.00029288908,0.00029202306],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005579138,0.0016024687,0.00075725256,0.00088894996,0.00006873857,0.00007641338,0.00022641076,0.014527495,0.8887946,0.00065693125,0.0003866294,0.086434975],"study_design_scores_gemma":[0.0009885362,0.013917866,0.022760669,0.00011126729,0.00026447698,0.00021091032,0.000252437,0.19509503,0.762377,0.0005758903,0.0033392385,0.00010665271],"about_ca_topic_score_codex":0.000999166,"about_ca_topic_score_gemma":0.00092239154,"teacher_disagreement_score":0.0038828992,"about_ca_system_score_codex":0.0001868278,"about_ca_system_score_gemma":0.00018683991,"threshold_uncertainty_score":0.012989521},"labels":[],"label_agreement":null},{"id":"W3184008549","doi":"10.1088/2631-8695/ac1848","title":"A numerical study of the effect of the thickness parameter on machining distortion for aluminum alloy plates","year":2021,"lang":"en","type":"article","venue":"Engineering Research Express","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Distortion (music); Machining; Residual stress; Materials science; Finite element method; Structural engineering; Deformation (meteorology); Aluminium; Position (finance); Composite material; Engineering; Metallurgy","score_opus":0.018441629706281205,"score_gpt":0.30098410459969255,"score_spread":0.28254247489341133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184008549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9856252,0.00008310599,0.01206172,0.000031951964,0.000009144478,0.000016014032,0.00003956128,0.00004831592,0.002084941],"genre_scores_gemma":[0.9965102,0.000022464397,0.003234096,0.0000034029308,8.773001e-7,0.0000044401127,0.00001292671,0.0000058462783,0.0002058892],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986124,0.000035224974,0.000009320258,0.0000148309255,0.000052983443,0.000026318057],"domain_scores_gemma":[0.9986833,0.00091303216,0.00015455329,0.00009354046,0.00011661922,0.000038978815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043307152,0.00030051492,0.0003070555,0.00028290635,0.00028833552,0.00036727765,0.00039930313,0.00045209733,0.0010776633],"category_scores_gemma":[0.0017829023,0.0002449338,0.00030094985,0.00033824198,0.00050083525,0.00022075365,0.00018814729,0.00023785651,0.00007305212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030060235,0.000083126615,0.0072652246,0.00012256963,0.000032070177,0.0003104481,0.00013527519,0.93458223,0.048408613,0.0010268572,0.00010537321,0.00762771],"study_design_scores_gemma":[0.000019491257,0.00020676662,0.004044522,0.000008898686,0.000015034266,0.00006332706,0.00006961541,0.98416454,0.011088032,0.00011590629,0.00019221888,0.000011638652],"about_ca_topic_score_codex":0.0045939726,"about_ca_topic_score_gemma":0.0038408192,"teacher_disagreement_score":0.0045939726,"about_ca_system_score_codex":0.00039220366,"about_ca_system_score_gemma":0.00030120532,"threshold_uncertainty_score":0.009134471},"labels":[],"label_agreement":null},{"id":"W3185182094","doi":"10.1007/s00170-021-07745-5","title":"Multi-response optimization using artificial neural network-based GWO algorithm for high machining performance with minimum quantity lubrication","year":2021,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Machining; Surface roughness; Artificial neural network; Taguchi methods; Lubrication; Response surface methodology; Insert (composites); Mechanical engineering; Tool wear; RADIUS; Lubricant; Algorithm; Engineering; Materials science; Computer science; Composite material; Artificial intelligence; Machine learning","score_opus":0.013557385357505253,"score_gpt":0.25716059214192544,"score_spread":0.24360320678442018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185182094","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10764417,0.00053401076,0.884904,0.00021602945,0.00011628892,0.0000714907,0.00003910324,0.00040394618,0.0060708947],"genre_scores_gemma":[0.847247,0.00015731319,0.14849612,0.00008038848,0.000029335744,0.00017612815,0.00008089808,0.00010035642,0.0036324267],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998505,0.000041851792,0.000008409685,0.000030593477,0.000045900193,0.000022726188],"domain_scores_gemma":[0.999775,0.00012499533,0.000027970696,0.0000120006325,0.000048921527,0.000011159417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044836217,0.00064838224,0.0008044948,0.00043375348,0.00032113545,0.0004700352,0.0006640658,0.0008849979,0.0016593183],"category_scores_gemma":[0.0007455965,0.00034108752,0.00054906955,0.00040642353,0.0003402102,0.00056312035,0.00051479024,0.00060401036,0.00019670224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007534296,0.000058968526,0.0003181734,0.00006108457,0.00002547105,0.0000355878,0.000024001132,0.96892613,0.004196386,0.001179681,0.00032562285,0.024773486],"study_design_scores_gemma":[0.0000030865083,0.000014850547,0.000051041192,0.0000011776596,0.000001909564,0.0000021301812,0.0000019241904,0.9995022,0.00023553427,0.000115677416,0.00006926287,0.0000011580357],"about_ca_topic_score_codex":0.00294594,"about_ca_topic_score_gemma":0.0031673864,"teacher_disagreement_score":0.00294594,"about_ca_system_score_codex":0.00029840594,"about_ca_system_score_gemma":0.000629728,"threshold_uncertainty_score":0.005857587},"labels":[],"label_agreement":null},{"id":"W3185230479","doi":"10.1007/s00170-021-07725-9","title":"Finite element simulation of cutting process under the worn tool edge geometries","year":2021,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Flank; Enhanced Data Rates for GSM Evolution; Finite element method; Materials science; Mechanical engineering; Tool wear; Process (computing); Cutting tool; Rake angle; Mechanics; Structural engineering; Metallurgy; Engineering; Computer science; Machining","score_opus":0.008617378656073836,"score_gpt":0.2664244623369455,"score_spread":0.2578070836808717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185230479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83134615,0.00028210098,0.12917615,0.0003205661,0.0001375036,0.0001128941,0.0011357124,0.00074142654,0.036747415],"genre_scores_gemma":[0.98198867,0.00009796995,0.013791467,0.000032885437,0.000006327343,0.00004698718,0.0003584778,0.000060187227,0.0036171414],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997856,0.000037362457,0.000010810252,0.000029746388,0.00009053808,0.00004585574],"domain_scores_gemma":[0.99932766,0.00038191935,0.0000626084,0.00006776248,0.00012006233,0.00003999485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031774983,0.00040516476,0.0006947609,0.00046165558,0.00039514588,0.00074040965,0.0010394467,0.0018293904,0.005552628],"category_scores_gemma":[0.0012280891,0.0004146911,0.0005962097,0.0005245291,0.00057442003,0.00045088815,0.00034691062,0.0005616522,0.0004948987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000652769,0.000052906373,0.0006259191,0.00004701746,0.0000108385675,0.000066848675,0.00006211806,0.9910813,0.00385911,0.00123892,0.00020597814,0.0026838533],"study_design_scores_gemma":[0.000007683963,0.000026106158,0.00031464116,0.0000040685914,0.0000031756497,0.000014033998,0.000022609573,0.99824655,0.0009708722,0.00015389985,0.00023129139,0.0000050923595],"about_ca_topic_score_codex":0.006641978,"about_ca_topic_score_gemma":0.0050683133,"teacher_disagreement_score":0.006641978,"about_ca_system_score_codex":0.0004350923,"about_ca_system_score_gemma":0.00080046104,"threshold_uncertainty_score":0.01857537},"labels":[],"label_agreement":null},{"id":"W3186491567","doi":"","title":"Fatigue Reliability Assessment of Drill String Due to Stick-Slip Vibrations and Wave-Frequency Vessel Motions","year":2021,"lang":"en","type":"article","venue":"The 31st International Ocean and Polar Engineering Conference","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Drill string; Vibration; Slip (aerodynamics); Structural engineering; Reliability (semiconductor); Engineering; Physics; Drill; Mechanics; Acoustics; Mechanical engineering; Aerospace engineering","score_opus":0.016207255385245648,"score_gpt":0.2550523425437472,"score_spread":0.23884508715850156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186491567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9671543,0.00047475687,0.031023074,0.00004323801,0.000033705925,0.000038633494,0.00018161,0.00019779605,0.000852904],"genre_scores_gemma":[0.99860495,0.0000404033,0.0009854846,0.0000062261142,0.0000043029254,0.000009888619,0.0000672146,0.00000661173,0.0002749367],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993874,0.00011903495,0.00005363407,0.00009947734,0.00027176185,0.00006868013],"domain_scores_gemma":[0.9953122,0.0015035121,0.0005932376,0.0002947668,0.0021094752,0.00018670538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011033382,0.00045498594,0.00044812547,0.0014935341,0.00024883292,0.00021659135,0.0005014414,0.00085257116,0.0011057367],"category_scores_gemma":[0.0033568402,0.00031306082,0.00053492043,0.0004023849,0.0002925458,0.0004432624,0.0002967287,0.00027555195,0.00033189252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005615055,0.00039860356,0.12943624,0.0007970532,0.00042309662,0.0018723331,0.0011251599,0.2804233,0.40834764,0.0005831391,0.001814454,0.16916387],"study_design_scores_gemma":[0.000053555355,0.005627099,0.22065412,0.00007418242,0.000301989,0.00107747,0.00032328165,0.7096747,0.06090139,0.00034242184,0.0008812107,0.00008849613],"about_ca_topic_score_codex":0.0014887807,"about_ca_topic_score_gemma":0.0022612293,"teacher_disagreement_score":0.0014935341,"about_ca_system_score_codex":0.0003188608,"about_ca_system_score_gemma":0.00019140284,"threshold_uncertainty_score":0.005835116},"labels":[],"label_agreement":null},{"id":"W3191263520","doi":"10.1007/s10845-021-01822-y","title":"Predicting the quality of a machined workpiece with a variational autoencoder approach","year":2021,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Autoencoder; Metric (unit); Machining; Dimensioning; Artificial intelligence; Quality (philosophy); Context (archaeology); Computer science; Euclidean distance; Interval (graph theory); Algorithm; Mathematics; Pattern recognition (psychology); Engineering; Deep learning; Mechanical engineering","score_opus":0.016928210276048027,"score_gpt":0.25472980431430053,"score_spread":0.23780159403825252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191263520","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15540124,0.00031976114,0.8428993,0.00012473909,0.000045278906,0.000027432685,0.000055048884,0.00039300206,0.0007341857],"genre_scores_gemma":[0.936767,0.00014874997,0.061535083,0.00004125508,0.000021773283,0.00002827039,0.00009668893,0.000041781088,0.0013194483],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999846,0.00002087339,0.000008682118,0.000051505755,0.000051138377,0.000021763573],"domain_scores_gemma":[0.9996214,0.00020786343,0.000050546474,0.000033936492,0.00006875192,0.00001750535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046305225,0.00042969175,0.0005740952,0.00036715265,0.00015964851,0.00052382983,0.0007703196,0.0010658746,0.00070383225],"category_scores_gemma":[0.0010770869,0.0005638301,0.0006411395,0.000299905,0.0004581969,0.00058925373,0.0004932306,0.0008111166,0.00015193434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007264939,0.000043712254,0.0009584345,0.000030288846,0.000045277335,0.000032524607,0.000019305198,0.9511674,0.010215898,0.00076716114,0.00017293364,0.036474377],"study_design_scores_gemma":[9.197411e-7,0.000005045939,0.00014681452,6.0799937e-7,0.000001680401,0.000002481554,5.6790094e-7,0.9993825,0.00037717642,0.00006725102,0.000013873481,0.0000010912785],"about_ca_topic_score_codex":0.008353393,"about_ca_topic_score_gemma":0.0069443416,"teacher_disagreement_score":0.008353393,"about_ca_system_score_codex":0.0005076513,"about_ca_system_score_gemma":0.00057051657,"threshold_uncertainty_score":0.01660955},"labels":[],"label_agreement":null},{"id":"W3192166487","doi":"10.3390/ma14154293","title":"Low and High Speed Orthogonal Cutting of AA6061-T6 under Dry and Flood-Coolant Modes: Tool Wear and Residual Stress Measurements and Predictions","year":2021,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Residual stress; Machining; Coolant; Materials science; Tool wear; Ultimate tensile strength; Residual; Composite material; Cutting fluid; Normal force; Metallurgy; Structural engineering; Mechanical engineering; Mechanics; Engineering; Computer science","score_opus":0.013156220054402583,"score_gpt":0.21945590857468636,"score_spread":0.20629968852028377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3192166487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976603,0.00010187352,0.0019168596,0.000004878484,0.0000056107488,0.0000054909515,0.00006292212,0.000019459374,0.00022259245],"genre_scores_gemma":[0.99695766,0.00008080856,0.0025290227,0.0000028088566,0.0000015565713,0.000005940857,0.00007130318,0.000005783822,0.00034509026],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997882,0.000010387642,0.000011469443,0.00003527922,0.00013091502,0.000023845128],"domain_scores_gemma":[0.9997347,0.000065005835,0.00007427703,0.000032368036,0.00007356137,0.000020156698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031621344,0.00022339507,0.00024359884,0.0003103666,0.00014790065,0.00022580245,0.00019604295,0.00031790498,0.00083424203],"category_scores_gemma":[0.000392124,0.00013821073,0.0002855898,0.00025184194,0.00024587158,0.00023806047,0.00016830816,0.00019437452,0.000114944116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041593143,0.000053174324,0.0075624874,0.00018202544,0.000009805877,0.0001322958,0.00014821316,0.012043361,0.96533793,0.00017184077,0.00008965209,0.013853261],"study_design_scores_gemma":[0.000028580871,0.0021987455,0.07410256,0.000022156766,0.00003653618,0.00034045745,0.00034779884,0.09968219,0.82070917,0.00025138544,0.002220073,0.000060399685],"about_ca_topic_score_codex":0.0007573831,"about_ca_topic_score_gemma":0.0014439313,"teacher_disagreement_score":0.00083424203,"about_ca_system_score_codex":0.0001258364,"about_ca_system_score_gemma":0.0001191894,"threshold_uncertainty_score":0.0027908683},"labels":[],"label_agreement":null},{"id":"W3195204777","doi":"10.3390/lubricants9080084","title":"An Evaluation of the Tribological Behavior of Cutting Fluid Additives on Aluminum-Manganese Alloys","year":2021,"lang":"en","type":"article","venue":"Lubricants","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tribology; Materials science; Lubrication; Boundary lubrication; Machining; Composite material; Metallurgy; Aluminium","score_opus":0.02654348511586082,"score_gpt":0.293778791124386,"score_spread":0.2672353060085252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3195204777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982565,0.0007045743,0.0006474672,0.000007671343,0.0000071630093,0.000014104325,0.000042502874,0.000012695072,0.0003073588],"genre_scores_gemma":[0.9976392,0.00045516374,0.0012769767,0.0000060873667,0.00000378077,0.0000081629205,0.000050782102,0.000005702388,0.00055414607],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995402,0.00006614676,0.000042485754,0.00005323239,0.0002478268,0.000050037637],"domain_scores_gemma":[0.9995963,0.00006310906,0.000083991035,0.000021653725,0.00020916747,0.00002578939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029001868,0.0003737322,0.00030691273,0.0006707819,0.00027168097,0.00030474836,0.00027017505,0.00027911857,0.00053055986],"category_scores_gemma":[0.00066052645,0.00014989499,0.0002563249,0.0004399656,0.00018850641,0.0003191035,0.00018925923,0.00020964148,0.00013577663],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022321123,0.00003464459,0.0013723923,0.00012344388,0.0000100767575,0.00008433554,0.000076540964,0.00026377724,0.9920387,0.000021398511,0.00001509327,0.005736395],"study_design_scores_gemma":[0.0000033848444,0.00092432555,0.0076459893,0.000009063464,0.000028976983,0.00010105515,0.0000824321,0.001182849,0.98920804,0.000007388415,0.00079682,0.000009610447],"about_ca_topic_score_codex":0.0012312692,"about_ca_topic_score_gemma":0.0020903035,"teacher_disagreement_score":0.0012312692,"about_ca_system_score_codex":0.00021531167,"about_ca_system_score_gemma":0.00017259033,"threshold_uncertainty_score":0.0024482012},"labels":[],"label_agreement":null},{"id":"W3196386841","doi":"10.32920/ryerson.14645091.v1","title":"Drilling Burr Formation With Tool Wear","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Drilling; Machining; Drill; Mechanical engineering; Shearing (physics); Enhanced Data Rates for GSM Evolution; Engineering; Thrust; Cutting tool; Shear (geology); Geology; Geotechnical engineering","score_opus":0.006439948117775516,"score_gpt":0.1979511221722905,"score_spread":0.19151117405451498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196386841","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2876345,0.001910502,0.6906027,0.00034909247,0.00014631856,0.00026456124,0.0002609162,0.00055966584,0.018271755],"genre_scores_gemma":[0.9784137,0.0005415826,0.014891874,0.000034903842,0.000014646805,0.000075012555,0.00007441504,0.000034837733,0.0059189927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995505,0.000078815116,0.000027481,0.00012334443,0.00015832348,0.000061444414],"domain_scores_gemma":[0.99891794,0.00041058104,0.00032289771,0.00015399836,0.00015728676,0.000037230908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063580537,0.00082587305,0.00069699617,0.0005307604,0.00025837912,0.0012421984,0.0013453433,0.0014335063,0.0010680768],"category_scores_gemma":[0.0018912265,0.0006162837,0.0013170907,0.00031425155,0.00092377147,0.0014970667,0.0009200848,0.0007661537,0.00020757016],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038822738,0.000040202252,0.0014007158,0.00012381654,0.000016674014,0.00021987723,0.00013661005,0.9750019,0.009192179,0.006280674,0.00018539991,0.0073630796],"study_design_scores_gemma":[0.000015295065,0.000073496936,0.0006869448,0.000010931609,0.000013414614,0.0001415162,0.000024580293,0.99453706,0.0017542854,0.001864962,0.00086280546,0.0000146888215],"about_ca_topic_score_codex":0.0048317895,"about_ca_topic_score_gemma":0.002731932,"teacher_disagreement_score":0.0048317895,"about_ca_system_score_codex":0.00054501655,"about_ca_system_score_gemma":0.00060299144,"threshold_uncertainty_score":0.009607315},"labels":[],"label_agreement":null},{"id":"W3196439122","doi":"10.1016/j.procir.2020.11.008","title":"High performance grinding of titanium alloys with electroplated diamond wheels","year":2021,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Electroplating; Materials science; Metallurgy; Grinding; Surface roughness; Diamond; Titanium; Surface finish; Titanium alloy; Diamond grinding; Grinding wheel; Composite material; Alloy; Layer (electronics)","score_opus":0.003579963357170561,"score_gpt":0.1748881087462988,"score_spread":0.17130814538912822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196439122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99171245,0.00070593925,0.0065591517,0.00001615055,0.000025072739,0.000019426405,0.00005885627,0.000063088424,0.0008398564],"genre_scores_gemma":[0.9844503,0.00033733805,0.013208887,0.000010395738,0.000005514862,0.000009005801,0.00010515005,0.000042583884,0.0018308901],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99947363,0.00002659576,0.000020038826,0.00006847402,0.00032470052,0.00008667112],"domain_scores_gemma":[0.999579,0.00012352537,0.00007269352,0.00006782919,0.00012369736,0.00003330095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005196542,0.0003296888,0.0004957826,0.0004699151,0.00024536432,0.0003372795,0.0005529968,0.00034152175,0.00083109806],"category_scores_gemma":[0.0007151895,0.000256213,0.00033961344,0.00032364193,0.00033417344,0.0002491458,0.00029343885,0.00031167336,0.0002326316],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000638533,0.00001550909,0.00042683486,0.00006583362,0.0000058996075,0.000057281577,0.00005564197,0.0006409799,0.99484825,0.000041497588,0.000032118576,0.0037463163],"study_design_scores_gemma":[0.000012598273,0.00033382195,0.0086374255,0.000005187112,0.000011621978,0.0000994815,0.00004142152,0.0029023709,0.9866443,0.000031580093,0.0012703137,0.000009859965],"about_ca_topic_score_codex":0.002753094,"about_ca_topic_score_gemma":0.010810329,"teacher_disagreement_score":0.002753094,"about_ca_system_score_codex":0.00044265648,"about_ca_system_score_gemma":0.00031563814,"threshold_uncertainty_score":0.0054740906},"labels":[],"label_agreement":null},{"id":"W3197205684","doi":"10.23977/aetp.2021.55017","title":"Innovative Application of Friction Stir Welding in Practical Teaching","year":2021,"lang":"en","type":"article","venue":"Advances in Educational Technology and Psychology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Welding; Consciousness; Computer science; Course (navigation); Mathematics education; Engineering; Psychology; Mechanical engineering","score_opus":0.009500449580684713,"score_gpt":0.3657592676793043,"score_spread":0.3562588180986196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3197205684","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27065176,0.0075000506,0.4533967,0.0051011457,0.002493708,0.0012526833,0.000086283115,0.0024161697,0.25710157],"genre_scores_gemma":[0.57468367,0.005405984,0.33908528,0.0010926201,0.00059427187,0.00060945225,0.00012977052,0.00010537508,0.0782935],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996859,0.0000823435,0.0000116843385,0.00005081349,0.000104238155,0.00006497341],"domain_scores_gemma":[0.9997873,0.00005546972,0.000010660002,0.00001886717,0.000040439107,0.00008744933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047894238,0.00061033457,0.00020987488,0.0004417407,0.00039755326,0.00074669364,0.0008568587,0.0008402302,0.00667843],"category_scores_gemma":[0.00073707587,0.00016010707,0.00041227115,0.00024247754,0.00047271317,0.00068609853,0.0013705603,0.0007138569,0.0011984679],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002614064,0.0021465444,0.0021239496,0.0009994566,0.000020674934,0.0013706221,0.003052195,0.0060475697,0.08994278,0.031296603,0.017838886,0.8448993],"study_design_scores_gemma":[0.00047102332,0.0055971285,0.024449097,0.0015577048,0.00015143568,0.015647886,0.0040509887,0.07906577,0.08273969,0.08440064,0.7016398,0.00022890214],"about_ca_topic_score_codex":0.00027576456,"about_ca_topic_score_gemma":0.00057236163,"teacher_disagreement_score":0.00667843,"about_ca_system_score_codex":0.0003688146,"about_ca_system_score_gemma":0.0009209715,"threshold_uncertainty_score":0.022341609},"labels":[],"label_agreement":null},{"id":"W3197364050","doi":"10.1016/j.procir.2021.02.036","title":"Sustainable machining of Ti-6Al-4V using cryogenic cooling: an optimized approach","year":2021,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"","keywords":"Machining; Mechanical engineering; Grey relational analysis; Materials science; Surface roughness; Sorting; Taguchi methods; Cryogenic treatment; Genetic algorithm; Surface finish; Metallurgy; Process engineering; Computer science; Engineering; Composite material; Microstructure; Mathematics","score_opus":0.01606122135367655,"score_gpt":0.24960440141631454,"score_spread":0.233543180062638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3197364050","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8022123,0.00064416695,0.19174425,0.00011339879,0.00001996462,0.00007268868,0.00009406219,0.00013898681,0.004960163],"genre_scores_gemma":[0.9625379,0.00017040143,0.036586843,0.000011488475,0.000002676596,0.000036636247,0.000048797927,0.000017075501,0.00058834266],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99991,0.000010817455,0.0000027516892,0.000013599426,0.000045256176,0.000017494347],"domain_scores_gemma":[0.99993694,0.00001924786,0.000014167546,0.0000064532173,0.00001942524,0.0000037605546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026037305,0.00027339827,0.0003023487,0.00031605037,0.00021502096,0.00038363488,0.00035723668,0.00032243927,0.00055103033],"category_scores_gemma":[0.00022543139,0.00023222606,0.0003533052,0.00023476576,0.0002456096,0.0003127774,0.00026061645,0.00026297118,0.00007692037],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013514007,0.000066967936,0.0021999034,0.000231045,0.000040846284,0.00013102061,0.00009175246,0.70109963,0.26274288,0.0023491497,0.00026911503,0.030642532],"study_design_scores_gemma":[0.000035735255,0.0005978012,0.0049264687,0.000017006172,0.000054091037,0.00010603234,0.00012543387,0.89594764,0.09422422,0.001906682,0.0020343217,0.000024508094],"about_ca_topic_score_codex":0.0015965201,"about_ca_topic_score_gemma":0.0036392221,"teacher_disagreement_score":0.0015965201,"about_ca_system_score_codex":0.00033951763,"about_ca_system_score_gemma":0.00060622796,"threshold_uncertainty_score":0.0031744242},"labels":[],"label_agreement":null},{"id":"W3198391813","doi":"10.1115/1.4052007","title":"Chatter Stability of Serrated Milling Tools in Frequency Domain","year":2021,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Serration; Stability (learning theory); Time domain; Frequency domain; RADIUS; Nyquist stability criterion; Control theory (sociology); Structural engineering; Engineering; Computer science; Mechanical engineering; Mathematical analysis; Mathematics","score_opus":0.012696806152479017,"score_gpt":0.22077269348063278,"score_spread":0.20807588732815377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198391813","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41463348,0.00027645507,0.58046156,0.000086725384,0.000030281262,0.00003506663,0.00005748029,0.00044982176,0.003969105],"genre_scores_gemma":[0.9906826,0.000055482695,0.008171541,0.000006280592,0.0000023166522,0.000013165471,0.0000167196,0.000014175741,0.0010377679],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998323,0.0000398234,0.000007045933,0.000030542167,0.00007461721,0.000015657659],"domain_scores_gemma":[0.9991943,0.00045733506,0.00014218704,0.000059760278,0.00012685405,0.000019527659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003854364,0.00033012818,0.00029467267,0.00034846837,0.00019878166,0.00044896652,0.00043843684,0.0004560183,0.0008078276],"category_scores_gemma":[0.001449531,0.00015910385,0.0003234809,0.00015206392,0.00062118703,0.00039340602,0.00020605809,0.000368912,0.00012572379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000115275114,0.00002596483,0.001371833,0.00008904526,0.000021764386,0.00015088833,0.00022637245,0.94427395,0.035834327,0.007998211,0.00019352119,0.009698916],"study_design_scores_gemma":[0.0000015156079,0.000009740534,0.00010001148,0.0000019391462,9.063677e-7,0.0000073435504,0.0000042826255,0.9980246,0.0015259102,0.00025817478,0.00006327021,0.00000229445],"about_ca_topic_score_codex":0.003117857,"about_ca_topic_score_gemma":0.0014023621,"teacher_disagreement_score":0.003117857,"about_ca_system_score_codex":0.0004820337,"about_ca_system_score_gemma":0.00035094694,"threshold_uncertainty_score":0.0061994195},"labels":[],"label_agreement":null},{"id":"W3198781634","doi":"10.1007/s00170-021-06643-0","title":"Theoretical and experimental studies of chatter in turning and machining stainless steel workpiece","year":2021,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Machining; Stiffness; Structural engineering; Timoshenko beam theory; Flexibility (engineering); Machine tool; Engineering; Cutting tool; Damper; Mechanical engineering; Moment (physics); Bending; Beam (structure); Mathematics","score_opus":0.006733318484860352,"score_gpt":0.2729127093718209,"score_spread":0.2661793908869605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198781634","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9695519,0.0006517913,0.021143561,0.00007266699,0.000024482542,0.000032121596,0.000034886725,0.00009072898,0.008397779],"genre_scores_gemma":[0.998021,0.000081457634,0.0011930418,0.0000033909816,0.0000036636418,0.00000590621,0.000011888393,0.0000061047913,0.0006735423],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996358,0.00009201621,0.000011015844,0.00004153532,0.00016922902,0.00005044054],"domain_scores_gemma":[0.99601424,0.0032710144,0.00014120644,0.00017993702,0.00034384793,0.000049801154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070751517,0.00032064322,0.00034494905,0.0005249825,0.00064153346,0.00038628725,0.001158339,0.00058221404,0.003670822],"category_scores_gemma":[0.0036290092,0.00032963473,0.0002703606,0.00031359433,0.0014107823,0.0006384833,0.0002574263,0.0005886169,0.00019086756],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024605915,0.0007778594,0.007736772,0.0012399878,0.0000679338,0.0013020422,0.002371592,0.15092108,0.7491236,0.043347247,0.0005868411,0.040064476],"study_design_scores_gemma":[0.00013541021,0.0014026563,0.016521323,0.000048850667,0.000054395758,0.0008757586,0.0010362586,0.6202614,0.35194486,0.0058265985,0.0017981742,0.0000942143],"about_ca_topic_score_codex":0.0013047882,"about_ca_topic_score_gemma":0.0013118783,"teacher_disagreement_score":0.003670822,"about_ca_system_score_codex":0.00048885494,"about_ca_system_score_gemma":0.00026345978,"threshold_uncertainty_score":0.012280107},"labels":[],"label_agreement":null},{"id":"W3200386066","doi":"10.21203/rs.3.rs-893942/v1","title":"Thin Floor Milling Using Moving Support","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Association of Emergency Physicians","funders":"","keywords":"Rigidity (electromagnetism); Machining; Surface (topology); Materials science; Milling cutter; Mechanical engineering; Computer science; Structural engineering; Engineering; Composite material; Geometry; Mathematics","score_opus":0.06792497347245491,"score_gpt":0.38431278275881137,"score_spread":0.31638780928635646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200386066","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55264556,0.0003943999,0.44091985,0.00005460288,0.00006596963,0.000060604027,0.000067010995,0.00065562717,0.005136349],"genre_scores_gemma":[0.851953,0.00008565263,0.14629595,0.000016621821,0.00000783732,0.000017983206,0.000047452788,0.000028578625,0.0015469929],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983406,0.00001138301,0.000008070716,0.00003473339,0.00008994442,0.00002168562],"domain_scores_gemma":[0.999764,0.000048754253,0.000058265898,0.00005912659,0.000044231427,0.000025561301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014837498,0.00037917992,0.0003755381,0.0002796681,0.00018437994,0.00035006244,0.00038518442,0.00033171478,0.0012558834],"category_scores_gemma":[0.00025484382,0.0002344973,0.00024498237,0.0002235229,0.00033246257,0.0002527512,0.00040896138,0.0004237866,0.00024688966],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022225895,0.000046933703,0.00085870235,0.00022941876,0.000022588985,0.00029813978,0.00006984857,0.02583841,0.8987641,0.0017499793,0.00036073592,0.071538866],"study_design_scores_gemma":[0.00009237665,0.0012488771,0.006347822,0.000036978523,0.000045945264,0.00072253414,0.000096294076,0.355597,0.6277747,0.0017014461,0.006273826,0.000062263025],"about_ca_topic_score_codex":0.00041211298,"about_ca_topic_score_gemma":0.00072727725,"teacher_disagreement_score":0.0012558834,"about_ca_system_score_codex":0.00013279074,"about_ca_system_score_gemma":0.0002840033,"threshold_uncertainty_score":0.004201293},"labels":[],"label_agreement":null},{"id":"W3203012563","doi":"10.1007/s11665-021-06302-1","title":"The Influence of Polymeric Ester-Type Additives on the Performance of Metal Cutting Fluids for Machining of Titanium Alloy","year":2021,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Materials science; Polyester; Polymer; Drilling; Machining; Alloy; Titanium alloy; Composite material; Drilling fluid; Chemical engineering; Metallurgy","score_opus":0.006286892954170287,"score_gpt":0.2077774062302017,"score_spread":0.2014905132760314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203012563","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99761033,0.0011678893,0.00048076647,0.000019849564,0.000024722434,0.0000054460675,0.000028654551,0.00001620485,0.0006461308],"genre_scores_gemma":[0.9980342,0.00059409346,0.0006548186,0.000012041016,0.000013590079,0.0000035490134,0.000036873877,0.000014193467,0.00063664146],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971527,0.00006567443,0.000033761902,0.00003739683,0.00008692312,0.00006100398],"domain_scores_gemma":[0.9993741,0.00025165168,0.00014737315,0.00002775987,0.00015532326,0.000043838525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036863377,0.00046136038,0.00029442218,0.00030256555,0.0002611114,0.00062791957,0.00027130847,0.0003574048,0.00089305325],"category_scores_gemma":[0.0010508072,0.00016978901,0.00024037251,0.0002563073,0.0002531064,0.0005367614,0.00023587255,0.0003796293,0.00026286638],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015241415,0.0001340095,0.0005416367,0.0002013823,0.00002246645,0.00008606269,0.00009190097,0.0008699861,0.98671,0.00009442055,0.0000629426,0.0096609825],"study_design_scores_gemma":[0.000005436412,0.0004252835,0.00054283685,0.000004885583,0.000018921633,0.0000187763,0.000022100987,0.0008833404,0.9977266,0.0000058740493,0.00033909935,0.0000067563806],"about_ca_topic_score_codex":0.0006586249,"about_ca_topic_score_gemma":0.0011600356,"teacher_disagreement_score":0.00089305325,"about_ca_system_score_codex":0.0001901526,"about_ca_system_score_gemma":0.00030413913,"threshold_uncertainty_score":0.0029875636},"labels":[],"label_agreement":null},{"id":"W3203444565","doi":"10.3390/ma14195697","title":"Experimental Investigation on Dry Routing of CFRP Composite: Temperature, Forces, Tool Wear, and Fine Dust Emission","year":2021,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Materials science; Tool wear; Machining; Composite material; Design of experiments; Composite number; Drilling; Particle (ecology); Mechanical engineering; Metallurgy; Engineering","score_opus":0.010264458594171577,"score_gpt":0.22916880425603567,"score_spread":0.2189043456618641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203444565","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99642307,0.00012366528,0.0031152533,0.0000060705597,0.0000066568755,0.000022336868,0.000062625644,0.000024550414,0.00021567362],"genre_scores_gemma":[0.99463356,0.00011654054,0.0046933466,0.000009721659,0.000004335638,0.000025174904,0.00007432124,0.000016720724,0.0004262138],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995548,0.000042014344,0.000027761977,0.00011563013,0.00020322847,0.000056426004],"domain_scores_gemma":[0.9990256,0.0004461848,0.00021321098,0.00013308066,0.00015085423,0.000031098007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005846817,0.00047812104,0.000579057,0.0002865392,0.00036269517,0.00030914755,0.0003438234,0.0005000958,0.0009136617],"category_scores_gemma":[0.0009767091,0.00021793744,0.00031184006,0.00030993487,0.00044024922,0.00027393314,0.00022776822,0.0005005792,0.00013265178],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004457343,0.00012864674,0.001454034,0.00014681132,0.000010257791,0.00009643174,0.00017523758,0.0017220132,0.9914352,0.000041249616,0.000034282362,0.004310178],"study_design_scores_gemma":[0.000027855056,0.003108621,0.016067958,0.000010263264,0.00003240257,0.00017355818,0.00012547126,0.005450288,0.9743368,0.000050565322,0.0005949168,0.000021282796],"about_ca_topic_score_codex":0.00042439986,"about_ca_topic_score_gemma":0.0008377335,"teacher_disagreement_score":0.0009136617,"about_ca_system_score_codex":0.00023275272,"about_ca_system_score_gemma":0.00014607831,"threshold_uncertainty_score":0.0030921102},"labels":[],"label_agreement":null},{"id":"W3204514969","doi":"10.1016/j.ijmachtools.2021.103805","title":"Rapid stability analysis of serrated end mills using graphical-frequency domain methods","year":2021,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of British Columbia; Ministry of Education, India; Shastri Indo-Canadian Institute","keywords":"Discretization; Stability (learning theory); Nyquist stability criterion; Frequency domain; Machining; Control theory (sociology); Computer science; Algorithm; Mathematics; Mathematical optimization; Engineering; Mathematical analysis; Mechanical engineering; Artificial intelligence","score_opus":0.020557562259138892,"score_gpt":0.31053928647131124,"score_spread":0.28998172421217233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204514969","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037856042,0.00007263582,0.9599495,0.000031215317,0.00001727692,0.000027613574,0.000027197213,0.0004081592,0.0016102579],"genre_scores_gemma":[0.77002794,0.0001464265,0.22490422,0.000028201317,0.00002080367,0.000087850574,0.00010611709,0.00019488067,0.0044835745],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998022,0.00007366055,0.000007057449,0.000022196886,0.00008015581,0.000014782789],"domain_scores_gemma":[0.9991948,0.000522185,0.000068895424,0.000054785087,0.00014034039,0.000019080258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043351186,0.00054067804,0.00039198963,0.0004788182,0.00020782383,0.00050276157,0.00060491485,0.00045012613,0.0035950744],"category_scores_gemma":[0.0012692013,0.0002504698,0.000443393,0.00017203776,0.00034404735,0.0005003359,0.00050945,0.00057431794,0.00051617535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036938963,0.00011951954,0.0009085014,0.0003199546,0.00006894578,0.00020029026,0.00018768628,0.7535618,0.09853851,0.017427254,0.0010355285,0.1272626],"study_design_scores_gemma":[0.000008870294,0.000030353282,0.00015487165,0.000004633236,0.0000027046055,0.000013596271,0.0000094348525,0.99421114,0.003873018,0.0014028888,0.00028337617,0.0000051132583],"about_ca_topic_score_codex":0.00057624036,"about_ca_topic_score_gemma":0.0007531755,"teacher_disagreement_score":0.0035950744,"about_ca_system_score_codex":0.00016612858,"about_ca_system_score_gemma":0.0002779125,"threshold_uncertainty_score":0.012026727},"labels":[],"label_agreement":null},{"id":"W3206240704","doi":"10.3390/ma14206106","title":"Analysis and Optimization of Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools","year":2021,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machinability; Materials science; Machining; Tool wear; Surface roughness; Hardened steel; Mechanical engineering; Response surface methodology; Surface finish; Metallurgy; Composite material; Computer science; Engineering","score_opus":0.00647987111342465,"score_gpt":0.2007775039328173,"score_spread":0.19429763281939263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206240704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94280964,0.0003991705,0.053786065,0.00003733536,0.00001127319,0.00010507112,0.00007249033,0.00016019828,0.0026188653],"genre_scores_gemma":[0.9822916,0.00019823237,0.016486755,0.0000067175843,0.000001395014,0.00004565509,0.00007297689,0.000018630226,0.000878096],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997632,0.00002802588,0.000015478718,0.00003586914,0.00012006678,0.000037445872],"domain_scores_gemma":[0.9997708,0.00008943358,0.000060165938,0.000013840435,0.00005621533,0.00000944102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039675328,0.00057328487,0.0005689001,0.0005948398,0.00021512104,0.00061634684,0.00042635782,0.0005439247,0.00055488857],"category_scores_gemma":[0.00047009837,0.00037068684,0.0006937694,0.0004059987,0.00024470224,0.00019559635,0.00018076661,0.0002238123,0.00009348995],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007778373,0.0000936296,0.0019186783,0.00030242227,0.000044317676,0.00015671948,0.00005263828,0.9015838,0.07926905,0.0002455552,0.00006155752,0.01619386],"study_design_scores_gemma":[0.000018724142,0.00042899037,0.0036239568,0.000007408448,0.00004214977,0.000031915053,0.00005235723,0.9755368,0.019611582,0.0001215143,0.0005126336,0.000012022025],"about_ca_topic_score_codex":0.0060754283,"about_ca_topic_score_gemma":0.006880818,"teacher_disagreement_score":0.0060754283,"about_ca_system_score_codex":0.00057206495,"about_ca_system_score_gemma":0.00086385274,"threshold_uncertainty_score":0.012080133},"labels":[],"label_agreement":null},{"id":"W3207972588","doi":"10.1016/j.precisioneng.2021.10.010","title":"Predicting the position-dependent dynamics of machine tools using progressive network","year":2021,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Pratt and Whitney Canada","keywords":"Position (finance); Computer science; Dependency (UML); Artificial intelligence; Domain (mathematical analysis); Artificial neural network; Machine learning; Machine tool; Kinematics; Control reconfiguration; Bridge (graph theory); Domain knowledge; Engineering","score_opus":0.008361186451750935,"score_gpt":0.2294180790452199,"score_spread":0.22105689259346897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207972588","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7447914,0.00017610547,0.252083,0.000099200195,0.000023929737,0.000034626362,0.00013402854,0.00034008338,0.0023175965],"genre_scores_gemma":[0.98887455,0.00005770138,0.010358997,0.000004170457,0.0000033377373,0.000009579852,0.00005582469,0.000012923104,0.0006228874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999422,0.00000871732,0.0000022993147,0.000016629405,0.000022163691,0.000008047332],"domain_scores_gemma":[0.9996797,0.00021015189,0.000038293478,0.000018581326,0.000038157796,0.000015234622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017881334,0.00044265456,0.00024786114,0.00034257353,0.00018581054,0.00030214005,0.00045769097,0.0004899573,0.0008210415],"category_scores_gemma":[0.0010643257,0.00030167002,0.00018461567,0.00035244602,0.00030089048,0.0006961663,0.0002379282,0.00039490525,0.00013203733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032174637,0.000019800736,0.0015586417,0.000011782608,0.000006827776,0.00002250223,0.0000107796195,0.9892084,0.0024397317,0.000380069,0.000054757893,0.006254487],"study_design_scores_gemma":[7.3624244e-7,0.0000031302854,0.0002123496,2.7274532e-7,4.7118797e-7,0.0000013329925,7.584942e-7,0.9994925,0.00018044266,0.000095826246,0.000011488862,6.0930626e-7],"about_ca_topic_score_codex":0.007840273,"about_ca_topic_score_gemma":0.008836661,"teacher_disagreement_score":0.007840273,"about_ca_system_score_codex":0.0004374912,"about_ca_system_score_gemma":0.00037337485,"threshold_uncertainty_score":0.015589297},"labels":[],"label_agreement":null},{"id":"W3209119107","doi":"10.3390/ma14216496","title":"CNC Edge Finishing of Granite: Effect of Machining Conditions on Part Quality, Cutting Forces, and Particle Emissions","year":2021,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Machining; Particle (ecology); Quality (philosophy); Mechanical engineering; Materials science; Metallurgy; Engineering; Geology; Physics","score_opus":0.014225384096152396,"score_gpt":0.2925234515554536,"score_spread":0.27829806745930125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209119107","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992119,0.00013009392,0.00033070467,0.0000035345756,0.0000030210952,0.000008091388,0.000048694812,0.000010888101,0.00025306482],"genre_scores_gemma":[0.9969607,0.00013981684,0.0018927108,0.0000123498285,0.000001456638,0.000011329944,0.00016981138,0.000020671858,0.0007911907],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996898,0.000031410615,0.000021094565,0.00009095839,0.0001131868,0.000053535103],"domain_scores_gemma":[0.99951124,0.0001532821,0.00012773047,0.00004394639,0.00012486383,0.00003898283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028775664,0.00040560725,0.00043328918,0.0003014179,0.00027449836,0.0004843576,0.00030931734,0.0003775641,0.0009378497],"category_scores_gemma":[0.0006576057,0.00019687299,0.00036971757,0.0003093085,0.00024387703,0.00023355812,0.00022130283,0.0004426086,0.00019489617],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015447363,0.00010773564,0.0043273326,0.00012923752,0.000026938817,0.00013358804,0.00010319173,0.0010461084,0.98669016,0.000018744318,0.00003322546,0.005838947],"study_design_scores_gemma":[0.000033437023,0.0030757745,0.099408425,0.00001592427,0.000072737676,0.00023254291,0.0002495747,0.0033732003,0.8919355,0.00003381294,0.0015350599,0.000034049615],"about_ca_topic_score_codex":0.0038297519,"about_ca_topic_score_gemma":0.0068756095,"teacher_disagreement_score":0.0038297519,"about_ca_system_score_codex":0.00027668287,"about_ca_system_score_gemma":0.00016905784,"threshold_uncertainty_score":0.0076149106},"labels":[],"label_agreement":null},{"id":"W3209440801","doi":"10.3390/app10207298","title":"A Qualitative Tool Condition Monitoring Framework Using Convolution Neural Network and Transfer Learning","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Economic Development and Trade, Government of Alberta; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Quality (philosophy); Artificial neural network; Machine tool; Artificial intelligence; Machine learning; Machining; Engineering; Mechanical engineering","score_opus":0.042702148787332694,"score_gpt":0.3222526933079284,"score_spread":0.2795505445205957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209440801","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012964777,0.000256325,0.9833119,0.00023221168,0.000026644748,0.00004791739,0.000078033474,0.0006287955,0.0024534126],"genre_scores_gemma":[0.8621834,0.0003601471,0.13222057,0.00014898171,0.000055180244,0.00018976435,0.00020808252,0.00009361776,0.004540199],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995097,0.0001075968,0.000021155025,0.00016582907,0.00012223562,0.000073367024],"domain_scores_gemma":[0.9993586,0.00022115774,0.00012677922,0.000057374422,0.00018722127,0.000048865626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001021839,0.0008932894,0.0007606699,0.0010506045,0.00037594268,0.0011835238,0.0023652383,0.001450575,0.002681738],"category_scores_gemma":[0.0022488623,0.00049608725,0.00090430584,0.000740089,0.001139788,0.00216391,0.001386831,0.0012722645,0.0003699862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008168426,0.00007343227,0.0015117665,0.00009739864,0.00004995335,0.00015316266,0.00010226914,0.91311556,0.0039155814,0.018118393,0.0006123994,0.062168397],"study_design_scores_gemma":[0.0000012420219,0.000008906054,0.000092961156,0.0000028289821,0.0000035333624,0.000006427454,0.0000043728596,0.99664897,0.00032707135,0.0027804538,0.00011902177,0.000004132093],"about_ca_topic_score_codex":0.017461864,"about_ca_topic_score_gemma":0.00795858,"teacher_disagreement_score":0.017461864,"about_ca_system_score_codex":0.0021344929,"about_ca_system_score_gemma":0.0016736877,"threshold_uncertainty_score":0.03472048},"labels":[],"label_agreement":null},{"id":"W3210279744","doi":"10.32920/ryerson.14663340.v1","title":"Experimental implementation of artificial neural network-based active vibration control &amp; chatter suppression","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Vibration; Artificial neural network; Active vibration control; Control theory (sociology); Vibration control; Engineering; Computer science; Control system; Cantilever; Control engineering; Control (management); Artificial intelligence; Structural engineering; Acoustics","score_opus":0.015581522123927972,"score_gpt":0.29615407215190864,"score_spread":0.28057255002798065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210279744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7451515,0.00034868848,0.23849492,0.000225238,0.00040663267,0.00033116652,0.00032796667,0.0018078604,0.012905962],"genre_scores_gemma":[0.97842056,0.000058993777,0.018970396,0.00001873743,0.0000075512025,0.00013262946,0.00007012469,0.00002434227,0.0022966934],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99965715,0.00003962196,0.000028413024,0.00006819669,0.00015947453,0.00004724432],"domain_scores_gemma":[0.9994394,0.00012764834,0.00006679972,0.000093271585,0.00023851034,0.000034261004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045839284,0.00038801227,0.0002517615,0.00039532376,0.00024813876,0.00026486086,0.0007057338,0.00046966434,0.003770567],"category_scores_gemma":[0.00078446936,0.00015104885,0.00016848816,0.00024272759,0.00040245245,0.0002785717,0.00031876354,0.000407576,0.0003366463],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007550673,0.00063043303,0.0012957826,0.0006938236,0.000041994994,0.0002145898,0.00028876046,0.037059765,0.849497,0.0015754717,0.0009845108,0.10696276],"study_design_scores_gemma":[0.00011290845,0.0026278866,0.007150616,0.000039143037,0.00003654731,0.00013119224,0.00009614051,0.30022395,0.6853093,0.0004972198,0.003735445,0.000039653307],"about_ca_topic_score_codex":0.0009138602,"about_ca_topic_score_gemma":0.0010504643,"teacher_disagreement_score":0.003770567,"about_ca_system_score_codex":0.00020298018,"about_ca_system_score_gemma":0.00021070258,"threshold_uncertainty_score":0.012613773},"labels":[],"label_agreement":null},{"id":"W3211704489","doi":"10.1115/imece2000-1900","title":"Numerical Analysis of Cutting With Chamfered and Worn Edge Tools","year":2000,"lang":"en","type":"article","venue":"Manufacturing engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Chamfer (geometry); Enhanced Data Rates for GSM Evolution; Finite element method; Materials science; Chip formation; Thrust; Machining; Cutting tool; Chip; Rake; Structural engineering; Tool wear; Mechanical engineering; Computer science; Geometry; Engineering; Mathematics; Metallurgy","score_opus":0.004790884749977564,"score_gpt":0.181661767878415,"score_spread":0.17687088312843743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211704489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97294676,0.0001344528,0.024095982,0.000050715902,0.000021427739,0.000024766414,0.000045800793,0.00010494368,0.002575129],"genre_scores_gemma":[0.9907611,0.00003803315,0.00868256,0.000006739281,0.000001616385,0.0000103993225,0.000026935359,0.0000082072875,0.0004643324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999824,0.000030720985,0.000008143962,0.000017506143,0.00008215703,0.00003757863],"domain_scores_gemma":[0.99927944,0.0004288205,0.00009153991,0.00007044714,0.00009611954,0.0000337338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045837206,0.0002420987,0.00035344332,0.00035626808,0.00034708597,0.00054125476,0.00046855377,0.0008362417,0.0011398521],"category_scores_gemma":[0.0011638929,0.0002185909,0.00040663412,0.0002740413,0.00061832496,0.00030558105,0.00021789089,0.00027069123,0.00010273704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018947995,0.00006565937,0.0027969095,0.000106118765,0.00002315526,0.00021374706,0.00010241339,0.94825286,0.038748875,0.001895856,0.00012040048,0.0074845003],"study_design_scores_gemma":[0.000016540525,0.00011421554,0.0012550167,0.000005380785,0.0000068238323,0.00004089332,0.000031382417,0.9903026,0.007706271,0.0002656601,0.00024700828,0.00000821105],"about_ca_topic_score_codex":0.0020105229,"about_ca_topic_score_gemma":0.0018251011,"teacher_disagreement_score":0.0020105229,"about_ca_system_score_codex":0.00043439897,"about_ca_system_score_gemma":0.0003839735,"threshold_uncertainty_score":0.003997624},"labels":[],"label_agreement":null},{"id":"W3212002185","doi":"10.1115/imece2000-1895","title":"Prediction of Tool and Chip Temperature in Continuous Metal Cutting and Milling","year":2000,"lang":"en","type":"article","venue":"Manufacturing engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Chip; Rake; Chip formation; Transient (computer programming); Finite element method; Mechanical engineering; Materials science; Heat transfer; Machine tool; Heat flux; Mechanics; Computer science; Tool wear; Engineering; Structural engineering; Physics","score_opus":0.0036718530379641554,"score_gpt":0.16406690962741133,"score_spread":0.16039505658944717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212002185","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65956956,0.00015954147,0.33795658,0.00005872635,0.000028315022,0.000036100188,0.00007138205,0.0004593228,0.0016604115],"genre_scores_gemma":[0.9876766,0.000020046964,0.011824987,0.0000036524186,0.0000015966966,0.000014128064,0.000021555798,0.000008621714,0.00042874934],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999112,0.000013081525,0.0000028344741,0.00002149563,0.000037104193,0.000014334877],"domain_scores_gemma":[0.9996309,0.00024590734,0.000023894778,0.000024087514,0.00005219089,0.000022885562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029671966,0.00029316315,0.00032086216,0.00021060958,0.00018389623,0.0004201192,0.00047615083,0.0006317875,0.0005057103],"category_scores_gemma":[0.00074928394,0.00027786614,0.0002815408,0.00015015935,0.00044543343,0.000288155,0.00018491005,0.0003854695,0.00009704393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009348208,0.000049119546,0.0016831277,0.000030478612,0.000008656433,0.00003913822,0.0000316236,0.97091866,0.013288366,0.00054450607,0.00009931283,0.013213548],"study_design_scores_gemma":[0.000002917665,0.000016037382,0.00022235069,8.9639076e-7,9.4436155e-7,0.0000024423427,0.0000018299856,0.99807286,0.0015775712,0.000063897176,0.000036723133,0.0000015663],"about_ca_topic_score_codex":0.00512599,"about_ca_topic_score_gemma":0.003072818,"teacher_disagreement_score":0.00512599,"about_ca_system_score_codex":0.0005838719,"about_ca_system_score_gemma":0.0005416431,"threshold_uncertainty_score":0.010192335},"labels":[],"label_agreement":null},{"id":"W3213631548","doi":"10.1016/j.ifacol.2021.08.089","title":"Machine-Learning Digital Twin of Overlay Metal Deposition for Distortion Control of Panel Structures","year":2021,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Surrey Memorial Hospital","funders":"","keywords":"Computer science; Fidelity; Distortion (music); Overlay; Artificial intelligence; Distributed computing; Telecommunications; Bandwidth (computing)","score_opus":0.008235650515761984,"score_gpt":0.2191668404817429,"score_spread":0.21093118996598093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3213631548","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22289695,0.00015858747,0.77100986,0.00017067988,0.000038635637,0.000036873866,0.000035123703,0.0005171649,0.005136162],"genre_scores_gemma":[0.94054997,0.00003341932,0.05823803,0.000025976608,0.0000051191864,0.000014374706,0.00002741142,0.000023264525,0.0010824036],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999162,0.000016672833,0.0000040162677,0.000021976846,0.00003214245,0.00000892464],"domain_scores_gemma":[0.9997552,0.00011218615,0.000028862112,0.000043226708,0.000039584145,0.00002091617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027744603,0.00025188204,0.00024980775,0.00018252335,0.00015901087,0.00038407525,0.00047210412,0.00032371195,0.0011207542],"category_scores_gemma":[0.0009279339,0.00014761252,0.00019309235,0.00013658016,0.00039291897,0.00049796834,0.0005285663,0.0003525285,0.00009941374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011052698,0.00007358262,0.0013030795,0.000051985517,0.000021463444,0.00005814628,0.000050163053,0.9043743,0.027685015,0.0038357829,0.0004061526,0.062029745],"study_design_scores_gemma":[0.000001539873,0.000013493774,0.00008437591,5.187775e-7,8.6728863e-7,0.0000048291067,0.000002144911,0.9971426,0.0022825787,0.000368157,0.000097557015,0.0000013452009],"about_ca_topic_score_codex":0.0010984506,"about_ca_topic_score_gemma":0.0018314238,"teacher_disagreement_score":0.0011207542,"about_ca_system_score_codex":0.00033806835,"about_ca_system_score_gemma":0.00033727146,"threshold_uncertainty_score":0.0037492514},"labels":[],"label_agreement":null},{"id":"W3213739883","doi":"10.1115/imece2001/med-23304","title":"An Improved Time Domain Simulation for Dynamic Milling at Small Radial Immersions and Large Depths of Cut","year":2001,"lang":"en","type":"article","venue":"Manufacturing engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Kinematics; Discretization; Vibration; Time domain; Immersion (mathematics); Deflection (physics); Mechanics; Stability (learning theory); Control theory (sociology); Materials science; Dynamic simulation; Computer science; Simulation; Acoustics; Physics; Geometry; Mathematics; Optics; Classical mechanics; Mathematical analysis","score_opus":0.004447759014067172,"score_gpt":0.21332217946722176,"score_spread":0.2088744204531546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3213739883","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49419963,0.00012425952,0.49202567,0.0002065615,0.00005614249,0.00010390523,0.000340173,0.0009256381,0.012018037],"genre_scores_gemma":[0.96075296,0.000064557215,0.03641062,0.000022934419,0.0000057199454,0.00008744584,0.00015117675,0.00006645224,0.0024381399],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990344,0.000020122223,0.0000040152127,0.0000109984685,0.000047272508,0.000014103725],"domain_scores_gemma":[0.9997223,0.00015222556,0.000020709893,0.00002770415,0.000059917547,0.00001705625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002574906,0.00031848502,0.00050294684,0.00020139129,0.00026442736,0.00044485764,0.00058444985,0.0007447387,0.002390257],"category_scores_gemma":[0.0006489819,0.00022535122,0.00042689705,0.00015060417,0.00031981006,0.00035431475,0.0002420756,0.00044640366,0.00021869659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003628044,0.00001847726,0.00021068424,0.0000139116455,0.0000041977273,0.000028374534,0.000024743209,0.9916248,0.0055870404,0.0008131887,0.00007312019,0.0015652932],"study_design_scores_gemma":[0.0000064949645,0.00000847701,0.000036178222,8.394162e-7,0.000001011809,0.000002710992,0.0000021244573,0.99898344,0.0007909458,0.000053263204,0.00011281413,0.000001657024],"about_ca_topic_score_codex":0.0062635597,"about_ca_topic_score_gemma":0.0032532504,"teacher_disagreement_score":0.0062635597,"about_ca_system_score_codex":0.00043404277,"about_ca_system_score_gemma":0.00062339485,"threshold_uncertainty_score":0.012454212},"labels":[],"label_agreement":null},{"id":"W3214150967","doi":"10.1115/imece2001/med-23312","title":"A Model for the Tool Temperature During Machining With a Rotary Tool","year":2001,"lang":"en","type":"article","venue":"Manufacturing engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Rotational speed; Rake; Machining; Discretization; Mechanical engineering; Chip; Rake angle; Heat transfer; Machine tool; Materials science; Computer science; Rotational energy; Mechanics; Engineering; Physics; Mathematics; Mathematical analysis","score_opus":0.005676403622920564,"score_gpt":0.18431257185489403,"score_spread":0.17863616823197345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214150967","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14972016,0.000613636,0.83567876,0.00035187879,0.000105526684,0.000129885,0.00038138952,0.00060943805,0.01240942],"genre_scores_gemma":[0.9689714,0.00036802999,0.019967735,0.000049176586,0.000021811218,0.0002015194,0.00019594262,0.000119606564,0.010104729],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998273,0.000031687905,0.0000059758195,0.000045513803,0.000059778806,0.000029732031],"domain_scores_gemma":[0.99977845,0.00011460186,0.000028591016,0.000029272884,0.000035951703,0.000013122944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003397067,0.00053494493,0.0007023203,0.0002767272,0.00048063594,0.0008269315,0.0011334848,0.0014581626,0.002060642],"category_scores_gemma":[0.00085151696,0.00050870125,0.00086791685,0.00027821976,0.000883343,0.0009283477,0.00031566917,0.00073902664,0.0005701456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032616,0.00001709914,0.0003146641,0.000032051656,0.0000072034945,0.00005283921,0.000046932386,0.9847482,0.009267276,0.0029580162,0.00015942371,0.002363694],"study_design_scores_gemma":[0.000008579328,0.000014513316,0.00015702288,0.0000029832847,0.0000032919822,0.000015787222,0.000004916748,0.9979336,0.0010758103,0.00038868075,0.00038919278,0.00000556894],"about_ca_topic_score_codex":0.007945399,"about_ca_topic_score_gemma":0.0032493116,"teacher_disagreement_score":0.007945399,"about_ca_system_score_codex":0.00083438394,"about_ca_system_score_gemma":0.00096194854,"threshold_uncertainty_score":0.01579827},"labels":[],"label_agreement":null},{"id":"W3214434665","doi":"10.1115/imece2000-2368","title":"Improving the Performance of Process Controllers Using a New Clustered Neural Network","year":2000,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Artificial neural network; Controller (irrigation); Multilayer perceptron; Machining; Feed forward; Scheme (mathematics); Process (computing); Line (geometry); Perceptron; Artificial intelligence; Control engineering; Control theory (sociology); Engineering; Control (management)","score_opus":0.007899307836041694,"score_gpt":0.21669918486031575,"score_spread":0.20879987702427405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214434665","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22841635,0.0003800971,0.765376,0.00015268974,0.00010253607,0.000092754024,0.00004459963,0.0012583889,0.0041765734],"genre_scores_gemma":[0.9380629,0.000067823516,0.060329515,0.000045383385,0.000020631673,0.000047082962,0.000041003597,0.000022826294,0.0013627799],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976987,0.000033394772,0.00001236506,0.000070311595,0.00008459629,0.000029372242],"domain_scores_gemma":[0.9995819,0.0001242278,0.00004506323,0.000055204775,0.00017254577,0.000021097276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004871543,0.00045736454,0.00030613245,0.00023090046,0.00018249497,0.00045361987,0.0009520729,0.0005370411,0.001199196],"category_scores_gemma":[0.001288437,0.00020246312,0.00020810918,0.00018873859,0.00027040826,0.00045912951,0.00040219468,0.00046188929,0.00022580073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024912978,0.00017124205,0.0010105261,0.00011183429,0.00009549724,0.0000712928,0.000060970655,0.7569196,0.069589145,0.0015009097,0.0008392005,0.1693806],"study_design_scores_gemma":[0.000009934441,0.00007838935,0.00023546215,0.000002607467,0.00000786313,0.000010362015,0.0000023262485,0.99262756,0.006646572,0.00014645855,0.00022861703,0.0000038214757],"about_ca_topic_score_codex":0.0032504392,"about_ca_topic_score_gemma":0.0034197469,"teacher_disagreement_score":0.0032504392,"about_ca_system_score_codex":0.00050141534,"about_ca_system_score_gemma":0.0004230939,"threshold_uncertainty_score":0.006463051},"labels":[],"label_agreement":null},{"id":"W3214572536","doi":"10.1115/imece2000-1909","title":"Generic Simulation Approach for Multi-Axis Machining: Part II—Model Calibration and Feed Rate Scheduling","year":2000,"lang":"en","type":"article","venue":"Manufacturing engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Computer science; Deflection (physics); Scheduling (production processes); Mechanical engineering; Calibration; Machine tool; Airfoil; Engineering; Structural engineering; Mathematical optimization; Mathematics; Physics","score_opus":0.023493803132275656,"score_gpt":0.23277432127485045,"score_spread":0.2092805181425748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214572536","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025474122,0.00011043151,0.9651899,0.000105638406,0.000033268727,0.00013828433,0.00017045719,0.0012782656,0.0074998024],"genre_scores_gemma":[0.68473184,0.0004492287,0.3079038,0.00010344643,0.000031947282,0.00069127424,0.00048540373,0.0005304348,0.0050726626],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972266,0.00008011154,0.000015844631,0.000039285605,0.000108154134,0.00003389374],"domain_scores_gemma":[0.999648,0.00012758673,0.00004841233,0.00008733513,0.000074144824,0.0000146017355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005750292,0.00065231306,0.0006540496,0.000431255,0.0003481086,0.00071462843,0.0014472522,0.0012112089,0.004442287],"category_scores_gemma":[0.0010280913,0.0004164266,0.0008236317,0.00042559177,0.000367585,0.0007553919,0.00058371585,0.00085950765,0.00061360816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022908413,0.000024387085,0.00018048253,0.000027005837,0.000008288953,0.000025542415,0.000022798089,0.9877743,0.0026319588,0.004197111,0.00016960506,0.0049155713],"study_design_scores_gemma":[0.000005188657,0.000009149222,0.00003869979,0.0000027937153,0.0000018632036,0.0000072746657,0.0000027084232,0.9973098,0.0012134317,0.00054948527,0.0008568142,0.000002806009],"about_ca_topic_score_codex":0.003748496,"about_ca_topic_score_gemma":0.0021002626,"teacher_disagreement_score":0.004442287,"about_ca_system_score_codex":0.0008584085,"about_ca_system_score_gemma":0.0010041556,"threshold_uncertainty_score":0.014860868},"labels":[],"label_agreement":null},{"id":"W3214588501","doi":"10.1177/00219983211055825","title":"Experimental and numerical investigations of the damages induced while drilling flax/epoxy composite","year":2021,"lang":"en","type":"article","venue":"Journal of Composite Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Université du Québec à Trois-Rivières","funders":"","keywords":"Delamination (geology); Materials science; Drilling; Composite number; Composite material; Epoxy; Machining; Thrust; Composite laminates; Drill; Stacking; Structural engineering; Mechanical engineering; Geology; Engineering","score_opus":0.01485244497463981,"score_gpt":0.24761500170504308,"score_spread":0.23276255673040327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214588501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918405,0.00010629614,0.006897838,0.000018233299,0.000016098289,0.000028835748,0.00012019743,0.00007448133,0.0008975527],"genre_scores_gemma":[0.99227035,0.000071232505,0.0072089434,0.0000038374087,0.0000023819193,0.00002331657,0.0000384675,0.0000064380188,0.00037512401],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996444,0.000024933755,0.000024710482,0.000053290463,0.00019245855,0.00006023968],"domain_scores_gemma":[0.99869627,0.0005778373,0.00025259962,0.00019743468,0.00021567845,0.0000601768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000600849,0.000442839,0.00053598895,0.00041330408,0.00035475055,0.00021091363,0.00044957447,0.00078866375,0.0016059277],"category_scores_gemma":[0.0009015683,0.00023844394,0.00024953426,0.00039437442,0.00066933007,0.00029265656,0.00029772788,0.00042279696,0.00010372427],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050310866,0.0003202041,0.0028587368,0.00043337102,0.000015249873,0.0004723961,0.00033749567,0.08689349,0.89898586,0.0004770697,0.00016524694,0.008537668],"study_design_scores_gemma":[0.000056188106,0.0029175193,0.019956673,0.000032832046,0.00004583404,0.00045497727,0.00029984,0.23393889,0.7407318,0.00033426372,0.0011541967,0.00007709445],"about_ca_topic_score_codex":0.0005512848,"about_ca_topic_score_gemma":0.0010226965,"teacher_disagreement_score":0.0016059277,"about_ca_system_score_codex":0.00021763655,"about_ca_system_score_gemma":0.00019952508,"threshold_uncertainty_score":0.0053723454},"labels":[],"label_agreement":null},{"id":"W3214683459","doi":"10.1115/imece2000-1906","title":"A Mechanistic Force Model of the 5-Axis Milling Process","year":2000,"lang":"en","type":"article","venue":"Manufacturing engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University Medical Centre","funders":"","keywords":"Cartesian coordinate system; Robustness (evolution); Tungsten carbide; Calibration; Computer science; Enhanced Data Rates for GSM Evolution; Scalability; Intersection (aeronautics); Mechanical engineering; Process (computing); Milling cutter; Discretization; Materials science; Engineering; Geometry; Machining; Mathematics; Mathematical analysis; Artificial intelligence; Composite material","score_opus":0.004959884629013862,"score_gpt":0.1806510597900339,"score_spread":0.17569117516102004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214683459","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08741008,0.00035919837,0.8798642,0.00033338068,0.000053258256,0.000161451,0.00050366856,0.00054835,0.030766455],"genre_scores_gemma":[0.9199952,0.00055052916,0.058901418,0.000072291994,0.000020817472,0.00036681755,0.0004071648,0.00006513863,0.01962058],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983644,0.00002077699,0.0000094987745,0.000039566978,0.00007654461,0.000017177763],"domain_scores_gemma":[0.999863,0.00005004969,0.000028602462,0.000014365621,0.00003657822,0.000007339285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036476547,0.0004501465,0.00036803557,0.00044336298,0.00031168255,0.0007471015,0.0015109594,0.0011687959,0.0047802282],"category_scores_gemma":[0.00046889693,0.00038617456,0.00053029845,0.00032001105,0.0004167328,0.00082617224,0.00034448731,0.0004324913,0.0007414278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013413771,0.000021297337,0.0002151355,0.000030825748,0.000006094718,0.000050704697,0.00002680014,0.9865671,0.002880861,0.005561972,0.00014766122,0.004478202],"study_design_scores_gemma":[0.000006177503,0.00001576622,0.00019876623,0.000003125803,0.0000025118065,0.000019552244,0.0000031090353,0.9979804,0.00036283716,0.0007482963,0.0006549397,0.000004464284],"about_ca_topic_score_codex":0.0055454187,"about_ca_topic_score_gemma":0.0030993994,"teacher_disagreement_score":0.0055454187,"about_ca_system_score_codex":0.00053464674,"about_ca_system_score_gemma":0.0007224766,"threshold_uncertainty_score":0.01599145},"labels":[],"label_agreement":null},{"id":"W3215977773","doi":"10.1007/s10556-021-00993-y","title":"Study of TiB2 Coated Hard Alloy Tool Wear Resistance During Titanium Alloy Machining","year":2021,"lang":"en","type":"article","venue":"Chemical and Petroleum Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Alloy; Metallurgy; Materials science; Machining; Titanium alloy; Wear resistance; Titanium","score_opus":0.005927529580524542,"score_gpt":0.19274461716648728,"score_spread":0.18681708758596274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215977773","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99861455,0.0003369739,0.00040936974,0.000008362874,0.000010204251,0.0000044764347,0.000068914866,0.0000217158,0.00052528665],"genre_scores_gemma":[0.9990565,0.000055930068,0.00016371769,0.0000042902516,0.0000026082118,0.000002069528,0.000057470752,0.000007244238,0.00065018487],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997596,0.000021160295,0.000011578928,0.000049687613,0.00010964053,0.000048344053],"domain_scores_gemma":[0.99922276,0.00024641366,0.00010712939,0.00008547146,0.0003034871,0.00003480753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022693624,0.00023707493,0.00037656497,0.0003815737,0.0003535085,0.00035963408,0.00040762482,0.00043729835,0.0013860664],"category_scores_gemma":[0.0007045691,0.0001589569,0.0002520228,0.0003855066,0.00024769886,0.00023411616,0.00011626395,0.00020784624,0.00020496975],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015753026,0.000056840487,0.00660227,0.0002609227,0.000048056634,0.00047173206,0.0005017416,0.002314986,0.97604376,0.00010688615,0.0002897415,0.011727707],"study_design_scores_gemma":[0.000032260272,0.002452729,0.13292624,0.0000287498,0.00009929608,0.0008077785,0.0008562445,0.02570198,0.8339892,0.00008571653,0.0029616768,0.000058162605],"about_ca_topic_score_codex":0.0018893166,"about_ca_topic_score_gemma":0.0026706872,"teacher_disagreement_score":0.0018893166,"about_ca_system_score_codex":0.00025540715,"about_ca_system_score_gemma":0.00015506042,"threshold_uncertainty_score":0.0046368837},"labels":[],"label_agreement":null},{"id":"W33579934","doi":"10.1038/s41467-021-21196-2","title":"A.I.- based modelling and optimization of turning process","year":2012,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Academy of Finland; Mitacs; Government of Canada","keywords":"Process (computing); Computer science","score_opus":0.016439442342226145,"score_gpt":0.2797461618175818,"score_spread":0.2633067194753556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W33579934","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19618735,0.0014167173,0.60053223,0.0011069978,0.00036023266,0.00043078655,0.0028708572,0.0018960467,0.19519888],"genre_scores_gemma":[0.91542435,0.0006811706,0.062775694,0.00014789385,0.000040777188,0.0005101212,0.000725063,0.00040340654,0.019291634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988484,0.000019592599,0.000006108906,0.000023348499,0.000031893498,0.00003414124],"domain_scores_gemma":[0.99980253,0.0000709656,0.000030300203,0.00002638693,0.00005465721,0.000015160659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027957346,0.00073624786,0.0006861786,0.000518982,0.00049395894,0.0012044981,0.00094525964,0.0018176525,0.0074422695],"category_scores_gemma":[0.0006698658,0.00056547264,0.0008569578,0.00051984197,0.00042538551,0.00054250576,0.0004117584,0.00065272476,0.0014888197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017154733,0.000014139063,0.00026262214,0.000032800934,0.000007374233,0.00003720432,0.000014220769,0.99293137,0.0015980381,0.0026262142,0.00033261455,0.002126207],"study_design_scores_gemma":[0.000006789768,0.0000074028244,0.00009512829,0.0000057780735,0.0000033604995,0.000007829291,0.000006655084,0.9975182,0.00047193415,0.000679742,0.0011925289,0.000004651672],"about_ca_topic_score_codex":0.012586714,"about_ca_topic_score_gemma":0.008645297,"teacher_disagreement_score":0.012586714,"about_ca_system_score_codex":0.0010065247,"about_ca_system_score_gemma":0.0013201324,"threshold_uncertainty_score":0.025026917},"labels":[],"label_agreement":null},{"id":"W407347021","doi":"10.1007/s00170-015-7323-8","title":"3D FEM simulation of helical milling hole process for titanium alloy Ti-6Al-4V","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Titanium alloy; Machining; Finite element method; End mill; Materials science; Process (computing); Mechanical engineering; Alloy; Metallurgy; Titanium; Engineering; Structural engineering; Engineering drawing; Computer science","score_opus":0.01977121243096747,"score_gpt":0.29817057173842504,"score_spread":0.2783993593074576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W407347021","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80590886,0.00082190376,0.09184114,0.00073437835,0.00031421724,0.00020687531,0.0036459567,0.0022504951,0.094276],"genre_scores_gemma":[0.98518246,0.00016521938,0.008836214,0.0000451614,0.0000118034795,0.00007204868,0.0004077416,0.00011329282,0.0051660836],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982375,0.00002100895,0.00000780809,0.000024824947,0.000081087564,0.00004147591],"domain_scores_gemma":[0.99958426,0.0002146768,0.000049959544,0.000031776002,0.00009168763,0.000027729136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022847988,0.0005373591,0.0005860905,0.00055426615,0.0007358298,0.00074081833,0.0009437451,0.0019452659,0.011773199],"category_scores_gemma":[0.0006730138,0.0006698297,0.0008920621,0.0006360593,0.00051187887,0.00044904122,0.0003288591,0.00045778436,0.00071092235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000083934196,0.00004027122,0.00085955084,0.0000861502,0.000014719037,0.00014968883,0.00007093655,0.99075013,0.0027962981,0.00090472447,0.000803521,0.0034399957],"study_design_scores_gemma":[0.000013073438,0.000032466152,0.00074520544,0.0000070107526,0.00000709966,0.000027829341,0.000038855153,0.99732035,0.00094166235,0.0001661152,0.0006905617,0.000009928063],"about_ca_topic_score_codex":0.01690789,"about_ca_topic_score_gemma":0.014069301,"teacher_disagreement_score":0.01690789,"about_ca_system_score_codex":0.0008264151,"about_ca_system_score_gemma":0.001091881,"threshold_uncertainty_score":0.03938526},"labels":[],"label_agreement":null},{"id":"W4200295208","doi":"10.3390/ma14247876","title":"Predictive Analytical Modeling of Thermo-Mechanical Effects in Orthogonal Machining","year":2021,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Rake angle; Machining; Rake; Cutting tool; Materials science; Work (physics); RADIUS; Mechanical engineering; Plasticity; Sensitivity (control systems); Empirical modelling; Computer science; Engineering; Composite material; Simulation","score_opus":0.008397977717206321,"score_gpt":0.23440650828320347,"score_spread":0.22600853056599715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200295208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52386135,0.0005655112,0.465477,0.0001260966,0.000031752465,0.000113430295,0.00012406708,0.0005373112,0.009163563],"genre_scores_gemma":[0.9903696,0.00017930947,0.008463046,0.000008737724,0.0000037591242,0.000045468427,0.000027181162,0.000022565288,0.0008802515],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997683,0.0000404982,0.0000076283063,0.000041211304,0.00010852586,0.000033825538],"domain_scores_gemma":[0.9995229,0.00028094667,0.00008548735,0.000035441815,0.00006681818,0.000008390037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045568214,0.00047768536,0.00041949295,0.0003771461,0.00022805853,0.00057400606,0.0006617769,0.0006070296,0.00072179147],"category_scores_gemma":[0.0013727354,0.00035464944,0.00046582054,0.00035732967,0.0005237767,0.00046074882,0.00032451196,0.0004757266,0.00016721466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002614546,0.000038048638,0.00068075844,0.00003544491,0.000007434689,0.00005252991,0.000042724685,0.9855703,0.0075473995,0.0011845223,0.000048828406,0.0047658607],"study_design_scores_gemma":[9.0273323e-7,0.00000762106,0.00016964454,9.2168887e-7,0.0000013972794,0.0000041234653,0.0000024949736,0.9989386,0.00069780817,0.00012712115,0.00004781267,0.0000015979011],"about_ca_topic_score_codex":0.003859024,"about_ca_topic_score_gemma":0.002508603,"teacher_disagreement_score":0.003859024,"about_ca_system_score_codex":0.0004755394,"about_ca_system_score_gemma":0.00048021894,"threshold_uncertainty_score":0.0076730847},"labels":[],"label_agreement":null},{"id":"W4200439651","doi":"10.21203/rs.3.rs-1101476/v1","title":"Turning of Inconel 718 Using Liquid Nitrogen: Multi-objective Optimization of Cutting Parameters Using RSM","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Inconel; Flank; Response surface methodology; Surface roughness; Materials science; Cutting tool; Metallurgy; Composite material; Mathematics; Alloy","score_opus":0.07623100124478369,"score_gpt":0.3785719214038011,"score_spread":0.30234092015901737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200439651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91906583,0.00064212724,0.07688843,0.000063881,0.000020653228,0.000120512006,0.00008961656,0.00020010723,0.0029088703],"genre_scores_gemma":[0.9405723,0.0002861783,0.057489637,0.000031813604,0.0000043095706,0.00016374844,0.000116654795,0.00002448169,0.0013108561],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99965394,0.00007009149,0.000023612796,0.000061406005,0.00014823955,0.000042737924],"domain_scores_gemma":[0.99969566,0.00014394174,0.00007150342,0.0000133937365,0.000064429194,0.000011110068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007719131,0.0007176597,0.00079410546,0.00056561414,0.00018587097,0.000567766,0.00054323376,0.00061284454,0.0008852843],"category_scores_gemma":[0.0005449472,0.00036067993,0.0007639075,0.0003751665,0.00022153973,0.00019338753,0.0003208423,0.0003822334,0.00013120084],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030049507,0.00021812083,0.0029314817,0.00062676764,0.000077367535,0.0002613327,0.000088594454,0.7101285,0.23850702,0.00034535435,0.00022975706,0.046285253],"study_design_scores_gemma":[0.00005996461,0.0014893432,0.0063553615,0.000034956072,0.00006897916,0.00008505508,0.00012572353,0.92064685,0.06975396,0.00020942942,0.0011290917,0.000041275925],"about_ca_topic_score_codex":0.0032009904,"about_ca_topic_score_gemma":0.006273944,"teacher_disagreement_score":0.0032009904,"about_ca_system_score_codex":0.00036807155,"about_ca_system_score_gemma":0.00045335531,"threshold_uncertainty_score":0.006364703},"labels":[],"label_agreement":null},{"id":"W4200616504","doi":"10.21203/rs.3.rs-1054589/v1","title":"The Use of Wavelet Transform To Evaluate The Sensitivity of Acoustic Emission Attributes To Variation of Cutting Parameters in Milling Aluminium Alloys","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; University of British Columbia","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Acoustic emission; SIGNAL (programming language); Wavelet; Signal processing; Wavelet transform; Sensitivity (control systems); Cutting tool; Computer science; Process (computing); Machining; Pattern recognition (psychology); Materials science; Engineering; Artificial intelligence; Mechanical engineering; Electronic engineering; Digital signal processing; Composite material","score_opus":0.0874354826616384,"score_gpt":0.36035647645166297,"score_spread":0.27292099379002455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200616504","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96691203,0.00013360917,0.032469105,0.000012469663,0.000008490443,0.000016097132,0.000041503867,0.000046616726,0.00036008225],"genre_scores_gemma":[0.9955627,0.000058991085,0.0042533916,0.0000028969575,0.0000021917115,0.000006977012,0.000032897864,0.0000072105377,0.00007285317],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997739,0.00006243776,0.00001764374,0.000034904035,0.00009290113,0.000018229246],"domain_scores_gemma":[0.99897623,0.0006672733,0.00012228206,0.000055137873,0.00015326728,0.000025842157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079325953,0.00027452584,0.00026580621,0.00074411614,0.00011059989,0.00030562325,0.00016065747,0.00028593908,0.00035477272],"category_scores_gemma":[0.0020546762,0.000120268865,0.00023573292,0.0005226862,0.00023291344,0.00028076855,0.00017691325,0.00024079597,0.00006952336],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016919001,0.00033316299,0.04407884,0.00037666832,0.0001597313,0.00036300335,0.000364159,0.085336715,0.71579957,0.0005022548,0.00016669522,0.15082729],"study_design_scores_gemma":[0.00003076987,0.0015117921,0.18065545,0.00003712606,0.00012362273,0.00030839155,0.00029355846,0.54428077,0.2717387,0.0005021075,0.00046158527,0.000056193297],"about_ca_topic_score_codex":0.00048435136,"about_ca_topic_score_gemma":0.00030299826,"teacher_disagreement_score":0.00079325953,"about_ca_system_score_codex":0.000085505184,"about_ca_system_score_gemma":0.00008126847,"threshold_uncertainty_score":0.0041952133},"labels":[],"label_agreement":null},{"id":"W4205490300","doi":"10.1115/1.4053596","title":"Hybrid Modeling of Position-Dependent Dynamics of Thin-Walled Parts Using Shell Elements for Milling Simulation","year":2022,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Shell (structure); Eigenvalues and eigenvectors; Computation; Frequency response; Position (finance); Stiffness; Natural frequency; Finite element method; Normal mode; Structural engineering; Acoustics; Materials science; Algorithm; Mathematical analysis; Engineering; Computer science; Mathematics; Mechanical engineering; Vibration; Physics","score_opus":0.012389645191100468,"score_gpt":0.24008340811305862,"score_spread":0.22769376292195814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205490300","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0724862,0.000115341594,0.9212742,0.000049039812,0.0000251143,0.000054571967,0.000085094456,0.00043332807,0.0054770745],"genre_scores_gemma":[0.87495106,0.00022273554,0.11699276,0.000039575698,0.000010802979,0.0002478962,0.00020326966,0.00013790927,0.0071938904],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998574,0.00003512052,0.000007743052,0.000020067064,0.00006422416,0.000015347176],"domain_scores_gemma":[0.9997732,0.00010190514,0.000033033783,0.000028636601,0.00004915996,0.000014117701],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003014501,0.00051515887,0.0005936001,0.00038729922,0.0002857241,0.00065957726,0.001003154,0.00087394833,0.0017467464],"category_scores_gemma":[0.0005467536,0.0004456581,0.00077432406,0.00026987586,0.00052081654,0.0005134996,0.0006321149,0.00053996884,0.00043717542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012134531,0.000010939657,0.0002262563,0.000014184688,0.000008568998,0.000026968888,0.000024767287,0.99329233,0.0032088673,0.00092081726,0.000038662514,0.0022154266],"study_design_scores_gemma":[0.0000012915389,0.0000043934583,0.000031646083,0.0000012751717,0.0000010239894,0.0000031726058,0.0000020031082,0.99948335,0.0002799935,0.00008792089,0.00010266159,0.000001315487],"about_ca_topic_score_codex":0.0043863957,"about_ca_topic_score_gemma":0.003248547,"teacher_disagreement_score":0.0043863957,"about_ca_system_score_codex":0.0003116576,"about_ca_system_score_gemma":0.00055245706,"threshold_uncertainty_score":0.008721709},"labels":[],"label_agreement":null},{"id":"W4205509938","doi":"10.1016/j.ymssp.2021.108620","title":"Chatter stability analysis in Micro-milling with aerostatic spindle considering speed effect","year":2022,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Compute Canada","keywords":"Rotational speed; Stiffness; Bearing (navigation); Engineering; End milling; Stability (learning theory); Centrifugal force; Process (computing); Mechanical engineering; Critical speed; Structural engineering; Vibration; Control theory (sociology); Machining; Materials science; Acoustics; Rotor (electric); Computer science; Physics","score_opus":0.010330690717438558,"score_gpt":0.21582948632589177,"score_spread":0.20549879560845322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205509938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36862838,0.0015008842,0.6187976,0.00023134508,0.00012392573,0.000034874312,0.000033510543,0.00017845831,0.010471108],"genre_scores_gemma":[0.9934702,0.00017786991,0.0041290675,0.000009322713,0.000015600639,0.00001054956,0.000011407273,0.000018625884,0.0021572865],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997973,0.00005685258,0.000008053413,0.000039197672,0.00007847595,0.000020209296],"domain_scores_gemma":[0.99922514,0.0004031822,0.00009543049,0.00003347677,0.00022048761,0.000022317037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043965536,0.00046207473,0.0005643473,0.00043704893,0.00034446333,0.0005638091,0.00058899575,0.00059902377,0.0011993255],"category_scores_gemma":[0.0012882224,0.0002385549,0.00049635215,0.00022466901,0.0005691675,0.00061846076,0.0004033902,0.00046313016,0.00012398088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007896189,0.00009002148,0.0034314387,0.00058724417,0.00018661692,0.0013621355,0.0007036397,0.81799024,0.10455999,0.03999455,0.00095423515,0.029350182],"study_design_scores_gemma":[0.000002597634,0.00003014554,0.0005630495,0.0000030002263,0.000008390408,0.000030168145,0.000018470124,0.9966743,0.0017886638,0.0007889535,0.00008693826,0.000005352707],"about_ca_topic_score_codex":0.0027426106,"about_ca_topic_score_gemma":0.0018375751,"teacher_disagreement_score":0.0027426106,"about_ca_system_score_codex":0.00032443585,"about_ca_system_score_gemma":0.00028087804,"threshold_uncertainty_score":0.005453229},"labels":[],"label_agreement":null},{"id":"W4206098095","doi":"10.1007/s00170-021-08349-9","title":"Performance analysis of developed micro-textured cutting tool in machining aluminum alloy 7075-T6: assessment of tool wear and surface roughness","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Materials science; Enhanced Data Rates for GSM Evolution; Machining; Surface roughness; Aluminium; Tool wear; Insert (composites); Tungsten carbide; Metallurgy; Surface finish; Lubrication; Cutting tool; Rake; Aluminium alloy; Alloy; Mechanical engineering; Composite material; Computer science; Engineering","score_opus":0.00615596625362672,"score_gpt":0.25144595570332356,"score_spread":0.24528998944969685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206098095","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960096,0.00019927835,0.0031951626,0.000010789408,0.000008094522,0.000007760284,0.000054736993,0.00006126576,0.00045328581],"genre_scores_gemma":[0.9984882,0.000035612575,0.0010763548,0.000002807294,0.0000012792358,0.0000021171013,0.00003221209,0.0000048693773,0.000356565],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997036,0.000018722383,0.000014008115,0.00004429169,0.00018991057,0.000029401457],"domain_scores_gemma":[0.99947554,0.00015967031,0.00009446954,0.00005110539,0.00019335945,0.000025875448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026090385,0.0002208604,0.0003300917,0.00030368395,0.0001789986,0.00033631513,0.0004665349,0.0004841565,0.0007491301],"category_scores_gemma":[0.00057200197,0.00016051307,0.0002855694,0.00029048635,0.00017130884,0.00019287743,0.0001050826,0.00014516825,0.00012620026],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009995997,0.00009439239,0.008337734,0.0002727716,0.000041459698,0.00019226212,0.00015839079,0.014506313,0.94695187,0.00009283933,0.0001805753,0.028171794],"study_design_scores_gemma":[0.000044567558,0.00472024,0.12192221,0.000012936891,0.00009836055,0.0004692495,0.00028310795,0.112083875,0.75905746,0.00009190972,0.0011547016,0.00006137602],"about_ca_topic_score_codex":0.0016545439,"about_ca_topic_score_gemma":0.0028662167,"teacher_disagreement_score":0.0016545439,"about_ca_system_score_codex":0.00023134031,"about_ca_system_score_gemma":0.0001922286,"threshold_uncertainty_score":0.0032898784},"labels":[],"label_agreement":null},{"id":"W4206183436","doi":"10.1016/j.jmatprotec.2022.117498","title":"Effect of speed ratio on shear angle and forces in elliptical vibration assisted machining","year":2022,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Materials science; Vibration; Hardening (computing); Shear (geology); Strain hardening exponent; Mechanics; Structural engineering; Composite material; Metallurgy; Engineering; Physics; Acoustics","score_opus":0.005905994492488466,"score_gpt":0.24782217196661607,"score_spread":0.2419161774741276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206183436","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99714154,0.00027802776,0.0019148665,0.0000124280705,0.000013216447,0.0000050559247,0.000012599151,0.000030533814,0.0005917033],"genre_scores_gemma":[0.99930155,0.000058796224,0.00046778886,0.000001901763,0.0000027528856,0.0000017269886,0.0000073455517,0.0000057613356,0.00015235315],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997155,0.00006837873,0.000026228587,0.000055635424,0.000085726395,0.00004858276],"domain_scores_gemma":[0.9980469,0.0012790163,0.0002597837,0.00007623415,0.00024896392,0.00008910499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047452553,0.00033956114,0.00039634522,0.00039015003,0.00024948525,0.00041395452,0.0003326528,0.00038247035,0.0018879215],"category_scores_gemma":[0.0015875302,0.0002729974,0.00016600586,0.0003083457,0.0002978551,0.0003768446,0.00015100406,0.00019223556,0.0001924384],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007825066,0.0003152413,0.0076193367,0.00031733236,0.000054669323,0.0003209594,0.00029050154,0.01523138,0.9255161,0.0004934412,0.00019195855,0.041823965],"study_design_scores_gemma":[0.00016528842,0.005300101,0.051544283,0.00003903276,0.00019329261,0.0003647726,0.00034245307,0.0685562,0.872176,0.00020751673,0.001039294,0.0000716881],"about_ca_topic_score_codex":0.00027083218,"about_ca_topic_score_gemma":0.0004758407,"teacher_disagreement_score":0.0018879215,"about_ca_system_score_codex":0.0001409109,"about_ca_system_score_gemma":0.00017894211,"threshold_uncertainty_score":0.006315708},"labels":[],"label_agreement":null},{"id":"W4206431842","doi":"10.1007/s12206-021-1201-0","title":"Artificial intelligence enabled smart machining and machine tools","year":2022,"lang":"en","type":"article","venue":"Journal of Mechanical Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Machining; Transferability; Computer science; Artificial intelligence; Machine tool; Quality (philosophy); Machine learning; Engineering; Manufacturing engineering; Control engineering; Mechanical engineering","score_opus":0.019623438886648015,"score_gpt":0.24936252866714878,"score_spread":0.22973908978050075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206431842","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15331534,0.0057615573,0.7443456,0.0016668541,0.00089851284,0.000111003224,0.0002008137,0.0012708869,0.09242947],"genre_scores_gemma":[0.8091416,0.0021270688,0.16986066,0.00027020785,0.00009839698,0.000060211194,0.00018715234,0.00007641832,0.01817819],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999796,0.0000368856,0.0000120297145,0.000032538825,0.00010186636,0.000020733158],"domain_scores_gemma":[0.9997677,0.0000978883,0.000023112141,0.00005970294,0.00004019267,0.000011421792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027395037,0.00028015647,0.00036858523,0.0002955894,0.00024054467,0.0010670339,0.0005666907,0.0007817392,0.0027879332],"category_scores_gemma":[0.00064041524,0.00022431434,0.00031533078,0.00037626486,0.00093779655,0.0012611336,0.00076560484,0.00076814543,0.00050062855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026968902,0.00015584375,0.0013253895,0.0005923327,0.000118974545,0.00045104235,0.00030487258,0.18011309,0.11288143,0.47227296,0.005951815,0.22556248],"study_design_scores_gemma":[0.00003373704,0.00019731157,0.0020131462,0.00006795431,0.00004172171,0.0002630491,0.00009712844,0.7089973,0.036164682,0.19643107,0.0556428,0.00005007135],"about_ca_topic_score_codex":0.00045413448,"about_ca_topic_score_gemma":0.00052585744,"teacher_disagreement_score":0.0027879332,"about_ca_system_score_codex":0.00040237437,"about_ca_system_score_gemma":0.00029137838,"threshold_uncertainty_score":0.009326637},"labels":[],"label_agreement":null},{"id":"W4206825532","doi":"10.32864/0202-4977-2021-42-6-707-716","title":"Influence of Cutting Conditions on Wear Resistance of Tools with TiB2 Coating During Titanium Alloy Machining","year":2021,"lang":"en","type":"article","venue":"Trenie i Iznos","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Metallurgy; Titanium alloy; Coating; Materials science; Alloy; Wear resistance; Titanium; Composite material","score_opus":0.007522749670751575,"score_gpt":0.22764691278651342,"score_spread":0.22012416311576183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206825532","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987914,0.0005624369,0.00020846256,0.00001008698,0.000016193308,0.0000033417095,0.000048756738,0.000017181588,0.00034215435],"genre_scores_gemma":[0.9992205,0.00012167117,0.00027062386,0.000007424778,0.000005735147,0.0000027987342,0.000057403053,0.000013891434,0.00029997126],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996623,0.000039997027,0.00002796261,0.00007191526,0.00009849938,0.000099224126],"domain_scores_gemma":[0.99882036,0.00050688605,0.00019428725,0.00009148066,0.00031022268,0.000076764125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003759556,0.0003149549,0.0004040963,0.00029713806,0.00031051633,0.0005254884,0.00031358594,0.0004180171,0.0013047489],"category_scores_gemma":[0.0012300495,0.00023808045,0.00024014984,0.0002553541,0.00023036083,0.00034232475,0.00019542783,0.00028625934,0.00023736853],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027290364,0.0000978572,0.004379359,0.00031103552,0.000054387252,0.00022425986,0.00037980467,0.0023903172,0.97474784,0.00006640232,0.00033734165,0.014282379],"study_design_scores_gemma":[0.000043618118,0.0022690727,0.03709864,0.000026534282,0.0000934906,0.00018402518,0.00040180652,0.006815186,0.95162237,0.000047812067,0.0013518572,0.000045684683],"about_ca_topic_score_codex":0.00090207654,"about_ca_topic_score_gemma":0.0020287924,"teacher_disagreement_score":0.0013047489,"about_ca_system_score_codex":0.0002054084,"about_ca_system_score_gemma":0.0001662812,"threshold_uncertainty_score":0.0043647885},"labels":[],"label_agreement":null},{"id":"W4206968285","doi":"10.1007/s00170-021-08322-6","title":"Analytical model for predicting tool wear in orthogonal machining of unidirectional carbon fibre reinforced polymer (CFRP)","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Innosuisse - Schweizerische Agentur für Innovationsförderung","keywords":"Machining; Tool wear; Materials science; Abrasive; Enhanced Data Rates for GSM Evolution; Mechanical engineering; Geometry; Composite material; Computer science; Mathematics; Engineering; Metallurgy","score_opus":0.0073379903690942985,"score_gpt":0.2394842325576034,"score_spread":0.2321462421885091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206968285","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46709713,0.00060074346,0.524395,0.0001501489,0.00004276253,0.00011894283,0.00023735018,0.0006777698,0.0066800597],"genre_scores_gemma":[0.9913025,0.00010382152,0.006698838,0.000009816533,0.0000036836018,0.000042142277,0.00003908545,0.000014928067,0.0017851212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998363,0.00002355875,0.000009159192,0.000030193487,0.00007315787,0.000027551008],"domain_scores_gemma":[0.9996588,0.0001642732,0.000059456786,0.000026052796,0.00008115062,0.000010178688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030187517,0.0004460961,0.00041867615,0.0005764488,0.0002239882,0.00045844723,0.0007861692,0.0011191837,0.0007493529],"category_scores_gemma":[0.0008851704,0.0002652465,0.00060670683,0.00027553958,0.00031924102,0.00031112204,0.00022793331,0.00033945128,0.00022153485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002914367,0.000028552573,0.0010023488,0.000040271112,0.0000072615694,0.00012477628,0.00004771061,0.98521477,0.008140658,0.00037373547,0.00008041355,0.0049104025],"study_design_scores_gemma":[0.0000011446671,0.0000148834915,0.00017854988,0.000001732862,0.000001323252,0.00001502356,0.0000034850548,0.99922156,0.00044880947,0.000054626646,0.00005724146,0.0000016062678],"about_ca_topic_score_codex":0.006801132,"about_ca_topic_score_gemma":0.0042129005,"teacher_disagreement_score":0.006801132,"about_ca_system_score_codex":0.00052550767,"about_ca_system_score_gemma":0.00044475243,"threshold_uncertainty_score":0.013523102},"labels":[],"label_agreement":null},{"id":"W4210242691","doi":"10.1007/s10845-022-01913-4","title":"Autonomous self-healing mechanism for a CNC milling machine based on pattern recognition","year":2022,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Mitacs","keywords":"Mechanism (biology); Manufacturing engineering; Production (economics); Computer science; Engineering; Artificial intelligence; Engineering drawing","score_opus":0.01591198603505117,"score_gpt":0.23225932796836612,"score_spread":0.21634734193331495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210242691","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38211447,0.00047835975,0.60279363,0.000390667,0.00038512595,0.00019799758,0.000057302255,0.00288308,0.010699388],"genre_scores_gemma":[0.946979,0.000055651326,0.049695335,0.000051403626,0.00001533791,0.00004916625,0.000023134278,0.000017565006,0.0031134482],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998419,0.000009092473,0.0000082207525,0.00004213706,0.00008038008,0.000018297666],"domain_scores_gemma":[0.999806,0.000031125805,0.0000379393,0.0000395313,0.00006444405,0.000020975622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016332869,0.00023139612,0.00033990544,0.0002812578,0.00044743932,0.00033578856,0.0010689074,0.0005200967,0.0016077],"category_scores_gemma":[0.0002496668,0.00018056661,0.00020012297,0.00016092407,0.00030972218,0.00036597307,0.00034293314,0.00024139133,0.00023794045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003893718,0.00017245248,0.0012950437,0.00013360134,0.000034445424,0.00037547058,0.00014123472,0.02507221,0.8250022,0.0049705193,0.0016414253,0.1407721],"study_design_scores_gemma":[0.0000687711,0.0004892307,0.003525225,0.000014165407,0.00004213478,0.000493326,0.000039946925,0.8057076,0.1820803,0.0016875054,0.005802535,0.000049308535],"about_ca_topic_score_codex":0.00067676743,"about_ca_topic_score_gemma":0.0007844891,"teacher_disagreement_score":0.0016077,"about_ca_system_score_codex":0.00021150507,"about_ca_system_score_gemma":0.00043221578,"threshold_uncertainty_score":0.0053782463},"labels":[],"label_agreement":null},{"id":"W4210257440","doi":"10.1002/ls.1592","title":"An investigation into the tribological behaviour of cutting fluid additives on <scp>Ti‐6Al‐4V</scp> alloy","year":2022,"lang":"en","type":"article","venue":"Lubrication Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tribology; Materials science; Polymer; Machining; Alloy; Composite material; Friction coefficient; Coefficient of friction; Titanium alloy; Metallurgy","score_opus":0.015073174331400416,"score_gpt":0.2670054672352201,"score_spread":0.2519322929038197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210257440","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983113,0.00048034298,0.00057553325,0.0000128410875,0.000009927716,0.000012349964,0.000058245354,0.0000201318,0.00051931565],"genre_scores_gemma":[0.9975096,0.0002676642,0.0011298315,0.000007938558,0.000004558165,0.000008163806,0.00007044857,0.000011699545,0.0009900285],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994204,0.00007091332,0.000033804707,0.000056703877,0.0003499191,0.00006823115],"domain_scores_gemma":[0.9995994,0.00009984577,0.00006972965,0.000027953705,0.00018105618,0.000022062057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029634195,0.00035564875,0.00042022718,0.0006904201,0.00033151306,0.00042210871,0.00041630556,0.00042502678,0.0012460343],"category_scores_gemma":[0.00067432964,0.00021449696,0.0002870946,0.0004305214,0.00026170159,0.0003130259,0.00021852004,0.00030493175,0.00027701652],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018066574,0.000023155666,0.00048517017,0.00010337714,0.000010876839,0.00007794688,0.00003987475,0.00022778058,0.99532676,0.000021356835,0.000022202956,0.0034807418],"study_design_scores_gemma":[0.0000033297424,0.0005880041,0.0034176908,0.000006922804,0.000017734093,0.00006806944,0.00004161073,0.000934682,0.99411607,0.000008455829,0.0007914578,0.0000058710507],"about_ca_topic_score_codex":0.0010711357,"about_ca_topic_score_gemma":0.0019140827,"teacher_disagreement_score":0.0012460343,"about_ca_system_score_codex":0.00024905198,"about_ca_system_score_gemma":0.00021781756,"threshold_uncertainty_score":0.004168391},"labels":[],"label_agreement":null},{"id":"W4210990065","doi":"10.1007/s00170-021-08648-1","title":"Milling of Inconel 718: an experimental and integrated modeling approach for surface roughness","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Response surface methodology; Machining; Surface roughness; Machinability; Inconel; Mechanical engineering; Particle swarm optimization; End mill; Design of experiments; Box–Behnken design; Surface finish; Materials science; Engineering; Computer science; Mathematics; Metallurgy; Composite material; Machine learning; Statistics","score_opus":0.011814870418714003,"score_gpt":0.25352215751349144,"score_spread":0.24170728709477743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210990065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90314883,0.00029033137,0.07814308,0.00013072949,0.000048751426,0.00016516507,0.002247145,0.0013960752,0.014429859],"genre_scores_gemma":[0.9787717,0.00010793493,0.018704541,0.000015485115,0.0000038082915,0.000070204675,0.00055180606,0.000089368885,0.0016852367],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964285,0.00003116899,0.000019837362,0.000082054845,0.00018985738,0.00003432086],"domain_scores_gemma":[0.9996593,0.000092582086,0.000035544144,0.00007227973,0.00013093148,0.000009392195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004242318,0.00050933874,0.0007036532,0.00034094643,0.0004005901,0.0006170689,0.001251526,0.0009074187,0.0026064904],"category_scores_gemma":[0.00057260605,0.00037150105,0.00046058526,0.0007330068,0.00023823827,0.00061880774,0.00022746024,0.00051351334,0.00037966642],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037056275,0.0004915614,0.008266938,0.0004388618,0.00006115227,0.00016674194,0.00017384316,0.83337563,0.10192955,0.0024505027,0.002185252,0.050089326],"study_design_scores_gemma":[0.000025270863,0.00016640402,0.0033076918,0.0000059322615,0.000014554372,0.000033695174,0.000024663463,0.96574545,0.029100398,0.00015797422,0.0013947873,0.000023146607],"about_ca_topic_score_codex":0.009360558,"about_ca_topic_score_gemma":0.01219438,"teacher_disagreement_score":0.009360558,"about_ca_system_score_codex":0.0006016243,"about_ca_system_score_gemma":0.0008541055,"threshold_uncertainty_score":0.018612146},"labels":[],"label_agreement":null},{"id":"W4211098532","doi":"10.1139/tcsme-2021-0086","title":"Optimizing the parameters for force, temperature, and metal removal rate: a multi-feature fusion model for titanium alloy milling","year":2022,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Materials science; Titanium alloy; Fusion; Alloy; Titanium; Mechanical engineering; Milling cutter; Process (computing); Metallurgy; Feature (linguistics); Particle swarm optimization; Machining; Computer science; Algorithm; Engineering","score_opus":0.012887737488570672,"score_gpt":0.21032151756876333,"score_spread":0.19743378008019266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211098532","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12708908,0.00037424953,0.86976767,0.000093168106,0.000022425716,0.00009550122,0.00006576597,0.00026379398,0.0022284752],"genre_scores_gemma":[0.96059155,0.00016907335,0.0380105,0.000020816706,0.000005926218,0.00012026703,0.000057948444,0.000025790137,0.0009980691],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996954,0.000037502123,0.00001646653,0.00007164594,0.00013919108,0.000039853436],"domain_scores_gemma":[0.9996562,0.00014399248,0.00007525741,0.000021633348,0.00009018978,0.000012634768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066107535,0.00060854584,0.0008584143,0.00044871474,0.00038027097,0.0006587411,0.0009929124,0.0010478686,0.0005599935],"category_scores_gemma":[0.0009211404,0.0004236333,0.0011481582,0.00039625753,0.00040843015,0.0007751543,0.00047365585,0.0005788347,0.00014072009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045110584,0.000032513788,0.00051040336,0.00003784294,0.000016938004,0.000030662457,0.00003858822,0.98153013,0.007900561,0.0006055055,0.00007383865,0.009177926],"study_design_scores_gemma":[0.0000021369335,0.000018931793,0.00013243593,8.9656277e-7,0.0000040963146,0.0000048606125,0.0000025043325,0.9991234,0.0005682914,0.00008523082,0.000054486634,0.0000028204188],"about_ca_topic_score_codex":0.007785868,"about_ca_topic_score_gemma":0.004308884,"teacher_disagreement_score":0.007785868,"about_ca_system_score_codex":0.00085237937,"about_ca_system_score_gemma":0.0008274044,"threshold_uncertainty_score":0.015481055},"labels":[],"label_agreement":null},{"id":"W4212777341","doi":"10.1016/j.ymssp.2022.108945","title":"Multibody dynamic modeling of five-axis machine tools with improved efficiency","year":2022,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Multibody system; Kinematics; Jacobian matrix and determinant; Vibration; Machine tool; Control theory (sociology); Substructure; Computer science; Computation; Engineering; Algorithm; Mathematics; Structural engineering; Mechanical engineering; Artificial intelligence; Physics; Applied mathematics","score_opus":0.0086119826697677,"score_gpt":0.22052496735527372,"score_spread":0.211912984685506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212777341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20319878,0.00048488379,0.7666331,0.00016911209,0.00006893649,0.0000658377,0.00019711844,0.00047745858,0.028704766],"genre_scores_gemma":[0.9719642,0.0001437374,0.022242548,0.000022262982,0.000009118874,0.00005031953,0.00007252068,0.000067504705,0.005427654],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998466,0.000037636284,0.000008230157,0.000019387604,0.000068242276,0.000019824476],"domain_scores_gemma":[0.99982053,0.00006193679,0.000037495338,0.000026630656,0.00004250063,0.00001087332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002759613,0.00052240555,0.00048526333,0.0004953081,0.0003319438,0.00078312785,0.0010152686,0.0010009902,0.002913228],"category_scores_gemma":[0.0005782226,0.00034994032,0.000625128,0.0005076235,0.00033171065,0.00069734897,0.00039003568,0.00032147762,0.00058457325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028333094,0.000017690689,0.00021742484,0.000028554061,0.000007278747,0.000057380785,0.000035109202,0.9878855,0.003568082,0.0027698413,0.00013503061,0.005249695],"study_design_scores_gemma":[0.0000027877056,0.000011603106,0.00012533196,0.0000022226523,0.0000017930097,0.000008878466,0.000005861798,0.99885833,0.00045168563,0.00025901094,0.0002704786,0.0000020709338],"about_ca_topic_score_codex":0.0035436887,"about_ca_topic_score_gemma":0.0029846374,"teacher_disagreement_score":0.0035436887,"about_ca_system_score_codex":0.00029989326,"about_ca_system_score_gemma":0.0003528326,"threshold_uncertainty_score":0.009745777},"labels":[],"label_agreement":null},{"id":"W4213117502","doi":"10.1177/09544054221078144","title":"Prediction of tool wear based on GA-BP neural network","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Jiangsu Key Laboratory of Precision and Micro-Manufacturing Technology","keywords":"Artificial neural network; Backpropagation; Genetic algorithm; Approximation error; Mean squared error; Algorithm; Anisotropy; Computer science; Mean absolute percentage error; Artificial intelligence; Materials science; Machine learning; Mathematics; Statistics","score_opus":0.008352201400205095,"score_gpt":0.1837754815513098,"score_spread":0.1754232801511047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213117502","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4188319,0.000663949,0.5748569,0.00018378477,0.000102148915,0.00011905801,0.00014573526,0.0014447923,0.0036517112],"genre_scores_gemma":[0.97179765,0.00012311457,0.026697991,0.000021174581,0.000009103175,0.00006673202,0.00007470881,0.000016976666,0.0011925821],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977535,0.000040510535,0.000014010725,0.000058105412,0.000070541675,0.000041432002],"domain_scores_gemma":[0.99941206,0.00029321812,0.00005420924,0.000026797565,0.00019681547,0.000016860653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052671897,0.0008716787,0.0006673517,0.00070498453,0.00027661512,0.0005138409,0.0006246441,0.0009230276,0.00074008584],"category_scores_gemma":[0.001682373,0.00033075572,0.0004647096,0.0005340391,0.0002925224,0.0004885717,0.00027717187,0.000594114,0.0001408694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065407796,0.000038680835,0.0014244093,0.00003526205,0.000023921833,0.000043103635,0.00001821266,0.964716,0.0022293276,0.00017136018,0.00018490272,0.03104937],"study_design_scores_gemma":[0.000001397268,0.0000075951452,0.00022910966,9.843898e-7,0.000002007623,0.000002305829,0.0000013067279,0.99941635,0.00027833055,0.000043840795,0.000015457994,0.0000013944738],"about_ca_topic_score_codex":0.019842682,"about_ca_topic_score_gemma":0.009520665,"teacher_disagreement_score":0.019842682,"about_ca_system_score_codex":0.0006386604,"about_ca_system_score_gemma":0.0005867005,"threshold_uncertainty_score":0.0394544},"labels":[],"label_agreement":null},{"id":"W4213173565","doi":"10.1007/978-3-642-20617-7_100306","title":"Micro-turning","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science","score_opus":0.006263201780177489,"score_gpt":0.1926082741537908,"score_spread":0.1863450723736133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213173565","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035920588,0.012786383,0.030562814,0.00031982298,0.0016058476,0.000035581346,0.000140347,0.0005670125,0.9503901],"genre_scores_gemma":[0.04443475,0.009953208,0.011757477,0.00028912674,0.00028054733,0.000047217152,0.00033930337,0.00026496337,0.93263346],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99982435,0.000008113963,0.0000035998216,0.000039963015,0.000099340294,0.000024762514],"domain_scores_gemma":[0.9999589,0.00000779263,0.000002952138,0.000011122938,0.000013823579,0.000005418789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007778219,0.0007953729,0.00045306928,0.0008511069,0.0006726387,0.0011639523,0.00057000323,0.0006233824,0.04132861],"category_scores_gemma":[0.00014135406,0.00036534228,0.0003977565,0.00056530535,0.00059018534,0.00092182006,0.0010063176,0.0013337154,0.014315336],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005911758,0.000049459733,0.000105894345,0.00048364047,0.000015567412,0.00018177832,0.00016693058,0.0030943248,0.035097815,0.22830449,0.09508644,0.6373546],"study_design_scores_gemma":[0.0000046404384,0.000044781787,0.0004164271,0.00013395688,0.000008133746,0.00051293266,0.00005157725,0.0024606446,0.017389577,0.0276682,0.9512874,0.00002177409],"about_ca_topic_score_codex":0.0006053018,"about_ca_topic_score_gemma":0.0016949082,"teacher_disagreement_score":0.04132861,"about_ca_system_score_codex":0.00052014604,"about_ca_system_score_gemma":0.00033576935,"threshold_uncertainty_score":0.13825798},"labels":[],"label_agreement":null},{"id":"W4220666717","doi":"10.18280/mmep.090123","title":"Comparative Prediction and Modelling of Surface Roughness in Milling of AL-7075 Using Regression Analysis and Neural Network","year":2022,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Regression analysis; Surface roughness; Regression; Linear regression; Process (computing); Surface finish; Polynomial regression; Computer science; Statistics; Mathematics; Artificial intelligence; Engineering; Materials science; Metallurgy; Composite material","score_opus":0.03517445996565457,"score_gpt":0.2397883212869582,"score_spread":0.20461386132130363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220666717","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8514849,0.00069361716,0.14305006,0.0001477392,0.000029704475,0.000041108135,0.000116409465,0.0006089952,0.003827425],"genre_scores_gemma":[0.9895579,0.0001733683,0.00936597,0.00000663631,0.000003016264,0.000016509026,0.00006659676,0.000011527433,0.00079837686],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998161,0.00003981182,0.000016491467,0.00004238921,0.000061970015,0.000023312652],"domain_scores_gemma":[0.99959606,0.00026092248,0.000043412492,0.00001873405,0.000073410876,0.0000075356047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047081657,0.0005184475,0.00034313428,0.000581413,0.0001861434,0.0005595242,0.00036437812,0.0005297094,0.00052631024],"category_scores_gemma":[0.00096229557,0.00021999849,0.0006753767,0.00032576363,0.00014689601,0.00036963666,0.0001317056,0.00031201853,0.000117818156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008523143,0.000058716632,0.0048099565,0.000083240775,0.000033936853,0.000066993925,0.000046410336,0.95300347,0.006723869,0.000295725,0.00017163304,0.03462078],"study_design_scores_gemma":[9.938036e-7,0.000027413784,0.0008804785,0.0000021643864,0.0000055117325,0.000005970833,0.0000069139005,0.9976221,0.0013509704,0.000039470917,0.000054712003,0.0000033290742],"about_ca_topic_score_codex":0.013354715,"about_ca_topic_score_gemma":0.009403208,"teacher_disagreement_score":0.013354715,"about_ca_system_score_codex":0.00041743714,"about_ca_system_score_gemma":0.00030580166,"threshold_uncertainty_score":0.026553988},"labels":[],"label_agreement":null},{"id":"W4220672308","doi":"10.21203/rs.3.rs-1443976/v1","title":"A Comparative Analysis of Chip Shape, Residual Stresses, and Surface Roughness in Minimum-Quantity-Lubrication Turning with Various Flow Rates","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Volumetric flow rate; Surface roughness; Lubrication; Machining; Surface integrity; Materials science; Chip; Flow (mathematics); Surface finish; Residual; Residual stress; Composite material; Mechanics; Engineering drawing; Mechanical engineering; Metallurgy; Mathematics; Geometry; Engineering; Physics","score_opus":0.0426527950055864,"score_gpt":0.36855963892907345,"score_spread":0.32590684392348707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220672308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981359,0.0002201998,0.001436692,0.000006139418,0.000007306456,0.0000071420363,0.00003066891,0.000019003954,0.0001369162],"genre_scores_gemma":[0.99874204,0.000077607365,0.0009834665,0.000006380835,0.0000021171431,0.0000049403384,0.000044162705,0.0000075652692,0.00013179319],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995753,0.000054422402,0.000034378718,0.000052801657,0.00021809232,0.000064910986],"domain_scores_gemma":[0.99916565,0.00029418233,0.00017354706,0.0000600942,0.00025764084,0.000048946014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005059304,0.00026108275,0.00041807015,0.00047807847,0.00018128444,0.00037295328,0.00019139043,0.00032380642,0.00059205276],"category_scores_gemma":[0.0009838172,0.00016456538,0.0003914788,0.00027605207,0.00032396236,0.00031624327,0.00014066415,0.00022338209,0.00010095688],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046813485,0.0000404771,0.004026468,0.00007919901,0.000013241443,0.00007169338,0.0000934425,0.0008099181,0.9869196,0.000033497738,0.000028812567,0.007415529],"study_design_scores_gemma":[0.00001686675,0.0016019411,0.052822623,0.00000897334,0.000057457728,0.00014021533,0.00019602204,0.006274222,0.93841875,0.00003619513,0.0003918682,0.000034827848],"about_ca_topic_score_codex":0.000561188,"about_ca_topic_score_gemma":0.0008387799,"teacher_disagreement_score":0.00059205276,"about_ca_system_score_codex":0.0001335608,"about_ca_system_score_gemma":0.000113973176,"threshold_uncertainty_score":0.002675593},"labels":[],"label_agreement":null},{"id":"W4220725518","doi":"10.1007/s42452-022-04987-0","title":"Teaching machines to optimizing machining parameters: using independent fuzzy logic controller and image data","year":2022,"lang":"en","type":"article","venue":"SN Applied Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Computer science; Fuzzy logic; Artificial neural network; Controller (irrigation); Control engineering; Industrial engineering; Mechanical engineering; Artificial intelligence; Engineering","score_opus":0.04387373409956748,"score_gpt":0.2988088521964413,"score_spread":0.25493511809687386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220725518","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02580996,0.0001582103,0.96709824,0.0001430586,0.000041376217,0.0001091715,0.00001485298,0.00089623133,0.005728935],"genre_scores_gemma":[0.5726513,0.00029345683,0.42150146,0.00017862776,0.00004420158,0.00020677774,0.000044865894,0.00008159578,0.0049976497],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998104,0.000026753132,0.000010296344,0.00005545995,0.000081583225,0.000015588408],"domain_scores_gemma":[0.99964523,0.00016821612,0.000038137932,0.000028001736,0.00010292332,0.000017422692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047494707,0.00063205796,0.0002935452,0.00024326464,0.00026835004,0.0005426741,0.00076564826,0.0006353723,0.0026291907],"category_scores_gemma":[0.0015627205,0.00023823646,0.00025495415,0.00018557435,0.00033817216,0.00064903166,0.00044671292,0.0007869131,0.00038911763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019985488,0.00037045407,0.0012720918,0.00030931615,0.000039389393,0.000108255,0.0003759833,0.19655418,0.077816196,0.008314833,0.0022419987,0.71239746],"study_design_scores_gemma":[0.000025136127,0.0001266579,0.0005140473,0.000030454883,0.000020038011,0.000043237753,0.00003518008,0.9730334,0.020987075,0.0024111082,0.002758683,0.000014947671],"about_ca_topic_score_codex":0.0029318251,"about_ca_topic_score_gemma":0.0039413185,"teacher_disagreement_score":0.0029318251,"about_ca_system_score_codex":0.0004065202,"about_ca_system_score_gemma":0.00065055763,"threshold_uncertainty_score":0.0087955},"labels":[],"label_agreement":null},{"id":"W4220762911","doi":"10.18280/ts.390131","title":"Analysis of Regenerative Raw Signals Using Variational Mode Decomposition","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Microphone; Mode (computer interface); Frequency domain; Machining; Computer science; Frequency response; Control theory (sociology); Time domain; Engineering; Algorithm; Artificial intelligence; Mechanical engineering; Computer vision","score_opus":0.014750600352742399,"score_gpt":0.28909960432558107,"score_spread":0.2743490039728387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220762911","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07047491,0.00021935622,0.9277337,0.000041938478,0.00002167966,0.000045215413,0.000072245624,0.00021649546,0.001174491],"genre_scores_gemma":[0.75971496,0.00043869132,0.23674421,0.000021908683,0.00001685791,0.000086757274,0.00023851506,0.00006972692,0.002668342],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998629,0.00002739778,0.0000067972896,0.000023513207,0.00006677503,0.000012576654],"domain_scores_gemma":[0.9997799,0.00011532661,0.000026527981,0.000020297502,0.00005106628,0.0000068766985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039819544,0.00048132017,0.00031873467,0.0004134584,0.00011800952,0.0003839925,0.00034740873,0.0003445819,0.0012144696],"category_scores_gemma":[0.0006882787,0.00013832543,0.00038851862,0.0003195574,0.0002831063,0.00033275684,0.00024042361,0.00041190346,0.00017017442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002677998,0.00009112186,0.0028074323,0.00058332505,0.00011284189,0.00031618238,0.00038957453,0.2992412,0.44134104,0.013143422,0.0006552939,0.24105078],"study_design_scores_gemma":[0.0000056531067,0.00010936215,0.0030461478,0.000016853754,0.000010685042,0.00008539377,0.00005783765,0.9662588,0.027375676,0.001739925,0.0012744662,0.000019199502],"about_ca_topic_score_codex":0.0012041093,"about_ca_topic_score_gemma":0.00112374,"teacher_disagreement_score":0.0012144696,"about_ca_system_score_codex":0.0001568818,"about_ca_system_score_gemma":0.0002867141,"threshold_uncertainty_score":0.0040628314},"labels":[],"label_agreement":null},{"id":"W4220764481","doi":"10.18280/mmep.090117","title":"Experimental Investigation on the Performance of Different Cutting Fluids on Cutting Force During Turning of Duplex Stainless Steel-2205 under MQL Technique","year":2022,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Technology Warangal","keywords":"Cutting fluid; Lubrication; Materials science; Machining; Metallurgy; Mineral oil; Composite material","score_opus":0.018082211994372453,"score_gpt":0.20329053833768726,"score_spread":0.1852083263433148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220764481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976666,0.00022053791,0.0017016822,0.000014581065,0.000009963851,0.000016440856,0.000050637344,0.000016616295,0.00030292952],"genre_scores_gemma":[0.9953746,0.00021698719,0.003732359,0.000011521636,0.0000049561686,0.000021497923,0.000060409486,0.0000072254466,0.0005703697],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99951684,0.000056577377,0.00004459317,0.00008199218,0.00022010274,0.00007991811],"domain_scores_gemma":[0.99923444,0.0002925418,0.00014164271,0.000052128715,0.00023905183,0.00004016154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000450834,0.0003708869,0.00045875373,0.0003210329,0.0002540028,0.00022241785,0.00026821677,0.00041284238,0.0008542557],"category_scores_gemma":[0.00080624723,0.00016784036,0.00027001512,0.00028836523,0.00029264708,0.00022131679,0.00017523605,0.00033116335,0.00013009085],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035366323,0.00009732136,0.00077470794,0.00020480786,0.000005060079,0.000057639005,0.00017629228,0.0005740704,0.991302,0.000037276735,0.000035267938,0.006381846],"study_design_scores_gemma":[0.000012988229,0.0030027595,0.007980239,0.000010869556,0.000019836933,0.00006719444,0.00016455067,0.0021189789,0.98599017,0.00002913208,0.0005868021,0.000016428228],"about_ca_topic_score_codex":0.0005812337,"about_ca_topic_score_gemma":0.0014829887,"teacher_disagreement_score":0.0008542557,"about_ca_system_score_codex":0.00015314156,"about_ca_system_score_gemma":0.00018721797,"threshold_uncertainty_score":0.0028577447},"labels":[],"label_agreement":null},{"id":"W4220851744","doi":"10.1080/17480272.2022.2049867","title":"Modeling and optimizing the specific cutting energy of medium density fiberboard during the helical up-milling process","year":2022,"lang":"en","type":"article","venue":"Wood Material Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Science Research of Jiangsu Higher Education Institutions of China","keywords":"Medium density fiberboard; Materials science; Rotation (mathematics); Fiberboard; Rotational speed; Machining; Energy (signal processing); Surface roughness; Process (computing); Surface finish; Composite material; Mechanical engineering; Mathematics; Geometry; Metallurgy; Engineering; Statistics; Computer science","score_opus":0.005501612731891741,"score_gpt":0.19007444723919728,"score_spread":0.18457283450730555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220851744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8120013,0.0006084749,0.18271364,0.000070347334,0.000018199587,0.00006906431,0.00017513266,0.00013525102,0.0042085727],"genre_scores_gemma":[0.9864877,0.0003104323,0.011999692,0.0000052201804,0.0000020351251,0.00003739688,0.0000750073,0.00001568107,0.0010668818],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999087,0.0000089501245,0.0000055318624,0.000022400367,0.000034967114,0.000019529045],"domain_scores_gemma":[0.99991083,0.00004261515,0.00001981339,0.000005716932,0.000017322565,0.0000037896539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025006157,0.00046037984,0.00034912012,0.00027944875,0.00021232828,0.00053925626,0.0003606605,0.00045020122,0.0005992716],"category_scores_gemma":[0.00030553035,0.0002809643,0.0005501602,0.00035883838,0.00019775495,0.00035290982,0.00015990126,0.00029235508,0.00011218028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046827736,0.000049169957,0.002128695,0.000121985904,0.000009765924,0.00008043324,0.000027105227,0.9519583,0.03612021,0.00036097315,0.000062531275,0.009033939],"study_design_scores_gemma":[0.000004068989,0.00006395142,0.0018096955,0.0000037434156,0.000011157502,0.000014767029,0.000012925658,0.98473686,0.012984698,0.00011456234,0.00023665446,0.0000069381376],"about_ca_topic_score_codex":0.007142126,"about_ca_topic_score_gemma":0.007849696,"teacher_disagreement_score":0.007142126,"about_ca_system_score_codex":0.00043263912,"about_ca_system_score_gemma":0.0005773269,"threshold_uncertainty_score":0.014201105},"labels":[],"label_agreement":null},{"id":"W4221020998","doi":"10.1007/s00170-022-08906-w","title":"Turning of Inconel 718 using liquid nitrogen: multi-objective optimization of cutting parameters using RSM","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Inconel; Flank; Response surface methodology; Surface roughness; Materials science; Liquid nitrogen; Cutting tool; Tool wear; Machining; Metallurgy; Composite material; Mathematics; Chemistry","score_opus":0.013657449894749792,"score_gpt":0.26036961366847866,"score_spread":0.24671216377372887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221020998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9140534,0.00064732344,0.06817518,0.00012327738,0.00009110595,0.00014704125,0.00026601495,0.00043501868,0.016061721],"genre_scores_gemma":[0.96896577,0.0001935852,0.027306154,0.000027724447,0.000008374785,0.00009877036,0.00025540873,0.000064871005,0.0030792048],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99974483,0.000041749307,0.000011664252,0.000043825436,0.00009269558,0.00006518529],"domain_scores_gemma":[0.9996505,0.00017986173,0.00004750995,0.0000225548,0.00007996432,0.000019625106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006393151,0.0009497404,0.0014084204,0.00095159316,0.0005664779,0.0010840378,0.00066139636,0.0012238323,0.0028307876],"category_scores_gemma":[0.00064398255,0.0006798785,0.0011578337,0.0006556132,0.0003408166,0.0004216571,0.00040838323,0.0006082762,0.00028779285],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028519993,0.00014803825,0.00090004544,0.00025126716,0.000046768277,0.0001159935,0.00004134046,0.961732,0.017853254,0.00047386903,0.00036169498,0.01779053],"study_design_scores_gemma":[0.00003676548,0.0004736924,0.0014343539,0.0000125908555,0.000040690167,0.000020284124,0.000058238296,0.9888566,0.008247354,0.00013975851,0.000661046,0.000018681372],"about_ca_topic_score_codex":0.011476865,"about_ca_topic_score_gemma":0.0140064,"teacher_disagreement_score":0.011476865,"about_ca_system_score_codex":0.0007410082,"about_ca_system_score_gemma":0.0010526583,"threshold_uncertainty_score":0.022820115},"labels":[],"label_agreement":null},{"id":"W4221021497","doi":"10.1016/j.ijmachtools.2022.103873","title":"Optimal cutting condition selection for high quality receptance measurements by sweep milling force excitation","year":2022,"lang":"en","type":"article","venue":"International Journal of Machine Tools and Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Centro para el Desarrollo Tecnológico Industrial","keywords":"Machining; Computation; Vibration; Sweep frequency response analysis; SIGNAL (programming language); Time domain; Noise (video); Characterization (materials science); Excitation; Stability (learning theory); Computer science; Boundary (topology); Mechanical engineering; Machine tool; Quality (philosophy); Acoustics; Engineering; Algorithm; Materials science; Physics; Artificial intelligence; Mathematics","score_opus":0.017526496197498635,"score_gpt":0.28791791174796527,"score_spread":0.27039141555046664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221021497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6220736,0.00047769383,0.37159237,0.00015244777,0.00003749732,0.00011069667,0.00021600032,0.0008717312,0.0044679246],"genre_scores_gemma":[0.9106094,0.00009713114,0.08854453,0.000031027514,0.000008022456,0.00004913235,0.00009147855,0.00006182468,0.0005073553],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99948263,0.00009439384,0.000027613904,0.00011527551,0.00021948609,0.00006052151],"domain_scores_gemma":[0.9993061,0.00035227265,0.000113792295,0.000050801744,0.00015321147,0.000023923032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041384145,0.0007592837,0.00045210076,0.0005928808,0.00037322164,0.0005474177,0.00038905846,0.00092766335,0.0019119667],"category_scores_gemma":[0.0011000297,0.00033418555,0.00022731195,0.00043012103,0.0003027147,0.0005340318,0.0003180696,0.00029640438,0.0003678809],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005492594,0.00007747842,0.0015576582,0.00016475834,0.000016850237,0.00007722422,0.000077692996,0.006661326,0.9408981,0.0004603169,0.00032572972,0.049133595],"study_design_scores_gemma":[0.00010095631,0.0006444821,0.018297711,0.00003678289,0.000054195425,0.0002545184,0.00012667685,0.19067067,0.78767914,0.00051805377,0.0015356849,0.000081143575],"about_ca_topic_score_codex":0.000644553,"about_ca_topic_score_gemma":0.0016234671,"teacher_disagreement_score":0.0019119667,"about_ca_system_score_codex":0.00025948015,"about_ca_system_score_gemma":0.00039274857,"threshold_uncertainty_score":0.0063961744},"labels":[],"label_agreement":null},{"id":"W4221133782","doi":"10.3390/s22062206","title":"Tool Condition Monitoring for High-Performance Machining Systems—A Review","year":2022,"lang":"en","type":"review","venue":"Sensors","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":144,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"","keywords":"Machining; Engineering; Computer science; Systems engineering; Mechanical engineering","score_opus":0.03409289144050574,"score_gpt":0.3079308721806382,"score_spread":0.27383798074013244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221133782","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024374494,0.9969313,0.0010064367,0.00011464598,0.00019610314,0.000014011271,0.000032840733,0.000016044603,0.0014447685],"genre_scores_gemma":[0.002143087,0.9955434,0.0012499056,0.00011378019,0.00018182056,0.000017112949,0.00006560251,0.0000048425172,0.0006804637],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995628,0.000057006175,0.00006082854,0.00009540577,0.00019754795,0.000026407308],"domain_scores_gemma":[0.99913836,0.0004807139,0.00010740933,0.000028318038,0.00022299476,0.000022130738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007543956,0.0011699783,0.0012820179,0.0025606735,0.00031325038,0.0010862139,0.0011976698,0.0012431081,0.0034045018],"category_scores_gemma":[0.0012241644,0.00052056886,0.00088806933,0.002997699,0.00036575246,0.0019657575,0.00060848927,0.00092818495,0.0017381485],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005023454,0.00008474601,0.0002753596,0.04020221,0.000114715935,0.00012017827,0.00006719016,0.0010980266,0.0035193698,0.0041744253,0.012184924,0.93810856],"study_design_scores_gemma":[0.000010883063,0.00027017304,0.0016989437,0.008668464,0.00033006052,0.0011579454,0.00011836566,0.0010347955,0.0033610722,0.0025061916,0.9807751,0.000068079105],"about_ca_topic_score_codex":0.00140834,"about_ca_topic_score_gemma":0.0014159482,"teacher_disagreement_score":0.0034045018,"about_ca_system_score_codex":0.0004065601,"about_ca_system_score_gemma":0.0011630091,"threshold_uncertainty_score":0.011389196},"labels":[],"label_agreement":null},{"id":"W4223643567","doi":"10.21203/rs.3.rs-1510190/v1","title":"Tool condition monitoring based on the fractal analysis of current and cutting force signals during CFRP trimming","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Trimming; Fractal; Current (fluid); Fractal analysis; Computer science; Acoustics; Engineering; Mechanical engineering; Fractal dimension; Mathematics; Physics; Electrical engineering; Mathematical analysis","score_opus":0.04698601898729434,"score_gpt":0.38913130448552596,"score_spread":0.34214528549823164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223643567","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9335516,0.00044497085,0.061993014,0.000056540626,0.00004214464,0.000031244657,0.00019402591,0.00048301753,0.0032033883],"genre_scores_gemma":[0.9958587,0.000034369015,0.0038241316,0.000006536691,0.000008158421,0.0000049435034,0.000037123118,0.0000117533045,0.00021429932],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987566,0.000011700206,0.000003926081,0.000033203218,0.000059049165,0.000016536245],"domain_scores_gemma":[0.999559,0.0001943058,0.00007075465,0.0000387671,0.00011059654,0.000026616428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001284202,0.00021558137,0.00022328625,0.0008287679,0.00018372886,0.00026509125,0.00022902209,0.00035440258,0.000977749],"category_scores_gemma":[0.00074015715,0.00010195258,0.0000946397,0.00041842178,0.00021136356,0.0003194526,0.00012464041,0.0002146019,0.00012802833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015844883,0.00013923478,0.019878436,0.00023853166,0.00003471057,0.00045437735,0.0005320646,0.01035671,0.72053665,0.0007778167,0.0011827666,0.24428427],"study_design_scores_gemma":[0.00004744117,0.0009409005,0.3197781,0.000080176826,0.00009018151,0.0013056778,0.0004151116,0.38728672,0.2852573,0.0014179556,0.0032838888,0.00009655044],"about_ca_topic_score_codex":0.0006806484,"about_ca_topic_score_gemma":0.0010187392,"teacher_disagreement_score":0.000977749,"about_ca_system_score_codex":0.00014329143,"about_ca_system_score_gemma":0.00009098007,"threshold_uncertainty_score":0.003270924},"labels":[],"label_agreement":null},{"id":"W4224076927","doi":"10.1016/j.rcim.2022.102354","title":"Estimating pose-dependent FRF in machining robots using multibody dynamics and Gaussian Process Regression","year":2022,"lang":"en","type":"article","venue":"Robotics and Computer-Integrated Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Dynamics (music); Machining; Regression; Gaussian process; Kriging; Process (computing); Regression analysis; Computer science; Gaussian; Multibody system; Mathematics; Control theory (sociology); Artificial intelligence; Engineering; Statistics; Psychology; Mechanical engineering; Physics; Classical mechanics","score_opus":0.00839039212873942,"score_gpt":0.24040850929194243,"score_spread":0.232018117163203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224076927","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048011888,0.0001885482,0.9511493,0.00005222116,0.000018614222,0.000009890984,0.000018370327,0.0002912843,0.0002598863],"genre_scores_gemma":[0.8287734,0.00032600417,0.16892171,0.00004697907,0.00004481329,0.00003165334,0.00013724157,0.00012380771,0.0015944224],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996706,0.00006772176,0.000010773955,0.000087855464,0.00012558447,0.000037420097],"domain_scores_gemma":[0.9992249,0.00042983211,0.0001141773,0.00007037628,0.00012955134,0.00003108974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068719295,0.00062445394,0.0007219428,0.0006115303,0.00027327603,0.00044886512,0.00062869414,0.0010151366,0.00038552276],"category_scores_gemma":[0.0027145052,0.00055411906,0.000565543,0.00055646,0.0005127129,0.0009624464,0.00054416084,0.0010995687,0.00027848672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012753777,0.00008459014,0.0026028166,0.00007129708,0.000056065026,0.00011024893,0.00013725582,0.8123071,0.028020343,0.0021046526,0.00064819015,0.15372987],"study_design_scores_gemma":[0.000002252791,0.000014591484,0.0011394577,0.00000203059,0.00000352849,0.00002004967,0.000005928922,0.9963097,0.0017424267,0.0006223325,0.00013140829,0.0000061273317],"about_ca_topic_score_codex":0.0044367085,"about_ca_topic_score_gemma":0.0046647773,"teacher_disagreement_score":0.0044367085,"about_ca_system_score_codex":0.00030800313,"about_ca_system_score_gemma":0.0005722997,"threshold_uncertainty_score":0.008821726},"labels":[],"label_agreement":null},{"id":"W4224981218","doi":"10.18280/mmep.090224","title":"Comparative Study of the Effect of Dry, Mineral Oil, and TiO2 Nano-Lubricant on Tool Wear During Face-Milling Machining of Ti-6al-4v-Eli Using Carbide Tool Insert","year":2022,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Johannesburg","keywords":"Machining; Materials science; Lubricant; Machinability; Tool wear; Metallurgy; Lubrication; Taguchi methods; Carbide; Titanium alloy; Cutting fluid; Composite material; Alloy","score_opus":0.015954317764210194,"score_gpt":0.22405929954392587,"score_spread":0.20810498177971568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224981218","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981433,0.0009406373,0.00060148933,0.000013876841,0.000012735794,0.000009012618,0.000044261844,0.000014281121,0.00022032578],"genre_scores_gemma":[0.99710876,0.00045332647,0.0016775241,0.00001663008,0.0000059409135,0.000011020719,0.00006416388,0.0000104937435,0.00065203913],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996375,0.000035022433,0.000041967163,0.00007079383,0.00015918787,0.000055481938],"domain_scores_gemma":[0.9993405,0.00024333173,0.00015007569,0.00004340363,0.00019054826,0.000032124335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031730667,0.0003097538,0.0005370222,0.00027948793,0.00022562277,0.00031771592,0.00031466197,0.00034504067,0.0006504922],"category_scores_gemma":[0.0006479831,0.00017854723,0.00043504004,0.00024874232,0.00020437651,0.0004088875,0.00017342455,0.00034503307,0.0001051639],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007576355,0.00011642285,0.0016656109,0.00041376066,0.00002376799,0.00014508043,0.00024335545,0.00045574745,0.98528856,0.000029759814,0.00006178632,0.010798514],"study_design_scores_gemma":[0.000015408903,0.002560505,0.015278883,0.000015731828,0.00006422973,0.00013718633,0.00024809467,0.0024165933,0.9782516,0.000022863844,0.0009661188,0.00002275365],"about_ca_topic_score_codex":0.0005715145,"about_ca_topic_score_gemma":0.0018621703,"teacher_disagreement_score":0.0006504922,"about_ca_system_score_codex":0.00013892436,"about_ca_system_score_gemma":0.00011188842,"threshold_uncertainty_score":0.002176106},"labels":[],"label_agreement":null},{"id":"W4225129498","doi":"10.1016/j.matpr.2022.04.558","title":"Modeling residual stresses in hard turning with self-propelled rotary tools","year":2022,"lang":"en","type":"article","venue":"Materials Today Proceedings","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"National Plan for Science, Technology and Innovation; King Abdulaziz City for Science and Technology","keywords":"Residual stress; Materials science; Residual; Finite element method; Displacement (psychology); Mechanics; Structural engineering; Mechanical engineering; Composite material; Engineering; Mathematics; Physics; Algorithm","score_opus":0.011185406980020036,"score_gpt":0.1977251612688842,"score_spread":0.18653975428886416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225129498","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.895034,0.00047070332,0.09165118,0.00014840161,0.00007638222,0.000046302055,0.000097069424,0.00028885598,0.01218702],"genre_scores_gemma":[0.99532473,0.000060386414,0.003042678,0.000008386185,0.000004877574,0.000010530056,0.00002630209,0.000030786177,0.001491329],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986136,0.000021287786,0.000004895387,0.000019359657,0.00004858475,0.000044461925],"domain_scores_gemma":[0.9996489,0.00017602368,0.000048173537,0.000028293141,0.00006571443,0.000032956304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028953244,0.00047882003,0.0005566632,0.00046449451,0.00032702324,0.00086407986,0.0009835557,0.0010750382,0.0013707327],"category_scores_gemma":[0.0008705254,0.0004980787,0.00060517696,0.00026734793,0.00073648745,0.00040205917,0.0003793842,0.00044131774,0.00015028456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038971168,0.000026590984,0.0004131218,0.000014784256,0.000007343795,0.000051420262,0.000020832784,0.99503666,0.0017410561,0.00076879276,0.000058898888,0.0018214808],"study_design_scores_gemma":[0.0000055742557,0.00001933679,0.00019872097,0.0000018610511,0.0000025352088,0.000005800711,0.000008865017,0.9991548,0.00036007955,0.00016907552,0.00007041391,0.0000029047994],"about_ca_topic_score_codex":0.012374742,"about_ca_topic_score_gemma":0.011067509,"teacher_disagreement_score":0.012374742,"about_ca_system_score_codex":0.00051965937,"about_ca_system_score_gemma":0.00083604694,"threshold_uncertainty_score":0.024605393},"labels":[],"label_agreement":null},{"id":"W4225159762","doi":"10.1016/j.cirpj.2022.04.009","title":"Monitoring of in-process force coefficients and tool wear","year":2022,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dynamometer; Machining; Mechanical engineering; Shear force; Enhanced Data Rates for GSM Evolution; Tool wear; Process (computing); Resultant force; Milling cutter; Shearing (physics); Materials science; Engineering; Computer science; Structural engineering; Physics; Composite material; Classical mechanics","score_opus":0.005379097270662246,"score_gpt":0.23523244493386908,"score_spread":0.22985334766320684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225159762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98828876,0.00022924728,0.009381983,0.000028585038,0.00002218099,0.00002824754,0.00035692475,0.00025584092,0.001408256],"genre_scores_gemma":[0.99642426,0.000077921424,0.0020778493,0.000012424817,0.0000080842265,0.000011764914,0.00014620235,0.00003060438,0.0012108857],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996277,0.000031606796,0.000012893494,0.000069273214,0.00020726377,0.000051238163],"domain_scores_gemma":[0.998558,0.0005528801,0.00027937198,0.00014974325,0.00037605638,0.00008396127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002260862,0.00053925446,0.0004068286,0.0009346482,0.00029855446,0.00039877434,0.00047857797,0.00064431323,0.0017392641],"category_scores_gemma":[0.0011238086,0.000240241,0.00017703795,0.0005435093,0.00018791761,0.00044002893,0.00020344074,0.00044493587,0.00033064347],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011993194,0.00030643438,0.02607841,0.00017868468,0.000049737813,0.00022887577,0.0002030405,0.0020016155,0.937579,0.00008113511,0.00042106374,0.031672783],"study_design_scores_gemma":[0.000030678162,0.0012346457,0.19312176,0.000019488498,0.000073154624,0.0006227229,0.00015693916,0.032380044,0.77078295,0.00010319526,0.001427767,0.00004666864],"about_ca_topic_score_codex":0.0011323796,"about_ca_topic_score_gemma":0.00193559,"teacher_disagreement_score":0.0017392641,"about_ca_system_score_codex":0.00019525106,"about_ca_system_score_gemma":0.00019043092,"threshold_uncertainty_score":0.0058184266},"labels":[],"label_agreement":null},{"id":"W4225248428","doi":"10.3390/machines10050331","title":"Modeling and Predicting the Machined Surface Roughness and Milling Power in Scot’s Pine Helical Milling Process","year":2022,"lang":"en","type":"article","venue":"Machines","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Rotational speed; Rotation (mathematics); Machinability; Machining; Materials science; Surface roughness; Power (physics); Mechanical engineering; Response surface methodology; Surface finish; Process (computing); Engineering drawing; Composite material; Geometry; Metallurgy; Mathematics; Engineering; Computer science; Statistics; Physics","score_opus":0.00708393471346402,"score_gpt":0.23035120925972674,"score_spread":0.22326727454626272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225248428","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.913772,0.0009247895,0.081885576,0.000087227396,0.000028743261,0.000100720245,0.00044908974,0.00035917482,0.0023925975],"genre_scores_gemma":[0.99087006,0.00030247404,0.007847803,0.000011124866,0.0000033552994,0.000057047462,0.0001551181,0.00001594062,0.00073703664],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972373,0.000032511656,0.000019850719,0.00006748372,0.00011106466,0.0000453187],"domain_scores_gemma":[0.9996711,0.00017275136,0.0000586251,0.000015666576,0.000071767965,0.0000101537225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005461403,0.00066832674,0.0005635373,0.00053679215,0.0002201359,0.00088229607,0.00051823456,0.00072540453,0.00052691204],"category_scores_gemma":[0.0006370774,0.00041132918,0.00089355925,0.000558312,0.00022946885,0.00033649665,0.00020998939,0.00039982933,0.0001608351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013573663,0.00013092412,0.008766872,0.00028425432,0.000036049456,0.0001953331,0.00005922022,0.94053066,0.034861624,0.0001676568,0.0001866724,0.014645038],"study_design_scores_gemma":[0.000007839545,0.00015341993,0.004901417,0.0000054640127,0.000019746107,0.000020403404,0.000027117027,0.9867691,0.007834975,0.00006995951,0.00017726894,0.000013305978],"about_ca_topic_score_codex":0.019699628,"about_ca_topic_score_gemma":0.017518263,"teacher_disagreement_score":0.019699628,"about_ca_system_score_codex":0.0005818767,"about_ca_system_score_gemma":0.0007141274,"threshold_uncertainty_score":0.039169908},"labels":[],"label_agreement":null},{"id":"W4226216888","doi":"10.3103/s1068366621060118","title":"Influence of Cutting Conditions on the Wear Resistance of Tools with a TiB2 Coating during Titanium Alloy Machining","year":2021,"lang":"en","type":"article","venue":"Journal of Friction and Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Materials science; Machining; Coating; Metallurgy; Alloy; Titanium alloy; Carbide; Lubricant; Titanium; Wear resistance; Cutting tool; Composite material","score_opus":0.007180012711833746,"score_gpt":0.21622136022467642,"score_spread":0.20904134751284267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226216888","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987795,0.0004951543,0.0004766441,0.0000072483167,0.000008039124,0.000006607029,0.00004933577,0.000020143203,0.00015734237],"genre_scores_gemma":[0.9988059,0.00012930771,0.000745222,0.0000069256507,0.0000041391563,0.000005819082,0.00007680108,0.000019116154,0.00020674746],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99945027,0.00006374533,0.000055999408,0.00011473469,0.00016764124,0.00014760184],"domain_scores_gemma":[0.99870896,0.00061074446,0.00019941179,0.00014070411,0.00027544142,0.00006470035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044083482,0.00043443067,0.00075183524,0.00046572663,0.00036205724,0.0006112628,0.00034878394,0.0005568999,0.0008121197],"category_scores_gemma":[0.0017936254,0.00029835556,0.00038909298,0.00032158458,0.0002934268,0.00035058262,0.00023362407,0.00035615484,0.00018796063],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009746541,0.000036329446,0.0025289997,0.00018257553,0.00003519395,0.00016504632,0.00027983208,0.00062219077,0.9883887,0.000015470952,0.000036685684,0.0067343744],"study_design_scores_gemma":[0.000023341117,0.0015321559,0.038187917,0.000015462681,0.000065721244,0.00030372743,0.0002579944,0.002549573,0.95626247,0.000030076242,0.00073550316,0.00003586681],"about_ca_topic_score_codex":0.0009155702,"about_ca_topic_score_gemma":0.0014894854,"teacher_disagreement_score":0.0009155702,"about_ca_system_score_codex":0.0001863716,"about_ca_system_score_gemma":0.00015492372,"threshold_uncertainty_score":0.0027167797},"labels":[],"label_agreement":null},{"id":"W4229373731","doi":"10.1115/1.4054516","title":"Condition Monitoring of Machine Tool Feed Drives: A Review","year":2022,"lang":"en","type":"review","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Prognostics; Machine tool; Condition monitoring; Engineering; Manufacturing engineering; Control engineering; Computer science; Mechanical engineering; Reliability engineering","score_opus":0.016845274504200827,"score_gpt":0.2812050029410736,"score_spread":0.2643597284368728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229373731","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00025919254,0.99836963,0.00036885493,0.00009407497,0.00010670211,0.0000075344883,0.000032505235,0.000013338672,0.000748113],"genre_scores_gemma":[0.0020013852,0.99663514,0.0005247456,0.00009243141,0.000115878145,0.00000921251,0.00006838414,0.0000031491973,0.00054966577],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99958783,0.000043962165,0.000062730505,0.00009718142,0.00018164644,0.000026743248],"domain_scores_gemma":[0.99914837,0.00040226118,0.00012857291,0.00002154135,0.0002663536,0.00003293836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007726188,0.0009960956,0.0014253149,0.0029842374,0.00024667956,0.00112064,0.0012507966,0.0010241917,0.0036598498],"category_scores_gemma":[0.0013477306,0.0004086461,0.0007962685,0.002889511,0.0002918115,0.001530923,0.0005656697,0.00082262227,0.0015975176],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007480363,0.00008860427,0.0003373583,0.049412325,0.00012828218,0.0001576574,0.000067675806,0.0008660822,0.002360455,0.0021253082,0.014164398,0.930217],"study_design_scores_gemma":[0.000016538208,0.00029625767,0.0024661787,0.016568433,0.00046047702,0.0016181824,0.00012692196,0.0006396194,0.002356189,0.0018175055,0.9735744,0.000059327074],"about_ca_topic_score_codex":0.0013554255,"about_ca_topic_score_gemma":0.0013405585,"teacher_disagreement_score":0.0036598498,"about_ca_system_score_codex":0.00038347632,"about_ca_system_score_gemma":0.0011226727,"threshold_uncertainty_score":0.01224339},"labels":[],"label_agreement":null},{"id":"W4229374126","doi":"10.3390/ma15093369","title":"A Numerical Model for Predicting the Effect of Tool Nose Radius on Machining Process Performance during Orthogonal Cutting of AISI 1045 Steel","year":2022,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Canadian Bureau for International Education","keywords":"RADIUS; Machining; Rake angle; Materials science; Flank; Tool wear; Finite element method; Cutting tool; Structural engineering; Mechanical engineering; Composite material; Engineering; Metallurgy; Computer science","score_opus":0.005660541957711271,"score_gpt":0.23034201548136682,"score_spread":0.22468147352365556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229374126","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3409578,0.0003601352,0.6507999,0.00009491402,0.000054684002,0.00014172852,0.00023472794,0.0008337481,0.0065223784],"genre_scores_gemma":[0.9482652,0.00019485806,0.04941253,0.000017439539,0.0000068935624,0.00011474478,0.00015429234,0.00005618102,0.001777919],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998497,0.00002494368,0.000011436702,0.000022960838,0.0000733302,0.000017705372],"domain_scores_gemma":[0.9995894,0.00020506521,0.00007440148,0.000045936984,0.00007061006,0.000014601605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003913676,0.00043106038,0.00038180986,0.0003004937,0.0002654028,0.00035364451,0.00053455785,0.0008078218,0.0007923171],"category_scores_gemma":[0.0011835847,0.00029865498,0.0004745556,0.00021745483,0.0002909287,0.00031638442,0.00018739424,0.0002931623,0.00022709987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026212365,0.000021090991,0.000858785,0.000030735333,0.000006426558,0.00003254286,0.000021420776,0.9791901,0.013933204,0.0003428578,0.00006517942,0.0054713488],"study_design_scores_gemma":[0.000003356438,0.000026010372,0.00039867492,0.0000019693862,0.0000039819292,0.000013879635,0.000002978382,0.99752,0.001787232,0.00006138284,0.00017714128,0.0000032095143],"about_ca_topic_score_codex":0.0046540983,"about_ca_topic_score_gemma":0.003816261,"teacher_disagreement_score":0.0046540983,"about_ca_system_score_codex":0.000435632,"about_ca_system_score_gemma":0.0006782661,"threshold_uncertainty_score":0.009254038},"labels":[],"label_agreement":null},{"id":"W4229449139","doi":"10.1016/j.ymssp.2022.109245","title":"Dynamics identification and stability analysis in turning of slender workpieces with flexible boundary constraints","year":2022,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Science Challenge Project; National Natural Science Foundation of China; Société Canadienne de Pédiatrie","keywords":"Stiffness; Stability (learning theory); Boundary (topology); Engineering; Boundary value problem; Cantilever; Control theory (sociology); Structural engineering; Position (finance); Mathematics; Computer science; Mathematical analysis; Artificial intelligence","score_opus":0.010148322321942821,"score_gpt":0.22584753768960342,"score_spread":0.2156992153676606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229449139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5256383,0.0005360333,0.4677145,0.0001563185,0.000042001597,0.000028720693,0.000040729727,0.0001247839,0.0057186726],"genre_scores_gemma":[0.9944133,0.00006676613,0.0045362385,0.0000069017387,0.0000050308613,0.000011414813,0.000021495725,0.000011818247,0.0009271721],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99984753,0.000041546256,0.000005698238,0.00003658153,0.00004325734,0.000025373258],"domain_scores_gemma":[0.99943453,0.00035850337,0.00007096404,0.00003151254,0.00008441305,0.000019979841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036683254,0.0003701113,0.00064051687,0.00045865335,0.00041420854,0.0006952384,0.00047189713,0.00060213916,0.0010382294],"category_scores_gemma":[0.0012459375,0.00033451675,0.0005731163,0.00025340656,0.0007283221,0.0004474773,0.00064505264,0.00044248582,0.00011217355],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030400057,0.000039119393,0.0018843047,0.0001437078,0.00005377158,0.00029069526,0.00026446834,0.92132074,0.042352553,0.0085982075,0.00032588368,0.02442265],"study_design_scores_gemma":[0.000003861503,0.000031202097,0.000867941,0.0000040601767,0.00000506771,0.000020332971,0.000028898783,0.9964631,0.0017171365,0.0007455373,0.00010764884,0.000005253332],"about_ca_topic_score_codex":0.0040543377,"about_ca_topic_score_gemma":0.002417098,"teacher_disagreement_score":0.0040543377,"about_ca_system_score_codex":0.00034437387,"about_ca_system_score_gemma":0.0003370958,"threshold_uncertainty_score":0.008061469},"labels":[],"label_agreement":null},{"id":"W4229783720","doi":"10.1115/1.4024959","title":"Modeling of Abradable Coating Removal in Aircraft Engines Through Delay Differential Equations","year":2013,"lang":"en","type":"article","venue":"Journal of Engineering for Gas Turbines and Power","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Office National d'études et de Recherches Aérospatiales; Safran; Centre National de la Recherche Scientifique","keywords":"Materials science; Turbomachinery; Vibration; Coating; Machining; Turbine; Instability; Stability (learning theory); Turbine blade; Mechanics; Computer science; Mechanical engineering; Composite material; Acoustics; Physics; Metallurgy; Engineering","score_opus":0.009196500978069752,"score_gpt":0.22391861678927047,"score_spread":0.2147221158112007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229783720","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09695662,0.0011111519,0.8809394,0.0004379882,0.00012368725,0.00012108375,0.00033351636,0.00033002882,0.019646518],"genre_scores_gemma":[0.9421168,0.0010945041,0.03392296,0.00010110521,0.00004679953,0.00029231972,0.00024158353,0.000102054175,0.02208185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983895,0.00003398939,0.000009084403,0.000031529748,0.000055490367,0.00003088722],"domain_scores_gemma":[0.9997652,0.00010794821,0.00004679476,0.000009676069,0.00005115063,0.000019138328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003560606,0.00086980325,0.00073220505,0.00051096245,0.0004921148,0.001025229,0.0012482413,0.0015782019,0.001821861],"category_scores_gemma":[0.0007428947,0.00046279322,0.00069815683,0.00036499766,0.00077133,0.0007429906,0.00077406404,0.00079996244,0.0002905772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019390594,0.00001669108,0.00041750466,0.000044771663,0.000009448816,0.00010795307,0.00005559784,0.9856435,0.0029800418,0.008602593,0.00016282155,0.0019396072],"study_design_scores_gemma":[0.0000029856803,0.000005546286,0.00004760639,0.0000021627854,0.000002040563,0.000007446792,0.000004641283,0.99870074,0.00021102505,0.00072136184,0.0002917107,0.0000026728599],"about_ca_topic_score_codex":0.01708459,"about_ca_topic_score_gemma":0.0076051787,"teacher_disagreement_score":0.01708459,"about_ca_system_score_codex":0.001059042,"about_ca_system_score_gemma":0.0012484238,"threshold_uncertainty_score":0.033970296},"labels":[],"label_agreement":null},{"id":"W4230109161","doi":"10.1007/978-3-662-53120-4_300447","title":"Milling Machine","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Materials science; Computer science","score_opus":0.00724100372243257,"score_gpt":0.18874241527282384,"score_spread":0.18150141155039126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230109161","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032100314,0.0042890087,0.09269794,0.0003723959,0.0010358082,0.00022992367,0.0017541335,0.004644132,0.89176655],"genre_scores_gemma":[0.020018447,0.0028077052,0.034548055,0.00032647865,0.00018099377,0.00011019826,0.0031627964,0.0005367493,0.93830854],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994072,0.000015397338,0.000018070352,0.00012241464,0.00039736019,0.000039542527],"domain_scores_gemma":[0.9998313,0.000022968388,0.000010413681,0.000036731326,0.00008412093,0.000014494313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023878792,0.0009347172,0.0009763728,0.0020345324,0.0011049323,0.0015364044,0.0011068175,0.0009444323,0.15523744],"category_scores_gemma":[0.00035678098,0.00049119716,0.0004153116,0.001857653,0.00038762408,0.001453584,0.0010448045,0.001600603,0.07639726],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001022355,0.00008271107,0.00015658725,0.00048545422,0.000009386807,0.00014214583,0.00009017864,0.0011938353,0.028377714,0.032686662,0.15064122,0.78603184],"study_design_scores_gemma":[0.000012800113,0.00007010362,0.00063566427,0.00006735,0.000011989302,0.00046149455,0.000022139804,0.0017174857,0.011305242,0.0041166306,0.9815607,0.000018309333],"about_ca_topic_score_codex":0.0006215572,"about_ca_topic_score_gemma":0.0016244644,"teacher_disagreement_score":0.15523744,"about_ca_system_score_codex":0.00039590907,"about_ca_system_score_gemma":0.0006120104,"threshold_uncertainty_score":0.51932096},"labels":[],"label_agreement":null},{"id":"W4230879773","doi":"10.1177/0954405411408499","title":"The extension of a simple predictive model for orthogonal cutting to include flow below the cutting edge","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Chamfer (geometry); Enhanced Data Rates for GSM Evolution; Rake angle; Flow (mathematics); Hydrostatic equilibrium; Flank; Moment (physics); Deformation (meteorology); Mechanics; Geometry; Machining; Geology; Computer science; Mathematics; Engineering; Mechanical engineering; Physics","score_opus":0.01559980169912914,"score_gpt":0.22019785353804763,"score_spread":0.2045980518389185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230879773","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015179561,0.00017943623,0.97618854,0.00021106833,0.00010323867,0.00009588714,0.00020342738,0.0003614068,0.0074774404],"genre_scores_gemma":[0.81660515,0.0011195162,0.15204917,0.00029984931,0.00019562377,0.0010326601,0.0005201943,0.00036715157,0.027810661],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981314,0.000026474574,0.000007607622,0.0000449193,0.0000734507,0.000034425386],"domain_scores_gemma":[0.9996481,0.00016765331,0.000048164948,0.000038944614,0.000070581285,0.00002659779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005796493,0.00085775973,0.0011091988,0.00041352576,0.00060856726,0.001171947,0.002387239,0.0018650176,0.0046111215],"category_scores_gemma":[0.0012643937,0.00065766374,0.0011371202,0.00051226496,0.0007597708,0.001098438,0.0007847232,0.0015350211,0.0007656239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008595315,0.000017779412,0.00018165931,0.000021897224,0.0000053281087,0.000036070618,0.0000123546115,0.9898553,0.0008216097,0.005027803,0.00022727391,0.00378425],"study_design_scores_gemma":[0.0000027115293,0.000007503005,0.000050645547,0.000002138664,0.0000026320674,0.0000075529647,0.0000016610535,0.9980709,0.00010095717,0.0013096734,0.00044003694,0.0000036917402],"about_ca_topic_score_codex":0.011566711,"about_ca_topic_score_gemma":0.0061368095,"teacher_disagreement_score":0.011566711,"about_ca_system_score_codex":0.00081299385,"about_ca_system_score_gemma":0.0015815218,"threshold_uncertainty_score":0.02299875},"labels":[],"label_agreement":null},{"id":"W4232352807","doi":"10.1007/978-3-662-53120-4_300297","title":"Hard Milling","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Materials science","score_opus":0.01121417673548356,"score_gpt":0.19356648080314526,"score_spread":0.1823523040676617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232352807","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019907823,0.005333763,0.039436385,0.00036976387,0.0012901216,0.000091097936,0.00045763497,0.0011923825,0.949838],"genre_scores_gemma":[0.005324985,0.0017733944,0.0069876458,0.00015058722,0.00010016158,0.000023520603,0.00037633395,0.00024940714,0.985014],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999564,0.000013825911,0.000013504423,0.00009016056,0.00028378709,0.000034718876],"domain_scores_gemma":[0.99984086,0.000026883617,0.00000879663,0.000045117697,0.00006290023,0.000015364774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020726441,0.0012403848,0.000697544,0.0018928006,0.0012397103,0.0027857544,0.0010612326,0.00075558305,0.16579546],"category_scores_gemma":[0.00042870815,0.00057197385,0.00042828012,0.0018606014,0.000729843,0.0014783512,0.0016389162,0.0019115984,0.067908846],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007225208,0.000049890485,0.00009401482,0.00045958394,0.000008669003,0.00009605441,0.00015250946,0.0010980272,0.015805125,0.04938511,0.15386248,0.77891624],"study_design_scores_gemma":[0.0000055032338,0.000029444062,0.00040864205,0.00008063792,0.000005148004,0.0002062607,0.000043494594,0.0008129228,0.006415891,0.010226067,0.98175263,0.000013243058],"about_ca_topic_score_codex":0.0010264736,"about_ca_topic_score_gemma":0.0039097155,"teacher_disagreement_score":0.16579546,"about_ca_system_score_codex":0.0006447198,"about_ca_system_score_gemma":0.0006500364,"threshold_uncertainty_score":0.55464107},"labels":[],"label_agreement":null},{"id":"W4233395246","doi":"10.1007/978-3-662-53120-4_300365","title":"Laser-Assisted Turning","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Laser; Optics; Physics","score_opus":0.009774469892175366,"score_gpt":0.20561249736495385,"score_spread":0.19583802747277848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233395246","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035909328,0.018459428,0.028844148,0.00023321061,0.0014121723,0.000039110797,0.00013111444,0.0005279968,0.9467619],"genre_scores_gemma":[0.029324377,0.010874908,0.009398908,0.00017629443,0.00019664646,0.000033405307,0.00026099765,0.00016707911,0.9495673],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998404,0.000008545372,0.0000028215438,0.000029458866,0.00009931944,0.00001947883],"domain_scores_gemma":[0.9999701,0.0000066908055,0.0000020351,0.0000075668463,0.000010078025,0.000003484999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007462451,0.0006316539,0.00039382404,0.0008548599,0.00058758556,0.0012143824,0.0005363099,0.00058929814,0.027686426],"category_scores_gemma":[0.0001011363,0.000312798,0.00031670462,0.00077193254,0.00048218647,0.0007827712,0.0008655665,0.0010476855,0.012928241],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053853386,0.00006416122,0.000080208796,0.00042848295,0.000013582679,0.00014650573,0.00015699553,0.0035236431,0.03142143,0.15334669,0.10042005,0.71034443],"study_design_scores_gemma":[0.00000473111,0.000055504228,0.00045420392,0.00012296044,0.0000071837085,0.0005161051,0.000048777947,0.003020644,0.013637987,0.01889592,0.9632161,0.000019839283],"about_ca_topic_score_codex":0.00059802976,"about_ca_topic_score_gemma":0.0020522694,"teacher_disagreement_score":0.027686426,"about_ca_system_score_codex":0.0004720661,"about_ca_system_score_gemma":0.00032020698,"threshold_uncertainty_score":0.09262031},"labels":[],"label_agreement":null},{"id":"W4233909213","doi":"10.1007/978-3-642-20617-7_100499","title":"Ultrasonic-Assisted Turning","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Ultrasonic sensor; Materials science; Acoustics; Physics","score_opus":0.009045011723283425,"score_gpt":0.20494808425730737,"score_spread":0.19590307253402395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233909213","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010163033,0.039417956,0.10608345,0.0003950022,0.0023097154,0.0000715684,0.00015870058,0.0010850152,0.84031564],"genre_scores_gemma":[0.102504514,0.021573197,0.033243064,0.00038252005,0.00048151874,0.00007956899,0.0004901945,0.0003328735,0.8409125],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975747,0.000013873076,0.0000047909416,0.00004082317,0.00015224153,0.000030933694],"domain_scores_gemma":[0.9999565,0.000011185012,0.0000032392618,0.00000972071,0.000014993388,0.0000043517093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010097836,0.000706656,0.00046936248,0.0008144978,0.00041541696,0.0009182167,0.0006675145,0.00065687,0.015570641],"category_scores_gemma":[0.00014735026,0.00037681602,0.0003105892,0.0006516001,0.0005434769,0.0007511535,0.0009592737,0.0011601908,0.0077165514],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008055171,0.000072237905,0.0001227556,0.0005878092,0.00001960218,0.00016411906,0.00021843998,0.003472693,0.08768938,0.089652985,0.05406339,0.763856],"study_design_scores_gemma":[0.000011202094,0.0001373492,0.00084734155,0.00018484525,0.000018400006,0.00091211725,0.000109493274,0.006343339,0.05924119,0.015853455,0.9162984,0.00004303919],"about_ca_topic_score_codex":0.00043235853,"about_ca_topic_score_gemma":0.0013767987,"teacher_disagreement_score":0.015570641,"about_ca_system_score_codex":0.000446413,"about_ca_system_score_gemma":0.00030018162,"threshold_uncertainty_score":0.052088976},"labels":[],"label_agreement":null},{"id":"W4234101909","doi":"10.1177/0014485103043001007","title":"Three-Dimensional Stress-Relief Displacements from Blind-Hole Drilling: A Parametric Description","year":2003,"lang":"en","type":"article","venue":"Experimental Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Hole drilling method; RADIUS; Drilling; Solid mechanics; Stress (linguistics); Strain gauge; Parametric statistics; Displacement (psychology); Deep hole drilling; Position (finance); Geometry; Optics; Mechanics; Mathematics; Physics; Materials science; Structural engineering; Engineering; Statistics; Computer science","score_opus":0.019374263082270877,"score_gpt":0.2502320581980931,"score_spread":0.2308577951158222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234101909","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27637964,0.00082310283,0.70199543,0.00050805934,0.000085995656,0.00020869194,0.0004402715,0.0003887651,0.01917006],"genre_scores_gemma":[0.97272766,0.00025916795,0.024246633,0.000030432888,0.000017833812,0.000072963914,0.00008185189,0.00003674287,0.0025266379],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997106,0.000051466868,0.00001765506,0.000035916506,0.0001538401,0.000030447545],"domain_scores_gemma":[0.99958104,0.00023141778,0.00005549108,0.00007547585,0.000042416075,0.000014083375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063511677,0.00045575533,0.00049842114,0.00033595157,0.00041814125,0.0008420163,0.00138146,0.001487992,0.0018072322],"category_scores_gemma":[0.0018755775,0.00046097222,0.0005051264,0.00056087004,0.0015406103,0.0012715716,0.00085621513,0.0007033314,0.00018792962],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000148786,0.00012790781,0.0015170963,0.0003216795,0.000016279138,0.00038191024,0.0004026961,0.88013446,0.040774412,0.053014394,0.00049884093,0.022661615],"study_design_scores_gemma":[0.000015002485,0.000062858686,0.0008781005,0.000010018008,0.0000055652044,0.00021719543,0.000038960865,0.9875143,0.005413694,0.0049538356,0.00086413976,0.000026370539],"about_ca_topic_score_codex":0.0007499551,"about_ca_topic_score_gemma":0.00097502937,"teacher_disagreement_score":0.0018072322,"about_ca_system_score_codex":0.0002535675,"about_ca_system_score_gemma":0.00046948707,"threshold_uncertainty_score":0.0060458183},"labels":[],"label_agreement":null},{"id":"W4234296256","doi":"10.32920/14639913.v1","title":"Effects of Machine Tool Spindle Decay on the Stability Lobe Diagram: An Analytical-Experimental Study","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machine tool; Natural frequency; Vibration; Machining; Stability (learning theory); Stiffness; Finite element method; Modal analysis; Boundary (topology); Control theory (sociology); Diagram; Modal; Structural engineering; Engineering; Computer science; Mechanical engineering; Acoustics; Physics; Mathematical analysis; Mathematics; Materials science","score_opus":0.018299161779270375,"score_gpt":0.28669542021790045,"score_spread":0.2683962584386301,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234296256","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9763406,0.00023812718,0.02191345,0.0000386024,0.000018896848,0.00004678733,0.00013749658,0.00020288843,0.0010631637],"genre_scores_gemma":[0.99778384,0.000045902572,0.0017328896,0.0000071440327,0.0000020515563,0.000015655172,0.000042823624,0.000022476257,0.00034722898],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990128,0.00014285842,0.000065051085,0.00021108313,0.0004353067,0.00013286846],"domain_scores_gemma":[0.9953876,0.0023332464,0.0005762308,0.0006093784,0.0009543465,0.00013919636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00138998,0.00043585364,0.00056570553,0.0004555041,0.00035742184,0.0004287376,0.00056675496,0.0006028891,0.0021058817],"category_scores_gemma":[0.0047916165,0.0003060945,0.00033931877,0.0004701517,0.000883271,0.0004794503,0.0005469598,0.0006971223,0.0004034323],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002044098,0.00050870277,0.005297777,0.0005136003,0.000019190295,0.00042656163,0.0010616262,0.014153721,0.9460319,0.0005472505,0.00032250944,0.029073086],"study_design_scores_gemma":[0.00006246762,0.0048010554,0.029416446,0.000064050735,0.000037863345,0.000455473,0.0004036221,0.10921304,0.8529335,0.0003120918,0.0022325467,0.00006790929],"about_ca_topic_score_codex":0.00061169645,"about_ca_topic_score_gemma":0.00070738484,"teacher_disagreement_score":0.0021058817,"about_ca_system_score_codex":0.00032551528,"about_ca_system_score_gemma":0.00021079903,"threshold_uncertainty_score":0.0073509812},"labels":[],"label_agreement":null},{"id":"W4234440451","doi":"10.32920/ryerson.14645091","title":"Drilling Burr Formation With Tool Wear","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Drilling; Drill; Machining; Shearing (physics); Mechanical engineering; Enhanced Data Rates for GSM Evolution; Engineering; Thrust; Cutting tool; Geotechnical engineering","score_opus":0.006439948117775516,"score_gpt":0.1979511221722905,"score_spread":0.19151117405451498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234440451","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2876345,0.001910502,0.6906027,0.00034909247,0.00014631856,0.00026456124,0.0002609162,0.00055966584,0.018271755],"genre_scores_gemma":[0.9784137,0.0005415826,0.014891874,0.000034903842,0.000014646805,0.000075012555,0.00007441504,0.000034837733,0.0059189927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995505,0.000078815116,0.000027481,0.00012334443,0.00015832348,0.000061444414],"domain_scores_gemma":[0.99891794,0.00041058104,0.00032289771,0.00015399836,0.00015728676,0.000037230908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063580537,0.00082587305,0.00069699617,0.0005307604,0.00025837912,0.0012421984,0.0013453433,0.0014335063,0.0010680768],"category_scores_gemma":[0.0018912265,0.0006162837,0.0013170907,0.00031425155,0.00092377147,0.0014970667,0.0009200848,0.0007661537,0.00020757016],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038822738,0.000040202252,0.0014007158,0.00012381654,0.000016674014,0.00021987723,0.00013661005,0.9750019,0.009192179,0.006280674,0.00018539991,0.0073630796],"study_design_scores_gemma":[0.000015295065,0.000073496936,0.0006869448,0.000010931609,0.000013414614,0.0001415162,0.000024580293,0.99453706,0.0017542854,0.001864962,0.00086280546,0.0000146888215],"about_ca_topic_score_codex":0.0048317895,"about_ca_topic_score_gemma":0.002731932,"teacher_disagreement_score":0.0048317895,"about_ca_system_score_codex":0.00054501655,"about_ca_system_score_gemma":0.00060299144,"threshold_uncertainty_score":0.009607315},"labels":[],"label_agreement":null},{"id":"W4234807974","doi":"10.32920/ryerson.14652987","title":"Predictive modeling of surface finish in fine grinding","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Grinding; Materials science; Surface roughness; Ellipsoid; Surface (topology); Enhanced Data Rates for GSM Evolution; Surface finish; Process (computing); Chip; Mechanical engineering; Consistency (knowledge bases); Engineering drawing; Metallurgy; Computer science; Composite material; Geometry; Engineering; Mathematics; Physics; Artificial intelligence","score_opus":0.013846438379005987,"score_gpt":0.2371927901630209,"score_spread":0.2233463517840149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234807974","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41593295,0.0005326641,0.572231,0.00025503515,0.00006140658,0.00010038971,0.00038196615,0.00074333325,0.009761273],"genre_scores_gemma":[0.9859658,0.00019593089,0.0105207935,0.000015767626,0.000008732576,0.00005782103,0.00014603374,0.000048350645,0.003040851],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997999,0.000029781188,0.000006534271,0.000046555437,0.000079959646,0.00003721662],"domain_scores_gemma":[0.9995678,0.0002568739,0.000056807774,0.000032220545,0.00006895027,0.000017274759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044019736,0.00042912606,0.00073020684,0.00035533175,0.0002746853,0.00085270515,0.000821854,0.0008045462,0.0011953822],"category_scores_gemma":[0.0011420829,0.00050604035,0.0006815562,0.0003335092,0.0006066773,0.0005088722,0.00038729073,0.00067691255,0.00020605496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004327863,0.0000042060406,0.00012278286,0.0000038274893,0.0000016613469,0.00000725396,0.0000040034356,0.9984301,0.000361927,0.0002869261,0.000022097931,0.00075094606],"study_design_scores_gemma":[6.539187e-7,0.000002618033,0.000067769615,3.9281827e-7,4.3570014e-7,8.843133e-7,7.156499e-7,0.99971515,0.00007340156,0.00011020277,0.00002701199,7.829726e-7],"about_ca_topic_score_codex":0.017586289,"about_ca_topic_score_gemma":0.008880815,"teacher_disagreement_score":0.017586289,"about_ca_system_score_codex":0.0008432174,"about_ca_system_score_gemma":0.0006945474,"threshold_uncertainty_score":0.03496784},"labels":[],"label_agreement":null},{"id":"W4234886136","doi":"10.3390/jmmp5020050","title":"The Effect of MQL on Tool Wear Progression in Low-Frequency Vibration-Assisted Drilling of CFRP/Ti6Al4V Stack Material","year":2021,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; National Research Council Canada","funders":"","keywords":"Delamination (geology); Materials science; Drilling; Tool wear; Vibration; Stack (abstract data type); Machining; Composite material; Titanium alloy; Lubricant; Metallurgy; Acoustics; Computer science; Geology; Alloy","score_opus":0.004409139696562057,"score_gpt":0.2376212380529132,"score_spread":0.23321209835635112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234886136","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99696714,0.0006972721,0.0021477798,0.000014868987,0.000009374596,0.0000065384274,0.00001541097,0.000027392573,0.000114193215],"genre_scores_gemma":[0.9986015,0.000096999174,0.0011789628,0.000005975282,0.000002123467,0.0000028744755,0.0000088666575,0.0000050490157,0.00009761424],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996588,0.00005249886,0.000030326286,0.00005417672,0.00014418468,0.000060059912],"domain_scores_gemma":[0.99911636,0.00034216352,0.00023929046,0.00007434877,0.00019265595,0.000035182493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038142953,0.00025860683,0.00025096894,0.0003036602,0.00019029152,0.00027002438,0.0002840198,0.00028004407,0.0004185101],"category_scores_gemma":[0.0011977062,0.00019609455,0.00021724676,0.000117592775,0.00032043696,0.000375787,0.00028224092,0.00020459681,0.000077630066],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032906095,0.000020009393,0.0022168478,0.00019775456,0.000013567559,0.00009004351,0.000143518,0.00072247884,0.98598343,0.0000329491,0.000024619369,0.010225702],"study_design_scores_gemma":[0.000014278904,0.0012050372,0.013403535,0.000015600966,0.000029727738,0.00021734173,0.00013222873,0.0055883997,0.97864544,0.000032806183,0.00069456827,0.00002108133],"about_ca_topic_score_codex":0.00036659412,"about_ca_topic_score_gemma":0.0008238484,"teacher_disagreement_score":0.0004185101,"about_ca_system_score_codex":0.00015685054,"about_ca_system_score_gemma":0.000104170416,"threshold_uncertainty_score":0.0020172},"labels":[],"label_agreement":null},{"id":"W4235481456","doi":"10.1007/978-3-662-53120-4_300308","title":"High-Performance Grinding","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Grinding; Materials science; Composite material","score_opus":0.006888438512237733,"score_gpt":0.18473329087431908,"score_spread":0.17784485236208136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235481456","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006349128,0.01663704,0.2813939,0.000729637,0.0018559917,0.0000896395,0.00044235188,0.0030590994,0.68944323],"genre_scores_gemma":[0.042364072,0.0096932845,0.10470205,0.00026614047,0.00028659878,0.00004414069,0.0009034346,0.00087801996,0.84086233],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995939,0.000010788942,0.0000072521448,0.000050792005,0.00030728904,0.000029969257],"domain_scores_gemma":[0.99990535,0.000016585587,0.0000056403255,0.000026205611,0.00003971965,0.000006537054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025061675,0.00081032363,0.0005793576,0.000765219,0.00050548237,0.0011846619,0.0012017385,0.00059908006,0.03968341],"category_scores_gemma":[0.00024856877,0.00045074182,0.00034687688,0.0011935715,0.00056289305,0.0010848426,0.001040314,0.0013383949,0.017167334],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049781323,0.00006013822,0.000127287,0.00053466705,0.00001902167,0.000097874145,0.00010219979,0.0061552394,0.06627014,0.08918365,0.101355426,0.7360446],"study_design_scores_gemma":[0.00001068907,0.00007635692,0.0014374097,0.00013527743,0.000015004887,0.00054160994,0.000042352116,0.01638432,0.055660006,0.039818835,0.88584214,0.000035930785],"about_ca_topic_score_codex":0.00073487114,"about_ca_topic_score_gemma":0.002523304,"teacher_disagreement_score":0.03968341,"about_ca_system_score_codex":0.00065290206,"about_ca_system_score_gemma":0.00044270308,"threshold_uncertainty_score":0.1327542},"labels":[],"label_agreement":null},{"id":"W4237279538","doi":"10.1007/978-3-662-53120-4_300442","title":"Micro-milling","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Materials science","score_opus":0.007508222602945667,"score_gpt":0.1906923662490917,"score_spread":0.18318414364614602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237279538","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017409719,0.012395442,0.052079473,0.00042760748,0.0014172351,0.000091964655,0.00045312222,0.0013682806,0.93002594],"genre_scores_gemma":[0.007281925,0.004556382,0.012197111,0.00016813648,0.00013069282,0.000038892376,0.00039787317,0.00022902156,0.97500014],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961406,0.000010620452,0.000009912707,0.00007612599,0.00026297366,0.00002639907],"domain_scores_gemma":[0.99989915,0.000016833788,0.0000053349077,0.000026762063,0.000044056458,0.000007768376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017183677,0.0009739301,0.0006175422,0.0014078411,0.00092045794,0.0020038586,0.00096966233,0.0007494868,0.10844885],"category_scores_gemma":[0.00029570272,0.0004938923,0.00035979648,0.0017248489,0.0005646373,0.0014187401,0.0013172425,0.0015459821,0.051777814],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039187096,0.000035707355,0.00008905457,0.00039468164,0.000007819866,0.00007858319,0.00012891274,0.00094228674,0.015172123,0.06558603,0.14590159,0.771624],"study_design_scores_gemma":[0.000003461375,0.00002371544,0.00032478277,0.000078913705,0.0000051683746,0.00023482007,0.000031489064,0.00087854406,0.006905607,0.008884734,0.98261803,0.000010715639],"about_ca_topic_score_codex":0.0010180232,"about_ca_topic_score_gemma":0.003811091,"teacher_disagreement_score":0.10844885,"about_ca_system_score_codex":0.0006269218,"about_ca_system_score_gemma":0.0006322812,"threshold_uncertainty_score":0.36279756},"labels":[],"label_agreement":null},{"id":"W4237559291","doi":"10.32920/14668791","title":"Modal analysis of spindles while accounting for system decay and its application to machine tool chatter prevention","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Stiffness; Machine tool; Span (engineering); Natural frequency; Vibration; Life span; Modal; Stability (learning theory); Modal analysis; Process (computing); Engineering; Structural engineering; Mechanical engineering; Computer science; Physics; Finite element method; Acoustics; Materials science","score_opus":0.010450568276154489,"score_gpt":0.25766923494430677,"score_spread":0.2472186666681523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237559291","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38153768,0.00025430313,0.6158288,0.00003403437,0.0000151795375,0.00003460401,0.00007635281,0.00040186115,0.0018170665],"genre_scores_gemma":[0.96760476,0.000087106884,0.03139812,0.000005732536,0.000004871092,0.000015062113,0.000068892165,0.000035763285,0.00077972794],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998184,0.000022532786,0.000008965427,0.000043107004,0.000090490896,0.000016642354],"domain_scores_gemma":[0.9993401,0.00027716983,0.00011119243,0.000078417994,0.00017251952,0.0000206738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004305335,0.00029059107,0.0002207568,0.0007721165,0.00015971779,0.00031922368,0.0003335852,0.00027772735,0.0012760686],"category_scores_gemma":[0.001583171,0.00017228877,0.0002608404,0.00028280469,0.00026045225,0.00046128276,0.0003093477,0.00028666435,0.00019593327],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004919268,0.00009426573,0.017330904,0.00058037566,0.000057781475,0.000418986,0.0015309575,0.15193185,0.4955386,0.004320981,0.0005774961,0.32712582],"study_design_scores_gemma":[0.0000056240715,0.00019646971,0.021868948,0.000025836285,0.00002354957,0.00027328468,0.0002191051,0.94071627,0.03409047,0.0011153731,0.001442749,0.000022223767],"about_ca_topic_score_codex":0.001000311,"about_ca_topic_score_gemma":0.001223908,"teacher_disagreement_score":0.0012760686,"about_ca_system_score_codex":0.00016870198,"about_ca_system_score_gemma":0.00015916106,"threshold_uncertainty_score":0.0042688847},"labels":[],"label_agreement":null},{"id":"W4239363828","doi":"10.1007/978-3-662-53120-4_300743","title":"Water-Based Cutting Fluid","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Geology; Petroleum engineering; Environmental science; Computer science","score_opus":0.00824838222532998,"score_gpt":0.19683124601533367,"score_spread":0.1885828637900037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239363828","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018074054,0.031316746,0.32136744,0.001727481,0.0030753678,0.00017845561,0.00050997763,0.0012077814,0.62254274],"genre_scores_gemma":[0.11537607,0.02364219,0.0558137,0.00067017425,0.00039369983,0.00018059339,0.0005699032,0.0003801801,0.8029735],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997948,0.000009324155,0.000004422349,0.000035834608,0.0001329149,0.000022771324],"domain_scores_gemma":[0.99996424,0.000006923065,0.0000032408257,0.0000047021085,0.00001619188,0.0000047252233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012433865,0.00066417345,0.00041177173,0.00074360153,0.0005670986,0.0011919138,0.0007847026,0.00074332557,0.014145211],"category_scores_gemma":[0.00020994355,0.00031371394,0.00032553266,0.0008360807,0.0007605339,0.0019382383,0.0015015991,0.001165782,0.004597336],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079691425,0.0000834526,0.00015890364,0.0006801139,0.000018673021,0.00015369218,0.00021266758,0.009609945,0.10533198,0.30906406,0.048012633,0.52659416],"study_design_scores_gemma":[0.000012927667,0.000098719924,0.00032576566,0.00015568074,0.000018578772,0.00023853534,0.00010560199,0.019524796,0.08141878,0.04860383,0.84945416,0.000042655345],"about_ca_topic_score_codex":0.001396661,"about_ca_topic_score_gemma":0.0022745607,"teacher_disagreement_score":0.014145211,"about_ca_system_score_codex":0.00067384396,"about_ca_system_score_gemma":0.00068444136,"threshold_uncertainty_score":0.047320485},"labels":[],"label_agreement":null},{"id":"W4239460768","doi":"10.32920/ryerson.14661939.v1","title":"A Newtonian approach to predict the parameters required to machine high aspect ratio channels of prescribed topography","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aspect ratio (aeronautics); Borosilicate glass; Materials science; Surface micromachining; Machining; Cross section (physics); Microfluidics; Mechanical engineering; Fabrication; Optics; Composite material; Nanotechnology; Physics; Engineering","score_opus":0.015371473901021051,"score_gpt":0.22606191957367894,"score_spread":0.21069044567265788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239460768","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022497209,0.00014088862,0.974422,0.00007871431,0.00001783279,0.000055902947,0.00005687493,0.00030508335,0.0024254571],"genre_scores_gemma":[0.38740557,0.0005266722,0.60750544,0.00005237098,0.000027228562,0.00029152483,0.00015792256,0.00027811964,0.0037550877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999866,0.000018030354,0.000006598265,0.000028220858,0.00006910027,0.000012074879],"domain_scores_gemma":[0.9992937,0.0004328922,0.000109065506,0.000049148144,0.00009938154,0.000015747584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045659114,0.00077575794,0.0004403955,0.00033575323,0.00026977554,0.00052349217,0.0006673434,0.00080911146,0.0015013146],"category_scores_gemma":[0.0013665375,0.0006039684,0.00038386186,0.00021351039,0.00048389198,0.00067020615,0.00023106606,0.00094527635,0.00050811196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013733783,0.000051875562,0.00084758457,0.00012704394,0.000012004802,0.000029715968,0.0000536177,0.94681555,0.018988889,0.005366558,0.00030751276,0.02738583],"study_design_scores_gemma":[0.0000025311833,0.000016616861,0.00014265648,0.0000033632527,0.0000018016518,0.000008471286,0.000003809182,0.99581844,0.0029011765,0.0006830863,0.0004136633,0.0000043184855],"about_ca_topic_score_codex":0.0028241326,"about_ca_topic_score_gemma":0.0050503216,"teacher_disagreement_score":0.0028241326,"about_ca_system_score_codex":0.0006227841,"about_ca_system_score_gemma":0.0016015733,"threshold_uncertainty_score":0.0056153536},"labels":[],"label_agreement":null},{"id":"W4240872655","doi":"10.1007/978-3-662-53120-4_300249","title":"Fine Grinding","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Grinding; Materials science; Metallurgy","score_opus":0.008455958214819927,"score_gpt":0.1967533942673617,"score_spread":0.18829743605254176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240872655","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004343444,0.0073545235,0.07027706,0.00065816974,0.0017147776,0.00012286576,0.0005805988,0.0020042704,0.9129443],"genre_scores_gemma":[0.018634869,0.003305361,0.026816964,0.00036305023,0.00014481937,0.00003514013,0.0006500829,0.00046039128,0.9495894],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995009,0.000011697438,0.000012142491,0.00009823059,0.0003353473,0.0000416348],"domain_scores_gemma":[0.99983907,0.000018402789,0.000008064017,0.000047765992,0.000073700714,0.000012969484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032222967,0.0009621837,0.0006609402,0.0019157276,0.0012327301,0.0016234331,0.0008877305,0.0008647227,0.077038035],"category_scores_gemma":[0.00049859483,0.0005352356,0.00048719862,0.0012578245,0.00088074344,0.001085599,0.0014752215,0.001971572,0.032515507],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054371103,0.00006416179,0.00019022191,0.00044625544,0.00001105595,0.0001613344,0.00022265952,0.0019281572,0.0421402,0.07452604,0.13950193,0.7407536],"study_design_scores_gemma":[0.0000051307807,0.00004449725,0.0010997113,0.00009313429,0.000007492594,0.0005002825,0.000053290783,0.0014351258,0.01848729,0.016429016,0.96182394,0.000021106933],"about_ca_topic_score_codex":0.0018093617,"about_ca_topic_score_gemma":0.008316652,"teacher_disagreement_score":0.077038035,"about_ca_system_score_codex":0.0007538835,"about_ca_system_score_gemma":0.0006831149,"threshold_uncertainty_score":0.2577179},"labels":[],"label_agreement":null},{"id":"W4241102883","doi":"10.1007/978-1-4020-3995-9_3","title":"Abrasion","year":2007,"lang":"en","type":"book-chapter","venue":"Encyclopedia of earth sciences series/Encyclopedia of earth sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Abrasion (mechanical); Materials science; Composite material","score_opus":0.01870318987176639,"score_gpt":0.25172371637691243,"score_spread":0.23302052650514604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241102883","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004862352,0.0014002537,0.011275378,0.00083092303,0.0024088067,0.00016941252,0.0004658329,0.0022508386,0.9763362],"genre_scores_gemma":[0.025306405,0.0008487917,0.004474202,0.00085367874,0.0002076575,0.00005597475,0.0005727028,0.00056020997,0.9671203],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99878484,0.000044990637,0.00003482613,0.00018503793,0.00082294503,0.0001273983],"domain_scores_gemma":[0.9993481,0.000072197574,0.000031342406,0.00014670478,0.00032846013,0.00007316366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005007741,0.0010701703,0.00063791766,0.002478223,0.001643587,0.0027192559,0.0016129176,0.0013325289,0.27212375],"category_scores_gemma":[0.0018876422,0.00039076884,0.0005989476,0.00094009575,0.00080648926,0.0018543447,0.0026314924,0.001866935,0.14524612],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020315999,0.00017717175,0.0006765521,0.0004620821,0.000015327023,0.00055289984,0.00065967964,0.00044359983,0.01569363,0.046904404,0.29673666,0.63747483],"study_design_scores_gemma":[0.000010341017,0.000051110885,0.0005237604,0.00009655129,0.000009646712,0.0005578182,0.00019860754,0.00027502832,0.0050764577,0.003951919,0.98923385,0.000015061651],"about_ca_topic_score_codex":0.0018146364,"about_ca_topic_score_gemma":0.0028866658,"teacher_disagreement_score":0.27212375,"about_ca_system_score_codex":0.00054953864,"about_ca_system_score_gemma":0.00087982375,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4241570161","doi":"10.1504/ijhm.2021.114174","title":"Self-supervised learning for tool wear monitoring with a disentangled-variational-autoencoder","year":2021,"lang":"en","type":"article","venue":"International Journal of Hydromechatronics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Autoencoder; Artificial intelligence; Supervised learning; Machine learning; Computer science; Deep learning; Pattern recognition (psychology); Artificial neural network","score_opus":0.005737306654933823,"score_gpt":0.23377832386344363,"score_spread":0.2280410172085098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241570161","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03797196,0.0005048268,0.9586653,0.00014929783,0.000046275767,0.000036219568,0.0001297586,0.0018296419,0.000666761],"genre_scores_gemma":[0.7464355,0.00023777291,0.24764027,0.00023859611,0.000058595313,0.00011312102,0.0010586337,0.0002100469,0.0040074433],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994661,0.00011061012,0.00003117335,0.0002116059,0.000121842975,0.000058589103],"domain_scores_gemma":[0.99905354,0.0004245217,0.000096345204,0.00014993406,0.0002424887,0.000033163484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001190719,0.0009717381,0.0010226439,0.00052086666,0.0002171809,0.0005852205,0.0016837271,0.0009871686,0.00071654236],"category_scores_gemma":[0.0025286397,0.0006243655,0.0008616479,0.0004939778,0.0005476168,0.001003112,0.00082231784,0.0015393207,0.00037380843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016825653,0.00021096833,0.0032106044,0.00010148943,0.00019296097,0.000075156386,0.00008663078,0.7187962,0.012360726,0.0024111844,0.0030009148,0.25938493],"study_design_scores_gemma":[0.0000021536875,0.000010069251,0.0001647472,0.000002246424,0.0000030138838,0.000005885358,0.00000211002,0.9984403,0.00083849044,0.00042355267,0.00010503474,0.0000022991874],"about_ca_topic_score_codex":0.0062421937,"about_ca_topic_score_gemma":0.010663493,"teacher_disagreement_score":0.0062421937,"about_ca_system_score_codex":0.0006635778,"about_ca_system_score_gemma":0.0009896103,"threshold_uncertainty_score":0.012411714},"labels":[],"label_agreement":null},{"id":"W4242201776","doi":"10.32920/ryerson.14652987.v1","title":"Predictive modeling of surface finish in fine grinding","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Grinding; Materials science; Surface roughness; Ellipsoid; Enhanced Data Rates for GSM Evolution; Surface (topology); Surface finish; Process (computing); Mechanical engineering; Chip; Consistency (knowledge bases); Engineering drawing; Metallurgy; Computer science; Composite material; Geometry; Engineering; Mathematics; Physics; Artificial intelligence","score_opus":0.013846438379005987,"score_gpt":0.2371927901630209,"score_spread":0.2233463517840149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242201776","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41593295,0.0005326641,0.572231,0.00025503515,0.00006140658,0.00010038971,0.00038196615,0.00074333325,0.009761273],"genre_scores_gemma":[0.9859658,0.00019593089,0.0105207935,0.000015767626,0.000008732576,0.00005782103,0.00014603374,0.000048350645,0.003040851],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997999,0.000029781188,0.000006534271,0.000046555437,0.000079959646,0.00003721662],"domain_scores_gemma":[0.9995678,0.0002568739,0.000056807774,0.000032220545,0.00006895027,0.000017274759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044019736,0.00042912606,0.00073020684,0.00035533175,0.0002746853,0.00085270515,0.000821854,0.0008045462,0.0011953822],"category_scores_gemma":[0.0011420829,0.00050604035,0.0006815562,0.0003335092,0.0006066773,0.0005088722,0.00038729073,0.00067691255,0.00020605496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004327863,0.0000042060406,0.00012278286,0.0000038274893,0.0000016613469,0.00000725396,0.0000040034356,0.9984301,0.000361927,0.0002869261,0.000022097931,0.00075094606],"study_design_scores_gemma":[6.539187e-7,0.000002618033,0.000067769615,3.9281827e-7,4.3570014e-7,8.843133e-7,7.156499e-7,0.99971515,0.00007340156,0.00011020277,0.00002701199,7.829726e-7],"about_ca_topic_score_codex":0.017586289,"about_ca_topic_score_gemma":0.008880815,"teacher_disagreement_score":0.017586289,"about_ca_system_score_codex":0.0008432174,"about_ca_system_score_gemma":0.0006945474,"threshold_uncertainty_score":0.03496784},"labels":[],"label_agreement":null},{"id":"W4243109604","doi":"10.1007/978-3-319-95966-5_2","title":"Hardened Steels","year":2018,"lang":"en","type":"book-chapter","venue":"Materials forming, machining and tribology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Materials science; Metallurgy","score_opus":0.0095829259314563,"score_gpt":0.21397916107058715,"score_spread":0.20439623513913086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243109604","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008177284,0.007351944,0.024904026,0.00066031056,0.0026248551,0.00013343786,0.0006134542,0.0010299735,0.95450467],"genre_scores_gemma":[0.020074865,0.0026120057,0.008165672,0.00033303103,0.00021823928,0.000026658634,0.00059844885,0.00019079169,0.96778023],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995179,0.000026797132,0.000016433036,0.00010303178,0.0002978331,0.00003793568],"domain_scores_gemma":[0.999856,0.000014107294,0.000012913496,0.00002989666,0.0000695794,0.000017460497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025475395,0.0011633693,0.00039531582,0.0017585242,0.0007036082,0.0013180571,0.001133799,0.00074687443,0.08580411],"category_scores_gemma":[0.0003346373,0.0003707761,0.00037294882,0.0009450268,0.0008318115,0.0011773299,0.0011269995,0.001343014,0.035588443],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001910684,0.000099807854,0.00018311417,0.0011201763,0.000042836527,0.00028882647,0.00030732402,0.0027056574,0.07718314,0.20137857,0.14654131,0.5699581],"study_design_scores_gemma":[0.0000069182042,0.000061134066,0.0003805098,0.000054130855,0.000006120498,0.0001083725,0.00002779827,0.0003045713,0.007905243,0.007268864,0.98386765,0.000008654718],"about_ca_topic_score_codex":0.00086104753,"about_ca_topic_score_gemma":0.0021484678,"teacher_disagreement_score":0.08580411,"about_ca_system_score_codex":0.00072294835,"about_ca_system_score_gemma":0.00044524155,"threshold_uncertainty_score":0.28704333},"labels":[],"label_agreement":null},{"id":"W4243315236","doi":"10.32920/ryerson.14661939","title":"A Newtonian approach to predict the parameters required to machine high aspect ratio channels of prescribed topography","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aspect ratio (aeronautics); Borosilicate glass; Materials science; Surface micromachining; Machining; Cross section (physics); Mechanical engineering; Fabrication; Composite material; Engineering; Physics","score_opus":0.015371473901021051,"score_gpt":0.22606191957367894,"score_spread":0.21069044567265788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243315236","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022497209,0.00014088862,0.974422,0.00007871431,0.00001783279,0.000055902947,0.00005687493,0.00030508335,0.0024254571],"genre_scores_gemma":[0.38740557,0.0005266722,0.60750544,0.00005237098,0.000027228562,0.00029152483,0.00015792256,0.00027811964,0.0037550877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999866,0.000018030354,0.000006598265,0.000028220858,0.00006910027,0.000012074879],"domain_scores_gemma":[0.9992937,0.0004328922,0.000109065506,0.000049148144,0.00009938154,0.000015747584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045659114,0.00077575794,0.0004403955,0.00033575323,0.00026977554,0.00052349217,0.0006673434,0.00080911146,0.0015013146],"category_scores_gemma":[0.0013665375,0.0006039684,0.00038386186,0.00021351039,0.00048389198,0.00067020615,0.00023106606,0.00094527635,0.00050811196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013733783,0.000051875562,0.00084758457,0.00012704394,0.000012004802,0.000029715968,0.0000536177,0.94681555,0.018988889,0.005366558,0.00030751276,0.02738583],"study_design_scores_gemma":[0.0000025311833,0.000016616861,0.00014265648,0.0000033632527,0.0000018016518,0.000008471286,0.000003809182,0.99581844,0.0029011765,0.0006830863,0.0004136633,0.0000043184855],"about_ca_topic_score_codex":0.0028241326,"about_ca_topic_score_gemma":0.0050503216,"teacher_disagreement_score":0.0028241326,"about_ca_system_score_codex":0.0006227841,"about_ca_system_score_gemma":0.0016015733,"threshold_uncertainty_score":0.0056153536},"labels":[],"label_agreement":null},{"id":"W4244927257","doi":"10.32920/14668791.v1","title":"Modal analysis of spindles while accounting for system decay and its application to machine tool chatter prevention","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Stiffness; Machine tool; Span (engineering); Natural frequency; Modal; Vibration; Modal analysis; Stability (learning theory); Life span; Process (computing); Engineering; Structural engineering; Mechanical engineering; Computer science; Physics; Acoustics; Finite element method; Materials science","score_opus":0.010450568276154489,"score_gpt":0.25766923494430677,"score_spread":0.2472186666681523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244927257","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38153768,0.00025430313,0.6158288,0.00003403437,0.0000151795375,0.00003460401,0.00007635281,0.00040186115,0.0018170665],"genre_scores_gemma":[0.96760476,0.000087106884,0.03139812,0.000005732536,0.000004871092,0.000015062113,0.000068892165,0.000035763285,0.00077972794],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998184,0.000022532786,0.000008965427,0.000043107004,0.000090490896,0.000016642354],"domain_scores_gemma":[0.9993401,0.00027716983,0.00011119243,0.000078417994,0.00017251952,0.0000206738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004305335,0.00029059107,0.0002207568,0.0007721165,0.00015971779,0.00031922368,0.0003335852,0.00027772735,0.0012760686],"category_scores_gemma":[0.001583171,0.00017228877,0.0002608404,0.00028280469,0.00026045225,0.00046128276,0.0003093477,0.00028666435,0.00019593327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004919268,0.00009426573,0.017330904,0.00058037566,0.000057781475,0.000418986,0.0015309575,0.15193185,0.4955386,0.004320981,0.0005774961,0.32712582],"study_design_scores_gemma":[0.0000056240715,0.00019646971,0.021868948,0.000025836285,0.00002354957,0.00027328468,0.0002191051,0.94071627,0.03409047,0.0011153731,0.001442749,0.000022223767],"about_ca_topic_score_codex":0.001000311,"about_ca_topic_score_gemma":0.001223908,"teacher_disagreement_score":0.0012760686,"about_ca_system_score_codex":0.00016870198,"about_ca_system_score_gemma":0.00015916106,"threshold_uncertainty_score":0.0042688847},"labels":[],"label_agreement":null},{"id":"W4245077091","doi":"10.1007/978-3-662-53120-4_300286","title":"Grinding Spindle","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Grinding; Materials science; Metallurgy","score_opus":0.008465286650323225,"score_gpt":0.19534753233309243,"score_spread":0.1868822456827692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245077091","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022458003,0.006186356,0.043227263,0.00035013744,0.0011427364,0.000101843594,0.00043570428,0.0014992576,0.94481075],"genre_scores_gemma":[0.009364302,0.004028118,0.01810625,0.00019935553,0.00012824115,0.000025731013,0.0006428244,0.00027529278,0.9672299],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99975353,0.000006494023,0.00000613621,0.00004599503,0.0001731737,0.000014747107],"domain_scores_gemma":[0.9999056,0.000011891377,0.00000491089,0.000022293847,0.00004965507,0.0000056396007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015016238,0.00081197615,0.0005554492,0.001276415,0.0007191988,0.001160575,0.00072253303,0.000590344,0.07670502],"category_scores_gemma":[0.00026978122,0.00036645873,0.0003468015,0.0010991351,0.00043791113,0.0008929393,0.00072067836,0.0013579373,0.044051167],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003901271,0.00004568431,0.000115432544,0.00044834783,0.000006959913,0.00016663792,0.00015892347,0.0014172032,0.021180514,0.048977353,0.16176383,0.7656801],"study_design_scores_gemma":[0.0000048592524,0.000045504523,0.00084605,0.00007595179,0.0000046815862,0.00045016798,0.000037063106,0.0010935623,0.006586044,0.009261545,0.9815855,0.00000910027],"about_ca_topic_score_codex":0.0010789766,"about_ca_topic_score_gemma":0.004742244,"teacher_disagreement_score":0.07670502,"about_ca_system_score_codex":0.00044978832,"about_ca_system_score_gemma":0.00044793735,"threshold_uncertainty_score":0.2566039},"labels":[],"label_agreement":null},{"id":"W4245587492","doi":"10.32920/ryerson.14663589","title":"Numerical and experimental modal analysis of machine tool spindles accounting for system decay and its application to chatter avoidance.","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Natural frequency; Vibration; Engineering; Stiffness; Modal analysis; Machine tool; Modal; Mechanical engineering; Structural engineering; Finite element method; Acoustics; Materials science","score_opus":0.007073037416199999,"score_gpt":0.2558329008825711,"score_spread":0.2487598634663711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245587492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9285483,0.00023317443,0.06401284,0.00008377101,0.000033674038,0.000053404274,0.0003034788,0.00041007108,0.0063213957],"genre_scores_gemma":[0.9943269,0.000037747835,0.0048322068,0.0000037497912,0.0000014458263,0.000011339923,0.00008426742,0.0000089599735,0.00069340464],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998704,0.000013136798,0.0000069790835,0.000021643145,0.0000761222,0.000011583613],"domain_scores_gemma":[0.9993575,0.00027633537,0.00009227308,0.00007303942,0.0001788547,0.000021926895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041347195,0.00017042353,0.00016200534,0.000434335,0.00023834438,0.00024266812,0.0002279033,0.00031680608,0.0028657452],"category_scores_gemma":[0.0010877257,0.0001230117,0.00022311111,0.00023584759,0.00028877598,0.00022247001,0.00019779551,0.00023606444,0.00029001455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073828775,0.00022558728,0.014685178,0.0009973822,0.000031175936,0.00048580603,0.0015655928,0.3167047,0.5661419,0.004552317,0.0027010995,0.09117094],"study_design_scores_gemma":[0.000021174823,0.0005614543,0.022191025,0.000031021194,0.000014796611,0.00022764318,0.00041393595,0.9262934,0.04705846,0.0006624198,0.002493019,0.000031738735],"about_ca_topic_score_codex":0.001352434,"about_ca_topic_score_gemma":0.0018336348,"teacher_disagreement_score":0.0028657452,"about_ca_system_score_codex":0.00016856127,"about_ca_system_score_gemma":0.0001550375,"threshold_uncertainty_score":0.009586811},"labels":[],"label_agreement":null},{"id":"W4245844389","doi":"10.1007/978-3-662-53120-4_300306","title":"High-Efficiency Grinding","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Grinding; Materials science; Metallurgy","score_opus":0.007184788107557001,"score_gpt":0.1943379289051535,"score_spread":0.1871531407975965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245844389","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007828449,0.013134515,0.3574521,0.0005171982,0.0010050372,0.000087977736,0.00032017208,0.0019522103,0.6177023],"genre_scores_gemma":[0.06835855,0.011049837,0.13858393,0.00025758133,0.00022167874,0.000051377418,0.0007523187,0.0008369898,0.7798878],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995697,0.000013530593,0.000007779085,0.00004836037,0.00033072874,0.000029864621],"domain_scores_gemma":[0.99991405,0.000015656879,0.000005337664,0.000026839934,0.000033238073,0.0000047882204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026513598,0.0006731219,0.0005744786,0.0008103657,0.00043436728,0.0010270693,0.0011199339,0.0005183319,0.0320195],"category_scores_gemma":[0.00025327105,0.00040326506,0.00037667918,0.0011541696,0.0005611176,0.0011309653,0.0010323047,0.0012012309,0.013209111],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048134567,0.000075200864,0.00015213116,0.0006406113,0.00002296953,0.00009712226,0.00011036631,0.007662899,0.06737028,0.1298844,0.055660192,0.7382757],"study_design_scores_gemma":[0.000015367246,0.00009115953,0.0020997627,0.0001976643,0.000023108296,0.0008322566,0.00005818318,0.022167364,0.09279588,0.069696814,0.8119799,0.000042484102],"about_ca_topic_score_codex":0.00048649483,"about_ca_topic_score_gemma":0.001872143,"teacher_disagreement_score":0.0320195,"about_ca_system_score_codex":0.00056644256,"about_ca_system_score_gemma":0.00036941457,"threshold_uncertainty_score":0.107115865},"labels":[],"label_agreement":null},{"id":"W4246047103","doi":"10.1007/978-3-662-53120-4_300599","title":"Self-Excited Vibrations in Metal Cutting","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Vibration; Excited state; Metal; Materials science; Metallurgy; Physics; Acoustics; Atomic physics","score_opus":0.00721267756612551,"score_gpt":0.20402185717057308,"score_spread":0.19680917960444758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246047103","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012768801,0.07525935,0.1471338,0.000987111,0.0041146716,0.000047388243,0.00008454581,0.00040510646,0.7591993],"genre_scores_gemma":[0.07802251,0.026628533,0.018807665,0.00030589887,0.0012874457,0.000046822162,0.00013867817,0.00022262066,0.87453985],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99986076,0.000016979895,0.0000032373027,0.0000184957,0.00009017511,0.000010344481],"domain_scores_gemma":[0.9999453,0.000030173516,0.000003025196,0.0000074560007,0.000010398313,0.0000037850707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010796871,0.00051426253,0.00037939794,0.00040227865,0.0002937042,0.0008859944,0.00069549883,0.00077243405,0.012727446],"category_scores_gemma":[0.00019582924,0.0002938986,0.00023648437,0.00058282225,0.0007415518,0.0007235814,0.00071002723,0.0009949522,0.0033323872],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000066740904,0.00012591432,0.00013359138,0.000784154,0.000032626423,0.0001459508,0.00054989196,0.021862347,0.025687343,0.4361235,0.07004767,0.44444025],"study_design_scores_gemma":[0.000023714783,0.00012989952,0.0013344734,0.00045041202,0.000023347076,0.0005948087,0.00027589963,0.04441372,0.009563938,0.25837183,0.6847667,0.000051177984],"about_ca_topic_score_codex":0.00030371145,"about_ca_topic_score_gemma":0.00075555575,"teacher_disagreement_score":0.012727446,"about_ca_system_score_codex":0.00030572177,"about_ca_system_score_gemma":0.00019247913,"threshold_uncertainty_score":0.042577505},"labels":[],"label_agreement":null},{"id":"W4246068124","doi":"10.2493/jjspe.77.470","title":"Research on Metal Cutting, Machine Tool Vibrations and Control","year":2011,"lang":"en","type":"article","venue":"Journal of the Japan Society for Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Vibration; Mechanical engineering; Machine tool; Engineering; Materials science; Structural engineering; Computer science; Acoustics; Physics","score_opus":0.02948433090717565,"score_gpt":0.27901696105731355,"score_spread":0.2495326301501379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246068124","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3912587,0.24483694,0.18502331,0.006809162,0.0024457572,0.00007350168,0.00016902364,0.00017764598,0.16920604],"genre_scores_gemma":[0.8842684,0.054924898,0.018393856,0.0006336789,0.0012455343,0.00003778585,0.00017357852,0.00003328089,0.040288948],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99951124,0.00006838223,0.000023344359,0.00016116844,0.00018409717,0.00005175484],"domain_scores_gemma":[0.99885154,0.00060528936,0.000090512774,0.00007940225,0.0003290636,0.00004419911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068215077,0.00038573676,0.00042646308,0.0010319145,0.00044402512,0.0013514458,0.00076953607,0.0008684356,0.004587229],"category_scores_gemma":[0.001588046,0.00022371052,0.0003706881,0.0011971085,0.0010519044,0.0018615555,0.00030588912,0.00064923614,0.00041346074],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036395152,0.00040321198,0.00945231,0.0015755659,0.00016571807,0.0003763496,0.0007226784,0.02169315,0.0751179,0.16305952,0.003799213,0.7232704],"study_design_scores_gemma":[0.00016390355,0.002221538,0.094460845,0.0011506535,0.0004921948,0.0018420414,0.0030108462,0.16297765,0.087887414,0.34841284,0.29711893,0.00026113406],"about_ca_topic_score_codex":0.0022394303,"about_ca_topic_score_gemma":0.0019233072,"teacher_disagreement_score":0.004587229,"about_ca_system_score_codex":0.00069033547,"about_ca_system_score_gemma":0.00092263153,"threshold_uncertainty_score":0.015345812},"labels":[],"label_agreement":null},{"id":"W4246604647","doi":"10.1007/978-3-662-53120-4_300387","title":"Machine Tool Vibrations","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Vibration; Computer science; Physics; Acoustics","score_opus":0.007284529905832488,"score_gpt":0.20037611852125292,"score_spread":0.19309158861542045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246604647","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004554156,0.01136658,0.17059793,0.0006166437,0.0024048572,0.000082059516,0.00039009657,0.0019287622,0.8080589],"genre_scores_gemma":[0.04360358,0.0050214673,0.016365556,0.00029056484,0.00047282942,0.00006142209,0.00040725528,0.0004236613,0.9333537],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999616,0.000022755337,0.000008638484,0.000069540016,0.00025961734,0.000023418814],"domain_scores_gemma":[0.9998684,0.000038529535,0.000008078055,0.000032121236,0.000044155164,0.00000877615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015764024,0.0008172359,0.0005450696,0.00087907043,0.0005286436,0.0013413638,0.0007867017,0.001055483,0.06029918],"category_scores_gemma":[0.00041402553,0.00037098577,0.00033797653,0.0007935756,0.00060227606,0.0009895203,0.0010894239,0.0012777561,0.024569534],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007240238,0.000045136003,0.00015022409,0.00041149525,0.000011824606,0.00010981231,0.00022700019,0.00422354,0.034518607,0.059436712,0.07625416,0.8245391],"study_design_scores_gemma":[0.000010691401,0.0000986168,0.0013405036,0.00023729497,0.000014046589,0.00050155254,0.00010551673,0.007573868,0.014107659,0.030898256,0.94508237,0.000029655406],"about_ca_topic_score_codex":0.00036336418,"about_ca_topic_score_gemma":0.00076645677,"teacher_disagreement_score":0.06029918,"about_ca_system_score_codex":0.0003848506,"about_ca_system_score_gemma":0.00031033935,"threshold_uncertainty_score":0.2017209},"labels":[],"label_agreement":null},{"id":"W4247357885","doi":"10.32920/14639913","title":"Effects of Machine Tool Spindle Decay on the Stability Lobe Diagram: An Analytical-Experimental Study","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machine tool; Natural frequency; Vibration; Machining; Stability (learning theory); Stiffness; Finite element method; Modal analysis; Boundary (topology); Control theory (sociology); Diagram; Modal; Structural engineering; Engineering; Computer science; Mechanical engineering; Acoustics; Physics; Materials science; Mathematical analysis; Mathematics","score_opus":0.018299161779270375,"score_gpt":0.28669542021790045,"score_spread":0.2683962584386301,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247357885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9763406,0.00023812718,0.02191345,0.0000386024,0.000018896848,0.00004678733,0.00013749658,0.00020288843,0.0010631637],"genre_scores_gemma":[0.99778384,0.000045902572,0.0017328896,0.0000071440327,0.0000020515563,0.000015655172,0.000042823624,0.000022476257,0.00034722898],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990128,0.00014285842,0.000065051085,0.00021108313,0.0004353067,0.00013286846],"domain_scores_gemma":[0.9953876,0.0023332464,0.0005762308,0.0006093784,0.0009543465,0.00013919636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00138998,0.00043585364,0.00056570553,0.0004555041,0.00035742184,0.0004287376,0.00056675496,0.0006028891,0.0021058817],"category_scores_gemma":[0.0047916165,0.0003060945,0.00033931877,0.0004701517,0.000883271,0.0004794503,0.0005469598,0.0006971223,0.0004034323],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002044098,0.00050870277,0.005297777,0.0005136003,0.000019190295,0.00042656163,0.0010616262,0.014153721,0.9460319,0.0005472505,0.00032250944,0.029073086],"study_design_scores_gemma":[0.00006246762,0.0048010554,0.029416446,0.000064050735,0.000037863345,0.000455473,0.0004036221,0.10921304,0.8529335,0.0003120918,0.0022325467,0.00006790929],"about_ca_topic_score_codex":0.00061169645,"about_ca_topic_score_gemma":0.00070738484,"teacher_disagreement_score":0.0021058817,"about_ca_system_score_codex":0.00032551528,"about_ca_system_score_gemma":0.00021079903,"threshold_uncertainty_score":0.0073509812},"labels":[],"label_agreement":null},{"id":"W4247445923","doi":"10.1106/xc54-8c3f-drw0-3b0u","title":"Evolution of Residual Stresses Induced during Curing Processing Using a Viscoelastic Micromechanical Model","year":2001,"lang":"en","type":"article","venue":"Journal of Composite Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Materials science; Viscoelasticity; Composite material; Curing (chemistry); Residual stress; Micromechanics; Residual; Composite number; Computer science","score_opus":0.01533513653061873,"score_gpt":0.2567724691819151,"score_spread":0.24143733265129635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247445923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9503081,0.00016231228,0.047915008,0.00003862711,0.000008351189,0.000018679488,0.00005897355,0.00014122958,0.0013487702],"genre_scores_gemma":[0.9937949,0.000097926946,0.005293177,0.0000045606166,0.0000020184032,0.0000139676295,0.000045806788,0.000011566096,0.0007360259],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999379,0.000007972696,0.0000033777035,0.000014342602,0.000025387122,0.000011080589],"domain_scores_gemma":[0.99989367,0.000037813414,0.000026956717,0.00001540069,0.000018211878,0.000007896577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017581598,0.00034273803,0.00020296469,0.0001858164,0.00011544402,0.00019881314,0.00022681465,0.00041050932,0.0005247416],"category_scores_gemma":[0.00031849986,0.00017284673,0.00031208724,0.00010605848,0.00024072365,0.0002488111,0.00010497943,0.0002793414,0.00011405058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000106597276,0.00006758543,0.0015540306,0.000048656377,0.000014798289,0.00017707088,0.000098126184,0.3970132,0.5919379,0.0011763851,0.00006215452,0.0077434075],"study_design_scores_gemma":[0.000004989162,0.00011164828,0.0017846246,0.0000032997425,0.000007908548,0.000036654437,0.000008315892,0.94619596,0.051492367,0.00016571069,0.00017863886,0.000009912931],"about_ca_topic_score_codex":0.0010126448,"about_ca_topic_score_gemma":0.000655821,"teacher_disagreement_score":0.0010126448,"about_ca_system_score_codex":0.00019517179,"about_ca_system_score_gemma":0.00017841805,"threshold_uncertainty_score":0.002013445},"labels":[],"label_agreement":null},{"id":"W4247755052","doi":"10.32920/ryerson.14663340","title":"Experimental implementation of artificial neural network-based active vibration control &amp; chatter suppression","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Vibration; Artificial neural network; Active vibration control; Control theory (sociology); Vibration control; Engineering; Computer science; Control system; Cantilever; Control engineering; Control (management); Artificial intelligence; Structural engineering; Acoustics","score_opus":0.015581522123927972,"score_gpt":0.29615407215190864,"score_spread":0.28057255002798065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247755052","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7451515,0.00034868848,0.23849492,0.000225238,0.00040663267,0.00033116652,0.00032796667,0.0018078604,0.012905962],"genre_scores_gemma":[0.97842056,0.000058993777,0.018970396,0.00001873743,0.0000075512025,0.00013262946,0.00007012469,0.00002434227,0.0022966934],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965715,0.00003962196,0.000028413024,0.00006819669,0.00015947453,0.00004724432],"domain_scores_gemma":[0.9994394,0.00012764834,0.00006679972,0.000093271585,0.00023851034,0.000034261004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045839284,0.00038801227,0.0002517615,0.00039532376,0.00024813876,0.00026486086,0.0007057338,0.00046966434,0.003770567],"category_scores_gemma":[0.00078446936,0.00015104885,0.00016848816,0.00024272759,0.00040245245,0.0002785717,0.00031876354,0.000407576,0.0003366463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007550673,0.00063043303,0.0012957826,0.0006938236,0.000041994994,0.0002145898,0.00028876046,0.037059765,0.849497,0.0015754717,0.0009845108,0.10696276],"study_design_scores_gemma":[0.00011290845,0.0026278866,0.007150616,0.000039143037,0.00003654731,0.00013119224,0.00009614051,0.30022395,0.6853093,0.0004972198,0.003735445,0.000039653307],"about_ca_topic_score_codex":0.0009138602,"about_ca_topic_score_gemma":0.0010504643,"teacher_disagreement_score":0.003770567,"about_ca_system_score_codex":0.00020298018,"about_ca_system_score_gemma":0.00021070258,"threshold_uncertainty_score":0.012613773},"labels":[],"label_agreement":null},{"id":"W4249629696","doi":"10.1109/.2001.980628","title":"Chatter suppression with adaptive control in turning metal via application of piezoactuator","year":2002,"lang":"en","type":"article","venue":"Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Machining; Control theory (sociology); Nonlinear system; Vibration; Displacement (psychology); Adaptive control; Controller (irrigation); Computer science; Engineering; Control engineering; Mechanical engineering; Control (management); Acoustics; Artificial intelligence; Physics","score_opus":0.009178141145667111,"score_gpt":0.2036990916429349,"score_spread":0.19452095049726778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249629696","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14757472,0.0006920647,0.8488688,0.00012152213,0.000060051425,0.000023119344,0.000007037337,0.00034402582,0.002308601],"genre_scores_gemma":[0.9848363,0.00012624676,0.014272708,0.000024690971,0.000013816778,0.0000194606,0.000004981028,0.0000065786885,0.00069519767],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997583,0.000059116042,0.000012076999,0.000038371767,0.00011215515,0.000019989326],"domain_scores_gemma":[0.9997477,0.000123246,0.000043204705,0.00001993389,0.000057156965,0.000008651519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003259696,0.00023682056,0.0002551448,0.00015154282,0.00012985923,0.00023464805,0.0004233662,0.00030885264,0.00027692778],"category_scores_gemma":[0.00073054445,0.00014768208,0.0002055775,0.0001338151,0.0004069822,0.00020216432,0.00032296966,0.0003212463,0.000056794823],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048243708,0.00010671779,0.0013215335,0.00031010728,0.00008608699,0.00054105127,0.0005701614,0.58156025,0.26687357,0.014096599,0.00067610655,0.1333755],"study_design_scores_gemma":[0.00002002401,0.00024598837,0.00037868822,0.000006003102,0.000012104543,0.000063198786,0.000012925526,0.98966473,0.008178301,0.0008603871,0.0005487762,0.00000881509],"about_ca_topic_score_codex":0.0016872623,"about_ca_topic_score_gemma":0.0011259671,"teacher_disagreement_score":0.0016872623,"about_ca_system_score_codex":0.000162871,"about_ca_system_score_gemma":0.00018604171,"threshold_uncertainty_score":0.003354907},"labels":[],"label_agreement":null},{"id":"W4250025965","doi":"10.1007/978-3-642-20617-7_100180","title":"Fine Grinding","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Grinding; Materials science; Metallurgy","score_opus":0.007833184606404054,"score_gpt":0.1941675420830353,"score_spread":0.18633435747663124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250025965","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005544032,0.010009175,0.13442312,0.0008468667,0.0020261584,0.0001317806,0.0005498813,0.002307865,0.8441612],"genre_scores_gemma":[0.030357756,0.0053694644,0.052173913,0.00052403455,0.00023919171,0.000051792562,0.0008029884,0.0007331279,0.9097477],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994659,0.000013755693,0.000013496596,0.00010652943,0.0003552397,0.000045047986],"domain_scores_gemma":[0.9998369,0.000020665251,0.000008979397,0.000049827504,0.00007057927,0.000013049317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035392464,0.0010164643,0.0007018225,0.0017407284,0.0011294843,0.0014993136,0.0009607359,0.0008830463,0.05703387],"category_scores_gemma":[0.00054093293,0.0005636474,0.0005002257,0.0010973822,0.0009885926,0.0012481641,0.0015345344,0.0021315578,0.023061607],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052288007,0.00006138167,0.00019400485,0.00049681636,0.000013890572,0.00015992853,0.0002308642,0.0029136264,0.046380095,0.09794358,0.10973419,0.7418193],"study_design_scores_gemma":[0.000005772608,0.000045183915,0.0010055272,0.00011241017,0.000009054657,0.0005414332,0.000056822046,0.0021402545,0.023626171,0.025936576,0.946493,0.000027659016],"about_ca_topic_score_codex":0.0015105911,"about_ca_topic_score_gemma":0.0065225824,"teacher_disagreement_score":0.05703387,"about_ca_system_score_codex":0.0007719333,"about_ca_system_score_gemma":0.0007045114,"threshold_uncertainty_score":0.19079727},"labels":[],"label_agreement":null},{"id":"W4251068933","doi":"10.1007/978-3-642-20617-7_100202","title":"Hard Material Machining","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Machining; Materials science; Mechanical engineering; Engineering","score_opus":0.008398168912566707,"score_gpt":0.1930337067462731,"score_spread":0.1846355378337064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251068933","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033523545,0.01298753,0.11157972,0.00056411116,0.0020948758,0.00009803109,0.00035216068,0.0011609085,0.86781037],"genre_scores_gemma":[0.014923455,0.0050577032,0.026296776,0.00026973474,0.00025621842,0.00004523697,0.00054120965,0.00041597104,0.9521937],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996512,0.000015205535,0.000009000944,0.00006676362,0.00023094434,0.000026855252],"domain_scores_gemma":[0.9998901,0.000020316551,0.000006095489,0.000032531214,0.000041912324,0.0000090681015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019447201,0.0011415884,0.00069051876,0.0012790504,0.0008912894,0.0015087288,0.0011363779,0.00069516455,0.06864957],"category_scores_gemma":[0.00031407695,0.0005146448,0.00037850114,0.0011168448,0.00074330927,0.0013235089,0.0014422835,0.0017556497,0.029241856],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048528975,0.000052596137,0.00009222778,0.000642553,0.00001444942,0.0000785344,0.00013636649,0.0030602524,0.02487981,0.08353254,0.11505422,0.772408],"study_design_scores_gemma":[0.0000048076713,0.000036249166,0.00041250043,0.000111525784,0.0000075126886,0.00022899365,0.00003525093,0.0024501488,0.013023252,0.02372979,0.959943,0.000017005674],"about_ca_topic_score_codex":0.0006795805,"about_ca_topic_score_gemma":0.00248312,"teacher_disagreement_score":0.06864957,"about_ca_system_score_codex":0.000617016,"about_ca_system_score_gemma":0.00061123545,"threshold_uncertainty_score":0.22965568},"labels":[],"label_agreement":null},{"id":"W4251310814","doi":"10.1007/978-3-642-20617-7_100287","title":"Mechanical Machining","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Machining; Materials science; Mechanical engineering; Engineering","score_opus":0.008749046191773132,"score_gpt":0.2052125332014622,"score_spread":0.19646348700968908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251310814","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016243814,0.012022992,0.06384644,0.0005560674,0.0014259645,0.00006569133,0.00028076392,0.0008713439,0.91930646],"genre_scores_gemma":[0.008883296,0.0054924833,0.013726881,0.00022191607,0.000191885,0.000043883956,0.00036191047,0.00024547338,0.97083235],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961805,0.000015610296,0.000008918244,0.000075170115,0.00025745385,0.000024670366],"domain_scores_gemma":[0.9999125,0.000013771897,0.000004281313,0.000024079302,0.000039212286,0.0000061049805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021383147,0.0011763771,0.0006613567,0.0014022813,0.001042607,0.0014337752,0.0010198501,0.00085928495,0.077148125],"category_scores_gemma":[0.0003192526,0.00053623144,0.00038074364,0.0012081509,0.0008411923,0.0014690324,0.0013945684,0.001694271,0.04245597],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002685774,0.000041138388,0.0000972895,0.0004987152,0.000010557286,0.00006928581,0.0001788445,0.0021368163,0.013462998,0.099067025,0.16201168,0.7223988],"study_design_scores_gemma":[0.0000023505079,0.000019510355,0.00027735188,0.000102473896,0.0000043463465,0.00016727376,0.00002967946,0.0010676646,0.0040677134,0.014676653,0.9795752,0.000009845627],"about_ca_topic_score_codex":0.0009564223,"about_ca_topic_score_gemma":0.0036770708,"teacher_disagreement_score":0.077148125,"about_ca_system_score_codex":0.0006823972,"about_ca_system_score_gemma":0.00069299724,"threshold_uncertainty_score":0.2580862},"labels":[],"label_agreement":null},{"id":"W4251505201","doi":"10.1007/978-3-642-20617-7_100264","title":"Machine Tool Vibrations","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Vibration; Computer science; Physics; Acoustics","score_opus":0.006819120082696443,"score_gpt":0.19806333698907647,"score_spread":0.19124421690638002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251505201","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0057690437,0.011572741,0.27275115,0.00075055036,0.0023849222,0.000087957604,0.00033055726,0.0020403387,0.7043128],"genre_scores_gemma":[0.07396619,0.006960419,0.032886546,0.00045437104,0.0007126102,0.00010116412,0.0004664315,0.00070187805,0.88375044],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99952316,0.000031457508,0.000010592742,0.00008731607,0.00031896672,0.000028543045],"domain_scores_gemma":[0.99986005,0.000044158627,0.000009257828,0.000033869932,0.00004344624,0.000009095839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001836201,0.0008835345,0.0005954181,0.000885221,0.00051088794,0.0012145235,0.0008807606,0.0011197525,0.04693107],"category_scores_gemma":[0.00048782598,0.00041050813,0.00038534641,0.000679565,0.0007198841,0.0011354857,0.0012242928,0.0014132687,0.017437434],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007290786,0.000045561002,0.00016205315,0.00042017637,0.000015137785,0.00012877503,0.00025657474,0.006179333,0.039299462,0.073704384,0.05691404,0.8228017],"study_design_scores_gemma":[0.000013746614,0.00010902385,0.001331613,0.000285113,0.000018097971,0.0005962014,0.00012934265,0.011213248,0.018810812,0.048143417,0.91930664,0.000042675463],"about_ca_topic_score_codex":0.00031671004,"about_ca_topic_score_gemma":0.0006495478,"teacher_disagreement_score":0.04693107,"about_ca_system_score_codex":0.00039606684,"about_ca_system_score_gemma":0.00033895794,"threshold_uncertainty_score":0.157},"labels":[],"label_agreement":null},{"id":"W4252677920","doi":"10.1007/978-3-662-53120-4_300279","title":"Gear Hobbing","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Hobbing; Computer science; Engineering; Mechanical engineering; Machining","score_opus":0.007910006939822604,"score_gpt":0.19259855582422414,"score_spread":0.18468854888440153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252677920","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006566626,0.0026070238,0.005591625,0.0002635166,0.00083543785,0.000033675162,0.00013945818,0.00031388807,0.9895587],"genre_scores_gemma":[0.001877077,0.00096757815,0.0010782842,0.00010782719,0.000060328588,0.00001155803,0.00008882312,0.00010643456,0.9957021],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99976975,0.000015437055,0.0000069485104,0.000048046793,0.00013346435,0.000026399252],"domain_scores_gemma":[0.9999008,0.000016350848,0.0000037936727,0.00002261374,0.000042592783,0.000013892622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018823754,0.0009512591,0.0005319798,0.0015953743,0.0016570315,0.0022468762,0.00081468135,0.000992139,0.22596332],"category_scores_gemma":[0.00048859173,0.00039654438,0.00037958697,0.0009998888,0.0006418597,0.0015878523,0.0017174972,0.0013845797,0.13349582],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043746055,0.000052687865,0.0001295157,0.0002901242,0.000005185674,0.000117407064,0.00039963325,0.0003757155,0.003521601,0.07435642,0.32591748,0.59479046],"study_design_scores_gemma":[0.0000015758807,0.000010134253,0.00021152751,0.000085401945,0.0000020499292,0.00012920915,0.000064970685,0.00014466392,0.00052783155,0.005247681,0.9935707,0.0000041918215],"about_ca_topic_score_codex":0.001941063,"about_ca_topic_score_gemma":0.00813957,"teacher_disagreement_score":0.22596332,"about_ca_system_score_codex":0.00068681553,"about_ca_system_score_gemma":0.0006293671,"threshold_uncertainty_score":0.7559226},"labels":[],"label_agreement":null},{"id":"W4252798391","doi":"10.1007/978-3-662-53120-4_300146","title":"Cutting Tool","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science","score_opus":0.006627909727081416,"score_gpt":0.19196376432640957,"score_spread":0.18533585459932816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252798391","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012304011,0.0020355766,0.07860568,0.00021829647,0.0007852107,0.000117964446,0.0010781131,0.003298518,0.9126304],"genre_scores_gemma":[0.006105878,0.0013822505,0.019737843,0.00017424526,0.00007386717,0.00007101623,0.0016884999,0.00059835153,0.970168],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996088,0.000010144012,0.000009844861,0.00007833174,0.00026488217,0.000027893093],"domain_scores_gemma":[0.99986136,0.000016946322,0.0000065604177,0.000036922294,0.00006630407,0.000011866395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017816186,0.0012545065,0.0006820169,0.0019448502,0.0010054096,0.002012785,0.0014753788,0.001211809,0.21862765],"category_scores_gemma":[0.0003652998,0.0006547718,0.00053660874,0.001647652,0.00038912802,0.0014579612,0.0013298994,0.0015796188,0.14237449],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057370817,0.00005985184,0.000102969294,0.00041166905,0.000009438542,0.00012433695,0.000109938235,0.0016903381,0.02009828,0.056394365,0.2037527,0.7171887],"study_design_scores_gemma":[0.0000060057,0.00003263622,0.00022369847,0.00006664598,0.0000067640553,0.00032327895,0.000024622123,0.0013584316,0.006146014,0.0056711906,0.9861267,0.000014125711],"about_ca_topic_score_codex":0.0010415065,"about_ca_topic_score_gemma":0.0024719234,"teacher_disagreement_score":0.21862765,"about_ca_system_score_codex":0.00045386425,"about_ca_system_score_gemma":0.0006427673,"threshold_uncertainty_score":0.73138237},"labels":[],"label_agreement":null},{"id":"W4253151246","doi":"10.1007/978-3-662-53120-4_300141","title":"Cutting of Carbon Steel","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Materials science","score_opus":0.007783765957939534,"score_gpt":0.19851348876177038,"score_spread":0.19072972280383085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253151246","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021901964,0.025937956,0.020372164,0.0006766612,0.0022684091,0.000051528335,0.00017957322,0.0002484649,0.94807494],"genre_scores_gemma":[0.011391512,0.014260979,0.008661055,0.0002822477,0.00033693036,0.000024001281,0.0003367511,0.00011392566,0.9645925],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99981827,0.000007691379,0.000003304578,0.00002575495,0.00013166133,0.000013277453],"domain_scores_gemma":[0.9999479,0.000010269663,0.0000026601035,0.00000789446,0.000026497619,0.000004880963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001014627,0.00071146386,0.00035440864,0.0013201733,0.0006822086,0.0009094948,0.0005023578,0.00065905665,0.0290031],"category_scores_gemma":[0.00016808556,0.00028829568,0.0002995395,0.001115223,0.00047915496,0.0006982213,0.0005869416,0.0012772608,0.010530522],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028786983,0.00004428764,0.000082879196,0.0006890359,0.000010567085,0.00009881696,0.0001416322,0.002354818,0.014787017,0.13708398,0.20086744,0.6438108],"study_design_scores_gemma":[0.0000020858372,0.000025308445,0.0004803226,0.0001347292,0.000003608275,0.00024967323,0.00002705832,0.0010865607,0.004707582,0.019410644,0.97386336,0.000009070873],"about_ca_topic_score_codex":0.0020795895,"about_ca_topic_score_gemma":0.005752788,"teacher_disagreement_score":0.0290031,"about_ca_system_score_codex":0.0007855046,"about_ca_system_score_gemma":0.0006259063,"threshold_uncertainty_score":0.0970251},"labels":[],"label_agreement":null},{"id":"W4253523609","doi":"10.1007/978-3-642-20617-7_100305","title":"Micro-milling","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Materials science; Business","score_opus":0.006960401319764878,"score_gpt":0.18818789553300555,"score_spread":0.18122749421324066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253523609","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022841156,0.016128737,0.10954252,0.0005461584,0.0015815498,0.00009790754,0.00039061558,0.0016695368,0.86775875],"genre_scores_gemma":[0.013274019,0.0077144713,0.027204826,0.00026700128,0.00023065817,0.000064565764,0.00049782626,0.00040786454,0.9503389],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995858,0.000012558907,0.000010439479,0.000082942635,0.00027961176,0.000028552267],"domain_scores_gemma":[0.99990284,0.000017555558,0.0000055733244,0.000027769816,0.00003927362,0.0000070135393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018140339,0.0010658975,0.00068566616,0.0012892724,0.0008450779,0.0017914966,0.0010840963,0.0007830171,0.07572381],"category_scores_gemma":[0.000311646,0.0005462507,0.00039347206,0.0014435394,0.0006708618,0.001612473,0.0014318356,0.0016954836,0.035085205],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003607348,0.000036789843,0.00009180246,0.00043294474,0.0000106205025,0.000080193415,0.00013617522,0.001628252,0.01874495,0.09333126,0.11001387,0.7754571],"study_design_scores_gemma":[0.0000040043014,0.000025372243,0.00030306383,0.00009590628,0.000006603034,0.00025921827,0.000034067343,0.0014962938,0.010305598,0.0151237175,0.9723302,0.000015850283],"about_ca_topic_score_codex":0.0008113164,"about_ca_topic_score_gemma":0.0029338342,"teacher_disagreement_score":0.07572381,"about_ca_system_score_codex":0.0006456179,"about_ca_system_score_gemma":0.00064961653,"threshold_uncertainty_score":0.2533214},"labels":[],"label_agreement":null},{"id":"W4255133390","doi":"10.1007/978-3-662-53120-4_300629","title":"Slot Milling","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Materials science","score_opus":0.008265805425631295,"score_gpt":0.188125571763808,"score_spread":0.1798597663381767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255133390","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042484803,0.004894172,0.066890836,0.000256589,0.0011258308,0.00007754863,0.00048531682,0.0018034922,0.9202177],"genre_scores_gemma":[0.014937202,0.002234207,0.016366959,0.000120408935,0.00009382404,0.000026430616,0.00053900486,0.0003180605,0.9653639],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997614,0.0000072423904,0.0000060172856,0.00005751086,0.00014200206,0.000025989555],"domain_scores_gemma":[0.9999305,0.0000095746755,0.0000039456877,0.000018169909,0.000031382988,0.00000643612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015229099,0.00073742296,0.0005309623,0.0010205703,0.00086761144,0.00164274,0.00072468974,0.0005714426,0.09087378],"category_scores_gemma":[0.00019970704,0.0004670833,0.0003312224,0.0014045547,0.0005316153,0.0010624952,0.00084571633,0.0013022888,0.0381822],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000918795,0.00005218005,0.00014053818,0.0003795131,0.0000073089823,0.00010364443,0.00019602494,0.0012238871,0.028466614,0.06890513,0.12682755,0.77360576],"study_design_scores_gemma":[0.000006224331,0.00004637091,0.0005199672,0.00005239431,0.000005849069,0.00032382226,0.000065029715,0.0014774436,0.010493739,0.008137266,0.9788576,0.000014298572],"about_ca_topic_score_codex":0.00072428025,"about_ca_topic_score_gemma":0.002860496,"teacher_disagreement_score":0.09087378,"about_ca_system_score_codex":0.00042427448,"about_ca_system_score_gemma":0.0005234727,"threshold_uncertainty_score":0.30400306},"labels":[],"label_agreement":null},{"id":"W4255453034","doi":"10.1007/978-3-662-53120-4_300364","title":"Laser-Assisted Milling","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Materials science; Laser; Optics; Physics","score_opus":0.011198940387291263,"score_gpt":0.20212165587836722,"score_spread":0.19092271549107595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255453034","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026678322,0.021516452,0.08623205,0.00038039815,0.0013145725,0.000102708225,0.00031519216,0.0013312263,0.88613963],"genre_scores_gemma":[0.011585079,0.009208875,0.021446127,0.0001887,0.00014989954,0.00005084098,0.00035145893,0.00023483805,0.95678425],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996283,0.000012807618,0.000008105938,0.00005666874,0.00027087532,0.000023281436],"domain_scores_gemma":[0.9999387,0.000012950936,0.000003969101,0.000015663178,0.00002481199,0.0000039799224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015046823,0.00074044743,0.00057103613,0.0011705668,0.0007334523,0.0017326262,0.0010000984,0.00076416094,0.047126118],"category_scores_gemma":[0.00019522334,0.00044304755,0.0003363903,0.0016631063,0.00056652864,0.001273961,0.0011274118,0.0013825465,0.026257234],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038163278,0.000051570292,0.000063907435,0.0005500386,0.000011780238,0.000083224644,0.00014714737,0.0019543532,0.028733157,0.08508264,0.10567827,0.7776057],"study_design_scores_gemma":[0.0000041066646,0.000029349583,0.00031385233,0.00009994291,0.0000057289058,0.00027425744,0.000032696767,0.0018438,0.0098113,0.011395698,0.97617334,0.000015885758],"about_ca_topic_score_codex":0.00071837305,"about_ca_topic_score_gemma":0.002671039,"teacher_disagreement_score":0.047126118,"about_ca_system_score_codex":0.0005914431,"about_ca_system_score_gemma":0.00055626675,"threshold_uncertainty_score":0.15765256},"labels":[],"label_agreement":null},{"id":"W4256097736","doi":"10.1007/978-3-642-20617-7_100261","title":"Machinability of Non-rusting Steel","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Machinability; Materials science; Metallurgy; Geology; Machining","score_opus":0.007070345003872312,"score_gpt":0.21269535532403555,"score_spread":0.20562501032016323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256097736","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030135458,0.02256623,0.110667005,0.0009559834,0.0011169302,0.000057185753,0.00016650424,0.00034833103,0.83398634],"genre_scores_gemma":[0.31569073,0.02209931,0.032311887,0.0003227772,0.00077928195,0.00009691501,0.0005114502,0.000602707,0.62758493],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996681,0.00003218563,0.0000092455175,0.00004330059,0.00022629174,0.000020766143],"domain_scores_gemma":[0.9998267,0.00007286244,0.000011156674,0.000035090718,0.000046895526,0.000007274409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022861498,0.000597447,0.0004833314,0.0005372308,0.00041366354,0.0009970032,0.001118768,0.00055985607,0.014045509],"category_scores_gemma":[0.0005687792,0.00040102564,0.000509349,0.00033854521,0.000925202,0.0011642799,0.00064695696,0.0014969099,0.002464942],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007621932,0.000056454588,0.0001447853,0.0015629104,0.000027637527,0.0003886889,0.00043133364,0.021171367,0.07947048,0.66478807,0.028386738,0.20349535],"study_design_scores_gemma":[0.000023177516,0.00024259421,0.0016423257,0.0003347618,0.00002796878,0.0014507219,0.00010338679,0.036461543,0.044724666,0.46996582,0.44497728,0.00004572386],"about_ca_topic_score_codex":0.00029039997,"about_ca_topic_score_gemma":0.00052017305,"teacher_disagreement_score":0.014045509,"about_ca_system_score_codex":0.0005396496,"about_ca_system_score_gemma":0.00028871515,"threshold_uncertainty_score":0.046986878},"labels":[],"label_agreement":null},{"id":"W4280538857","doi":"10.18280/jesa.550206","title":"Ratio Study of High-Pressure Lubrication and Cutting Parameters Effects on Machining Operations and Its Effect Towards Sustainable Machining: A Review","year":2022,"lang":"en","type":"review","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Lubrication; Lubricant; Mechanical engineering; Surface roughness; Aerospace; Tool wear; Materials science; Manufacturing engineering; Process engineering; Engineering; Composite material","score_opus":0.01989965335335892,"score_gpt":0.29438197588262793,"score_spread":0.274482322529269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280538857","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007948857,0.9983108,0.00017129394,0.000082796,0.00006261846,0.0000049267464,0.000024231456,0.0000048894412,0.0005435981],"genre_scores_gemma":[0.003934881,0.9952779,0.0002469748,0.00007507579,0.000069335365,0.000008359633,0.000038885264,0.0000021871388,0.0003465297],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99970466,0.000044822253,0.000061990235,0.000062839026,0.00010349186,0.000022220516],"domain_scores_gemma":[0.9988563,0.00065285276,0.00021178438,0.000020891326,0.00022187618,0.000036333935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006681825,0.0007364678,0.0012639271,0.0022856893,0.00025720106,0.0010335462,0.0006704406,0.0008138383,0.001868255],"category_scores_gemma":[0.0011787103,0.00036313024,0.00082482904,0.0028262215,0.00029096476,0.001269951,0.00036735993,0.0005387505,0.00050938805],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002013765,0.00020988123,0.0008941005,0.16869943,0.00052281696,0.0003000817,0.00026546256,0.0011725174,0.0107070925,0.0032456615,0.012628926,0.80115265],"study_design_scores_gemma":[0.00003501515,0.00089199905,0.0048379423,0.018376669,0.0023214216,0.0020073291,0.0003218871,0.00081494194,0.011609023,0.0016463331,0.95704985,0.000087618595],"about_ca_topic_score_codex":0.0012774402,"about_ca_topic_score_gemma":0.0014806251,"teacher_disagreement_score":0.0022856893,"about_ca_system_score_codex":0.00033497723,"about_ca_system_score_gemma":0.001368235,"threshold_uncertainty_score":0.0062499046},"labels":[],"label_agreement":null},{"id":"W4280540352","doi":"10.1016/j.cirp.2022.04.045","title":"Influence of guideway friction on the cutting point receptance in machine tools","year":2022,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Actuator; Point (geometry); Servo; Engineering; Hammer; Inertial frame of reference; Control theory (sociology); Mechanical engineering; Computer science; Control engineering; Control (management); Mathematics; Physics","score_opus":0.024710077023764383,"score_gpt":0.2574242040501905,"score_spread":0.23271412702642613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280540352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916849,0.00037316908,0.0048471065,0.00003133895,0.000019701749,0.0000062426748,0.00002482711,0.000076274046,0.002936388],"genre_scores_gemma":[0.9992772,0.000045152115,0.00022059142,0.0000023936934,0.0000013419543,0.0000012155615,0.000008208763,0.000014674902,0.00042922067],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996369,0.00010408216,0.000012033686,0.000054378335,0.00008014133,0.00011237717],"domain_scores_gemma":[0.9977055,0.0016209583,0.00018468554,0.000120594166,0.00025025252,0.0001179634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005986839,0.0003665314,0.00061668054,0.0006811,0.000552322,0.001216476,0.000447169,0.0007947054,0.0025043052],"category_scores_gemma":[0.004861956,0.00034657246,0.0003985093,0.0003770514,0.00070158846,0.0006708931,0.0005706939,0.00044547694,0.00042679047],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008996556,0.00044616612,0.019773908,0.00047969274,0.00009904289,0.0018944319,0.0005661687,0.6248691,0.29859942,0.004561407,0.00076975406,0.0389443],"study_design_scores_gemma":[0.00013471428,0.0033570204,0.05936744,0.00007598201,0.00018468623,0.0007709231,0.00058818853,0.7333887,0.19857484,0.0013248764,0.0020299384,0.00020268654],"about_ca_topic_score_codex":0.002369562,"about_ca_topic_score_gemma":0.0017863213,"teacher_disagreement_score":0.0025043052,"about_ca_system_score_codex":0.00042839628,"about_ca_system_score_gemma":0.00044298972,"threshold_uncertainty_score":0.00837779},"labels":[],"label_agreement":null},{"id":"W4280650559","doi":"10.1016/j.cirp.2022.04.063","title":"Orthogonal cutting mechanics of multi-directional carbon fiber reinforced polymer with interlaminar bonding effect","year":2022,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Chip formation; Carbon fiber reinforced polymer; Composite material; Fiber; Polymer; Chip; Structural engineering; Computer science; Machining; Tool wear; Engineering; Composite number","score_opus":0.011566037863089637,"score_gpt":0.2427814903123419,"score_spread":0.23121545244925226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280650559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9720596,0.00018921965,0.022571739,0.000036728776,0.000017960483,0.0000068255076,0.000014902947,0.000026805488,0.0050761676],"genre_scores_gemma":[0.9968251,0.00006643984,0.0022487566,0.000003539525,0.0000021675842,0.0000048086104,0.0000056543927,0.0000051449465,0.0008383927],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999318,0.000008383246,0.0000017675807,0.000014187944,0.000032401415,0.000011458506],"domain_scores_gemma":[0.99990094,0.000027518048,0.000032534794,0.000008969555,0.00002141312,0.000008558645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011468125,0.0001717819,0.00011060475,0.00022727164,0.00016739125,0.0002515,0.00021979008,0.0002617712,0.0007451416],"category_scores_gemma":[0.00022066421,0.0001321105,0.00012311626,0.0001673721,0.00024093282,0.00033289866,0.00019459668,0.00011244728,0.00007124528],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026002916,0.00022054672,0.0066761407,0.00018119666,0.00004154222,0.0004321139,0.00023100305,0.26850864,0.62904274,0.04344907,0.00054063275,0.050416313],"study_design_scores_gemma":[0.000009529608,0.00018103093,0.00713389,0.0000063363173,0.000016879885,0.00011852682,0.00006247438,0.9417486,0.048015546,0.0017954601,0.0008889885,0.000022747057],"about_ca_topic_score_codex":0.0004724102,"about_ca_topic_score_gemma":0.00081264536,"teacher_disagreement_score":0.0007451416,"about_ca_system_score_codex":0.00013935541,"about_ca_system_score_gemma":0.00024512675,"threshold_uncertainty_score":0.0024927855},"labels":[],"label_agreement":null},{"id":"W4281714846","doi":"10.21203/rs.3.rs-1678194/v1","title":"A Novel Elasto-Geometric Model Exploiting Loaded Circular Test on a Machine Tool","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Geometric mean; Mathematics; Range (aeronautics); Constant (computer programming); Variable (mathematics); Mean squared error; Geometric modeling; Mathematical analysis; Simulation; Geometry; Statistics; Computer science; Engineering","score_opus":0.06553588221850488,"score_gpt":0.345680273254693,"score_spread":0.28014439103618816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281714846","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09724559,0.00022373392,0.89459074,0.00015226542,0.000052176874,0.00012962466,0.0002875443,0.001135699,0.0061826613],"genre_scores_gemma":[0.95410603,0.00018016422,0.040069878,0.000050734943,0.000012095094,0.00017714061,0.00024244025,0.00009863959,0.0050628996],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996958,0.00005293508,0.000019406873,0.00008212088,0.000121078236,0.000028683962],"domain_scores_gemma":[0.99960846,0.00014146915,0.00008007435,0.00006374186,0.00008984655,0.000016452446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004071378,0.00063244393,0.00060575403,0.00052214344,0.00021752472,0.0007875139,0.0014550145,0.0017338952,0.0023721692],"category_scores_gemma":[0.0010098713,0.00034992298,0.0006616798,0.00036015682,0.0006050429,0.00063090754,0.0004894644,0.00048644267,0.000642672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058922164,0.000037075617,0.0010663073,0.00007044759,0.000022671717,0.00022314786,0.00004763187,0.97135496,0.013846611,0.0011247192,0.00016309693,0.011984478],"study_design_scores_gemma":[0.0000026488956,0.000030943236,0.00031454823,0.0000045557513,0.0000051432958,0.0000329038,0.0000044657995,0.9979346,0.0011753277,0.00017548901,0.0003124834,0.0000068550175],"about_ca_topic_score_codex":0.005614326,"about_ca_topic_score_gemma":0.0042982367,"teacher_disagreement_score":0.005614326,"about_ca_system_score_codex":0.00036601457,"about_ca_system_score_gemma":0.00066244137,"threshold_uncertainty_score":0.011163294},"labels":[],"label_agreement":null},{"id":"W4281715719","doi":"10.3390/ma15124059","title":"Tool Wear Prediction When Machining with Self-Propelled Rotary Tools","year":2022,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"King Abdulaziz City for Science and Technology","keywords":"Machining; Tool wear; Materials science; Mechanical engineering; Engineering; Engineering drawing; Manufacturing engineering","score_opus":0.006170982487425967,"score_gpt":0.17300621916217104,"score_spread":0.16683523667474506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281715719","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97811025,0.00018770911,0.021130387,0.000009437819,0.000007278724,0.000022162249,0.000036207784,0.0000967411,0.00039976498],"genre_scores_gemma":[0.9962451,0.00006906225,0.003406254,0.0000015792277,8.117175e-7,0.0000054028255,0.000026262893,0.0000034695477,0.0002419293],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997002,0.00003409102,0.00002037509,0.000047481102,0.00016145814,0.000036394056],"domain_scores_gemma":[0.9986344,0.0006637462,0.00026394293,0.000115447874,0.00029487704,0.00002760655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005724896,0.00043395095,0.00039233643,0.00056728296,0.00013769337,0.00039333123,0.0006851654,0.0006858426,0.0002958564],"category_scores_gemma":[0.0017967324,0.00021286502,0.00038876518,0.0003304396,0.0002449053,0.0003327378,0.00019461577,0.000230403,0.00009269819],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007818115,0.00025199231,0.03696146,0.0004862027,0.00006147096,0.00062367244,0.00030960105,0.6789787,0.1947098,0.00021961173,0.00021157756,0.086404145],"study_design_scores_gemma":[0.000011172684,0.0006510524,0.017416488,0.000011402437,0.000020749752,0.00011487732,0.00007074227,0.9271183,0.054306928,0.00007546559,0.00017983557,0.000022998393],"about_ca_topic_score_codex":0.002647841,"about_ca_topic_score_gemma":0.0032487167,"teacher_disagreement_score":0.002647841,"about_ca_system_score_codex":0.00021864737,"about_ca_system_score_gemma":0.00023345706,"threshold_uncertainty_score":0.0052648187},"labels":[],"label_agreement":null},{"id":"W4283218269","doi":"10.1109/iemtronics55184.2022.9795726","title":"Predictive Maintenance and Condition Monitoring in Machine Tools: An IoT Approach","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; McMaster University","funders":"","keywords":"Downtime; Predictive maintenance; Internet of Things; Computer science; Condition monitoring; Quality (philosophy); Reliability engineering; Preventive maintenance; Selection (genetic algorithm); Embedded system; Engineering; Machine learning","score_opus":0.015876606578894645,"score_gpt":0.25379008488924837,"score_spread":0.23791347831035373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283218269","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02085326,0.017931975,0.9204496,0.0024392158,0.00048204462,0.00016884283,0.000109828106,0.0007727756,0.036792457],"genre_scores_gemma":[0.6929953,0.016508846,0.2715224,0.0007688845,0.0007244103,0.00018486763,0.00014710244,0.00007852799,0.017069623],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960047,0.00005889711,0.000014294865,0.000062809835,0.00023788381,0.000025659669],"domain_scores_gemma":[0.9996227,0.00014143961,0.000059373386,0.00005708859,0.000102865364,0.000016558239],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000396004,0.0005493721,0.000349954,0.0012050432,0.0003182255,0.0013988687,0.00092369533,0.0010609935,0.001253874],"category_scores_gemma":[0.00069441495,0.00025736223,0.00040063116,0.0008282863,0.00073130365,0.0020478482,0.000575283,0.0006843654,0.00031049442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023306598,0.0003821857,0.005456936,0.0010873718,0.00017019693,0.0007869349,0.00050929206,0.10952213,0.08128923,0.15925911,0.0071554445,0.6341481],"study_design_scores_gemma":[0.000034346056,0.00061034766,0.0080002425,0.00051547715,0.00017134585,0.001277441,0.0005822687,0.7485462,0.040174272,0.119867496,0.08008229,0.0001383307],"about_ca_topic_score_codex":0.00081522024,"about_ca_topic_score_gemma":0.0008952824,"teacher_disagreement_score":0.0013988687,"about_ca_system_score_codex":0.00061821565,"about_ca_system_score_gemma":0.00035519153,"threshold_uncertainty_score":0.004485488},"labels":[],"label_agreement":null},{"id":"W4283263415","doi":"10.1007/s40799-022-00590-5","title":"In-Process Frequency Response Function Measurement for Robotic Milling","year":2022,"lang":"en","type":"article","venue":"Experimental Techniques","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Research Council Canada","keywords":"Frequency response; Machining; Vibration; Engineering; Dynamometer; Impulse response; Acoustics; Control theory (sociology); Mechanical engineering; Structural engineering; Computer science; Mathematics; Artificial intelligence","score_opus":0.020616348512509985,"score_gpt":0.2867678073756837,"score_spread":0.2661514588631737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283263415","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5844,0.0013080053,0.40088034,0.00031536235,0.0001520677,0.00011960145,0.00043493818,0.002131178,0.010258514],"genre_scores_gemma":[0.9567367,0.00014260091,0.04004788,0.000065418026,0.000024914252,0.00003225946,0.00014233706,0.00011011297,0.0026979228],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992035,0.00013634546,0.000019742996,0.00011790683,0.00046198242,0.000060543392],"domain_scores_gemma":[0.99916136,0.00034826488,0.00012617963,0.00010895055,0.00022706726,0.000028248667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005325792,0.0004909105,0.00038634654,0.0004665916,0.000362649,0.0005415368,0.00075216306,0.000840042,0.00285442],"category_scores_gemma":[0.0010572668,0.00023931648,0.00015447718,0.00040704178,0.0002822587,0.00065646606,0.00033741203,0.00037373597,0.0008688378],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007707528,0.00016470897,0.0018848066,0.00020869252,0.000024833302,0.00005840228,0.00010659896,0.0022411335,0.9205862,0.0005516215,0.0006881339,0.07271409],"study_design_scores_gemma":[0.000041585386,0.0006941042,0.013939029,0.000020746571,0.000034465305,0.0003075855,0.000077635734,0.03753645,0.9398676,0.0003489268,0.007097165,0.000034680343],"about_ca_topic_score_codex":0.0003995548,"about_ca_topic_score_gemma":0.0007625068,"teacher_disagreement_score":0.00285442,"about_ca_system_score_codex":0.00034030052,"about_ca_system_score_gemma":0.00025704002,"threshold_uncertainty_score":0.009548962},"labels":[],"label_agreement":null},{"id":"W4283380302","doi":"10.3390/coatings12070892","title":"Vibration-Based System Degradation Monitoring under Gear Wear Progression","year":2022,"lang":"en","type":"article","venue":"Coatings","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Vibration; Degradation (telecommunications); Automotive engineering; Materials science; Computer science; Structural engineering; Acoustics; Engineering; Physics; Telecommunications","score_opus":0.010693745135205738,"score_gpt":0.23996744752115273,"score_spread":0.229273702385947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283380302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9413332,0.0009635086,0.051989526,0.000108522356,0.000087153436,0.000048902773,0.0005791216,0.0013756708,0.0035143357],"genre_scores_gemma":[0.9971795,0.00007521127,0.002026773,0.000018280749,0.000009253821,0.000008036617,0.00009434668,0.000013008504,0.0005755196],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997392,0.000029726121,0.000013129589,0.00006525521,0.00012275558,0.000029875899],"domain_scores_gemma":[0.99968684,0.0000847645,0.00006183928,0.00002961379,0.000115958486,0.000021013644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024179442,0.00028749747,0.00030921886,0.00053799845,0.00018007161,0.00028716685,0.00030509374,0.00045970365,0.0015373783],"category_scores_gemma":[0.00066555355,0.0000859068,0.00010361542,0.00029126534,0.00015144776,0.00031900706,0.00022748607,0.00021990451,0.00042597635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001624562,0.00019596751,0.039419018,0.00056410796,0.000116997806,0.0004681823,0.0005684567,0.017831437,0.7584735,0.00024692796,0.0023480393,0.1781428],"study_design_scores_gemma":[0.000058873276,0.0022486004,0.31644627,0.00008510608,0.00014222594,0.0014217311,0.00049545855,0.3377586,0.33709615,0.00059658877,0.003539075,0.0001113279],"about_ca_topic_score_codex":0.0008618076,"about_ca_topic_score_gemma":0.000982878,"teacher_disagreement_score":0.0015373783,"about_ca_system_score_codex":0.00015886736,"about_ca_system_score_gemma":0.000092515744,"threshold_uncertainty_score":0.0051430464},"labels":[],"label_agreement":null},{"id":"W4283588664","doi":"10.11159/ffhmt22.139","title":"Numerical Investigation on Evolving Chip Geometry and Its Impact on Convective Heat Transfer during Orthogonal Cutting Processes","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Convective heat transfer; Convection; Heat transfer; Chip; Mechanics; Materials science; Geometry; Mechanical engineering; Computer science; Physics; Engineering; Mathematics; Telecommunications","score_opus":0.01548562747169362,"score_gpt":0.23695021961376345,"score_spread":0.22146459214206982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283588664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9893657,0.00014432835,0.007812737,0.000056798228,0.000023772323,0.000018252771,0.00007472618,0.00007740583,0.0024263128],"genre_scores_gemma":[0.9973718,0.000056961726,0.0021818967,0.0000055686187,0.0000025997292,0.000007160129,0.00003265579,0.000010741372,0.0003305972],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988675,0.000021121128,0.0000053844365,0.000022062,0.00003353598,0.000031211577],"domain_scores_gemma":[0.99932957,0.00041068185,0.00008931886,0.000055399243,0.000079739766,0.00003531119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032710368,0.00026022887,0.00029247638,0.00033197226,0.00026817585,0.0005774279,0.00031629123,0.0005283411,0.00097379053],"category_scores_gemma":[0.001650256,0.00015244355,0.00022336376,0.00031532714,0.0005497592,0.0002509675,0.00023140803,0.0002330805,0.000088591536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004205996,0.0002924075,0.012655185,0.0001679818,0.000026078376,0.0004799158,0.00032955926,0.8380557,0.12508863,0.0026659283,0.0005224432,0.01929553],"study_design_scores_gemma":[0.000014424371,0.00019677955,0.0057268627,0.0000069628013,0.00001069555,0.000066761386,0.000076733275,0.9771778,0.016220009,0.00017267508,0.0003145074,0.000015705482],"about_ca_topic_score_codex":0.0020287277,"about_ca_topic_score_gemma":0.0015481049,"teacher_disagreement_score":0.0020287277,"about_ca_system_score_codex":0.00026231608,"about_ca_system_score_gemma":0.0002943694,"threshold_uncertainty_score":0.004033804},"labels":[],"label_agreement":null},{"id":"W4283713723","doi":"10.1007/s00170-022-09592-4","title":"A comparative analysis of chip shape, residual stresses, and surface roughness in minimum-quantity-lubrication turning with various flow rates","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Surface roughness; Volumetric flow rate; Lubrication; Materials science; Flow (mathematics); Surface (topology); Surface finish; Geometry; Composite material; Engineering drawing; Mathematics; Physics; Mechanics; Engineering","score_opus":0.008722117511202034,"score_gpt":0.2588786960167324,"score_spread":0.25015657850553036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283713723","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99796605,0.00015142231,0.0014190524,0.000007956481,0.0000052944806,0.0000034433415,0.000035904883,0.000040718474,0.00037012703],"genre_scores_gemma":[0.9994429,0.000033265434,0.00033407848,0.0000019448973,0.000001237481,0.0000015409075,0.00003618195,0.000006553489,0.00014233612],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998124,0.00002097484,0.000009102069,0.000031203635,0.00008360422,0.000042869786],"domain_scores_gemma":[0.9989152,0.0005436466,0.00010744731,0.00007805196,0.00030577465,0.000049907063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036442588,0.000178879,0.0004125202,0.0005614097,0.00027058827,0.0003278308,0.0002583099,0.00032342816,0.0009113394],"category_scores_gemma":[0.0009183773,0.00017429836,0.0004300208,0.00037692845,0.00034795864,0.00027971825,0.0000956535,0.00016141462,0.000095770505],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033006854,0.00013433906,0.019216083,0.00020480882,0.000059425853,0.00035924435,0.0003177491,0.019177191,0.9204532,0.00036167266,0.0002749375,0.036140695],"study_design_scores_gemma":[0.00007141655,0.0026830293,0.20358402,0.000014358618,0.00020212904,0.0004950946,0.00039779866,0.08773359,0.7035913,0.00020588857,0.0009362965,0.0000851412],"about_ca_topic_score_codex":0.0014111506,"about_ca_topic_score_gemma":0.0026150753,"teacher_disagreement_score":0.0014111506,"about_ca_system_score_codex":0.00021250772,"about_ca_system_score_gemma":0.00018872619,"threshold_uncertainty_score":0.0030486584},"labels":[],"label_agreement":null},{"id":"W4284688094","doi":"10.1016/j.jsv.2022.117158","title":"Finite-amplitude stability in regenerative chatter: The effect of process damping nonlinearity and intermittent cutting in turning","year":2022,"lang":"en","type":"article","venue":"Journal of Sound and Vibration","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vibration; Amplitude; Bifurcation; Nonlinear system; Machining; Limit (mathematics); Limit cycle; Control theory (sociology); Mechanics; Engineering; Structural engineering; Physics; Mathematics; Mechanical engineering; Acoustics; Mathematical analysis; Computer science; Optics","score_opus":0.010758151604139739,"score_gpt":0.2609956122639031,"score_spread":0.2502374606597634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284688094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8798357,0.0004091301,0.11333072,0.0002071809,0.000054332464,0.000015027971,0.000018037263,0.00013444234,0.005995439],"genre_scores_gemma":[0.9990822,0.000024990773,0.00049123314,0.000004565691,0.0000034433845,0.0000026483453,0.0000024390301,0.0000069052326,0.0003816084],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998404,0.000055988046,0.000007035824,0.000022182878,0.000048206155,0.000026241445],"domain_scores_gemma":[0.99791783,0.0015844272,0.00014430068,0.00007942758,0.00019206789,0.0000818977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052720826,0.0002786976,0.0003554537,0.00031267304,0.00031796197,0.0004982017,0.00055927795,0.0006434694,0.0014917672],"category_scores_gemma":[0.0031725892,0.00024268917,0.00034378323,0.00010088712,0.0011305667,0.00059544086,0.0004704682,0.00051565823,0.000095560696],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012744576,0.00024208824,0.0069677415,0.0004261617,0.00012505255,0.0020882802,0.0013295719,0.73072726,0.1810087,0.046027858,0.0005840278,0.02919878],"study_design_scores_gemma":[0.000012511921,0.00007467688,0.0019422056,0.000011643235,0.000014050906,0.00013528336,0.000074420575,0.990781,0.003944833,0.0029112364,0.00008165796,0.000016520355],"about_ca_topic_score_codex":0.0014052251,"about_ca_topic_score_gemma":0.0013663743,"teacher_disagreement_score":0.0014917672,"about_ca_system_score_codex":0.00025699174,"about_ca_system_score_gemma":0.00024156584,"threshold_uncertainty_score":0.004990399},"labels":[],"label_agreement":null},{"id":"W4284896313","doi":"10.18280/acsm.460303","title":"Optimization of Machining Parameters in Drilling of Glass/Hemp/Bamboo Fibres Based Hybrid Polymer Composites","year":2022,"lang":"en","type":"article","venue":"Annales de Chimie Science des Matériaux","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Delamination (geology); Taguchi methods; Materials science; Composite material; Machining; Grey relational analysis; Drilling; Drill; Surface roughness; Composite number; Orthogonal array; Composite laminates; Mathematics; Geology","score_opus":0.01702345653612879,"score_gpt":0.24230962765849856,"score_spread":0.22528617112236976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284896313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954678,0.0012194345,0.0025803763,0.000022210656,0.000010553869,0.000020427957,0.00007300736,0.000024856849,0.0005812575],"genre_scores_gemma":[0.99299264,0.00064944004,0.0059704254,0.000006043456,0.0000024248852,0.000017790864,0.000054111515,0.000012935306,0.00029424226],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978226,0.000035614208,0.000025732614,0.000037632177,0.00008661383,0.00003214013],"domain_scores_gemma":[0.9996767,0.00011278707,0.00013346948,0.000013883773,0.00004496717,0.000018268385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003714968,0.00038991225,0.0003088812,0.00036100452,0.00016569068,0.00033092414,0.00016243225,0.0002603862,0.00043683883],"category_scores_gemma":[0.00047095818,0.00021977563,0.00023411571,0.0003021389,0.0001361064,0.0002817473,0.00015101688,0.00029650444,0.00013604775],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024787962,0.00007091441,0.0007349244,0.00027553466,0.000008742503,0.00008648833,0.00006337762,0.0023049966,0.9903832,0.000030484349,0.000030173449,0.005763234],"study_design_scores_gemma":[0.000011392751,0.0011765349,0.009146392,0.000023386263,0.000031726973,0.000085378684,0.000094721145,0.0050974214,0.98354197,0.000040320803,0.00073300244,0.000017729339],"about_ca_topic_score_codex":0.0003813121,"about_ca_topic_score_gemma":0.0015740403,"teacher_disagreement_score":0.00043683883,"about_ca_system_score_codex":0.00012268955,"about_ca_system_score_gemma":0.00015366214,"threshold_uncertainty_score":0.0019646883},"labels":[],"label_agreement":null},{"id":"W4285161620","doi":"10.1016/j.procir.2022.03.066","title":"Effect of Chip Segmentation on Machining-Induced Residual Stresses during Turning of Ti6Al4V","year":2022,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; ArcelorMittal (Canada); National Research Council Canada; Polytechnique Montréal","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Residual stress; Chip formation; Segmentation; Chip; Surface integrity; Materials science; Finite element method; Residual; Structural engineering; Titanium alloy; Vibration; Mechanical engineering; Tool wear; Engineering; Composite material; Metallurgy; Computer science; Artificial intelligence; Acoustics; Alloy; Physics; Algorithm","score_opus":0.005015013329562401,"score_gpt":0.23550658164220312,"score_spread":0.23049156831264073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285161620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99851865,0.00007950944,0.0010477215,0.000005582167,0.0000050154367,0.0000055977334,0.000018622704,0.000024937144,0.0002944534],"genre_scores_gemma":[0.9995185,0.000021279755,0.00037657033,0.0000032468536,8.984377e-7,0.0000026392154,0.000016629685,0.000004612668,0.00005558114],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999861,0.000013813516,0.00000752232,0.0000227752,0.00005359014,0.000041204312],"domain_scores_gemma":[0.9995844,0.00022841097,0.000072731214,0.000031131163,0.00005990094,0.000023514345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016292614,0.00026103944,0.0002593622,0.00018400935,0.00018620942,0.00023763462,0.00023985856,0.00028723612,0.0005524131],"category_scores_gemma":[0.0004749654,0.0001861599,0.00020165415,0.00014100861,0.00035680953,0.00015987488,0.00012402958,0.00019494265,0.000064509964],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080515153,0.0000972478,0.004597365,0.00013482863,0.00003095616,0.00028856585,0.00024840632,0.03343683,0.9510323,0.00012188677,0.00007907827,0.009127344],"study_design_scores_gemma":[0.000033817698,0.0024136472,0.056560207,0.000016950156,0.00005850652,0.00021614354,0.00023896042,0.114525825,0.8252207,0.00009803802,0.0005747775,0.00004229971],"about_ca_topic_score_codex":0.0010694799,"about_ca_topic_score_gemma":0.0024881363,"teacher_disagreement_score":0.0010694799,"about_ca_system_score_codex":0.00022223023,"about_ca_system_score_gemma":0.00020936501,"threshold_uncertainty_score":0.002126515},"labels":[],"label_agreement":null},{"id":"W4285285719","doi":"10.5267/j.esm.2022.4.002","title":"Experimental investigation into the performance of cutting betel nut machine via response surface methodology and desirability function","year":2022,"lang":"en","type":"article","venue":"Engineering Solid Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Nut; Response surface methodology; Central composite design; Betel; Water content; Rotational speed; Materials science; Moisture; Composite material; Mathematics; Mechanical engineering; Engineering; Statistics","score_opus":0.01704412189732983,"score_gpt":0.2419620319956747,"score_spread":0.2249179100983449,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285285719","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9626133,0.00035269838,0.035377994,0.00004217265,0.000025646128,0.00012813724,0.0001420558,0.0001573748,0.0011607395],"genre_scores_gemma":[0.9664827,0.00024038769,0.032087106,0.000016732421,0.0000050080735,0.00012542281,0.00011278611,0.000023621646,0.0009062563],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989311,0.00018324853,0.000090852176,0.00017326539,0.00053396914,0.00008759836],"domain_scores_gemma":[0.9989434,0.0003847453,0.00017364536,0.00013524055,0.00033653426,0.000026440168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016718887,0.00057161116,0.0005428898,0.0004034748,0.00023881867,0.00035822688,0.00063039333,0.00062411564,0.0008105009],"category_scores_gemma":[0.0015632125,0.00026025317,0.0005060061,0.0005202618,0.0002432934,0.00034187207,0.00022754549,0.0004142322,0.00020935283],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058469275,0.0003423217,0.0020897738,0.00041249,0.000027305972,0.00007751821,0.00018069148,0.010688862,0.9639574,0.00019159027,0.00009964068,0.021347735],"study_design_scores_gemma":[0.000038279893,0.0062450063,0.011239757,0.000018945115,0.000052807765,0.00010616757,0.00011241584,0.05329037,0.9275428,0.00012340861,0.0011895024,0.00004048414],"about_ca_topic_score_codex":0.00039118537,"about_ca_topic_score_gemma":0.0006637138,"teacher_disagreement_score":0.0016718887,"about_ca_system_score_codex":0.0001824134,"about_ca_system_score_gemma":0.0002100811,"threshold_uncertainty_score":0.008841932},"labels":[],"label_agreement":null},{"id":"W4285596786","doi":"10.3390/machines10070567","title":"Assessment of Surface Roughness in Milling of Beech Using a Response Surface Methodology and an Adaptive Network-Based Fuzzy Inference System","year":2022,"lang":"en","type":"article","venue":"Machines","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"National Natural Science Foundation of China","keywords":"Beech; Machining; Surface roughness; Rake angle; Smoothness; Surface finish; Adaptive neuro fuzzy inference system; Surface (topology); Materials science; Fuzzy logic; Work (physics); Computer science; Mechanical engineering; Engineering drawing; Process engineering; Mathematics; Composite material; Engineering; Fuzzy control system; Geometry; Metallurgy; Artificial intelligence; Mathematical analysis; Geography","score_opus":0.04989897628032902,"score_gpt":0.34267973583264083,"score_spread":0.2927807595523118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285596786","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55900174,0.00028398272,0.43933156,0.000051860476,0.000014740567,0.000070114584,0.000037111182,0.00021377979,0.0009950899],"genre_scores_gemma":[0.9668605,0.00005807026,0.032782648,0.00000840479,0.0000023824384,0.000027217267,0.00002187789,0.0000040929576,0.00023487682],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996948,0.00009637065,0.000017637178,0.00007221876,0.00009917806,0.000019849236],"domain_scores_gemma":[0.99965525,0.00019301519,0.000042369655,0.000019709245,0.00008102235,0.000008623168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065776025,0.0003123358,0.00030757705,0.00033427955,0.00015667774,0.00030955186,0.0002761421,0.00042929727,0.00028974286],"category_scores_gemma":[0.0008895798,0.00014783973,0.00034934437,0.00021328028,0.00018476466,0.0002500389,0.00015612952,0.00026346455,0.000046084086],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006319906,0.00022856158,0.011351872,0.0004149194,0.0001240043,0.00021102517,0.00022953635,0.55915314,0.24039054,0.0007643853,0.00020171123,0.18629839],"study_design_scores_gemma":[0.00001142917,0.0002478908,0.0074089034,0.000004909824,0.00002436628,0.00002556252,0.00003223298,0.97659236,0.015290368,0.00021134241,0.0001356001,0.000015113116],"about_ca_topic_score_codex":0.0031443,"about_ca_topic_score_gemma":0.004343198,"teacher_disagreement_score":0.0031443,"about_ca_system_score_codex":0.0002622118,"about_ca_system_score_gemma":0.00019787434,"threshold_uncertainty_score":0.006251991},"labels":[],"label_agreement":null},{"id":"W4285605961","doi":"10.1016/j.jmatprotec.2022.117723","title":"Predictive model of chip segmentation in machining of high-strength metallic alloys","year":2022,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Armed Forces; Innovation, Science and Economic Development Canada","keywords":"Materials science; Chip; Machining; Chip formation; Rake; Segmentation; Titanium alloy; Shear (geology); Structural engineering; Composite material; Mechanical engineering; Metallurgy; Computer science; Tool wear; Artificial intelligence; Engineering; Alloy","score_opus":0.008764338538995746,"score_gpt":0.23304494039959475,"score_spread":0.224280601860599,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285605961","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6553046,0.0010350955,0.33448943,0.00050247053,0.00010026191,0.000066840126,0.00033756337,0.00081536267,0.00734837],"genre_scores_gemma":[0.9955623,0.00006552122,0.0032636314,0.000018291405,0.000008058314,0.000015714524,0.000060682407,0.000016621716,0.0009890466],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987173,0.000030187559,0.0000050977033,0.00003413236,0.000025569396,0.000033145916],"domain_scores_gemma":[0.9991235,0.0006197131,0.00008983816,0.000037180514,0.000100916295,0.000028901424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047085472,0.00050920894,0.001017373,0.00045086278,0.0003666892,0.00083916046,0.0012016875,0.0013428829,0.001459287],"category_scores_gemma":[0.0013460906,0.0007140199,0.00049223186,0.0003776786,0.00072206254,0.000419304,0.0003444914,0.0007905252,0.00019160972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021450443,0.000011257631,0.00020949199,0.000008051945,0.000005166018,0.000009409674,0.0000046648565,0.9976284,0.0004081212,0.0003153647,0.000054708387,0.0013239746],"study_design_scores_gemma":[9.772223e-7,0.0000024565538,0.00007487909,3.689759e-7,7.4454834e-7,7.2906266e-7,4.6389664e-7,0.99978346,0.00006767215,0.000059368267,0.000008243762,5.817541e-7],"about_ca_topic_score_codex":0.021766692,"about_ca_topic_score_gemma":0.016237568,"teacher_disagreement_score":0.021766692,"about_ca_system_score_codex":0.0010543067,"about_ca_system_score_gemma":0.0010097933,"threshold_uncertainty_score":0.043280005},"labels":[],"label_agreement":null},{"id":"W4286489409","doi":"10.21203/rs.3.rs-1863221/v1","title":"Modelling forces in milling screw rotors","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Vanderbilt Memory and Alzheimer's Center","keywords":"Mechanical engineering; Engineering; Nanotechnology; Materials science","score_opus":0.06649405632670329,"score_gpt":0.37294644368283414,"score_spread":0.30645238735613084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286489409","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3145607,0.0013634517,0.65049195,0.00055063056,0.00026043877,0.00013342199,0.00027437785,0.0004972745,0.031867806],"genre_scores_gemma":[0.9609012,0.00040814755,0.028256623,0.000036476522,0.000046198456,0.00007048537,0.00012119642,0.00014387463,0.010015755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977833,0.00006808713,0.00001152147,0.000037073056,0.000073793155,0.000031193827],"domain_scores_gemma":[0.99948645,0.00034684766,0.000051452676,0.00002701382,0.00006226819,0.000025866997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039595284,0.00086803763,0.0007894984,0.00063224597,0.00048916094,0.001261443,0.0008910372,0.0021699623,0.003420444],"category_scores_gemma":[0.0016442804,0.00067230477,0.00076027925,0.0005262756,0.0008024903,0.0008235419,0.00058159366,0.00069850456,0.00044308053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024332065,0.00001671239,0.00016402379,0.00002939091,0.000008757681,0.000027823013,0.000017475475,0.99149805,0.0012880326,0.0037183636,0.000107454085,0.0030996324],"study_design_scores_gemma":[0.000005881275,0.0000092245355,0.00009332511,0.0000026443713,0.0000015853757,0.00000372219,0.0000043449713,0.9984863,0.00021246845,0.0009745389,0.00020402261,0.0000019956212],"about_ca_topic_score_codex":0.011081348,"about_ca_topic_score_gemma":0.0074017453,"teacher_disagreement_score":0.011081348,"about_ca_system_score_codex":0.00059855235,"about_ca_system_score_gemma":0.0006609468,"threshold_uncertainty_score":0.022033691},"labels":[],"label_agreement":null},{"id":"W4288463478","doi":"10.18280/ts.390325","title":"Multi-Scale Edge Detection of Crack in Extra-High Arch Dam Based on Orthogonal Wavelet Construction","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Wavelet; Biorthogonal wavelet; Wavelet packet decomposition; Mathematics; Cascade algorithm; Stationary wavelet transform; Algorithm; Wavelet transform; Lifting scheme; Edge detection; Filter (signal processing); Curvelet; Undercut; Artificial intelligence; Computer vision; Computer science; Image (mathematics); Image processing; Structural engineering; Engineering","score_opus":0.010700268035052448,"score_gpt":0.21855590682224893,"score_spread":0.20785563878719648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288463478","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14825688,0.00012536948,0.8504723,0.00004283459,0.0000122532865,0.000017463164,0.00002028616,0.00015585129,0.00089668046],"genre_scores_gemma":[0.73445624,0.00020313823,0.2642973,0.000015773321,0.00001005553,0.000020747939,0.000048826038,0.000040588027,0.0009073548],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999845,0.000021658863,0.0000067159735,0.000035946865,0.00007259521,0.000018114408],"domain_scores_gemma":[0.99978215,0.00007591467,0.00003396277,0.00002498113,0.000068370566,0.000014574895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028975806,0.00024654905,0.00028558166,0.00081728573,0.00015438722,0.0003365677,0.00030680007,0.0003179368,0.0005579939],"category_scores_gemma":[0.0008401149,0.00016999588,0.0003611281,0.00043851184,0.0003141042,0.00090234214,0.00036907595,0.00027839278,0.00009700156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004107811,0.00010357646,0.008964809,0.0002641882,0.00005849821,0.00034414933,0.0003973253,0.11999147,0.37885976,0.01943875,0.0008387642,0.47032803],"study_design_scores_gemma":[0.000010433353,0.00008534565,0.0049590296,0.000009737428,0.000022789212,0.00016956443,0.000058162113,0.9565429,0.034863908,0.0024604946,0.00079746376,0.000020122365],"about_ca_topic_score_codex":0.0006578721,"about_ca_topic_score_gemma":0.0007944858,"teacher_disagreement_score":0.00081728573,"about_ca_system_score_codex":0.00017772768,"about_ca_system_score_gemma":0.0002271382,"threshold_uncertainty_score":0.0018666387},"labels":[],"label_agreement":null},{"id":"W4291971987","doi":"10.1007/s00170-022-09894-7","title":"Tool health monitoring and prediction via attention-based encoder-decoder with a multi-step mechanism","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Science Foundation of Hebei Province; National Natural Science Foundation of China","keywords":"Tool wear; Encoder; Artificial neural network; Mechanism (biology); Computer science; Focus (optics); Moment (physics); Artificial intelligence; Data mining; Engineering; Real-time computing; Machining; Mechanical engineering","score_opus":0.007038074947985553,"score_gpt":0.23708935194399297,"score_spread":0.23005127699600741,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4291971987","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043080486,0.00077420246,0.94924486,0.00018739079,0.00020492425,0.0000985262,0.00030978658,0.0042608357,0.0018389195],"genre_scores_gemma":[0.7654026,0.00038697576,0.22850774,0.00027980257,0.000102785576,0.00012751059,0.00053617853,0.00015346734,0.0045029647],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963737,0.000025169935,0.000025556405,0.00014117836,0.00012065471,0.000050230505],"domain_scores_gemma":[0.9993511,0.0002274641,0.00006813006,0.00008708292,0.00022310816,0.00004306911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046967017,0.0012133556,0.0011003672,0.00078255724,0.00040516318,0.000665683,0.0018423935,0.0011749733,0.0027348057],"category_scores_gemma":[0.001196101,0.0005765186,0.0005409461,0.0005624466,0.00030699818,0.0009835501,0.0011900556,0.0011360359,0.00091411796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001112371,0.00049521995,0.0041466197,0.0002450056,0.00015007732,0.00049338525,0.00009831578,0.085991286,0.1201504,0.0019271532,0.0045433105,0.7806468],"study_design_scores_gemma":[0.000021686941,0.00013047131,0.002434629,0.00001458021,0.000065228975,0.00016299149,0.0000109868015,0.9681005,0.027332956,0.0010285105,0.0006731291,0.000024318539],"about_ca_topic_score_codex":0.0062402715,"about_ca_topic_score_gemma":0.0119534135,"teacher_disagreement_score":0.0062402715,"about_ca_system_score_codex":0.00045033748,"about_ca_system_score_gemma":0.0012443447,"threshold_uncertainty_score":0.012407899},"labels":[],"label_agreement":null},{"id":"W4292169204","doi":"10.1007/s00170-022-09860-3","title":"Tool condition monitoring based on the fractal analysis of current and cutting force signals during CFRP trimming","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure","funders":"","keywords":"Machining; Trimming; Tool wear; Aerospace; Surface roughness; Surface finish; Cutting tool; Mechanical engineering; Fractal; SIGNAL (programming language); Quality (philosophy); Surface integrity; Engineering; Structural engineering; Materials science; Computer science; Composite material","score_opus":0.007827292082127967,"score_gpt":0.2612300240235315,"score_spread":0.25340273194140356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292169204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92741925,0.0005939763,0.06754527,0.000072974115,0.00006508812,0.000037981867,0.00020789224,0.0005308745,0.0035266248],"genre_scores_gemma":[0.9949162,0.000046338588,0.004709052,0.000009879924,0.000010475163,0.0000061611913,0.00003991612,0.000011722097,0.00025020965],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998636,0.000010092187,0.0000046002265,0.00003438178,0.00007012719,0.000017167913],"domain_scores_gemma":[0.9995671,0.00017225632,0.000075129166,0.000032166914,0.00012709697,0.000026154708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001228756,0.00023301897,0.00021380477,0.0009054133,0.00019492909,0.000246081,0.0002291514,0.0003583256,0.0008620305],"category_scores_gemma":[0.00067560846,0.00009403033,0.000098660494,0.00041713877,0.0002044609,0.00035058026,0.00012019984,0.00022568926,0.00012752027],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011309962,0.00012487917,0.020135818,0.00022088728,0.000030255796,0.0005326631,0.000527859,0.005469229,0.7493956,0.0006482358,0.0011295448,0.22065397],"study_design_scores_gemma":[0.0000468405,0.0011723982,0.39657,0.00009211983,0.00010860935,0.002181533,0.0005729181,0.29099992,0.30204508,0.0013414688,0.004738013,0.00013100686],"about_ca_topic_score_codex":0.00061670615,"about_ca_topic_score_gemma":0.0010733958,"teacher_disagreement_score":0.0009054133,"about_ca_system_score_codex":0.0001403671,"about_ca_system_score_gemma":0.00009967611,"threshold_uncertainty_score":0.002883792},"labels":[],"label_agreement":null},{"id":"W4292566194","doi":"10.5267/j.msl.2022.5.001","title":"An integrated approach of VIKOR and teaching learning based optimization algorithm for milling machinability computations","year":2022,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machinability; Materials science; Machining; Response surface methodology; Computer science; Process (computing); Productivity; Composite number; Algorithm; Process engineering; Mechanical engineering; Composite material; Metallurgy; Machine learning; Engineering","score_opus":0.006247979231798836,"score_gpt":0.23256102965086772,"score_spread":0.22631305041906888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292566194","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01136095,0.00017613417,0.9856818,0.00009102495,0.000030997988,0.000050030147,0.000014374848,0.0003728625,0.0022219385],"genre_scores_gemma":[0.30976534,0.00022264484,0.6847629,0.00012981112,0.00004060379,0.00050007907,0.000120973724,0.0001486652,0.004308937],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975044,0.00007072584,0.000019231575,0.000045110133,0.00007785097,0.00003669047],"domain_scores_gemma":[0.9995746,0.00026305756,0.000032991084,0.000017726143,0.0000954901,0.000016162818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069287606,0.0007970641,0.00092548586,0.00048443468,0.00039067463,0.00059957016,0.0009679372,0.0011294252,0.0026636082],"category_scores_gemma":[0.0014964275,0.00044141698,0.00063453655,0.00041887694,0.00041124766,0.0004659509,0.00069548195,0.0009798966,0.00046156888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056995887,0.00006857599,0.00064275,0.000106899824,0.000037753987,0.000044683802,0.00006331238,0.9010656,0.002291962,0.0046219276,0.00057025114,0.09042935],"study_design_scores_gemma":[0.000004094856,0.000017128566,0.000043469565,0.000003215702,0.0000020139132,0.0000033826811,0.0000041328176,0.9990239,0.00021831569,0.0004208645,0.00025777682,0.0000016589697],"about_ca_topic_score_codex":0.0059790234,"about_ca_topic_score_gemma":0.005094709,"teacher_disagreement_score":0.0059790234,"about_ca_system_score_codex":0.00043984837,"about_ca_system_score_gemma":0.0011357128,"threshold_uncertainty_score":0.011888444},"labels":[],"label_agreement":null},{"id":"W4293572335","doi":"10.1139/tcsme-2022-0022","title":"Research on the coupling characteristics of energy power density of cutting vibration and cutting heat based on the particle swarm optimization algorithm","year":2022,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Vibration; Coupling (piping); Particle swarm optimization; Machining; Cutting tool; Mechanical engineering; Power (physics); Energy (signal processing); Materials science; Acoustics; Computer science; Engineering; Mathematics; Physics; Algorithm","score_opus":0.015062361460688725,"score_gpt":0.22753306303415044,"score_spread":0.2124707015734617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293572335","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06300077,0.00038167494,0.9342259,0.00014175015,0.000047134858,0.00004513142,0.000013696254,0.00010940157,0.0020344178],"genre_scores_gemma":[0.86085963,0.0006983647,0.13594957,0.000051402403,0.000059814014,0.00014973574,0.00007208166,0.0000512275,0.002108207],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995498,0.00011471243,0.000027287986,0.000100359954,0.00016249748,0.000045313063],"domain_scores_gemma":[0.99917233,0.00052038283,0.00007213354,0.000030682113,0.00017528895,0.000029125438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012329656,0.00081879017,0.00089678203,0.0008656836,0.0003764898,0.0008501335,0.00061050063,0.0007005135,0.0006187255],"category_scores_gemma":[0.0023483771,0.00046770752,0.00072910194,0.00087273255,0.00049754867,0.0012235333,0.00044051954,0.0006270413,0.00008558693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085822445,0.000083350795,0.0046441196,0.00017083384,0.00013255996,0.0000702513,0.00016891604,0.9039271,0.0065992526,0.009322307,0.0005400632,0.074255444],"study_design_scores_gemma":[0.0000037878956,0.000013904298,0.00048158012,0.0000020209122,0.000006784503,0.0000062808062,0.0000072126636,0.9985876,0.00036107094,0.00044648285,0.0000801479,0.0000032742573],"about_ca_topic_score_codex":0.0051531265,"about_ca_topic_score_gemma":0.0016212518,"teacher_disagreement_score":0.0051531265,"about_ca_system_score_codex":0.00046567692,"about_ca_system_score_gemma":0.000926685,"threshold_uncertainty_score":0.010246277},"labels":[],"label_agreement":null},{"id":"W4294326331","doi":"10.3390/f13091397","title":"Investigation on Cutting Power of Wood–Plastic Composite Using Response Surface Methodology","year":2022,"lang":"en","type":"article","venue":"Forests","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"National Natural Science Foundation of China","keywords":"Rake angle; Flank; Response surface methodology; Composite number; Machining; Materials science; Cutting tool; Rake; Power (physics); Specific energy; Composite material; Mechanical engineering; Mathematics; Metallurgy; Engineering; Statistics","score_opus":0.05664495784736976,"score_gpt":0.2929358255114131,"score_spread":0.23629086766404336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294326331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9073302,0.0011047778,0.08984894,0.000059396094,0.000028965986,0.000072123046,0.0001585132,0.00013862972,0.0012583546],"genre_scores_gemma":[0.96961236,0.0006736662,0.028828863,0.000027571818,0.000006696209,0.00007821747,0.000101387195,0.000018803637,0.00065254094],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99961853,0.00005444578,0.000020830805,0.00006687035,0.00019687849,0.000042380423],"domain_scores_gemma":[0.99970144,0.00016232402,0.00004454028,0.000019698413,0.000063895386,0.000008093553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065232214,0.0005577801,0.00046119816,0.00051536196,0.00011685448,0.00026536765,0.00024141526,0.0004084987,0.00064207724],"category_scores_gemma":[0.0005574708,0.00024295358,0.00072437455,0.00058569905,0.00017891345,0.0003517537,0.00015065013,0.00046615748,0.00017057324],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009028886,0.00006791374,0.00053840416,0.00027089848,0.000015207806,0.000057372756,0.000047881815,0.0061446065,0.9788519,0.00011826115,0.00002691737,0.013770388],"study_design_scores_gemma":[0.00001434106,0.0008414538,0.005753362,0.000009300623,0.000028921704,0.000095259995,0.00008678577,0.071507625,0.9206601,0.00020749132,0.0007697024,0.000025533833],"about_ca_topic_score_codex":0.00027627614,"about_ca_topic_score_gemma":0.0005680984,"teacher_disagreement_score":0.00065232214,"about_ca_system_score_codex":0.00012446796,"about_ca_system_score_gemma":0.00014406412,"threshold_uncertainty_score":0.0034498572},"labels":[],"label_agreement":null},{"id":"W4296335337","doi":"10.1007/s00170-022-10150-1","title":"Effect of graphene additive on cutting forces and temperature during the trimming process of CFRP","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; École de Technologie Supérieure","funders":"National Research Council Canada","keywords":"Materials science; Composite material; Delamination (geology); Trimming; Machinability; Machining; Graphene; Epoxy; Volume fraction; Composite number; Nanocomposite; Stiffness; Composite laminates; Mechanical engineering; Nanotechnology; Metallurgy","score_opus":0.001686448047515748,"score_gpt":0.22442777552526158,"score_spread":0.22274132747774583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296335337","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984836,0.000529379,0.00031279968,0.00002433097,0.00002753284,0.000004307358,0.0000511418,0.000020918413,0.0005460429],"genre_scores_gemma":[0.9987866,0.00017423247,0.0004936585,0.0000175053,0.0000061131345,0.000004237596,0.000032613974,0.0000099780345,0.00047503356],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981326,0.000015867417,0.000011492395,0.000040948747,0.000061040926,0.00005743546],"domain_scores_gemma":[0.9996773,0.00012184862,0.00007252201,0.000032980697,0.000067163295,0.000028156448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015909947,0.00035681907,0.000279578,0.00024728876,0.0003297306,0.0002616043,0.00028938756,0.00039552184,0.0021824944],"category_scores_gemma":[0.0005142255,0.00019236025,0.0002779716,0.00028956032,0.00027036676,0.0003782378,0.00015687582,0.0005133205,0.00020210321],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013061449,0.00008188371,0.0005693871,0.0002237175,0.000022183718,0.00019576456,0.00016803786,0.0009218721,0.9894656,0.000079696554,0.00013083707,0.0068349172],"study_design_scores_gemma":[0.000008561104,0.0005928478,0.005851723,0.000012679513,0.00003531326,0.00005471465,0.00009812261,0.0017813324,0.9910238,0.000023231534,0.00049897446,0.00001871089],"about_ca_topic_score_codex":0.0011011127,"about_ca_topic_score_gemma":0.0030325064,"teacher_disagreement_score":0.0021824944,"about_ca_system_score_codex":0.00020202558,"about_ca_system_score_gemma":0.00018524905,"threshold_uncertainty_score":0.0073011518},"labels":[],"label_agreement":null},{"id":"W4296545256","doi":"10.14743/apem2022.2.431","title":"Machinability analysis and multi-response optimization using NGSA-II algorithm for particle reinforced aluminum based metal matrix composites","year":2022,"lang":"en","type":"article","venue":"Advances in Production Engineering & Management","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Materials science; Machining; Machinability; Composite material; Response surface methodology; Surface roughness; Volume fraction; Tool wear; Silicon carbide; Metal matrix composite; Particle (ecology); Aluminium; Computer science; Metallurgy","score_opus":0.006135706438149558,"score_gpt":0.25252022662702006,"score_spread":0.2463845201888705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296545256","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12521829,0.0003874324,0.86794335,0.00022416197,0.000046656653,0.00016948394,0.00007650154,0.0009101368,0.0050240555],"genre_scores_gemma":[0.61491024,0.00014180661,0.3794101,0.00012627657,0.000017328744,0.0005609961,0.00025632657,0.00013987649,0.0044371276],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997303,0.0000868757,0.000014621082,0.000053598826,0.000062537176,0.000052016596],"domain_scores_gemma":[0.99943477,0.00035637993,0.000055570916,0.000019005833,0.000113415925,0.000020847921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079886004,0.0011157459,0.00093193655,0.00079527096,0.00046617724,0.0006903217,0.0007523334,0.0012596576,0.0026177855],"category_scores_gemma":[0.0011712712,0.0005551269,0.0010177133,0.00038641025,0.00044910132,0.00032254565,0.00062691374,0.00082773,0.00031301365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006353118,0.000056592355,0.00055890274,0.000058080506,0.00003074421,0.0000466427,0.00004156075,0.9768852,0.002167186,0.0005645003,0.00021207881,0.01931489],"study_design_scores_gemma":[0.0000073777787,0.00003498294,0.000112809954,0.000003885437,0.000003928029,0.000004187327,0.000009948586,0.9992009,0.00028101797,0.00019588564,0.00014322242,0.00000192768],"about_ca_topic_score_codex":0.007047897,"about_ca_topic_score_gemma":0.006075396,"teacher_disagreement_score":0.007047897,"about_ca_system_score_codex":0.0005524305,"about_ca_system_score_gemma":0.0011049676,"threshold_uncertainty_score":0.014013708},"labels":[],"label_agreement":null},{"id":"W4297236499","doi":"10.3390/lubricants10100235","title":"Implementation of Sustainable Vegetable-Oil-Based Minimum Quantity Cooling Lubrication (MQCL) Machining of Titanium Alloy with Coated Tools","year":2022,"lang":"en","type":"article","venue":"Lubricants","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Lubrication; Materials science; Machining; Lubricant; Titanium alloy; Metallurgy; Machinability; Composite material; Alloy","score_opus":0.010873239965613176,"score_gpt":0.24898115784858227,"score_spread":0.2381079178829691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297236499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961719,0.00019146653,0.0032113206,0.000013807194,0.0000058049322,0.000014877402,0.000022788736,0.000040161474,0.00032784202],"genre_scores_gemma":[0.9946085,0.00008140122,0.004982923,0.000003910595,0.000001126567,0.000006071392,0.00002717454,0.000006380781,0.0002823648],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997718,0.000022023625,0.000019533765,0.00003962151,0.00010313247,0.000043992823],"domain_scores_gemma":[0.99980944,0.00003259324,0.00007227611,0.000019923165,0.000052357864,0.0000135052405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022475875,0.00021214815,0.00023110265,0.00024230123,0.00013099557,0.00027425823,0.00048150026,0.00021529052,0.00042138],"category_scores_gemma":[0.00041970008,0.00012747016,0.00023032833,0.0001585216,0.00020894145,0.00023977098,0.00021443174,0.00017154946,0.00008872486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000120784534,0.000022913544,0.00076577085,0.000116391435,0.0000066373927,0.000048887403,0.000060181985,0.0011534198,0.99278235,0.00007999397,0.000022538348,0.00482012],"study_design_scores_gemma":[0.0000103472075,0.00065821747,0.0028661923,0.0000042855945,0.000012246749,0.000054782373,0.000034074823,0.0068370365,0.98883176,0.00001704072,0.0006634173,0.0000105717245],"about_ca_topic_score_codex":0.0015639985,"about_ca_topic_score_gemma":0.003473964,"teacher_disagreement_score":0.0015639985,"about_ca_system_score_codex":0.00030890887,"about_ca_system_score_gemma":0.00028311304,"threshold_uncertainty_score":0.0031098723},"labels":[],"label_agreement":null},{"id":"W4297986329","doi":"","title":"THE SPECIFIC CUTTING ENERGY ON THE CUTTING EDGES OF A THE COMBINED DRILLING/THREAD MILLING PROCESS: THRILLING","year":2009,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Thread (computing); Drilling; Materials science; Computer science; Mechanical engineering; Metallurgy; Engineering","score_opus":0.011113986471802045,"score_gpt":0.20792324872756948,"score_spread":0.19680926225576745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297986329","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9356633,0.00015188774,0.06107838,0.000019464707,0.0000038505937,0.000010162228,0.000029691091,0.000022879258,0.0030203373],"genre_scores_gemma":[0.9915454,0.00013249752,0.005714719,0.000008575508,0.0000019939366,0.000010902925,0.000043175976,0.000026992644,0.002515635],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983525,0.000013199352,0.0000038385865,0.000031963227,0.00008645493,0.000029280132],"domain_scores_gemma":[0.9995641,0.00025762047,0.000080540725,0.000032785112,0.00004804122,0.000016870728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002565902,0.00024485347,0.00034425306,0.00035104246,0.00017499227,0.0004659056,0.00037436673,0.00042078094,0.002635231],"category_scores_gemma":[0.00074419525,0.00021793222,0.00031807262,0.00029575685,0.00039700887,0.0006574926,0.00031330835,0.0002541765,0.00023745453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036359509,0.00012827452,0.007980287,0.00033690478,0.000050083443,0.00038524275,0.0002885585,0.4217316,0.4457736,0.012351809,0.00019547183,0.11041465],"study_design_scores_gemma":[0.00002846913,0.0005245239,0.039138794,0.00003815408,0.000054097924,0.0003317922,0.00027457188,0.70497954,0.24490519,0.0068887686,0.0027640664,0.00007201464],"about_ca_topic_score_codex":0.0006738055,"about_ca_topic_score_gemma":0.00087114825,"teacher_disagreement_score":0.002635231,"about_ca_system_score_codex":0.00026932862,"about_ca_system_score_gemma":0.00019156004,"threshold_uncertainty_score":0.008815765},"labels":[],"label_agreement":null},{"id":"W4298009683","doi":"10.18280/ts.390414","title":"Signal Processing Algorithms Like Ensemble Empirical Mode Decomposition and Statistical Analysis-Based Tool Chatter Severity Prediction","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Hilbert–Huang transform; Preprocessor; Mode (computer interface); Computer science; Filter (signal processing); Algorithm; Machining; Time domain; Signal processing; Frequency domain; Pattern recognition (psychology); Data mining; Artificial intelligence; Engineering; Digital signal processing","score_opus":0.012241557675980404,"score_gpt":0.2979535598738283,"score_spread":0.2857120021978479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298009683","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009735762,0.00044311554,0.98877597,0.00006219079,0.000046322748,0.000026609594,0.00005665977,0.00039261117,0.0004607165],"genre_scores_gemma":[0.34847182,0.0019939786,0.64568144,0.0001187985,0.00016424082,0.00018321967,0.00062442827,0.00015977293,0.0026023276],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994136,0.00011284473,0.00005422473,0.00015816449,0.00022585192,0.000035304965],"domain_scores_gemma":[0.9986688,0.00054387155,0.0002102768,0.00016162601,0.00038229793,0.000033234912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010917255,0.0014912538,0.0009108043,0.0015686107,0.00021656182,0.0007428479,0.00078621606,0.00069619744,0.0013038731],"category_scores_gemma":[0.0036857408,0.00029618913,0.0009346321,0.0012550522,0.00031533497,0.0011944,0.0005126736,0.0012194831,0.00072544394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022151184,0.00018037578,0.004107193,0.00037839782,0.00023882667,0.0001543832,0.0001626893,0.20905975,0.051077694,0.006929375,0.0021054011,0.72538435],"study_design_scores_gemma":[0.0000057531684,0.00010924777,0.0024738172,0.000025649832,0.00002554496,0.00010749087,0.000025155783,0.9862038,0.0073393276,0.0023168903,0.0013459342,0.000021378937],"about_ca_topic_score_codex":0.001231227,"about_ca_topic_score_gemma":0.0013381004,"teacher_disagreement_score":0.0015686107,"about_ca_system_score_codex":0.00026299048,"about_ca_system_score_gemma":0.00041160497,"threshold_uncertainty_score":0.005773604},"labels":[],"label_agreement":null},{"id":"W4298615157","doi":"10.1016/j.precisioneng.2022.09.008","title":"Review and status of tool tip frequency response function prediction using receptance coupling","year":2022,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Calgary","funders":"Office of Energy Efficiency; Office of Energy Efficiency and Renewable Energy; Advanced Manufacturing Office; U.S. Department of Energy","keywords":"Substructure; Function (biology); Coupling (piping); Computer science; Engineering; Structural engineering; Mechanical engineering","score_opus":0.011132735990514725,"score_gpt":0.23208704585935425,"score_spread":0.22095430986883952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298615157","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014156041,0.7343386,0.24109726,0.0007261518,0.00096813176,0.00004693817,0.0003940793,0.0008751532,0.0073976913],"genre_scores_gemma":[0.11791059,0.7693494,0.10415663,0.00061145803,0.0021684242,0.00011049423,0.001296985,0.00031700372,0.0040790956],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99940693,0.000102519225,0.00006511158,0.00019677168,0.00020194097,0.00002667163],"domain_scores_gemma":[0.9977837,0.0012627994,0.00021014575,0.00017457087,0.0005275617,0.000041270432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013243947,0.0012559963,0.0017386904,0.0016762423,0.00024844887,0.0014062679,0.002106053,0.0011900023,0.0018550077],"category_scores_gemma":[0.0030872829,0.0006341678,0.00087698095,0.002633721,0.00034159468,0.0016737961,0.00068595435,0.0008211871,0.0015061429],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011589814,0.000119083925,0.0023295153,0.010979852,0.00025416806,0.0001063463,0.00007913687,0.04156517,0.009985482,0.0043066866,0.007956838,0.92220193],"study_design_scores_gemma":[0.00006397782,0.0008968133,0.01099286,0.0061634816,0.0014993101,0.0008730782,0.0003310592,0.5590521,0.030828675,0.016327828,0.37255886,0.00041194342],"about_ca_topic_score_codex":0.0014755847,"about_ca_topic_score_gemma":0.0011315811,"teacher_disagreement_score":0.002106053,"about_ca_system_score_codex":0.00023342944,"about_ca_system_score_gemma":0.00094510923,"threshold_uncertainty_score":0.0070042014},"labels":[],"label_agreement":null},{"id":"W4299305225","doi":"10.1007/978-1-4471-5102-9_256-1","title":"Control of Machining Processes","year":2014,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Systems and Control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Machining; Machine tool; Mechanism (biology); Engineering; Servo; Power consumption; Control engineering; Vibration; Mechanical engineering; Control (management); Chip; Power (physics); Computer science; Physics; Artificial intelligence; Electrical engineering","score_opus":0.003979980454042592,"score_gpt":0.18324422908319027,"score_spread":0.17926424862914767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299305225","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004102181,0.03631633,0.59085333,0.00046900078,0.0016556988,0.000102537066,0.00029861383,0.0015679465,0.36463434],"genre_scores_gemma":[0.24326573,0.039001722,0.10970538,0.0006739124,0.0018447379,0.00036113925,0.0010178321,0.00042204608,0.60370743],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99971503,0.000024315159,0.000009918748,0.0000671994,0.00016864759,0.000014959334],"domain_scores_gemma":[0.9999362,0.000017630271,0.0000060959906,0.000015375195,0.000020729185,0.000003972601],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014741645,0.00080021436,0.0006643963,0.0004898882,0.00023543417,0.0013415075,0.00085864286,0.00061780063,0.012598477],"category_scores_gemma":[0.00023039554,0.00020763114,0.00026644208,0.00061167567,0.00063730933,0.00053124805,0.00057624775,0.0007647102,0.004228731],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062434345,0.000059996215,0.00011383945,0.000731167,0.000035800684,0.000097497315,0.00017402336,0.024402743,0.042752463,0.1689384,0.04159687,0.7210349],"study_design_scores_gemma":[0.000030193592,0.00017366135,0.0011425767,0.00026498054,0.000033657154,0.00039029936,0.00004808473,0.0818053,0.018492715,0.078475945,0.81909025,0.00005229284],"about_ca_topic_score_codex":0.00086103927,"about_ca_topic_score_gemma":0.001162121,"teacher_disagreement_score":0.012598477,"about_ca_system_score_codex":0.00037165888,"about_ca_system_score_gemma":0.00029823498,"threshold_uncertainty_score":0.042146146},"labels":[],"label_agreement":null},{"id":"W4300926444","doi":"","title":"MODELING AND ANALYSIS OF THE THREAD MILLING OPERATION IN THE COMBINED DRILLING/THREAD MILLING PROCESS","year":2008,"lang":"en","type":"other","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Thread (computing); Computer science; Drilling; Materials science; Operating system; Metallurgy","score_opus":0.009661618284028546,"score_gpt":0.2185015149880924,"score_spread":0.20883989670406386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300926444","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22702478,0.0003904378,0.765189,0.00007329892,0.000017753064,0.000047391644,0.00006315786,0.00026683375,0.0069272923],"genre_scores_gemma":[0.961465,0.00033577817,0.034682374,0.000010712119,0.00000672604,0.000043658143,0.000052115247,0.00004442511,0.0033592056],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983144,0.000018230832,0.0000066121784,0.000033056633,0.00008966447,0.000021042275],"domain_scores_gemma":[0.99983025,0.000080740465,0.00003733232,0.000016964583,0.000026467707,0.000008305685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003008575,0.00035518626,0.000479012,0.00024142332,0.00021279664,0.00063210435,0.0005779077,0.0005964922,0.0009344674],"category_scores_gemma":[0.0005108928,0.00026998782,0.00044370777,0.0002465641,0.00030021567,0.00065213215,0.00029017715,0.00033477801,0.00022794874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005076813,0.00003863234,0.0010837709,0.00006671411,0.000010757411,0.00012212008,0.00007826814,0.94218105,0.0371925,0.003062404,0.00011265787,0.016000371],"study_design_scores_gemma":[0.0000025298614,0.000023801655,0.00027863964,0.000001373362,0.00000365371,0.000023435861,0.000005709031,0.9963678,0.002696006,0.00029940487,0.00029455562,0.0000031751674],"about_ca_topic_score_codex":0.004243374,"about_ca_topic_score_gemma":0.0023326057,"teacher_disagreement_score":0.004243374,"about_ca_system_score_codex":0.00031184455,"about_ca_system_score_gemma":0.0005972346,"threshold_uncertainty_score":0.0084373355},"labels":[],"label_agreement":null},{"id":"W4301435645","doi":"","title":"Influence of the Double Cone Drill Geometry on the Holes Quality during Drilling Multi-Stack Made of CFRP/Al","year":2014,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Stack (abstract data type); Drilling; Cone (formal languages); Drill; Geometry; Quality (philosophy); Mechanical engineering; Materials science; Geology; Engineering drawing; Structural engineering; Engineering; Computer science; Physics; Mathematics","score_opus":0.013882164079816538,"score_gpt":0.23765448612540613,"score_spread":0.22377232204558958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301435645","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955869,0.00029484113,0.0034236028,0.00002151943,0.000023717112,0.000008384187,0.000051558425,0.000057832032,0.0005316289],"genre_scores_gemma":[0.99898154,0.00005041964,0.00074569037,0.0000037967113,0.0000021463718,0.0000020155321,0.000020956028,0.000013437988,0.00017996435],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99961865,0.00005043751,0.000019840949,0.00008280428,0.0001553324,0.00007279706],"domain_scores_gemma":[0.99748635,0.0013308652,0.00042592396,0.00015250486,0.0005128856,0.0000915205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051753264,0.00031880944,0.0003519467,0.00019611682,0.00027402744,0.00056287996,0.00024386864,0.00055231596,0.0010163249],"category_scores_gemma":[0.0019364597,0.00029889937,0.00019579711,0.00020713283,0.00045453315,0.0004393141,0.00020510601,0.000271508,0.00012488321],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022391586,0.000055627967,0.005173479,0.00027329,0.000024852234,0.0003097038,0.0003521405,0.010423702,0.9698186,0.00015626416,0.00022650229,0.010946665],"study_design_scores_gemma":[0.000055054585,0.0022803012,0.072765805,0.000037193404,0.00012495647,0.00046151495,0.0006400013,0.025765296,0.89643687,0.00014612624,0.0012230586,0.00006389045],"about_ca_topic_score_codex":0.0008810297,"about_ca_topic_score_gemma":0.0019447422,"teacher_disagreement_score":0.0010163249,"about_ca_system_score_codex":0.00020168106,"about_ca_system_score_gemma":0.00029258739,"threshold_uncertainty_score":0.0033999085},"labels":[],"label_agreement":null},{"id":"W4303712171","doi":"10.3390/jmmp6050115","title":"Tool Condition Monitoring Using Machine Tool Spindle Electric Current and Multiscale Analysis while Milling Steel Alloy","year":2022,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure","funders":"","keywords":"Downtime; Tool wear; SIGNAL (programming language); Machine tool; Fractal; Process (computing); Mechanical engineering; Machining; Engineering; Condition monitoring; End mill; Electrical discharge machining; Grinding; Computer science; Reliability engineering; Electrical engineering","score_opus":0.01356448620328528,"score_gpt":0.2555674626932479,"score_spread":0.24200297648996263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4303712171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8537975,0.00047695846,0.14343739,0.000047453268,0.000026005793,0.00003087275,0.000102093814,0.0003137797,0.0017679066],"genre_scores_gemma":[0.9868645,0.000059852235,0.012888236,0.000007107198,0.000006699039,0.0000042316565,0.000026928523,0.0000044825265,0.00013801368],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99986756,0.000012376557,0.0000060863185,0.000042053674,0.000059787195,0.00001203753],"domain_scores_gemma":[0.99983,0.000045947516,0.00004453743,0.000016769063,0.000051666488,0.0000110932115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013322626,0.00017203417,0.00016804005,0.0009893883,0.00008797329,0.00025238688,0.00014169926,0.00023848076,0.00020808181],"category_scores_gemma":[0.0004312533,0.000083015955,0.00017671885,0.00043659194,0.00019000073,0.0003337605,0.00011960509,0.00010849155,0.00004230309],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000307778,0.000087101274,0.020905335,0.00015406558,0.0000532637,0.00031997773,0.0002532152,0.01695558,0.7868931,0.0010312242,0.00038065322,0.17265873],"study_design_scores_gemma":[0.000024480207,0.00053217745,0.1811103,0.000029175117,0.00008058559,0.0008950876,0.00023847705,0.6258119,0.18739665,0.0016698135,0.0021291664,0.000082310995],"about_ca_topic_score_codex":0.0005815421,"about_ca_topic_score_gemma":0.00070857327,"teacher_disagreement_score":0.0009893883,"about_ca_system_score_codex":0.00014152426,"about_ca_system_score_gemma":0.00007697819,"threshold_uncertainty_score":0.0011563301},"labels":[],"label_agreement":null},{"id":"W4306405747","doi":"10.1139/tcsme-2022-0052","title":"A comparison of four machine learning techniques and continuous wavelet transform approach for detection and classification of tool breakage during milling process","year":2022,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Breakage; Machine tool; Machining; Fault detection and isolation; Frequency domain; Time domain; Tool wear; Computer science; Process (computing); Artificial intelligence; Vibration; Wavelet transform; Continuous wavelet transform; Enhanced Data Rates for GSM Evolution; Support vector machine; Fault (geology); Artificial neural network; Cutting tool; Wavelet; Condition monitoring; Engineering; Discrete wavelet transform; Computer vision; Mechanical engineering; Acoustics; Actuator","score_opus":0.011677943590676833,"score_gpt":0.22457595647831016,"score_spread":0.21289801288763333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306405747","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19856617,0.0037972396,0.7931348,0.00022217339,0.00020473334,0.00012306611,0.00009292921,0.00087745336,0.0029814402],"genre_scores_gemma":[0.7535596,0.002053964,0.24228123,0.000070895745,0.00007887172,0.00012386449,0.00019753436,0.00004433058,0.001589729],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884546,0.00022542257,0.00009490197,0.00017891657,0.00056070526,0.000094543975],"domain_scores_gemma":[0.9986688,0.00060979655,0.000112408256,0.00007113657,0.0004991419,0.000038779068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017327657,0.0007244632,0.00073905056,0.00209314,0.00023532599,0.00084182696,0.00059077516,0.00096189306,0.00056963664],"category_scores_gemma":[0.0030565276,0.00022163162,0.0007261131,0.0014924457,0.00031773135,0.0012717412,0.00032879013,0.0006580746,0.00026926238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081760477,0.0003550729,0.0076019224,0.00039908753,0.0002272458,0.00011531256,0.00016266177,0.03537781,0.027206497,0.0012788045,0.0008137434,0.9256442],"study_design_scores_gemma":[0.000061967905,0.000912472,0.020284295,0.000073655065,0.00021763437,0.00029664312,0.00019841155,0.9503773,0.024112662,0.0013178802,0.0020903533,0.00005666886],"about_ca_topic_score_codex":0.0015368427,"about_ca_topic_score_gemma":0.0010388824,"teacher_disagreement_score":0.00209314,"about_ca_system_score_codex":0.00032194136,"about_ca_system_score_gemma":0.00045133496,"threshold_uncertainty_score":0.0091638565},"labels":[],"label_agreement":null},{"id":"W4306778370","doi":"10.18280/i2m.210402","title":"Experimental and Numerical Study of Different Methods' Effects on Lubricant Flow on Temperatures and Strains of Turning Cutting Tool (HSS)","year":2022,"lang":"en","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Lubricant; Drilling; Mechanical engineering; Materials science; Cutting tool; Drill; Process (computing); Machining; Flow (mathematics); Composite material; Metallurgy; Computer science; Engineering; Geometry; Mathematics","score_opus":0.013469754103400547,"score_gpt":0.31025059092906726,"score_spread":0.2967808368256667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306778370","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935601,0.00024822174,0.0048924256,0.000025723186,0.000024723831,0.000012070331,0.00008587341,0.00007141848,0.0010793902],"genre_scores_gemma":[0.9965681,0.00006388785,0.0030427594,0.000003061205,0.0000040646646,0.000010335194,0.000041111012,0.000012904487,0.00025390316],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99947995,0.000072078714,0.00003185384,0.00007574748,0.00025543256,0.000084964966],"domain_scores_gemma":[0.99856263,0.0006623292,0.00019295947,0.00018447667,0.00034646492,0.000051110448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005535561,0.0003024545,0.0003148012,0.0003554659,0.0002967222,0.00027875742,0.0004085263,0.0004185283,0.0016718195],"category_scores_gemma":[0.0016576888,0.00016972604,0.00025170966,0.00041114082,0.0004981509,0.00025341404,0.00022446108,0.00027966173,0.00013294087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011075166,0.00029739575,0.005216716,0.00050208054,0.000022841221,0.00016879261,0.00041725807,0.020970052,0.9432665,0.00082471035,0.0002862292,0.026919952],"study_design_scores_gemma":[0.00005900606,0.0015160637,0.011211236,0.000018693849,0.000038685048,0.00013010738,0.00013200397,0.057550535,0.9278364,0.00014292593,0.0013296611,0.00003473342],"about_ca_topic_score_codex":0.0007216402,"about_ca_topic_score_gemma":0.00070676516,"teacher_disagreement_score":0.0016718195,"about_ca_system_score_codex":0.00024379704,"about_ca_system_score_gemma":0.00018158181,"threshold_uncertainty_score":0.005592823},"labels":[],"label_agreement":null},{"id":"W4306930491","doi":"10.1115/1.4056033","title":"A Unique Method to Determine Ferrite and Martensite Phase Stress–Strain Curve for Manufacturing Process","year":2022,"lang":"en","type":"article","venue":"Journal of Engineering Materials and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Martensite; Materials science; Microstructure; Ferrite (magnet); Stress (linguistics); Dual-phase steel; Composite material; Metallurgy","score_opus":0.007770326066842872,"score_gpt":0.26525981313941605,"score_spread":0.2574894870725732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306930491","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019890584,0.000023900457,0.97772527,0.000021492562,0.000011286709,0.000045278346,0.000030316369,0.0007684527,0.0014833929],"genre_scores_gemma":[0.31128994,0.000044430213,0.6862521,0.000017401444,0.000007095497,0.00014267123,0.00009766862,0.000114277034,0.0020343217],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997389,0.000028169894,0.00001376638,0.00006036701,0.00014756605,0.000011236263],"domain_scores_gemma":[0.9996056,0.00010344105,0.00004827446,0.00005706508,0.00017168386,0.000013999665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028959732,0.00057545415,0.00024523406,0.0005925459,0.0002718846,0.00037349144,0.000643002,0.0005215995,0.0019920545],"category_scores_gemma":[0.0010122268,0.00027473795,0.00026938642,0.00033029786,0.00020771903,0.00040475203,0.00028521894,0.00053702394,0.00054373906],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010162083,0.00015679731,0.0050070523,0.00018065012,0.00004068776,0.000055303848,0.00021030879,0.27681884,0.20142631,0.007867027,0.0012345455,0.50690085],"study_design_scores_gemma":[0.000006459025,0.00003319133,0.0008047518,0.000004813573,0.000004013714,0.000040911742,0.000007415429,0.97243595,0.024738528,0.0004296013,0.0014834056,0.000010939245],"about_ca_topic_score_codex":0.0016129513,"about_ca_topic_score_gemma":0.0022687486,"teacher_disagreement_score":0.0019920545,"about_ca_system_score_codex":0.0003464271,"about_ca_system_score_gemma":0.0007355476,"threshold_uncertainty_score":0.0066640377},"labels":[],"label_agreement":null},{"id":"W4307190006","doi":"10.3390/met12111796","title":"The Use of TOPSIS Method for Multi-Objective Optimization in Milling Ti-MMC","year":2022,"lang":"en","type":"article","venue":"Metals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"TOPSIS; Ideal solution; Machining; Taguchi methods; Surface roughness; Tool wear; Mechanical engineering; Cutting tool; Closeness; Computer science; Engineering; Materials science; Mathematics; Composite material; Machine learning; Operations research","score_opus":0.05748875430162964,"score_gpt":0.31038745111182625,"score_spread":0.2528986968101966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307190006","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064614154,0.0005950713,0.98968995,0.0000553805,0.0000459758,0.00019227031,0.000053616,0.00031082495,0.0025956447],"genre_scores_gemma":[0.094038114,0.0007140892,0.9032106,0.000044585482,0.0000151816175,0.00050468685,0.000103242564,0.00009972355,0.0012697001],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99699956,0.0009565573,0.00021319946,0.0001816652,0.0015491277,0.00009981981],"domain_scores_gemma":[0.99861825,0.00079325476,0.00014465005,0.00005894859,0.00036496346,0.000019886435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031752582,0.0012655847,0.001223518,0.0018714349,0.00065924856,0.0015932719,0.0010820832,0.00079908513,0.0024218145],"category_scores_gemma":[0.0023688718,0.00069855613,0.0020158247,0.0018782798,0.0005400126,0.00062869623,0.0008171896,0.0014920642,0.0005905967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021545214,0.00018617167,0.0012697798,0.0029334035,0.0004958377,0.00027857575,0.00039162932,0.35415816,0.09458544,0.013723771,0.0022562712,0.52950555],"study_design_scores_gemma":[0.00007845806,0.0010489398,0.0022874381,0.00015417878,0.0002208844,0.00028994723,0.00016450559,0.9128557,0.058039192,0.008357992,0.016335925,0.00016681834],"about_ca_topic_score_codex":0.003110825,"about_ca_topic_score_gemma":0.005541142,"teacher_disagreement_score":0.0031752582,"about_ca_system_score_codex":0.0008862794,"about_ca_system_score_gemma":0.0018533672,"threshold_uncertainty_score":0.016792595},"labels":[],"label_agreement":null},{"id":"W4307266377","doi":"10.3390/pr10112171","title":"Numerical Prediction of the Performance of Chamfered and Sharp Cutting Tools during Orthogonal Cutting of AISI 1045 Steel","year":2022,"lang":"en","type":"article","venue":"Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Chamfer (geometry); Materials science; Machining; Finite element method; Composite material; Stress (linguistics); Structural engineering; Metallurgy; Mathematics; Geometry; Engineering","score_opus":0.009107418307595845,"score_gpt":0.19375114135882693,"score_spread":0.18464372305123108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307266377","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98835444,0.00007998672,0.010786495,0.00001198445,0.0000068061686,0.000011070493,0.000032846398,0.000046320845,0.0006699678],"genre_scores_gemma":[0.99712807,0.000024792158,0.0026748811,0.0000014378154,6.6330296e-7,0.0000051829643,0.000018668397,0.0000053548074,0.00014093857],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999798,0.00003314866,0.000014606044,0.000028044233,0.00008832454,0.000037823065],"domain_scores_gemma":[0.99891746,0.000684032,0.00016246796,0.00006812011,0.00012937185,0.000038672155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005176396,0.00035149424,0.00032220266,0.00038123978,0.00022305813,0.0003828313,0.00030245967,0.0005513765,0.00060439017],"category_scores_gemma":[0.0018003603,0.0002463822,0.00037200606,0.00020134846,0.0003828304,0.00027172838,0.00017535841,0.00019785717,0.0000904869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059549074,0.00013998638,0.012573695,0.00018764628,0.000034740548,0.00018809833,0.00020386242,0.8169308,0.14650868,0.00037143088,0.000119824304,0.022145728],"study_design_scores_gemma":[0.000017330301,0.000506655,0.011071398,0.000008082314,0.000019394121,0.00004897823,0.00006872765,0.96252894,0.025438128,0.00009445403,0.00017680749,0.000021106216],"about_ca_topic_score_codex":0.0024483313,"about_ca_topic_score_gemma":0.0028433397,"teacher_disagreement_score":0.0024483313,"about_ca_system_score_codex":0.00036377195,"about_ca_system_score_gemma":0.0003364253,"threshold_uncertainty_score":0.0048681498},"labels":[],"label_agreement":null},{"id":"W4308863922","doi":"10.5267/j.esm.2022.11.002","title":"Optimization and finite element modeling of orthogonal turning of Ti6Al4V alloys: A comparative study of different optimization techniques","year":2022,"lang":"en","type":"article","venue":"Engineering Solid Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Taguchi methods; Dynamometer; Finite element method; Mechanical engineering; Orthogonal array; Titanium alloy; Design of experiments; Structural engineering; Materials science; Engineering; Mathematics; Composite material; Alloy","score_opus":0.012959799852307852,"score_gpt":0.2412752066239377,"score_spread":0.22831540677162984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308863922","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3106321,0.00081429665,0.6767901,0.00014403282,0.00003936185,0.0001538732,0.00015303187,0.0003883836,0.010884814],"genre_scores_gemma":[0.8875731,0.00052327744,0.10824945,0.000028390079,0.000010554205,0.0002467607,0.00014859017,0.00009226271,0.0031274974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981016,0.000063778745,0.000010114752,0.000019945803,0.00007030504,0.000025665051],"domain_scores_gemma":[0.999589,0.00028690873,0.000046914436,0.00001712889,0.000051301253,0.000008647384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006157303,0.00052082795,0.0007339386,0.0006462452,0.00021961618,0.00068536564,0.0005365594,0.000874849,0.0012181933],"category_scores_gemma":[0.00077246205,0.00037109788,0.0007768669,0.0003947338,0.00032510402,0.00023705981,0.00023509165,0.00035905567,0.00020606478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035263576,0.00003906368,0.00052634225,0.00007099897,0.000010253589,0.000019326293,0.0000296351,0.9856989,0.0043107313,0.0005711755,0.0000504301,0.008637786],"study_design_scores_gemma":[0.0000028958432,0.00002628349,0.000213156,0.000004965468,0.0000037728273,0.000007745208,0.000012361637,0.9984108,0.0010190569,0.000097882985,0.0001984664,0.0000026348828],"about_ca_topic_score_codex":0.0033864328,"about_ca_topic_score_gemma":0.0036010528,"teacher_disagreement_score":0.0033864328,"about_ca_system_score_codex":0.0003293021,"about_ca_system_score_gemma":0.00058488845,"threshold_uncertainty_score":0.006733477},"labels":[],"label_agreement":null},{"id":"W4309221341","doi":"10.21203/rs.3.rs-2243032/v1","title":"A noval high-order discretization method for the milling stability prediction considering the differential of directional cutting coefficient and vibration velocities","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Discretization; Floquet theory; Stability (learning theory); Coefficient matrix; Matrix (chemical analysis); Finite element method; Vibration; Mathematics; Monodromy matrix; Applied mathematics; Partial differential equation; Differential (mechanical device); Algorithm; Mathematical analysis; Mathematical optimization; Computer science; Eigenvalues and eigenvectors; Physics; Structural engineering; Engineering; Materials science; Acoustics","score_opus":0.04482889596055672,"score_gpt":0.3523234768210747,"score_spread":0.30749458086051795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309221341","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009221012,0.000124297,0.9888439,0.00004919486,0.0000404779,0.000017788843,0.000019169938,0.00011101298,0.0015731909],"genre_scores_gemma":[0.5574662,0.00038144644,0.43596283,0.000085477026,0.000054770495,0.00015184515,0.00012668071,0.00011270493,0.0056580612],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979955,0.00005485433,0.000012712538,0.000028824166,0.00008746424,0.000016544735],"domain_scores_gemma":[0.99964523,0.00014225894,0.000032951873,0.00004616516,0.000111812165,0.00002150894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004474502,0.0002851575,0.0005250193,0.00029526718,0.00039501145,0.00055135554,0.00074235257,0.0006247765,0.0020542343],"category_scores_gemma":[0.0009982113,0.00026184632,0.0005076622,0.0002722034,0.00047887754,0.00057693553,0.0004393313,0.0008041786,0.00033931085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008808196,0.000057146168,0.0013252278,0.00017341893,0.000034283108,0.00010213428,0.000114593626,0.8729356,0.019160127,0.02241004,0.00097258284,0.082626864],"study_design_scores_gemma":[0.0000017027492,0.000004277487,0.000039140417,0.000002375575,9.460764e-7,0.000005666777,0.0000025284585,0.9988569,0.00039280872,0.0004198149,0.00027224497,0.0000016487832],"about_ca_topic_score_codex":0.0053762514,"about_ca_topic_score_gemma":0.0042408663,"teacher_disagreement_score":0.0053762514,"about_ca_system_score_codex":0.00045188938,"about_ca_system_score_gemma":0.0008985419,"threshold_uncertainty_score":0.010689914},"labels":[],"label_agreement":null},{"id":"W4310013323","doi":"10.1016/j.matpr.2022.11.161","title":"Machining investigation of textured tungsten carbide tools","year":2022,"lang":"en","type":"article","venue":"Materials Today Proceedings","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Institute of Infection and Immunity","keywords":"Machining; Tungsten carbide; Materials science; Carbide; Taguchi methods; Tool wear; Surface roughness; Metallurgy; Adhesion; Composite material; Mechanical engineering; Engineering","score_opus":0.01102989689670215,"score_gpt":0.20027104116940128,"score_spread":0.18924114427269914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310013323","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9953975,0.00033489705,0.0018927696,0.000020394435,0.000011379351,0.000017048285,0.00004524514,0.00004220497,0.0022385293],"genre_scores_gemma":[0.99729687,0.000091633156,0.0017685854,0.0000051731,0.0000019712286,0.000003936294,0.00004559908,0.000009328646,0.0007767866],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997917,0.000010086303,0.000007635894,0.000033160966,0.00012334702,0.00003405852],"domain_scores_gemma":[0.9997434,0.00006536311,0.000054493466,0.00004389083,0.000075896474,0.000016968805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000109051325,0.00012240875,0.00025487688,0.00026988616,0.00031033906,0.00043250032,0.00038724902,0.00039409613,0.0011024105],"category_scores_gemma":[0.00046218376,0.00017945866,0.00014590584,0.00031918805,0.00025582002,0.00024741655,0.0001604794,0.00019227865,0.0001346811],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028506067,0.000034130782,0.0013910081,0.00012551888,0.000011554351,0.00024219837,0.00011500676,0.00184999,0.98920107,0.0003881758,0.0000977283,0.006258665],"study_design_scores_gemma":[0.00007306243,0.0018050966,0.037817966,0.000024984873,0.000043708278,0.0009711113,0.0003479083,0.031350825,0.9215828,0.00039066913,0.0055644577,0.000027373602],"about_ca_topic_score_codex":0.0011223423,"about_ca_topic_score_gemma":0.0015205836,"teacher_disagreement_score":0.0011223423,"about_ca_system_score_codex":0.0002952458,"about_ca_system_score_gemma":0.00030932884,"threshold_uncertainty_score":0.0036879778},"labels":[],"label_agreement":null},{"id":"W4310207725","doi":"10.1007/s00170-022-10563-y","title":"Modeling forces in milling screw rotors","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Industrial and production engineering; Mechanical engineering; Engineering; Engineering drawing; Materials science; Structural engineering","score_opus":0.006396194433494654,"score_gpt":0.23015038186655223,"score_spread":0.22375418743305758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310207725","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34977698,0.0014404664,0.59526134,0.00074274826,0.00037910228,0.0001977709,0.00032903953,0.00064285944,0.051229697],"genre_scores_gemma":[0.9668359,0.00041630026,0.02173175,0.000051912823,0.000051264393,0.00007137884,0.000102531965,0.00011311263,0.010625735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998006,0.000049844897,0.000011278356,0.000033277884,0.00006941298,0.00003556002],"domain_scores_gemma":[0.999579,0.0002238962,0.00007104412,0.0000230566,0.000072940245,0.000030093048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036042643,0.0007891084,0.0007291774,0.00069637795,0.0006825299,0.0012052142,0.0011449127,0.001986302,0.0036383695],"category_scores_gemma":[0.0012916863,0.0006866961,0.0006951377,0.0005690953,0.0007507406,0.000847412,0.00056209747,0.0006264544,0.00047484157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014992015,0.000018213806,0.00024102592,0.000017313132,0.0000072729185,0.000034752957,0.000015922327,0.99261683,0.0008327929,0.0037687644,0.00010018521,0.0023320296],"study_design_scores_gemma":[0.000004862324,0.0000077862605,0.00008422975,0.000001709384,0.000001408842,0.0000035931737,0.0000041838857,0.9990978,0.000110371184,0.0005072572,0.00017486348,0.0000018448368],"about_ca_topic_score_codex":0.020209631,"about_ca_topic_score_gemma":0.012472086,"teacher_disagreement_score":0.020209631,"about_ca_system_score_codex":0.0007676245,"about_ca_system_score_gemma":0.00091943186,"threshold_uncertainty_score":0.04018402},"labels":[],"label_agreement":null},{"id":"W4311005217","doi":"10.1007/s00170-022-10579-4","title":"Heat transfer mechanisms of nano-cutting fluids: a comparative performance analysis model","year":2022,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanofluid; Machining; Heat transfer; Materials science; Nano-; Mechanical engineering; Cutting fluid; Thermal diffusivity; Work (physics); Convective heat transfer; Heat transfer coefficient; Engineering; Nanotechnology; Composite material; Mechanics; Thermodynamics; Nanoparticle","score_opus":0.00941824388702777,"score_gpt":0.24025268802033928,"score_spread":0.2308344441333115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311005217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6001626,0.00220998,0.31249455,0.00045977585,0.00012157146,0.00018710997,0.0004278173,0.00035299893,0.0835836],"genre_scores_gemma":[0.9902873,0.00032552797,0.0034620168,0.000018532492,0.000018870674,0.0000714771,0.00007308287,0.000025702057,0.0057174405],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998766,0.000026140511,0.0000041483067,0.000021418664,0.00004427811,0.000027416869],"domain_scores_gemma":[0.9996216,0.00020756536,0.000037410304,0.000027659653,0.0000920049,0.000013740071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004444717,0.00052880513,0.0006677197,0.0005654169,0.0004656687,0.00069640187,0.0010460658,0.0009816394,0.003423641],"category_scores_gemma":[0.0008492165,0.00026242415,0.0009999688,0.00049255736,0.0004633927,0.001139579,0.0003784385,0.00045636896,0.00046794116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005830968,0.000053259886,0.0003169153,0.00005404405,0.000012602382,0.000027043307,0.000026689424,0.9833097,0.004447398,0.006205158,0.00024345917,0.0052454574],"study_design_scores_gemma":[0.0000051724405,0.000031184496,0.0002596968,0.0000021919607,0.000008061947,0.000006347368,0.000005907275,0.99793833,0.00081534364,0.00071901036,0.00020496444,0.0000037814568],"about_ca_topic_score_codex":0.0046224524,"about_ca_topic_score_gemma":0.0017420108,"teacher_disagreement_score":0.0046224524,"about_ca_system_score_codex":0.00072539656,"about_ca_system_score_gemma":0.00060852466,"threshold_uncertainty_score":0.011453211},"labels":[],"label_agreement":null},{"id":"W4311133098","doi":"10.18280/jesa.550503","title":"Study and Experimental Investigation of the Effect of Progressive Feed Rate on Surface Roughness in CNC End Milling Process Using RSM","year":2022,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Technology Karnataka, Surathkal","keywords":"Surface roughness; Machining; Response surface methodology; Taguchi methods; Design of experiments; End milling; Materials science; End mill; Surface finish; Engineering drawing; Process (computing); Mechanical engineering; Metallurgy; Composite material; Mathematics; Engineering; Computer science; Statistics","score_opus":0.014298146726363635,"score_gpt":0.2717920656791325,"score_spread":0.25749391895276885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311133098","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9842152,0.000516127,0.014040159,0.000019848525,0.000016158727,0.00006478592,0.000101414116,0.00008706865,0.0009392614],"genre_scores_gemma":[0.98151326,0.00022990507,0.017454647,0.000015007671,0.000005324252,0.00003147491,0.000064224245,0.000016121423,0.00066997274],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987902,0.00014331094,0.000068469366,0.00019829885,0.0007201617,0.00007964589],"domain_scores_gemma":[0.9983765,0.0006723041,0.00024192169,0.00020516869,0.0004701294,0.000033952947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000991753,0.00042991585,0.0005545243,0.00033281298,0.0002149316,0.00031666478,0.00053878507,0.00060453877,0.0005739552],"category_scores_gemma":[0.0015879868,0.00022868474,0.0004953664,0.00043317577,0.0002813106,0.00026245016,0.0001815297,0.0004586011,0.0001655312],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038921897,0.00016551369,0.0020673915,0.0003052234,0.00001537614,0.00013807297,0.0001717132,0.005236977,0.9700244,0.00011252939,0.000100245525,0.021273341],"study_design_scores_gemma":[0.000017821407,0.0020542021,0.014803358,0.000012108488,0.00004110328,0.00014061002,0.000073611845,0.018733611,0.9629846,0.00004160688,0.0010658788,0.00003152195],"about_ca_topic_score_codex":0.0009220858,"about_ca_topic_score_gemma":0.0013985265,"teacher_disagreement_score":0.000991753,"about_ca_system_score_codex":0.00026566305,"about_ca_system_score_gemma":0.00019120018,"threshold_uncertainty_score":0.0052449107},"labels":[],"label_agreement":null},{"id":"W4311309315","doi":"10.22214/ijraset.2022.47969","title":"Antibacterial Coating on Filtration Membranes for Treatment of Cutting Fluid","year":2022,"lang":"en","type":"article","venue":"International Journal for Research in Applied Science and Engineering Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Filtration (mathematics); Polypropylene; Cutting fluid; Membrane; Coating; Materials science; Distilled water; Composite material; Chromatography; Machining; Chemistry; Metallurgy; Mathematics","score_opus":0.043810566550189035,"score_gpt":0.3655082363113712,"score_spread":0.32169766976118214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311309315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96169525,0.007490021,0.027136376,0.00027237905,0.00026383574,0.000112087735,0.00021443763,0.00028456227,0.0025311147],"genre_scores_gemma":[0.9652033,0.0025865287,0.028071271,0.00012322176,0.000041687945,0.000075799835,0.00024327367,0.00004424369,0.003610717],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995883,0.000054317647,0.00003366162,0.00007933702,0.00018677098,0.000057695408],"domain_scores_gemma":[0.9996606,0.00006415141,0.00010771203,0.00003284555,0.00011092004,0.000023765106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003384881,0.00048034784,0.00035912995,0.00035954893,0.00032412825,0.00044221026,0.00036501003,0.00082223123,0.000889043],"category_scores_gemma":[0.00038767306,0.00019331489,0.00049767864,0.00018946921,0.00018203011,0.00035743343,0.00023622994,0.00041202243,0.0004815875],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029723911,0.000012546539,0.00020839232,0.00009363052,0.0000051810975,0.00004322074,0.000010103335,0.000033383913,0.9968317,0.000022728145,0.00004200547,0.0026674154],"study_design_scores_gemma":[0.0000031057991,0.00014069669,0.0021063397,0.000012564855,0.000013291993,0.00018509652,0.000012281038,0.00034864934,0.99571395,0.00000978577,0.001449701,0.000004645079],"about_ca_topic_score_codex":0.0006159102,"about_ca_topic_score_gemma":0.0005309648,"teacher_disagreement_score":0.000889043,"about_ca_system_score_codex":0.0002970562,"about_ca_system_score_gemma":0.00022586643,"threshold_uncertainty_score":0.002974093},"labels":[],"label_agreement":null},{"id":"W4311950992","doi":"10.1016/j.jmapro.2022.12.019","title":"Indirect measurement of cutting forces during robotic milling using multiple sensors and a machine learning-based system identifier","year":2022,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Machining; Machine tool; Identifier; Accelerometer; Vibration; Modal analysis; Modal; Acceleration; Robot; Computer science; Kalman filter; Mechanical engineering; Engineering; Artificial intelligence; Acoustics; Materials science","score_opus":0.02056241809882155,"score_gpt":0.21359583829120984,"score_spread":0.19303342019238828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311950992","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.54589635,0.0009807105,0.44823098,0.00027586598,0.0003053561,0.00011235877,0.00017948683,0.00055497134,0.003463894],"genre_scores_gemma":[0.94630843,0.00015064042,0.05197283,0.000060930084,0.000051215004,0.00006154598,0.00006752559,0.000017094842,0.0013097218],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99956185,0.00005142114,0.000021359323,0.00008805769,0.00024020395,0.00003713714],"domain_scores_gemma":[0.9995028,0.00020138815,0.00010341285,0.000036236197,0.000127187,0.000029049868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032362805,0.00039200945,0.00053517317,0.0003250284,0.00026488912,0.00039212755,0.00038029542,0.0005659655,0.00088242895],"category_scores_gemma":[0.00085921655,0.00022876826,0.0001323854,0.000344655,0.00032717356,0.00044482856,0.00041363598,0.00049358007,0.0001753718],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009837318,0.00021185268,0.008918459,0.00031176533,0.00005263687,0.00012820968,0.00024371003,0.01123055,0.7539454,0.0006849705,0.0009677286,0.22232096],"study_design_scores_gemma":[0.00012486661,0.0016359375,0.09652223,0.00006919167,0.00012542467,0.0010186335,0.00015149504,0.5150454,0.37971053,0.0009254509,0.004562699,0.00010824809],"about_ca_topic_score_codex":0.00060280785,"about_ca_topic_score_gemma":0.0014662357,"teacher_disagreement_score":0.00088242895,"about_ca_system_score_codex":0.0001970033,"about_ca_system_score_gemma":0.0004520133,"threshold_uncertainty_score":0.0029519796},"labels":[],"label_agreement":null},{"id":"W4311968934","doi":"10.3390/ma15248781","title":"Self-Propelled Rotary Tools in Hard Turning: Analysis and Optimization via Finite Element Models","year":2022,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"King Abdulaziz City for Science and Technology","keywords":"Finite element method; Chip; Design of experiments; Displacement (psychology); Mechanical engineering; Central composite design; Stress (linguistics); Chip formation; Process (computing); Process variable; Matrix (chemical analysis); Materials science; Gaussian; Structural engineering; Response surface methodology; Engineering; Computer science; Tool wear; Machining; Composite material; Mathematics; Physics","score_opus":0.012599610000756914,"score_gpt":0.21378267899057868,"score_spread":0.20118306898982177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311968934","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19439147,0.00056007545,0.7943462,0.00012057093,0.00003003352,0.00015231043,0.00015055362,0.00042253835,0.009826162],"genre_scores_gemma":[0.8610922,0.0004639016,0.13402049,0.000030942338,0.000009620674,0.00033948396,0.00015917234,0.0000962939,0.0037877792],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997919,0.000056266235,0.0000072623307,0.000018280947,0.00010167456,0.000024601793],"domain_scores_gemma":[0.9994838,0.00035553076,0.000054029897,0.000024894707,0.0000671243,0.000014662266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051636575,0.00051752967,0.0007243179,0.0004990496,0.00025131495,0.0007155157,0.0006718616,0.0008494589,0.0012744671],"category_scores_gemma":[0.00095666794,0.00051105034,0.0006508063,0.00027565652,0.0004313551,0.00033025254,0.000356989,0.0004361562,0.0002579732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014825732,0.00001613795,0.00020032021,0.000029176023,0.0000054141365,0.000013535167,0.000016908169,0.99318475,0.0018139697,0.0006553537,0.000041757783,0.004007874],"study_design_scores_gemma":[0.0000037866014,0.000014184104,0.000077224824,0.0000042388388,0.0000020993066,0.000003998773,0.000006777898,0.99894637,0.00056037435,0.00016403562,0.0002145488,0.000002443343],"about_ca_topic_score_codex":0.004169807,"about_ca_topic_score_gemma":0.004741445,"teacher_disagreement_score":0.004169807,"about_ca_system_score_codex":0.00039816942,"about_ca_system_score_gemma":0.0006599111,"threshold_uncertainty_score":0.008291125},"labels":[],"label_agreement":null},{"id":"W4312125365","doi":"10.3390/f13122126","title":"Cutting Force and Surface Roughness during Straight-Tooth Milling of Walnut Wood","year":2022,"lang":"en","type":"article","venue":"Forests","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Qinglan Project of Jiangsu Province of China; National Natural Science Foundation of China","keywords":"Rake angle; Surface roughness; Machinability; Materials science; Juglans; Surface finish; Machining; Juglandaceae; Rake; Composite material; Mechanical engineering; Metallurgy; Engineering; Botany","score_opus":0.005332873162522233,"score_gpt":0.2067994743471217,"score_spread":0.20146660118459947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312125365","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99887997,0.00014446143,0.0008467465,0.0000036382387,0.0000022401719,0.0000060379634,0.000020687807,0.0000066219254,0.000089579655],"genre_scores_gemma":[0.99862814,0.00007966161,0.0010694589,0.000004744495,0.0000010687751,0.0000044366175,0.000038922542,0.0000033843994,0.00017011065],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997948,0.000021537202,0.000013579794,0.0000425342,0.000092530456,0.000035078257],"domain_scores_gemma":[0.99968266,0.00014874442,0.00007396151,0.000015460448,0.000062431456,0.000016663264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035430223,0.000225162,0.0003619641,0.0002512208,0.00015616168,0.00029537024,0.00016499574,0.00020313179,0.00036163002],"category_scores_gemma":[0.0005501206,0.00014470528,0.00035007746,0.0002004518,0.00016093205,0.00017239805,0.00012896763,0.00022915665,0.00006729505],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048704402,0.00011633234,0.0074268105,0.00011712662,0.000022790075,0.000097769014,0.00011596869,0.0046335375,0.9751594,0.000029404307,0.000035533067,0.011758185],"study_design_scores_gemma":[0.00002883518,0.0031169641,0.33112568,0.000017536402,0.00008930725,0.00015996606,0.0004333196,0.05114387,0.61313814,0.00009529708,0.0005978453,0.00005317559],"about_ca_topic_score_codex":0.002178957,"about_ca_topic_score_gemma":0.0040779384,"teacher_disagreement_score":0.002178957,"about_ca_system_score_codex":0.00018135738,"about_ca_system_score_gemma":0.00015905395,"threshold_uncertainty_score":0.0043325424},"labels":[],"label_agreement":null},{"id":"W4312419131","doi":"10.1115/msec2022-85157","title":"Estimating Milling Forces From Vibration Measurements","year":2022,"lang":"en","type":"article","venue":"Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Acceleration; Vibration; Accelerometer; Machining; Kalman filter; Deconvolution; Acoustics; Filter (signal processing); Control theory (sociology); Computer science; Engineering; Mechanical engineering; Physics; Computer vision; Algorithm; Artificial intelligence","score_opus":0.009388087520941106,"score_gpt":0.20354295752789064,"score_spread":0.19415487000694953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312419131","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18770969,0.00024703518,0.8104111,0.000036896927,0.000021632723,0.000040448173,0.00009659783,0.00051629293,0.00092030957],"genre_scores_gemma":[0.8587554,0.0002326813,0.13929296,0.000017332142,0.000019646728,0.00004910345,0.00017098416,0.000046055193,0.00141585],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99975926,0.00002685703,0.000014006117,0.000068042405,0.00011136931,0.000020511874],"domain_scores_gemma":[0.99959975,0.00019153958,0.00007894666,0.000035817782,0.000080969185,0.0000129595055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002847774,0.00068305986,0.00044906922,0.00059764576,0.000136826,0.00043236188,0.000272949,0.00049397704,0.0010135522],"category_scores_gemma":[0.0011119425,0.00028936908,0.000269352,0.00030950436,0.00022142293,0.00046874405,0.00038215198,0.00045612935,0.00031576215],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003465404,0.000117423704,0.009818431,0.0003233013,0.00007433991,0.00011563233,0.00010380816,0.27102038,0.33844197,0.0011824049,0.00049296714,0.37796283],"study_design_scores_gemma":[0.000018289718,0.00013630858,0.00955118,0.000017316523,0.000019928724,0.00004154715,0.000024907842,0.9079045,0.08083893,0.0006906883,0.0007299667,0.000026374873],"about_ca_topic_score_codex":0.0016142136,"about_ca_topic_score_gemma":0.0018829824,"teacher_disagreement_score":0.0016142136,"about_ca_system_score_codex":0.00021169998,"about_ca_system_score_gemma":0.00043745682,"threshold_uncertainty_score":0.0033906698},"labels":[],"label_agreement":null},{"id":"W4312901390","doi":"10.11159/jffhmt.2022.021","title":"Numerical Investigation of Convective Heat Transfer during Orthogonal Cutting Processes","year":2022,"lang":"en","type":"article","venue":"Journal of Fluid Flow Heat and Mass Transfer","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Convective heat transfer; Convection; Heat transfer; Mechanics; Materials science; Physics","score_opus":0.007083256902047737,"score_gpt":0.20175842396875376,"score_spread":0.19467516706670604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312901390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9248648,0.00046099027,0.06016076,0.00022258978,0.00008096346,0.00009122573,0.0001990874,0.00017993408,0.013739639],"genre_scores_gemma":[0.9907636,0.000110652625,0.0074793743,0.000014550625,0.0000091194,0.000035722325,0.000049453654,0.000015747806,0.0015217849],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980706,0.00003632038,0.000008692518,0.000031483913,0.00006560747,0.000050920993],"domain_scores_gemma":[0.999464,0.00031360227,0.00008908017,0.00003700923,0.00006125702,0.000035023833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004166718,0.00037301035,0.0004624528,0.00044134716,0.00047452195,0.0008317731,0.0005475445,0.0010287131,0.0013774845],"category_scores_gemma":[0.0016098007,0.00021127812,0.000362414,0.00039737218,0.0010049241,0.0004064547,0.00048411018,0.00046553824,0.00012253523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019216987,0.00016695562,0.0030299646,0.00013324694,0.000019018886,0.00026596437,0.00023797163,0.95284,0.028246388,0.00763224,0.00026209507,0.0069740172],"study_design_scores_gemma":[0.0000104567525,0.000069291156,0.0005723236,0.000004745308,0.00000330013,0.000023518249,0.000022064334,0.99623257,0.002496394,0.00033222316,0.00022721842,0.000005933485],"about_ca_topic_score_codex":0.003350847,"about_ca_topic_score_gemma":0.00147489,"teacher_disagreement_score":0.003350847,"about_ca_system_score_codex":0.0005376022,"about_ca_system_score_gemma":0.0006182377,"threshold_uncertainty_score":0.0066627264},"labels":[],"label_agreement":null},{"id":"W4313443942","doi":"10.1007/978-981-19-6945-4_51","title":"Analysis of Chip Morphology Using Machine Learning Technique","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Machining; Chip; Inconel; Chip formation; Tool wear; Process (computing); Materials science; Superalloy; Mechanical engineering; Machine tool; MATLAB; Computer science; Engineering drawing; Engineering; Metallurgy","score_opus":0.011990710452046945,"score_gpt":0.23255942018786777,"score_spread":0.22056870973582082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313443942","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032409225,0.00074569223,0.9623228,0.00006742691,0.000041323194,0.00005113909,0.00015806212,0.0012718617,0.0029324647],"genre_scores_gemma":[0.2887811,0.0011468902,0.70091856,0.00005377968,0.000033256067,0.00008157607,0.0005665797,0.00034232583,0.008075866],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99982244,0.000018571594,0.000010940858,0.000039068334,0.00009171595,0.00001726297],"domain_scores_gemma":[0.999373,0.00023053025,0.00006223252,0.00010996666,0.00021142725,0.000012815268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027340138,0.0004067619,0.00051984744,0.0011766686,0.0002546648,0.00080580555,0.0006016335,0.00041763773,0.0034200149],"category_scores_gemma":[0.00075023604,0.0003173018,0.0005810537,0.0011300698,0.0002718149,0.0007381953,0.0002823424,0.00054815155,0.0010691676],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006981103,0.00006842043,0.0025161759,0.0003511808,0.00005451312,0.00018951288,0.000112681926,0.07266171,0.21297973,0.0061487905,0.0026412022,0.7022063],"study_design_scores_gemma":[0.000004545319,0.00009292161,0.006585774,0.000025912543,0.000036104684,0.00044584976,0.000052672374,0.91552925,0.066518955,0.0039396095,0.0067402446,0.00002808585],"about_ca_topic_score_codex":0.00085193565,"about_ca_topic_score_gemma":0.0015231486,"teacher_disagreement_score":0.0034200149,"about_ca_system_score_codex":0.00029804057,"about_ca_system_score_gemma":0.00045418297,"threshold_uncertainty_score":0.011441112},"labels":[],"label_agreement":null},{"id":"W4313593459","doi":"10.1016/j.jmatprotec.2023.117867","title":"Numerical CFD-FEM model for machining titanium Ti-6Al-4V with nano minimum quantity lubrication: A step towards digital twin","year":2023,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Lubrication; Computational fluid dynamics; Materials science; Finite element method; Mechanical engineering; Nanofluid; Heat transfer coefficient; Heat transfer; Mechanics; Engineering; Composite material; Structural engineering; Physics","score_opus":0.015894871744193274,"score_gpt":0.2630142551216813,"score_spread":0.24711938337748804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313593459","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.081615716,0.0012430303,0.8546659,0.0007218667,0.00040351745,0.0001610468,0.00096048263,0.0015823105,0.058646142],"genre_scores_gemma":[0.83367854,0.0007528522,0.12947398,0.00017656243,0.00005772249,0.00025579234,0.0007759211,0.00026016982,0.034568284],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990034,0.000013252381,0.0000050904646,0.000017363467,0.00005139962,0.000012525569],"domain_scores_gemma":[0.9998715,0.000040264757,0.000016669686,0.00001552315,0.00004624352,0.000009741757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014348954,0.0003150471,0.0004671608,0.0002542376,0.000360838,0.0005289382,0.0010759291,0.0011214681,0.0058479314],"category_scores_gemma":[0.0004696489,0.0003071328,0.00047638392,0.0002974728,0.00032381012,0.00047859826,0.00040685516,0.00041075575,0.00092714507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006351604,0.000037035155,0.0006097513,0.00013436232,0.00001660151,0.00009939082,0.00006200819,0.96584773,0.0090754535,0.009793604,0.001238045,0.013022483],"study_design_scores_gemma":[0.000006290266,0.000013308761,0.0001092582,0.0000049998316,0.0000030171411,0.000024719577,0.000006684073,0.99676275,0.00076012046,0.0005028935,0.0018015152,0.000004549248],"about_ca_topic_score_codex":0.0081509,"about_ca_topic_score_gemma":0.006139878,"teacher_disagreement_score":0.0081509,"about_ca_system_score_codex":0.00047020166,"about_ca_system_score_gemma":0.0011453519,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4313639700","doi":"10.1016/j.jmapro.2022.12.047","title":"Initial tool wear and process monitoring during titanium metal matrix composite machining (TiMMC)","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Tool wear; Materials science; Machining; Machinability; Abrasion (mechanical); Scanning electron microscope; Composite material; Titanium; Cutting tool; Tool steel; Metallurgy","score_opus":0.010402370337322286,"score_gpt":0.2764437532476456,"score_spread":0.2660413829103233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313639700","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974782,0.00013728986,0.0015227066,0.00001155115,0.000013001249,0.000014961307,0.0001496257,0.0000783332,0.00059445825],"genre_scores_gemma":[0.9988134,0.000018191648,0.0005198931,0.0000058686933,0.0000030687079,0.0000059478352,0.00008308993,0.000009611902,0.00054096873],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997328,0.00002031634,0.000010912587,0.000049344446,0.00013500838,0.000051546456],"domain_scores_gemma":[0.9991234,0.00035026646,0.0001098762,0.00011328158,0.0002422424,0.00006091515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026818478,0.00025606842,0.0003751799,0.0005130512,0.00044299735,0.00031980366,0.00039474678,0.00057765935,0.0016939968],"category_scores_gemma":[0.0010051583,0.00017975477,0.00023465743,0.00030611057,0.00027003107,0.00031737532,0.00026617319,0.00040349946,0.00024199093],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003906363,0.0002506083,0.02426252,0.00018834624,0.000032940192,0.0007511541,0.0010704797,0.0017881095,0.93189186,0.00010890492,0.0006631931,0.03508546],"study_design_scores_gemma":[0.000037472262,0.0035515572,0.33958325,0.000025705895,0.00005364624,0.00085280614,0.0006985967,0.016424438,0.63655365,0.00010362973,0.0020584397,0.000056890436],"about_ca_topic_score_codex":0.0013459296,"about_ca_topic_score_gemma":0.0026958496,"teacher_disagreement_score":0.0016939968,"about_ca_system_score_codex":0.00026084986,"about_ca_system_score_gemma":0.00017489969,"threshold_uncertainty_score":0.005666971},"labels":[],"label_agreement":null},{"id":"W4317628592","doi":"10.1108/ijieom-11-2022-0059","title":"Investigation of the effect of vibration in the multi-objective optimization of dry turning of hardened steel","year":2023,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering and Operations Management","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Taguchi methods; Vibration; Hardened steel; Machining; Ceramic; Numerical control; Engineering; Tool wear; Design of experiments; Mechanical engineering; TOPSIS; Materials science; Mathematics; Metallurgy; Composite material; Acoustics; Statistics","score_opus":0.013637079780844464,"score_gpt":0.23522499773842528,"score_spread":0.22158791795758082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317628592","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84625626,0.00051784917,0.15083015,0.00003702336,0.000018195899,0.00006309518,0.000030299567,0.00007505047,0.0021721274],"genre_scores_gemma":[0.9871471,0.00005277164,0.012360219,0.000009716049,0.0000019662991,0.00001959408,0.000016084297,0.000008365156,0.00038409783],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968576,0.00006720423,0.00001561698,0.000054396867,0.00014157256,0.000035468693],"domain_scores_gemma":[0.99958664,0.00024208051,0.00007853487,0.000020065301,0.000058118774,0.000014548023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048160285,0.00039860976,0.00039346397,0.0002505176,0.00014965849,0.00050500006,0.00025588076,0.000369229,0.00073907414],"category_scores_gemma":[0.0006944405,0.00017643835,0.0003860947,0.000120852754,0.00018824902,0.00019439508,0.00026803502,0.0003103867,0.00007006687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005307894,0.00027459182,0.004125681,0.0006211691,0.000091438866,0.0001612654,0.00011504858,0.56322366,0.3433391,0.0005110976,0.00011630531,0.08688981],"study_design_scores_gemma":[0.000034582124,0.0019818952,0.01261213,0.000025213121,0.000059427774,0.00008327439,0.00009880981,0.91985637,0.06434864,0.00029693404,0.0005770004,0.000025796466],"about_ca_topic_score_codex":0.00093088706,"about_ca_topic_score_gemma":0.0013240428,"teacher_disagreement_score":0.00093088706,"about_ca_system_score_codex":0.00019213294,"about_ca_system_score_gemma":0.00026148235,"threshold_uncertainty_score":0.0025470257},"labels":[],"label_agreement":null},{"id":"W4318703265","doi":"10.15376/biores.18.1.2024-2044","title":"Improved life of circular saws used in primary wood processing","year":2023,"lang":"en","type":"article","venue":"BioResources","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"FPInnovations; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; FPInnovations","keywords":"Circular saw; Materials science; Cracking; Composite material; Machining; Waterfall; Crown (dentistry); Rake; Structural engineering; Engineering; Metallurgy; Mechanical engineering","score_opus":0.010637259825156408,"score_gpt":0.2176922388884968,"score_spread":0.2070549790633404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318703265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99855465,0.00038708356,0.0008416779,0.000008590031,0.00001108607,0.00000661187,0.00003069963,0.000018014589,0.00014153637],"genre_scores_gemma":[0.997159,0.00018009866,0.0019407483,0.000012133489,0.000005272123,0.000007176483,0.00008480486,0.000014761646,0.00059602753],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99967754,0.000027388205,0.000028961056,0.0000908716,0.00010453525,0.00007074901],"domain_scores_gemma":[0.9993926,0.00013211508,0.00016444275,0.000067952875,0.00013843086,0.00010449538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029281146,0.00029925237,0.00030863748,0.00021946443,0.00012744793,0.00027339775,0.00026026956,0.00029131255,0.0008905364],"category_scores_gemma":[0.0007819426,0.00020238476,0.00025582954,0.0002214525,0.00015095698,0.00023235848,0.00027186028,0.0003593829,0.0002079741],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022272184,0.000040194613,0.0012868864,0.000054606,0.0000053399867,0.00005871927,0.00005906017,0.00017006256,0.9919739,0.00001298905,0.000023888788,0.00609181],"study_design_scores_gemma":[0.000009193575,0.0021631387,0.02355991,0.000006772611,0.000027330294,0.00017337826,0.0000830482,0.0014181753,0.9714489,0.000016570055,0.001083064,0.000010518806],"about_ca_topic_score_codex":0.0003860137,"about_ca_topic_score_gemma":0.001053992,"teacher_disagreement_score":0.0008905364,"about_ca_system_score_codex":0.0001285833,"about_ca_system_score_gemma":0.00013837885,"threshold_uncertainty_score":0.0029790998},"labels":[],"label_agreement":null},{"id":"W4319457633","doi":"10.1139/tcsme-2022-0150","title":"The effect of piercing and drilling processes on burr formation and delamination of aged carbon and aramid fiber-reinforced polymer composites","year":2023,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Aramid; Fibre-reinforced plastic; Delamination (geology); Materials science; Composite material; Drilling; Machining; Fiber; Metallurgy","score_opus":0.004058499340840628,"score_gpt":0.18936708147984668,"score_spread":0.18530858213900606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319457633","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989623,0.00041648615,0.0004859676,0.0000033497322,0.0000049960963,0.0000027403698,0.000014926902,0.000007719214,0.000101590085],"genre_scores_gemma":[0.9982881,0.0002026199,0.0012430158,0.0000064825936,0.0000019517176,0.0000029234614,0.000027423244,0.000005705379,0.00022178823],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996859,0.000049841266,0.00003286186,0.000047476664,0.00012595736,0.000057976176],"domain_scores_gemma":[0.9990007,0.00021121025,0.0004259056,0.000066869434,0.00020562967,0.00008969128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038438514,0.00034717514,0.00019334475,0.00025399338,0.00014939344,0.00020326294,0.00014263639,0.000273331,0.0003340419],"category_scores_gemma":[0.0006118643,0.00024088137,0.000247268,0.00017459076,0.00025170704,0.00030547267,0.00017072067,0.0003185008,0.00006834357],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022897428,0.000028851262,0.0015028956,0.00009162907,0.000010902187,0.00014587716,0.00010777058,0.0006180015,0.9944593,0.00002486342,0.000012823161,0.0027681303],"study_design_scores_gemma":[0.000005470632,0.0014588762,0.01658986,0.000008419193,0.000029848603,0.0002078948,0.000120292294,0.0016638548,0.9794648,0.0000155771,0.00042045195,0.000014499485],"about_ca_topic_score_codex":0.0005665724,"about_ca_topic_score_gemma":0.0013780744,"teacher_disagreement_score":0.0005665724,"about_ca_system_score_codex":0.00014410478,"about_ca_system_score_gemma":0.000119512726,"threshold_uncertainty_score":0.002032876},"labels":[],"label_agreement":null},{"id":"W4321112896","doi":"10.1002/mawe.202200136","title":"Optimization of cutting power and power efficiency during particleboard helical milling","year":2023,"lang":"en","type":"article","venue":"Materialwissenschaft und Werkstofftechnik","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Materials science; Power (physics); Machining; Spiral (railway); Work (physics); Mechanical engineering; Helix angle; Efficient energy use; Response surface methodology; Composite material; Engineering drawing; Metallurgy; Engineering; Chemistry; Chromatography; Electrical engineering; Thermodynamics; Physics","score_opus":0.004658937818262681,"score_gpt":0.22683401129429898,"score_spread":0.2221750734760363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321112896","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9805931,0.000489079,0.01806881,0.000023226663,0.00001016538,0.000031698346,0.00007929096,0.00008709937,0.0006175342],"genre_scores_gemma":[0.99420375,0.00020763035,0.0051427986,0.0000068296895,0.0000014921702,0.00001131632,0.000051789113,0.000017800421,0.00035659733],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997688,0.000032373155,0.000018334544,0.000047444573,0.000088409935,0.000044601646],"domain_scores_gemma":[0.99970585,0.000119489,0.000079833415,0.000023753833,0.00005514332,0.00001582787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044550988,0.00044035455,0.0004074451,0.0002443234,0.00012975548,0.00047518619,0.00019318426,0.00022961,0.0006381415],"category_scores_gemma":[0.00059525814,0.00019092181,0.00028010202,0.00036543407,0.00021093796,0.00027287094,0.0001389233,0.00024315748,0.00016836563],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044536142,0.000060884602,0.0015492693,0.00017358226,0.000017601764,0.000051288018,0.00005278241,0.010091176,0.97063035,0.00006335955,0.000051161398,0.016813183],"study_design_scores_gemma":[0.000012366035,0.00049138855,0.0070930445,0.0000047763506,0.000019582158,0.000019223397,0.000042384523,0.013832257,0.97792304,0.000036860958,0.0005167901,0.0000082728875],"about_ca_topic_score_codex":0.0005788871,"about_ca_topic_score_gemma":0.00097467605,"teacher_disagreement_score":0.0006381415,"about_ca_system_score_codex":0.00020362218,"about_ca_system_score_gemma":0.00016664977,"threshold_uncertainty_score":0.002356112},"labels":[],"label_agreement":null},{"id":"W4321241863","doi":"10.1007/s00170-023-11013-z","title":"A novel high-order discretization method for the milling stability prediction considering the differential of directional cutting coefficient and vibration velocities","year":2023,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Discretization; Floquet theory; Stability (learning theory); Mathematics; Coefficient matrix; Matrix (chemical analysis); Vibration; Finite element method; Monodromy matrix; Applied mathematics; Algorithm; Mathematical optimization; Mathematical analysis; Eigenvalues and eigenvectors; Computer science; Engineering; Structural engineering; Physics; Acoustics; Materials science; Nonlinear system","score_opus":0.011183471177967986,"score_gpt":0.25383095306625186,"score_spread":0.2426474818882839,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321241863","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059532295,0.00013682892,0.99200785,0.000048374815,0.00007388311,0.000025277588,0.00002832965,0.00018605146,0.001540169],"genre_scores_gemma":[0.38346314,0.00044318504,0.60992986,0.00014335025,0.00010907342,0.00024598435,0.00022280429,0.00015952362,0.005283148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982625,0.000034889952,0.000011117169,0.000033166765,0.00007743163,0.000017152344],"domain_scores_gemma":[0.99966514,0.00014082619,0.000028787768,0.000033225362,0.00010281078,0.000029162242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034638037,0.0004655684,0.0007946039,0.0003200385,0.000495862,0.0006477417,0.0011669308,0.0010995032,0.003076209],"category_scores_gemma":[0.00067405787,0.0003540284,0.0006372875,0.00042372377,0.00039147207,0.0007134645,0.0005391093,0.0010891831,0.0006001476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015164784,0.00016543824,0.0013299822,0.00031481788,0.00007742658,0.00018981883,0.00014018927,0.7964279,0.03410275,0.016156623,0.0025047737,0.14843868],"study_design_scores_gemma":[0.0000042227193,0.000007733442,0.00003650486,0.0000027769804,0.0000017326962,0.000006686421,0.0000023810446,0.9988955,0.00036170863,0.00035313194,0.00032498967,0.000002548354],"about_ca_topic_score_codex":0.006423338,"about_ca_topic_score_gemma":0.0063536344,"teacher_disagreement_score":0.006423338,"about_ca_system_score_codex":0.00037204634,"about_ca_system_score_gemma":0.001165283,"threshold_uncertainty_score":0.012771845},"labels":[],"label_agreement":null},{"id":"W4321787857","doi":"10.1142/s0218625x23500257","title":"EXPERIMENTAL EVALUATION OF PARAMETERS AFFECTING DELAMINATION FACTOR, TENSILE STRENGTH, THRUST FORCE AND SURFACE ROUGHNESS IN DRILLING OF GFRP","year":2023,"lang":"en","type":"article","venue":"Surface Review and Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Delamination (geology); Fibre-reinforced plastic; Materials science; Drilling; Composite material; Ultimate tensile strength; Surface roughness; Thrust; Machining; Surface finish; Composite number; Fiber pull-out; Structural engineering; Composite laminates; Mechanical engineering; Metallurgy; Engineering; Geology","score_opus":0.025040570347475165,"score_gpt":0.2951613159666815,"score_spread":0.27012074561920635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321787857","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975847,0.0003713995,0.0016253128,0.000010804647,0.000011278307,0.000019473568,0.00007154664,0.00001817348,0.00028731025],"genre_scores_gemma":[0.996876,0.0003613762,0.002347572,0.000007342419,0.0000035226456,0.000019524052,0.00005493198,0.000008776678,0.0003208957],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995633,0.00005547115,0.00004081306,0.00006383832,0.00021576113,0.00006076143],"domain_scores_gemma":[0.99876404,0.00043688496,0.00029135775,0.00011281613,0.00035027607,0.000044612734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056118687,0.00033069326,0.00034181116,0.00022820142,0.00021616861,0.0001680362,0.00019168793,0.00041631842,0.0005640911],"category_scores_gemma":[0.0009778189,0.00025024902,0.00026738667,0.00030518768,0.00035138498,0.0003167354,0.00017854042,0.0003974974,0.00009878674],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017696305,0.00005948098,0.000730566,0.00015439084,0.0000080214895,0.000057169906,0.00010889928,0.00076591683,0.9952892,0.00003474723,0.000032003387,0.0025826534],"study_design_scores_gemma":[0.000009781043,0.00120734,0.007989054,0.000008417357,0.000023015451,0.000054888013,0.00008629901,0.0019178585,0.9882483,0.00001864033,0.0004210889,0.000015391086],"about_ca_topic_score_codex":0.0007476517,"about_ca_topic_score_gemma":0.0013816007,"teacher_disagreement_score":0.0007476517,"about_ca_system_score_codex":0.00016381829,"about_ca_system_score_gemma":0.00013952547,"threshold_uncertainty_score":0.002967894},"labels":[],"label_agreement":null},{"id":"W4322207938","doi":"10.1007/s00170-023-11113-w","title":"Sensor fusion and the application of artificial intelligence to identify tool wear in turning operations","year":2023,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Trent University; Nottingham Trent University","keywords":"Sensor fusion; Tool wear; Engineering; Artificial neural network; Novelty detection; Artificial intelligence; Signal processing; Learning vector quantization; SIGNAL (programming language); Fusion; Control engineering; Machine learning; Computer science; Novelty; Electronic engineering; Digital signal processing; Machining; Mechanical engineering","score_opus":0.009431795264016283,"score_gpt":0.29051779618378865,"score_spread":0.28108600091977237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322207938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1896255,0.00095955166,0.8064978,0.00018598964,0.00009122236,0.000043398297,0.000045459386,0.00042582466,0.0021251587],"genre_scores_gemma":[0.98342943,0.000121716264,0.016047345,0.000018907194,0.000015723002,0.0000107158385,0.000018019084,0.0000065654826,0.00033150185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996344,0.00008196007,0.000019777633,0.00005865919,0.00017393474,0.00003117595],"domain_scores_gemma":[0.99958414,0.00021882281,0.00005900966,0.000033195374,0.00009429519,0.000010603252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063110836,0.00033749212,0.0004476236,0.0008038844,0.00017286983,0.00046375283,0.0003520026,0.00043980984,0.00045044094],"category_scores_gemma":[0.0014108892,0.00014557898,0.00043549002,0.00046952916,0.00042023018,0.000598298,0.00030828424,0.00035397796,0.00007825835],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000359685,0.00015824713,0.0058613434,0.00020006506,0.00012964019,0.0002894365,0.00018177449,0.70205015,0.0641702,0.0049996,0.0005736685,0.22102623],"study_design_scores_gemma":[0.0000035280145,0.000087345645,0.002946585,0.0000059428176,0.0000113950555,0.000053240477,0.000022181448,0.9889635,0.0058195177,0.0018186835,0.00025833523,0.000009687603],"about_ca_topic_score_codex":0.0013991152,"about_ca_topic_score_gemma":0.000833411,"teacher_disagreement_score":0.0013991152,"about_ca_system_score_codex":0.00029634958,"about_ca_system_score_gemma":0.00018007074,"threshold_uncertainty_score":0.0033376813},"labels":[],"label_agreement":null},{"id":"W4322755439","doi":"10.1520/jte20220469","title":"Predicting the Magnitude of Microsphere Parameters Obtained from Microscopical Examination of Hardened Concrete","year":2023,"lang":"en","type":"article","venue":"Journal of Testing and Evaluation","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Discovery Centre","funders":"","keywords":"Microsphere; Volume (thermodynamics); Volume fraction; Materials science; Fraction (chemistry); Magnitude (astronomy); Composite material; Specific surface area; Chemistry; Chromatography; Thermodynamics; Physics","score_opus":0.03470064540455073,"score_gpt":0.28162946187081556,"score_spread":0.24692881646626483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322755439","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9370461,0.000117751675,0.061873116,0.000013807936,0.0000044269646,0.000041989413,0.00010846675,0.00021416512,0.00058013014],"genre_scores_gemma":[0.9904501,0.000048687278,0.009259492,0.0000031925038,0.0000014249589,0.000013330114,0.00007406675,0.00001166823,0.00013811387],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953794,0.0000925493,0.000026413729,0.00009656508,0.00021098957,0.000035460907],"domain_scores_gemma":[0.9975694,0.001308208,0.00059464166,0.00013224722,0.0003160421,0.000079462414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011325517,0.00042105396,0.00022829673,0.0013998756,0.00014623761,0.00045748704,0.00032682158,0.00032680633,0.0004984466],"category_scores_gemma":[0.0039083506,0.00031149245,0.00026745631,0.0003223732,0.00041109358,0.00060133706,0.00039137746,0.00034574873,0.0001880829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005513174,0.000059331982,0.13333033,0.00018487913,0.00007184204,0.00019374823,0.00014077408,0.26560053,0.56626,0.0009834084,0.00007366062,0.032550156],"study_design_scores_gemma":[0.000014037265,0.0006412702,0.19354984,0.00002261438,0.000059989074,0.00021228338,0.00014748482,0.36327064,0.44051236,0.001048754,0.0004508785,0.00006994116],"about_ca_topic_score_codex":0.0014806159,"about_ca_topic_score_gemma":0.0022281809,"teacher_disagreement_score":0.0014806159,"about_ca_system_score_codex":0.00072681304,"about_ca_system_score_gemma":0.00024592315,"threshold_uncertainty_score":0.0059895515},"labels":[],"label_agreement":null},{"id":"W4323041803","doi":"10.18280/mmep.100121","title":"Experimental and Metamodel Based Optimization of Cutting Parameters for Milling Inconel-800 Superalloy Under Nanofluid MQL Condition","year":2023,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Trường Đại học Nha Trang","keywords":"Inconel; Machining; Machinability; Lubrication; Superalloy; Nanofluid; Materials science; Mechanical engineering; Tool wear; Metallurgy; Process engineering; Computer science; Nanoparticle; Composite material; Engineering; Microstructure; Nanotechnology","score_opus":0.025105839822679693,"score_gpt":0.23483298008294373,"score_spread":0.20972714026026404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323041803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96672064,0.00023817352,0.027689453,0.00009605906,0.000026125794,0.000047489466,0.00021631105,0.00019351482,0.004772139],"genre_scores_gemma":[0.9903018,0.00005002658,0.009093457,0.0000058147766,0.0000010920569,0.000030809373,0.00007079729,0.0000105241825,0.00043569447],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998797,0.000014416614,0.000007155865,0.000028971666,0.000047678863,0.000022010296],"domain_scores_gemma":[0.99966574,0.000131546,0.00006871013,0.00003784386,0.00008414576,0.00001199797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048223842,0.00044895493,0.00040292114,0.00032933097,0.00030799874,0.00038709235,0.00034636716,0.0005963069,0.0014577848],"category_scores_gemma":[0.0005717297,0.00017595802,0.0003995548,0.00036641295,0.00024930714,0.00031757297,0.00020431161,0.00034776345,0.00011820245],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004727195,0.00053280976,0.004236495,0.0008375706,0.000045485816,0.00019219788,0.00023086928,0.68675,0.27005672,0.0016532497,0.00079768867,0.034194235],"study_design_scores_gemma":[0.00004476175,0.0010034698,0.0050305235,0.000018384557,0.00003212497,0.000032637556,0.00012912258,0.85543984,0.13708657,0.00031127877,0.0008392621,0.00003197639],"about_ca_topic_score_codex":0.0018459028,"about_ca_topic_score_gemma":0.0029489177,"teacher_disagreement_score":0.0018459028,"about_ca_system_score_codex":0.00029988756,"about_ca_system_score_gemma":0.00033327655,"threshold_uncertainty_score":0.004876733},"labels":[],"label_agreement":null},{"id":"W4323051784","doi":"10.1016/j.jmapro.2023.02.051","title":"Straightening of the rollers of planetary roller screw — Design of straightening die and experimental validation","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"National Natural Science Foundation of China","keywords":"Die (integrated circuit); Carburizing; Materials science; Mechanical engineering; Smoothness; Process (computing); Bending; Deformation (meteorology); Tooth surface; Structural engineering; Engineering; Composite material; Computer science; Metallurgy","score_opus":0.017760173743428018,"score_gpt":0.2300646430750977,"score_spread":0.2123044693316697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323051784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9050885,0.00034504413,0.08870233,0.00006583659,0.000044879915,0.00032513135,0.00021494647,0.0003997373,0.004813659],"genre_scores_gemma":[0.9681074,0.00015135523,0.02960974,0.00001189264,0.0000044483054,0.00010013103,0.00012574093,0.00003172617,0.0018574271],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99953306,0.00007316463,0.000024602017,0.0000997321,0.00021482923,0.000054710054],"domain_scores_gemma":[0.99892235,0.00037254073,0.00015512858,0.00019415926,0.0003161522,0.000039649203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082106894,0.0006444959,0.00061146705,0.00051659,0.00041133605,0.00057733955,0.0011052254,0.0008679525,0.0030820873],"category_scores_gemma":[0.001298413,0.00051296904,0.00046205972,0.00032004036,0.0005239235,0.0005111295,0.00033478535,0.0005101879,0.00044604723],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010410676,0.00079503364,0.0062240795,0.0009122711,0.00009386718,0.00026966888,0.0004916825,0.24245165,0.64415246,0.0049098716,0.0006554254,0.098002866],"study_design_scores_gemma":[0.00018647389,0.004931185,0.010699403,0.000045548757,0.0001142029,0.00014507484,0.00019277466,0.3695277,0.60725754,0.00059270713,0.0062493486,0.00005798941],"about_ca_topic_score_codex":0.0009769957,"about_ca_topic_score_gemma":0.0011935333,"teacher_disagreement_score":0.0030820873,"about_ca_system_score_codex":0.0003936553,"about_ca_system_score_gemma":0.0007921582,"threshold_uncertainty_score":0.01031065},"labels":[],"label_agreement":null},{"id":"W4323658000","doi":"10.1016/j.jmrt.2023.03.044","title":"Experimental and numerical analyses of residual stress redistributions in large steel dies: Influence of tempering cycles and rough milling","year":2023,"lang":"en","type":"article","venue":"Journal of Materials Research and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cégep de Sorel-Tracy; École de Technologie Supérieure","funders":"Mitacs","keywords":"Tempering; Residual stress; Materials science; Quenching (fluorescence); Residual; Ultimate tensile strength; Metallurgy; Composite material; Finite element method; Structural engineering; Optics; Computer science; Engineering","score_opus":0.039232610581235325,"score_gpt":0.3813107365988486,"score_spread":0.3420781260176133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323658000","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976687,0.00007934847,0.0018530503,0.000007421799,0.000004185362,0.0000056236368,0.000052699328,0.000049063125,0.00028001526],"genre_scores_gemma":[0.99848217,0.000026476422,0.0012897943,0.0000021665664,0.000001453707,0.0000054427082,0.000029873923,0.000006989042,0.000155694],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983585,0.000016915905,0.000011029655,0.000035724293,0.00007360144,0.000026739986],"domain_scores_gemma":[0.9993461,0.00025650044,0.00010450546,0.00013299442,0.00013009289,0.000029812103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030553268,0.0003015369,0.0002707444,0.0003005831,0.00020941693,0.0001434764,0.0003062454,0.00031595276,0.0011317482],"category_scores_gemma":[0.0006898469,0.0001684284,0.00020961571,0.0002461204,0.000439727,0.00020235313,0.00015016523,0.0002267859,0.00009697595],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041786724,0.00010061653,0.0028533519,0.00011305309,0.0000133788435,0.00014354588,0.00021264351,0.026064627,0.9610463,0.00016765129,0.000085856365,0.0087811295],"study_design_scores_gemma":[0.00003638037,0.0020948031,0.031280313,0.00001151996,0.000033503475,0.00014904945,0.00016587992,0.102102116,0.8633375,0.00014047443,0.0006117085,0.000036675112],"about_ca_topic_score_codex":0.00047738015,"about_ca_topic_score_gemma":0.00080814987,"teacher_disagreement_score":0.0011317482,"about_ca_system_score_codex":0.00017160247,"about_ca_system_score_gemma":0.0000875434,"threshold_uncertainty_score":0.003786087},"labels":[],"label_agreement":null},{"id":"W4323857568","doi":"10.1016/j.jmapro.2023.02.032","title":"Direct calculation of Johnson-Cook constitutive material parameters for oblique cutting operations","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Machining; Constitutive equation; Chip formation; Split-Hopkinson pressure bar; Strain hardening exponent; Hardening (computing); Mechanical engineering; Strain rate; Inverse; Mechanics; Structural engineering; Finite element method; Composite material; Tool wear; Geometry; Metallurgy; Engineering; Mathematics","score_opus":0.015619777277394439,"score_gpt":0.2600584906045725,"score_spread":0.24443871332717804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323857568","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1985715,0.0008039885,0.71906096,0.00027040867,0.00015655546,0.0002755887,0.00054452283,0.0014578197,0.078858726],"genre_scores_gemma":[0.81905425,0.00039247557,0.16553393,0.00008811353,0.000040341078,0.00018139892,0.00024579582,0.00065908476,0.013804526],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997981,0.000025156725,0.0000077994655,0.00001623833,0.00012630303,0.000026450758],"domain_scores_gemma":[0.99931145,0.00029637228,0.00005250635,0.00009926415,0.00021595645,0.000024411549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037705715,0.0005656325,0.0008254247,0.0005812562,0.0005187651,0.0008183865,0.0012202837,0.0009052516,0.0067941877],"category_scores_gemma":[0.0017132016,0.00061117596,0.00044387468,0.00070498185,0.00039058508,0.0009467658,0.00061710563,0.0007947429,0.00113413],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000186267,0.00026139463,0.0018403427,0.00050778897,0.000041667317,0.0002725043,0.00021618667,0.84731984,0.021723708,0.033261374,0.0031910383,0.09117787],"study_design_scores_gemma":[0.00003338581,0.000029462144,0.00059330283,0.000018005863,0.000013664905,0.00005348466,0.00003731364,0.9902755,0.004907006,0.002166321,0.0018603946,0.000012137116],"about_ca_topic_score_codex":0.005916078,"about_ca_topic_score_gemma":0.016319593,"teacher_disagreement_score":0.0067941877,"about_ca_system_score_codex":0.0007517833,"about_ca_system_score_gemma":0.001914325,"threshold_uncertainty_score":0.0227288},"labels":[],"label_agreement":null},{"id":"W4353098262","doi":"10.1016/j.jsv.2023.117687","title":"A whole discretization method for milling stability prediction considering the discrete vibration velocities","year":2023,"lang":"en","type":"article","venue":"Journal of Sound and Vibration","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Discretization; Floquet theory; Vibration; Stability (learning theory); Mathematics; Discretization of continuous features; Matrix (chemical analysis); Discretization error; Control theory (sociology); Applied mathematics; Mathematical analysis; Computer science; Physics; Nonlinear system; Materials science; Acoustics; Artificial intelligence","score_opus":0.022517078536396805,"score_gpt":0.275688057442973,"score_spread":0.2531709789065762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4353098262","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010196033,0.0001042523,0.98795277,0.00003213113,0.000046185458,0.000019324096,0.00003302228,0.00018747419,0.0014288437],"genre_scores_gemma":[0.5412312,0.00031805108,0.45316708,0.0000856127,0.00006413801,0.00019367144,0.00020046074,0.00020205801,0.004537608],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987876,0.00003062759,0.0000079059455,0.000024034096,0.000045768174,0.0000129581285],"domain_scores_gemma":[0.9996784,0.00016188617,0.000016691392,0.000043858687,0.00007986061,0.000019324021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002979755,0.0003162047,0.00071893464,0.00023072374,0.0003897177,0.00041696485,0.0008649485,0.0007072385,0.0031807339],"category_scores_gemma":[0.0007167342,0.00032174253,0.0005344658,0.00030045243,0.00033743033,0.0005822609,0.00047896197,0.0008483762,0.0005290527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001112266,0.00006990225,0.00064281834,0.00013210413,0.000045613713,0.000082892075,0.00007250358,0.84708804,0.015167438,0.008679616,0.0010660208,0.12684184],"study_design_scores_gemma":[0.0000031878064,0.0000070037936,0.000042776785,0.0000021628668,0.0000017344798,0.0000035265043,0.0000019996135,0.99899346,0.0003140977,0.00041216984,0.0002161372,0.000001776042],"about_ca_topic_score_codex":0.004804563,"about_ca_topic_score_gemma":0.0035539255,"teacher_disagreement_score":0.004804563,"about_ca_system_score_codex":0.00020295271,"about_ca_system_score_gemma":0.00071311137,"threshold_uncertainty_score":0.010640621},"labels":[],"label_agreement":null},{"id":"W4361005478","doi":"10.3390/pr11040996","title":"The Influence of Tool Geometry Parameters on Thermo-Mechanical Loads and Residual Stresses Induced by Orthogonal Cutting of AA6061-T6: A Numerical Investigation","year":2023,"lang":"en","type":"article","venue":"Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Rake angle; Machining; Residual stress; Enhanced Data Rates for GSM Evolution; Materials science; RADIUS; Residual; Rake; Structural engineering; Cutting tool; Surface integrity; Mechanical engineering; Geometry; Composite material; Engineering; Computer science; Metallurgy; Mathematics","score_opus":0.012102506872267087,"score_gpt":0.23777804588361265,"score_spread":0.22567553901134557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361005478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99395883,0.000094457675,0.004556183,0.00001896155,0.000007575796,0.000014484131,0.00006117034,0.00004072788,0.0012476037],"genre_scores_gemma":[0.9968721,0.0000561698,0.0027705086,0.0000040288387,0.0000013019762,0.000008506047,0.000029692845,0.000005631309,0.0002521077],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998258,0.000019396852,0.0000117809195,0.000026832447,0.000080117505,0.000036148176],"domain_scores_gemma":[0.99941313,0.00033801497,0.000114372655,0.000043385844,0.00007248209,0.000018725585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036032562,0.00027925087,0.0003628361,0.00036796226,0.0002450812,0.00047053435,0.00042157448,0.00064526877,0.000779661],"category_scores_gemma":[0.0009556909,0.0002293877,0.00049065345,0.0004079741,0.00046494574,0.00026159553,0.0001951139,0.00025661956,0.00009712893],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038925244,0.00022991734,0.012635569,0.0003996368,0.000048303627,0.00072555675,0.00035314556,0.77237153,0.19219878,0.0010143243,0.00028452705,0.019349491],"study_design_scores_gemma":[0.000022866972,0.00037406216,0.008467014,0.000015142916,0.00003063741,0.00015350147,0.00014010364,0.96164566,0.028502855,0.00015949653,0.00046290128,0.000025765554],"about_ca_topic_score_codex":0.003056417,"about_ca_topic_score_gemma":0.0026850393,"teacher_disagreement_score":0.003056417,"about_ca_system_score_codex":0.00025401395,"about_ca_system_score_gemma":0.00026124535,"threshold_uncertainty_score":0.00607723},"labels":[],"label_agreement":null},{"id":"W4361276066","doi":"10.1016/j.wear.2023.204852","title":"Surface roughness and morphology evaluation of bearing steel after grinding with multilayer graphene platelets dispersed in different base fluids","year":2023,"lang":"en","type":"article","venue":"Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Universidade Federal de Minas Gerais; Fundação de Apoio à Pesquisa do Distrito Federal; Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Department of Mechanical Engineering, University of Alberta; Universidade Federal de Uberlândia; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Universidade de Brasília; Kansas State University","keywords":"Materials science; Grinding; Surface roughness; Lubrication; Lubricant; Scanning electron microscope; Context (archaeology); Tribology; Surface finish; Surface integrity; Base oil; Bearing (navigation); Machining; Composite material; Cutting fluid; Metallurgy; Surface grinding","score_opus":0.017995175927422957,"score_gpt":0.2521008226949743,"score_spread":0.23410564676755136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361276066","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99878556,0.0001313243,0.000576631,0.000015821477,0.0000139070535,0.0000038274356,0.0000941217,0.000022236702,0.000356475],"genre_scores_gemma":[0.9979286,0.000085904154,0.0009618521,0.000012303507,0.000004516936,0.0000048293377,0.00014634964,0.000008643176,0.00084694097],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998134,0.000012232917,0.0000132350115,0.000028621205,0.00009831886,0.000034209002],"domain_scores_gemma":[0.9997031,0.00005536395,0.000053661504,0.000029306375,0.00013288128,0.00002566037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001684093,0.00023590874,0.000204481,0.0003012223,0.00021168869,0.00020942034,0.00019241656,0.00042953657,0.0013785339],"category_scores_gemma":[0.00040246567,0.00018110215,0.00028291365,0.00024579518,0.0002274455,0.00024140834,0.00011389006,0.00034727083,0.00018772403],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011598608,0.000011439557,0.00055244257,0.000026599797,0.0000067088645,0.00006499147,0.00005004252,0.00018199171,0.9977538,0.000019912544,0.000045919845,0.0011703393],"study_design_scores_gemma":[0.0000122384,0.0004348216,0.03736941,0.0000052093073,0.000031371113,0.00013250197,0.00017784204,0.0034133415,0.95777893,0.00002724504,0.0005934692,0.000023632376],"about_ca_topic_score_codex":0.0019683582,"about_ca_topic_score_gemma":0.0035770906,"teacher_disagreement_score":0.0019683582,"about_ca_system_score_codex":0.00018656699,"about_ca_system_score_gemma":0.00009559934,"threshold_uncertainty_score":0.004611671},"labels":[],"label_agreement":null},{"id":"W4362453046","doi":"10.1016/j.compositesb.2023.110706","title":"Mediating compositional machining difference of UD-CFRP in orthogonal cutting by epoxy coating","year":2023,"lang":"en","type":"article","venue":"Composites Part B Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Science Challenge Project; Energy Council of Canada","keywords":"Epoxy; Machining; Materials science; Machinability; Coating; Composite material; Metallurgy","score_opus":0.006632628657173163,"score_gpt":0.2106487195492499,"score_spread":0.20401609089207676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362453046","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98239374,0.00021744736,0.010080602,0.000024680312,0.000032737164,0.000007793961,0.000016701571,0.00007314732,0.007153158],"genre_scores_gemma":[0.9977456,0.00004199641,0.0015844565,0.000007340902,0.0000020635903,0.0000019709273,0.000007744456,0.000012029248,0.00059674826],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999125,0.0000072906882,0.000002764867,0.000019113437,0.00003347875,0.000024814723],"domain_scores_gemma":[0.9998679,0.000037839967,0.000033260225,0.000020285182,0.0000251218,0.000015486998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010592284,0.00015687042,0.0001065679,0.00010578909,0.00013587624,0.00027924046,0.00021924045,0.00018588816,0.0015560248],"category_scores_gemma":[0.00027960865,0.00011237856,0.000080619095,0.00007956027,0.0002815086,0.00026427413,0.0001999042,0.00023215343,0.00018770952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010694226,0.000017149756,0.00027482767,0.00003741399,0.0000018305828,0.00005797987,0.00004891469,0.0008816218,0.99205655,0.0024631612,0.00005384666,0.0039998693],"study_design_scores_gemma":[0.000011564418,0.00017060967,0.0037527364,0.0000057697684,0.00001034098,0.00014112267,0.00009124347,0.021577938,0.97238016,0.00045470623,0.0013923694,0.000011495716],"about_ca_topic_score_codex":0.00024631267,"about_ca_topic_score_gemma":0.00045915885,"teacher_disagreement_score":0.0015560248,"about_ca_system_score_codex":0.00010599792,"about_ca_system_score_gemma":0.0001421247,"threshold_uncertainty_score":0.0052054524},"labels":[],"label_agreement":null},{"id":"W4362513452","doi":"10.1007/s44245-023-00011-w","title":"A review on the machining of polymer composites reinforced with carbon (CFRP), glass (GFRP), and natural fibers (NFRP)","year":2023,"lang":"en","type":"review","venue":"Discover Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Machinability; Fibre-reinforced plastic; Materials science; Composite material; Composite number; Delamination (geology); Aerospace; Carbon fiber reinforced polymer; Glass fiber; Automotive industry; Engineering; Metallurgy","score_opus":0.013451925549287156,"score_gpt":0.25064531725216993,"score_spread":0.23719339170288278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362513452","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00039735125,0.99762875,0.00033600727,0.000067672576,0.00013871625,0.0000083359555,0.000032864682,0.000010743749,0.0013796808],"genre_scores_gemma":[0.000977506,0.9975727,0.0005099477,0.0000632748,0.00007239653,0.00000755719,0.000049527367,0.000002367973,0.00074465154],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99974114,0.00002914897,0.00004791698,0.000057157245,0.00010586432,0.000018822397],"domain_scores_gemma":[0.99965525,0.00015292119,0.0000715184,0.0000116038955,0.00009080842,0.000017965045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043461952,0.0010860452,0.0012344457,0.0030574563,0.00028109289,0.000730572,0.0008024918,0.00078683294,0.0033822851],"category_scores_gemma":[0.00050566933,0.0004959012,0.00069113204,0.0037292428,0.0002709298,0.0012244397,0.00041071678,0.000780234,0.001511497],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007566157,0.00015464825,0.00023733238,0.075859904,0.00017510394,0.00022480403,0.00010901459,0.0011124691,0.008043635,0.0032153374,0.018425984,0.8923662],"study_design_scores_gemma":[0.000008450978,0.00021294167,0.0013585916,0.006447392,0.00021843032,0.00083398697,0.000070512084,0.00020149974,0.0027904832,0.00068744936,0.9871395,0.00003079261],"about_ca_topic_score_codex":0.0011751876,"about_ca_topic_score_gemma":0.0020858431,"teacher_disagreement_score":0.0033822851,"about_ca_system_score_codex":0.0003048934,"about_ca_system_score_gemma":0.0009920856,"threshold_uncertainty_score":0.0113149285},"labels":[],"label_agreement":null},{"id":"W4365144710","doi":"10.1016/j.cirp.2023.04.017","title":"Hybrid offline-online optimization, monitoring and control of milling processes","year":2023,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Machining; Tool wear; Deflection (physics); Online and offline; Engineering; Process (computing); Cutting tool; Control engineering; Mechanical engineering; Computer science","score_opus":0.02314074587356673,"score_gpt":0.27504125853171396,"score_spread":0.2519005126581472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365144710","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18951619,0.0004075029,0.8044031,0.0001533662,0.00006198198,0.000047151603,0.00008070293,0.0012302318,0.00409968],"genre_scores_gemma":[0.9717837,0.0000519378,0.026934944,0.000020343772,0.00001930409,0.0000372612,0.000035194324,0.000041019,0.00107619],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994747,0.00012815846,0.000026940284,0.00014320717,0.00016528394,0.000061717525],"domain_scores_gemma":[0.99922156,0.0004205792,0.00012852765,0.00007901748,0.00011557107,0.000034751996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006352103,0.0007944578,0.0010717624,0.00039574038,0.0003320552,0.0012264672,0.0007885435,0.000626467,0.0011021002],"category_scores_gemma":[0.0010199414,0.0004343706,0.0003940952,0.0003108146,0.000470235,0.0006829014,0.0006700985,0.00055053685,0.0001979319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012105844,0.0004247594,0.0018718445,0.00027884656,0.00008995858,0.000079085294,0.000094956944,0.72642356,0.054582015,0.0019618315,0.00090019644,0.2120824],"study_design_scores_gemma":[0.000011018968,0.0000762027,0.0005480648,0.000001988411,0.0000072593493,0.000008220839,0.0000034235484,0.99375135,0.005079787,0.00037507818,0.00013167586,0.00000593472],"about_ca_topic_score_codex":0.0022527261,"about_ca_topic_score_gemma":0.0025654167,"teacher_disagreement_score":0.0022527261,"about_ca_system_score_codex":0.00037927713,"about_ca_system_score_gemma":0.0005816521,"threshold_uncertainty_score":0.00447917},"labels":[],"label_agreement":null},{"id":"W4365149431","doi":"10.3390/s23083894","title":"A Real-Time Deep Machine Learning Approach for Sudden Tool Failure Prediction and Prevention in Machining Processes","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Autoencoder; Machining; Process (computing); Computer science; Wavelet; Artificial intelligence; Representation (politics); Artificial neural network; Machine learning; Pattern recognition (psychology); Engineering; Mechanical engineering","score_opus":0.008271034634781797,"score_gpt":0.2269999828167959,"score_spread":0.2187289481820141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365149431","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06484562,0.0004096396,0.932649,0.00014103933,0.000049062568,0.000038832713,0.00006319115,0.00087457435,0.000929081],"genre_scores_gemma":[0.88142,0.00025514752,0.115697876,0.00009757759,0.000034832134,0.0000997329,0.000171134,0.00003126614,0.0021924046],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981517,0.00002386329,0.0000132191535,0.000054517655,0.000057805835,0.000035441903],"domain_scores_gemma":[0.9997578,0.00009043797,0.000036430287,0.000020111043,0.00008040582,0.000014682339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004687859,0.00067459734,0.00042522902,0.00037394746,0.00019283034,0.00034061942,0.00074940856,0.0006702972,0.00075409986],"category_scores_gemma":[0.0008622084,0.0003067986,0.00039809028,0.00028756878,0.0002457994,0.00048699384,0.00046631438,0.00094906514,0.00019229607],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015907655,0.00018345131,0.0015638783,0.00008570666,0.000052435218,0.00011354937,0.000053971475,0.6591381,0.02571351,0.0015661187,0.0009977256,0.31037247],"study_design_scores_gemma":[0.0000013194627,0.000021023321,0.0001712773,0.0000019976314,0.0000027728074,0.0000053202193,0.0000018136523,0.9981481,0.0013567362,0.00019264295,0.000094958246,0.000002160202],"about_ca_topic_score_codex":0.0038904075,"about_ca_topic_score_gemma":0.004668569,"teacher_disagreement_score":0.0038904075,"about_ca_system_score_codex":0.00042808233,"about_ca_system_score_gemma":0.00068096304,"threshold_uncertainty_score":0.007735491},"labels":[],"label_agreement":null},{"id":"W4366087584","doi":"10.21203/rs.3.rs-2798984/v1","title":"A novel in-situ tool wear monitoring approach using multivariate signal processing and intrinsic multiscale entropy analysis","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Wuhan University of Science and Technology; Wuhan University; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Multivariate statistics; In situ; Signal processing; Entropy (arrow of time); Computer science; Biological system; Pattern recognition (psychology); Artificial intelligence; Materials science; Machine learning; Physics; Digital signal processing; Thermodynamics; Biology; Computer hardware; Meteorology","score_opus":0.07949163782490219,"score_gpt":0.37207175135216664,"score_spread":0.29258011352726443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366087584","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.096297145,0.0001626752,0.9022572,0.00005087597,0.000019951873,0.000028318927,0.00008464773,0.00031228905,0.0007869052],"genre_scores_gemma":[0.83928204,0.00015271863,0.15940052,0.00002795122,0.00004034141,0.000034267,0.00011717599,0.000034076165,0.00091093016],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983954,0.000026233041,0.000009383108,0.000044478937,0.00006412387,0.000016232361],"domain_scores_gemma":[0.99980325,0.00004648722,0.00004275238,0.000028812236,0.000063394145,0.00001531583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025471215,0.0005897881,0.00037970007,0.0009276465,0.00012250777,0.00038382548,0.0004399983,0.00031377884,0.00070190243],"category_scores_gemma":[0.00054477743,0.00017282614,0.00043612294,0.00047903115,0.00020803737,0.00063360983,0.0004545121,0.0002870445,0.000113950795],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026962592,0.00017640021,0.00919958,0.00027336672,0.00015538785,0.0002755825,0.00021561765,0.12876147,0.3890017,0.0032649047,0.0009214239,0.467485],"study_design_scores_gemma":[0.0000051226584,0.000067759465,0.0053924015,0.0000059210784,0.000022378821,0.00007922535,0.000027158083,0.9681396,0.024500033,0.0012110085,0.00053432654,0.000015031653],"about_ca_topic_score_codex":0.0007602275,"about_ca_topic_score_gemma":0.0011865988,"teacher_disagreement_score":0.0009276465,"about_ca_system_score_codex":0.00016432516,"about_ca_system_score_gemma":0.00014269448,"threshold_uncertainty_score":0.002348125},"labels":[],"label_agreement":null},{"id":"W4367021425","doi":"10.2139/ssrn.4428555","title":"The Impact of the Cutting Parameters and Tool Condition on Surface Integrity When Milling Inconel 625","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Surface integrity; Inconel; Materials science; Machining; Corrosion; Metallurgy; Residual stress; Superalloy; Work hardening; Thermal conductivity; Inconel 625; Composite material; Alloy; Microstructure","score_opus":0.01481088927825592,"score_gpt":0.2743759312342097,"score_spread":0.2595650419559538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367021425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99631053,0.0002992252,0.001805857,0.000027152126,0.000012082259,0.0000056596828,0.00007089621,0.00003895911,0.0014295264],"genre_scores_gemma":[0.9990938,0.000044749606,0.00042747718,0.000004928406,0.0000021872524,0.0000012359002,0.00004450081,0.000022579246,0.00035856094],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99908674,0.000108800996,0.00004797639,0.0001654025,0.00040775695,0.00018324493],"domain_scores_gemma":[0.9967488,0.0017153631,0.0003998147,0.00031638352,0.00071477244,0.00010477353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007680375,0.00026687147,0.00045578313,0.00042616663,0.0005528134,0.0013844083,0.0004742947,0.0008980994,0.0032830953],"category_scores_gemma":[0.0040652235,0.00031911262,0.00027466123,0.0004938059,0.0005677706,0.00084191037,0.00043176668,0.00051732076,0.00056313246],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0062208422,0.00028503072,0.026224265,0.00029120262,0.000102009246,0.0006837486,0.00033626682,0.041400004,0.8692691,0.00034382398,0.0005219729,0.054321926],"study_design_scores_gemma":[0.000046502497,0.0030975956,0.119565375,0.0000290559,0.00016389794,0.00041615442,0.0005544988,0.05180319,0.82293785,0.00027860233,0.0010352215,0.0000720743],"about_ca_topic_score_codex":0.0013682591,"about_ca_topic_score_gemma":0.0022629565,"teacher_disagreement_score":0.0032830953,"about_ca_system_score_codex":0.00039710294,"about_ca_system_score_gemma":0.00026715023,"threshold_uncertainty_score":0.01098299},"labels":[],"label_agreement":null},{"id":"W4367680779","doi":"10.1016/j.cirp.2023.04.054","title":"A hybrid physics and data-driven model for spindle fault detection","year":2023,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Pratt and Whitney Canada","keywords":"Vibration; Machining; Machine tool; Engineering; Fault detection and isolation; Fault (geology); Control engineering; Real-time computing; Simulation; Computer science; Mechanical engineering; Acoustics; Actuator; Physics; Electrical engineering","score_opus":0.08148289981025864,"score_gpt":0.3294886752468546,"score_spread":0.24800577543659597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367680779","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033175196,0.00019846196,0.9600273,0.00029950892,0.0000733238,0.000067208166,0.0003404257,0.0012126352,0.0046059117],"genre_scores_gemma":[0.9277875,0.00020203086,0.0648707,0.00014198563,0.000048985978,0.00019781642,0.0003577647,0.00020343509,0.0061899163],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997999,0.00003443839,0.000010896046,0.0000457096,0.00008241039,0.000026778684],"domain_scores_gemma":[0.99931073,0.0003882871,0.0000612179,0.000056187797,0.0001483029,0.000035263576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004659662,0.00059532735,0.0009677403,0.0005361241,0.0003851299,0.0011128427,0.0017211884,0.0014013795,0.0034762712],"category_scores_gemma":[0.001645914,0.0005712038,0.0008795497,0.00041597072,0.0005536983,0.0010546242,0.000795488,0.0009525783,0.0005639599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027926464,0.000018597555,0.00015654761,0.00001877485,0.000010856024,0.000021429654,0.000008060352,0.99366635,0.0006700485,0.0017817679,0.00015424189,0.0034653344],"study_design_scores_gemma":[0.00000254514,0.000003560021,0.000021789852,7.176809e-7,0.0000016747737,0.0000022173015,4.7153145e-7,0.99939835,0.00009497143,0.00041515063,0.000057272457,0.0000013221364],"about_ca_topic_score_codex":0.010020834,"about_ca_topic_score_gemma":0.0073311473,"teacher_disagreement_score":0.010020834,"about_ca_system_score_codex":0.0007216065,"about_ca_system_score_gemma":0.0012301456,"threshold_uncertainty_score":0.019924998},"labels":[],"label_agreement":null},{"id":"W4367840964","doi":"10.1016/j.jmapro.2023.04.053","title":"A comprehensive investigation of surface morphology during grinding of Inconel 625 using conventional grinding wheels","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Department of Mechanical Engineering, University of Alberta; National Institute of Technology Hamirpur","keywords":"Materials science; Grinding; Grinding wheel; Silicon carbide; Inconel 625; Grind; Surface roughness; Inconel; Surface grinding; Scanning electron microscope; Surface finish; Metallurgy; Composite material; Corrosion; Alloy","score_opus":0.029140466621240976,"score_gpt":0.26186176895218183,"score_spread":0.23272130233094085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367840964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99809295,0.00023314693,0.0010309027,0.0000070479514,0.000004806212,0.000008396688,0.00007019808,0.00002032139,0.0005323052],"genre_scores_gemma":[0.99636996,0.0002000971,0.0022980508,0.000010837881,0.0000018232676,0.0000073508168,0.0001346079,0.000018403254,0.0009588842],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997584,0.0000149734005,0.000010065723,0.00003715599,0.00013910522,0.00004034903],"domain_scores_gemma":[0.99979,0.00004658038,0.00003632828,0.000026339281,0.0000888449,0.000011918351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025265265,0.00018059382,0.00028117356,0.00024972728,0.0003030014,0.00025381785,0.00022449793,0.00029549416,0.00081034173],"category_scores_gemma":[0.0004108546,0.00019257827,0.00026645375,0.00030585908,0.00023796064,0.0002799837,0.0001587491,0.00021635421,0.0001538614],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005726427,0.000015107707,0.0015355671,0.000044187484,0.0000040353566,0.00007296047,0.000101463425,0.00026533785,0.9938432,0.000036106238,0.000043867283,0.003980966],"study_design_scores_gemma":[0.000007646148,0.000632671,0.10508787,0.000011657516,0.000028183265,0.00019845871,0.0003439146,0.0040346878,0.8873568,0.000044042987,0.0022282014,0.000025951485],"about_ca_topic_score_codex":0.0027371463,"about_ca_topic_score_gemma":0.0059401146,"teacher_disagreement_score":0.0027371463,"about_ca_system_score_codex":0.0002472883,"about_ca_system_score_gemma":0.00023674675,"threshold_uncertainty_score":0.0054424405},"labels":[],"label_agreement":null},{"id":"W4378193189","doi":"10.1016/j.cirp.2023.04.012","title":"Wide-bandwidth cutting force monitoring via motor current and accelerometer signals","year":2023,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Accelerometer; Dynamometer; Machining; Kalman filter; Smoothing; Acceleration; Engineering; Bandwidth (computing); Control theory (sociology); Automotive engineering; Control engineering; Computer science; Mechanical engineering; Artificial intelligence","score_opus":0.041943154117247805,"score_gpt":0.3029979524753902,"score_spread":0.2610547983581424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378193189","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5448747,0.0018719013,0.43035108,0.00040157326,0.00022354882,0.00015417612,0.00081192394,0.003360947,0.01795014],"genre_scores_gemma":[0.9712676,0.0002142609,0.025746772,0.000089919944,0.000037522586,0.00003960141,0.00013931032,0.00004224974,0.0024228357],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996338,0.000043178858,0.000013279815,0.0000852329,0.00019176415,0.000032777298],"domain_scores_gemma":[0.99960333,0.00011913893,0.00006562388,0.00004263936,0.00014712846,0.000022041242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020886796,0.0005496099,0.00033791098,0.0007092648,0.00017112584,0.00038022565,0.00033497758,0.00059808104,0.0014632326],"category_scores_gemma":[0.000786458,0.00017268003,0.00008772933,0.00045117,0.00014161618,0.00050354504,0.00029535842,0.00025245256,0.0004963079],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010808714,0.00013582704,0.009693906,0.00026859512,0.000038091366,0.00017467036,0.00016308029,0.0041368394,0.691706,0.00064192404,0.002152462,0.28980762],"study_design_scores_gemma":[0.000104263,0.0013101035,0.11592415,0.00017013821,0.00012637838,0.0019738355,0.0003608718,0.25254592,0.60751855,0.0019216839,0.017901959,0.0001421512],"about_ca_topic_score_codex":0.0004849621,"about_ca_topic_score_gemma":0.0014454095,"teacher_disagreement_score":0.0014632326,"about_ca_system_score_codex":0.00014832546,"about_ca_system_score_gemma":0.00015763499,"threshold_uncertainty_score":0.0048950315},"labels":[],"label_agreement":null},{"id":"W4378965583","doi":"10.18280/jesa.560212","title":"An Overview of the Study of ANN-GA, ANN-PSO, ANFIS-GA, ANFIS-PSO and ANFIS-FCM Predictions Analysis on Tool Wear During Machining Process","year":2023,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Adaptive neuro fuzzy inference system; Machining; Artificial neural network; Particle swarm optimization; Computer science; Artificial intelligence; Machine learning; Engineering; Mechanical engineering; Fuzzy logic","score_opus":0.022147288388402502,"score_gpt":0.2936507499565967,"score_spread":0.27150346156819416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378965583","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0465897,0.23900622,0.6636307,0.001374954,0.00081479136,0.00025358223,0.00039299414,0.0007753631,0.047161624],"genre_scores_gemma":[0.5533209,0.2229974,0.20531096,0.00036816407,0.00083920796,0.00034278756,0.0006251213,0.00011246546,0.016083013],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995834,0.00009384459,0.00006198615,0.00009287509,0.00013988432,0.000028009405],"domain_scores_gemma":[0.99924064,0.00047355905,0.000056999652,0.00003270282,0.00017942608,0.000016618245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095764734,0.0010235163,0.0006315633,0.001173753,0.00028793392,0.00097205717,0.0007026601,0.00088255503,0.0013567983],"category_scores_gemma":[0.0017840543,0.00032735482,0.0008528157,0.0014019455,0.0002761379,0.00066812075,0.0002870166,0.0006762742,0.00031510115],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013168456,0.00014978817,0.004361821,0.004109264,0.00036744316,0.00030645417,0.00022762231,0.26808715,0.00612823,0.015610717,0.0040854765,0.6964344],"study_design_scores_gemma":[0.000014693037,0.000531012,0.009781883,0.0012094141,0.0003698937,0.00047828356,0.00024692796,0.9076484,0.009193111,0.010130773,0.060273662,0.00012200958],"about_ca_topic_score_codex":0.0047051758,"about_ca_topic_score_gemma":0.003057475,"teacher_disagreement_score":0.0047051758,"about_ca_system_score_codex":0.0005188835,"about_ca_system_score_gemma":0.00059615914,"threshold_uncertainty_score":0.009355605},"labels":[],"label_agreement":null},{"id":"W4379046899","doi":"10.1016/j.cirpj.2023.05.004","title":"Identification and effect of chip shear band on chatter vibration in the turning of Nickel Alloy 718","year":2023,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adiabatic shear band; Chip formation; Machining; Vibration; Materials science; Chip; Shear (geology); Alloy; Natural frequency; Structural engineering; Metallurgy; Acoustics; Tool wear; Engineering; Composite material; Physics; Electrical engineering","score_opus":0.0054188500923071335,"score_gpt":0.23435742228069803,"score_spread":0.2289385721883909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379046899","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97737646,0.00019311233,0.021160748,0.000026714171,0.00003497658,0.00000822559,0.000023674915,0.00010662591,0.0010695773],"genre_scores_gemma":[0.99849236,0.000029302164,0.0011836735,0.000004675745,0.0000042011834,0.0000020666894,0.000017151351,0.0000061025744,0.00026058467],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99986184,0.000024164321,0.000004813545,0.000029270524,0.00004885164,0.00003107042],"domain_scores_gemma":[0.9993629,0.00036871608,0.000053457654,0.000034393874,0.00014163471,0.000038832568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025535945,0.00027712007,0.00041709704,0.00041972872,0.00022475363,0.00027417272,0.00024759662,0.00038054984,0.00073634816],"category_scores_gemma":[0.00078766403,0.00014111717,0.0002531769,0.00017295688,0.00022975454,0.00018784507,0.0001452958,0.0002312157,0.00010761031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055670445,0.00025841847,0.030612295,0.00044575147,0.00014826102,0.001385155,0.0007614067,0.030254208,0.7868245,0.00043519775,0.0006434603,0.14266422],"study_design_scores_gemma":[0.0000483418,0.0011824828,0.2243681,0.000045021454,0.00019920382,0.0008090291,0.0005441488,0.5605631,0.21119101,0.00020977446,0.00076884666,0.000071030474],"about_ca_topic_score_codex":0.0022695907,"about_ca_topic_score_gemma":0.003693944,"teacher_disagreement_score":0.0022695907,"about_ca_system_score_codex":0.00013228231,"about_ca_system_score_gemma":0.00013809795,"threshold_uncertainty_score":0.0045127273},"labels":[],"label_agreement":null},{"id":"W4379389214","doi":"10.37965/jdmd.2023.231","title":"Wavelet Denoising Applied to Hardware Redundant Systems for Rolling Element Bearing Fault Detection","year":2023,"lang":"en","type":"article","venue":"Journal of Dynamics Monitoring and Diagnostics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Noise reduction; Fault detection and isolation; Residual; Vibration; Computer science; Wavelet; Fault (geology); Noise (video); Redundancy (engineering); Reduction (mathematics); SIGNAL (programming language); Wavelet transform; Signature (topology); Bearing (navigation); Computer hardware; Artificial intelligence; Algorithm; Mathematics; Acoustics","score_opus":0.010496003915423805,"score_gpt":0.24911225504086612,"score_spread":0.23861625112544232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379389214","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07048107,0.00034175417,0.9280046,0.00006578077,0.00004034134,0.00002116197,0.000019113815,0.00018779666,0.0008382942],"genre_scores_gemma":[0.66459733,0.00063078053,0.33304465,0.000046763686,0.00004340197,0.000035791214,0.00008190885,0.00006336069,0.0014559609],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996511,0.00007402579,0.000018605602,0.00005134996,0.00018256763,0.000022369284],"domain_scores_gemma":[0.9996189,0.00015957067,0.0000553386,0.000050077953,0.00010530565,0.000010781909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057856576,0.0004822853,0.0004282364,0.00045888816,0.00014414862,0.00029501,0.00033177802,0.00045352735,0.00045072273],"category_scores_gemma":[0.0015662214,0.00019487184,0.0003363648,0.0003611837,0.00029115457,0.00047644478,0.00030719928,0.0004283634,0.00019440918],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041921306,0.00010027529,0.0023533301,0.0003444343,0.00008855992,0.00024463772,0.0002502801,0.08556054,0.4421977,0.0042736456,0.0006769419,0.4634904],"study_design_scores_gemma":[0.000014519124,0.00025484446,0.0030180523,0.000022306236,0.000046407484,0.00024527582,0.00004658743,0.8656941,0.12664494,0.0013390534,0.0026522363,0.00002165327],"about_ca_topic_score_codex":0.00068340136,"about_ca_topic_score_gemma":0.000865475,"teacher_disagreement_score":0.00068340136,"about_ca_system_score_codex":0.0001734988,"about_ca_system_score_gemma":0.00024825754,"threshold_uncertainty_score":0.0030598044},"labels":[],"label_agreement":null},{"id":"W4380489216","doi":"10.1016/j.cirpj.2023.06.004","title":"Corrigendum to “Analysis of machining green compacts of a sinter-hardenable powder metallurgy steel: A perspective of material removal mechanism” [CIRP Journal of Manufacturing Science and Technology 41 (2023) 430–445]","year":2023,"lang":"en","type":"erratum","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Machining; Metallurgy; Powder metallurgy; Materials science; Mechanism (biology); Perspective (graphical); Manufacturing engineering; Engineering; Computer science; Microstructure","score_opus":0.01170767705845014,"score_gpt":0.2501838249735942,"score_spread":0.23847614791514407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380489216","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00077970704,0.0029403311,0.0029712042,0.034948252,0.93474245,0.00009293468,0.0016297493,0.0005913441,0.021303995],"genre_scores_gemma":[0.011661527,0.0068602255,0.0063026855,0.051550806,0.106730774,0.00019954334,0.0040120115,0.0012282259,0.8114542],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965011,0.00028382876,0.0003232773,0.0004165139,0.0021812867,0.0002940855],"domain_scores_gemma":[0.9897427,0.0012569545,0.00024504864,0.00050336664,0.008008795,0.00024308116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017414801,0.0022050366,0.002423354,0.003493775,0.0038306199,0.0027974702,0.0036720068,0.004977858,0.07731359],"category_scores_gemma":[0.013091803,0.00093491224,0.0026578421,0.0025445397,0.0012647177,0.001644376,0.0015281127,0.0039586606,0.03391983],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049485858,0.00001549814,0.000067879664,0.00012873512,0.000011941934,0.00016479248,0.000017141483,0.00025734512,0.00035331465,0.00090550515,0.9893951,0.008633278],"study_design_scores_gemma":[0.000031276366,0.0000925555,0.0027164156,0.00013995508,0.000090685186,0.00026776994,0.00008634825,0.0018086655,0.0018587406,0.0022495545,0.9905847,0.00007331308],"about_ca_topic_score_codex":0.07466562,"about_ca_topic_score_gemma":0.12519974,"teacher_disagreement_score":0.07731359,"about_ca_system_score_codex":0.0045802277,"about_ca_system_score_gemma":0.0038995913,"threshold_uncertainty_score":0.2586397},"labels":[],"label_agreement":null},{"id":"W4380738222","doi":"10.1115/1.4062749","title":"Time-Varying Tool-Chip Contact in the Cutting Mechanics of Shear Localization","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Chip; Chip formation; Shear (geology); Shear band; Mechanics; Rake; Machining; Shear stress; Adiabatic shear band; Shear zone; Mechanical engineering; Composite material; Tool wear; Engineering; Geology; Metallurgy; Physics; Electrical engineering","score_opus":0.008293576168917658,"score_gpt":0.21943582705057504,"score_spread":0.2111422508816574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380738222","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69737643,0.00078360696,0.29471877,0.00013711196,0.000060001777,0.00004797959,0.000058148176,0.00019887973,0.0066189487],"genre_scores_gemma":[0.99772507,0.000080046826,0.0013129964,0.0000056951076,0.0000041342437,0.0000099439385,0.000007090109,0.0000062772665,0.0008487959],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999012,0.000015862277,0.000003328648,0.000026733369,0.00003482661,0.00001802198],"domain_scores_gemma":[0.999881,0.0000474214,0.000026354017,0.000016206877,0.00002144715,0.000007486758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017119863,0.00033671694,0.00028062056,0.00024660712,0.00019939804,0.00040848483,0.00045470955,0.0005862397,0.00086622156],"category_scores_gemma":[0.0003930795,0.00022041146,0.0003659403,0.0001587659,0.0005364175,0.00047883258,0.00027076944,0.0002669613,0.0001636734],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009805146,0.000108636,0.0040348144,0.00011131877,0.000032476994,0.00063465885,0.00022885128,0.78321356,0.18723299,0.008970296,0.00030736302,0.015027042],"study_design_scores_gemma":[0.0000017248868,0.000021974214,0.0010032305,0.0000020008388,0.000003453442,0.000024581805,0.000008679328,0.9955776,0.0028224103,0.0003891245,0.0001404581,0.000004705679],"about_ca_topic_score_codex":0.0017878857,"about_ca_topic_score_gemma":0.001155111,"teacher_disagreement_score":0.0017878857,"about_ca_system_score_codex":0.00036381788,"about_ca_system_score_gemma":0.00025960413,"threshold_uncertainty_score":0.0035549998},"labels":[],"label_agreement":null},{"id":"W4381280166","doi":"10.1007/s12541-023-00831-6","title":"Prediction of Tool Tip Dynamics Through Machine Learning and Inverse Receptance Coupling","year":2023,"lang":"en","type":"article","venue":"International Journal of Precision Engineering and Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Korea Institute of Industrial Technology","keywords":"Machining; Machine tool; Artificial neural network; Deflection (physics); Frequency response; Computer science; Cutting tool; Engineering; Finite element method; Coupling (piping); Control engineering; Mechanical engineering; Machine learning; Structural engineering","score_opus":0.009703288526791483,"score_gpt":0.2312024980868044,"score_spread":0.22149920956001293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381280166","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3012901,0.00026332235,0.6947668,0.00011874551,0.000063428975,0.00004107905,0.000097312,0.0012288854,0.0021303575],"genre_scores_gemma":[0.97212,0.000063821666,0.026768453,0.000014620403,0.0000094924435,0.000018830437,0.00007003786,0.00003126154,0.00090352487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998641,0.000024966695,0.0000071539794,0.000040458297,0.0000447212,0.00001865292],"domain_scores_gemma":[0.99935466,0.0003557066,0.00007817183,0.000058743582,0.00012615242,0.00002655957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031462777,0.000573504,0.00049992587,0.0005548643,0.000260344,0.00051902427,0.0004380642,0.0007625558,0.00089251396],"category_scores_gemma":[0.0016599116,0.00037793972,0.00040443504,0.00034951253,0.00027745633,0.00073265244,0.00036688513,0.00075527385,0.00040543618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014255544,0.000110849825,0.00454392,0.0000668745,0.000037341866,0.00011862785,0.000058377165,0.8819089,0.021839159,0.0007569546,0.0004595093,0.0899569],"study_design_scores_gemma":[0.0000014893731,0.000007686362,0.0003482087,9.845057e-7,0.0000011956714,0.0000058625747,0.0000016254153,0.9988249,0.0006778419,0.00009974349,0.000028924987,0.0000016674652],"about_ca_topic_score_codex":0.0031628308,"about_ca_topic_score_gemma":0.0031928807,"teacher_disagreement_score":0.0031628308,"about_ca_system_score_codex":0.0002281501,"about_ca_system_score_gemma":0.00047115167,"threshold_uncertainty_score":0.0062888265},"labels":[],"label_agreement":null},{"id":"W4381326091","doi":"10.1016/j.jmapro.2023.06.026","title":"Improved direct laser assisted machining of Al 7075-T6 and Ti-6Al-4V using cubic zirconia tool","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Science Basic Research Program of Shaanxi Province; Fundamental Research Funds for the Central Universities","keywords":"Materials science; Machinability; Machining; Cubic zirconia; Superalloy; Surface roughness; Laser; Surface finish; Cutting tool; Metallurgy; Composite material; Mechanical engineering; Ceramic; Alloy; Optics","score_opus":0.015020743490907318,"score_gpt":0.2531986188755427,"score_spread":0.23817787538463536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381326091","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9684133,0.00081712,0.023833686,0.0000634815,0.00007670179,0.00004902851,0.00015904884,0.00045775867,0.0061299847],"genre_scores_gemma":[0.9576571,0.00015879137,0.03679925,0.000016469001,0.000009018047,0.000014865411,0.00012358469,0.000041867905,0.0051790047],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996654,0.000009316904,0.000017153889,0.000044971464,0.0002102383,0.000052964177],"domain_scores_gemma":[0.9998534,0.000024379386,0.0000363615,0.000026849388,0.00004771959,0.000011348111],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020015558,0.0002430219,0.00044423254,0.0003985205,0.00027559607,0.000510469,0.00085462525,0.00041567624,0.0015264301],"category_scores_gemma":[0.00024596558,0.00032135381,0.0004401042,0.0003946441,0.000227323,0.0002856078,0.00030234494,0.00037494538,0.00033928448],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000155454,0.0000292543,0.00040598592,0.00016286685,0.000010627639,0.000101771075,0.000079912876,0.0021997788,0.9816442,0.00058572803,0.00022802714,0.014396424],"study_design_scores_gemma":[0.000055962195,0.0006051854,0.007820423,0.000010377804,0.000031865136,0.0004788118,0.000097117365,0.016961977,0.96735895,0.00019391054,0.0063489904,0.000036397865],"about_ca_topic_score_codex":0.0019034096,"about_ca_topic_score_gemma":0.0065300246,"teacher_disagreement_score":0.0019034096,"about_ca_system_score_codex":0.00038772996,"about_ca_system_score_gemma":0.0008509009,"threshold_uncertainty_score":0.0051063895},"labels":[],"label_agreement":null},{"id":"W4381857294","doi":"10.1007/s10845-023-02164-7","title":"Tool wear prediction in milling CFRP with different fiber orientations based on multi-channel 1DCNN-LSTM","year":2023,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Delamination (geology); Materials science; Fiber; Feature (linguistics); Machining; Tool wear; Abrasive; Representation (politics); Anisotropy; Pyramid (geometry); SIGNAL (programming language); Artificial intelligence; Computer science; Layer (electronics); Pattern recognition (psychology); Composite material; Geometry; Mathematics; Geology","score_opus":0.016493642995784374,"score_gpt":0.24130360822086158,"score_spread":0.2248099652250772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381857294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8997811,0.00042378585,0.09771328,0.000051891006,0.0000679579,0.000018314046,0.00016379144,0.0006223789,0.0011574994],"genre_scores_gemma":[0.9891121,0.00008430578,0.010062583,0.000012280071,0.00000452429,0.0000071252803,0.00009264142,0.000014959155,0.00060960377],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983644,0.000010455489,0.00000907656,0.00004866664,0.00006521477,0.000030201783],"domain_scores_gemma":[0.9996475,0.00011346657,0.000047639885,0.000037678095,0.00013621834,0.00001742755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002769043,0.00043075063,0.0003734608,0.00040923007,0.00018067252,0.00035826737,0.00043377333,0.0005912179,0.00059575104],"category_scores_gemma":[0.000548034,0.00020009262,0.00035089793,0.0003808235,0.00022321365,0.00050032703,0.00018370696,0.00030584744,0.00014979539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014164865,0.00034783472,0.023292763,0.0004075168,0.00010761379,0.00036943256,0.00030052822,0.38482168,0.19458866,0.00035196444,0.0017723177,0.39222318],"study_design_scores_gemma":[0.0000055356486,0.000090363705,0.011226899,0.000006563973,0.000014937188,0.00004589895,0.000040834857,0.97109264,0.017237147,0.00007809015,0.00014669703,0.000014438736],"about_ca_topic_score_codex":0.007261939,"about_ca_topic_score_gemma":0.013120562,"teacher_disagreement_score":0.007261939,"about_ca_system_score_codex":0.00027139412,"about_ca_system_score_gemma":0.00031371092,"threshold_uncertainty_score":0.014439344},"labels":[],"label_agreement":null},{"id":"W4382680910","doi":"10.11159/iccste23.206","title":"Development of Digital Twin Concept for Real-Time Detection of Abnormal Changes in Structural Behaviour","year":2023,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Civil, Structural and Transportation Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Truss; Artificial neural network; Computer science; Finite element method; Stiffness; Damages; Artificial intelligence; Reduction (mathematics); Identification (biology); Stage (stratigraphy); Data mining; Structural engineering; Machine learning; Engineering; Mathematics","score_opus":0.012423729703486186,"score_gpt":0.2309891492939248,"score_spread":0.21856541959043863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382680910","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008496449,0.00011268597,0.9899907,0.000031108622,0.000038120463,0.000024648523,0.000026762355,0.00028753508,0.0009919803],"genre_scores_gemma":[0.3958075,0.00040434243,0.5998408,0.00007280777,0.000038429658,0.000117537,0.00017354137,0.000069494665,0.0034755901],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957734,0.00006668914,0.000021272079,0.00009119342,0.0002227377,0.000020778263],"domain_scores_gemma":[0.99953854,0.00011667969,0.00007177755,0.00007259594,0.00016975016,0.000030725456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005593867,0.0005535624,0.00045947934,0.00078497175,0.00015771437,0.0005639709,0.000925105,0.00051660306,0.0015361183],"category_scores_gemma":[0.001278556,0.00028294305,0.0003856099,0.0005211771,0.000524142,0.0017546178,0.0008362366,0.0006561427,0.00034444724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003660823,0.00013172654,0.0031664432,0.00043696078,0.00007027332,0.0002702554,0.00021083574,0.23788372,0.16642587,0.04856109,0.002281217,0.5401956],"study_design_scores_gemma":[0.0000062522236,0.0002089124,0.00073097396,0.000014795026,0.000013313015,0.00026667275,0.000024696114,0.97040987,0.020890508,0.003904956,0.0035072116,0.000021888705],"about_ca_topic_score_codex":0.0011179125,"about_ca_topic_score_gemma":0.00089574326,"teacher_disagreement_score":0.0015361183,"about_ca_system_score_codex":0.0003788083,"about_ca_system_score_gemma":0.00043309876,"threshold_uncertainty_score":0.005138874},"labels":[],"label_agreement":null},{"id":"W4383343708","doi":"10.1007/s00170-023-11617-5","title":"Anomaly detection in three-axis CNC machines using LSTM networks and transfer learning","year":2023,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Anomaly detection; Machine learning; Artificial intelligence; Computer science; Transfer of learning; Set (abstract data type); Process (computing); Machine tool; Data set; Factory (object-oriented programming); Engineering","score_opus":0.007207465817009918,"score_gpt":0.234318515738637,"score_spread":0.22711104992162706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383343708","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18409492,0.0005678935,0.8094919,0.0003566801,0.00033558416,0.00004219045,0.00021695417,0.0027751916,0.002118773],"genre_scores_gemma":[0.93495864,0.000112833455,0.06298101,0.000053502154,0.00004676386,0.000026740452,0.00022595581,0.000075119715,0.0015194099],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966216,0.00003642305,0.000018279867,0.00012248884,0.00009650481,0.000064181804],"domain_scores_gemma":[0.9991412,0.0003142841,0.00011626749,0.000089112065,0.00029056607,0.000048449063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005900743,0.00060436595,0.0006279782,0.00067778496,0.00049959053,0.00078834244,0.0009111692,0.00082537427,0.001060454],"category_scores_gemma":[0.0017375859,0.00030021626,0.00043370447,0.000914978,0.00045986054,0.0008873525,0.0005910897,0.0012941621,0.00033879577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068448787,0.00021643254,0.008428675,0.00012624217,0.00009506141,0.0003678188,0.00014988513,0.41593382,0.031080537,0.005805283,0.005148029,0.53196377],"study_design_scores_gemma":[0.0000016545031,0.000011817543,0.0006781858,0.0000019576394,0.00000302535,0.000019262978,0.0000052730197,0.9961442,0.0019689796,0.0009783662,0.0001830949,0.0000041195603],"about_ca_topic_score_codex":0.008328726,"about_ca_topic_score_gemma":0.0070948596,"teacher_disagreement_score":0.008328726,"about_ca_system_score_codex":0.00073441333,"about_ca_system_score_gemma":0.0009104494,"threshold_uncertainty_score":0.016560495},"labels":[],"label_agreement":null},{"id":"W4384068244","doi":"10.1007/s00170-023-11904-1","title":"Integrated and efficient cutter-workpiece engagement determination in three-axis milling via voxel modeling","year":2023,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Voxel; Slicing; Machining; Milling cutter; Intersection (aeronautics); Surface (topology); Boundary (topology); Sequence (biology); Engineering drawing; Engineering; Computer science; Mechanical engineering; Geometry; Artificial intelligence; Mathematics; Mathematical analysis","score_opus":0.011502739856422053,"score_gpt":0.24763715464454142,"score_spread":0.23613441478811936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384068244","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02397024,0.00008842066,0.97441846,0.000024092657,0.0000062961094,0.000022992794,0.00003613199,0.0007414532,0.0006917892],"genre_scores_gemma":[0.495041,0.00011625755,0.5036457,0.000019910995,0.000006802335,0.0000651188,0.00017074587,0.00022627965,0.0007081788],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995246,0.000088727604,0.000026292339,0.00008440398,0.00022492302,0.000050988285],"domain_scores_gemma":[0.9993548,0.00033109373,0.00007956099,0.00008618993,0.00012434025,0.000023923378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046757245,0.0006090672,0.000908099,0.0005782998,0.00038785473,0.0011276708,0.0010714419,0.0007895928,0.001426186],"category_scores_gemma":[0.0012266244,0.0006190865,0.00064161693,0.00086620834,0.00036915054,0.000952444,0.0010452325,0.0006848887,0.00038956432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046212447,0.00017103492,0.0044360687,0.00036108916,0.00010926896,0.00019990152,0.0003495975,0.5445958,0.10323482,0.00895177,0.0013944828,0.3357341],"study_design_scores_gemma":[0.00000486065,0.00002820466,0.00040060095,0.000004033438,0.0000065102813,0.000044482615,0.000014850259,0.98949975,0.008935694,0.0006209548,0.00043137782,0.000008758987],"about_ca_topic_score_codex":0.00244444,"about_ca_topic_score_gemma":0.0041612834,"teacher_disagreement_score":0.00244444,"about_ca_system_score_codex":0.00040274582,"about_ca_system_score_gemma":0.0012006109,"threshold_uncertainty_score":0.0048604608},"labels":[],"label_agreement":null},{"id":"W4384817090","doi":"10.3390/lubricants11070301","title":"The Influence of Phosphate-Ester-Based Additives on Metal Cutting Fluid Behavior during the Machining of Titanium Alloy","year":2023,"lang":"en","type":"article","venue":"Lubricants","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Phosphate; Phosphorus; Titanium; Drilling; Titanium alloy; Alloy; Materials science; Machining; Chemical engineering; Metallurgy; Chemistry; Organic chemistry","score_opus":0.007922089567407899,"score_gpt":0.2378940006377224,"score_spread":0.2299719110703145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384817090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99856466,0.00047185787,0.0006655941,0.000009644378,0.0000066748294,0.000008582764,0.000022015713,0.000016317543,0.00023468716],"genre_scores_gemma":[0.9966444,0.00036578695,0.0025127658,0.000009858566,0.000004706967,0.0000088610195,0.00003753894,0.000011052923,0.00040500666],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99956506,0.00008696188,0.00005866687,0.000061007147,0.00016492208,0.00006346209],"domain_scores_gemma":[0.9994018,0.00021404299,0.00017476761,0.000025336298,0.00014392205,0.00004010905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043606473,0.00043666773,0.00037410113,0.0004388424,0.00020705485,0.0005530962,0.00033116242,0.00031596364,0.0004690185],"category_scores_gemma":[0.0012792149,0.00022685382,0.0002162948,0.00029000762,0.000294805,0.0004919856,0.00027677655,0.0002672371,0.00012850092],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007495068,0.000047734917,0.0010508911,0.00016257238,0.000012298136,0.00010533152,0.00010427488,0.00048606153,0.99089116,0.000038679555,0.000015652744,0.006335905],"study_design_scores_gemma":[0.000007915699,0.0007472737,0.0021464447,0.000010499226,0.000023643093,0.000059404163,0.00006657602,0.0011210684,0.9952834,0.000010648558,0.0005128038,0.0000103346165],"about_ca_topic_score_codex":0.0011197339,"about_ca_topic_score_gemma":0.0017975928,"teacher_disagreement_score":0.0011197339,"about_ca_system_score_codex":0.00022225462,"about_ca_system_score_gemma":0.0003397203,"threshold_uncertainty_score":0.0023061633},"labels":[],"label_agreement":null},{"id":"W4385009849","doi":"10.2139/ssrn.4517118","title":"A Hybrid Model in a Nonlinear Disturbance Observer for Improving Compliance Error Compensation of Robotic Machining","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Compensation (psychology); Machining; Control theory (sociology); Nonlinear system; Observer (physics); Control engineering; Compliance (psychology); Disturbance (geology); Nonlinear model; Computer science; Engineering; Control (management); Artificial intelligence; Psychology; Mechanical engineering; Physics; Geology","score_opus":0.040230434148225996,"score_gpt":0.2857482230061333,"score_spread":0.2455177888579073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385009849","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0342246,0.00021411254,0.962289,0.000094020535,0.0001412354,0.000038597653,0.000025385338,0.00033492516,0.0026382068],"genre_scores_gemma":[0.95107716,0.00015237917,0.043160915,0.000060625665,0.000044570854,0.00009244407,0.00005694874,0.000034245008,0.005320786],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997174,0.00006195131,0.000018268745,0.00006939264,0.000103155195,0.000029807057],"domain_scores_gemma":[0.99974316,0.00006560239,0.000041969557,0.000036219964,0.00010084309,0.0000122710935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042262327,0.0005195977,0.0006577583,0.00019920232,0.00028572598,0.0007445425,0.0006361248,0.00078703574,0.0014960477],"category_scores_gemma":[0.00060188724,0.00029886002,0.00039845478,0.00021760334,0.00046140462,0.00060129614,0.00071963103,0.00069067377,0.00032707222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048429356,0.0001739934,0.0009384705,0.00042280497,0.000113995404,0.00018616275,0.00020715066,0.81242925,0.08219023,0.010871897,0.0014514605,0.09053033],"study_design_scores_gemma":[0.000012647189,0.00008264025,0.00016274792,0.0000041406943,0.000010913627,0.000008720309,0.0000055163714,0.99677867,0.0020791504,0.00030866024,0.000541612,0.000004622055],"about_ca_topic_score_codex":0.0039812583,"about_ca_topic_score_gemma":0.004724318,"teacher_disagreement_score":0.0039812583,"about_ca_system_score_codex":0.00029668031,"about_ca_system_score_gemma":0.00039251763,"threshold_uncertainty_score":0.0079161525},"labels":[],"label_agreement":null},{"id":"W4385167795","doi":"10.1016/j.jmapro.2023.07.030","title":"An analysis of different cutting strategies to improve tool life when machining Ti-5Al-5V-5Mo-3Cr alloy","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Machining; Surface integrity; Coolant; Tool wear; Ultimate tensile strength; Alloy; Surface roughness; Metallurgy; Residual stress; Titanium alloy; Work hardening; Fretting; Abrasion (mechanical); Surface finish; Tribology; Composite material; Mechanical engineering; Microstructure","score_opus":0.010490797170613348,"score_gpt":0.2592038021299566,"score_spread":0.24871300495934323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385167795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98553187,0.00085461035,0.0109705515,0.00002162266,0.00001146363,0.000029420029,0.00008916027,0.0001009207,0.0023902217],"genre_scores_gemma":[0.9960989,0.000112558984,0.0033177114,0.000004563811,0.0000018326248,0.000009318604,0.000066431596,0.000017508028,0.00037125486],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971384,0.000037126993,0.000016192225,0.00004342506,0.00013258586,0.000056750825],"domain_scores_gemma":[0.99929845,0.00031202604,0.00010033682,0.000037500387,0.00023123766,0.000020515798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004025589,0.00041321033,0.00029048804,0.0009346669,0.00026321624,0.0004971339,0.00043730106,0.00049827225,0.0010296578],"category_scores_gemma":[0.00088794535,0.0001802049,0.00053349574,0.00048091204,0.00019230449,0.0003669843,0.000112474736,0.00015990568,0.00016509599],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024742638,0.00043133332,0.020065734,0.0010367561,0.00023494424,0.00035074123,0.0002381297,0.17926176,0.58104616,0.0014332539,0.0005083408,0.21291852],"study_design_scores_gemma":[0.00007180982,0.0065802303,0.08064946,0.00007303771,0.0006336751,0.00043134,0.0004820424,0.49597982,0.41095552,0.00088389573,0.0031789052,0.00008017844],"about_ca_topic_score_codex":0.0010008218,"about_ca_topic_score_gemma":0.0019323573,"teacher_disagreement_score":0.0010296578,"about_ca_system_score_codex":0.00036873532,"about_ca_system_score_gemma":0.00031308382,"threshold_uncertainty_score":0.003444612},"labels":[],"label_agreement":null},{"id":"W4385346693","doi":"10.3390/machines11080781","title":"Motor Current-Based Degradation Modeling for Tool Wear Hybrid Prognostics in Turning Process","year":2023,"lang":"en","type":"article","venue":"Machines","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Prognostics; Total harmonic distortion; Harmonics; Process (computing); Computer science; Time domain; Engineering; Encoder; Machine tool; Control theory (sociology); Electronic engineering; Control engineering; Artificial intelligence; Voltage; Reliability engineering; Mechanical engineering; Computer vision","score_opus":0.018623053986402315,"score_gpt":0.28231930360367385,"score_spread":0.26369624961727156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385346693","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22405474,0.0004914583,0.7734646,0.00012880831,0.000034028784,0.000029777311,0.00012881348,0.0005130136,0.0011547905],"genre_scores_gemma":[0.9912997,0.000089069756,0.008135037,0.000010392213,0.000006142666,0.000010260693,0.000065458255,0.000010087262,0.00037386283],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991345,0.00001562617,0.0000057268453,0.000021595828,0.00003034761,0.000013228475],"domain_scores_gemma":[0.9997992,0.00009275148,0.00003468002,0.00001714727,0.00004578531,0.00001044102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039688154,0.00042613776,0.0003744544,0.0004220128,0.00009072995,0.00034972187,0.0003894778,0.00035831722,0.0004294829],"category_scores_gemma":[0.0009008122,0.00016060185,0.00034770663,0.00023418247,0.00023673793,0.00042713684,0.00028263245,0.0003956678,0.000097361306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008008122,0.000032180797,0.0033857361,0.0000479776,0.000022834925,0.00006196424,0.000042041014,0.95053947,0.010017684,0.0006984056,0.00020516732,0.034866534],"study_design_scores_gemma":[6.273313e-7,0.000008525658,0.00039212024,8.402502e-7,0.000001401933,0.000006053905,0.0000020839555,0.9988932,0.0005146551,0.00014558028,0.000033648223,0.0000013484316],"about_ca_topic_score_codex":0.002896288,"about_ca_topic_score_gemma":0.0022520777,"teacher_disagreement_score":0.002896288,"about_ca_system_score_codex":0.00025654348,"about_ca_system_score_gemma":0.00026213133,"threshold_uncertainty_score":0.0057588816},"labels":[],"label_agreement":null},{"id":"W4385662977","doi":"10.1016/j.cirp.2023.05.009","title":"Sensor and actuator integrated tooling systems","year":2023,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Actuator; Miniaturization; Mechatronics; Electronics; Machine tool; Magnetorheological fluid; Engineering; Robustness (evolution); Machining; Mechanical engineering; Computer science; Control engineering; Embedded system; Electrical engineering; Damper","score_opus":0.027757056872407176,"score_gpt":0.2643235749263032,"score_spread":0.23656651805389603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385662977","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07801269,0.004082323,0.8302595,0.00066518557,0.0014130133,0.00038215573,0.001622322,0.0067383037,0.07682455],"genre_scores_gemma":[0.71731704,0.0013346216,0.18497902,0.0005366781,0.00024616392,0.00023202423,0.0015149835,0.00014917384,0.09369022],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99931014,0.000040408704,0.000028725666,0.00012894029,0.00044567944,0.000046152327],"domain_scores_gemma":[0.9996667,0.000046267927,0.000036399677,0.000057135443,0.00016993373,0.000023619988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003468458,0.0005383254,0.00040281954,0.0004917866,0.00033350315,0.0008916049,0.0011532761,0.00071338634,0.009156194],"category_scores_gemma":[0.00047920406,0.00025439035,0.00023484211,0.0006754835,0.0002039782,0.0009334383,0.0006393687,0.00059274357,0.0022287448],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056100654,0.00019900517,0.001975455,0.0006024829,0.00008435961,0.00019475911,0.000133385,0.013400216,0.3427071,0.016355094,0.013975446,0.60981166],"study_design_scores_gemma":[0.00016921127,0.0022779936,0.014188623,0.00011763701,0.00016690986,0.00085669424,0.0001154841,0.2916721,0.43059373,0.0075664534,0.2521105,0.00016457771],"about_ca_topic_score_codex":0.000811987,"about_ca_topic_score_gemma":0.0019669994,"teacher_disagreement_score":0.009156194,"about_ca_system_score_codex":0.00036938937,"about_ca_system_score_gemma":0.00064710213,"threshold_uncertainty_score":0.030630529},"labels":[],"label_agreement":null},{"id":"W4385973924","doi":"10.2139/ssrn.4545340","title":"Piezoelectric Gripper with Force and Displacement Control Using Integrated Strain Sensing Electrodes","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Piezoelectricity; Displacement (psychology); Strain (injury); Electrode; Materials science; Mechanical engineering; Acoustics; Composite material; Engineering; Physics; Medicine; Psychology; Anatomy","score_opus":0.00811147828391659,"score_gpt":0.22913523418832363,"score_spread":0.22102375590440704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385973924","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2569889,0.0014536418,0.7229138,0.00032833742,0.0004176271,0.0002138157,0.00024180296,0.001571601,0.015870422],"genre_scores_gemma":[0.80856025,0.00027247035,0.18248886,0.0001565842,0.000076406985,0.00010724724,0.00009360624,0.000058137124,0.008186442],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996996,0.000013995081,0.000015868774,0.00008791978,0.00015595224,0.000026719621],"domain_scores_gemma":[0.99978536,0.000056101693,0.000028877797,0.00004565274,0.0000648524,0.000019237896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000233838,0.0004113296,0.0004629942,0.00017776429,0.00022705852,0.0005510319,0.001179801,0.00073708675,0.0018877562],"category_scores_gemma":[0.00034800675,0.00041675183,0.00020461809,0.00033792047,0.00024543732,0.0005729688,0.0006141391,0.00037886246,0.00048153105],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015961422,0.00007785486,0.00035477406,0.00014413538,0.000032555883,0.00014699264,0.00004080888,0.0036971283,0.9376869,0.0015300238,0.00070186745,0.055427346],"study_design_scores_gemma":[0.00016437922,0.001218307,0.0064476714,0.000034159235,0.0000999763,0.001293084,0.000037084734,0.17236972,0.80555254,0.0014191018,0.011274705,0.000089195775],"about_ca_topic_score_codex":0.00035616534,"about_ca_topic_score_gemma":0.00072097854,"teacher_disagreement_score":0.0018877562,"about_ca_system_score_codex":0.00019501794,"about_ca_system_score_gemma":0.00026503744,"threshold_uncertainty_score":0.0063152313},"labels":[],"label_agreement":null},{"id":"W4385984398","doi":"10.21203/rs.3.rs-3252792/v1","title":"Intelligent Characterization of Spark-Assisted Chemical Engraving (SACE) Process Using Time Series Classification","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Engraving; SPARK (programming language); Bayesian optimization; Computer science; Process (computing); Key (lock); Series (stratigraphy); Algorithm; Field (mathematics); Energy (signal processing); Sequence (biology); Artificial intelligence; Electrical discharge machining; Machine learning; Machining; Engineering; Mathematics; Mechanical engineering","score_opus":0.1008470421365168,"score_gpt":0.38662937312538925,"score_spread":0.28578233098887246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385984398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81539077,0.00031448147,0.17932174,0.00015540699,0.000056871348,0.000049600756,0.0003342878,0.0012916686,0.0030851976],"genre_scores_gemma":[0.98050874,0.000061673636,0.018645393,0.0000135088085,0.0000039344454,0.0000126560135,0.00010084717,0.000021818718,0.00063146814],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998362,0.000011084113,0.00000884895,0.00004248444,0.00008734132,0.000014051857],"domain_scores_gemma":[0.9997211,0.00008338996,0.00006176289,0.000034403907,0.00008720868,0.000012068214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003448616,0.00025666828,0.0002559813,0.00048239774,0.00013862185,0.00042321492,0.0003383663,0.00028643594,0.00077098643],"category_scores_gemma":[0.0006515728,0.00010054531,0.00017843321,0.00035936612,0.00023634573,0.00039099934,0.00016439178,0.00030711995,0.00015263817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006193602,0.00020890024,0.016154867,0.00025357428,0.000075437965,0.00028751357,0.0002191606,0.1154896,0.6342896,0.0028445025,0.0014965786,0.22806089],"study_design_scores_gemma":[0.0000044204576,0.00007689469,0.006524431,0.000004472718,0.000008316736,0.000058466045,0.000034737444,0.8293061,0.16288017,0.0004634368,0.00062433316,0.000014257699],"about_ca_topic_score_codex":0.0014830903,"about_ca_topic_score_gemma":0.0019619062,"teacher_disagreement_score":0.0014830903,"about_ca_system_score_codex":0.00037279245,"about_ca_system_score_gemma":0.00024278661,"threshold_uncertainty_score":0.0029488802},"labels":[],"label_agreement":null},{"id":"W4386072863","doi":"10.11159/mmme23.117","title":"Model-Based Determination Of Process Force In Multi-Axis Milling","year":2023,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Process (computing); Computer science; Process engineering; Engineering","score_opus":0.012536195694578148,"score_gpt":0.2408000517529894,"score_spread":0.22826385605841126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386072863","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07735931,0.0006808018,0.9151355,0.00018808704,0.000056628916,0.000086670705,0.00016017133,0.0010042676,0.005328581],"genre_scores_gemma":[0.9647692,0.00028939938,0.032950994,0.000029148327,0.000014498285,0.00010583623,0.00013756377,0.0000739834,0.0016295033],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977225,0.000042692307,0.00001131432,0.000053252264,0.000084072104,0.00003649146],"domain_scores_gemma":[0.999584,0.0002120157,0.00006482037,0.00002978484,0.00008798309,0.000021481528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045232495,0.0008217268,0.0013592112,0.00051066664,0.0004916197,0.0012280769,0.0009850506,0.0015165104,0.0013708201],"category_scores_gemma":[0.001213325,0.00065344275,0.0007273642,0.0004883952,0.0005331643,0.0007613095,0.0005661959,0.00082400226,0.00042514125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024229674,0.000019919995,0.00023433479,0.00002900211,0.000007961985,0.000030027477,0.000012330987,0.99168175,0.0018544428,0.0008391179,0.00010433946,0.0051625855],"study_design_scores_gemma":[0.0000035596136,0.0000061716887,0.00008084855,0.000001712421,0.0000010958479,0.000003031562,0.0000013384523,0.9994135,0.00022084109,0.00019159284,0.000074333155,0.0000021354026],"about_ca_topic_score_codex":0.018670633,"about_ca_topic_score_gemma":0.011754434,"teacher_disagreement_score":0.018670633,"about_ca_system_score_codex":0.000918247,"about_ca_system_score_gemma":0.0012083965,"threshold_uncertainty_score":0.03712386},"labels":[],"label_agreement":null},{"id":"W4386213415","doi":"10.30955/gnc2023.00496","title":"Paradigm Shift Towards Integrated Sustainability and High Performance Machining","year":2023,"lang":"en","type":"article","venue":"Global NEST International Conference on Environmental Science & Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Partenariat Canadien Contre Le Cancer","keywords":"Sustainability; Productivity; Machining; Process (computing); Manufacturing engineering; Quality (philosophy); Lubrication; Risk analysis (engineering); Production (economics); Computer science; Engineering; Environmental economics; Business; Mechanical engineering","score_opus":0.008106683619302432,"score_gpt":0.24838768201935402,"score_spread":0.24028099840005157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386213415","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07751419,0.0407137,0.54485893,0.12193877,0.002710825,0.00017384774,0.0001333818,0.0006671992,0.2112891],"genre_scores_gemma":[0.80986035,0.01884597,0.13915181,0.010859526,0.0011937422,0.0002811052,0.00009090319,0.00012475038,0.019591799],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99725085,0.00076193805,0.00008052901,0.0003411799,0.0013059898,0.0002594721],"domain_scores_gemma":[0.99828243,0.0005052086,0.00018984072,0.00025257806,0.00055830745,0.00021173983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043268134,0.0006958313,0.0005399194,0.00084730895,0.0007637015,0.0034569732,0.0013838889,0.0031249777,0.0016924669],"category_scores_gemma":[0.0015059902,0.00023282265,0.00051069027,0.0005919035,0.00632786,0.004320317,0.0036399276,0.003148045,0.00042799502],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035972025,0.00008349832,0.00030449408,0.0003930311,0.00002443639,0.000099934405,0.0005000384,0.0048535685,0.00443551,0.93908715,0.003704009,0.046478417],"study_design_scores_gemma":[0.000026949756,0.00018302239,0.0005540302,0.00031668445,0.000014814772,0.000255892,0.0006908023,0.011884369,0.0040976373,0.8329827,0.14895019,0.000042983487],"about_ca_topic_score_codex":0.0007136297,"about_ca_topic_score_gemma":0.0007554694,"teacher_disagreement_score":0.0043268134,"about_ca_system_score_codex":0.003363435,"about_ca_system_score_gemma":0.0042594075,"threshold_uncertainty_score":0.024403512},"labels":[],"label_agreement":null},{"id":"W4386293303","doi":"10.1115/1.4063286","title":"Virtual Dynamics Model for Five-Axis Machining of Thin-Walled Blades","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; End mill; Vibration; Ball (mathematics); Finite element method; Machine tool; Structural engineering; Mechanical engineering; Engineering; Blade (archaeology); Frequency response; Acoustics; Geometry; Physics; Mathematics","score_opus":0.009306890616064874,"score_gpt":0.22956310303793764,"score_spread":0.22025621242187277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386293303","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23098145,0.00033736628,0.7465427,0.0001709857,0.00010207083,0.00011301346,0.00025763296,0.00072889606,0.02076596],"genre_scores_gemma":[0.9772978,0.00016090079,0.015515217,0.000026071346,0.0000074979503,0.00010540574,0.0001093012,0.000030125497,0.006747741],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999014,0.000017132774,0.0000050214812,0.000018067794,0.000044526507,0.000013766624],"domain_scores_gemma":[0.99986947,0.000035824367,0.000030130657,0.000015258047,0.000035655514,0.000013609488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015334248,0.00039512498,0.00047352875,0.00029091595,0.00037123976,0.0007762967,0.0007030613,0.0007402294,0.0023425906],"category_scores_gemma":[0.0003421114,0.00027087788,0.00040142363,0.00020268891,0.0006191434,0.00038470537,0.00047444776,0.00036234886,0.00036486774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019701783,0.000011550952,0.000315662,0.000022338654,0.0000064937926,0.000083966675,0.000044645043,0.9913708,0.0039077895,0.0021392521,0.00007362149,0.002004116],"study_design_scores_gemma":[0.000004617209,0.0000126834275,0.00011118533,0.0000019034477,0.0000017429545,0.000010341906,0.0000060451302,0.99911624,0.00028068802,0.00019577064,0.00025658775,0.0000021563335],"about_ca_topic_score_codex":0.007812133,"about_ca_topic_score_gemma":0.003726317,"teacher_disagreement_score":0.007812133,"about_ca_system_score_codex":0.00040723875,"about_ca_system_score_gemma":0.000697531,"threshold_uncertainty_score":0.015533328},"labels":[],"label_agreement":null},{"id":"W4386715496","doi":"10.3390/met13091587","title":"Experimental Investigation of the Derivative Cutting When Machining AISI 1045 with Micro-Textured Cutting Tools","year":2023,"lang":"en","type":"article","venue":"Metals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Materials science; Tool wear; Surface roughness; Mechanical engineering; Cutting tool; Groove (engineering); Chip; Surface finish; Metallurgy; Composite material; Computer science; Engineering","score_opus":0.021117006844018422,"score_gpt":0.2397618316236342,"score_spread":0.21864482477961578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386715496","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979899,0.00013950703,0.0013778104,0.000009314311,0.000009145948,0.00002198452,0.000049474038,0.000024721514,0.00037811292],"genre_scores_gemma":[0.9938736,0.00014725089,0.0053527984,0.00000966366,0.000004021596,0.000018172283,0.000055264336,0.000010022556,0.0005292374],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99944884,0.000035028446,0.000043279404,0.0001033774,0.00028118156,0.00008833783],"domain_scores_gemma":[0.99921703,0.00017621866,0.00021387772,0.00010302759,0.00024460544,0.00004505202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004344768,0.00033367012,0.00030038028,0.00039265762,0.00021951154,0.00029749126,0.0004238807,0.00058268785,0.0008940954],"category_scores_gemma":[0.0008513129,0.00022739713,0.0003006754,0.0003887724,0.00030654628,0.00029586515,0.00018637853,0.00041112772,0.00016167031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021237657,0.00009552591,0.00088568806,0.00016275916,0.000008420622,0.00010588527,0.00013617465,0.0008046666,0.9938782,0.000043700802,0.000035573863,0.0036310714],"study_design_scores_gemma":[0.000031385407,0.0039240257,0.0169534,0.000016070093,0.000037135665,0.00014759923,0.0002217122,0.0075504747,0.9702032,0.000039952924,0.0008446934,0.000030373487],"about_ca_topic_score_codex":0.0008836869,"about_ca_topic_score_gemma":0.0014966455,"teacher_disagreement_score":0.0008940954,"about_ca_system_score_codex":0.00015632929,"about_ca_system_score_gemma":0.00015548756,"threshold_uncertainty_score":0.0029910803},"labels":[],"label_agreement":null},{"id":"W4386920594","doi":"10.1109/icaiss58487.2023.10250572","title":"Prediction of Flank Wear of Inconel by using the Levenberg-Marquardt ANN Model","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Inconel; Flank; Tool wear; Artificial neural network; Machining; Process (computing); Backpropagation; Computer science; Artificial intelligence; Engineering; Mechanical engineering; Machine learning; Materials science; Metallurgy","score_opus":0.029637472424985656,"score_gpt":0.24047321504906885,"score_spread":0.2108357426240832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386920594","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7088654,0.0005496789,0.2854499,0.000120751436,0.000059648846,0.0000546162,0.00021844085,0.000695511,0.003986092],"genre_scores_gemma":[0.9805828,0.00011115059,0.017658686,0.000011621092,0.000005715878,0.00002739023,0.00013885254,0.000011169864,0.0014526312],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986327,0.00002355705,0.00001025968,0.00003911385,0.000046050776,0.000017809643],"domain_scores_gemma":[0.999589,0.00021010198,0.000047806356,0.00002081619,0.00012233677,0.000009882904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036233832,0.0005521886,0.00045162695,0.00042122218,0.00023221121,0.00046662297,0.00042345424,0.000522303,0.000685107],"category_scores_gemma":[0.0011214028,0.00025340487,0.00040047648,0.0002427755,0.00015723809,0.00028979094,0.00021444685,0.0004231026,0.0001440361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042413525,0.000027883461,0.0022420115,0.000029231374,0.000014884063,0.000057403453,0.000013820662,0.9730208,0.0022806064,0.00008429405,0.00012649993,0.02206016],"study_design_scores_gemma":[8.294395e-7,0.000009650398,0.00050374714,0.0000014593728,0.0000015292084,0.000004900902,0.000001950887,0.9989955,0.0004126625,0.00003232779,0.000034019096,0.0000013871473],"about_ca_topic_score_codex":0.009239082,"about_ca_topic_score_gemma":0.0107493,"teacher_disagreement_score":0.009239082,"about_ca_system_score_codex":0.00031405955,"about_ca_system_score_gemma":0.0003826087,"threshold_uncertainty_score":0.018370628},"labels":[],"label_agreement":null},{"id":"W4387043281","doi":"10.21203/rs.3.rs-3325111/v1","title":"Influence of Machining Parameters on Dynamic Errors in a Hexapod Machining Cell","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Hexapod; Machining; Mechanical engineering; Computer science; Engineering; Artificial intelligence; Robot","score_opus":0.04104962170275615,"score_gpt":0.36708975083005585,"score_spread":0.3260401291272997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387043281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9756079,0.00015572988,0.023603499,0.00001714878,0.00001585483,0.00001962152,0.00005360725,0.00010678688,0.0004199253],"genre_scores_gemma":[0.995378,0.000018174207,0.0044178134,0.0000042269335,8.9800534e-7,0.000005106241,0.000023682282,0.000005400734,0.0001467136],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994367,0.00008020289,0.0000422136,0.00013898527,0.0002582461,0.000043629636],"domain_scores_gemma":[0.9984837,0.000771972,0.00022685871,0.00021834565,0.0002550364,0.00004406396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045234908,0.0002826462,0.0003508414,0.00029433405,0.0001473171,0.00040555888,0.00028268367,0.00029941244,0.0007142785],"category_scores_gemma":[0.0012803461,0.00015914632,0.000109677676,0.00030547936,0.00036893203,0.00026275538,0.0002524114,0.00021855775,0.000105612904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072469417,0.00012241659,0.009318174,0.00025105348,0.000036405596,0.0003097967,0.00020140744,0.038744185,0.886261,0.00021308886,0.00012855713,0.06368932],"study_design_scores_gemma":[0.00002911843,0.001326379,0.050219618,0.00001846726,0.000036563535,0.00030322574,0.00020383236,0.23448254,0.71187496,0.00021656684,0.0012376938,0.000050928847],"about_ca_topic_score_codex":0.0006176535,"about_ca_topic_score_gemma":0.00068911124,"teacher_disagreement_score":0.0007142785,"about_ca_system_score_codex":0.00015975282,"about_ca_system_score_gemma":0.00013675714,"threshold_uncertainty_score":0.002392292},"labels":[],"label_agreement":null},{"id":"W4387100088","doi":"10.18280/jesa.560411","title":"Modelling the Effects of Workpiece Flexibility on Cutting Performance in Turning Operations","year":2023,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Flexibility (engineering); Manufacturing engineering; Mechanical engineering; Computer science; Engineering drawing; Engineering; Economics; Management","score_opus":0.017273998497239373,"score_gpt":0.25325048050266646,"score_spread":0.2359764820054271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387100088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80723184,0.00022718748,0.18421718,0.00006990726,0.000015262038,0.00009026885,0.00020571826,0.00016795985,0.0077745696],"genre_scores_gemma":[0.99338794,0.00010167832,0.0053870897,0.0000056872905,0.0000017078769,0.000034714772,0.00004154688,0.000014598366,0.0010250787],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998425,0.0000279395,0.0000076629685,0.000027713404,0.000056536523,0.000037639325],"domain_scores_gemma":[0.99961543,0.00026259435,0.000052182917,0.000033822205,0.00002660032,0.000009375326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030368945,0.0004980032,0.00033708388,0.00025887793,0.00018896583,0.0008616479,0.0006739968,0.00092317583,0.001297411],"category_scores_gemma":[0.0009925474,0.0003182164,0.0005744885,0.0002881775,0.00036185712,0.00041703935,0.00034935467,0.00040505722,0.00023903759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034609795,0.00003237789,0.0010159704,0.000035635658,0.00000676474,0.000055241828,0.00003657741,0.9855298,0.0083624385,0.00040992483,0.000027637738,0.004452939],"study_design_scores_gemma":[0.000004106611,0.00007823477,0.0017005273,0.0000052955047,0.000008186194,0.000027192023,0.000015819653,0.99442977,0.0033197335,0.00024488888,0.00015671451,0.000009572829],"about_ca_topic_score_codex":0.004564716,"about_ca_topic_score_gemma":0.004005445,"teacher_disagreement_score":0.004564716,"about_ca_system_score_codex":0.00030370423,"about_ca_system_score_gemma":0.0005075117,"threshold_uncertainty_score":0.009076238},"labels":[],"label_agreement":null},{"id":"W4387336504","doi":"10.1115/1.4063654","title":"Chatter Avoidance by Spindle Speed and Orientation Planning in Five-Axis Ball-End Milling of Thin-Walled Blades","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"End milling; Ball (mathematics); Orientation (vector space); Materials science; Mechanical engineering; Engineering; Geometry; Mathematics; Machining","score_opus":0.007346587358939585,"score_gpt":0.2297584977911753,"score_spread":0.2224119104322357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387336504","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55871797,0.00016930826,0.43982396,0.00003922525,0.0000097946395,0.000035637935,0.0000073469223,0.00013581228,0.0010609358],"genre_scores_gemma":[0.9827571,0.000024761453,0.017028196,0.0000037500683,9.826172e-7,0.00000753305,0.00000408736,0.000005788644,0.0001678885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998745,0.000037073794,0.000009034519,0.000020790247,0.00003674931,0.000021929995],"domain_scores_gemma":[0.9992981,0.00036635296,0.0001745646,0.000028301612,0.00010128946,0.000031453303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004873763,0.00040725697,0.00036523608,0.00029564239,0.00022564146,0.00038058087,0.00034814127,0.00029999876,0.0002472687],"category_scores_gemma":[0.0011999101,0.00033912895,0.00019224803,0.000119556964,0.00037882724,0.00019372121,0.00025878762,0.00022228323,0.00004894933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030487374,0.000071759256,0.0025352233,0.000096458636,0.000027185593,0.00019832686,0.00019334503,0.90735495,0.05354633,0.00086570904,0.0000946313,0.03471114],"study_design_scores_gemma":[0.00001692368,0.00012655387,0.0006631619,0.0000057373823,0.000006556572,0.000025105832,0.000017729066,0.9928964,0.005987317,0.00018802872,0.00006086976,0.0000056071162],"about_ca_topic_score_codex":0.001960466,"about_ca_topic_score_gemma":0.0018793957,"teacher_disagreement_score":0.001960466,"about_ca_system_score_codex":0.00020121664,"about_ca_system_score_gemma":0.0003507043,"threshold_uncertainty_score":0.0038980842},"labels":[],"label_agreement":null},{"id":"W4387353163","doi":"10.1016/j.jmapro.2023.09.050","title":"Machining pre-sintered compacts of a sinter-hardenable powder metallurgy steel: A novel methodology for selecting sintering temperatures for the optimum machinability","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Ministry of Education, India","keywords":"Machinability; Materials science; Metallurgy; Machining; Powder metallurgy; Sintering; Surface roughness; Composite material","score_opus":0.057879700546301004,"score_gpt":0.32297842416226663,"score_spread":0.26509872361596565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387353163","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92525727,0.0008243503,0.070893414,0.000077479795,0.00005440395,0.00010428682,0.00011093348,0.00028130494,0.0023966075],"genre_scores_gemma":[0.94112027,0.00024187106,0.05647943,0.00002038734,0.000014663011,0.00003809227,0.00011033133,0.00006482161,0.0019100297],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998079,0.000009699293,0.000016560421,0.000049842598,0.00010136433,0.000014679643],"domain_scores_gemma":[0.99976355,0.000049493854,0.000083376566,0.00004343617,0.00004713036,0.000012978339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025008112,0.00025865075,0.00044564705,0.00026880993,0.00018599225,0.00027943036,0.0004206516,0.00031794558,0.00091296853],"category_scores_gemma":[0.0003994232,0.00034919567,0.00017963994,0.00025962418,0.00026017328,0.00033645172,0.0002048748,0.00039946512,0.00021643135],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052827323,0.000010769884,0.00011702908,0.000056262663,0.0000034124816,0.000022270518,0.000023606179,0.00025885808,0.9960531,0.0000993355,0.000029602175,0.0032728848],"study_design_scores_gemma":[0.000011913072,0.00017340039,0.0020512145,0.0000028873687,0.000007869436,0.000067959576,0.000012502117,0.0028142724,0.9939883,0.000030312784,0.0008342697,0.0000051406837],"about_ca_topic_score_codex":0.0003051295,"about_ca_topic_score_gemma":0.0020953524,"teacher_disagreement_score":0.00091296853,"about_ca_system_score_codex":0.00019274562,"about_ca_system_score_gemma":0.00034594198,"threshold_uncertainty_score":0.003054142},"labels":[],"label_agreement":null},{"id":"W4387368888","doi":"10.1016/j.jmatprotec.2023.118170","title":"Effect of cutting fluids on surface residual stress in machining of waspaloy","year":2023,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Innovation, Science and Economic Development Canada","keywords":"Residual stress; Cutting fluid; Materials science; Machining; Stress (linguistics); Composite material; Surface integrity; Fluid dynamics; Metallurgy; Ultimate tensile strength; Mechanical engineering; Mechanics; Engineering","score_opus":0.005760248259082739,"score_gpt":0.264422123218204,"score_spread":0.2586618749591213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387368888","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989109,0.0003838404,0.00035745904,0.000019907084,0.000012279273,0.0000032387336,0.000021477772,0.000017405542,0.00027356963],"genre_scores_gemma":[0.99941957,0.00008273396,0.00023812718,0.000004918549,0.0000034891245,0.0000012962811,0.000019893261,0.0000072286616,0.00022279218],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981314,0.000029930752,0.000015314623,0.00003083783,0.000058677233,0.00005227997],"domain_scores_gemma":[0.99919444,0.00041845615,0.0001135749,0.000030508716,0.00019234569,0.000050620958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002932923,0.00028906798,0.00040932486,0.0002563733,0.00035034257,0.00057309226,0.00037077308,0.0004377167,0.0013656723],"category_scores_gemma":[0.0010228802,0.00017002797,0.00024659114,0.00026143098,0.00046476675,0.0004934394,0.00019290134,0.00037155577,0.000117812866],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002888455,0.0001169082,0.0020680688,0.000267914,0.000035657504,0.0003728093,0.00031133537,0.0038194004,0.9793372,0.0001979255,0.00012117915,0.010463246],"study_design_scores_gemma":[0.000043242773,0.002565612,0.0075920075,0.000017966253,0.0000581458,0.00009402616,0.00026775117,0.013133335,0.97549814,0.00006884877,0.0006354485,0.000025432439],"about_ca_topic_score_codex":0.0012312493,"about_ca_topic_score_gemma":0.0016765154,"teacher_disagreement_score":0.0013656723,"about_ca_system_score_codex":0.0002772805,"about_ca_system_score_gemma":0.00035505302,"threshold_uncertainty_score":0.004568577},"labels":[],"label_agreement":null},{"id":"W4387399337","doi":"10.1007/s00170-023-12393-y","title":"Influence of nanoparticle concentration in nanofluid MQL on cutting forces, tool wear, chip morphology when milling of Inconel 718","year":2023,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanofluid; Machinability; Inconel; Materials science; Lubrication; Machining; Surface roughness; Morphology (biology); Nanoparticle; Superalloy; Chip formation; Metallurgy; Tool wear; Surface finish; Composite material; Nanotechnology; Microstructure","score_opus":0.006457575715934696,"score_gpt":0.2360056335941436,"score_spread":0.2295480578782089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387399337","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989538,0.00021357357,0.00034462963,0.000034797664,0.0000139456715,0.000004479036,0.00005144468,0.000013860655,0.00036944036],"genre_scores_gemma":[0.9987336,0.000077786775,0.00048284102,0.00001528537,0.0000037538446,0.0000069244893,0.000030750052,0.0000067295186,0.00064232876],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996942,0.0000314715,0.000026410604,0.000075899676,0.00011269894,0.000059291004],"domain_scores_gemma":[0.99929917,0.00033925637,0.00013686936,0.000034294146,0.00015375302,0.00003659223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034532088,0.00017956393,0.00022287555,0.00017307416,0.00030439848,0.0003859019,0.00023972138,0.00044398004,0.0012259784],"category_scores_gemma":[0.0008778162,0.00024313568,0.00018463715,0.00015187553,0.00030795322,0.0003412241,0.0001709282,0.00035644593,0.00020160264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026030667,0.000022830729,0.0004386672,0.00005889119,0.0000065817053,0.00006360082,0.00011015783,0.00022871842,0.9973386,0.000035328736,0.000046124176,0.0013903406],"study_design_scores_gemma":[0.000008172596,0.0002627617,0.0030750937,0.0000052535875,0.000010681686,0.000019685715,0.00006343425,0.0013838205,0.99490297,0.000010451384,0.00025020825,0.0000075188595],"about_ca_topic_score_codex":0.0014302568,"about_ca_topic_score_gemma":0.0026759403,"teacher_disagreement_score":0.0014302568,"about_ca_system_score_codex":0.0003917474,"about_ca_system_score_gemma":0.00020550673,"threshold_uncertainty_score":0.0041012764},"labels":[],"label_agreement":null},{"id":"W4387463044","doi":"10.1016/j.mfglet.2023.08.088","title":"Nonlinearity and periodicity in machining carbon fiber reinforced polymer","year":2023,"lang":"en","type":"article","venue":"Manufacturing Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chip formation; Materials science; Machining; Carbon fiber reinforced polymer; Chip; Rake; Composite material; Drilling; Fiber; Nonlinear system; Fibre-reinforced plastic; Polymer; Orientation (vector space); Tool wear; Mechanical engineering; Computer science; Geometry; Metallurgy; Reinforced concrete; Engineering; Physics; Telecommunications","score_opus":0.006575202185351279,"score_gpt":0.2048211280769427,"score_spread":0.1982459258915914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387463044","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9708708,0.00026392812,0.020745572,0.00017140555,0.00003386783,0.000009724918,0.00001105818,0.000047117825,0.007846492],"genre_scores_gemma":[0.9955781,0.0000469165,0.0028671974,0.000012475042,0.000008449806,0.000004761033,0.0000058401133,0.000012345152,0.0014637724],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998913,0.000022691209,0.000004066932,0.000013761495,0.00005218358,0.000015942238],"domain_scores_gemma":[0.9994679,0.00030194325,0.00010110794,0.000034295485,0.000051669947,0.000043044492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001753263,0.000104927094,0.0001555844,0.00021931175,0.00029608214,0.0003003926,0.00018310711,0.00035347583,0.00084578845],"category_scores_gemma":[0.0008739612,0.00023153402,0.000088997294,0.00013491376,0.0005095655,0.00039156704,0.00025037528,0.0003479087,0.00013409062],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048150177,0.00023071024,0.00683624,0.0001528151,0.000021088594,0.00074637216,0.00027695872,0.17541003,0.75681955,0.033073857,0.0004300758,0.02552081],"study_design_scores_gemma":[0.000021031088,0.00029034153,0.007518892,0.000011432355,0.00000706031,0.00032975458,0.00009993663,0.8747575,0.11195522,0.004503451,0.00047162204,0.00003368774],"about_ca_topic_score_codex":0.00054084015,"about_ca_topic_score_gemma":0.0011487647,"teacher_disagreement_score":0.00084578845,"about_ca_system_score_codex":0.00026442233,"about_ca_system_score_gemma":0.00033663845,"threshold_uncertainty_score":0.0028294325},"labels":[],"label_agreement":null},{"id":"W4388230683","doi":"10.1115/1.4063983","title":"Experimental Validation of Reconstructed Microstructure via Deep Learning in Discontinuous Fiber Platelet Composite","year":2023,"lang":"en","type":"article","venue":"Journal of Applied Mechanics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Materials science; Composite material; Optical microscope; Nondestructive testing; Microstructure; Fiber; Composite number; Digital image correlation; Composite plate; Microscopy; Optics; Scanning electron microscope","score_opus":0.004723365719097222,"score_gpt":0.213572830578601,"score_spread":0.20884946485950376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388230683","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9480229,0.000081265345,0.05036132,0.00004278872,0.00001791596,0.000024059269,0.00015955245,0.00042940726,0.0008608207],"genre_scores_gemma":[0.9820403,0.000023699284,0.017513119,0.000008400975,0.0000011198886,0.000012244803,0.00007801793,0.000015506954,0.00030758444],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981815,0.000026047455,0.000008254494,0.0000434021,0.000081571015,0.000022692924],"domain_scores_gemma":[0.9994997,0.00012207574,0.00008698224,0.00010805971,0.00015154544,0.00003162458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066569087,0.00041486035,0.00025749084,0.00042552015,0.00018642689,0.00027965452,0.00048764696,0.0005095046,0.0008180334],"category_scores_gemma":[0.00078979676,0.00018743803,0.00023205053,0.00023770418,0.00047226003,0.00022782163,0.00034241925,0.00040414848,0.00012624456],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007970031,0.0003757573,0.007034332,0.00021115517,0.00005267067,0.00029484447,0.00012759761,0.34064764,0.6130825,0.00089688157,0.00033778432,0.036141884],"study_design_scores_gemma":[0.000013451603,0.0003096257,0.005105829,0.000007766393,0.000010720699,0.00005204628,0.000024633362,0.7963268,0.19777746,0.00014017816,0.0002182802,0.000013085574],"about_ca_topic_score_codex":0.0020259416,"about_ca_topic_score_gemma":0.0025763921,"teacher_disagreement_score":0.0020259416,"about_ca_system_score_codex":0.00034649004,"about_ca_system_score_gemma":0.0003286955,"threshold_uncertainty_score":0.0040283203},"labels":[],"label_agreement":null},{"id":"W4388441474","doi":"10.18280/isi.280525","title":"Enhancing Fault Detection in CNC Machinery: A Deep Learning and Genetic Algorithm Approach","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Fault detection and isolation; Genetic algorithm; Deep learning; Algorithm; Machine learning; Actuator","score_opus":0.005317496891530257,"score_gpt":0.20883054577996962,"score_spread":0.20351304888843935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388441474","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07246958,0.00041049236,0.92224413,0.0005896074,0.000048397,0.000073780146,0.00009034199,0.0018747712,0.0021988768],"genre_scores_gemma":[0.7068735,0.00021637852,0.28965995,0.00033018022,0.000037285572,0.00011041884,0.00022066096,0.00008986291,0.0024618164],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997538,0.000057131154,0.000009742273,0.00006468001,0.000068859066,0.000045734527],"domain_scores_gemma":[0.99947745,0.0002448139,0.00005490945,0.00004157019,0.00015613824,0.000025146308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006763203,0.0009443437,0.0005619745,0.00090810284,0.00030502857,0.0006664857,0.0011345072,0.0013236708,0.00077653566],"category_scores_gemma":[0.0020436049,0.00030395246,0.0004085939,0.0005355005,0.0005285147,0.00085079344,0.0006882325,0.001168301,0.00025115613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008808617,0.00013653621,0.0021037606,0.00004699573,0.00004561303,0.000057537498,0.000037178703,0.8035068,0.0075323367,0.0031154845,0.0010257789,0.18230382],"study_design_scores_gemma":[0.000002897681,0.000015547172,0.000109981476,0.0000021631713,0.0000034282052,0.0000058850064,0.0000037150162,0.99796754,0.0010266914,0.0007271364,0.00013326327,0.0000017161071],"about_ca_topic_score_codex":0.012101844,"about_ca_topic_score_gemma":0.011613262,"teacher_disagreement_score":0.012101844,"about_ca_system_score_codex":0.0013417713,"about_ca_system_score_gemma":0.0012647217,"threshold_uncertainty_score":0.024062753},"labels":[],"label_agreement":null},{"id":"W4388661171","doi":"10.3390/ma16227157","title":"Experimental Investigation on Machinability of α/β Titanium Alloys with Different Microstructures","year":2023,"lang":"en","type":"article","venue":"Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Academy of Scientific Research and Technology","keywords":"Machinability; Materials science; Microstructure; Martensite; Metallurgy; Martensitic stainless steel; Machining; Surface roughness; Surface finish; Tool wear; Titanium alloy; Layer (electronics); Titanium; Phase (matter); Deformation (meteorology); Composite material","score_opus":0.011277286981593873,"score_gpt":0.22804479931024801,"score_spread":0.21676751232865415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388661171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9953595,0.000633429,0.0024908474,0.000016832866,0.000015999902,0.000044477623,0.00015306904,0.00003101144,0.0012548602],"genre_scores_gemma":[0.9929476,0.00034503225,0.0050669466,0.000017398015,0.000006088947,0.00003756775,0.0001706267,0.000019519763,0.0013893322],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971706,0.000018975301,0.000024885063,0.000056187386,0.00014388894,0.000038967177],"domain_scores_gemma":[0.9996762,0.000032930184,0.00009842789,0.000040438474,0.00013365131,0.000018231358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027054286,0.00023417466,0.00018874885,0.00026153322,0.00026409657,0.00019108044,0.00030686092,0.0002357219,0.0008628231],"category_scores_gemma":[0.0003652676,0.00019709498,0.00016538384,0.00025360717,0.00020862333,0.00015383793,0.00013934252,0.00022638579,0.00015985567],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005511424,0.000013523005,0.0005518991,0.0000665858,0.0000040161617,0.000036491954,0.00005656045,0.00016462,0.9979303,0.000043627115,0.000019611243,0.0010576729],"study_design_scores_gemma":[0.000008947566,0.0006843811,0.01119553,0.0000067836195,0.000022761373,0.00013597641,0.00008835472,0.00086610427,0.9852003,0.00003104981,0.0017513048,0.000008504533],"about_ca_topic_score_codex":0.0008683938,"about_ca_topic_score_gemma":0.0019615272,"teacher_disagreement_score":0.0008683938,"about_ca_system_score_codex":0.0002487563,"about_ca_system_score_gemma":0.00012776857,"threshold_uncertainty_score":0.0028864741},"labels":[],"label_agreement":null},{"id":"W4388665772","doi":"10.1016/j.jmapro.2023.11.020","title":"Experimental and numerical investigation of cooling effectiveness of nano minimum quantity lubrication","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lubrication; Materials science; Nanofluid; Heat transfer coefficient; Heat transfer; Thermal conductivity; Coolant; Machining; Composite material; Base oil; Inconel; Surface roughness; Metallurgy; Nanoparticle; Mechanical engineering; Thermodynamics; Nanotechnology; Scanning electron microscope","score_opus":0.013880248421086991,"score_gpt":0.25718960407297226,"score_spread":0.24330935565188527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388665772","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955354,0.0001476436,0.0020861432,0.000038119604,0.000016503593,0.000010129078,0.00008232335,0.000044183136,0.0020395785],"genre_scores_gemma":[0.9987577,0.000026742886,0.00088806514,0.0000023048806,0.000002098838,0.0000045881848,0.000022301152,0.000006378362,0.00028983885],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998392,0.000021556243,0.000008450906,0.000025826967,0.00007429578,0.000030730476],"domain_scores_gemma":[0.9993204,0.00034457038,0.0000763382,0.00008384934,0.0001519725,0.000022861659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030328927,0.00015483334,0.000344257,0.0002869405,0.00045084904,0.0002744345,0.0004938947,0.00033700725,0.0026515736],"category_scores_gemma":[0.0011285406,0.00014315895,0.0001676852,0.00022012835,0.0005814246,0.00044992147,0.0001813147,0.00027168484,0.000119229866],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015402893,0.00029247333,0.0027142786,0.00028831454,0.000013987347,0.00010746161,0.00022205044,0.030381588,0.95170504,0.0029198504,0.00041664744,0.0093980795],"study_design_scores_gemma":[0.0001178826,0.00093766884,0.0061401287,0.000012928875,0.00002018827,0.000069001,0.000102451006,0.21302253,0.77801013,0.0002522051,0.0012925849,0.0000223261],"about_ca_topic_score_codex":0.0012999944,"about_ca_topic_score_gemma":0.0008507112,"teacher_disagreement_score":0.0026515736,"about_ca_system_score_codex":0.0002881852,"about_ca_system_score_gemma":0.0002463848,"threshold_uncertainty_score":0.008870363},"labels":[],"label_agreement":null},{"id":"W4388698762","doi":"10.1139/tcsme-2023-0066","title":"On modelling the cutting forces and impact resistance of honed milling tools","year":2023,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Enhanced Data Rates for GSM Evolution; RADIUS; Materials science; Cracking; Mechanical engineering; Structural engineering; Engineering; Composite material; Computer science","score_opus":0.014652295399513881,"score_gpt":0.22134816772282942,"score_spread":0.20669587232331554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388698762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5998117,0.0008169056,0.3852564,0.00010571448,0.00004846169,0.00023415465,0.00030040173,0.0006523519,0.012773899],"genre_scores_gemma":[0.9803491,0.00029500065,0.01662396,0.000010932781,0.0000045840557,0.00006273234,0.000074031675,0.000029941584,0.0025496418],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997074,0.000032557797,0.00002067578,0.000050348463,0.0001342198,0.00005480995],"domain_scores_gemma":[0.9994917,0.00027482334,0.00009281734,0.000040864972,0.0000810792,0.00001873917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000390753,0.00082541246,0.0005859338,0.0007768576,0.0002930997,0.0009627925,0.001170593,0.0017441531,0.0013283519],"category_scores_gemma":[0.0012869971,0.00043698977,0.0007783263,0.00053284626,0.0006177695,0.0006397701,0.00036028522,0.0005269382,0.00030794146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031728705,0.00004178008,0.00076433003,0.00005576091,0.000007980463,0.00012466783,0.000044881785,0.9840628,0.008690357,0.0005703446,0.000044211414,0.0055611236],"study_design_scores_gemma":[0.0000023592665,0.000028699791,0.00030499836,0.0000037000414,0.0000028622012,0.000018634693,0.0000056867034,0.99817,0.0012427247,0.00007623462,0.000139568,0.000004463757],"about_ca_topic_score_codex":0.011522457,"about_ca_topic_score_gemma":0.0067273625,"teacher_disagreement_score":0.011522457,"about_ca_system_score_codex":0.0005136563,"about_ca_system_score_gemma":0.0006375378,"threshold_uncertainty_score":0.022910833},"labels":[],"label_agreement":null},{"id":"W4389396074","doi":"10.1007/s00170-023-12692-4","title":"Intelligent characterization of spark-assisted chemical engraving (SACE) process using time series classification","year":2023,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Engraving; Characterization (materials science); SPARK (programming language); Process (computing); Series (stratigraphy); Industrial and production engineering; Engineering; Materials science; Computer science; Process engineering; Nanotechnology; Mechanical engineering; Geology; Operating system","score_opus":0.013554493209411933,"score_gpt":0.2643534695208184,"score_spread":0.25079897631140646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389396074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7770266,0.0004942909,0.218667,0.00010790186,0.00006784899,0.000040876497,0.0001963665,0.00078544725,0.002613668],"genre_scores_gemma":[0.9823799,0.00010228897,0.016604455,0.000010671703,0.000010178214,0.00001143692,0.0001373641,0.000016677797,0.0007268851],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997495,0.000018560324,0.000018927225,0.000056277157,0.00013085056,0.000025843028],"domain_scores_gemma":[0.99970144,0.000086496635,0.00007199857,0.000025721089,0.00009960288,0.000014705233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031590095,0.0003621296,0.0004457945,0.00092523894,0.00020620647,0.0005269847,0.00033764547,0.00034436054,0.00047710878],"category_scores_gemma":[0.00048224351,0.00012207328,0.00039789887,0.00063533295,0.00020235911,0.00045456673,0.00014658872,0.00028030635,0.00012245942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001067088,0.00050121575,0.023055047,0.0002846778,0.0001318296,0.00038417784,0.00017379683,0.2059441,0.34377998,0.002289879,0.001446676,0.42094153],"study_design_scores_gemma":[0.0000051343304,0.00012042928,0.01149654,0.0000027931328,0.000019989291,0.000069414076,0.000027986214,0.94527304,0.042195003,0.00031139803,0.00046341022,0.000014885441],"about_ca_topic_score_codex":0.0016550645,"about_ca_topic_score_gemma":0.0018775353,"teacher_disagreement_score":0.0016550645,"about_ca_system_score_codex":0.00025935675,"about_ca_system_score_gemma":0.00029392858,"threshold_uncertainty_score":0.003290832},"labels":[],"label_agreement":null},{"id":"W4389540755","doi":"10.17118/11143/21075","title":"Recursive identification of force model parameters in milling carbonfibre-reinforced polymers","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Polymer; Identification (biology); Materials science; Carbon fibers; Composite material; Biological system; Computer science; Composite number","score_opus":0.011580927879140366,"score_gpt":0.23494941662535307,"score_spread":0.2233684887462127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389540755","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24670042,0.00014538315,0.751605,0.00006237027,0.000016015369,0.00002495431,0.000033175627,0.00051017967,0.00090263784],"genre_scores_gemma":[0.9804883,0.000042374577,0.018823246,0.000007745976,0.0000024168185,0.00002146174,0.000030505436,0.000016946606,0.0005670527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998523,0.000025440668,0.000007017238,0.000038988732,0.000057985882,0.00001829433],"domain_scores_gemma":[0.9997193,0.00013884716,0.00005287044,0.000024778788,0.00005756501,0.0000065110153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031421948,0.00037237332,0.00030960765,0.00019449965,0.00016611068,0.0002680051,0.00031007998,0.00041120357,0.00045058478],"category_scores_gemma":[0.0008848365,0.000296492,0.0002578714,0.00012416106,0.00026636638,0.0004309242,0.00018695949,0.00040075544,0.00014646132],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010745162,0.00006458941,0.0024501516,0.00010746187,0.00003814575,0.000087695786,0.000120163044,0.86681885,0.06571294,0.001088815,0.00023042531,0.063173294],"study_design_scores_gemma":[0.000003498362,0.000023760113,0.0010914315,0.000002106002,0.000003900227,0.000011932554,0.00000432098,0.9922422,0.006399295,0.00012838679,0.000084223815,0.000005005985],"about_ca_topic_score_codex":0.0067479233,"about_ca_topic_score_gemma":0.008128757,"teacher_disagreement_score":0.0067479233,"about_ca_system_score_codex":0.00031070973,"about_ca_system_score_gemma":0.0004186416,"threshold_uncertainty_score":0.013417304},"labels":[],"label_agreement":null},{"id":"W4389540765","doi":"10.17118/11143/21151","title":"Assessment of Hashin’s failure criteria in finite element modelling oforthogonal cutting of fiber-reinforced composites","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Finite element method; Composite material; Materials science; Fiber-reinforced composite; Fiber; Structural engineering; Engineering","score_opus":0.0155626920343445,"score_gpt":0.2773994936986455,"score_spread":0.261836801664301,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389540765","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78477687,0.00019656323,0.21184301,0.000058754413,0.000021133343,0.00008214559,0.000052516247,0.00016449994,0.0028043909],"genre_scores_gemma":[0.98396075,0.000042880336,0.015522218,0.000005659948,0.0000017836587,0.000032155913,0.00002868832,0.000015854726,0.00038998912],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996119,0.00012534915,0.000031650063,0.000039512095,0.00014295022,0.00004854762],"domain_scores_gemma":[0.9985825,0.0008758893,0.00017146317,0.00008671929,0.0002427408,0.000040754665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013804428,0.00070506183,0.00056832476,0.0009832039,0.00036536946,0.00058133487,0.0006490883,0.0013476529,0.00076727517],"category_scores_gemma":[0.0024704905,0.00031802958,0.0005510051,0.00027222885,0.00075091125,0.00048322428,0.00051826565,0.00046048185,0.00013811086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007848469,0.000076018194,0.0049244007,0.00006868897,0.000012822384,0.00010514268,0.0001480685,0.9759563,0.011632253,0.0012278951,0.000060248192,0.0057096737],"study_design_scores_gemma":[0.0000017963052,0.000029297966,0.00043457656,0.0000056823137,0.000002173318,0.000011799735,0.000014256291,0.99722457,0.002131877,0.00007694519,0.000063149346,0.000003926194],"about_ca_topic_score_codex":0.0047958586,"about_ca_topic_score_gemma":0.0023656501,"teacher_disagreement_score":0.0047958586,"about_ca_system_score_codex":0.00045727866,"about_ca_system_score_gemma":0.0006365151,"threshold_uncertainty_score":0.009535849},"labels":[],"label_agreement":null},{"id":"W4389540767","doi":"10.17118/11143/21093","title":"Prediction of diameter error in one-setup machining test by using machinelearning algorithms","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Machining; Computer science; Algorithm; Test (biology); Machine learning; Artificial intelligence; Engineering; Mechanical engineering","score_opus":0.03838589997769701,"score_gpt":0.2605541755865784,"score_spread":0.2221682756088814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389540767","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8973235,0.00033601123,0.09940752,0.000055985158,0.00007614743,0.000107503336,0.00025996377,0.0015665835,0.0008667773],"genre_scores_gemma":[0.9757169,0.000035255103,0.023164725,0.000019443705,0.0000061115966,0.00006960257,0.00034038164,0.000044398555,0.0006031892],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884015,0.00017407241,0.00008919589,0.00031970712,0.00045924602,0.00011769593],"domain_scores_gemma":[0.9953744,0.0025905238,0.00066747697,0.00048325985,0.0007349547,0.00014942822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014754997,0.0010981738,0.0007700939,0.00073041907,0.0002590651,0.00056470296,0.0008868568,0.001167643,0.0015876105],"category_scores_gemma":[0.0038652024,0.00030055703,0.0008024158,0.0005634438,0.00047078938,0.0005397116,0.0004570845,0.00077138474,0.00045226046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029041802,0.001719137,0.042363808,0.0006451109,0.00021827607,0.00030606825,0.00014977342,0.615502,0.1567719,0.00037216494,0.001272892,0.17777473],"study_design_scores_gemma":[0.00004744348,0.0015774088,0.03519462,0.000015121001,0.00003286608,0.00007012707,0.000035107354,0.8695837,0.09294127,0.00013144489,0.00032200426,0.00004891543],"about_ca_topic_score_codex":0.00207027,"about_ca_topic_score_gemma":0.0021563924,"teacher_disagreement_score":0.00207027,"about_ca_system_score_codex":0.0006523255,"about_ca_system_score_gemma":0.0004812475,"threshold_uncertainty_score":0.0078032613},"labels":[],"label_agreement":null},{"id":"W4390043994","doi":"10.1109/jsen.2023.3343399","title":"Improved 2-D Multiscale Fractional Dispersion Entropy: A Novel Health Condition Indicator for Fault Diagnosis of Rolling Bearings","year":2023,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Wuhan University of Science and Technology; Natural Science Foundation of Hubei Province; National Natural Science Foundation of China","keywords":"Dispersion (optics); Condition monitoring; Fault (geology); Entropy (arrow of time); Statistical physics; Physics; Computer science; Materials science; Engineering; Electrical engineering; Thermodynamics; Geology; Optics; Seismology","score_opus":0.014634693367679717,"score_gpt":0.2805038084612527,"score_spread":0.265869115093573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390043994","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27209386,0.002577308,0.71977496,0.0004931906,0.00021892882,0.00008148172,0.00055121694,0.000755141,0.003453957],"genre_scores_gemma":[0.9603557,0.0006122304,0.03743468,0.000078117606,0.0001084296,0.00003823099,0.00034941972,0.000022323089,0.001000972],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997503,0.000032652322,0.000022356893,0.00005414862,0.00011240075,0.000028068742],"domain_scores_gemma":[0.99968517,0.00010194127,0.000062068175,0.000024002942,0.000100044796,0.000026716814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038918343,0.0006689949,0.0006024882,0.0016385589,0.00022080544,0.00055693014,0.00038368607,0.00044474693,0.0006770823],"category_scores_gemma":[0.0013956997,0.00015229173,0.0003975601,0.00070441945,0.00033055083,0.00091814727,0.0005728673,0.00035547267,0.00015355214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008384532,0.0002555904,0.037687574,0.00048876373,0.00023995867,0.0007865932,0.0003271646,0.23449476,0.09828788,0.0075064367,0.0064607356,0.6126261],"study_design_scores_gemma":[0.000017125296,0.00011989484,0.01238719,0.000024866313,0.00006089677,0.0003753724,0.00004943465,0.97117716,0.01230588,0.0020154454,0.0014192065,0.0000474369],"about_ca_topic_score_codex":0.0013154035,"about_ca_topic_score_gemma":0.0012652894,"teacher_disagreement_score":0.0016385589,"about_ca_system_score_codex":0.00028729747,"about_ca_system_score_gemma":0.00028844358,"threshold_uncertainty_score":0.0026155114},"labels":[],"label_agreement":null},{"id":"W4390427307","doi":"10.1016/j.jmapro.2023.12.029","title":"Tool wear prediction in edge trimming of MD CFRP considering interlaminar effect","year":2023,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Xi’an Jiaotong University; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Trimming; Materials science; Enhanced Data Rates for GSM Evolution; Composite material; Surface roughness; Layer (electronics); Surface finish; Structural engineering; Mechanical engineering; Computer science; Artificial intelligence","score_opus":0.008427865267335227,"score_gpt":0.22982791225817129,"score_spread":0.22140004699083607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390427307","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96249974,0.00032255304,0.034594934,0.000026239974,0.000017971392,0.000013065192,0.000071643226,0.00021819079,0.0022357379],"genre_scores_gemma":[0.9981749,0.000025377602,0.0014587961,0.0000025932072,0.0000012391247,0.0000019716663,0.000016974658,0.000006233632,0.00031199222],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987984,0.000012411069,0.0000035505004,0.000029154377,0.000044855213,0.000030132636],"domain_scores_gemma":[0.9994678,0.00026742343,0.000055002314,0.00005492751,0.00013457556,0.000020244932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026258384,0.00036357326,0.00040754513,0.00037963074,0.00027098172,0.0003636868,0.00054639624,0.0006984976,0.00089965854],"category_scores_gemma":[0.0006823666,0.00018270129,0.00039226512,0.00028374078,0.00016209588,0.00031907368,0.0001748255,0.00025071113,0.00011055803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007854862,0.00015746983,0.010181858,0.00023716925,0.000041516883,0.00047027407,0.00012126123,0.86884034,0.058133822,0.00044715998,0.0005338816,0.06004984],"study_design_scores_gemma":[0.0000031910226,0.000094442934,0.004337046,0.0000043454597,0.000009732612,0.000027377648,0.000017997318,0.99001324,0.005368402,0.000049688588,0.00006812838,0.00000642699],"about_ca_topic_score_codex":0.0065261307,"about_ca_topic_score_gemma":0.0055539683,"teacher_disagreement_score":0.0065261307,"about_ca_system_score_codex":0.00025682762,"about_ca_system_score_gemma":0.00028479667,"threshold_uncertainty_score":0.012976289},"labels":[],"label_agreement":null},{"id":"W4390519277","doi":"10.20944/preprints202312.2220.v1","title":"Solid Lubricants Used at Extreme Conditions Experienced in Machining: A Comprehensive Review of Recent Developments and Applications","year":2023,"lang":"en","type":"review","venue":"Preprints.org","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Lubricant; Sustainability; Productivity; Mechanical engineering; Materials science; Environmental science; Engineering; Ecology","score_opus":0.2786893186717349,"score_gpt":0.44109820493847807,"score_spread":0.16240888626674316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390519277","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032043384,0.9983942,0.00023002525,0.000092596485,0.00007559827,0.000007229473,0.000031614556,0.000009914623,0.0008383669],"genre_scores_gemma":[0.0018200874,0.99712986,0.00034672816,0.000067883586,0.000066580884,0.000007693593,0.00004954278,0.0000038302633,0.0005077985],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99964845,0.000044780598,0.00006500804,0.00007195144,0.00013691263,0.00003286288],"domain_scores_gemma":[0.99930465,0.0003610087,0.000102543636,0.000021319358,0.00017830897,0.00003215963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084308087,0.00087893853,0.0012589331,0.003382513,0.00034433283,0.0011772695,0.00082253217,0.00089253904,0.00334237],"category_scores_gemma":[0.0013016224,0.00045219145,0.0008417006,0.0031889887,0.00037852296,0.0014693211,0.0006131802,0.0009008157,0.0013649396],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011308534,0.00009528491,0.00046451195,0.055571843,0.00017935522,0.0001839257,0.00012254617,0.00090304186,0.0044909245,0.00418988,0.012925224,0.92076033],"study_design_scores_gemma":[0.000014165455,0.00023763462,0.0013615413,0.0065434724,0.0003383298,0.00095657277,0.00011637554,0.00028614092,0.002824415,0.0014133042,0.9858635,0.00004463954],"about_ca_topic_score_codex":0.0016027014,"about_ca_topic_score_gemma":0.0021024742,"teacher_disagreement_score":0.003382513,"about_ca_system_score_codex":0.0005140329,"about_ca_system_score_gemma":0.0012251788,"threshold_uncertainty_score":0.011181295},"labels":[],"label_agreement":null},{"id":"W4390846800","doi":"10.1504/ijmmm.2023.136037","title":"Numerical study on the impacts of tool edge geometry and cutting conditions in orthogonal machining of AISI 1045 steel","year":2023,"lang":"en","type":"article","venue":"International Journal of Machining and Machinability of Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Enhanced Data Rates for GSM Evolution; Geometry; Mechanical engineering; Engineering drawing; Structural engineering; Materials science; Engineering; Mathematics","score_opus":0.013534341823745494,"score_gpt":0.3003545024612684,"score_spread":0.2868201606375229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390846800","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9873175,0.00010381027,0.010861315,0.00003077453,0.000012884348,0.00001695579,0.00006082894,0.000050950857,0.0015450842],"genre_scores_gemma":[0.9962514,0.000041030158,0.0034526123,0.000003633776,0.0000013847401,0.0000073888214,0.000027144353,0.0000052127,0.00021020317],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998276,0.000034356945,0.000012086974,0.000024160867,0.00006365905,0.00003809301],"domain_scores_gemma":[0.99916613,0.00051599846,0.00013520493,0.000053399956,0.00010255064,0.000026795851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000372994,0.0002776855,0.0003005152,0.00033009294,0.0002900693,0.0003408091,0.00027754682,0.0005121439,0.0007396346],"category_scores_gemma":[0.0014813275,0.00019343731,0.00032140405,0.00028335795,0.00038065543,0.00026532868,0.00016905865,0.00016134199,0.00006781059],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036593116,0.00017011164,0.014526664,0.00028552854,0.0000368343,0.0003891292,0.00025580023,0.87455827,0.091963395,0.00090677856,0.00025777108,0.016283767],"study_design_scores_gemma":[0.000025733085,0.00036151402,0.00801129,0.000009491053,0.000024028823,0.00008085125,0.00013327462,0.9768768,0.013895846,0.00017496278,0.00038581283,0.00002039323],"about_ca_topic_score_codex":0.0037157994,"about_ca_topic_score_gemma":0.0038591323,"teacher_disagreement_score":0.0037157994,"about_ca_system_score_codex":0.00029303657,"about_ca_system_score_gemma":0.00036305873,"threshold_uncertainty_score":0.0073883533},"labels":[],"label_agreement":null},{"id":"W4391328039","doi":"10.20944/preprints202401.1951.v1","title":"High-Performance Machining System: Process Optimization for a Cyber-Physical System – a Review","year":2024,"lang":"en","type":"review","venue":"Preprints.org","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs; McGill University","keywords":"Cyber-physical system; Process (computing); Machining; System optimization; Computer science; Manufacturing engineering; Mechanical engineering; Engineering; Operating system; Mathematical optimization; Mathematics","score_opus":0.06732365326799228,"score_gpt":0.3605970304016801,"score_spread":0.29327337713368784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391328039","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020039578,0.99546295,0.002346576,0.00022487505,0.0001940342,0.000006841549,0.000016784004,0.000015212724,0.001532329],"genre_scores_gemma":[0.0029566085,0.9945262,0.0013283935,0.00013046668,0.00034115653,0.0000127904605,0.000040417308,0.000008525957,0.0006554795],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996797,0.000052655698,0.000038728027,0.00007398761,0.00013306852,0.000021828084],"domain_scores_gemma":[0.9990884,0.0005409827,0.000088125846,0.000037031296,0.00021204642,0.000033494696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005923694,0.0012569681,0.0015371171,0.0017605225,0.00029969346,0.0012927966,0.0009358012,0.0014950858,0.0029914065],"category_scores_gemma":[0.0012913395,0.0005169375,0.0006776565,0.0031735576,0.0005793204,0.0020243332,0.0005997342,0.0013915481,0.0017206135],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048795057,0.00010394196,0.00034799453,0.025276188,0.000163538,0.00014027194,0.00008843424,0.007758619,0.0016053626,0.02780223,0.023201592,0.91346294],"study_design_scores_gemma":[0.000010559109,0.00015313,0.0011193634,0.0056662536,0.00016758128,0.00061442493,0.00008634395,0.002959203,0.0008735837,0.011828936,0.9764683,0.00005231245],"about_ca_topic_score_codex":0.0014789525,"about_ca_topic_score_gemma":0.0011586397,"teacher_disagreement_score":0.0029914065,"about_ca_system_score_codex":0.0005395187,"about_ca_system_score_gemma":0.0013792791,"threshold_uncertainty_score":0.010007262},"labels":[],"label_agreement":null},{"id":"W4391387501","doi":"10.1504/ijat.2023.136325","title":"Investigation on workpiece microstructure and wheel performance on grinding titanium metal matrix composites","year":2023,"lang":"en","type":"article","venue":"International Journal of Abrasive Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Polytechnique Montréal","funders":"","keywords":"Materials science; Microstructure; Composite material; Grinding; Matrix (chemical analysis); Grinding wheel; Metal matrix composite; Titanium; Metal; Titanium alloy; Metallurgy; Alloy","score_opus":0.009338979965212185,"score_gpt":0.24786356162407416,"score_spread":0.23852458165886198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391387501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99741226,0.00030389035,0.0018685664,0.0000050818285,0.000004513802,0.0000078789935,0.000041667157,0.00003172362,0.0003243793],"genre_scores_gemma":[0.9957147,0.00014904627,0.0033406694,0.000005445105,0.0000025030038,0.0000057609154,0.00007365102,0.000018099703,0.000689958],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99972695,0.000019179874,0.00000958293,0.000054012024,0.00015111497,0.000039183178],"domain_scores_gemma":[0.9993906,0.00019141953,0.00011035111,0.00006662888,0.0002090327,0.000031980107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037262987,0.00025795132,0.00029269033,0.00028826436,0.00024186958,0.0001796158,0.00020719308,0.00023720632,0.00096556917],"category_scores_gemma":[0.00058990304,0.00017642674,0.00021224932,0.0001893222,0.00018568481,0.00014734126,0.00009567832,0.00019219892,0.00018387678],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004553564,0.0000112010075,0.00055459165,0.000031277537,0.0000025608654,0.000025406933,0.000033888075,0.00019524297,0.99734735,0.000008931328,0.00000829192,0.0017356875],"study_design_scores_gemma":[0.000005025963,0.0007837147,0.032520648,0.000004273456,0.000016793025,0.00014317276,0.00006223724,0.0016864483,0.9641774,0.0000131026645,0.00057786173,0.000009242715],"about_ca_topic_score_codex":0.0018089801,"about_ca_topic_score_gemma":0.00511503,"teacher_disagreement_score":0.0018089801,"about_ca_system_score_codex":0.00026480807,"about_ca_system_score_gemma":0.00014282626,"threshold_uncertainty_score":0.0035969615},"labels":[],"label_agreement":null},{"id":"W4391435507","doi":"10.1016/j.cirpj.2024.01.005","title":"Digital twin assisted intelligent machining process monitoring and control","year":2024,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Pratt and Whitney Canada","keywords":"Machining; Process (computing); Engineering; Sensor fusion; Tool wear; Accelerometer; Transient (computer programming); Control engineering; Real-time computing; Computer science; Mechanical engineering; Artificial intelligence","score_opus":0.006733099673252616,"score_gpt":0.24868670503874848,"score_spread":0.24195360536549587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391435507","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09901215,0.00031507525,0.8838279,0.00013615261,0.0003010918,0.00012469877,0.00023341566,0.0039400877,0.012109364],"genre_scores_gemma":[0.85328305,0.00011955433,0.13422002,0.000109494234,0.000057224617,0.000086537715,0.00023371022,0.000119952805,0.011770375],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994074,0.000055216406,0.000025643705,0.00012435523,0.00034054962,0.000046954246],"domain_scores_gemma":[0.9995776,0.00008246793,0.000053639982,0.00010602562,0.00015389387,0.000026340016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032220327,0.00039979257,0.00043161976,0.0007360374,0.00032232646,0.0007850702,0.00076695974,0.0004122961,0.0037187538],"category_scores_gemma":[0.00069453375,0.00023823373,0.00021227056,0.0005896796,0.0002654233,0.0006853042,0.0008737444,0.0003676106,0.0006014666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015426226,0.00017944285,0.0030736714,0.00022185595,0.000058074842,0.00012232494,0.0001996874,0.020075466,0.3071412,0.0049395235,0.0061649787,0.65628123],"study_design_scores_gemma":[0.00008887559,0.0005049224,0.008386823,0.000017773964,0.00008917027,0.0004249287,0.00006920238,0.8032627,0.16481352,0.0022046883,0.02007249,0.00006487646],"about_ca_topic_score_codex":0.0010974403,"about_ca_topic_score_gemma":0.0022357863,"teacher_disagreement_score":0.0037187538,"about_ca_system_score_codex":0.00036421086,"about_ca_system_score_gemma":0.0005151044,"threshold_uncertainty_score":0.012440503},"labels":[],"label_agreement":null},{"id":"W4391595248","doi":"10.1007/s00170-024-12968-3","title":"Influence of machining parameters on dynamic errors in a hexapod machining cell","year":2024,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Machining; Hexapod; Taguchi methods; Vibration; Computer science; Machine tool; Mechanical engineering; Engineering; Robot; Acoustics; Artificial intelligence; Physics; Machine learning","score_opus":0.0040271973986561954,"score_gpt":0.2420627072276543,"score_spread":0.2380355098289981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391595248","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922576,0.00014124789,0.006333482,0.000028319897,0.000013566399,0.000004766616,0.00002524776,0.000052856936,0.0011428734],"genre_scores_gemma":[0.99907184,0.000016617229,0.0006560835,0.000002385982,6.600167e-7,0.0000010280966,0.000008558852,0.000006532359,0.00023617609],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998215,0.00002779959,0.000011892237,0.00004517684,0.0000659474,0.00002776324],"domain_scores_gemma":[0.99839264,0.0010993561,0.0001472447,0.00010689207,0.00021352893,0.00004029779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025592445,0.00022624964,0.00031684837,0.0002345465,0.0003500953,0.00059898524,0.00029319865,0.00046042833,0.0012248678],"category_scores_gemma":[0.0015203411,0.00016207749,0.00010921847,0.00031990887,0.00038845753,0.00034683789,0.00025193774,0.00023065005,0.00011869966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024734507,0.00017684743,0.0076829507,0.0001615524,0.00004626811,0.0006600323,0.00029162568,0.625739,0.3191712,0.0012714687,0.00028107472,0.042044535],"study_design_scores_gemma":[0.000036721838,0.0006935971,0.012176183,0.000013808117,0.00004154076,0.00018712829,0.00020411407,0.78504926,0.2004648,0.00039023356,0.00069163594,0.000050911756],"about_ca_topic_score_codex":0.0020422263,"about_ca_topic_score_gemma":0.0022165384,"teacher_disagreement_score":0.0020422263,"about_ca_system_score_codex":0.0003422732,"about_ca_system_score_gemma":0.00025625114,"threshold_uncertainty_score":0.0040976405},"labels":[],"label_agreement":null},{"id":"W4391612226","doi":"10.1016/j.triboint.2024.109388","title":"The prediction of 3D surface topography in a high-speed micro-milling process with aerostatic spindle","year":2024,"lang":"en","type":"article","venue":"Tribology International","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Fundamental Research Funds for the Central Universities; Aeronautical Science Foundation of China; National Natural Science Foundation of China","keywords":"Surface roughness; Machining; Vibration; Process (computing); Machine tool; Rotor (electric); Mechanical engineering; Surface (topology); Coupling (piping); Surface finish; Materials science; Engineering; Structural engineering; Mechanics; Acoustics; Geometry; Computer science; Composite material; Physics","score_opus":0.0057536940830993435,"score_gpt":0.23666533441269297,"score_spread":0.23091164032959363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391612226","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9702021,0.000086911125,0.028621906,0.000043847645,0.000011678068,0.000014607905,0.000056505087,0.00017412363,0.0007882911],"genre_scores_gemma":[0.99708265,0.000028816077,0.0026624936,0.000002340563,0.0000012659825,0.0000031092616,0.00002107387,0.0000057874104,0.00019242743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999423,0.0000071011905,0.0000025160055,0.00001170507,0.000028015238,0.000008422377],"domain_scores_gemma":[0.99976355,0.00013400453,0.000022413122,0.000017787821,0.000048342445,0.000013858904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011203713,0.00030828515,0.00020358646,0.00020914814,0.00022164114,0.0003602612,0.00021298969,0.000574209,0.00049731205],"category_scores_gemma":[0.00043904452,0.00027593708,0.00029281536,0.00019920914,0.00019743804,0.00028489798,0.0001532064,0.0002630045,0.00008919858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039233203,0.00011867987,0.017885149,0.00008633206,0.000037675996,0.00037798556,0.00014065989,0.8102572,0.13571729,0.00045952504,0.00040450232,0.034122676],"study_design_scores_gemma":[0.0000050760864,0.000055326316,0.0044498215,8.7623926e-7,0.000003342856,0.000022462282,0.000013821425,0.98766136,0.007691469,0.00004471962,0.00004685879,0.0000047886756],"about_ca_topic_score_codex":0.008204113,"about_ca_topic_score_gemma":0.007916799,"teacher_disagreement_score":0.008204113,"about_ca_system_score_codex":0.00025965043,"about_ca_system_score_gemma":0.00034034564,"threshold_uncertainty_score":0.016312718},"labels":[],"label_agreement":null},{"id":"W4391645768","doi":"10.2139/ssrn.4720844","title":"Deep Learning-Based Topology Optimization for Multi-Axis Machining","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Machining; Topology optimization; Topology (electrical circuits); Computer science; Artificial intelligence; Geometry; Mechanical engineering; Mathematics; Engineering; Structural engineering; Combinatorics; Finite element method","score_opus":0.010289189883284975,"score_gpt":0.2704792323780536,"score_spread":0.2601900424947686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391645768","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027286444,0.00043794,0.96720314,0.00017545378,0.000058246173,0.000034821995,0.00012600781,0.00082123856,0.0038566112],"genre_scores_gemma":[0.6717067,0.00038006928,0.3193336,0.00012916575,0.00006410226,0.00012457174,0.00048141115,0.00041900948,0.007361399],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998037,0.000045519806,0.000008830031,0.000047876078,0.00006827678,0.00002576853],"domain_scores_gemma":[0.9994537,0.00027042514,0.000056249348,0.00007344615,0.00011191246,0.000034345077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005079778,0.0008200927,0.0010455094,0.0005874475,0.0003611317,0.0008169027,0.0010291203,0.0011999462,0.0032507062],"category_scores_gemma":[0.0013475342,0.0006926919,0.00067563006,0.00066489895,0.00058939867,0.0010397299,0.00097516045,0.001462456,0.0005520149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004978848,0.000026753187,0.00022242218,0.000042048952,0.000016943375,0.00001665874,0.000013167871,0.94821715,0.0021376512,0.0031172528,0.00080307416,0.045337047],"study_design_scores_gemma":[0.0000020869638,0.000007855341,0.000030389841,0.0000017545227,0.0000011634639,0.0000037821578,0.000001362694,0.9980178,0.00030131688,0.001454509,0.00017686328,0.0000012280427],"about_ca_topic_score_codex":0.0032990372,"about_ca_topic_score_gemma":0.0050279154,"teacher_disagreement_score":0.0032990372,"about_ca_system_score_codex":0.00079996046,"about_ca_system_score_gemma":0.0009390456,"threshold_uncertainty_score":0.010874748},"labels":[],"label_agreement":null},{"id":"W4391660686","doi":"10.1016/j.nxmate.2024.100121","title":"Impact of short-time annealing on AISI 8670 tool steel saw during industrial brazing process","year":2024,"lang":"en","type":"article","venue":"Next Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"DK-SPEC (Canada); École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; École de technologie supérieure","keywords":"Brazing; Metallurgy; Materials science; Annealing (glass); Process (computing); Computer science; Operating system; Alloy","score_opus":0.02097612424348802,"score_gpt":0.289163805310797,"score_spread":0.26818768106730895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391660686","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99742633,0.0007586021,0.001057837,0.000019995643,0.000027637048,0.000008787488,0.0000673131,0.000052031064,0.0005813942],"genre_scores_gemma":[0.9985037,0.00017515593,0.0008119669,0.0000110893525,0.0000059667136,0.000005100569,0.000051103776,0.00002271892,0.00041332564],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997019,0.00003194084,0.000018917772,0.00007620786,0.00011927893,0.000051635343],"domain_scores_gemma":[0.9995085,0.00017282707,0.00011111151,0.00005272647,0.00012615175,0.00002860451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002734835,0.0002202936,0.0003493307,0.00017817087,0.00022659678,0.0003327892,0.0001713005,0.00035446676,0.0015824573],"category_scores_gemma":[0.0005887493,0.00019247437,0.00026484393,0.00018487674,0.00021550432,0.00024736184,0.00012005644,0.00032477875,0.00024437398],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004887901,0.000043664215,0.0026098231,0.00019570436,0.000023808132,0.000109367735,0.00014040686,0.0011079543,0.98852193,0.000056138935,0.00009741116,0.0066050286],"study_design_scores_gemma":[0.00001320396,0.0022544917,0.05869991,0.000015241749,0.00008925242,0.00014568314,0.0002899082,0.002695253,0.93397856,0.000053766093,0.0017426945,0.000021908883],"about_ca_topic_score_codex":0.0006899672,"about_ca_topic_score_gemma":0.0028924348,"teacher_disagreement_score":0.0015824573,"about_ca_system_score_codex":0.00021445545,"about_ca_system_score_gemma":0.00015425876,"threshold_uncertainty_score":0.0052937865},"labels":[],"label_agreement":null},{"id":"W4391669492","doi":"10.1016/j.cirpj.2024.01.009","title":"A unified FFT-based mechanistic force coefficient identification model for isotropic and anisotropic materials","year":2024,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Pratt and Whitney Canada","keywords":"Machining; Rake; Isotropy; Rake angle; Mechanical engineering; Kinematics; Drilling; Materials science; Deflection (physics); Tool wear; Structural engineering; Engineering; Physics; Classical mechanics","score_opus":0.008545647024143906,"score_gpt":0.23971604082384557,"score_spread":0.23117039379970167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391669492","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00608495,0.00015280342,0.9863644,0.000078396224,0.00003593491,0.00003410471,0.00017103186,0.00035829569,0.0067200433],"genre_scores_gemma":[0.73060304,0.0009907646,0.24035934,0.00019452498,0.00009325938,0.00039675567,0.0009708235,0.0003905673,0.02600089],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986494,0.000016466496,0.000007694688,0.0000273069,0.00006790697,0.000015544767],"domain_scores_gemma":[0.99980503,0.000059173406,0.000023838458,0.000028071405,0.00007284384,0.000011119425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003001544,0.0005765304,0.00074437156,0.000562348,0.0003686942,0.00058485137,0.00138673,0.0011921925,0.005355434],"category_scores_gemma":[0.0007325889,0.00033434236,0.0007319152,0.000556486,0.00036150077,0.0013045415,0.0005900169,0.00071892876,0.0014233461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002890695,0.00004492019,0.0002914238,0.00007465213,0.00001926121,0.000089722096,0.000038381408,0.94225276,0.0074155554,0.014362321,0.0009658157,0.03441632],"study_design_scores_gemma":[0.0000014188827,0.0000044262033,0.00005571771,0.000003055754,0.0000020818072,0.000011782717,0.0000024134536,0.99808717,0.00030239462,0.0010211574,0.00050553534,0.0000028716556],"about_ca_topic_score_codex":0.0072910096,"about_ca_topic_score_gemma":0.00683524,"teacher_disagreement_score":0.0072910096,"about_ca_system_score_codex":0.00041890287,"about_ca_system_score_gemma":0.0008698335,"threshold_uncertainty_score":0.017915785},"labels":[],"label_agreement":null},{"id":"W4391914373","doi":"10.1007/s00170-024-13237-z","title":"A review on machining Ti–5Al–5V–5Mo–3Cr alloy using defined geometry tools","year":2024,"lang":"en","type":"review","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Alloy; Machining; Geometry; Materials science; Titanium alloy; Metallurgy; Engineering drawing; Mechanical engineering; Engineering; Mathematics","score_opus":0.033877901584061065,"score_gpt":0.3335529485666268,"score_spread":0.29967504698256575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391914373","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018097603,0.9986559,0.0002783159,0.00006156513,0.00018162752,0.000006915675,0.000024237197,0.0000068017857,0.0006036206],"genre_scores_gemma":[0.00073529675,0.9977108,0.0006208864,0.00010484865,0.00011285517,0.000008532028,0.00005660812,0.0000036834533,0.0006463892],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99970883,0.000035057983,0.000053969954,0.000060271315,0.000119956225,0.00002186585],"domain_scores_gemma":[0.9996184,0.00019016658,0.00007275319,0.000012251333,0.000091919355,0.000014447388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059337466,0.0010584021,0.0014538433,0.0026444423,0.00022427582,0.0008295595,0.0012146108,0.00092183176,0.0033899865],"category_scores_gemma":[0.00084945647,0.00055915717,0.00088430673,0.0024933964,0.00029154847,0.0012868599,0.00046950497,0.0009577702,0.0015750877],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010980395,0.00008597079,0.00017773938,0.07208825,0.00033574962,0.00016307327,0.000043323755,0.0008024505,0.007116131,0.0027659591,0.021148512,0.895163],"study_design_scores_gemma":[0.000030596857,0.00024107963,0.00090545893,0.005732263,0.0004146462,0.00083004445,0.0000414374,0.00020408462,0.0028721867,0.0009759271,0.98771185,0.000040410392],"about_ca_topic_score_codex":0.0011312842,"about_ca_topic_score_gemma":0.0023265856,"teacher_disagreement_score":0.0033899865,"about_ca_system_score_codex":0.00034913726,"about_ca_system_score_gemma":0.001035691,"threshold_uncertainty_score":0.011340618},"labels":[],"label_agreement":null},{"id":"W4391927647","doi":"10.1007/s00170-024-13201-x","title":"An integrated framework for a multi-material surface roughness prediction model in CNC turning using theoretical and machine learning methods","year":2024,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Surface roughness; Industrial and production engineering; Surface (topology); Mechanical engineering; Engineering; Numerical control; Computer science; Manufacturing engineering; Engineering drawing; Control engineering; Artificial intelligence; Machining; Materials science; Mathematics; Geometry; Composite material","score_opus":0.016590789948594066,"score_gpt":0.33268071885357803,"score_spread":0.31608992890498394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391927647","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01081441,0.00021821116,0.9867446,0.0000988963,0.000036602873,0.000027798742,0.00003926091,0.00023094336,0.0017892903],"genre_scores_gemma":[0.8393336,0.0004491448,0.15454836,0.00010112068,0.00009597435,0.00028863165,0.00023071007,0.00015228252,0.004800214],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973553,0.00005564238,0.000014092108,0.000058258014,0.000093707626,0.000042799413],"domain_scores_gemma":[0.99965405,0.00013566487,0.000031171392,0.000021852602,0.00013780115,0.00001950641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074586336,0.00058545877,0.0010526744,0.000668229,0.0005337605,0.0010147623,0.0017645437,0.0014162867,0.0016150653],"category_scores_gemma":[0.0010158182,0.00044137303,0.0009613691,0.00052206777,0.0006016478,0.0008847475,0.00079283933,0.0010515051,0.00034106622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000084923195,0.000022424418,0.0001464166,0.000020709847,0.00001222072,0.0000246343,0.000011546657,0.9858883,0.0007279546,0.005201671,0.00018790513,0.0077477656],"study_design_scores_gemma":[5.084699e-7,0.0000025182167,0.000017350492,8.1173175e-7,0.0000012425223,0.0000013430989,0.0000010695013,0.9994067,0.000056916666,0.00045631753,0.000054239557,0.0000010293064],"about_ca_topic_score_codex":0.018461173,"about_ca_topic_score_gemma":0.013283247,"teacher_disagreement_score":0.018461173,"about_ca_system_score_codex":0.00080278434,"about_ca_system_score_gemma":0.0015827391,"threshold_uncertainty_score":0.0367074},"labels":[],"label_agreement":null},{"id":"W4391981392","doi":"10.21203/rs.3.rs-3960166/v1","title":"Investigating Drilling Efficiency: A Study on Indexable Centerless Drilling of Ti-6Al-4V Alloy","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Materials science; Tool wear; Delamination (geology); Drilling; Metallurgy; Surface roughness; Titanium alloy; Machining; Abrasion (mechanical); Ultimate tensile strength; Lubrication; Spall; Alloy; Composite material; Geology","score_opus":0.061050273542316104,"score_gpt":0.3819291186049421,"score_spread":0.320878845062626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391981392","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982809,0.00041108867,0.0010406075,0.000006610126,0.000005120664,0.00001404392,0.00002504631,0.000008567161,0.00020799032],"genre_scores_gemma":[0.9961576,0.00040482005,0.0029275164,0.0000081742355,0.0000034853597,0.000009182788,0.000051616524,0.000010593502,0.0004271187],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995142,0.000060359027,0.000035471094,0.00009414384,0.00024193605,0.000053926215],"domain_scores_gemma":[0.9991542,0.00019375127,0.00022837885,0.000057549812,0.0003327361,0.000033402674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049797876,0.0002699065,0.0004609046,0.00040299736,0.00018635367,0.0004090142,0.00040331198,0.0004288324,0.00045462567],"category_scores_gemma":[0.0010145458,0.00019616655,0.00032871962,0.00030133486,0.0003364519,0.00042856517,0.00021736133,0.0002664065,0.0001196004],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003841164,0.00017059152,0.0033459512,0.00032073425,0.000020439797,0.00018457095,0.00044238224,0.00063824136,0.98387086,0.000068493326,0.000047188263,0.010506443],"study_design_scores_gemma":[0.000024403718,0.008304572,0.045946337,0.000033471475,0.00014592826,0.00064165686,0.0013154935,0.006827409,0.93409425,0.00006502503,0.00254328,0.000058166723],"about_ca_topic_score_codex":0.00087183114,"about_ca_topic_score_gemma":0.001497677,"teacher_disagreement_score":0.00087183114,"about_ca_system_score_codex":0.00017543919,"about_ca_system_score_gemma":0.00016218695,"threshold_uncertainty_score":0.0026336312},"labels":[],"label_agreement":null},{"id":"W4392102733","doi":"10.3390/lubricants12030069","title":"Solid Lubricants Used in Extreme Conditions Experienced in Machining: A Comprehensive Review of Recent Developments and Applications","year":2024,"lang":"en","type":"review","venue":"Lubricants","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Materials science; Forensic engineering; Manufacturing engineering; Engineering; Mechanical engineering; Nanotechnology; Systems engineering","score_opus":0.10427412570604443,"score_gpt":0.38457237088980484,"score_spread":0.2802982451837604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392102733","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00054110115,0.9980615,0.00018868643,0.0000972499,0.00007403478,0.000008062696,0.00004172614,0.000009892725,0.0009777006],"genre_scores_gemma":[0.002290609,0.9967943,0.00026294653,0.000062927546,0.000048216156,0.000007867784,0.000049350532,0.0000022264455,0.00048167325],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997414,0.00003690706,0.0000482189,0.00004826039,0.00009641935,0.000028803639],"domain_scores_gemma":[0.999608,0.0001989304,0.00007506291,0.000010178695,0.00008950443,0.000018368068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005586527,0.00081171154,0.001095499,0.002565806,0.00029626538,0.0010439502,0.00065300224,0.0007399801,0.003464668],"category_scores_gemma":[0.0008789929,0.00034670383,0.0008419971,0.002416407,0.00027424438,0.0011712316,0.0004984717,0.0007754908,0.0010639937],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011883929,0.000120181336,0.00048881007,0.08933155,0.00020539232,0.0002778531,0.00015704526,0.0010245932,0.008148384,0.004075199,0.012754127,0.8832981],"study_design_scores_gemma":[0.000014769118,0.00030381454,0.001401843,0.0077503114,0.00044381237,0.0010589224,0.00013025347,0.00029123362,0.0041219555,0.0011536697,0.98329204,0.00003743419],"about_ca_topic_score_codex":0.0013396606,"about_ca_topic_score_gemma":0.0021880558,"teacher_disagreement_score":0.003464668,"about_ca_system_score_codex":0.00040193042,"about_ca_system_score_gemma":0.0011331771,"threshold_uncertainty_score":0.011590481},"labels":[],"label_agreement":null},{"id":"W4392365948","doi":"10.18280/rcma.340102","title":"Investigating Corrosion and Surface Hardness of Al6061 in Machining Fluids with Variable CNT Concentrations","year":2024,"lang":"fr","type":"article","venue":"Revue des composites et des matériaux avancés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Corrosion; Materials science; Hardness; Metallurgy; Composite material","score_opus":0.030376559218996284,"score_gpt":0.2681928849183296,"score_spread":0.2378163256993333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392365948","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969869,0.0007034417,0.0014838882,0.000033670112,0.000016967524,0.000013212431,0.00010581872,0.000022647146,0.0006333198],"genre_scores_gemma":[0.99541473,0.0005726369,0.0022938813,0.00002004783,0.000007289685,0.00001885645,0.00013025438,0.000012676221,0.0015296786],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996563,0.000026819072,0.00001995019,0.000062427076,0.00020485396,0.000029703593],"domain_scores_gemma":[0.9997658,0.00004081818,0.0000581573,0.000010493048,0.00011229545,0.0000125089755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016466662,0.00026851022,0.00028616216,0.0002867007,0.00018315358,0.0003391991,0.00021216413,0.00040314242,0.00075072236],"category_scores_gemma":[0.00044431578,0.00014847759,0.0003147934,0.00021162794,0.00016764922,0.0003743985,0.00016229105,0.000294859,0.00019483507],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069991096,0.000019645417,0.001052996,0.00007955628,0.000005841741,0.000057331374,0.00005864417,0.00020106166,0.9949831,0.00002893713,0.00002433251,0.0034186104],"study_design_scores_gemma":[0.0000037830284,0.00057490106,0.008857555,0.000007997132,0.00002096199,0.00009043795,0.0001537288,0.0022172774,0.9869357,0.000034501398,0.001092663,0.0000105339395],"about_ca_topic_score_codex":0.0013333656,"about_ca_topic_score_gemma":0.0020779348,"teacher_disagreement_score":0.0013333656,"about_ca_system_score_codex":0.00017532479,"about_ca_system_score_gemma":0.00009672004,"threshold_uncertainty_score":0.0026512146},"labels":[],"label_agreement":null},{"id":"W4392727326","doi":"10.1016/j.ymssp.2024.111326","title":"Health monitoring of CNC machining processes using machine learning and wavelet packet transform","year":2024,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Nature Conservancy of Canada","keywords":"Wavelet packet decomposition; Wavelet; Confusion matrix; Process (computing); Artificial intelligence; Computer science; Machining; Machine learning; Context (archaeology); Wavelet transform; Numerical control; Pattern recognition (psychology); Engineering; Mechanical engineering","score_opus":0.018355248689508136,"score_gpt":0.2719154275417339,"score_spread":0.2535601788522258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392727326","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8788207,0.00034350625,0.118905984,0.00011257354,0.000031273932,0.000045476143,0.0001434049,0.00027751765,0.0013195768],"genre_scores_gemma":[0.99432796,0.00007449238,0.005195328,0.00001170592,0.0000057322072,0.0000113328115,0.000061516585,0.0000064784226,0.0003056163],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979275,0.000028695034,0.000010976526,0.000047272006,0.000100567275,0.000019688545],"domain_scores_gemma":[0.99955446,0.0001492115,0.00007897124,0.000031991636,0.00016978684,0.00001554551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003464238,0.00028294223,0.00030775185,0.0006031081,0.00018042204,0.00036237462,0.00028387227,0.0004470239,0.00037945545],"category_scores_gemma":[0.00082995574,0.00009471301,0.00012487108,0.00041807172,0.00022008679,0.00037548871,0.00020089015,0.0002275776,0.00008018475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028573868,0.0005500484,0.074117295,0.0003115149,0.0001172167,0.0005603617,0.00032952803,0.17051174,0.29525036,0.001113039,0.0014747186,0.4528068],"study_design_scores_gemma":[0.00002218636,0.00030632177,0.057409402,0.00000965722,0.000032095984,0.00014225992,0.000059264996,0.8933571,0.047714874,0.00052394904,0.00040280944,0.000020047186],"about_ca_topic_score_codex":0.0024494997,"about_ca_topic_score_gemma":0.0019094625,"teacher_disagreement_score":0.0024494997,"about_ca_system_score_codex":0.00030136819,"about_ca_system_score_gemma":0.00031212147,"threshold_uncertainty_score":0.004870534},"labels":[],"label_agreement":null},{"id":"W4392738452","doi":"10.1016/j.cie.2024.110074","title":"Multimodal 1D CNN for delamination prediction in CFRP drilling process with industrial robots","year":2024,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Institute for Information and Communications Technology Promotion; National Research Foundation of Korea; Ministry of Trade, Industry and Energy","keywords":"Delamination (geology); Machining; Convolutional neural network; Drilling; Test data; Computer science; Data set; Deep hole drilling; Automotive industry; Structural engineering; Engineering; Artificial intelligence; Mechanical engineering; Geology","score_opus":0.018347494983261815,"score_gpt":0.2279103650947433,"score_spread":0.20956287011148148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392738452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.522503,0.0016558009,0.4642147,0.00041138916,0.00026256675,0.000071811206,0.0008621632,0.0023649926,0.0076536154],"genre_scores_gemma":[0.96536726,0.00025451794,0.030162783,0.00010161866,0.00003385924,0.000030272397,0.00042701975,0.000034970646,0.0035875933],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998696,0.000012298573,0.0000041467747,0.000044740642,0.00003218027,0.000036977286],"domain_scores_gemma":[0.9998648,0.000041096002,0.000017591121,0.000017551842,0.00004845734,0.000010419334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022330947,0.000753598,0.0004244031,0.0004082546,0.00017078809,0.00036552883,0.00060592237,0.00088662445,0.0019846833],"category_scores_gemma":[0.0005328856,0.00036425292,0.00050041097,0.00034292627,0.00018698856,0.0005196121,0.0004962372,0.00045423213,0.00038597858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006543998,0.00021912539,0.007832853,0.00017841002,0.000116386494,0.00040161022,0.0000905068,0.57125884,0.03755889,0.00096506526,0.0038980881,0.37682575],"study_design_scores_gemma":[0.000002281166,0.000033526732,0.0010879535,0.0000043242253,0.000008044174,0.000021633154,0.000008523302,0.9961564,0.002328292,0.00017883387,0.00016660219,0.0000036328508],"about_ca_topic_score_codex":0.007143986,"about_ca_topic_score_gemma":0.009735728,"teacher_disagreement_score":0.007143986,"about_ca_system_score_codex":0.00035948053,"about_ca_system_score_gemma":0.00037993633,"threshold_uncertainty_score":0.0142048},"labels":[],"label_agreement":null},{"id":"W4392806864","doi":"10.1115/1.4065062","title":"A Physics-Based Model-Data-Driven Method for Spindle Health Diagnosis, Part I: Modeling of Geometric Faults","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Geometric modeling; Computer science; Physics; Statistical physics; Engineering; Mechanical engineering","score_opus":0.03637809664483822,"score_gpt":0.31270174340383183,"score_spread":0.2763236467589936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392806864","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012824695,0.000074753465,0.9854651,0.00006210628,0.00001622845,0.000053222313,0.000053558564,0.00050647673,0.000943847],"genre_scores_gemma":[0.81921273,0.00014416278,0.17726313,0.00006848851,0.000023349292,0.0003263429,0.00018434253,0.00009330619,0.002684124],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998832,0.000022440765,0.000006821832,0.000026568649,0.000050622722,0.000010334123],"domain_scores_gemma":[0.999647,0.00020141069,0.000041188854,0.000022472917,0.000076487784,0.000011324797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035582716,0.00051788345,0.0004927205,0.00048137596,0.0003202091,0.0005058007,0.0007113537,0.0007620048,0.0019555814],"category_scores_gemma":[0.0010314442,0.00039873197,0.00054693996,0.00025241452,0.0003794175,0.0003450472,0.00038578638,0.00066372834,0.00027354324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020127813,0.00003262648,0.00029608875,0.000030284693,0.000011139521,0.000034362183,0.000019176134,0.9813534,0.0029316144,0.0012420963,0.0001480549,0.013881069],"study_design_scores_gemma":[0.000001278673,0.000003835835,0.000024635874,6.5194104e-7,7.5965573e-7,0.0000025119627,7.7641806e-7,0.9996427,0.00013677613,0.0001249434,0.000060238195,7.5011485e-7],"about_ca_topic_score_codex":0.007877765,"about_ca_topic_score_gemma":0.005712087,"teacher_disagreement_score":0.007877765,"about_ca_system_score_codex":0.0005958414,"about_ca_system_score_gemma":0.0007939243,"threshold_uncertainty_score":0.015663803},"labels":[],"label_agreement":null},{"id":"W4393201702","doi":"10.1115/1.4065180","title":"Efficient Voxel-Based Workpiece Update and Cutter-Workpiece Engagement Determination in Multi-Axis Milling","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Engineering drawing; Materials science; Milling cutter; Voxel; Mechanical engineering; Computer science; Machining; Engineering; Metallurgy; Artificial intelligence","score_opus":0.010399855925569013,"score_gpt":0.2416327237803322,"score_spread":0.23123286785476319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393201702","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02153049,0.000064484215,0.9767752,0.000022545602,0.000008520343,0.000028288447,0.00002204418,0.0007920647,0.00075635186],"genre_scores_gemma":[0.437702,0.00007319869,0.5608985,0.00002013928,0.000006212852,0.00006141996,0.000085856125,0.0001880089,0.00096479466],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996402,0.000059638314,0.000018838255,0.00005458307,0.0001939933,0.000032716547],"domain_scores_gemma":[0.99951243,0.00018474145,0.00007225415,0.00008911041,0.00011675578,0.000024779853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037187347,0.0004141582,0.00058946665,0.00044034616,0.00029848047,0.0006918012,0.0011353651,0.00051743,0.0013005733],"category_scores_gemma":[0.0011216791,0.0004037459,0.00037885635,0.00037702854,0.00037342485,0.000742012,0.0007878168,0.00048250347,0.00025348726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026813784,0.00007062531,0.0026857792,0.00013987426,0.000039049184,0.00016341436,0.00032357837,0.69043654,0.06894159,0.008618912,0.0009454204,0.2273671],"study_design_scores_gemma":[0.0000068799613,0.00001976127,0.00021807445,0.0000023867474,0.0000033337922,0.00003671954,0.000013132759,0.9864631,0.011781975,0.0005262658,0.0009200622,0.000008249011],"about_ca_topic_score_codex":0.0027090479,"about_ca_topic_score_gemma":0.0035676635,"teacher_disagreement_score":0.0027090479,"about_ca_system_score_codex":0.0004964676,"about_ca_system_score_gemma":0.0008559679,"threshold_uncertainty_score":0.0053865314},"labels":[],"label_agreement":null},{"id":"W4393203722","doi":"10.1016/j.simpat.2024.102928","title":"A novel finite element model for thermally induced machining of Ti6Al4V","year":2024,"lang":"en","type":"article","venue":"Simulation Modelling Practice and Theory","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chip; Taguchi methods; Machining; Materials science; Finite element method; Mechanical engineering; Deformation (meteorology); Structural engineering; Cutting tool; Orthogonal array; Simulation software; Software; Composite material; Engineering; Computer science","score_opus":0.03933279826043602,"score_gpt":0.3104984445085004,"score_spread":0.2711656462480644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393203722","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056005165,0.00043193382,0.9093346,0.000325091,0.00019796014,0.00015636015,0.0006358293,0.0008871772,0.032025818],"genre_scores_gemma":[0.7633927,0.00065998075,0.19416922,0.0002358084,0.000064492626,0.0005273852,0.0010094022,0.00034188858,0.03959896],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986136,0.000018633189,0.0000068191985,0.000020612159,0.00007753698,0.000014969131],"domain_scores_gemma":[0.9998981,0.000031149517,0.000015187854,0.000013183851,0.000034139543,0.00000838007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018844352,0.00044047317,0.00060600875,0.00033480674,0.00037609666,0.00059376046,0.0020796976,0.0019469126,0.004677396],"category_scores_gemma":[0.00034308145,0.00043366433,0.00061742484,0.00042353923,0.00039741155,0.0005321598,0.00038605643,0.0006017356,0.00091417064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002818579,0.000038683345,0.00019986632,0.00007112555,0.0000147670935,0.00006852633,0.000035704976,0.97807914,0.009499678,0.00570559,0.00043643266,0.0058223275],"study_design_scores_gemma":[0.00000579856,0.000015078321,0.00009112594,0.0000046882633,0.000004671959,0.000024142355,0.000007683697,0.99661404,0.0011197773,0.00041361514,0.0016949498,0.0000043711557],"about_ca_topic_score_codex":0.0050387853,"about_ca_topic_score_gemma":0.0062858346,"teacher_disagreement_score":0.0050387853,"about_ca_system_score_codex":0.0005120534,"about_ca_system_score_gemma":0.0009204662,"threshold_uncertainty_score":0.015647411},"labels":[],"label_agreement":null},{"id":"W4393232953","doi":"10.18280/mmep.110312","title":"Multi-objective Optimization for Enhanced Material Removal Rate and Reduced Machining Roughness in Hard Turning of SKD61 Alloy Steel","year":2024,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Alloy; Materials science; Metallurgy; Surface roughness; Surface finish; Alloy steel; Mechanical engineering; Composite material; Engineering","score_opus":0.0173226866327384,"score_gpt":0.23400032483281144,"score_spread":0.21667763820007305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393232953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.708923,0.00094886665,0.28090984,0.00025350074,0.000097269345,0.00009845573,0.00010763574,0.0002113528,0.0084500825],"genre_scores_gemma":[0.9821792,0.00011947413,0.016027672,0.000028407921,0.000013040871,0.000044653378,0.000054139942,0.000030131861,0.0015032828],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997267,0.00008602629,0.000011346328,0.000033482105,0.00007212932,0.00007036719],"domain_scores_gemma":[0.9994741,0.0003023805,0.000067478315,0.000019351308,0.00010512023,0.000031642143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088184857,0.0008031241,0.0012577106,0.0006935271,0.00039642907,0.0010621161,0.00061628956,0.0010710648,0.000992486],"category_scores_gemma":[0.00093111594,0.0005206515,0.0009897556,0.00038196804,0.00045636875,0.00037986191,0.0004897542,0.00055715395,0.00010413893],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006620128,0.000055028802,0.0002458051,0.000070792405,0.000027660908,0.00003946377,0.000015989985,0.9897501,0.0047536884,0.00047009665,0.00009827324,0.004407001],"study_design_scores_gemma":[0.000008717788,0.000066966364,0.0003030142,0.00000254419,0.000008638643,0.000005059017,0.000008883155,0.9984939,0.0009285278,0.00011317438,0.00005680192,0.0000037286493],"about_ca_topic_score_codex":0.0057122814,"about_ca_topic_score_gemma":0.0043045026,"teacher_disagreement_score":0.0057122814,"about_ca_system_score_codex":0.00065951684,"about_ca_system_score_gemma":0.0006946851,"threshold_uncertainty_score":0.011358023},"labels":[],"label_agreement":null},{"id":"W4393256399","doi":"10.1016/j.jmapro.2024.03.078","title":"Analyzing the effect of elliptical vibration assistance in machining of Zr-based BMG","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Machining; Vibration; Mechanical engineering; Metallurgy; Composite material; Structural engineering; Engineering; Acoustics","score_opus":0.0054526822160405625,"score_gpt":0.24092812263092261,"score_spread":0.23547544041488205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393256399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99418515,0.0002738707,0.0041549597,0.000034258483,0.000012871471,0.0000049768396,0.000023900428,0.00007263263,0.0012372974],"genre_scores_gemma":[0.9987651,0.000041852953,0.0008994441,0.0000060056623,0.0000014492955,0.0000012966077,0.000011988373,0.0000059556646,0.00026690253],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998596,0.000014625762,0.0000039350894,0.000024786354,0.000066378045,0.000030665113],"domain_scores_gemma":[0.9997825,0.00010163123,0.00004249565,0.000018206694,0.000044153523,0.000010989547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018984282,0.00022709055,0.0002092866,0.00017760876,0.00015305907,0.00023551074,0.00031511407,0.00038115509,0.0011131645],"category_scores_gemma":[0.00036420376,0.000097102624,0.00018580558,0.00021231975,0.00023366504,0.00022327731,0.00014220794,0.00014653464,0.00013100157],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010318595,0.000047537615,0.0019484787,0.00020601109,0.00002425424,0.00017236738,0.000087780856,0.018975237,0.9588277,0.0003286657,0.00019236197,0.018157663],"study_design_scores_gemma":[0.0000429682,0.0014486529,0.031972982,0.000021159081,0.00011293677,0.00018073338,0.00030415977,0.21035817,0.7532272,0.00017064477,0.0021256183,0.000034752866],"about_ca_topic_score_codex":0.00078795163,"about_ca_topic_score_gemma":0.0013791437,"teacher_disagreement_score":0.0011131645,"about_ca_system_score_codex":0.0001443383,"about_ca_system_score_gemma":0.00011244192,"threshold_uncertainty_score":0.0037239194},"labels":[],"label_agreement":null},{"id":"W4393357041","doi":"10.3390/jmmp8020068","title":"Enhancing Tool Performance in High-Speed End Milling of Ti-6Al-4V Alloy: The Role of AlCrN PVD Coatings and Resistance to Chipping Wear","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"End milling; Materials science; Wear resistance; Metallurgy; Alloy; Titanium alloy; High resistance; Machining","score_opus":0.00432379013613367,"score_gpt":0.20646755732119446,"score_spread":0.20214376718506077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393357041","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99591714,0.0008768513,0.002768162,0.000010186388,0.0000058331666,0.000008334821,0.000016646616,0.000039016515,0.00035793718],"genre_scores_gemma":[0.99696225,0.00019412361,0.0024892483,0.000005452592,0.0000021791711,0.0000023560706,0.000021716163,0.000011667116,0.00031105382],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99966085,0.000034829995,0.000017926619,0.000043665776,0.0001801441,0.00006258754],"domain_scores_gemma":[0.99961156,0.000098231634,0.00011630814,0.000037950627,0.00010816047,0.000027821518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033483165,0.00034760602,0.00027445573,0.00031400958,0.00016570238,0.00044166535,0.0004546352,0.00046460063,0.00028994182],"category_scores_gemma":[0.0006145946,0.00016255805,0.0002644478,0.00017084785,0.00017919105,0.0002918691,0.00018706791,0.00027301014,0.00015036983],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007283017,0.000017780068,0.00072128145,0.00007968792,0.00000633888,0.000048050842,0.000027568973,0.00050129375,0.99151117,0.000014275435,0.000018285571,0.0069813924],"study_design_scores_gemma":[0.0000050573653,0.0005207657,0.0088409195,0.00000529691,0.000018086126,0.00015018934,0.000025845955,0.002955494,0.9870301,0.000013422715,0.00042562274,0.000009160273],"about_ca_topic_score_codex":0.0005913103,"about_ca_topic_score_gemma":0.0014140052,"teacher_disagreement_score":0.0005913103,"about_ca_system_score_codex":0.000176671,"about_ca_system_score_gemma":0.00013708875,"threshold_uncertainty_score":0.0017707944},"labels":[],"label_agreement":null},{"id":"W4393411238","doi":"10.1115/1.4065227","title":"A Physics-Based Model-Data-Driven Method for Spindle Health Diagnosis—Part III: Model Training and Fault Detection","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Training (meteorology); Fault (geology); Computer science; Fault detection and isolation; Artificial intelligence; Physics; Geology; Seismology","score_opus":0.03909545296061598,"score_gpt":0.3082138345873652,"score_spread":0.26911838162674917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393411238","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067384564,0.00006218846,0.9920797,0.000056754667,0.000012828737,0.000024798463,0.000017772016,0.0006164085,0.00039104684],"genre_scores_gemma":[0.6959153,0.00012893292,0.30054292,0.00012458695,0.000043726624,0.00023697257,0.0002100468,0.00013703048,0.0026605546],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998367,0.000029766581,0.0000085664005,0.000051067622,0.000059119044,0.000014750809],"domain_scores_gemma":[0.9996025,0.00018952791,0.000048827842,0.00003992505,0.000105053856,0.00001413857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051113416,0.0006122336,0.0006280435,0.0004774816,0.000274281,0.0004780117,0.00095841684,0.00088499876,0.0018375735],"category_scores_gemma":[0.0014049641,0.00047880862,0.0006241555,0.00026423356,0.00032237012,0.0004847176,0.0005526393,0.0009908411,0.00037226774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050832186,0.000079309495,0.0006192929,0.0000683031,0.000039031114,0.0000607505,0.00003950864,0.8809121,0.01106533,0.0022180777,0.0006585338,0.10418892],"study_design_scores_gemma":[0.0000012760763,0.000005002248,0.00004768776,9.629124e-7,0.0000010996636,0.000004267068,7.5685233e-7,0.99923694,0.00041346176,0.00020873363,0.00007870335,0.0000012007994],"about_ca_topic_score_codex":0.004696994,"about_ca_topic_score_gemma":0.0036869491,"teacher_disagreement_score":0.004696994,"about_ca_system_score_codex":0.0005603899,"about_ca_system_score_gemma":0.0007886776,"threshold_uncertainty_score":0.009339333},"labels":[],"label_agreement":null},{"id":"W4394064432","doi":"10.2316/j.2024.201-0405","title":"APPLICATION OF CNC MACHINING FOR ELECTROMECHANICAL PARTS BASED ON MACHINE VISION TECHNOLOGY, 156-165.","year":2024,"lang":"en","type":"article","venue":"Mechatronic systems and control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machining; Numerical control; Machine vision; Engineering drawing; Manufacturing engineering; Computer vision; Computer science; Engineering; Artificial intelligence; Mechanical engineering","score_opus":0.002621170030004999,"score_gpt":0.22214541525621767,"score_spread":0.21952424522621267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394064432","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23818865,0.060807858,0.4344779,0.0020062795,0.0032572292,0.00046330242,0.00056068046,0.0012771541,0.25896105],"genre_scores_gemma":[0.79965484,0.008986873,0.13780765,0.00022111136,0.0001473376,0.00005989091,0.0003353892,0.00009393506,0.05269292],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996817,0.000024711922,0.0000105206,0.000042484477,0.00022224065,0.00001839691],"domain_scores_gemma":[0.99984145,0.000027616414,0.000009555006,0.000015311143,0.00009766259,0.000008423326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039509241,0.00031724313,0.00023230311,0.0011733733,0.0005284668,0.0006039318,0.0004846386,0.000630396,0.0034960934],"category_scores_gemma":[0.00042194137,0.00023974538,0.0002581767,0.0006621362,0.00049377745,0.0005329349,0.00035701846,0.00041423814,0.00061279547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022720448,0.00009298151,0.002545635,0.00081779686,0.000031186217,0.00064184656,0.0002112943,0.005291486,0.5423709,0.020822002,0.012438137,0.4145095],"study_design_scores_gemma":[0.00003773018,0.00034841063,0.023616852,0.000104533756,0.00008992906,0.0020449362,0.00017890637,0.050458096,0.74139476,0.005431235,0.17622654,0.00006807729],"about_ca_topic_score_codex":0.005933015,"about_ca_topic_score_gemma":0.014372956,"teacher_disagreement_score":0.005933015,"about_ca_system_score_codex":0.00092291494,"about_ca_system_score_gemma":0.0009352793,"threshold_uncertainty_score":0.011796951},"labels":[],"label_agreement":null},{"id":"W4394577314","doi":"10.3390/s24072324","title":"Cyber–Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era—A Review","year":2024,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs; McGill University","keywords":"Cyber-physical system; Machining; Process (computing); Computer science; Engineering; Risk analysis (engineering); Manufacturing engineering; Reliability engineering; Systems engineering; Mechanical engineering","score_opus":0.007516103061707233,"score_gpt":0.25063802387990136,"score_spread":0.24312192081819411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394577314","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006251643,0.9886341,0.0068684476,0.0003630928,0.0002935714,0.000015762482,0.000023477904,0.000031556327,0.0031447783],"genre_scores_gemma":[0.006664115,0.98956513,0.0022434779,0.00017630593,0.00046353135,0.000019535444,0.00004503686,0.00000832832,0.00081450294],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997538,0.000041719195,0.000028287423,0.000050221603,0.00010778208,0.000018295495],"domain_scores_gemma":[0.99913377,0.00058555015,0.00008342057,0.00002473062,0.0001460877,0.000026425569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004923501,0.0013193488,0.0012065149,0.0016124946,0.0002975471,0.0014429842,0.00084801414,0.0015114493,0.003116891],"category_scores_gemma":[0.00094947213,0.00046210643,0.00077147916,0.0019139241,0.0005963774,0.0022146166,0.00071066595,0.0012845247,0.0011413231],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052107138,0.000115258845,0.0006379848,0.027379172,0.00017883965,0.00023059826,0.00019247999,0.0123920925,0.0029882432,0.040152397,0.0135365,0.9021443],"study_design_scores_gemma":[0.000015282432,0.00035281683,0.0023089787,0.009590157,0.00032386326,0.001179036,0.00031041188,0.013189078,0.0026135577,0.027061613,0.94292945,0.00012572395],"about_ca_topic_score_codex":0.0009775115,"about_ca_topic_score_gemma":0.000852468,"teacher_disagreement_score":0.003116891,"about_ca_system_score_codex":0.0004571919,"about_ca_system_score_gemma":0.0010150486,"threshold_uncertainty_score":0.010427117},"labels":[],"label_agreement":null},{"id":"W4394691853","doi":"10.1139/tcsme-2023-0148","title":"Milling characteristics of SiCp/2024Al composites thin-walled part based on movable auxiliary support","year":2024,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Materials science; Composite material; Composite number","score_opus":0.007643664458939924,"score_gpt":0.19908776817383722,"score_spread":0.19144410371489728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394691853","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99614847,0.0000930765,0.0026700508,0.000011854483,0.000007879329,0.0000054570546,0.00006423489,0.00006192874,0.00093700923],"genre_scores_gemma":[0.9975249,0.00003668873,0.0018887128,0.00000342742,0.0000013307566,0.0000032160503,0.000058304857,0.000011470816,0.00047195738],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99984217,0.000007165703,0.000007810483,0.000024800227,0.000101829304,0.000016196032],"domain_scores_gemma":[0.99957293,0.00013747915,0.00009547701,0.000058941954,0.000107961314,0.000027282946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002310176,0.00022832786,0.00018984245,0.00040261896,0.00016219653,0.0002548256,0.0003000783,0.00032747907,0.0013822496],"category_scores_gemma":[0.0004500448,0.00020877816,0.00024158841,0.00034983322,0.00031228695,0.0002011098,0.00012003444,0.00020391519,0.00015666564],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004481459,0.000022138818,0.002624298,0.00013181655,0.00001285605,0.00023908877,0.00017876514,0.014925517,0.9696316,0.000248457,0.00024261634,0.0112947775],"study_design_scores_gemma":[0.000041376687,0.0015660191,0.0936544,0.000024966366,0.00006867365,0.0003641909,0.0002812016,0.16736658,0.7342519,0.000218079,0.0020776757,0.00008483001],"about_ca_topic_score_codex":0.000568519,"about_ca_topic_score_gemma":0.0011456094,"teacher_disagreement_score":0.0013822496,"about_ca_system_score_codex":0.00017518592,"about_ca_system_score_gemma":0.00011077954,"threshold_uncertainty_score":0.0046241283},"labels":[],"label_agreement":null},{"id":"W4394857480","doi":"10.1139/tcsme-2023-0214","title":"Multi-objective optimization design for the table of a CNC machine tool based on bionic structures","year":2024,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Bionics; Table (database); Finite element method; Bellows; Modal; Engineering; Engineering drawing; Computer science; Structural engineering; Mechanical engineering; Artificial intelligence; Data mining; Materials science","score_opus":0.011854728562947933,"score_gpt":0.2192560413491269,"score_spread":0.20740131278617896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394857480","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.113045886,0.00030691392,0.8750102,0.00008931875,0.000051301224,0.00028587505,0.00012073283,0.00026521852,0.010824621],"genre_scores_gemma":[0.74997026,0.00020597083,0.24521591,0.00004979059,0.0000117962045,0.0007187114,0.00015845768,0.00004644868,0.0036226623],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965835,0.00005699086,0.000012422872,0.000064199616,0.0001739618,0.000034046057],"domain_scores_gemma":[0.99974746,0.000092583454,0.00004385507,0.000015994141,0.000088380744,0.00001169951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007616382,0.0007734402,0.0006333928,0.0006820571,0.00031238195,0.00071511697,0.00079367653,0.0007698778,0.0021400903],"category_scores_gemma":[0.00067214237,0.00044572607,0.0005813878,0.0006218816,0.00036162022,0.00044904847,0.00037637193,0.00046789835,0.00023191229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004584612,0.00004060967,0.00050343404,0.00015127714,0.00002083397,0.000054063385,0.000028297472,0.95566493,0.01585962,0.0018675281,0.00033854868,0.025424866],"study_design_scores_gemma":[0.000011201361,0.00012107962,0.00043551825,0.0000058275614,0.0000100982425,0.000012892404,0.000010218758,0.9958847,0.0025095998,0.00023242465,0.0007600827,0.000006396175],"about_ca_topic_score_codex":0.0030052972,"about_ca_topic_score_gemma":0.0040422967,"teacher_disagreement_score":0.0030052972,"about_ca_system_score_codex":0.00066099025,"about_ca_system_score_gemma":0.0013606657,"threshold_uncertainty_score":0.0071593523},"labels":[],"label_agreement":null},{"id":"W4396554532","doi":"10.1016/j.cirpj.2024.04.008","title":"Physics based models for characterization of machining performance – A critical review","year":2024,"lang":"en","type":"review","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; University of British Columbia; McGill University","funders":"","keywords":"Machining; Characterization (materials science); Mechanical engineering; Computer science; Engineering; Manufacturing engineering; Materials science; Systems engineering; Nanotechnology","score_opus":0.03321355867917534,"score_gpt":0.3105007309753048,"score_spread":0.2772871722961294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396554532","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010387552,0.94702816,0.046703618,0.00043983723,0.0005361003,0.000044710632,0.00012433379,0.00017877997,0.0039056824],"genre_scores_gemma":[0.014078863,0.9664048,0.016804665,0.00018758861,0.00075080106,0.00008594593,0.0003139631,0.00006738464,0.0013060486],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991968,0.00013627838,0.00008091848,0.0001460529,0.0004010914,0.000038868682],"domain_scores_gemma":[0.9976993,0.0014950702,0.000116290525,0.00013588066,0.00051942543,0.000033981276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016671235,0.0018693988,0.00228764,0.0032972596,0.00028248268,0.001716738,0.0028266527,0.0019605975,0.002801424],"category_scores_gemma":[0.0027473373,0.0009297242,0.0012209592,0.003182311,0.0009934996,0.0028474552,0.00092502125,0.001908029,0.002043806],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090104324,0.00018781505,0.00090460316,0.01678103,0.00024398105,0.00015788214,0.00010326434,0.06261224,0.004606277,0.03922735,0.016107004,0.8589785],"study_design_scores_gemma":[0.000030325951,0.00040787816,0.002319192,0.006835526,0.0003917083,0.0010962303,0.00015332818,0.095698915,0.0062997853,0.040692057,0.8458388,0.00023613832],"about_ca_topic_score_codex":0.0015761108,"about_ca_topic_score_gemma":0.00076859834,"teacher_disagreement_score":0.0032972596,"about_ca_system_score_codex":0.0009440185,"about_ca_system_score_gemma":0.0011703516,"threshold_uncertainty_score":0.009371698},"labels":[],"label_agreement":null},{"id":"W4396753957","doi":"10.1051/mattech/2024001","title":"Artificial neural network-based modelling and prediction of white layer formation during hard turning of steels","year":2024,"lang":"en","type":"article","venue":"Matériaux & Techniques","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Artificial neural network; Layer (electronics); White (mutation); Computer science; Artificial intelligence; Materials science; Composite material; Chemistry","score_opus":0.023021154003106954,"score_gpt":0.23100690311315922,"score_spread":0.20798574911005227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396753957","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84282994,0.0005145802,0.15332806,0.0000916621,0.00005001947,0.000044102344,0.0001151814,0.00035527226,0.0026711228],"genre_scores_gemma":[0.9946983,0.00009751129,0.0044221017,0.0000066123025,0.00000347514,0.000019744906,0.000052326202,0.0000071389886,0.0006929016],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991596,0.00001942978,0.0000066392327,0.00001886895,0.000022541453,0.000016510045],"domain_scores_gemma":[0.99974304,0.00014017429,0.000045361216,0.000009996489,0.00004927986,0.000012177061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003334825,0.0006088986,0.00039998046,0.00044336167,0.00017740313,0.00046655178,0.00037719213,0.0007226487,0.00046021023],"category_scores_gemma":[0.00067146274,0.00033599848,0.00039428213,0.00028255943,0.00023899475,0.00032398922,0.00017940666,0.0004170511,0.00010718734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039656188,0.000026956888,0.00082677207,0.000018551065,0.000010448736,0.000023947798,0.000009314887,0.99198616,0.00239959,0.000078893805,0.00004532885,0.0045342897],"study_design_scores_gemma":[5.7973824e-7,0.000007946388,0.00024195419,6.4834666e-7,0.0000011236225,0.0000010320887,0.0000010945322,0.9994185,0.00029694362,0.000017782802,0.000011399111,0.0000010284082],"about_ca_topic_score_codex":0.008264701,"about_ca_topic_score_gemma":0.0067987135,"teacher_disagreement_score":0.008264701,"about_ca_system_score_codex":0.0004278763,"about_ca_system_score_gemma":0.0003818235,"threshold_uncertainty_score":0.01643318},"labels":[],"label_agreement":null},{"id":"W4396867900","doi":"10.1186/s10086-024-02132-6","title":"Impact of coating and microstructure on wear resistance of tool steels for wood cutting: a novel approach to quantification and analysis of wear-related damages","year":2024,"lang":"en","type":"article","venue":"Journal of Wood Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"DK-SPEC (Canada); École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microstructure; Materials science; Wear resistance; Coating; Metallurgy; Composite material; Forensic engineering; Engineering","score_opus":0.01397513075615345,"score_gpt":0.29328349347756294,"score_spread":0.27930836272140946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396867900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9930321,0.00041361063,0.005851869,0.000004351393,0.0000071669574,0.000026732901,0.00012457429,0.000076884404,0.00046256743],"genre_scores_gemma":[0.9952636,0.00015659527,0.0039166855,0.0000047130775,0.0000025599813,0.0000102891645,0.00007637822,0.000008709802,0.00056031614],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996656,0.000026449698,0.000019235484,0.00004923391,0.00021568508,0.000023865363],"domain_scores_gemma":[0.9995284,0.00007442654,0.00010868023,0.000051210205,0.00021542073,0.000021882846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032837258,0.00028998993,0.00024618403,0.0007953649,0.00013306261,0.00025882514,0.00022636009,0.0003600657,0.0006574027],"category_scores_gemma":[0.0003998356,0.00020081585,0.00019962365,0.00028379107,0.00015302406,0.00013649644,0.00015293507,0.00016914491,0.00014997547],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007032588,0.000018867811,0.0037981917,0.000072820854,0.000011945215,0.000038159345,0.000049571783,0.00042337817,0.9897245,0.000013529262,0.000021412701,0.0057573277],"study_design_scores_gemma":[0.000006108367,0.00087403576,0.11011483,0.000012139692,0.00005557291,0.00033762446,0.0001472778,0.010702857,0.8770005,0.000024626936,0.00070067786,0.000023700959],"about_ca_topic_score_codex":0.0012891674,"about_ca_topic_score_gemma":0.0028090645,"teacher_disagreement_score":0.0012891674,"about_ca_system_score_codex":0.00017404559,"about_ca_system_score_gemma":0.0000811715,"threshold_uncertainty_score":0.0025633574},"labels":[],"label_agreement":null},{"id":"W4396900034","doi":"10.1016/j.cirp.2024.04.088","title":"Machine learning based substructure coupling of machine tool dynamics and chatter stability","year":2024,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Substructure; Stability (learning theory); Coupling (piping); Dynamics (music); Computer science; Machine tool; Control engineering; Control theory (sociology); Engineering; Mechanical engineering; Artificial intelligence; Physics; Machine learning; Structural engineering; Control (management); Acoustics","score_opus":0.011956125315025722,"score_gpt":0.24241759565135435,"score_spread":0.23046147033632863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396900034","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043286014,0.0003073851,0.9545998,0.0000726406,0.000022616541,0.000026571626,0.000020963651,0.0002682907,0.0013956669],"genre_scores_gemma":[0.93767065,0.00016231433,0.060521048,0.000041947937,0.000024889052,0.000058995112,0.000055520126,0.00004197811,0.0014226339],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936503,0.00016596486,0.000038446728,0.00016510936,0.00022881513,0.000036516376],"domain_scores_gemma":[0.9961151,0.002725067,0.00044937336,0.00024029285,0.0004082073,0.00006192195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013133085,0.0006707307,0.0006194055,0.0007474636,0.00027522136,0.00051797676,0.0007173232,0.0005892071,0.0009831726],"category_scores_gemma":[0.005511699,0.00027549072,0.00042861947,0.00037792692,0.0009747572,0.000942867,0.0007257837,0.0007333646,0.00017006867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000871124,0.000053352862,0.0032927035,0.00017212532,0.000051212104,0.00013013298,0.00015722773,0.90430665,0.012057477,0.010586439,0.00030821943,0.068797424],"study_design_scores_gemma":[5.1391294e-7,0.0000119867545,0.0003027237,0.0000029055734,0.0000015055987,0.000010910983,0.000001948432,0.99799997,0.00067853945,0.00093683513,0.000049202154,0.0000029557489],"about_ca_topic_score_codex":0.001599353,"about_ca_topic_score_gemma":0.0011498431,"teacher_disagreement_score":0.001599353,"about_ca_system_score_codex":0.0005505733,"about_ca_system_score_gemma":0.00035184054,"threshold_uncertainty_score":0.0069455504},"labels":[],"label_agreement":null},{"id":"W4397002069","doi":"10.3390/app14104266","title":"Practical Estimation of Machine Tool Spindle Dynamics for Maintenance Decision Making","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Estimation; Dynamics (music); Engineering; Systems engineering; Psychology","score_opus":0.014440731616833787,"score_gpt":0.320325387161728,"score_spread":0.3058846555448942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4397002069","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06083537,0.00021479442,0.9371763,0.00009934092,0.000011131412,0.000049199363,0.00008992936,0.00035715985,0.0011667089],"genre_scores_gemma":[0.89665824,0.00018490435,0.102444254,0.000023098795,0.000014465643,0.000053852636,0.00011632913,0.000013019146,0.0004917636],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978155,0.00006201985,0.0000133764015,0.000055010187,0.00007154225,0.000016575186],"domain_scores_gemma":[0.9989114,0.0007720898,0.000111918525,0.000056645815,0.00011885294,0.000029172004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048604133,0.0005031828,0.00045794758,0.00037355517,0.00016071476,0.00048332772,0.00038477965,0.0006376119,0.001337743],"category_scores_gemma":[0.0026839196,0.00024092615,0.0001547017,0.00019013701,0.00018168625,0.00062586035,0.00032279975,0.00037947771,0.0003120542],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047503933,0.00017910598,0.011427317,0.00036197412,0.000042271084,0.0002642447,0.0001539225,0.50473565,0.1013332,0.004257708,0.0021071453,0.3746624],"study_design_scores_gemma":[0.00001122307,0.000087359316,0.002958136,0.000012461346,0.000005401197,0.00005920601,0.000026416217,0.98837334,0.006684948,0.0011777324,0.0005922623,0.000011418794],"about_ca_topic_score_codex":0.0009954803,"about_ca_topic_score_gemma":0.0011783986,"teacher_disagreement_score":0.001337743,"about_ca_system_score_codex":0.00021018468,"about_ca_system_score_gemma":0.00044617074,"threshold_uncertainty_score":0.0044751763},"labels":[],"label_agreement":null},{"id":"W4397010533","doi":"10.3390/machines12050349","title":"Optimizing Machining Efficiency in High-Speed Milling of Super Duplex Stainless Steel with SiAlON Ceramic Inserts","year":2024,"lang":"en","type":"article","venue":"Machines","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Sialon; Duplex (building); Machining; Materials science; Ceramic; Metallurgy","score_opus":0.006427330738940225,"score_gpt":0.22191728108662478,"score_spread":0.21548995034768456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4397010533","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949244,0.00033564636,0.0039816466,0.000014534043,0.000009286948,0.000015712618,0.000055939785,0.000059871825,0.0006028998],"genre_scores_gemma":[0.99167186,0.00020180464,0.007559264,0.000007882923,0.0000022877077,0.000009534699,0.000069263646,0.000019891491,0.00045816664],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996866,0.000025382267,0.000030270003,0.000046530982,0.00016681639,0.000044342374],"domain_scores_gemma":[0.999731,0.0000674958,0.00008346216,0.000023069693,0.00007354587,0.000021486307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046454082,0.00033601627,0.00021916917,0.00041636886,0.0001207393,0.0003597147,0.00033501908,0.00033028526,0.00054794183],"category_scores_gemma":[0.00061227125,0.00021850773,0.00028745446,0.0003519702,0.00018516871,0.0002945991,0.00019157848,0.0002823257,0.0002586241],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015426797,0.000026459378,0.0011979194,0.00016623414,0.000009103716,0.0000917269,0.000080582846,0.0013060423,0.98862773,0.0000965702,0.000073875075,0.008169551],"study_design_scores_gemma":[0.000020723532,0.0010854704,0.013529392,0.00001968343,0.00003960483,0.00017795348,0.00014320608,0.011264853,0.9712866,0.000064429885,0.0023378287,0.000030153855],"about_ca_topic_score_codex":0.00058238243,"about_ca_topic_score_gemma":0.002802026,"teacher_disagreement_score":0.00058238243,"about_ca_system_score_codex":0.00018809023,"about_ca_system_score_gemma":0.00021834967,"threshold_uncertainty_score":0.0024567842},"labels":[],"label_agreement":null},{"id":"W4398766880","doi":"10.1201/9781003450252-59","title":"Machining of titanium alloys by using micro abrasive jet machine: an experimental investigation","year":2024,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Materials science; Machining; Abrasive; Metallurgy; Titanium alloy; Jet (fluid); Titanium; Machine tool; Mechanical engineering; Engineering; Alloy; Aerospace engineering","score_opus":0.014718459785108553,"score_gpt":0.2487606821180023,"score_spread":0.23404222233289376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398766880","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9924827,0.0007443385,0.0039014013,0.000035926107,0.00003844892,0.000077333985,0.00010124774,0.000060256436,0.0025583308],"genre_scores_gemma":[0.9880151,0.00067109766,0.008690445,0.000018325532,0.00002123321,0.000041077226,0.0001399106,0.000024664289,0.0023781613],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99941456,0.000038636685,0.00003596475,0.00010808812,0.0003111087,0.00009171054],"domain_scores_gemma":[0.9993611,0.00013212526,0.00011652721,0.00011939199,0.00023101606,0.00003989493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000621913,0.00040310418,0.00049729994,0.00063264405,0.0005300099,0.00044178872,0.00078369747,0.0007318834,0.001728473],"category_scores_gemma":[0.0005666691,0.00031724857,0.0005055289,0.0005296062,0.00037812188,0.00046239837,0.0002550857,0.00043453192,0.000594238],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023196697,0.0006487601,0.0010613727,0.00033321776,0.000020431313,0.00028072903,0.00040392572,0.00091128296,0.98647016,0.0002446445,0.00022129714,0.009172171],"study_design_scores_gemma":[0.00009000775,0.008407158,0.012108091,0.000022987035,0.00008172041,0.0006243363,0.00049957377,0.010247907,0.9618943,0.00012900493,0.005840443,0.000054419987],"about_ca_topic_score_codex":0.00060755137,"about_ca_topic_score_gemma":0.0010742797,"teacher_disagreement_score":0.001728473,"about_ca_system_score_codex":0.0002283786,"about_ca_system_score_gemma":0.00023083948,"threshold_uncertainty_score":0.005782306},"labels":[],"label_agreement":null},{"id":"W4399039132","doi":"10.1109/access.2024.3406262","title":"Unlocking Dual Utility: 1D-CNN for Milling Tool Health Assessment and Experimental Optimization","year":2024,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Bottleneck; Computer science; Robustness (evolution); Dual (grammatical number); Convolutional neural network; Artificial intelligence; Data mining; Machine learning; Precision and recall; Raw data; Embedded system","score_opus":0.03453877935168125,"score_gpt":0.3733047644817774,"score_spread":0.33876598513009615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399039132","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17330036,0.0010011885,0.81704,0.00085690117,0.00013147999,0.00009566267,0.00048099918,0.0031274704,0.0039659413],"genre_scores_gemma":[0.8850846,0.0002997628,0.112204924,0.0002884988,0.000028764314,0.0001236109,0.00048744847,0.00014203218,0.0013402782],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994874,0.000105522595,0.000024420553,0.00016049722,0.00016429392,0.000057817255],"domain_scores_gemma":[0.9989237,0.0004946013,0.00012604405,0.00023030183,0.00018705771,0.000038242815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001610329,0.0012056074,0.00056016084,0.00047024334,0.00018764778,0.000971428,0.0011748251,0.0010481582,0.0010980248],"category_scores_gemma":[0.0050783358,0.00044214283,0.0004763456,0.00032629858,0.00078674173,0.0013960632,0.0011001659,0.0011059818,0.00028957028],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024219029,0.00013244974,0.0048505086,0.0001997785,0.00009274965,0.00010187178,0.00005218193,0.83948153,0.026218588,0.0036957937,0.0016062417,0.12332617],"study_design_scores_gemma":[0.0000039600795,0.00003919787,0.00052005856,0.000008316946,0.000009376525,0.000014528727,0.000006995848,0.9903582,0.007008165,0.0016319993,0.00039080484,0.000008325405],"about_ca_topic_score_codex":0.004659542,"about_ca_topic_score_gemma":0.0071763247,"teacher_disagreement_score":0.004659542,"about_ca_system_score_codex":0.0010365443,"about_ca_system_score_gemma":0.0009394841,"threshold_uncertainty_score":0.009264827},"labels":[],"label_agreement":null},{"id":"W4399141144","doi":"10.1139/tcsme-2024-0018","title":"Parametric optimization in drilling of sisal–glass reinforced epoxy composites using Taguchi grey relational analysis method","year":2024,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Taguchi methods; Grey relational analysis; Epoxy; SISAL; Composite material; Materials science; Parametric statistics; Drilling; Orthogonal array; Structural engineering; Engineering; Mathematics","score_opus":0.013584315711302941,"score_gpt":0.24434668750706068,"score_spread":0.23076237179575773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399141144","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20369014,0.00028810286,0.79366857,0.000043494085,0.000009440946,0.00008633275,0.00002984539,0.00013488682,0.0020492014],"genre_scores_gemma":[0.82667476,0.00021253094,0.17208385,0.000010385196,0.0000024540157,0.000094298695,0.000026980983,0.000022776063,0.00087194744],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99934036,0.00027386192,0.000028367827,0.00007487753,0.00023578356,0.000046719015],"domain_scores_gemma":[0.9994893,0.00035768564,0.00006304889,0.000022408894,0.00005869947,0.000008831196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011623328,0.0005042881,0.000587466,0.00051935116,0.00021783999,0.00061699864,0.0004025219,0.00039277106,0.0007286918],"category_scores_gemma":[0.0012820985,0.00033081693,0.00069083343,0.0004471315,0.00037224253,0.0004061785,0.00037750564,0.00032538775,0.00011236207],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020579268,0.00011732234,0.0015407053,0.00034647723,0.00005594395,0.00010478764,0.00028090135,0.8212611,0.10164213,0.0045742304,0.000117986485,0.06975266],"study_design_scores_gemma":[0.0000054358147,0.00018041524,0.0006816519,0.0000070114675,0.000016522134,0.000021645646,0.000042316547,0.9790877,0.018950721,0.00066592486,0.00032916665,0.0000114669865],"about_ca_topic_score_codex":0.0015434846,"about_ca_topic_score_gemma":0.0024370549,"teacher_disagreement_score":0.0015434846,"about_ca_system_score_codex":0.00043929715,"about_ca_system_score_gemma":0.0005218949,"threshold_uncertainty_score":0.0061470866},"labels":[],"label_agreement":null},{"id":"W4399358523","doi":"10.1016/j.tws.2024.112049","title":"Prediction of machining deformation for circular metallic plates under residual stress and clamping force in turning","year":2024,"lang":"en","type":"article","venue":"Thin-Walled Structures","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China; Société Canadienne de Pédiatrie","keywords":"Clamping; Machining; Residual stress; Deformation (meteorology); Materials science; Coupling (piping); Structural engineering; Stress (linguistics); Mechanical engineering; Composite material; Metallurgy; Engineering","score_opus":0.013672687709366868,"score_gpt":0.2387179168540473,"score_spread":0.22504522914468045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399358523","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9599282,0.00019458232,0.035568133,0.00009240328,0.000030609484,0.00002833345,0.00005463364,0.00024042904,0.0038627002],"genre_scores_gemma":[0.9982576,0.000020748077,0.0013781661,0.0000034180323,0.0000018376755,0.000004895554,0.000016975222,0.000011060662,0.00030537762],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999105,0.000015802225,0.0000032171258,0.000018702734,0.000025007987,0.000026777352],"domain_scores_gemma":[0.9994423,0.00037411926,0.000045954144,0.000030532672,0.00007196508,0.00003513796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024544366,0.00049416965,0.0005356077,0.00042722357,0.00039848743,0.00050981576,0.0004633185,0.001260673,0.00074196997],"category_scores_gemma":[0.0008656313,0.0003894104,0.00048094202,0.00023029408,0.00071578205,0.00022185023,0.0002327432,0.0003752529,0.000100072306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000993758,0.000026119775,0.00158712,0.00002984571,0.000009321271,0.00012991231,0.00003112524,0.98707473,0.007921743,0.00041940887,0.00009072991,0.0025806536],"study_design_scores_gemma":[0.0000037140217,0.000029240442,0.0009821798,0.0000017660716,0.0000026548232,0.000010383105,0.000008154473,0.99760336,0.0012687651,0.000060418257,0.000026315533,0.0000031375425],"about_ca_topic_score_codex":0.008941875,"about_ca_topic_score_gemma":0.0054928814,"teacher_disagreement_score":0.008941875,"about_ca_system_score_codex":0.00055333343,"about_ca_system_score_gemma":0.00055296125,"threshold_uncertainty_score":0.017779708},"labels":[],"label_agreement":null},{"id":"W4399555617","doi":"10.1016/j.cirpj.2024.05.018","title":"Identification of dynamic coefficient matrix for drilling process simulations from measured tool geometry, axial force and torque","year":2024,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Torque; Process (computing); Identification (biology); Matrix (chemical analysis); Drilling; Mechanical engineering; Geometry; Engineering; Control theory (sociology); Structural engineering; Computer science; Mathematics; Physics; Materials science; Control (management); Artificial intelligence","score_opus":0.005717566469279433,"score_gpt":0.2666975760396359,"score_spread":0.26098000957035644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399555617","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.322337,0.00013205681,0.6680187,0.00019239384,0.000039929288,0.00014357232,0.0004877576,0.0014637243,0.0071848603],"genre_scores_gemma":[0.9664736,0.000047750364,0.03181616,0.000017410703,0.000003869722,0.0001038355,0.00020218747,0.00007339021,0.0012616416],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998963,0.000024707515,0.0000059558633,0.00002021974,0.00003691056,0.000015888254],"domain_scores_gemma":[0.99923015,0.00046718743,0.00007803146,0.000042962085,0.00015998805,0.000021722266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034251116,0.00050879316,0.00039688588,0.00037695075,0.00039442576,0.00038573047,0.0004299603,0.0008494107,0.0021734538],"category_scores_gemma":[0.0016433086,0.00046625055,0.0003927909,0.00027574642,0.00022793091,0.0003932924,0.00032272527,0.0006595455,0.00035758203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004965409,0.00003809962,0.00073072937,0.00005995369,0.0000138624355,0.000055126686,0.000044714492,0.98464495,0.005671743,0.0008243799,0.00018909822,0.0076778247],"study_design_scores_gemma":[0.0000059918357,0.0000105679865,0.00021313348,0.0000026315133,0.0000019242611,0.000006641472,0.000006419039,0.9983139,0.0012202485,0.00009903473,0.00011629315,0.0000031442512],"about_ca_topic_score_codex":0.013121203,"about_ca_topic_score_gemma":0.010271607,"teacher_disagreement_score":0.013121203,"about_ca_system_score_codex":0.00029401155,"about_ca_system_score_gemma":0.00089985016,"threshold_uncertainty_score":0.026089609},"labels":[],"label_agreement":null},{"id":"W4399563369","doi":"10.1109/tmag.2024.3413539","title":"Differential Model-Based Parameter Estimation of IPMSMs From Multi-State Measurements","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Estimation; Differential (mechanical device); State (computer science); Estimation theory; Control theory (sociology); Algorithm; Physics; Artificial intelligence; Thermodynamics","score_opus":0.029945121535041544,"score_gpt":0.26144312137144593,"score_spread":0.2314979998364044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399563369","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016550241,0.00008872711,0.9814363,0.00004545831,0.000022511567,0.000027773167,0.000062338855,0.000586293,0.0011802936],"genre_scores_gemma":[0.8932773,0.00022223819,0.10402979,0.00007041258,0.000020460766,0.00009755766,0.00034937842,0.00009838745,0.0018345627],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995938,0.00006106059,0.00002846685,0.00012909021,0.00016174147,0.000025886384],"domain_scores_gemma":[0.9995548,0.00013068777,0.00008722927,0.00010720138,0.00010805711,0.000011976966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042430984,0.00081460335,0.0006153355,0.0005327521,0.0003296693,0.0006321221,0.0007765157,0.00055554666,0.0009812776],"category_scores_gemma":[0.0018741,0.00046101486,0.00044089073,0.000570254,0.0003921586,0.0013558838,0.000771816,0.0009452389,0.00046531108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020379922,0.00015769964,0.0050643766,0.00047297738,0.00012575778,0.00025844286,0.00032907544,0.60158324,0.08328195,0.010028461,0.0017152593,0.29677895],"study_design_scores_gemma":[0.0000056521435,0.000035375182,0.0008512116,0.000009833222,0.000010156068,0.000049506238,0.000013964902,0.9872751,0.009043425,0.0016911994,0.0010009246,0.00001355898],"about_ca_topic_score_codex":0.0019173,"about_ca_topic_score_gemma":0.0026101873,"teacher_disagreement_score":0.0019173,"about_ca_system_score_codex":0.00042892972,"about_ca_system_score_gemma":0.0005484834,"threshold_uncertainty_score":0.003812313},"labels":[],"label_agreement":null},{"id":"W4399567130","doi":"10.1115/1.4065726","title":"Effects of Failure Criteria on Quantitatively Determining the Machining Mechanics for CFRP With Different Tool Rake Angles","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rake angle; Rake; Machining; Structural engineering; Materials science; Mechanical engineering; Damage mechanics; Engineering; Computer science; Finite element method","score_opus":0.006104660542343288,"score_gpt":0.22928828232469312,"score_spread":0.22318362178234982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399567130","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98446137,0.00015697414,0.014746582,0.00000968711,0.0000054947436,0.000023477654,0.000044326363,0.000058076177,0.00049398636],"genre_scores_gemma":[0.9984534,0.000017526098,0.0014531724,0.0000020054188,4.595287e-7,0.000006189644,0.000013660459,0.0000051461952,0.000048493854],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993405,0.00015699473,0.000041744126,0.00011043474,0.00027003142,0.00008035785],"domain_scores_gemma":[0.9974037,0.001782791,0.00031955133,0.00021086978,0.00024663899,0.000036431327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012387342,0.0007538853,0.0003289635,0.00067634095,0.00020604179,0.0003858921,0.00030452822,0.00060000917,0.00051484443],"category_scores_gemma":[0.0030241797,0.0002491199,0.00041996443,0.00024056739,0.0004519047,0.00040047287,0.00025173175,0.00029394706,0.00008440087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088022347,0.0001364924,0.018515248,0.00021055488,0.000054659347,0.00021558699,0.00014568627,0.42135015,0.5383155,0.0006532519,0.00010441738,0.019418204],"study_design_scores_gemma":[0.000015577765,0.00094904314,0.022367975,0.000024450233,0.00003771573,0.00011216965,0.000074892174,0.56057006,0.41526517,0.00023487375,0.0002971103,0.00005096946],"about_ca_topic_score_codex":0.0010526056,"about_ca_topic_score_gemma":0.0012279378,"teacher_disagreement_score":0.0012387342,"about_ca_system_score_codex":0.00033091815,"about_ca_system_score_gemma":0.00012577882,"threshold_uncertainty_score":0.0065511465},"labels":[],"label_agreement":null},{"id":"W4399765925","doi":"10.1016/j.cirpj.2024.06.003","title":"A multiscale finite element modeling for predicting the surface integrity induced by thermo-mechanical loads during high-speed milling of Ti-6Al-4V","year":2024,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Finite element method; Materials science; Surface integrity; Surface (topology); Mechanical engineering; Structural engineering; Composite material; Engineering; Surface roughness; Geometry; Mathematics","score_opus":0.012045492050963379,"score_gpt":0.2460553869781955,"score_spread":0.23400989492723212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399765925","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8322213,0.00020978159,0.16284403,0.00011452103,0.00004903479,0.00005601396,0.00015089913,0.00037220278,0.003982269],"genre_scores_gemma":[0.9911608,0.000043124834,0.008190825,0.000009184189,0.0000036465592,0.000019174528,0.00003800009,0.00002066835,0.0005145547],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999336,0.000007860279,0.0000034243456,0.000012176699,0.000031307816,0.000011576614],"domain_scores_gemma":[0.99984574,0.000064912325,0.0000274746,0.000019884179,0.000029695993,0.000012270329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018516854,0.0003010681,0.00035355656,0.00024495364,0.00026103522,0.00040525125,0.00058047887,0.0008846936,0.0008945939],"category_scores_gemma":[0.00047340238,0.00028761922,0.00041663245,0.00018620677,0.0003340056,0.0003240853,0.00027646322,0.0002954753,0.000116787414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007240971,0.0000725989,0.0017832963,0.000041938747,0.000017827437,0.00008483487,0.000058496513,0.9461949,0.04344085,0.0008189476,0.00014082994,0.007273216],"study_design_scores_gemma":[0.0000017379526,0.000015846657,0.00043783706,9.383861e-7,0.0000024798437,0.0000053529698,0.0000053057383,0.9981805,0.00126468,0.000038262715,0.000045080247,0.0000019005972],"about_ca_topic_score_codex":0.0043588565,"about_ca_topic_score_gemma":0.00479653,"teacher_disagreement_score":0.0043588565,"about_ca_system_score_codex":0.00038296345,"about_ca_system_score_gemma":0.00047525638,"threshold_uncertainty_score":0.008666992},"labels":[],"label_agreement":null},{"id":"W4399827438","doi":"10.21926/rpm.2402013","title":"The Effect of Rake Angle and Cutting Edge Radius on the Orthogonal Cutting Process of Ti6Al4V Alloy","year":2024,"lang":"en","type":"article","venue":"Recent Progress in Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Rake angle; Enhanced Data Rates for GSM Evolution; Titanium alloy; RADIUS; Materials science; Alloy; Process (computing); Rake; Metallurgy; Mechanical engineering; Computer science; Engineering; Machining; Artificial intelligence","score_opus":0.006209789630735693,"score_gpt":0.2669194422062818,"score_spread":0.26070965257554607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399827438","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99476385,0.001151728,0.0034425915,0.000010502505,0.000009722692,0.0000073263313,0.000021583162,0.00003355898,0.0005590172],"genre_scores_gemma":[0.99801683,0.00024015219,0.0015207136,0.0000046925443,0.0000031770937,0.0000026081127,0.000021259946,0.000014694376,0.0001758711],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99956137,0.0000666554,0.00004089991,0.00009296547,0.00016481218,0.0000732959],"domain_scores_gemma":[0.9979674,0.0011187015,0.0005630694,0.00011560074,0.00017530544,0.000059843067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006065311,0.00035855197,0.0004021985,0.00031055897,0.0002093293,0.00037457846,0.00027443975,0.00030741846,0.0005758615],"category_scores_gemma":[0.0017390868,0.0002565748,0.000241838,0.00023631238,0.00028007076,0.00037329868,0.00018639062,0.00024115713,0.00015483687],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002788206,0.00014293227,0.013871286,0.0005152346,0.00006172507,0.0003237968,0.00032298028,0.026517816,0.89630556,0.00017724166,0.00010803972,0.05886506],"study_design_scores_gemma":[0.00003388406,0.0036002516,0.09019342,0.000037533104,0.00016230151,0.00058137876,0.00027331777,0.030546535,0.87217766,0.0001202328,0.002195575,0.000077861165],"about_ca_topic_score_codex":0.0005265501,"about_ca_topic_score_gemma":0.0012747032,"teacher_disagreement_score":0.0006065311,"about_ca_system_score_codex":0.00019211536,"about_ca_system_score_gemma":0.00019203899,"threshold_uncertainty_score":0.0032076836},"labels":[],"label_agreement":null},{"id":"W4399922291","doi":"10.18280/mmep.110617","title":"Application of Grey-Taguchi Method Optimizes the Structural Friction Clutch Disc","year":2024,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Clutch; Taguchi methods; Materials science; Mechanical engineering; Structural engineering; Computer science; Engineering; Composite material","score_opus":0.010583740590815035,"score_gpt":0.2363628792743466,"score_spread":0.22577913868353156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399922291","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13296737,0.00066252577,0.8616243,0.000069210204,0.00004333882,0.0001351874,0.0000461525,0.0004793848,0.00397265],"genre_scores_gemma":[0.7564309,0.00034475746,0.24120618,0.00004326857,0.000008723664,0.00016881399,0.00007320707,0.00010332893,0.0016208222],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993345,0.0001243655,0.00003705151,0.00017043986,0.00025526612,0.00007831629],"domain_scores_gemma":[0.99972075,0.00013664924,0.00004261599,0.000020887444,0.00006887465,0.000010175971],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012114733,0.0011021112,0.0009316093,0.00083651586,0.00030636572,0.00092448643,0.00077705015,0.0006663507,0.001052549],"category_scores_gemma":[0.0012903964,0.00055493356,0.0009124598,0.0006751891,0.0003764087,0.00052717683,0.0003923953,0.00045425424,0.0002914862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021913504,0.00025902942,0.005319038,0.00085309055,0.00013145639,0.0002157819,0.00036470106,0.58985144,0.20940736,0.0043581803,0.00092872203,0.18809201],"study_design_scores_gemma":[0.00004014473,0.0004651049,0.0024937282,0.000024011251,0.000093888244,0.000079229394,0.00007244605,0.9315682,0.061391786,0.0015710125,0.0021567703,0.000043676748],"about_ca_topic_score_codex":0.002686264,"about_ca_topic_score_gemma":0.0042905193,"teacher_disagreement_score":0.002686264,"about_ca_system_score_codex":0.0006643036,"about_ca_system_score_gemma":0.0009863822,"threshold_uncertainty_score":0.006406963},"labels":[],"label_agreement":null},{"id":"W4400351541","doi":"10.1109/intermagshortpapers61879.2024.10576958","title":"Differential Model based Parameter Estimation of IPMSMs from Multi-state Measurements","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Differential (mechanical device); Computer science; State (computer science); Estimation; Estimation theory; Control theory (sociology); Algorithm; Artificial intelligence; Engineering; Aerospace engineering","score_opus":0.03566672977640617,"score_gpt":0.2717718578279677,"score_spread":0.23610512805156153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400351541","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016024798,0.000101293306,0.98228747,0.00004112758,0.00001596752,0.000022078004,0.00005946736,0.00040420028,0.0010435508],"genre_scores_gemma":[0.9137303,0.00023263214,0.083722316,0.000057977508,0.00001974268,0.00012052913,0.0003643457,0.00007343442,0.0016787993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996722,0.00006271223,0.000022868831,0.00010718534,0.00011372049,0.000021408832],"domain_scores_gemma":[0.9995548,0.000161814,0.00009098896,0.00008471274,0.00009473688,0.000012837392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038365897,0.0009363814,0.0007103511,0.0005160086,0.00030985245,0.00066449767,0.0007694282,0.0006483319,0.00084033865],"category_scores_gemma":[0.001413577,0.0005099268,0.0005458908,0.00054802746,0.000396919,0.0013104778,0.00085253257,0.00092267536,0.0003760832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000115971154,0.000083494175,0.0028167302,0.00033400152,0.00009010927,0.00020284238,0.00021248336,0.8190863,0.04034394,0.006014669,0.0009219704,0.12977745],"study_design_scores_gemma":[0.0000034253612,0.000027364307,0.00048050593,0.0000057251914,0.0000073563338,0.000028334578,0.000010395297,0.9940282,0.0035561037,0.0012377924,0.00060662994,0.000008086807],"about_ca_topic_score_codex":0.0018946463,"about_ca_topic_score_gemma":0.0020838224,"teacher_disagreement_score":0.0018946463,"about_ca_system_score_codex":0.00039098272,"about_ca_system_score_gemma":0.00046192852,"threshold_uncertainty_score":0.003767252},"labels":[],"label_agreement":null},{"id":"W4400378793","doi":"10.1016/j.cirpj.2024.06.012","title":"Special Issue on Machinability Revisited: Integrated Machining Performance For Assessment of Cutting Tools (IMPACT)","year":2024,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machinability; Machining; Manufacturing engineering; Engineering; Mechanical engineering; Computer science","score_opus":0.011988094638059693,"score_gpt":0.29858136367619403,"score_spread":0.2865932690381343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400378793","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015175153,0.04797026,0.0028990128,0.040408757,0.88494754,0.000088009445,0.0003514134,0.00027165285,0.021545889],"genre_scores_gemma":[0.009950014,0.029445898,0.0014270649,0.015957879,0.88926834,0.00008661866,0.0004433304,0.00038226764,0.053038534],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.996179,0.00034601174,0.00054131326,0.0007705788,0.0018166852,0.00034649865],"domain_scores_gemma":[0.99196774,0.002275311,0.00062027073,0.0005438904,0.003781789,0.00081103644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049521737,0.0020864895,0.0031992914,0.0030950045,0.0018529166,0.0073795784,0.0047312537,0.011372983,0.027310276],"category_scores_gemma":[0.0080655,0.0010213047,0.0018617733,0.0022137424,0.002353405,0.0044084704,0.0025349366,0.0067325714,0.012334781],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014939158,0.00011208178,0.00033293103,0.0011042545,0.000053112497,0.00033537796,0.000049947368,0.00041828118,0.0017710347,0.004159073,0.9458536,0.045660898],"study_design_scores_gemma":[0.000030343039,0.0002290809,0.0028025815,0.00055716484,0.00008736682,0.0008176288,0.000071901086,0.0009480021,0.0015872088,0.0049242433,0.9878928,0.000051544215],"about_ca_topic_score_codex":0.0017913354,"about_ca_topic_score_gemma":0.0021525035,"teacher_disagreement_score":0.027310276,"about_ca_system_score_codex":0.0018644973,"about_ca_system_score_gemma":0.002232847,"threshold_uncertainty_score":0.091362},"labels":[],"label_agreement":null},{"id":"W4400381330","doi":"10.1016/j.eswa.2024.124656","title":"Accurate synthesis of sensor-to-machined-surface image generation in carbon fiber-reinforced plastic drilling","year":2024,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Delamination (geology); Drilling; Durability; Fibre-reinforced plastic; Computer science; Materials science; Machining; Mechanical engineering; Composite material; Geology; Engineering","score_opus":0.00873153816691692,"score_gpt":0.24358766910832275,"score_spread":0.23485613094140584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400381330","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053517528,0.00016293736,0.94428355,0.000059336486,0.00003571607,0.00003342972,0.000044843724,0.00070208893,0.0011605694],"genre_scores_gemma":[0.8105568,0.00016614169,0.1877908,0.000032717642,0.000011109992,0.00005193978,0.000109813154,0.00007141767,0.0012092323],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99990773,0.000011219764,0.0000035155915,0.000021511225,0.000045848526,0.0000101416945],"domain_scores_gemma":[0.99983823,0.000060697224,0.0000243067,0.000020547248,0.000048119513,0.00000800498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017787976,0.00034957888,0.0002678876,0.00017809562,0.00009488856,0.0002450779,0.00040196124,0.00038747833,0.000750874],"category_scores_gemma":[0.0005298877,0.0002160252,0.00029877343,0.00013825858,0.00019456643,0.00034641605,0.0002265877,0.0003076759,0.00024621995],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001811854,0.000062205196,0.00093717093,0.00016596945,0.000018489178,0.00021000102,0.00013108946,0.63990843,0.12959717,0.0025426936,0.00091408996,0.22533159],"study_design_scores_gemma":[0.0000034941377,0.000036262307,0.00020711917,0.0000023566927,0.0000021054761,0.000027149681,0.0000044893563,0.9857137,0.013411598,0.00019702966,0.00039017343,0.000004564013],"about_ca_topic_score_codex":0.0018665297,"about_ca_topic_score_gemma":0.0017569512,"teacher_disagreement_score":0.0018665297,"about_ca_system_score_codex":0.00023843416,"about_ca_system_score_gemma":0.00035496996,"threshold_uncertainty_score":0.0037112832},"labels":[],"label_agreement":null},{"id":"W4400811182","doi":"10.1115/1.4066033","title":"Effect of Shear Localization on Surface Residual Stress Distribution in Machining of Waspaloy","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Ontario Ministry of Research, Innovation and Science","keywords":"Machining; Residual stress; Shear stress; Shear (geology); Materials science; Surface (topology); Residual; Geology; Metallurgy; Composite material; Geometry; Mathematics","score_opus":0.003246423213663085,"score_gpt":0.22537577052929877,"score_spread":0.2221293473156357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400811182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969639,0.000031258507,0.0027770796,0.0000065745785,0.0000017551891,0.0000025508446,0.000008610013,0.000024226796,0.00018402858],"genre_scores_gemma":[0.999585,0.0000074177033,0.00034815964,6.8268736e-7,2.0846936e-7,0.0000011816261,0.0000057084935,0.0000025242782,0.00004910601],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999223,0.000010136486,0.000004243968,0.000015515709,0.000028285605,0.000019531562],"domain_scores_gemma":[0.99985504,0.000062544495,0.000035377736,0.000015613194,0.000021353182,0.000010081884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016440822,0.0001713683,0.00017977602,0.00015849575,0.00012434457,0.00029050632,0.00021657751,0.00018398043,0.00029608497],"category_scores_gemma":[0.00043721581,0.00015818623,0.00016959969,0.00011122727,0.00039346097,0.00016796107,0.00014691029,0.0001368568,0.000043950276],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000357189,0.000045401262,0.0067832456,0.000094092,0.000030881205,0.0005678551,0.00023004656,0.13902715,0.84432554,0.00051207433,0.00006535806,0.007961153],"study_design_scores_gemma":[0.000032784294,0.00070365705,0.017254023,0.0000103914745,0.000025464322,0.000118343385,0.00013590981,0.63057345,0.35053593,0.00021176251,0.00037367982,0.00002460909],"about_ca_topic_score_codex":0.0012462611,"about_ca_topic_score_gemma":0.0008781922,"teacher_disagreement_score":0.0012462611,"about_ca_system_score_codex":0.00024644047,"about_ca_system_score_gemma":0.00016991048,"threshold_uncertainty_score":0.002478063},"labels":[],"label_agreement":null},{"id":"W4401422007","doi":"10.1007/978-3-031-60255-9_11","title":"Optimization of Initial Cutting Parameters for a Turning Process Based on the Response Surface Methodology","year":2024,"lang":"en","type":"book-chapter","venue":"Springer proceedings in earth and environmental sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Université du Québec à Trois-Rivières; Dawson College","funders":"","keywords":"Response surface methodology; Process (computing); Process optimization; Computer science; Engineering; Machine learning; Chemical engineering","score_opus":0.032249304352814256,"score_gpt":0.2778620791323045,"score_spread":0.24561277477949023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401422007","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.067019664,0.0009657634,0.92030895,0.00011300521,0.000071414586,0.000117639924,0.00005729945,0.0005851314,0.010761116],"genre_scores_gemma":[0.7150709,0.000762681,0.27991325,0.00005086827,0.000029760524,0.00024169846,0.00019828007,0.0003134519,0.0034192028],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997272,0.00007590631,0.000011361253,0.000036511603,0.00010886638,0.000040188665],"domain_scores_gemma":[0.999689,0.00018342744,0.000024192423,0.000019701642,0.00007632638,0.000007415476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000722226,0.0008536242,0.0009997702,0.000722753,0.0003055146,0.0008713914,0.0006003326,0.0008964681,0.0019472972],"category_scores_gemma":[0.0008632269,0.00043668682,0.0012772906,0.00061763375,0.00036343953,0.00043010974,0.000347728,0.00090092816,0.00046251892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014667326,0.00010178844,0.0003209207,0.00029679094,0.00005606324,0.00007318429,0.0000806861,0.83199435,0.046562083,0.004136573,0.0007363763,0.11549453],"study_design_scores_gemma":[0.000016073676,0.0001939885,0.00038692117,0.000020602709,0.000024827734,0.000029680521,0.000026460608,0.98690367,0.009772251,0.0014457215,0.0011645155,0.00001528009],"about_ca_topic_score_codex":0.0011262686,"about_ca_topic_score_gemma":0.001580885,"teacher_disagreement_score":0.0019472972,"about_ca_system_score_codex":0.00034465484,"about_ca_system_score_gemma":0.0005846663,"threshold_uncertainty_score":0.006514311},"labels":[],"label_agreement":null},{"id":"W4401459608","doi":"10.1007/s11071-024-10109-9","title":"Correction to: Flexural–torsional modal interaction in MEMS actuators initiated by minuscule asymmetry","year":2024,"lang":"en","type":"article","venue":"Nonlinear Dynamics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Modal; Asymmetry; Actuator; Microelectromechanical systems; Modal analysis; Structural engineering; Engineering; Computer science; Physics; Materials science; Artificial intelligence; Finite element method; Composite material; Optoelectronics; Particle physics","score_opus":0.007958475727007426,"score_gpt":0.2665009585214029,"score_spread":0.25854248279439546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401459608","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005265873,0.0006680863,0.0019828642,0.0095290635,0.983752,0.000027873524,0.000640403,0.0005613685,0.0023117147],"genre_scores_gemma":[0.076006316,0.006379818,0.021015232,0.032543495,0.42295945,0.0004787226,0.0044963486,0.004358297,0.4317623],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973181,0.00026167944,0.0004323418,0.0004310828,0.0012111643,0.00034571448],"domain_scores_gemma":[0.98843926,0.0021514115,0.00068606494,0.0008884303,0.007031327,0.00080359797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013710128,0.0030670215,0.002787583,0.0038288604,0.0032037834,0.0026621658,0.0036636754,0.0064293086,0.08508643],"category_scores_gemma":[0.02048181,0.0013780935,0.0018296463,0.002151283,0.0021521572,0.0025530704,0.0022348482,0.006770909,0.026286747],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015790333,0.000014226474,0.00014862278,0.00039629376,0.000030441557,0.0007134301,0.000044337423,0.00034867084,0.00074281136,0.0026934152,0.9802321,0.014477691],"study_design_scores_gemma":[0.00008959425,0.00005497231,0.0018304875,0.00014494288,0.00004279064,0.0015856399,0.00010189888,0.00214503,0.002332692,0.0024757816,0.98912257,0.00007363246],"about_ca_topic_score_codex":0.008788558,"about_ca_topic_score_gemma":0.01352581,"teacher_disagreement_score":0.08508643,"about_ca_system_score_codex":0.003673256,"about_ca_system_score_gemma":0.0031474615,"threshold_uncertainty_score":0.28464246},"labels":[],"label_agreement":null},{"id":"W4401595547","doi":"10.1139/tcsme-2024-0085","title":"Development of an analytical model to investigate the effect of tool geometry and cutting parameters on the milling performance of Inconel 718","year":2024,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Inconel; Materials science; Mechanical engineering; Geometry; End milling; Machining; Engineering drawing; Metallurgy; Engineering; Mathematics","score_opus":0.013845846118109184,"score_gpt":0.22118961479456567,"score_spread":0.20734376867645649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401595547","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13337584,0.00076950167,0.8463063,0.00028814707,0.00006472248,0.00012777855,0.00018556241,0.0006777533,0.018204406],"genre_scores_gemma":[0.91816664,0.00081914425,0.0732244,0.00004572989,0.000017747534,0.00017939287,0.00013736909,0.00006518665,0.0073444913],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999848,0.00001948773,0.0000061371993,0.000024967865,0.0000829462,0.000018447445],"domain_scores_gemma":[0.9998523,0.000052645308,0.000022342761,0.000014733508,0.00005416917,0.000003953658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026451057,0.00045487558,0.00052283966,0.0003770111,0.0003617147,0.00047080373,0.001021745,0.0008752555,0.0011045502],"category_scores_gemma":[0.0006014795,0.00033729814,0.0004894331,0.00033002277,0.0003006175,0.0005840751,0.00026965007,0.00044241283,0.00040719603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002479891,0.00003826744,0.0007920367,0.00009451999,0.000013288377,0.00018534166,0.00010230122,0.95228195,0.021172477,0.0059569743,0.0004007553,0.018937374],"study_design_scores_gemma":[0.0000030374101,0.00001865965,0.00012443167,0.0000049021523,0.000005086821,0.000023124892,0.000010007289,0.996849,0.0019302021,0.00035012362,0.0006773757,0.0000039968863],"about_ca_topic_score_codex":0.006448133,"about_ca_topic_score_gemma":0.0050425665,"teacher_disagreement_score":0.006448133,"about_ca_system_score_codex":0.00043368564,"about_ca_system_score_gemma":0.0009116534,"threshold_uncertainty_score":0.0128211975},"labels":[],"label_agreement":null},{"id":"W4401806896","doi":"10.1007/s11665-024-09879-5","title":"Analysis of Machining a Sinter-Hardened Powder Metallurgy Steel: Significance of Localized Densification of Uncut Chip Material during Chip Formation","year":2024,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Machinability; Machining; Materials science; Chip formation; Chip; Microstructure; Metallurgy; Composite material; Tool wear; Shear (geology); Porosity; Mechanical engineering","score_opus":0.00723420408937552,"score_gpt":0.2136098685427516,"score_spread":0.20637566445337607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401806896","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956208,0.00013734559,0.003274203,0.0000150444575,0.0000054226825,0.00000985373,0.00010102158,0.00005470211,0.00078153564],"genre_scores_gemma":[0.9979773,0.000034890854,0.0011966381,0.0000056417466,0.0000013170395,0.0000043235777,0.00009885181,0.00001572774,0.0006654139],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998858,0.000007513896,0.000003963455,0.000027635662,0.00005803031,0.000017050876],"domain_scores_gemma":[0.99972254,0.000110609275,0.000043193482,0.000025832502,0.00008225601,0.000015576308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001410881,0.00019371603,0.0002665869,0.00031977714,0.00026553948,0.00025343965,0.00027436388,0.00041375193,0.0012986801],"category_scores_gemma":[0.0003189715,0.00023215209,0.00017051683,0.0002785465,0.0003317037,0.00021644044,0.000082445025,0.00022667953,0.00016170746],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028963672,0.000022895454,0.002575395,0.000075434946,0.000010071901,0.0001335496,0.00009958809,0.0023735417,0.9901564,0.000086805056,0.000074855896,0.00410183],"study_design_scores_gemma":[0.000016196924,0.0004421022,0.08843134,0.0000054391735,0.000021508287,0.00017153144,0.00014853674,0.029692678,0.8801654,0.00004685028,0.000845065,0.000013447853],"about_ca_topic_score_codex":0.0028099795,"about_ca_topic_score_gemma":0.0055303504,"teacher_disagreement_score":0.0028099795,"about_ca_system_score_codex":0.00035571202,"about_ca_system_score_gemma":0.00027625007,"threshold_uncertainty_score":0.00558728},"labels":[],"label_agreement":null},{"id":"W4401871413","doi":"10.1016/j.heliyon.2024.e36925","title":"Investigating the impact of drill material on hole quality in jute/palm fiber reinforced hybrid composite drilling with uncertainty analysis","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure","funders":"King Saud University; United Arab Emirates University; Mitacs; McGill University","keywords":"Drill; Delamination (geology); Drilling; Carbide; Materials science; High-speed steel; Composite material; Composite number; Metallurgy; Geology","score_opus":0.011551583160994576,"score_gpt":0.28034504767193863,"score_spread":0.26879346451094405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401871413","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8444252,0.00025733342,0.15441209,0.000020267535,0.000006922663,0.000042736527,0.0000632611,0.00014962646,0.0006224536],"genre_scores_gemma":[0.9804537,0.00006085952,0.019322554,0.000003186473,0.0000012355018,0.000014034153,0.000024389457,0.000009632396,0.00011042265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994634,0.00008497798,0.000034937413,0.000080147074,0.00029030596,0.000046261735],"domain_scores_gemma":[0.9977133,0.0014734097,0.00040670898,0.00009464544,0.0002837172,0.000028235936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011300009,0.00055493513,0.00036922088,0.00066064164,0.00018079177,0.00059981307,0.00036580965,0.0005785239,0.0003076671],"category_scores_gemma":[0.0030295642,0.00037433658,0.00039698047,0.0002482365,0.00032887165,0.00069193606,0.00044865636,0.00030573577,0.000045630168],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069285906,0.00013979776,0.019887848,0.00042979998,0.00007928187,0.00027933606,0.00018022241,0.80113995,0.12436605,0.000746863,0.0000612526,0.05199677],"study_design_scores_gemma":[0.000009296448,0.00039514544,0.0071023824,0.000015710642,0.000037435042,0.0000795868,0.000071246235,0.9332467,0.058564242,0.00024621843,0.00020262144,0.00002940721],"about_ca_topic_score_codex":0.0022987658,"about_ca_topic_score_gemma":0.0031754088,"teacher_disagreement_score":0.0022987658,"about_ca_system_score_codex":0.00033540957,"about_ca_system_score_gemma":0.00038312303,"threshold_uncertainty_score":0.005976081},"labels":[],"label_agreement":null},{"id":"W4401989643","doi":"10.2139/ssrn.4940756","title":"Automated Operational Modal Analysis of Self-Excited Vibrations in Turning","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Modal; Vibration; Excited state; Operational Modal Analysis; Modal analysis; Computer science; Acoustics; Physics; Materials science; Atomic physics","score_opus":0.004393768928251052,"score_gpt":0.24572736635523434,"score_spread":0.2413335974269833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401989643","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38115963,0.00008413404,0.613921,0.000049034057,0.00001541619,0.000026277346,0.00006485676,0.0005916865,0.0040881443],"genre_scores_gemma":[0.98491204,0.000017330545,0.0144030955,0.0000049614173,0.0000041691683,0.0000089305095,0.000044285243,0.00003452825,0.00057064625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998803,0.000030240577,0.000004343807,0.0000147486535,0.000047803962,0.00002253919],"domain_scores_gemma":[0.9997358,0.00015928614,0.000019409279,0.00003233549,0.000043835364,0.000009264865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016236442,0.0002371543,0.0002778264,0.0003396672,0.0001731671,0.00038676994,0.00032930743,0.00021094782,0.0019485655],"category_scores_gemma":[0.00057369977,0.00015199983,0.0002929667,0.0001387549,0.00036178503,0.00027745898,0.00040783468,0.00027320127,0.00017662418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002539633,0.000091787246,0.001855743,0.00010538626,0.00003053126,0.0001228569,0.00022676632,0.7886965,0.064051196,0.008832505,0.00061199174,0.13512063],"study_design_scores_gemma":[0.0000026190176,0.000018454044,0.00070589443,0.0000015836985,0.0000018738315,0.00000940746,0.000021689646,0.99575716,0.0019576396,0.0013850001,0.00013634379,0.0000023560472],"about_ca_topic_score_codex":0.0013907221,"about_ca_topic_score_gemma":0.0018543095,"teacher_disagreement_score":0.0019485655,"about_ca_system_score_codex":0.00016090536,"about_ca_system_score_gemma":0.00019947714,"threshold_uncertainty_score":0.0065186024},"labels":[],"label_agreement":null},{"id":"W4402054033","doi":"10.1007/978-3-031-63276-1_40","title":"Data-Driven Bearing Capacity Prediction of Self-drilling Screw in Cold-Formed Steel Using Machine Learning","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Drilling; Bearing (navigation); Bearing capacity; Mechanical engineering; Materials science; Computer science; Geology; Artificial intelligence; Structural engineering; Engineering","score_opus":0.0221895309846437,"score_gpt":0.2226928433220722,"score_spread":0.20050331233742852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402054033","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82424587,0.00047579576,0.17057316,0.00014793513,0.00009138389,0.0000328717,0.00049149245,0.0017531238,0.0021883934],"genre_scores_gemma":[0.9910159,0.00004747125,0.0077444077,0.000009634753,0.000006789558,0.000011140275,0.0002452184,0.000025974097,0.00089343375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99994767,0.0000048308916,0.0000032289997,0.000018553492,0.000015755906,0.000009977446],"domain_scores_gemma":[0.9996145,0.00021111722,0.0000333203,0.000019610425,0.00009978893,0.000021650238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020431123,0.00046797373,0.00044577237,0.00047654333,0.00020131431,0.00032323552,0.0005247724,0.0005009985,0.0010497306],"category_scores_gemma":[0.0005747002,0.00027384437,0.00032768832,0.00030330056,0.00021925967,0.00038248455,0.00023042849,0.0003721813,0.00031073255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055844,0.00013726385,0.005812536,0.000112583286,0.0000374322,0.00014906388,0.000042680887,0.8748052,0.023313452,0.000408745,0.0015091042,0.09311346],"study_design_scores_gemma":[0.0000023585123,0.000014490389,0.0009156273,0.0000011660395,0.0000017890843,0.0000048623633,0.000003082044,0.99688643,0.0020468114,0.000070636044,0.00004980523,0.0000029531973],"about_ca_topic_score_codex":0.010491497,"about_ca_topic_score_gemma":0.013479273,"teacher_disagreement_score":0.010491497,"about_ca_system_score_codex":0.0003726171,"about_ca_system_score_gemma":0.0004241111,"threshold_uncertainty_score":0.02086085},"labels":[],"label_agreement":null},{"id":"W4402269723","doi":"10.1364/cleo_at.2024.am1c.3","title":"Preliminary Development of Thermographic Monitoring of the Laser Remelting Process","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Western University","funders":"","keywords":"Process (computing); Laser; Process development; Materials science; Thermography; Computer science; Process engineering; Engineering; Infrared; Optics","score_opus":0.009619363311835239,"score_gpt":0.2438417902021488,"score_spread":0.23422242689031356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402269723","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31713605,0.0037793347,0.66855496,0.00028003962,0.00015685955,0.00061519275,0.0007944545,0.0017834634,0.0068996856],"genre_scores_gemma":[0.7850755,0.0016541384,0.20670465,0.00008133791,0.00006328582,0.00026125315,0.0004510267,0.00015309715,0.005555713],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994885,0.00008614377,0.0000281273,0.00009778503,0.00026728492,0.00003222241],"domain_scores_gemma":[0.9989417,0.0003020005,0.00008068409,0.00013266072,0.0004878047,0.00005517437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011106905,0.00041862085,0.0003637253,0.00078153884,0.00024037641,0.00050137687,0.0006682125,0.0006178354,0.0011086055],"category_scores_gemma":[0.0014897082,0.0002502376,0.00033315265,0.0004325482,0.0002660793,0.00058631453,0.00027019926,0.0005184937,0.00032676395],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015593073,0.00006347065,0.0017063618,0.00024996343,0.000010359828,0.00006480928,0.00013804609,0.0009292616,0.95046973,0.0004571225,0.00020020986,0.04555491],"study_design_scores_gemma":[0.0000079178835,0.00071374816,0.010407535,0.000022302822,0.000029276833,0.00024551112,0.00005299449,0.008693413,0.97448564,0.00013770838,0.0051838486,0.000020157799],"about_ca_topic_score_codex":0.00084099517,"about_ca_topic_score_gemma":0.0010701653,"teacher_disagreement_score":0.0011106905,"about_ca_system_score_codex":0.00029199242,"about_ca_system_score_gemma":0.00047420157,"threshold_uncertainty_score":0.005873978},"labels":[],"label_agreement":null},{"id":"W4402299345","doi":"10.1016/j.heliyon.2024.e37337","title":"Effect of ball nose flank wear on surface integrity in high-speed hard milling of AISI 4340 steel using MQL","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Flank; Surface integrity; Metallurgy; Materials science; Ball (mathematics); Machining; Medicine; Mathematics; Anatomy; Geometry","score_opus":0.01308118138309928,"score_gpt":0.2704787159063537,"score_spread":0.2573975345232544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402299345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994388,0.00012782942,0.00035690857,0.000005324859,0.0000021248159,0.000003229093,0.000013596986,0.0000068788113,0.000045289544],"genre_scores_gemma":[0.9991872,0.000072820694,0.00052143633,0.000008046464,0.0000018093057,0.00000313328,0.000026964608,0.0000036407462,0.00017491831],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995372,0.00008169553,0.00003499368,0.00007398278,0.00020587003,0.000066240056],"domain_scores_gemma":[0.9992347,0.00022812928,0.00026983835,0.00007931855,0.00014249183,0.00004564666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000394319,0.00027142957,0.00031331522,0.00015797069,0.00017548217,0.00025909994,0.00022266335,0.00031072603,0.0005409639],"category_scores_gemma":[0.0009230416,0.00021188051,0.00030969267,0.00013557391,0.00025598935,0.00023910642,0.00026758586,0.00026283404,0.00012059741],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018695145,0.00001828962,0.00201465,0.000063666936,0.000010684899,0.00006857466,0.0000946168,0.00015070314,0.9945229,0.0000038721178,0.000011765916,0.0028532196],"study_design_scores_gemma":[0.000009287245,0.0021079506,0.050793037,0.00000706042,0.000028778848,0.00018221501,0.00019197018,0.0015012503,0.9448217,0.000014922641,0.00032769406,0.000014120793],"about_ca_topic_score_codex":0.00071944075,"about_ca_topic_score_gemma":0.0013408464,"teacher_disagreement_score":0.00071944075,"about_ca_system_score_codex":0.00017713419,"about_ca_system_score_gemma":0.00012401173,"threshold_uncertainty_score":0.0020853877},"labels":[],"label_agreement":null},{"id":"W4402454964","doi":"10.11159/icmie24.116","title":"A Novel Approach to CNC Controller Parameter Optimization by Integrating Deep Learning Model with Particle Swarm Optimization","year":2024,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Particle swarm optimization; Computer science; Multi-swarm optimization; Controller (irrigation); Artificial intelligence; Control engineering; Control theory (sociology); Engineering; Algorithm; Control (management)","score_opus":0.0050969138720885305,"score_gpt":0.19207387091463582,"score_spread":0.1869769570425473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402454964","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003032692,0.00015775807,0.9947695,0.000066790555,0.000056190693,0.000021664064,0.000013764961,0.00025991534,0.0016217249],"genre_scores_gemma":[0.53317916,0.00031603087,0.45866323,0.00028531658,0.00015432654,0.00021796867,0.00016228053,0.00019369791,0.006827999],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976224,0.0000364358,0.000014392777,0.000061807856,0.00009402936,0.000031103493],"domain_scores_gemma":[0.99969137,0.000103504404,0.000031652762,0.000036618356,0.00011541102,0.000021520376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063481875,0.0010750137,0.0012047305,0.0005429221,0.00045688977,0.00085876766,0.0012465472,0.0012066684,0.0022294142],"category_scores_gemma":[0.0009682342,0.0006544218,0.000662359,0.0005623842,0.00052948325,0.00080134976,0.0010480294,0.0015554664,0.00044984685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039737606,0.000060566043,0.00027730808,0.000046451853,0.000049994986,0.000037290996,0.000028041435,0.8986776,0.0031481448,0.006151965,0.0015006044,0.0899823],"study_design_scores_gemma":[0.000001500217,0.000005280955,0.000015663956,0.0000010325974,0.0000017288268,0.0000020402229,7.407966e-7,0.9993154,0.00013936897,0.00037853495,0.00013748632,0.000001186432],"about_ca_topic_score_codex":0.0127144335,"about_ca_topic_score_gemma":0.014650287,"teacher_disagreement_score":0.0127144335,"about_ca_system_score_codex":0.0006832174,"about_ca_system_score_gemma":0.0012901028,"threshold_uncertainty_score":0.025280893},"labels":[],"label_agreement":null},{"id":"W4402738313","doi":"10.1016/j.compositesa.2024.108491","title":"The use of digital thread for reconstruction of local fiber orientation in a compression molded pin bracket via deep learning","year":2024,"lang":"en","type":"article","venue":"Composites Part A Applied Science and Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"U.S. Department of Energy; National Nuclear Security Administration; Old Dominion University; National Science Foundation","keywords":"Materials science; Composite material; Thread (computing); Bracket; Structural engineering; Mechanical engineering; Engineering","score_opus":0.014508846406435268,"score_gpt":0.2385401187742855,"score_spread":0.22403127236785023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402738313","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2258295,0.0002876206,0.76956415,0.00025936696,0.0000888143,0.00003071419,0.00011218467,0.0013525119,0.0024751732],"genre_scores_gemma":[0.85792255,0.00013470551,0.13918313,0.00007064821,0.000014014337,0.000017617756,0.000118133314,0.000090491434,0.0024487379],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99993896,0.000007294303,0.0000025971062,0.000018823444,0.000022779888,0.000009500508],"domain_scores_gemma":[0.9998684,0.000040592506,0.000024033021,0.000025037645,0.000027120395,0.000014738945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022966367,0.00045282254,0.0003520296,0.00025642465,0.00016638605,0.00034664053,0.00045616328,0.0005920705,0.001353635],"category_scores_gemma":[0.00045275802,0.00027104683,0.00028917877,0.00025761363,0.0003427828,0.0006102372,0.00047047425,0.0005567051,0.00021837819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005784232,0.00019352885,0.004500451,0.00015970523,0.0000756122,0.0003544152,0.0001522602,0.5911401,0.11704295,0.008633881,0.002654508,0.27451426],"study_design_scores_gemma":[0.0000025558327,0.000018884688,0.00013636985,0.0000019957422,0.0000036947265,0.00001786705,0.000005001067,0.9938147,0.005446356,0.00036164705,0.0001874376,0.000003506246],"about_ca_topic_score_codex":0.002498094,"about_ca_topic_score_gemma":0.0049120015,"teacher_disagreement_score":0.002498094,"about_ca_system_score_codex":0.00034167708,"about_ca_system_score_gemma":0.00062211335,"threshold_uncertainty_score":0.0049670935},"labels":[],"label_agreement":null},{"id":"W4402756108","doi":"10.3390/jmmp8050207","title":"Feed Drive Control and Non-Linear Friction Interaction Effect on Machining Chatter Stability Prediction","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Machining; Control theory (sociology); Stability (learning theory); Control (management); Computer science; Engineering; Mechanical engineering; Artificial intelligence; Machine learning","score_opus":0.006071817186957979,"score_gpt":0.2365188982475337,"score_spread":0.2304470810605757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402756108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90705127,0.00014357608,0.09145288,0.00004810848,0.000008699062,0.000020601923,0.000028214597,0.00026137833,0.0009852484],"genre_scores_gemma":[0.9980116,0.000013877909,0.0018569314,0.0000025379363,4.574884e-7,0.0000038257426,0.000006509645,0.000006616838,0.00009758766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996196,0.00009116789,0.000020782529,0.00006832875,0.00014653697,0.000053622236],"domain_scores_gemma":[0.9950848,0.0040109907,0.00026366126,0.00020852369,0.0003852749,0.000046693993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075850345,0.00045040058,0.00033827196,0.0004080982,0.00028061762,0.0004567805,0.00032327155,0.00047637915,0.00074211846],"category_scores_gemma":[0.005000977,0.00023396978,0.0002543176,0.00015312784,0.000483102,0.00045634242,0.0002845722,0.0003847996,0.00010251919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016244455,0.0002184854,0.022418344,0.00046843654,0.00008553327,0.00050033414,0.0011787353,0.6772599,0.21457322,0.001094041,0.00023812687,0.08034039],"study_design_scores_gemma":[0.000013282543,0.00033116637,0.012444455,0.000013291072,0.000022668764,0.00007392141,0.000069753296,0.9133406,0.0734018,0.00013664445,0.00012946666,0.000022840066],"about_ca_topic_score_codex":0.0038759543,"about_ca_topic_score_gemma":0.003683792,"teacher_disagreement_score":0.0038759543,"about_ca_system_score_codex":0.00027112488,"about_ca_system_score_gemma":0.0002850857,"threshold_uncertainty_score":0.0077067614},"labels":[],"label_agreement":null},{"id":"W4402875520","doi":"10.1007/978-3-031-70428-4_50","title":"Optimization and Prediction of White Layer Thickness After Hard Turning","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Materials science; Layer (electronics); White (mutation); Composite material; Chemistry","score_opus":0.006557820013838426,"score_gpt":0.19507942768622902,"score_spread":0.1885216076723906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402875520","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.782028,0.0008185002,0.20224874,0.00022993804,0.00015538916,0.0000575696,0.00024065377,0.0012525674,0.01296861],"genre_scores_gemma":[0.98283744,0.00011121371,0.013597734,0.000021097841,0.0000108583845,0.000022122898,0.00010343792,0.00010029256,0.0031957603],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999279,0.000013592526,0.0000019161998,0.000015598642,0.000017172913,0.00002385178],"domain_scores_gemma":[0.99974936,0.00014507791,0.000029109233,0.00001670194,0.000040864285,0.000018885861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028231923,0.0007144824,0.0006724656,0.00028776296,0.00030889505,0.00065214495,0.00045540833,0.00084623945,0.0016010953],"category_scores_gemma":[0.00050490064,0.00061825244,0.00049257965,0.00025542956,0.00038856565,0.0004369138,0.0003588346,0.00050002575,0.0002463371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012291432,0.000029092875,0.00030053715,0.000025200003,0.000011687504,0.000028324157,0.000009051003,0.98327535,0.009372184,0.00031650224,0.00020527444,0.0063038506],"study_design_scores_gemma":[0.0000066013586,0.00003208774,0.00024929107,0.0000016242175,0.0000044127783,0.000002406989,0.0000037109278,0.9962477,0.0032733479,0.00010991546,0.000065880035,0.0000029577745],"about_ca_topic_score_codex":0.00600285,"about_ca_topic_score_gemma":0.0060396222,"teacher_disagreement_score":0.00600285,"about_ca_system_score_codex":0.0005942273,"about_ca_system_score_gemma":0.00054379064,"threshold_uncertainty_score":0.01193583},"labels":[],"label_agreement":null},{"id":"W4403073760","doi":"10.1002/cjce.25516","title":"A physics‐constrained hybrid residual neural network for the prediction of moisture content in a closed‐cycle drying system","year":2024,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Zhejiang Province Public Welfare Technology Application Research Project; National Natural Science Foundation of China","keywords":"Residual; Water content; Artificial neural network; Content (measure theory); Environmental science; Process engineering; Biological system; Mathematics; Computer science; Engineering; Artificial intelligence; Geotechnical engineering; Algorithm; Mathematical analysis; Biology","score_opus":0.011262098044600103,"score_gpt":0.19080028679809768,"score_spread":0.17953818875349759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403073760","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23311698,0.00058496965,0.7615214,0.0002576907,0.000078295685,0.0000598431,0.000091866634,0.0011275536,0.003161429],"genre_scores_gemma":[0.9794112,0.00009861056,0.018852787,0.000041272844,0.000008319675,0.00004483326,0.00007311521,0.000015114128,0.0014547432],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984,0.00003051873,0.000010764093,0.000057223057,0.000042388037,0.00001902043],"domain_scores_gemma":[0.9997898,0.000092946466,0.000024779118,0.0000139646245,0.00006825389,0.000010247798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050075096,0.00058941805,0.0004906749,0.00023214369,0.00026648043,0.00044408816,0.0007119831,0.000775541,0.0007733992],"category_scores_gemma":[0.000692412,0.0002989612,0.00041280265,0.00021134704,0.00029619565,0.00070322916,0.0004218901,0.0006382907,0.00011738775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011613595,0.0000761633,0.0009981937,0.00004845701,0.000034548786,0.00005296129,0.000027832462,0.9555253,0.008098728,0.0006208077,0.000280382,0.034120537],"study_design_scores_gemma":[0.0000012421821,0.000010244633,0.00006771854,7.31613e-7,0.0000017175838,0.0000011312948,7.177409e-7,0.99944276,0.00040451993,0.00004550437,0.000022499074,0.000001343652],"about_ca_topic_score_codex":0.014025021,"about_ca_topic_score_gemma":0.007909996,"teacher_disagreement_score":0.014025021,"about_ca_system_score_codex":0.00056075404,"about_ca_system_score_gemma":0.00064096233,"threshold_uncertainty_score":0.027886808},"labels":[],"label_agreement":null},{"id":"W4403243896","doi":"10.1115/1.4066797","title":"Operational Modal Analysis of Self-Excited Vibrations in Milling Considering Periodic Dynamics","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Research Council Canada","keywords":"Vibration; Modal; Modal analysis; Dynamics (music); Excited state; Control theory (sociology); Physics; Mechanics; Acoustics; Classical mechanics; Materials science; Computer science; Atomic physics; Composite material; Artificial intelligence","score_opus":0.00506784990820015,"score_gpt":0.21635337161122495,"score_spread":0.2112855217030248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403243896","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18372108,0.000066062334,0.8147674,0.000020429548,0.000007590291,0.000029801367,0.000020287118,0.00016043358,0.0012069475],"genre_scores_gemma":[0.9702369,0.000027833928,0.029310595,0.0000037762575,0.0000026218236,0.000017913835,0.000014710007,0.000010816667,0.00037471208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998677,0.000028933682,0.000005834787,0.000021931228,0.00006557053,0.0000100043735],"domain_scores_gemma":[0.9996785,0.00018129166,0.00004686734,0.000027980563,0.000056381454,0.000009050719],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004017184,0.00027741006,0.00020639,0.00041207293,0.00013638013,0.000280169,0.0003251471,0.00020894305,0.00097178214],"category_scores_gemma":[0.00079379336,0.00012411253,0.00022078458,0.00012450771,0.00034263742,0.00034972804,0.0002543496,0.00021134078,0.00008965685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002736322,0.000104532686,0.0040675597,0.00029933656,0.00006497593,0.00021676932,0.00047060061,0.59795314,0.24581556,0.017142784,0.00026020047,0.13333096],"study_design_scores_gemma":[0.0000020042614,0.000027418177,0.0005846852,0.0000033060037,0.0000030580522,0.00001476484,0.000012339591,0.99307054,0.0055671916,0.0006035374,0.000106785534,0.000004434926],"about_ca_topic_score_codex":0.0006168734,"about_ca_topic_score_gemma":0.0006127321,"teacher_disagreement_score":0.00097178214,"about_ca_system_score_codex":0.0001920791,"about_ca_system_score_gemma":0.00019466979,"threshold_uncertainty_score":0.0032509565},"labels":[],"label_agreement":null},{"id":"W4403249858","doi":"10.1016/j.procir.2024.08.395","title":"A Generalized Multi-Stage Deep Machine Learning Framework for Tool Wear Level Prediction in Milling Operations","year":2024,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Stage (stratigraphy); Engineering; Computer science; Manufacturing engineering; Artificial intelligence; Tool wear; Industrial engineering; Mechanical engineering; Systems engineering; Geology; Machining","score_opus":0.041306658595091215,"score_gpt":0.2964831447971225,"score_spread":0.2551764862020313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403249858","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028639993,0.00025016174,0.96939206,0.00007734749,0.000026710877,0.000024421752,0.00008626712,0.0007994845,0.0007034692],"genre_scores_gemma":[0.841047,0.00019744961,0.15513775,0.000109765286,0.000038738086,0.00011013217,0.00030660472,0.000060944665,0.0029917036],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997745,0.0000338434,0.00001119637,0.00006227123,0.00007979087,0.00003842054],"domain_scores_gemma":[0.99977404,0.000059249385,0.000029276887,0.000030639403,0.00009149975,0.000015282947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045767985,0.00064273056,0.0005530181,0.00034138357,0.00017135197,0.00044144224,0.0011126519,0.00063518336,0.00089460966],"category_scores_gemma":[0.00076404546,0.00031794803,0.0005492276,0.0003326379,0.0002655377,0.0005875018,0.00063270313,0.0007959877,0.00025919432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011534883,0.00009906841,0.0015933758,0.00007734005,0.000063860796,0.00008560144,0.00004074536,0.7935867,0.013492797,0.0020473073,0.0011333482,0.18766461],"study_design_scores_gemma":[0.0000011324227,0.000014426385,0.00016397162,0.0000010704928,0.0000022785184,0.0000043051596,0.0000011326181,0.99883085,0.000606645,0.00027334923,0.00009895758,0.0000019655342],"about_ca_topic_score_codex":0.0054485328,"about_ca_topic_score_gemma":0.007840911,"teacher_disagreement_score":0.0054485328,"about_ca_system_score_codex":0.0004113545,"about_ca_system_score_gemma":0.00071313855,"threshold_uncertainty_score":0.010833621},"labels":[],"label_agreement":null},{"id":"W4403376647","doi":"10.1007/s00170-024-14654-w","title":"Leveraging metaheuristic algorithms with improved hybrid prediction model framework for enhancing surface roughness optimization in CNC turning AISI 316","year":2024,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Metaheuristic; Surface roughness; Industrial and production engineering; Numerical control; Algorithm; Computer science; Surface (topology); Engineering drawing; Engineering; Mechanical engineering; Materials science; Machining; Mathematics; Geometry; Composite material","score_opus":0.00699728123920488,"score_gpt":0.24649344782791188,"score_spread":0.239496166588707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403376647","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15981963,0.00067869446,0.82872534,0.00025900095,0.00014683082,0.00006124767,0.00010449825,0.00073024584,0.009474525],"genre_scores_gemma":[0.93457,0.00014205587,0.0625599,0.00008470701,0.00003071298,0.00007038227,0.00012655815,0.000075243326,0.0023403738],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981755,0.000040997846,0.000008656985,0.00003454123,0.00006272254,0.00003558328],"domain_scores_gemma":[0.99976975,0.00009131107,0.000027654281,0.000018419983,0.000080239864,0.0000126507575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043842933,0.00059451675,0.00084611046,0.0005433337,0.00039385332,0.0008165976,0.0009894185,0.0010536707,0.0009880738],"category_scores_gemma":[0.0006630948,0.0003147139,0.00083136855,0.0005424109,0.00025466966,0.0005323386,0.00044835662,0.00074693596,0.00018432931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018078206,0.000033287877,0.00030875448,0.000015393662,0.000018511739,0.000016966718,0.0000086597365,0.98613316,0.001201145,0.0008952734,0.00020697249,0.011143702],"study_design_scores_gemma":[8.8882234e-7,0.000005080658,0.000027879574,5.077773e-7,0.0000015810663,0.0000010452492,0.000001249085,0.9997296,0.0000951048,0.00009887853,0.000037386348,8.4123525e-7],"about_ca_topic_score_codex":0.0132845715,"about_ca_topic_score_gemma":0.010361217,"teacher_disagreement_score":0.0132845715,"about_ca_system_score_codex":0.00048255778,"about_ca_system_score_gemma":0.000883069,"threshold_uncertainty_score":0.026414454},"labels":[],"label_agreement":null},{"id":"W4403587171","doi":"10.1063/5.0235664","title":"Performance evaluation of machine learning algorithms in predicting machining responses of superalloys","year":2024,"lang":"en","type":"article","venue":"AIP Advances","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"Superalloy; Machining; Computer science; Algorithm; Machine learning; Artificial intelligence; Materials science; Metallurgy","score_opus":0.015590965709644725,"score_gpt":0.28439238716203785,"score_spread":0.2688014214523931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403587171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74676156,0.0029773586,0.2431547,0.0005218052,0.00012441436,0.00011526272,0.00029355072,0.0017376356,0.0043136594],"genre_scores_gemma":[0.9650212,0.00032377546,0.033760305,0.00005091165,0.000013340939,0.000046804245,0.0002807971,0.000033198357,0.00046967296],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898297,0.00034837975,0.00010951513,0.00019820005,0.00029385492,0.000066980894],"domain_scores_gemma":[0.99488294,0.003832854,0.00036624062,0.0001790425,0.0006833945,0.00005556866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035328919,0.0016073533,0.00086892897,0.0011765418,0.0002899106,0.00089977385,0.00073989475,0.0012042812,0.0004008655],"category_scores_gemma":[0.007911123,0.00025988868,0.0006238602,0.0006151561,0.0003449244,0.00092369225,0.00046146882,0.0009685355,0.00017534319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028304738,0.0001472208,0.0066936957,0.000114003116,0.00010540869,0.000051731233,0.00004188584,0.8972785,0.002937574,0.00041818686,0.00026433135,0.09166434],"study_design_scores_gemma":[0.0000025460529,0.000054924272,0.00080139266,0.0000051998454,0.0000057426387,0.000006618328,0.000008519289,0.99769384,0.001268963,0.00008973828,0.00005841264,0.000004031767],"about_ca_topic_score_codex":0.008279879,"about_ca_topic_score_gemma":0.0040822458,"teacher_disagreement_score":0.008279879,"about_ca_system_score_codex":0.00065919355,"about_ca_system_score_gemma":0.00079463003,"threshold_uncertainty_score":0.01868391},"labels":[],"label_agreement":null},{"id":"W4403623358","doi":"10.1016/j.cirpj.2024.10.005","title":"Digital dynamic modeling and topology optimized design of shell face mills","year":2024,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Pratt and Whitney Canada","keywords":"Face (sociological concept); Topology (electrical circuits); Shell (structure); Computer science; Engineering; Mechanical engineering; Electrical engineering; Sociology","score_opus":0.006776056069359214,"score_gpt":0.22947577908889802,"score_spread":0.2226997230195388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403623358","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14252752,0.00033170462,0.8080647,0.00019858046,0.000059692484,0.00008080491,0.00017516459,0.00051747233,0.04804432],"genre_scores_gemma":[0.95722,0.00014502867,0.03542616,0.00002548907,0.000008422036,0.00006126254,0.00007178803,0.000052192845,0.0069895354],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999175,0.000017771672,0.0000028161483,0.000011252642,0.000040623698,0.000009975318],"domain_scores_gemma":[0.9999186,0.000030033418,0.000014544003,0.0000100680545,0.000021848215,0.000004933298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015853098,0.0003069531,0.00043342632,0.00033840485,0.00025647576,0.00072894525,0.00067193806,0.0005909365,0.003852797],"category_scores_gemma":[0.00033710414,0.0003512482,0.0003861032,0.00027769266,0.0002714073,0.0003580963,0.00033434585,0.00025391905,0.0003776158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013572717,0.000010788459,0.00009653597,0.000013293453,0.0000037833836,0.000015596856,0.000009387902,0.9912307,0.0014759928,0.0020106484,0.00009848945,0.005021233],"study_design_scores_gemma":[0.0000021150831,0.0000062476893,0.000039125145,0.0000010097144,0.0000011766105,0.0000031944876,0.0000030286278,0.9992368,0.00027437333,0.00020531552,0.00022657582,9.586342e-7],"about_ca_topic_score_codex":0.0034300652,"about_ca_topic_score_gemma":0.003817697,"teacher_disagreement_score":0.003852797,"about_ca_system_score_codex":0.0004530734,"about_ca_system_score_gemma":0.00048386867,"threshold_uncertainty_score":0.012888849},"labels":[],"label_agreement":null},{"id":"W4403636404","doi":"10.1115/1.4066976","title":"A New Cutting Mechanics Model for Improved Shear Angle Prediction in Orthogonal Cutting Process","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Shear (geology); Process (computing); Computer science; Materials science; Mechanics; Mechanical engineering; Geology; Engineering; Physics; Composite material","score_opus":0.007418465710043357,"score_gpt":0.23199778995229714,"score_spread":0.22457932424225377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403636404","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09563021,0.000339948,0.8958723,0.000184373,0.00007193182,0.000098062745,0.00013991968,0.00039772116,0.0072655114],"genre_scores_gemma":[0.9486664,0.0003727531,0.04426332,0.00005734198,0.000028820737,0.00021223322,0.00014207252,0.000077995865,0.0061790734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998318,0.00003209924,0.00001047922,0.000037765236,0.00006480268,0.000022959859],"domain_scores_gemma":[0.99975806,0.000100814694,0.000039774368,0.000015635696,0.000077187105,0.000008443068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004337053,0.0006049129,0.0008384826,0.0005606849,0.00039401592,0.0008636469,0.0009967953,0.0013470184,0.0015462906],"category_scores_gemma":[0.00074769725,0.0005348993,0.0007650731,0.0004050381,0.00039026872,0.00062032975,0.00036300495,0.00067756866,0.00033229176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009985333,0.000018812187,0.0002727671,0.000012985207,0.0000055474975,0.00003523533,0.000014978828,0.9926777,0.0020501073,0.0009777909,0.00007333903,0.0038506642],"study_design_scores_gemma":[0.0000010725577,0.0000034204897,0.000034087585,9.386338e-7,8.68785e-7,0.0000020160037,8.051555e-7,0.99972445,0.000100364276,0.00006921229,0.00006181153,9.17004e-7],"about_ca_topic_score_codex":0.0101512,"about_ca_topic_score_gemma":0.0073493775,"teacher_disagreement_score":0.0101512,"about_ca_system_score_codex":0.00068322755,"about_ca_system_score_gemma":0.000956539,"threshold_uncertainty_score":0.020184219},"labels":[],"label_agreement":null},{"id":"W4403673327","doi":"10.2139/ssrn.4957890","title":"Optimization of Machining Parameters for Nimonic PE16 Using Machine Learning Models","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Nimonic; Machining; Computer science; Materials science; Machine learning; Artificial intelligence; Mechanical engineering; Metallurgy; Engineering; Superalloy","score_opus":0.01730138606543605,"score_gpt":0.2475594449567783,"score_spread":0.23025805889134227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403673327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7460153,0.0018418494,0.2101901,0.0004413185,0.00015129523,0.00028472315,0.0007114078,0.0018483874,0.03851562],"genre_scores_gemma":[0.95747083,0.00020049312,0.037612796,0.000026131294,0.0000055645064,0.00010093231,0.0003329358,0.00012276358,0.004127521],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989474,0.000014684306,0.0000066052917,0.000026449427,0.000034260305,0.00002335178],"domain_scores_gemma":[0.99970716,0.00013735238,0.00003913076,0.000034807897,0.00006525212,0.000016203858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038272477,0.0009224363,0.00063446094,0.0006331082,0.0005359815,0.0008647816,0.00060627534,0.0010703604,0.0051070843],"category_scores_gemma":[0.0010269593,0.00038112674,0.0005182047,0.0005998388,0.0003012912,0.00066001393,0.00036767015,0.00070275855,0.0008558529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024768646,0.000098867546,0.0009772124,0.00023778193,0.000029922412,0.00008753977,0.00005398155,0.9435593,0.012589568,0.0009384632,0.00088468665,0.040295],"study_design_scores_gemma":[0.00003259653,0.00029419726,0.001146938,0.000020298681,0.000025248752,0.000027524527,0.00005839504,0.98249304,0.012549012,0.0005559129,0.002778233,0.000018741532],"about_ca_topic_score_codex":0.0054267556,"about_ca_topic_score_gemma":0.0076928325,"teacher_disagreement_score":0.0054267556,"about_ca_system_score_codex":0.00071668025,"about_ca_system_score_gemma":0.0010429358,"threshold_uncertainty_score":0.017084897},"labels":[],"label_agreement":null},{"id":"W4403706201","doi":"10.1016/j.rcim.2024.102887","title":"A hybrid model in a nonlinear disturbance observer for improving compliance error compensation of robotic machining","year":2024,"lang":"en","type":"article","venue":"Robotics and Computer-Integrated Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Korea Institute of Industrial Technology","keywords":"Compensation (psychology); Machining; Control theory (sociology); Nonlinear system; Disturbance (geology); Control engineering; Compliance (psychology); Observer (physics); Nonlinear model; Computer science; Engineering; Control (management); Artificial intelligence; Psychology; Mechanical engineering; Physics; Social psychology; Geology","score_opus":0.023483473929163313,"score_gpt":0.24738359847743538,"score_spread":0.22390012454827207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403706201","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034693282,0.00022146081,0.96177065,0.00008912202,0.00015219298,0.00003459073,0.000022183782,0.00035720292,0.002659359],"genre_scores_gemma":[0.95344335,0.00014679052,0.04130135,0.000059647762,0.00003787995,0.00007802911,0.000054152686,0.000032901316,0.0048459386],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971634,0.000058137124,0.000019170457,0.00006728754,0.000108284104,0.000030638155],"domain_scores_gemma":[0.9997441,0.000063312036,0.00004144758,0.000031818385,0.00010730966,0.000012021843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039954585,0.0004882072,0.00062837603,0.00019960348,0.00030242538,0.0006908821,0.00063428114,0.00068671117,0.0012884077],"category_scores_gemma":[0.0005603456,0.0002854616,0.0003696649,0.0002025591,0.00043685792,0.0006019644,0.00065518817,0.00064110925,0.0002796105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005372786,0.00019158718,0.0011793977,0.00043518527,0.00012818482,0.00021750809,0.00024248354,0.7925594,0.08769632,0.011541411,0.0016220455,0.1036492],"study_design_scores_gemma":[0.000012324262,0.000076121265,0.00017717673,0.0000039207807,0.000011159534,0.000009149272,0.0000057714296,0.99661547,0.0022653327,0.00024526662,0.0005735721,0.000004758545],"about_ca_topic_score_codex":0.00467159,"about_ca_topic_score_gemma":0.005498127,"teacher_disagreement_score":0.00467159,"about_ca_system_score_codex":0.00029815055,"about_ca_system_score_gemma":0.00040944119,"threshold_uncertainty_score":0.009288847},"labels":[],"label_agreement":null},{"id":"W4404200196","doi":"10.1016/j.jmapro.2024.10.057","title":"Inverse kinematics model and trajectory generation of a dual-stage micro milling machine","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Materials science; Dual (grammatical number); Trajectory; Kinematics; Inverse; Stage (stratigraphy); Mechanical engineering; Composite material; Geometry; Classical mechanics; Engineering","score_opus":0.02369586951659549,"score_gpt":0.2452164782401427,"score_spread":0.2215206087235472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404200196","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014142019,0.00007478666,0.9835465,0.000056110675,0.00001738496,0.000027477574,0.000031015257,0.00030089886,0.0018037359],"genre_scores_gemma":[0.6764925,0.00027209485,0.3155766,0.000033742217,0.00001715163,0.00020696166,0.00018388915,0.00007595396,0.0071410625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998652,0.000015705313,0.000006822373,0.000037770456,0.000060575512,0.000014016126],"domain_scores_gemma":[0.999889,0.000025523888,0.00002498111,0.000011922123,0.000041275438,0.000007244704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022273553,0.0004148279,0.000532987,0.0002709006,0.0003522193,0.00049497397,0.0006981838,0.0007054725,0.0017618991],"category_scores_gemma":[0.00034004822,0.00037716515,0.00044862682,0.00028878203,0.0003260016,0.0004075172,0.00039111357,0.0005957885,0.0004476285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007140346,0.000021869126,0.00060481235,0.000083021245,0.000011866147,0.00013478236,0.00008705897,0.9354159,0.0138572715,0.004553269,0.00042410384,0.04473453],"study_design_scores_gemma":[0.0000048405805,0.000020843005,0.00011692095,0.0000029272205,0.0000028783884,0.000027343527,0.000006617197,0.9974663,0.0014560077,0.00030847103,0.0005827145,0.0000041760577],"about_ca_topic_score_codex":0.0061653326,"about_ca_topic_score_gemma":0.003633193,"teacher_disagreement_score":0.0061653326,"about_ca_system_score_codex":0.00040688677,"about_ca_system_score_gemma":0.0011533903,"threshold_uncertainty_score":0.012258887},"labels":[],"label_agreement":null},{"id":"W4404572639","doi":"10.1063/5.0227710","title":"Experimental and numerical analysis on the cutting force, cutting temperature, and tool wear of alloy steel (4340) during turning process","year":2024,"lang":"en","type":"article","venue":"AIP Advances","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"King Saud University","keywords":"Alloy; Materials science; Metallurgy; Process (computing); Mechanical engineering; Alloy steel; Computer science; Engineering","score_opus":0.004178873159588397,"score_gpt":0.24629786265300116,"score_spread":0.24211898949341276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404572639","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952638,0.000120086625,0.0035569486,0.000013907932,0.000009461475,0.000008512189,0.000101930586,0.00007903711,0.0008462722],"genre_scores_gemma":[0.99772507,0.000049680075,0.0018997791,0.0000026467815,0.0000023901307,0.000007289643,0.00006616632,0.000004769303,0.00024225336],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971646,0.000022921246,0.000017488657,0.000040631297,0.00016471252,0.000037796977],"domain_scores_gemma":[0.99936384,0.000250548,0.000083130166,0.00007349657,0.00020190627,0.000027013546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035609456,0.00030170512,0.00031860103,0.0004959823,0.00032477628,0.00016736843,0.00035320703,0.00047307444,0.0009981608],"category_scores_gemma":[0.0007379379,0.00016202897,0.00034732115,0.00037013475,0.0003305672,0.00018545035,0.00014555996,0.0001962283,0.00008865619],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007677354,0.00034451231,0.023464398,0.0007090742,0.000042263717,0.00062849524,0.0009136855,0.070048556,0.86047965,0.0004709132,0.00057049113,0.041560277],"study_design_scores_gemma":[0.000051649382,0.0026301863,0.1192151,0.00005045047,0.00009813985,0.0006747528,0.0005627564,0.2642642,0.61023784,0.00029356108,0.0018209849,0.00010041296],"about_ca_topic_score_codex":0.0010005787,"about_ca_topic_score_gemma":0.0018075256,"teacher_disagreement_score":0.0010005787,"about_ca_system_score_codex":0.00017625943,"about_ca_system_score_gemma":0.00015294921,"threshold_uncertainty_score":0.003339231},"labels":[],"label_agreement":null},{"id":"W4404763417","doi":"10.1139/tcsme-2024-0082","title":"Internal cooling system effects to heat transfer and tool wear in turning operations of titanium alloys Ti6Al4V","year":2024,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Titanium alloy; Heat transfer; Materials science; Mechanical engineering; Metallurgy; Titanium; Mechanics; Engineering; Alloy; Physics","score_opus":0.004073016704461736,"score_gpt":0.19533069668196076,"score_spread":0.19125767997749904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404763417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949851,0.00011579513,0.0044402694,0.000009121561,0.000006931552,0.000005692829,0.0000123543305,0.000028104747,0.00039658093],"genre_scores_gemma":[0.99945015,0.000026455298,0.0004032051,0.0000013774466,9.1712405e-7,0.0000023492642,0.000011696063,0.000004311326,0.00009947269],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998191,0.000022938511,0.000006893949,0.00002393205,0.000087310436,0.000039758746],"domain_scores_gemma":[0.9996413,0.00019999125,0.000044654647,0.00003235106,0.00007127222,0.000010361274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002447461,0.00027381512,0.0003249711,0.00031182403,0.00030207614,0.0002969871,0.00027634122,0.00027495335,0.000437269],"category_scores_gemma":[0.00056441856,0.00017005992,0.00046493203,0.00017818889,0.0003934546,0.0002880278,0.00020313023,0.00021218497,0.000043301443],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007460544,0.00014252841,0.03587053,0.0004311799,0.00008886512,0.00051397405,0.0011366217,0.24651004,0.66052693,0.0007794039,0.00035975635,0.052894052],"study_design_scores_gemma":[0.00003311693,0.0011662513,0.09451055,0.000021084074,0.00010140132,0.00036456375,0.0003898007,0.58314747,0.3189754,0.00037356807,0.0008494382,0.000067368666],"about_ca_topic_score_codex":0.0022768506,"about_ca_topic_score_gemma":0.002335155,"teacher_disagreement_score":0.0022768506,"about_ca_system_score_codex":0.00026461348,"about_ca_system_score_gemma":0.00024916575,"threshold_uncertainty_score":0.0045271516},"labels":[],"label_agreement":null},{"id":"W4404797168","doi":"10.1016/j.jmsy.2024.11.013","title":"Machining parameter optimization for a batch milling system using multi-task deep reinforcement learning","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Systems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Science Basic Research Program of Shaanxi Province; Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China","keywords":"Reinforcement learning; Reinforcement; Machining; Task (project management); Computer science; Mechanical engineering; Engineering; Manufacturing engineering; Materials science; Artificial intelligence; Structural engineering; Systems engineering","score_opus":0.01821142811721157,"score_gpt":0.2544938203271408,"score_spread":0.23628239220992922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404797168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11464667,0.00052738446,0.8809607,0.00027752673,0.00005708167,0.00007867705,0.00007468462,0.0013092112,0.002068159],"genre_scores_gemma":[0.9304795,0.00009689804,0.06738119,0.00010185136,0.000015628397,0.00009865109,0.00014609598,0.000043059757,0.0016371105],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972254,0.00004723831,0.00001730314,0.00009997661,0.00006580569,0.0000471483],"domain_scores_gemma":[0.99949217,0.00023753342,0.00007321413,0.00004431371,0.00011434342,0.000038471902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064918667,0.0009370895,0.0007778295,0.00025892066,0.0003180071,0.00054449996,0.0008750966,0.0008520433,0.0013423797],"category_scores_gemma":[0.0013060357,0.0004399035,0.0006167258,0.00023408895,0.00047704013,0.0006746729,0.0006845421,0.0012698609,0.00020663613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009790393,0.00007416773,0.0008814043,0.00005402382,0.000035151155,0.000059826132,0.000034004686,0.9528905,0.003980069,0.00070575916,0.00047885033,0.040708225],"study_design_scores_gemma":[0.0000043968344,0.000014231948,0.00007743686,9.149752e-7,0.0000021813537,0.0000027103072,0.0000012798106,0.9993237,0.000336889,0.00018372871,0.00005093751,0.0000015907766],"about_ca_topic_score_codex":0.0109142065,"about_ca_topic_score_gemma":0.009731779,"teacher_disagreement_score":0.0109142065,"about_ca_system_score_codex":0.0008345955,"about_ca_system_score_gemma":0.0011469884,"threshold_uncertainty_score":0.021701336},"labels":[],"label_agreement":null},{"id":"W4404991726","doi":"10.3390/physchem4040035","title":"Predicting Surface Roughness and Grinding Forces in UNS S34700 Steel Grinding: A Machine Learning and Genetic Algorithm Approach to Coolant Effects","year":2024,"lang":"en","type":"article","venue":"Physchem","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Machine learning; Artificial intelligence; Artificial neural network; Surface roughness; Grinding; Support vector machine; Computer science; Algorithm; Surface finish; Regression; Coolant; Mechanical engineering; Engineering; Materials science; Mathematics; Statistics","score_opus":0.006091784104069655,"score_gpt":0.22441223749990316,"score_spread":0.2183204533958335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404991726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86569315,0.0002402823,0.13193947,0.0002168198,0.00001787007,0.000059700782,0.00014337475,0.00036361802,0.0013257796],"genre_scores_gemma":[0.94809735,0.00011122139,0.05077517,0.000023383744,0.0000072050116,0.000034746507,0.00026069974,0.000021498952,0.0006686639],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979264,0.0000477126,0.000012195957,0.000065538545,0.00006133902,0.000020582673],"domain_scores_gemma":[0.99948126,0.0003264028,0.00005307358,0.00002588137,0.00010164558,0.000011791424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006916641,0.000567746,0.0004879948,0.0009527049,0.0002613333,0.00062466494,0.0005277226,0.0007310532,0.00038991243],"category_scores_gemma":[0.001605537,0.00023968755,0.00080983195,0.0007396646,0.00030562794,0.00041460947,0.0001787876,0.00059605716,0.00011360555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007689537,0.00017597496,0.017985795,0.00004828147,0.000051378494,0.00007773881,0.00006066344,0.9000043,0.00727589,0.0007764772,0.00024827028,0.07321832],"study_design_scores_gemma":[0.0000017951413,0.000024545041,0.0027840124,0.0000018230768,0.0000046033383,0.0000058380533,0.000011520563,0.99599504,0.0009782603,0.00013298364,0.00005528072,0.00000424149],"about_ca_topic_score_codex":0.022566129,"about_ca_topic_score_gemma":0.019736173,"teacher_disagreement_score":0.022566129,"about_ca_system_score_codex":0.00092855067,"about_ca_system_score_gemma":0.00083797064,"threshold_uncertainty_score":0.0448696},"labels":[],"label_agreement":null},{"id":"W4404993695","doi":"10.21741/9781644903377-18","title":"Analysis of Al7136 surface roughness in end milling process based on discriminant analysis","year":2024,"lang":"en","type":"article","venue":"Materials research proceedings","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Science North","funders":"","keywords":"Surface roughness; Linear discriminant analysis; Process (computing); End milling; Surface finish; Materials science; Computer science; Artificial intelligence; Composite material; Metallurgy; Machining","score_opus":0.03472211955899926,"score_gpt":0.359919732302618,"score_spread":0.3251976127436187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404993695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96876657,0.00015588429,0.030543312,0.000012093612,0.00000957452,0.000017991955,0.000067427995,0.00006046841,0.0003666582],"genre_scores_gemma":[0.9840193,0.000053008273,0.015392274,0.0000059043846,0.0000024385058,0.000011772691,0.00009308228,0.0000105863155,0.00041156443],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999514,0.0000710208,0.000019942538,0.000104258004,0.0002507413,0.00004013414],"domain_scores_gemma":[0.9990102,0.00040522616,0.00012561692,0.00007698188,0.0003458347,0.000036034224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005666996,0.00026367186,0.00048935285,0.0006364884,0.0001584048,0.0003399641,0.0002554885,0.00029886432,0.00052687444],"category_scores_gemma":[0.0010115303,0.00013808228,0.00037328215,0.00036887385,0.00023387276,0.00023399724,0.00017987547,0.00035582087,0.00018190863],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005958131,0.00009285215,0.008829446,0.00009928434,0.00001801613,0.00004604535,0.000094371215,0.003126927,0.9472759,0.00008886416,0.00008380417,0.03964875],"study_design_scores_gemma":[0.00003881065,0.0013002005,0.15734951,0.000010181092,0.00006986396,0.00022986009,0.00017859694,0.09627848,0.74369395,0.0001709474,0.0006154873,0.00006407483],"about_ca_topic_score_codex":0.00068145484,"about_ca_topic_score_gemma":0.00093793904,"teacher_disagreement_score":0.00068145484,"about_ca_system_score_codex":0.00019984895,"about_ca_system_score_gemma":0.000114496484,"threshold_uncertainty_score":0.0029970407},"labels":[],"label_agreement":null},{"id":"W4405063449","doi":"10.1115/1.4067324","title":"A Generalized Machining Process Damping Model for Orthogonal Cutting","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Damper; Vibration; Enhanced Data Rates for GSM Evolution; Discretization; Mechanical engineering; Machine tool; Cutting tool; Structural engineering; Process (computing); Engineering; Computer science; Acoustics; Mathematics; Physics; Mathematical analysis","score_opus":0.011541581518002214,"score_gpt":0.2603035209284496,"score_spread":0.24876193941044739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405063449","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06555912,0.00041250742,0.9225422,0.00016617114,0.000055719953,0.00008009667,0.00013121248,0.00031576297,0.010737225],"genre_scores_gemma":[0.9665981,0.00033285114,0.022365466,0.000046396675,0.000025579464,0.0001504569,0.00011486277,0.000058047746,0.010308234],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979085,0.000043263302,0.000009282224,0.000052217365,0.000072954936,0.000031402615],"domain_scores_gemma":[0.9998281,0.000057167887,0.000033651206,0.000016822738,0.000055250825,0.000008966585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034797817,0.00080472714,0.00062263483,0.0004757849,0.0003161414,0.0007177691,0.0011491873,0.0013430491,0.0016607699],"category_scores_gemma":[0.00053359516,0.00038003575,0.0007695841,0.0003088488,0.00054695876,0.00058257673,0.00045708887,0.00066209707,0.0003482757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016153475,0.000022938713,0.0002405343,0.000040182673,0.000010772568,0.00008515479,0.000066889195,0.98387086,0.0047103334,0.006090813,0.0001743747,0.00467093],"study_design_scores_gemma":[0.000001683657,0.00000509703,0.00003527142,0.0000012689145,0.0000015372226,0.0000059102967,0.0000021076826,0.99936324,0.00010426913,0.00032514744,0.00015286426,0.0000015413431],"about_ca_topic_score_codex":0.0066387164,"about_ca_topic_score_gemma":0.0041901455,"teacher_disagreement_score":0.0066387164,"about_ca_system_score_codex":0.000565471,"about_ca_system_score_gemma":0.0005626713,"threshold_uncertainty_score":0.013200104},"labels":[],"label_agreement":null},{"id":"W4405144332","doi":"","title":"Identification viscoélastique des thermoplastiques par les réseaux de neurones pour des applications en thermoformage","year":2019,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Computer science; Identification (biology); Biology","score_opus":0.007103901866926333,"score_gpt":0.22377875913204429,"score_spread":0.21667485726511795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405144332","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8581665,0.0012437704,0.13807516,0.00014932056,0.000047655678,0.000022520268,0.00005562891,0.00015422178,0.002085214],"genre_scores_gemma":[0.9786106,0.00048113204,0.016277278,0.000010367396,0.000008537866,0.000019146279,0.000033308977,0.000021478918,0.0045381715],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999044,0.000015565109,0.0000029221383,0.000027753576,0.000036217407,0.000013111762],"domain_scores_gemma":[0.9997842,0.00010868876,0.000023651437,0.000011709428,0.00005568798,0.000016141988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026223608,0.00031265337,0.00029858833,0.0003251536,0.00030274212,0.0004935742,0.00018849061,0.00042729586,0.0010684925],"category_scores_gemma":[0.0004744161,0.00013668895,0.00026911355,0.0002308943,0.00034329065,0.00054516597,0.00018849417,0.0004579932,0.00023519657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021997637,0.000025490062,0.0015927651,0.00004914069,0.000013000165,0.000075762466,0.0001087509,0.010683723,0.9585308,0.0010909156,0.00008558486,0.027524091],"study_design_scores_gemma":[0.000019253723,0.00025156926,0.022056423,0.0000155423,0.000039409177,0.00032793925,0.0002095731,0.21832621,0.7561092,0.00087179843,0.0017381753,0.000034932713],"about_ca_topic_score_codex":0.0034895146,"about_ca_topic_score_gemma":0.0032286826,"teacher_disagreement_score":0.0034895146,"about_ca_system_score_codex":0.00052552426,"about_ca_system_score_gemma":0.00039062806,"threshold_uncertainty_score":0.006938398},"labels":[],"label_agreement":null},{"id":"W4405236216","doi":"10.1016/j.jmapro.2024.11.092","title":"An improved machining temperature prediction model for aerospace alloys: Effect of cutting edge radius and tool wear","year":2024,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Aerospace; Enhanced Data Rates for GSM Evolution; Machining; RADIUS; Tool wear; Cutting tool; Mechanical engineering; Metallurgy; Composite material; Aerospace engineering; Engineering; Computer science","score_opus":0.004898605856139296,"score_gpt":0.2372366628918052,"score_spread":0.2323380570356659,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405236216","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05403777,0.00042171558,0.9413518,0.00010399877,0.00003832957,0.000046770092,0.00010250562,0.00055291096,0.003344255],"genre_scores_gemma":[0.9339139,0.0005077753,0.058746397,0.000045722227,0.00003321833,0.0001589923,0.00019706348,0.00012390388,0.0062730205],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997595,0.000040302268,0.000015144833,0.0000679952,0.00009019643,0.000026822252],"domain_scores_gemma":[0.99980265,0.000065819746,0.0000330735,0.000022156417,0.00006892958,0.0000074682725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035121,0.0006749658,0.000777462,0.00034075291,0.00034120606,0.0006922537,0.0014778204,0.0010570564,0.00094229047],"category_scores_gemma":[0.0005475028,0.0004560165,0.0008735241,0.0003570787,0.0003699342,0.0006076959,0.00037370337,0.0006219015,0.00037250397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017736851,0.000015170177,0.00031560473,0.00003319544,0.000007093796,0.00003543142,0.000027963337,0.98623776,0.005669046,0.00075036695,0.00011994952,0.0067706266],"study_design_scores_gemma":[0.0000015684302,0.0000072598555,0.00007613711,0.0000011863726,0.0000029880664,0.000007470106,0.0000011891977,0.99916625,0.0005240638,0.000083399405,0.00012637113,0.0000021823187],"about_ca_topic_score_codex":0.0071453257,"about_ca_topic_score_gemma":0.005644616,"teacher_disagreement_score":0.0071453257,"about_ca_system_score_codex":0.00048557916,"about_ca_system_score_gemma":0.0009049799,"threshold_uncertainty_score":0.014207423},"labels":[],"label_agreement":null},{"id":"W4405519009","doi":"10.2316/j.2025.201-0450","title":"APPLICATION OF BIG DATA ANALYSIS BASED ON IMPROVED APRIORI ALGORITHM AND ARTIFICIAL INTELLIGENCE IN IMPROVING THE STABILITY OF CNC MACHINE TOOLS, 1-9.","year":2024,"lang":"en","type":"article","venue":"Mechatronic systems and control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Stability (learning theory); Big data; Apriori algorithm; Artificial intelligence; A priori and a posteriori; Algorithm; Data mining; Machine learning; Association rule learning","score_opus":0.01818687052173434,"score_gpt":0.23678168432085317,"score_spread":0.21859481379911883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405519009","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.079859205,0.010438843,0.8969732,0.0018377533,0.00069064635,0.00041087042,0.002206259,0.0023977107,0.0051855864],"genre_scores_gemma":[0.42720985,0.003868465,0.5625574,0.00028168494,0.00041909775,0.00028698344,0.0030438094,0.0001320565,0.0022007239],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985366,0.0004674218,0.00018918159,0.00023525265,0.00050655217,0.00006506635],"domain_scores_gemma":[0.9962799,0.0018321567,0.00037095122,0.0002745148,0.0011474838,0.000094958836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003449592,0.0013372558,0.0012465287,0.003811907,0.00074894127,0.002070206,0.0009695968,0.00078672153,0.0014937915],"category_scores_gemma":[0.0052020266,0.0003591832,0.0012756676,0.0030798977,0.0003860934,0.0018623247,0.0006932714,0.0012383944,0.0005845702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014312882,0.00087339076,0.03078534,0.0017446447,0.001223997,0.0011696336,0.0003322693,0.16040827,0.025930118,0.012418449,0.016153807,0.74752873],"study_design_scores_gemma":[0.000054611046,0.0004970987,0.0064753834,0.000086317,0.00027364804,0.00042915935,0.00019961932,0.9446236,0.022260895,0.017102858,0.007923733,0.00007317912],"about_ca_topic_score_codex":0.001392691,"about_ca_topic_score_gemma":0.0020703392,"teacher_disagreement_score":0.003811907,"about_ca_system_score_codex":0.00051720295,"about_ca_system_score_gemma":0.0011204802,"threshold_uncertainty_score":0.018243372},"labels":[],"label_agreement":null},{"id":"W4405708294","doi":"10.1007/s11665-024-10598-0","title":"Stress Corrosion Behavior of AISI 4340 in High-Speed Hard Milling Using MQL","year":2024,"lang":"en","type":"article","venue":"Journal of Materials Engineering and Performance","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Materials science; Residual stress; Corrosion; Metallurgy; Lubrication; Ultimate tensile strength; Austenite; Surface roughness; Indentation hardness; Surface finish; Stress (linguistics); Texture (cosmology); Surface integrity; Composite material; Microstructure","score_opus":0.010467297727747911,"score_gpt":0.2246671927422961,"score_spread":0.2141998950145482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405708294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992549,0.0001261605,0.00022727351,0.00002261664,0.0000045751194,0.0000025537236,0.00004121757,0.000019901447,0.00030087866],"genre_scores_gemma":[0.9979175,0.00006919824,0.00022198877,0.000010485681,0.0000019186296,0.0000023774185,0.000057618254,0.000008562964,0.0017103666],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999749,0.000025324563,0.000011646871,0.00003807494,0.0001259282,0.000049964157],"domain_scores_gemma":[0.999678,0.000047905134,0.000055219192,0.00002681712,0.00016114813,0.000030935513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027412045,0.00019983867,0.00030204243,0.00017738908,0.00026119355,0.00030266304,0.00029240834,0.00033296755,0.001656914],"category_scores_gemma":[0.0004673824,0.00019755369,0.000165233,0.00021821752,0.00021665165,0.00031168555,0.00014606104,0.0003022795,0.00033707524],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042617397,0.000025530731,0.00091953465,0.000048912738,0.000009246468,0.000041468695,0.00011926771,0.0003178556,0.9957098,0.000031160824,0.00009126398,0.0022598319],"study_design_scores_gemma":[0.000010145928,0.0006577924,0.009461881,0.0000037447396,0.000012960551,0.000026090158,0.00010423381,0.0030146905,0.9859724,0.000012623837,0.0007137246,0.000009835449],"about_ca_topic_score_codex":0.0044458797,"about_ca_topic_score_gemma":0.006634655,"teacher_disagreement_score":0.0044458797,"about_ca_system_score_codex":0.00043898638,"about_ca_system_score_gemma":0.00029783775,"threshold_uncertainty_score":0.0088400245},"labels":[],"label_agreement":null},{"id":"W4406484829","doi":"10.1016/0967-0653(93)92647-3","title":"10.1016/0967-0653(93)92647-3","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Relation (database); Resistance (ecology); Motion (physics); Fault (geology); Geology; Geodesy; Computer science; Seismology; Artificial intelligence; Data mining; Biology; Agronomy","score_opus":0.0032028138768484212,"score_gpt":0.15877402734022114,"score_spread":0.15557121346337272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406484829","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00061582145,0.00038468232,0.0010814725,0.00034821464,0.00032391094,0.00010983319,0.0006807057,0.0008640521,0.9955913],"genre_scores_gemma":[0.000993287,0.00023068365,0.000503142,0.00020392427,0.000066141154,0.000049898208,0.0004105666,0.00016554356,0.9973769],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999474,0.000035796915,0.000041547377,0.00018708706,0.00014866516,0.00011283218],"domain_scores_gemma":[0.9982256,0.00045066056,0.000098457494,0.00020461717,0.000488695,0.0005319176],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00091315556,0.0022680385,0.0013647602,0.0024051138,0.0020893577,0.0034227527,0.0027364187,0.0044408576,0.9855364],"category_scores_gemma":[0.001318563,0.00087735505,0.0011505225,0.0022880035,0.0019314876,0.0039855377,0.0023155746,0.0022161123,0.99064296],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040673563,0.00024702746,0.0011829871,0.0006063667,0.0000497045,0.00031934577,0.0001301737,0.000635239,0.0037648804,0.005329312,0.3510155,0.63631266],"study_design_scores_gemma":[0.000059228623,0.0001492186,0.00084443175,0.00029496267,0.000018596329,0.00040786818,0.00015099395,0.000336834,0.00063037383,0.00078145147,0.99629945,0.00002658155],"about_ca_topic_score_codex":0.00420805,"about_ca_topic_score_gemma":0.0034455457,"teacher_disagreement_score":0.0144636035,"about_ca_system_score_codex":0.0009238071,"about_ca_system_score_gemma":0.0008715766,"threshold_uncertainty_score":0.020630598},"labels":[],"label_agreement":null},{"id":"W4406518701","doi":"10.1007/s00170-025-15039-3","title":"A comprehensive experimental investigation on the correlation between chip formation, machined surface integrity, and particle emissions during high-speed milling of TC4 titanium alloy","year":2025,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Surface integrity; Materials science; Titanium alloy; Chip formation; Chip; Alloy; Particle (ecology); Metallurgy; Machining; Tool wear; Engineering","score_opus":0.014403017063706496,"score_gpt":0.25444704523077977,"score_spread":0.24004402816707326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406518701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99766386,0.000114972834,0.0019229095,0.0000063064863,0.0000045573356,0.000009488833,0.000060893028,0.000019298785,0.00019775059],"genre_scores_gemma":[0.9984586,0.00005036452,0.0010747965,0.0000047163,0.0000024075598,0.0000069250655,0.000082285704,0.000006567396,0.00031338006],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99970824,0.000027262293,0.000014760438,0.00006340971,0.00014498453,0.000041281593],"domain_scores_gemma":[0.9993444,0.00025136402,0.00010731423,0.00008914132,0.00019154618,0.000016182259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035417188,0.00024481822,0.00030731325,0.00019881218,0.00028355714,0.00027297813,0.0003635289,0.00035394033,0.00069361104],"category_scores_gemma":[0.0006275528,0.00020104635,0.00023310227,0.00024329317,0.0003839779,0.0002798484,0.00017200052,0.00023195166,0.000121685334],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034505024,0.000056507506,0.0027016352,0.0000677246,0.000014661621,0.000055412856,0.00007188547,0.0005146517,0.99232626,0.000039696053,0.000038012597,0.003768592],"study_design_scores_gemma":[0.00000841685,0.00055120036,0.025178239,0.0000017105365,0.000020227322,0.000060633865,0.00006076342,0.0032154194,0.97060984,0.000018028715,0.00026514285,0.000010406535],"about_ca_topic_score_codex":0.0009558093,"about_ca_topic_score_gemma":0.0016380738,"teacher_disagreement_score":0.0009558093,"about_ca_system_score_codex":0.00026927318,"about_ca_system_score_gemma":0.0002361903,"threshold_uncertainty_score":0.0023204088},"labels":[],"label_agreement":null},{"id":"W4406520086","doi":"10.1016/j.ymssp.2025.112312","title":"A physics-informed learning approach for milling stability analysis with deep subdomain adaptation network","year":2025,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China; Canada Research Chairs","keywords":"Stability (learning theory); Adaptation (eye); Deep learning; Artificial intelligence; Network analysis; Engineering; Mechanical engineering; Computer science; Machine learning; Physics; Electrical engineering; Optics","score_opus":0.014175730175559046,"score_gpt":0.22880080291975313,"score_spread":0.2146250727441941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406520086","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01805218,0.00015285364,0.9804733,0.00007720138,0.000015637514,0.000020340736,0.000024652556,0.0002885266,0.0008952306],"genre_scores_gemma":[0.8483145,0.00021033076,0.14735255,0.00013461195,0.000035121015,0.00016799172,0.00017435454,0.00006774222,0.003542925],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986815,0.000024780351,0.0000071543286,0.000041838168,0.000043582295,0.000014379785],"domain_scores_gemma":[0.99969053,0.00014283296,0.00003984959,0.000028599738,0.000083330175,0.000014982782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043744218,0.0007007031,0.00044404247,0.00033944222,0.00021922372,0.00040315688,0.00090306293,0.000557509,0.0009674932],"category_scores_gemma":[0.0010667569,0.00033160567,0.0004159436,0.00026511072,0.0004347314,0.00055218465,0.00070777757,0.0009957298,0.00021005826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038704777,0.000022302553,0.0005930085,0.00002582911,0.00002118993,0.000039143728,0.000031600615,0.941698,0.0040061204,0.0020222494,0.0004064551,0.051095404],"study_design_scores_gemma":[4.7759994e-7,0.00000392637,0.000038206796,7.419935e-7,9.5092486e-7,0.0000021441401,7.065225e-7,0.99936,0.00021102565,0.00032694798,0.000053864187,0.0000010190188],"about_ca_topic_score_codex":0.0040787365,"about_ca_topic_score_gemma":0.004346749,"teacher_disagreement_score":0.0040787365,"about_ca_system_score_codex":0.00049689866,"about_ca_system_score_gemma":0.0006819047,"threshold_uncertainty_score":0.008109987},"labels":[],"label_agreement":null},{"id":"W4406571044","doi":"10.1016/b978-0-443-13334-3.00019-x","title":"Machining of difficult materials","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Materials science; Manufacturing engineering; Engineering; Metallurgy","score_opus":0.006124301639347406,"score_gpt":0.21248220091114137,"score_spread":0.20635789927179396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406571044","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006708244,0.023624402,0.15293714,0.0005208572,0.001261115,0.000099967874,0.0003069502,0.0012620991,0.8132791],"genre_scores_gemma":[0.02680054,0.014344114,0.075033285,0.0002904201,0.00032511106,0.00008797979,0.0007852213,0.0006268335,0.8817064],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99978906,0.000011616233,0.0000062731133,0.000031910644,0.00014425475,0.000016894268],"domain_scores_gemma":[0.99989414,0.00003746521,0.000005806381,0.00003062073,0.000023731473,0.000008239878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018980209,0.0009549277,0.0008258074,0.00090426323,0.00051302504,0.0011858501,0.0009466729,0.0006943528,0.07779889],"category_scores_gemma":[0.00038406282,0.0005180975,0.0004899664,0.0008531481,0.00048458754,0.0011719279,0.0015039222,0.0013370515,0.02828526],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051162522,0.00005895912,0.0001389816,0.0011087329,0.000021059244,0.00017533153,0.00021558187,0.0064574485,0.042537175,0.067728795,0.08434941,0.79715735],"study_design_scores_gemma":[0.0000128640195,0.00008002797,0.0010134758,0.00028065103,0.00001336681,0.0008613853,0.000057703637,0.008526882,0.014187603,0.04032506,0.9346195,0.000021561676],"about_ca_topic_score_codex":0.000455518,"about_ca_topic_score_gemma":0.001290107,"teacher_disagreement_score":0.07779889,"about_ca_system_score_codex":0.00030245623,"about_ca_system_score_gemma":0.00026218183,"threshold_uncertainty_score":0.2602632},"labels":[],"label_agreement":null},{"id":"W4407002724","doi":"10.1111/ffe.14590","title":"Performance Evaluation of Biocomposite Gears Under Fatigue and Wear: Steel Drive Gear Versus Biocomposite Drive Gear and Biocomposite Drive Gear Versus Biocomposite Gear","year":2025,"lang":"en","type":"article","venue":"Fatigue & Fracture of Engineering Materials & Structures","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada; European Commission; European Regional Development Fund; Université du Québec à Trois-Rivières","keywords":"Biocomposite; Materials science; Composite material; Metallurgy; Composite number","score_opus":0.013666303581693915,"score_gpt":0.26601532260294924,"score_spread":0.25234901902125534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407002724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99898535,0.00019320102,0.0005774071,0.0000036466092,0.000007029995,0.000007699234,0.00003441946,0.00001764848,0.0001735035],"genre_scores_gemma":[0.9986197,0.00007853338,0.00081474485,0.0000030291826,0.0000017235798,0.0000069969938,0.000044611857,0.000006538942,0.0004241521],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999676,0.000045627246,0.000038323153,0.000054322307,0.0001461433,0.000039641258],"domain_scores_gemma":[0.99909425,0.00025781043,0.00014694655,0.00009294906,0.00034129526,0.000066647124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005619239,0.00042566544,0.0003577752,0.00063524605,0.00019799589,0.00018783395,0.00033903925,0.00040432558,0.0012077809],"category_scores_gemma":[0.0009851125,0.00017476332,0.00026535246,0.00025361587,0.00019363662,0.00027571118,0.00017299976,0.0001446021,0.0002575085],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006380167,0.00010200778,0.0036553633,0.0001340009,0.000020618492,0.00009262588,0.0001224823,0.001443533,0.9842333,0.000023727755,0.00004673473,0.009487428],"study_design_scores_gemma":[0.0000150367,0.0038499439,0.026412068,0.000011452373,0.000032769018,0.00017030536,0.00010908662,0.0044696922,0.9643467,0.000015106871,0.0005541276,0.000013670405],"about_ca_topic_score_codex":0.00036373656,"about_ca_topic_score_gemma":0.00084602943,"teacher_disagreement_score":0.0012077809,"about_ca_system_score_codex":0.00016310193,"about_ca_system_score_gemma":0.00007862031,"threshold_uncertainty_score":0.0040403605},"labels":[],"label_agreement":null},{"id":"W4407058689","doi":"10.1016/j.jmrt.2025.01.246","title":"Optimising subsurface integrity and surface quality in mild steel turning: A multi-objective approach to tool wear and machining parameters","year":2025,"lang":"en","type":"article","venue":"Journal of Materials Research and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Department of Mechanical Engineering, University of Alberta; State Key Laboratory of Tribology; Tsinghua University","keywords":"Materials science; Surface integrity; Machining; Metallurgy; Quality (philosophy); Tool wear; Mechanical engineering; Engineering","score_opus":0.05218484253587878,"score_gpt":0.3626341942628321,"score_spread":0.3104493517269533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407058689","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65203565,0.000597801,0.34544635,0.000066405235,0.000015519137,0.00010429738,0.000054610173,0.00018431075,0.0014950634],"genre_scores_gemma":[0.95207196,0.00009107686,0.04721044,0.000016298127,0.0000045501183,0.000058523015,0.000048771322,0.000020318545,0.0004780919],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99972004,0.00005657226,0.000018754967,0.00005601025,0.000105059895,0.000043559885],"domain_scores_gemma":[0.9996958,0.00013005553,0.000076278004,0.000017482493,0.00006635951,0.0000140825605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007011807,0.0008269602,0.0007009295,0.00062237226,0.00022057228,0.0006890978,0.0005032627,0.00056315766,0.00034723405],"category_scores_gemma":[0.0007376644,0.0003252153,0.00075175794,0.0003057031,0.00026420938,0.0003498846,0.00034036365,0.0003269796,0.000052550095],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017172545,0.00021313792,0.006130089,0.00033643446,0.00012900165,0.000107325286,0.00014946313,0.78620535,0.12769957,0.00054117583,0.00013537824,0.07818139],"study_design_scores_gemma":[0.000016955866,0.0005596768,0.006855829,0.000011356078,0.000071840484,0.000040373838,0.00008202783,0.9773616,0.014386287,0.00029837462,0.00029435867,0.000021236616],"about_ca_topic_score_codex":0.0024659964,"about_ca_topic_score_gemma":0.0033401647,"teacher_disagreement_score":0.0024659964,"about_ca_system_score_codex":0.00032815602,"about_ca_system_score_gemma":0.0005564571,"threshold_uncertainty_score":0.0049033165},"labels":[],"label_agreement":null},{"id":"W4407367720","doi":"10.1016/j.wear.2025.205855","title":"On the tribological and thermal aspects of cryogenic machining of Inconel 718 and their effects on surface integrity","year":2025,"lang":"en","type":"article","venue":"Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Inconel; Surface integrity; Materials science; Tribology; Machining; Cryogenic temperature; Metallurgy; Cryogenic treatment; Thermal; Forensic engineering; Mechanical engineering; Composite material; Engineering; Thermodynamics; Microstructure; Alloy","score_opus":0.006708179285393088,"score_gpt":0.21980651606196464,"score_spread":0.21309833677657156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407367720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964637,0.00075055147,0.0015563049,0.000030082832,0.000006994164,0.0000049969162,0.000034524262,0.000016960077,0.0011358373],"genre_scores_gemma":[0.99839264,0.00027280752,0.0005971241,0.00000629574,0.000001940352,0.0000025036493,0.000040215557,0.0000054564644,0.00068101496],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983454,0.000014949798,0.000005699637,0.000026748163,0.00008735968,0.000030646515],"domain_scores_gemma":[0.9998417,0.000046764035,0.000033381984,0.000014794176,0.000055231976,0.000008140123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000104191175,0.00017527163,0.00018832495,0.00019778212,0.00028743388,0.00019162617,0.00020852331,0.0001707731,0.0009752974],"category_scores_gemma":[0.00020985446,0.000105551895,0.00014568437,0.00021091502,0.00020256141,0.00016581919,0.00011288174,0.00019653108,0.00014012452],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017092128,0.000034211876,0.0035761711,0.00020134167,0.0000108186605,0.00023913792,0.00017913643,0.004388778,0.96832085,0.00025319663,0.00018448506,0.022440808],"study_design_scores_gemma":[0.0000071916584,0.0007531182,0.05754157,0.000022902586,0.00003782341,0.0003567001,0.0002460807,0.017239282,0.91871876,0.0001245865,0.004924621,0.00002739779],"about_ca_topic_score_codex":0.002290418,"about_ca_topic_score_gemma":0.00455248,"teacher_disagreement_score":0.002290418,"about_ca_system_score_codex":0.0002453138,"about_ca_system_score_gemma":0.00015796407,"threshold_uncertainty_score":0.004554212},"labels":[],"label_agreement":null},{"id":"W4407379906","doi":"10.1080/15440478.2025.2461493","title":"Analysis of Entry and Exit Hole Delaminations During Drilling of Jute/Palm Fiber Reinforced Hybrid Composites Using HSS Drill Bits","year":2025,"lang":"en","type":"article","venue":"Journal of Natural Fibers","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"United Arab Emirates University","keywords":"Composite material; Drilling; Materials science; Drill; Fiber; Delamination (geology); Palm; Drill hole; Drill bit; Geology","score_opus":0.004495922378027631,"score_gpt":0.2368008665558196,"score_spread":0.232304944177792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407379906","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995458,0.00007783384,0.004202515,0.0000036245717,0.0000022697354,0.000008453284,0.00004897262,0.00003971726,0.00015867718],"genre_scores_gemma":[0.99518716,0.00005479924,0.0043877834,0.0000030725416,8.277271e-7,0.0000068654012,0.000060028644,0.000008679963,0.0002907837],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99982435,0.00001642217,0.000012794904,0.00003563837,0.00008364327,0.000027175562],"domain_scores_gemma":[0.9993538,0.00020998844,0.00018015337,0.000045715533,0.00018136176,0.000029055485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027930705,0.00024101326,0.00022438023,0.0004590553,0.00015330812,0.00021855171,0.00016916297,0.00027247448,0.0005836007],"category_scores_gemma":[0.00047952848,0.00022338465,0.00022172717,0.0001937319,0.0002882748,0.00035072136,0.00016767705,0.00024836694,0.00010660367],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032741544,0.00003152517,0.008115512,0.000103124235,0.000007588369,0.00014871603,0.00023231517,0.0015000368,0.9797019,0.000043160537,0.000026483738,0.009762397],"study_design_scores_gemma":[0.0000066228745,0.0011746063,0.08556262,0.000018977795,0.000031577834,0.00036719715,0.0005947,0.021397123,0.89012027,0.00007401795,0.00062097923,0.000031352447],"about_ca_topic_score_codex":0.0005786623,"about_ca_topic_score_gemma":0.0016147707,"teacher_disagreement_score":0.0005836007,"about_ca_system_score_codex":0.00010313969,"about_ca_system_score_gemma":0.00009658161,"threshold_uncertainty_score":0.0019522905},"labels":[],"label_agreement":null},{"id":"W4407566275","doi":"10.1007/s10751-025-02269-w","title":"Parametric analysis in the machining of gun metal using computer numerical control turning process","year":2025,"lang":"en","type":"article","venue":"Interactions","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Machining; Parametric statistics; Process (computing); Process analysis; Numerical control; Mechanical engineering; Engineering; Computer science; Materials science; Mathematics; Process engineering; Statistics","score_opus":0.009369737481133773,"score_gpt":0.30786698608430135,"score_spread":0.29849724860316756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407566275","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59111875,0.00037927483,0.39056918,0.00014047377,0.000046688165,0.000049969574,0.000030515997,0.0002831779,0.017381907],"genre_scores_gemma":[0.9916726,0.00004052773,0.00756589,0.000004753123,0.00000387561,0.000012291377,0.000007151728,0.000010338717,0.00068254996],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99976796,0.000055429413,0.000005617832,0.00001967627,0.00012436118,0.000027023569],"domain_scores_gemma":[0.9996214,0.00022135221,0.00003261914,0.000033224573,0.00008250639,0.000008861403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033578186,0.0002068092,0.00027491114,0.00035993612,0.0004016001,0.0005020866,0.0005319896,0.0004417146,0.0011996576],"category_scores_gemma":[0.0012274612,0.00021385717,0.00025866702,0.00030299014,0.0005517832,0.000334335,0.00030525782,0.00037067925,0.00007263277],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017209104,0.00006413724,0.0012614001,0.00006579398,0.000016665508,0.000104492334,0.00013326973,0.91523623,0.038247198,0.010389391,0.0002510732,0.0340582],"study_design_scores_gemma":[0.000004820484,0.00003923425,0.00089710596,0.0000018030036,0.0000044578696,0.000029699144,0.000012240901,0.99436873,0.0036673988,0.00065258075,0.00031554018,0.000006336606],"about_ca_topic_score_codex":0.0031509837,"about_ca_topic_score_gemma":0.002424904,"teacher_disagreement_score":0.0031509837,"about_ca_system_score_codex":0.0003098805,"about_ca_system_score_gemma":0.0004776307,"threshold_uncertainty_score":0.0062652826},"labels":[],"label_agreement":null},{"id":"W4407768837","doi":"10.1088/1742-6596/2951/1/012032","title":"Research on effect of pre-stress on cutting force of metal bar surface notching in low-stress cropping","year":2025,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Notching; Bar (unit); Materials science; Stress (linguistics); Metallurgy; Composite material; Geology","score_opus":0.017824704718483634,"score_gpt":0.32141990112550206,"score_spread":0.30359519640701843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407768837","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98974866,0.0006623917,0.008264108,0.000057220164,0.00004154543,0.000014418089,0.000030812815,0.000060077153,0.0011207107],"genre_scores_gemma":[0.99844736,0.00017160943,0.0009864799,0.000012340745,0.0000052746122,0.000004764074,0.000014741119,0.0000044218464,0.0003529846],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997553,0.0000141358105,0.00001079581,0.00005059048,0.00012696402,0.00004220862],"domain_scores_gemma":[0.99950135,0.00011888798,0.00008106366,0.000031936044,0.00022558415,0.00004124515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024768824,0.00028136853,0.00026666163,0.0002611144,0.0002343739,0.00027232722,0.0002709334,0.00034511616,0.0010748483],"category_scores_gemma":[0.0005401228,0.0001799228,0.0002249545,0.00017817851,0.00022559072,0.00050203607,0.00014422892,0.00022346622,0.00013663383],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023101026,0.000053097967,0.0030889765,0.0001578439,0.000010596687,0.00014444182,0.0001260613,0.0012922195,0.97771156,0.0001757809,0.000118618955,0.01688981],"study_design_scores_gemma":[0.00002380227,0.0010746778,0.03288619,0.000020924335,0.000055560446,0.00019084931,0.00026653273,0.02311057,0.94073415,0.0001989696,0.001403257,0.000034599056],"about_ca_topic_score_codex":0.00093912525,"about_ca_topic_score_gemma":0.0009908458,"teacher_disagreement_score":0.0010748483,"about_ca_system_score_codex":0.00019153154,"about_ca_system_score_gemma":0.00018164382,"threshold_uncertainty_score":0.0035957098},"labels":[],"label_agreement":null},{"id":"W4407959043","doi":"10.1016/j.rineng.2025.104415","title":"Enhancing machining efficiency of UNS S45000 alloy steel using cryogenically treated TiAlSiN coated tungsten carbide inserts","year":2025,"lang":"en","type":"article","venue":"Results in Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Tungsten carbide; Metallurgy; Machining; Carbide; Materials science; Alloy; Tungsten","score_opus":0.006987619993166115,"score_gpt":0.23798515823746286,"score_spread":0.23099753824429675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407959043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99833906,0.00031324662,0.0006271021,0.000009660903,0.0000050241656,0.000007974065,0.000050829552,0.00002266532,0.00062443985],"genre_scores_gemma":[0.99730337,0.00016479028,0.0013571836,0.0000072527014,0.0000013279589,0.000004638547,0.00009866699,0.000019246238,0.0010434985],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998405,0.000009536935,0.000010677082,0.000028207465,0.00008113,0.000029861547],"domain_scores_gemma":[0.99985874,0.000013798054,0.000051824954,0.000015195065,0.000046414003,0.000014050645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013074686,0.00023035008,0.00020040174,0.00026428193,0.00014541762,0.0003058862,0.0002776466,0.00025618833,0.0007270208],"category_scores_gemma":[0.00017800056,0.0001772741,0.00028547848,0.00018418544,0.00016462377,0.000163915,0.000116105075,0.0001774713,0.00024092133],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006179919,0.000007907573,0.00042688882,0.000050056486,0.0000047289113,0.000042074953,0.000023326536,0.00016804303,0.99801314,0.000013834442,0.000024773375,0.0011634592],"study_design_scores_gemma":[0.000005112457,0.00043920544,0.009126949,0.0000052855253,0.000017362647,0.00007518392,0.000034165467,0.0010033102,0.9884043,0.0000041558114,0.00087807374,0.0000070070864],"about_ca_topic_score_codex":0.0013572649,"about_ca_topic_score_gemma":0.006053039,"teacher_disagreement_score":0.0013572649,"about_ca_system_score_codex":0.0002723467,"about_ca_system_score_gemma":0.00016139583,"threshold_uncertainty_score":0.0026987195},"labels":[],"label_agreement":null},{"id":"W4408016836","doi":"10.1109/tii.2025.3540469","title":"Stabilizing a Class of Periodical Time-Delay Milling Systems by Adaptive Active Control Method","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China","keywords":"Class (philosophy); Control theory (sociology); Control system; Computer science; Adaptive control; Control (management); Adaptive system; Control engineering; Engineering; Electrical engineering; Artificial intelligence","score_opus":0.015347185778849954,"score_gpt":0.2505659944623438,"score_spread":0.23521880868349385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408016836","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07911296,0.00030379716,0.91628075,0.00008907224,0.000040189032,0.000031340198,0.00001538466,0.00015052925,0.003975972],"genre_scores_gemma":[0.98524725,0.00013518445,0.013373521,0.000017126496,0.000015662217,0.000035554407,0.000013749104,0.0000054201973,0.0011565702],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985707,0.000027502858,0.0000075288576,0.000044394455,0.000044727964,0.000018785697],"domain_scores_gemma":[0.99979883,0.00008671031,0.000053542117,0.000014872647,0.000036867208,0.000009277502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027031676,0.000588542,0.0004286552,0.00028748103,0.00024818987,0.00050822314,0.0005791418,0.0004102188,0.0006666963],"category_scores_gemma":[0.0004528368,0.00016304782,0.00033524464,0.00021407077,0.0006146594,0.00029490594,0.0004865983,0.0004213883,0.00006991829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015680917,0.000078446275,0.00076860463,0.00019807304,0.00006944681,0.00035571196,0.00022331438,0.84551567,0.055674985,0.024184331,0.0008096701,0.07196494],"study_design_scores_gemma":[0.000006549482,0.00004362502,0.00008481113,0.0000020633715,0.000004752075,0.00001715965,0.000007098217,0.9980414,0.0009490808,0.0006441307,0.00019682336,0.0000024766243],"about_ca_topic_score_codex":0.0018097605,"about_ca_topic_score_gemma":0.0012489941,"teacher_disagreement_score":0.0018097605,"about_ca_system_score_codex":0.00022625762,"about_ca_system_score_gemma":0.00029747083,"threshold_uncertainty_score":0.0035985112},"labels":[],"label_agreement":null},{"id":"W4408163795","doi":"10.1177/09544062251323061","title":"Temperature and tool wear effects on the milling process of Ti6Al4V titanium alloy","year":2025,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; University of Regina","funders":"","keywords":"Titanium alloy; Metallurgy; Materials science; Alloy; Titanium; Process (computing); Computer science","score_opus":0.004419397385427663,"score_gpt":0.21458980487105075,"score_spread":0.2101704074856231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408163795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989103,0.00019865566,0.00057243777,0.000009195184,0.0000070894384,0.000004033928,0.000035144658,0.000019986051,0.00024312263],"genre_scores_gemma":[0.999445,0.000047669182,0.00029852852,0.0000031621357,0.0000017972857,0.0000021256683,0.000027467937,0.0000057769803,0.00016851653],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99973434,0.000022940658,0.000023934153,0.000042335527,0.00013922584,0.00003722255],"domain_scores_gemma":[0.99895704,0.0005735165,0.00016668829,0.000092558956,0.00018906569,0.000021010002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035579765,0.000244818,0.00034821863,0.00028503517,0.00023366637,0.00042709167,0.00030144263,0.0003385896,0.00067690964],"category_scores_gemma":[0.0009647148,0.00021768427,0.0003777798,0.00026736988,0.00023603093,0.00026349898,0.00013365698,0.0002363942,0.00013577405],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023654872,0.00029528278,0.025668625,0.00065949775,0.000092652495,0.0006804483,0.0008225393,0.06055272,0.86581,0.0002488535,0.00040258982,0.042401206],"study_design_scores_gemma":[0.000048136015,0.003487003,0.13085446,0.00003946727,0.000109156324,0.00038934825,0.0004937787,0.14470969,0.7182623,0.00015661889,0.0013607589,0.00008931963],"about_ca_topic_score_codex":0.0011975693,"about_ca_topic_score_gemma":0.0016912797,"teacher_disagreement_score":0.0011975693,"about_ca_system_score_codex":0.00028575622,"about_ca_system_score_gemma":0.00012746787,"threshold_uncertainty_score":0.0023812056},"labels":[],"label_agreement":null},{"id":"W4408249754","doi":"10.1016/j.jmapro.2025.02.070","title":"Proposal of tilted helical grinding for grooving ZrO2 ceramics – Investigation of groove profile formation and machining performance","year":2025,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Southern University of Science and Technology; Science, Technology and Innovation Commission of Shenzhen Municipality; South University of Science and Technology of China","keywords":"Materials science; Groove (engineering); Grinding; Machining; Ceramic; Composite material; Metallurgy","score_opus":0.00806249846957918,"score_gpt":0.2278806978163218,"score_spread":0.21981819934674263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408249754","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9510243,0.00056609075,0.045662157,0.000070658076,0.00007525659,0.00008427809,0.00009780942,0.00028717783,0.002132195],"genre_scores_gemma":[0.9657246,0.00017185863,0.03313809,0.00001734926,0.000010441468,0.00001688503,0.00006671386,0.000018951967,0.0008350474],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981123,0.0000127135345,0.000006861702,0.00005992882,0.00007774427,0.00003151468],"domain_scores_gemma":[0.9998313,0.000020429403,0.000038321064,0.00004755808,0.000042444502,0.000019865469],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022641366,0.00029269228,0.00033127674,0.00018628189,0.0002399823,0.0003552601,0.0005469455,0.00038974965,0.0007203189],"category_scores_gemma":[0.00026378853,0.00026983267,0.00026631964,0.00019328394,0.00035467837,0.0002864832,0.00020192139,0.00025690452,0.00025368502],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011339267,0.000021268761,0.00047182172,0.00004873145,0.0000063161565,0.000067005116,0.00002263685,0.0009433344,0.9947373,0.0005029035,0.00005605197,0.0030093326],"study_design_scores_gemma":[0.00006215533,0.0010628618,0.008027436,0.000005501815,0.000029652074,0.000392456,0.000060473147,0.029997364,0.9580758,0.00021268449,0.0020400658,0.000033601482],"about_ca_topic_score_codex":0.00056701835,"about_ca_topic_score_gemma":0.0009747898,"teacher_disagreement_score":0.0007203189,"about_ca_system_score_codex":0.00020392567,"about_ca_system_score_gemma":0.00036132868,"threshold_uncertainty_score":0.0024096966},"labels":[],"label_agreement":null},{"id":"W4408844047","doi":"10.4028/p-6r9nxi","title":"Optimization of Precision Boring Conditions to Enhance the Surface Integrity of a Landing Gear Component","year":2025,"lang":"en","type":"article","venue":"Defect and diffusion forum/Diffusion and defect data, solid state data. Part A, Defect and diffusion forum","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Polytechnique Montréal","funders":"","keywords":"Component (thermodynamics); Surface integrity; Landing gear; Surface (topology); Computer science; Engineering; Mechanical engineering; Aerospace engineering; Physics; Mathematics","score_opus":0.017201894420952477,"score_gpt":0.3108001250669107,"score_spread":0.2935982306459582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408844047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9858255,0.0010683773,0.011586753,0.0000342017,0.0000198583,0.00003336777,0.000060832783,0.000074153155,0.001296989],"genre_scores_gemma":[0.9935091,0.00030525366,0.0058334903,0.000007960045,0.000003770983,0.000012046495,0.00004782102,0.00001710109,0.00026336452],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977285,0.000021004413,0.000020803325,0.000046584908,0.0000908775,0.000047776946],"domain_scores_gemma":[0.99976486,0.000049660157,0.00009894476,0.000020074967,0.00005084019,0.000015564689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032674154,0.0004283642,0.0004184836,0.00041767792,0.00021307073,0.00048545652,0.00025880465,0.00025743758,0.0007982342],"category_scores_gemma":[0.0004996172,0.00020558317,0.00024775648,0.00032407168,0.0001932736,0.00036393115,0.00021164045,0.00025169647,0.0001876952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000245012,0.00007009121,0.0017376463,0.0003100617,0.000013982581,0.00010666628,0.0000612471,0.0055450606,0.97920966,0.00018739162,0.000106308406,0.01240688],"study_design_scores_gemma":[0.00003896278,0.0021823077,0.014609769,0.000026363636,0.00007575792,0.00016011238,0.00017336363,0.01265454,0.9672377,0.00016899339,0.0026457522,0.000026375355],"about_ca_topic_score_codex":0.00047151675,"about_ca_topic_score_gemma":0.001258423,"teacher_disagreement_score":0.0007982342,"about_ca_system_score_codex":0.00020408303,"about_ca_system_score_gemma":0.00027295394,"threshold_uncertainty_score":0.0026703477},"labels":[],"label_agreement":null},{"id":"W4409075470","doi":"10.21203/rs.3.rs-6230011/v1","title":"Remaining thickness error modeling during thin floor milling","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Association of Emergency Physicians","funders":"","keywords":"Materials science; Geology; Computer science","score_opus":0.05888650941812669,"score_gpt":0.37704921085721954,"score_spread":0.31816270143909287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409075470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5224685,0.00040222635,0.47114444,0.000100264144,0.000090372814,0.000026573029,0.00014283035,0.00062027294,0.0050045447],"genre_scores_gemma":[0.9746105,0.00007043729,0.02301988,0.000010614863,0.0000075782623,0.000007742322,0.00006587805,0.00016407455,0.002043432],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997255,0.000059502505,0.0000126369105,0.000046683566,0.00011916088,0.000036487385],"domain_scores_gemma":[0.998607,0.0007793923,0.00015920692,0.00017642578,0.00023626283,0.000041790096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005836636,0.000537582,0.00045194777,0.00029722106,0.00023103082,0.00065141503,0.0006490908,0.0006184894,0.0011795015],"category_scores_gemma":[0.002164223,0.0002925709,0.00028528585,0.000289941,0.00036443456,0.0005500981,0.00043650062,0.0005121854,0.00017184939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000194232,0.000030067564,0.0008036597,0.000056096196,0.000013050265,0.00009048336,0.000049251656,0.9693665,0.012305637,0.0010848569,0.00017332433,0.015832797],"study_design_scores_gemma":[0.0000018717843,0.00001433815,0.00023876826,0.0000024281828,0.0000024211788,0.0000068916615,0.0000052651917,0.9952632,0.0042509083,0.000147062,0.00006438482,0.0000023870084],"about_ca_topic_score_codex":0.0046405066,"about_ca_topic_score_gemma":0.0034415724,"teacher_disagreement_score":0.0046405066,"about_ca_system_score_codex":0.00033542368,"about_ca_system_score_gemma":0.0004900997,"threshold_uncertainty_score":0.009227037},"labels":[],"label_agreement":null},{"id":"W4409077064","doi":"10.2139/ssrn.5200921","title":"Shadow and Contact Masks for Abrasive Slurry Jet Micro-Machining of Planar Areas with Uniform Depth","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Slurry; Shadow (psychology); Planar; Machining; Jet (fluid); Abrasive; Materials science; Abrasive machining; Optics; Mechanical engineering; Metallurgy; Composite material; Physics; Engineering; Mechanics; Computer science; Computer graphics (images)","score_opus":0.005982128701097456,"score_gpt":0.23501330219628946,"score_spread":0.229031173495192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409077064","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81928056,0.001654917,0.17038721,0.00015382795,0.00013097434,0.00010297828,0.00025125628,0.00067024044,0.0073679914],"genre_scores_gemma":[0.95212644,0.00029706582,0.044644117,0.000033283457,0.000023140597,0.00003376654,0.00009747025,0.00007805327,0.002666572],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998091,0.000014511958,0.000007241334,0.000027122045,0.00011819316,0.000023783965],"domain_scores_gemma":[0.9995363,0.00019700745,0.00009339501,0.00007224038,0.0000662609,0.000034818815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016490955,0.00027328412,0.00029829727,0.0002076735,0.0001796929,0.00042578188,0.00043553673,0.00038062368,0.0013648961],"category_scores_gemma":[0.00085673295,0.00031408202,0.00017841822,0.00016904526,0.00030141417,0.00035154415,0.00040842957,0.00029430937,0.00024071468],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000745616,0.000066552486,0.0009242512,0.00028966292,0.000019360417,0.00015664056,0.0001683819,0.0065730354,0.94195354,0.0041439766,0.00065996393,0.044299062],"study_design_scores_gemma":[0.00014456984,0.0010211547,0.014125727,0.000020958407,0.000051824292,0.00083225075,0.00013950882,0.16147245,0.8138286,0.00237044,0.0059472155,0.00004537995],"about_ca_topic_score_codex":0.00058939727,"about_ca_topic_score_gemma":0.0014835247,"teacher_disagreement_score":0.0013648961,"about_ca_system_score_codex":0.00032984253,"about_ca_system_score_gemma":0.0004005326,"threshold_uncertainty_score":0.004566014},"labels":[],"label_agreement":null},{"id":"W4409082746","doi":"10.18280/mmep.120325","title":"Improving Efficiency and Surface Quality in Hard Turning of SKD61 Steel Through Cooling and Cutting Parameter Optimization","year":2025,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Quality (philosophy); Materials science; Surface (topology); Mechanical engineering; Metallurgy; Process engineering; Manufacturing engineering; Engineering drawing; Engineering; Mathematics; Geometry; Physics","score_opus":0.016757327915476017,"score_gpt":0.23953834204048952,"score_spread":0.2227810141250135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409082746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95008004,0.00038325516,0.045567155,0.00005642258,0.000016155136,0.000019856723,0.000026892703,0.000095005176,0.0037552046],"genre_scores_gemma":[0.9948974,0.000068955866,0.0042721764,0.0000050254157,0.0000026359046,0.00000578338,0.000025348027,0.000025305084,0.0006973866],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981576,0.000027545451,0.00000674066,0.000024619374,0.00008124567,0.000043985445],"domain_scores_gemma":[0.99973816,0.00011785073,0.00004836746,0.000022592214,0.000060712337,0.000012385156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036047507,0.00032938624,0.000505326,0.00044047734,0.0002921386,0.00075978605,0.00030782056,0.00036200514,0.00070741173],"category_scores_gemma":[0.0004980571,0.00021822375,0.0004023481,0.00032506775,0.00037971308,0.0003415569,0.00031500054,0.00028761977,0.000109749344],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073146477,0.00023274972,0.0040306333,0.00031079378,0.00005056916,0.00010156258,0.00010470621,0.49700633,0.43633932,0.0025375881,0.0004361819,0.058118124],"study_design_scores_gemma":[0.000054236116,0.0007681856,0.0077835047,0.000010547815,0.00006171947,0.000062099934,0.00006862007,0.7959902,0.19340076,0.0010521493,0.0007218893,0.000026175074],"about_ca_topic_score_codex":0.0013270399,"about_ca_topic_score_gemma":0.0018991793,"teacher_disagreement_score":0.0013270399,"about_ca_system_score_codex":0.00040258002,"about_ca_system_score_gemma":0.0003213495,"threshold_uncertainty_score":0.0029209852},"labels":[],"label_agreement":null},{"id":"W4409222705","doi":"10.3390/jmmp9040123","title":"Cutting Fluid Effectiveness in the High-Speed Finish Machining of Inconel 718 Using a Whisker-Reinforced Ceramic Tool","year":2025,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inconel; Whisker; Machining; Materials science; Ceramic; Cutting fluid; Metallurgy; Superalloy; Composite material; Mechanical engineering; Engineering; Alloy","score_opus":0.007256684951354789,"score_gpt":0.2447065516837956,"score_spread":0.2374498667324408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409222705","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99892443,0.00032784275,0.0005992637,0.0000042818456,0.0000024705791,0.000004466019,0.000010481797,0.000009923975,0.00011681069],"genre_scores_gemma":[0.9985863,0.00013532586,0.0010870352,0.0000038571525,0.0000018919984,0.0000029973255,0.000019487617,0.0000057789784,0.00015738892],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995029,0.00007201208,0.00003133578,0.0000776052,0.00022438017,0.00009176179],"domain_scores_gemma":[0.99935013,0.00027352053,0.00017638472,0.00003555488,0.00013098851,0.000033257398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049187493,0.00031870793,0.0003511769,0.0004601405,0.00023524728,0.00051799306,0.0003140946,0.0004595562,0.0005034733],"category_scores_gemma":[0.0010292684,0.00018968194,0.00030666,0.00024602,0.00041583457,0.0006633767,0.00026974082,0.00024397214,0.000102267084],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006885248,0.00006680966,0.004094679,0.0002438523,0.00002371742,0.00018949933,0.00027032354,0.0014104987,0.97683036,0.000051944007,0.000025218693,0.016104486],"study_design_scores_gemma":[0.00001701157,0.002323857,0.028998895,0.000014320043,0.00005663433,0.00022427356,0.00033250533,0.0051351595,0.962111,0.000032160235,0.00072288903,0.00003130674],"about_ca_topic_score_codex":0.0009823785,"about_ca_topic_score_gemma":0.0015266103,"teacher_disagreement_score":0.0009823785,"about_ca_system_score_codex":0.00022621016,"about_ca_system_score_gemma":0.0002213307,"threshold_uncertainty_score":0.0026013255},"labels":[],"label_agreement":null},{"id":"W4409343637","doi":"10.1177/08927057251331573","title":"Formation and occurrence of subsurface damage mechanism with the analysis of optimal machining strategy when milling different fibre matrix combination of unidirectional FRP’s","year":2025,"lang":"en","type":"article","venue":"Journal of Thermoplastic Composite Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Materials science; Machining; Fibre-reinforced plastic; Composite material; Mechanism (biology); Matrix (chemical analysis); Metallurgy","score_opus":0.005500699310156372,"score_gpt":0.2271521295653832,"score_spread":0.22165143025522682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409343637","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99401265,0.00026839154,0.0050663752,0.0000065341137,0.0000025461475,0.0000075355083,0.00004322785,0.000038274196,0.000554422],"genre_scores_gemma":[0.99712,0.00009189298,0.0023594366,0.0000022677066,7.678194e-7,0.000004746506,0.000043248747,0.0000066189764,0.00037111517],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99989116,0.0000066921725,0.0000053222216,0.000024721037,0.000052783293,0.000019280193],"domain_scores_gemma":[0.99980587,0.00003757293,0.00007032137,0.000016114362,0.00005701395,0.00001320599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001373845,0.00019710005,0.00014071217,0.00034765573,0.00011097218,0.00019805858,0.0001666523,0.00035552066,0.0006935787],"category_scores_gemma":[0.00021900624,0.0001762092,0.00017711392,0.00019404545,0.0001882099,0.00020356882,0.000074176685,0.00016303771,0.00013342459],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024581052,0.000052024712,0.008066134,0.00017427036,0.000017438515,0.0002721591,0.00010665792,0.017992528,0.9587784,0.000162595,0.00008789546,0.01404407],"study_design_scores_gemma":[0.0000107311125,0.0012827023,0.10602907,0.000022890072,0.00004989705,0.0006307534,0.00025625338,0.124067985,0.7662117,0.00029424808,0.0011120412,0.00003187512],"about_ca_topic_score_codex":0.00047912064,"about_ca_topic_score_gemma":0.0009478096,"teacher_disagreement_score":0.0006935787,"about_ca_system_score_codex":0.00013796844,"about_ca_system_score_gemma":0.000077749864,"threshold_uncertainty_score":0.0023202896},"labels":[],"label_agreement":null},{"id":"W4409482602","doi":"10.1016/j.jmapro.2025.04.017","title":"Application of novel soft solid lubricant coatings on turning tools for sustainable and high-performance machining of INC 718 alloy: A new efficient fluid-free method","year":2025,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Lubricant; Machining; Alloy; Metallurgy; Cutting fluid; Mechanical engineering; Manufacturing engineering; Composite material; Engineering","score_opus":0.008996295423973451,"score_gpt":0.2637091000137774,"score_spread":0.25471280458980394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409482602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97198504,0.0026536705,0.020260388,0.00008019659,0.00011730392,0.000040366318,0.000051367046,0.00017374067,0.0046380027],"genre_scores_gemma":[0.9844967,0.0007681429,0.012135504,0.000026348791,0.00001757952,0.000011972481,0.000047076108,0.00003119593,0.0024655818],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998474,0.000008850095,0.0000092740775,0.000022873888,0.00007920274,0.000032330958],"domain_scores_gemma":[0.9999337,0.000009180785,0.000017718683,0.0000088184215,0.000020485912,0.000010068437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010595901,0.00036605785,0.0003267565,0.00028920552,0.00017864464,0.00041783144,0.00034124867,0.00035535207,0.00068492844],"category_scores_gemma":[0.00013923799,0.00018441194,0.00025478963,0.0001557575,0.00020781175,0.00030677608,0.00034270273,0.00028622683,0.00022361477],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035276884,0.000010451711,0.0000648331,0.000063743755,0.000004402058,0.00005069519,0.000019953157,0.00011271799,0.99488384,0.00015982657,0.000049659688,0.004544661],"study_design_scores_gemma":[0.000007700828,0.00012881335,0.000385375,0.0000025559418,0.00000912581,0.00010810429,0.0000133196645,0.0018906217,0.99570125,0.000025875517,0.0017211991,0.0000059771637],"about_ca_topic_score_codex":0.00039179574,"about_ca_topic_score_gemma":0.0015778075,"teacher_disagreement_score":0.00068492844,"about_ca_system_score_codex":0.00020568437,"about_ca_system_score_gemma":0.0002219814,"threshold_uncertainty_score":0.0022912621},"labels":[],"label_agreement":null},{"id":"W4409647190","doi":"10.23977/jemm.2025.100109","title":"Research on Optimization of Cutting Force of TC4 Titanium Alloy Based on Support Vector Machine","year":2025,"lang":"en","type":"article","venue":"Journal of Engineering Mechanics and Machinery","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Titanium alloy; Alloy; Materials science; Support vector machine; Titanium; Mechanical engineering; Computer science; Metallurgy; Engineering; Artificial intelligence","score_opus":0.01106271591303433,"score_gpt":0.27021481937874686,"score_spread":0.25915210346571255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409647190","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31042767,0.0014654987,0.68278855,0.00017957916,0.00006910135,0.000086343585,0.0000692041,0.00067922834,0.0042348444],"genre_scores_gemma":[0.9598361,0.0004597157,0.03826324,0.0000245328,0.000012672342,0.000058060305,0.00010942034,0.000027760785,0.0012084252],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958855,0.00003797731,0.000023476352,0.00008095252,0.00022020818,0.00004879574],"domain_scores_gemma":[0.9996841,0.00010843118,0.000050301795,0.00001455416,0.00012974629,0.000012895784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004644961,0.00081128906,0.0005890651,0.0005683231,0.00022995158,0.000554114,0.00053659163,0.0005144226,0.0006577477],"category_scores_gemma":[0.00077234756,0.00035064647,0.0005435215,0.0005102869,0.0002082783,0.00058355986,0.00018813222,0.00037961375,0.00011081345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002116651,0.00017732517,0.003911824,0.00041002894,0.00008339663,0.000081508726,0.000073466974,0.6642483,0.0789288,0.0020293328,0.000867117,0.24897724],"study_design_scores_gemma":[0.000007564338,0.00013932351,0.0009148526,0.000003985141,0.000014602727,0.000012179992,0.0000101240275,0.9918035,0.006605858,0.00015210154,0.0003291254,0.0000066075495],"about_ca_topic_score_codex":0.005655721,"about_ca_topic_score_gemma":0.003354035,"teacher_disagreement_score":0.005655721,"about_ca_system_score_codex":0.00041898535,"about_ca_system_score_gemma":0.0007837158,"threshold_uncertainty_score":0.011245549},"labels":[],"label_agreement":null},{"id":"W4409795100","doi":"10.61091/jcmcc127b-426","title":"Classification and identification of tempered flexural organization of spring steel based on improved GLCM-Resnet18","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Spring (device); Identification (biology); Forensic engineering; Engineering; Ecology; Structural engineering; Biology","score_opus":0.00740590983965505,"score_gpt":0.238190643363027,"score_spread":0.23078473352337195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409795100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.896467,0.00088270777,0.09178146,0.00027272373,0.00017503425,0.00011536115,0.002594557,0.0029774997,0.004733679],"genre_scores_gemma":[0.96549505,0.000242079,0.02529127,0.00008448175,0.000040166407,0.000046715402,0.0047726845,0.00007325664,0.0039542294],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997557,0.000015693025,0.000013252966,0.0000766852,0.00008402959,0.000054689994],"domain_scores_gemma":[0.9998023,0.000020711568,0.000030373421,0.000020689104,0.000102947735,0.000022950708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027940853,0.0010689654,0.00059705134,0.0026204563,0.00023787489,0.00042610307,0.00073056563,0.00064815884,0.001391421],"category_scores_gemma":[0.00047310378,0.00020603315,0.000804374,0.00085001957,0.00029644876,0.0005201431,0.00033971836,0.00040305255,0.0005214494],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017227271,0.0006701081,0.060135107,0.0005724522,0.0003489549,0.0014208814,0.00022898644,0.19641604,0.1530512,0.0016855595,0.02069536,0.56305265],"study_design_scores_gemma":[0.000029207173,0.00016075838,0.039125837,0.000020591126,0.00005617409,0.00018550936,0.00011870616,0.93575346,0.022389857,0.00065554027,0.0014715998,0.000032758806],"about_ca_topic_score_codex":0.013086314,"about_ca_topic_score_gemma":0.022523047,"teacher_disagreement_score":0.013086314,"about_ca_system_score_codex":0.00055167696,"about_ca_system_score_gemma":0.00049415766,"threshold_uncertainty_score":0.026020288},"labels":[],"label_agreement":null},{"id":"W4409799887","doi":"10.11159/icsect25.169","title":"Enhancing Cement Grinding Efficiency: Performance of Combined Polycarboxylate Ether and Triethanolamine Admixtures","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Civil, Structural, and Environmental Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; Bursa Uludağ Üniversitesi","keywords":"Triethanolamine; Grinding; Cement; Materials science; Ether; Composite material; Process engineering; Chemistry; Chromatography; Organic chemistry; Engineering","score_opus":0.002414814349562342,"score_gpt":0.17913988768891528,"score_spread":0.17672507333935294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409799887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941791,0.0030170525,0.0016530128,0.00003124208,0.000026463682,0.000034902758,0.00011939207,0.00005574286,0.0008830731],"genre_scores_gemma":[0.9894426,0.00251637,0.006451129,0.00002670752,0.000008931635,0.000023256554,0.00011827425,0.000033367527,0.0013792601],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995956,0.000046097015,0.000042838175,0.000094379306,0.0001613863,0.000059777944],"domain_scores_gemma":[0.9997633,0.00006917658,0.00006567358,0.000020439453,0.000046931837,0.000034410477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038878908,0.0007380289,0.0004814147,0.00053134654,0.00014917436,0.00038949912,0.0003107921,0.00038539674,0.0006924513],"category_scores_gemma":[0.0005381333,0.00027987963,0.0005622497,0.0004982321,0.000156377,0.00045443804,0.0002861188,0.00070747244,0.00020861242],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009474025,0.000042903815,0.00014797294,0.00009410066,0.00001211235,0.000029457118,0.000017081184,0.0001729626,0.9969951,0.000014539159,0.0000125488,0.0023665885],"study_design_scores_gemma":[0.0000049807295,0.00046199615,0.0017131843,0.000005876838,0.00002540694,0.000038804406,0.0000093090175,0.00052113144,0.996588,0.0000034884756,0.0006206536,0.000007157846],"about_ca_topic_score_codex":0.0012042824,"about_ca_topic_score_gemma":0.004231642,"teacher_disagreement_score":0.0012042824,"about_ca_system_score_codex":0.00028027777,"about_ca_system_score_gemma":0.00019780794,"threshold_uncertainty_score":0.0023946166},"labels":[],"label_agreement":null},{"id":"W4409879910","doi":"10.1016/j.ijmecsci.2025.110311","title":"Investigation on ultra-precision machining of eccentric shaft by applying UEVC","year":2025,"lang":"en","type":"article","venue":"International Journal of Mechanical Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MD Precision (Canada)","funders":"China National Funds for Distinguished Young Scientists; National Natural Science Foundation of China","keywords":"Machining; Eccentric; Mechanical engineering; Engineering; Structural engineering; Materials science; Engineering drawing","score_opus":0.0181249373304991,"score_gpt":0.29053245755850365,"score_spread":0.2724075202280046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409879910","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9647603,0.0014722723,0.02709846,0.00008083088,0.000057234112,0.000020718662,0.00001954504,0.00009606836,0.0063944757],"genre_scores_gemma":[0.9954183,0.00020131869,0.003431567,0.000011217662,0.0000067440997,0.0000035002847,0.000011639931,0.0000070308743,0.0009086016],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996877,0.000025705063,0.000009847609,0.000049955186,0.0001790418,0.000047818776],"domain_scores_gemma":[0.99970573,0.00009758556,0.00004383639,0.000042906024,0.00009781328,0.000011999961],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002380689,0.0001735564,0.0002827529,0.00022761906,0.0002783633,0.00038046116,0.00045172664,0.0004527114,0.0010451584],"category_scores_gemma":[0.00053893717,0.00013692441,0.00019762508,0.00033051174,0.0003340833,0.0004440973,0.00022099288,0.00019548467,0.0001098774],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035295886,0.000043132382,0.0033302337,0.00033276083,0.000017430348,0.0004407736,0.00022866653,0.00552268,0.9494055,0.0018560387,0.00022203189,0.038247705],"study_design_scores_gemma":[0.000029719487,0.001128796,0.03121053,0.000047601425,0.00005994679,0.0008328779,0.00040874255,0.07669802,0.8815299,0.000616501,0.0074012587,0.00003612929],"about_ca_topic_score_codex":0.00050832244,"about_ca_topic_score_gemma":0.00063756696,"teacher_disagreement_score":0.0010451584,"about_ca_system_score_codex":0.00014308581,"about_ca_system_score_gemma":0.00019435192,"threshold_uncertainty_score":0.0034964085},"labels":[],"label_agreement":null},{"id":"W4409914322","doi":"10.1139/tcsme-2024-0149","title":"Parameter optimization of fractional Maxwell viscoelastic system based on RSM model","year":2025,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Viscoelasticity; Applied mathematics; Fractional calculus; Mathematics; Physics; Computer science; Control theory (sociology); Mathematical analysis; Mathematical optimization; Thermodynamics","score_opus":0.006290599007770357,"score_gpt":0.19978963481031142,"score_spread":0.19349903580254108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409914322","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10302244,0.0010023589,0.8729854,0.0003235782,0.000058511276,0.00011259913,0.0001388373,0.00045335144,0.02190289],"genre_scores_gemma":[0.9204659,0.0005752719,0.07061628,0.00007294459,0.00002165307,0.00026002637,0.00019305282,0.00009493476,0.007700019],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978477,0.00006277207,0.000009987243,0.000043392538,0.00006865511,0.000030453666],"domain_scores_gemma":[0.99978405,0.000096771604,0.000039516715,0.000016098757,0.00005509349,0.000008425269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005202737,0.0008168155,0.0008369245,0.00058449415,0.00034475556,0.0007920034,0.0005861949,0.0008811367,0.0024716507],"category_scores_gemma":[0.00075119035,0.00033638952,0.0008101669,0.00048897706,0.00038744175,0.00056474144,0.0004824311,0.00048745645,0.00032341646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018609708,0.00001589629,0.00022616996,0.00005651047,0.000011477055,0.000041490162,0.000028492992,0.9860708,0.0023149247,0.002598495,0.00025329832,0.008363802],"study_design_scores_gemma":[0.0000023035439,0.00001299199,0.00006236982,0.00000290509,0.0000035885635,0.000005514691,0.000005648376,0.9989785,0.00030166705,0.00032170807,0.00029995095,0.000002797061],"about_ca_topic_score_codex":0.0051570786,"about_ca_topic_score_gemma":0.003005387,"teacher_disagreement_score":0.0051570786,"about_ca_system_score_codex":0.00049122924,"about_ca_system_score_gemma":0.00080287043,"threshold_uncertainty_score":0.010254145},"labels":[],"label_agreement":null},{"id":"W4409962040","doi":"10.1016/j.ymssp.2025.112705","title":"Automated Operational Modal Analysis of self-excited vibrations in turning","year":2025,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Research Council Canada","keywords":"Vibration; Modal analysis; Modal; Operational Modal Analysis; Acoustics; Excited state; Structural engineering; Physics; Engineering; Computer science; Materials science","score_opus":0.0065948005704076175,"score_gpt":0.24393712954028032,"score_spread":0.2373423289698727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409962040","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24925546,0.00011184771,0.7480896,0.00003210786,0.00001050988,0.00002901334,0.000034210334,0.00074637885,0.001690767],"genre_scores_gemma":[0.9750862,0.000025703264,0.024545997,0.0000052346845,0.0000035798325,0.000012565454,0.000028545883,0.000021070728,0.0002710456],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998227,0.000033381064,0.0000064432315,0.000025546935,0.00009327781,0.000018708692],"domain_scores_gemma":[0.99963796,0.00019236079,0.00005048314,0.000034536675,0.00007301826,0.000011607148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024171374,0.00027239628,0.00022869783,0.00055953383,0.00017367874,0.00030191173,0.00034006604,0.0002298983,0.000776828],"category_scores_gemma":[0.0006629192,0.0001334704,0.00022040938,0.000170944,0.00032276157,0.00025750507,0.0003462046,0.00022788158,0.00012552697],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026796488,0.00009910845,0.0047010113,0.00019442743,0.0000342237,0.00022469883,0.0006247053,0.5297952,0.1965643,0.0040965388,0.0006089655,0.26278877],"study_design_scores_gemma":[0.0000027278984,0.000030733114,0.0020372365,0.0000035282678,0.0000024954707,0.000026667645,0.000038213813,0.99156743,0.0053327437,0.0007239494,0.00022774129,0.0000065345334],"about_ca_topic_score_codex":0.0013296702,"about_ca_topic_score_gemma":0.001585747,"teacher_disagreement_score":0.0013296702,"about_ca_system_score_codex":0.00014116279,"about_ca_system_score_gemma":0.00019902385,"threshold_uncertainty_score":0.0026438236},"labels":[],"label_agreement":null},{"id":"W4409978961","doi":"10.1016/j.cirp.2025.04.073","title":"Automated identification of joints dynamic parameters in moving industrial robots for milling applications","year":2025,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Identification (biology); Robot; Engineering; Mechanical engineering; Computer science; Engineering drawing; Artificial intelligence","score_opus":0.03017928916056879,"score_gpt":0.3165895292926645,"score_spread":0.2864102401320957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409978961","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15143888,0.00024999192,0.8450303,0.0000485609,0.000018886107,0.00003570822,0.00008858179,0.0010288847,0.0020602997],"genre_scores_gemma":[0.8898638,0.00008312765,0.10805072,0.000014393603,0.000008384705,0.00003319715,0.0001234052,0.00007336773,0.0017495452],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99976856,0.00004145223,0.000009559962,0.000068793655,0.000090688976,0.000021012598],"domain_scores_gemma":[0.99973196,0.00010829943,0.000056463356,0.00004338867,0.000050623756,0.000009162281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022239093,0.0004052625,0.00045056868,0.00057339144,0.00030047796,0.00044653876,0.0003963276,0.00043111792,0.0015590978],"category_scores_gemma":[0.00083429413,0.0003468612,0.00021881172,0.00037877692,0.00031195962,0.00041558113,0.00032933473,0.00037679248,0.00051129615],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004923679,0.000085731575,0.003563665,0.00016309401,0.00004870878,0.00011223525,0.00016979063,0.23477276,0.19674052,0.0023524552,0.0012059778,0.56029266],"study_design_scores_gemma":[0.000020010559,0.00016047401,0.0104650445,0.000014070381,0.000018755203,0.00012769896,0.00005855311,0.9476569,0.037193965,0.0019652662,0.0022985998,0.000020641923],"about_ca_topic_score_codex":0.001968761,"about_ca_topic_score_gemma":0.0031977026,"teacher_disagreement_score":0.001968761,"about_ca_system_score_codex":0.00019666283,"about_ca_system_score_gemma":0.0004083856,"threshold_uncertainty_score":0.005215764},"labels":[],"label_agreement":null},{"id":"W4410452316","doi":"10.18280/rcma.350220","title":"Comparative Analysis of ANFIS-PSO and ANFIS-GA Predictions for MRR in AL-8112 Alloy Machining","year":2025,"lang":"fr","type":"article","venue":"Revue des composites et des matériaux avancés","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Adaptive neuro fuzzy inference system; Machining; Alloy; Materials science; Metallurgy; Computer science; Artificial intelligence; Fuzzy logic","score_opus":0.04124402796728582,"score_gpt":0.3291533586344967,"score_spread":0.28790933066721086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410452316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84053934,0.0013046608,0.14713496,0.000371815,0.00008818912,0.00009903443,0.00018856375,0.0010563139,0.009217069],"genre_scores_gemma":[0.9929033,0.00013407151,0.006066972,0.000019753536,0.000004700263,0.000022959912,0.0000790164,0.000012418932,0.00075664854],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997291,0.00007000577,0.000025300571,0.000050053586,0.000079530546,0.000046033925],"domain_scores_gemma":[0.9990891,0.00060285477,0.00007054814,0.000029764244,0.00018212842,0.00002569276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000976783,0.0007868407,0.0005075219,0.0005503582,0.00026100685,0.00053752377,0.00032371443,0.00064827316,0.0009161239],"category_scores_gemma":[0.0025024822,0.0001810452,0.00046711648,0.00021807899,0.0002125831,0.00029764642,0.00018673572,0.00044361915,0.00015198707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028038147,0.000106981905,0.0041920217,0.0001814292,0.00006959666,0.00014006492,0.00010587831,0.94161963,0.0045373226,0.00046291546,0.0006021541,0.047701564],"study_design_scores_gemma":[0.0000048216502,0.00008653536,0.002176799,0.000011629718,0.000014826256,0.000015864423,0.000028572225,0.99621564,0.0012112228,0.0000894119,0.0001388074,0.0000058570427],"about_ca_topic_score_codex":0.014436044,"about_ca_topic_score_gemma":0.008939927,"teacher_disagreement_score":0.014436044,"about_ca_system_score_codex":0.00037787884,"about_ca_system_score_gemma":0.00042299752,"threshold_uncertainty_score":0.028704047},"labels":[],"label_agreement":null},{"id":"W4410587905","doi":"10.3390/mi16060602","title":"Energy Harvesting Microelectromechanical System for Condition Monitoring Based on Piezoelectric Transducer Ring","year":2025,"lang":"en","type":"article","venue":"Micromachines","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"National Natural Science Foundation of China","keywords":"Energy harvesting; Microelectromechanical systems; Bearing (navigation); Transducer; Reliability (semiconductor); Piezoelectricity; Power (physics); Condition monitoring; Energy (signal processing); Vibration; Engineering; Electrical engineering; Automotive engineering; Electronic engineering; Acoustics; Computer science; Materials science; Optoelectronics","score_opus":0.0054131191926103965,"score_gpt":0.23389932240470288,"score_spread":0.22848620321209248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410587905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61400443,0.0043646023,0.36705363,0.00079960073,0.0006123973,0.00023543207,0.00045886586,0.0023054124,0.010165672],"genre_scores_gemma":[0.9338089,0.0006442807,0.06061882,0.00018639227,0.0000817342,0.00008146813,0.00008765163,0.000020478106,0.004470367],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983513,0.000016338457,0.00001033606,0.00005170875,0.000074331896,0.000012086465],"domain_scores_gemma":[0.99989474,0.000027045662,0.000027070615,0.000014651909,0.000030013116,0.000006409497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014970516,0.00020848296,0.0002512965,0.00017539183,0.00011359494,0.0001433368,0.0005115767,0.0002652561,0.0014193712],"category_scores_gemma":[0.00022276865,0.00010717875,0.00014258432,0.0001947628,0.00011941397,0.00041418461,0.00024088597,0.00016104257,0.00037107946],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006955381,0.00003116402,0.0006417792,0.000112159505,0.000012080601,0.00011836726,0.00004694345,0.00075373286,0.9573023,0.0006678806,0.000824172,0.039419964],"study_design_scores_gemma":[0.000059768812,0.0008051849,0.004723292,0.000025270087,0.00005271587,0.0008311332,0.000058179674,0.080270976,0.8998345,0.00055244996,0.01274027,0.00004642174],"about_ca_topic_score_codex":0.000117942596,"about_ca_topic_score_gemma":0.0002715546,"teacher_disagreement_score":0.0014193712,"about_ca_system_score_codex":0.00012597423,"about_ca_system_score_gemma":0.00010295152,"threshold_uncertainty_score":0.004748225},"labels":[],"label_agreement":null},{"id":"W4410640126","doi":"10.3390/app15115869","title":"Influence of Cutting Parameters and MQL on Surface Finish and Work Hardening of Inconel 617","year":2025,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inconel; Materials science; Metallurgy; Case hardening; Surface roughness; Work hardening; Hardening (computing); Composite material; Hardness; Microstructure; Alloy","score_opus":0.0072252658829080815,"score_gpt":0.2299398172815465,"score_spread":0.2227145513986384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410640126","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99864346,0.00055766286,0.00017891315,0.000011835484,0.000006021205,0.0000058610563,0.000044404424,0.000014164759,0.0005375783],"genre_scores_gemma":[0.99846065,0.00034736746,0.00057554035,0.000011796831,0.0000025893821,0.0000054284287,0.000055228586,0.000019276771,0.0005221256],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995956,0.000037760095,0.000036823945,0.00006622276,0.00018015294,0.000083430634],"domain_scores_gemma":[0.99937755,0.00023268862,0.00014197284,0.000035542394,0.0001728885,0.000039385242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028133715,0.00028634066,0.00035737958,0.00045281302,0.00019823674,0.00061693776,0.00027755607,0.00035679375,0.0011580361],"category_scores_gemma":[0.00090014987,0.00022141407,0.00025880837,0.00035441964,0.0002166151,0.0003237811,0.00023676344,0.00030313435,0.00026400114],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036766063,0.00006222764,0.0024815376,0.00021005796,0.000022346323,0.00019435264,0.00016396551,0.00086947455,0.98746526,0.000048995076,0.00008641158,0.008027774],"study_design_scores_gemma":[0.000011359496,0.0016707166,0.019728996,0.000022914666,0.000056800836,0.00013618953,0.0002849467,0.0017534392,0.9747185,0.000017822793,0.0015741909,0.000024103685],"about_ca_topic_score_codex":0.0018508715,"about_ca_topic_score_gemma":0.0031968958,"teacher_disagreement_score":0.0018508715,"about_ca_system_score_codex":0.0002257848,"about_ca_system_score_gemma":0.00018626945,"threshold_uncertainty_score":0.003874004},"labels":[],"label_agreement":null},{"id":"W4411008388","doi":"10.1016/j.cirp.2025.05.003","title":"Revisiting machinability assessment: Towards total machining performance","year":2025,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Machinability; Machining; Engineering; Manufacturing engineering; Metallurgy; Mechanical engineering; Engineering drawing; Computer science; Materials science","score_opus":0.013136334171153011,"score_gpt":0.304438512196996,"score_spread":0.291302178025843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411008388","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18388323,0.0019054643,0.75834894,0.0012337134,0.00034602638,0.00024052722,0.0006044438,0.0019213617,0.05151623],"genre_scores_gemma":[0.8080796,0.0008380513,0.17966872,0.00021458858,0.00011812558,0.00009475522,0.0006812266,0.00051131257,0.009793674],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9937109,0.001288816,0.000350689,0.00052234967,0.0039280625,0.00019916077],"domain_scores_gemma":[0.99152946,0.002153611,0.0006888776,0.0013037267,0.004196796,0.00012757315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053413073,0.0019130418,0.0011319951,0.0028319787,0.0007881499,0.0047336,0.0017812923,0.0012985837,0.004713937],"category_scores_gemma":[0.014809654,0.0005003244,0.0008676937,0.0015979444,0.0010645483,0.0036268493,0.0016431967,0.0013252749,0.0018627243],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003848269,0.00034460708,0.025047567,0.0012691866,0.00031462184,0.00020761765,0.00041612485,0.1756673,0.092961766,0.02171364,0.0058654593,0.6758073],"study_design_scores_gemma":[0.000025295449,0.0011086306,0.035001766,0.00047373257,0.0002745273,0.00034318137,0.0005162893,0.7910445,0.098028146,0.0488221,0.024177566,0.00018439996],"about_ca_topic_score_codex":0.0017121612,"about_ca_topic_score_gemma":0.0035860585,"teacher_disagreement_score":0.0053413073,"about_ca_system_score_codex":0.0008208053,"about_ca_system_score_gemma":0.0016422247,"threshold_uncertainty_score":0.028247893},"labels":[],"label_agreement":null},{"id":"W4411019938","doi":"10.1109/tmtt.2025.3571574","title":"A Novel Neuro-TF Modeling Technique Incorporating Parametric Sanathanan–Koerner Iteration of Continuous Pole/Residue Extraction","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Microwave Theory and Techniques","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Residue (chemistry); Parametric statistics; Extraction (chemistry); Control theory (sociology); Computer science; Biological system; Electronic engineering; Engineering; Mathematics; Chromatography; Chemistry; Artificial intelligence","score_opus":0.007775897885926136,"score_gpt":0.24685977789725486,"score_spread":0.23908388001132871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411019938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024367934,0.00004892174,0.9965475,0.000020920743,0.000006889179,0.000008339111,0.0000063977827,0.00009685534,0.00082737394],"genre_scores_gemma":[0.3552668,0.00028034285,0.6395464,0.00007820669,0.000028967459,0.00015631117,0.000095687705,0.00013064111,0.004416585],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997569,0.000053914315,0.00001689711,0.00005356458,0.00010042,0.00001822504],"domain_scores_gemma":[0.99973875,0.000098744975,0.000036870122,0.000032060456,0.00008436622,0.000009231546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056967925,0.00079132826,0.00052810926,0.00048196226,0.00038436992,0.00064165884,0.0009659193,0.0009187011,0.001509826],"category_scores_gemma":[0.0011828775,0.00035785092,0.00086829497,0.00038639075,0.00053053076,0.0010596546,0.0004928492,0.0008624849,0.0005782992],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007892752,0.000036794987,0.00063422014,0.00011860792,0.00005238997,0.000101288526,0.00017888147,0.78533053,0.019646345,0.021375678,0.0009309053,0.17151546],"study_design_scores_gemma":[0.0000014186388,0.0000120694285,0.00003977823,0.0000036267693,0.0000031207362,0.000021887867,0.0000035780613,0.9968997,0.0014520283,0.0009255868,0.0006327461,0.000004396669],"about_ca_topic_score_codex":0.003256109,"about_ca_topic_score_gemma":0.0031124167,"teacher_disagreement_score":0.003256109,"about_ca_system_score_codex":0.00049072545,"about_ca_system_score_gemma":0.00077065115,"threshold_uncertainty_score":0.006474316},"labels":[],"label_agreement":null},{"id":"W4411142852","doi":"10.1109/access.2025.3577667","title":"Optimizing Gammatone Cepstral Coefficients for Gear Fault Detection","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Fault detection and isolation; Mel-frequency cepstrum; Cepstrum; Fault (geology); Speech recognition; Feature extraction; Artificial intelligence","score_opus":0.013833755985118623,"score_gpt":0.2991075926448529,"score_spread":0.2852738366597343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411142852","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16172864,0.0015768239,0.83184963,0.0002947773,0.00010785802,0.00007042996,0.00024019364,0.0015505722,0.0025810841],"genre_scores_gemma":[0.80337554,0.00049622817,0.19369751,0.00010346382,0.00003408785,0.00007522409,0.0006545866,0.00015138161,0.0014119458],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997192,0.000052139334,0.00001843334,0.00006533435,0.00009571754,0.00004918291],"domain_scores_gemma":[0.99936,0.0003553037,0.00005973167,0.00003680867,0.00016823469,0.000020016209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007807014,0.0012488116,0.0007054983,0.0011129428,0.0002262147,0.00069961115,0.0004932264,0.0008859412,0.0008583913],"category_scores_gemma":[0.0036646156,0.00033576105,0.00044941265,0.000684099,0.00028582488,0.0006915264,0.00032352007,0.00077440514,0.0004994979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018812862,0.00009969477,0.0017068221,0.00010826121,0.000056147182,0.00011568656,0.00004875403,0.71392304,0.020892685,0.0011430618,0.0026026461,0.259115],"study_design_scores_gemma":[0.0000066094676,0.000021529204,0.00046051512,0.0000051383113,0.000011011048,0.000017592467,0.000011793453,0.9960038,0.0028324972,0.00028675754,0.00033744998,0.0000052964965],"about_ca_topic_score_codex":0.008638757,"about_ca_topic_score_gemma":0.007851182,"teacher_disagreement_score":0.008638757,"about_ca_system_score_codex":0.00050356926,"about_ca_system_score_gemma":0.0009892309,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4411231661","doi":"10.1016/j.cirpj.2025.05.015","title":"Optimization of clamping conditions in thin-walled part machining to minimize forced vibrations, Part I: Model for the single tool –workpiece contact location","year":2025,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Pratt and Whitney Canada","keywords":"Clamping; Machining; Vibration; Mechanical engineering; Materials science; Engineering; Structural engineering; Acoustics; Physics","score_opus":0.011936692872436231,"score_gpt":0.25279654366496424,"score_spread":0.240859850792528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411231661","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21326475,0.00050301,0.77371615,0.000122508,0.000028229395,0.00012490936,0.00011380646,0.00024027479,0.011886397],"genre_scores_gemma":[0.9551919,0.000250079,0.04092423,0.0000193078,0.000006263795,0.00012688639,0.0000535723,0.000041061678,0.003386707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991596,0.000017485043,0.0000030843985,0.000016871165,0.000031882726,0.0000147409955],"domain_scores_gemma":[0.9998264,0.00009734218,0.000033936234,0.000010480621,0.000024003699,0.000007864984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026441223,0.00047666623,0.0005761165,0.00031067684,0.00027286573,0.00064520666,0.00063975976,0.0010809031,0.0015784453],"category_scores_gemma":[0.00068933296,0.00039576474,0.0004877555,0.00023676615,0.00047766988,0.00037950772,0.00029191756,0.00039976396,0.00021734789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000098006585,0.00000858781,0.00010622928,0.000021069865,0.000002742343,0.000026057316,0.000013775942,0.99542063,0.002259294,0.0004732483,0.00003967174,0.0016188386],"study_design_scores_gemma":[0.0000029968794,0.000012886217,0.00008335586,0.0000023149676,0.0000020315879,0.000005171264,0.0000040735645,0.9992569,0.00041687983,0.00012511037,0.000086601845,0.0000016261586],"about_ca_topic_score_codex":0.005321617,"about_ca_topic_score_gemma":0.003943584,"teacher_disagreement_score":0.005321617,"about_ca_system_score_codex":0.00042863563,"about_ca_system_score_gemma":0.0007205338,"threshold_uncertainty_score":0.010581315},"labels":[],"label_agreement":null},{"id":"W4411260469","doi":"10.1016/j.cirpj.2025.05.014","title":"Optimization of clamping conditions in thin-walled part machining to minimize forced vibrations, part II: Dynamic updating of clamping force and location with position dependent dynamics","year":2025,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Pratt and Whitney Canada","keywords":"Clamping; Vibration; Position (finance); Machining; Dynamics (music); Control theory (sociology); Structural engineering; Engineering; Mechanical engineering; Physics; Computer science; Acoustics","score_opus":0.0033715408831827775,"score_gpt":0.228295383247534,"score_spread":0.22492384236435123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411260469","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33894816,0.00042177536,0.65610534,0.0001119108,0.00005980324,0.00006552873,0.000038316583,0.00018012711,0.004069008],"genre_scores_gemma":[0.96723735,0.00008228799,0.03196468,0.000012601377,0.000007439692,0.000039607567,0.000020243093,0.000028462142,0.0006072558],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998951,0.00002550976,0.0000068549384,0.000024966854,0.000032786334,0.000014745862],"domain_scores_gemma":[0.99964297,0.0002017359,0.00006427913,0.000022927386,0.000053748725,0.000014380578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034939463,0.0004930781,0.0005159604,0.000278602,0.00021389693,0.00060407055,0.0006032239,0.00062094524,0.0013310582],"category_scores_gemma":[0.0015394923,0.00036933954,0.00022919726,0.00020467292,0.00030510855,0.0005240933,0.00042216489,0.00032997274,0.00011051839],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011215153,0.00006316861,0.00058548787,0.0001141064,0.000021734431,0.00005880516,0.00007992606,0.9312989,0.035176516,0.0012684754,0.00025730662,0.03096343],"study_design_scores_gemma":[0.000011259629,0.000047129746,0.0003436945,0.0000055372725,0.0000060104003,0.000008406694,0.0000111288855,0.9959468,0.0033685486,0.00013181333,0.00011511061,0.0000045203215],"about_ca_topic_score_codex":0.002056336,"about_ca_topic_score_gemma":0.002318972,"teacher_disagreement_score":0.002056336,"about_ca_system_score_codex":0.00026030256,"about_ca_system_score_gemma":0.0004922781,"threshold_uncertainty_score":0.0044528246},"labels":[],"label_agreement":null},{"id":"W4411336587","doi":"10.1007/s40436-025-00564-x","title":"Survey on machine learning applied to CNC milling processes","year":2025,"lang":"en","type":"article","venue":"Advances in Manufacturing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Universidade do Porto","keywords":"Manufacturing engineering; Cnc milling; Engineering; Engineering drawing; Computer science; Mechanical engineering; Numerical control; Machining","score_opus":0.006882864303305701,"score_gpt":0.24824039267604875,"score_spread":0.24135752837274305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411336587","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015275263,0.8591059,0.09499015,0.0016419839,0.0011364918,0.000116591254,0.0006442427,0.00044830772,0.026641205],"genre_scores_gemma":[0.13957955,0.79758817,0.049801297,0.00079273316,0.0019267515,0.00015096854,0.0018969676,0.0001254642,0.0081380755],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986687,0.00026572277,0.00017074005,0.00031058877,0.0005286605,0.00005561078],"domain_scores_gemma":[0.9969445,0.0017975572,0.00015515844,0.0001494286,0.0009046175,0.00004861295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015588535,0.0009117376,0.0010917895,0.0040758396,0.00035682568,0.0015660572,0.001463133,0.0009888224,0.0025300125],"category_scores_gemma":[0.0047406126,0.0005029131,0.0009836785,0.0065756994,0.00037141962,0.0018867248,0.0006697171,0.0009798425,0.0014864377],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060766488,0.00008973907,0.0028544988,0.005204126,0.00011562971,0.00010468982,0.00008555534,0.012245937,0.0009356021,0.007019904,0.01211053,0.9591729],"study_design_scores_gemma":[0.000027665395,0.00052588916,0.020049376,0.008556273,0.00033116498,0.001423899,0.00042317802,0.13555525,0.01375717,0.027390037,0.7917684,0.0001916632],"about_ca_topic_score_codex":0.002279467,"about_ca_topic_score_gemma":0.0011600422,"teacher_disagreement_score":0.0040758396,"about_ca_system_score_codex":0.0006688764,"about_ca_system_score_gemma":0.0008666649,"threshold_uncertainty_score":0.00846374},"labels":[],"label_agreement":null},{"id":"W4411660742","doi":"10.1177/00219983251341623","title":"Effects of wax and graphene concentrations on cutting force in drilling GFRP composites: A comprehensive study using a full factorial design of experiments","year":2025,"lang":"en","type":"article","venue":"Journal of Composite Materials","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Composite material; Factorial experiment; Fibre-reinforced plastic; Wax; Drilling; Graphene; Epoxy; Computer science","score_opus":0.016119020402005253,"score_gpt":0.2861269940742564,"score_spread":0.27000797367225116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411660742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915376,0.0008436117,0.0067889136,0.000018698856,0.000023832006,0.0002200533,0.00017924243,0.000037814687,0.00035017138],"genre_scores_gemma":[0.96734357,0.0015262115,0.029286772,0.000046278303,0.0000112654425,0.0005225809,0.00016076305,0.000033274955,0.0010691867],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988348,0.00020367559,0.00015219692,0.00023709575,0.000428948,0.0001433321],"domain_scores_gemma":[0.99873394,0.0005119647,0.0003531043,0.00011152523,0.00021336392,0.00007612515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015301701,0.001068856,0.001176548,0.00050759426,0.00034998538,0.000574557,0.00043699145,0.0006715821,0.000784915],"category_scores_gemma":[0.0013053915,0.00042779208,0.0008517372,0.000459404,0.00039697537,0.0005453723,0.00042922053,0.0008044423,0.00013178914],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010868377,0.0005931978,0.00060156954,0.00033474978,0.00005231401,0.000032748107,0.00007241316,0.0018866437,0.98814666,0.00006473208,0.000020048035,0.007108205],"study_design_scores_gemma":[0.00006815309,0.014185669,0.0054927464,0.00002422359,0.00022023177,0.000048724516,0.00008092592,0.0037989365,0.9748266,0.00007193755,0.0011351458,0.00004677848],"about_ca_topic_score_codex":0.00080698746,"about_ca_topic_score_gemma":0.0014836327,"teacher_disagreement_score":0.0015301701,"about_ca_system_score_codex":0.0004142626,"about_ca_system_score_gemma":0.00059145887,"threshold_uncertainty_score":0.008092403},"labels":[],"label_agreement":null},{"id":"W4411678602","doi":"10.1016/j.ymssp.2025.113040","title":"A new data processing and synchronization method for measuring in-process machine tool spindle vibrations using non-contact sensors","year":2025,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Polytechnique Montréal","keywords":"Synchronization (alternating current); Vibration; Process (computing); Computer science; Machine tool; Engineering; Control engineering; Acoustics; Mechanical engineering; Physics; Electrical engineering; Topology (electrical circuits)","score_opus":0.028834496095625897,"score_gpt":0.3052311272206588,"score_spread":0.27639663112503293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411678602","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018915612,0.00033696825,0.9769588,0.00009579912,0.00025446256,0.00015583105,0.00014541628,0.0017881631,0.0013488355],"genre_scores_gemma":[0.24258626,0.00031084515,0.7489877,0.00026402026,0.00025098672,0.00043503768,0.00052504474,0.00020498931,0.006435142],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983045,0.00016673865,0.00009513357,0.00035666538,0.0010163436,0.000060673916],"domain_scores_gemma":[0.9988355,0.0002789804,0.00013194965,0.00018981734,0.0005128782,0.000050967952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006576897,0.0007841827,0.00087171525,0.0014144179,0.0005613701,0.000741942,0.0014734505,0.00092388503,0.0029910097],"category_scores_gemma":[0.0012226775,0.00053022214,0.00038124647,0.0011996558,0.00038170122,0.00128026,0.00070888834,0.0008156244,0.0012111259],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046232084,0.00020655376,0.00174737,0.00031846928,0.00008859771,0.00016410551,0.00017411794,0.0019187884,0.61958754,0.002200777,0.0028256606,0.37030572],"study_design_scores_gemma":[0.0002302256,0.0011216111,0.010424121,0.00004864962,0.0002026942,0.0014750474,0.00010282215,0.2882052,0.662596,0.0014594386,0.03391503,0.00021919479],"about_ca_topic_score_codex":0.0008214348,"about_ca_topic_score_gemma":0.0016748114,"teacher_disagreement_score":0.0029910097,"about_ca_system_score_codex":0.00041301185,"about_ca_system_score_gemma":0.0006446922,"threshold_uncertainty_score":0.010005951},"labels":[],"label_agreement":null},{"id":"W4411919012","doi":"10.1016/j.wear.2025.206222","title":"Initial wear of cutting coated tools while machining TiMMC","year":2025,"lang":"en","type":"article","venue":"Wear","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Machining; Metallurgy; Tool wear; Mechanical engineering; Manufacturing engineering; Engineering drawing; Engineering","score_opus":0.012475548131019556,"score_gpt":0.2596695065071408,"score_spread":0.24719395837612126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411919012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99767846,0.0002550551,0.0016823598,0.000005293091,0.0000049753016,0.000009277624,0.00006283738,0.000032895354,0.0002688224],"genre_scores_gemma":[0.9983058,0.000056281435,0.0012456046,0.0000047191147,0.0000025270153,0.0000050029794,0.000068296504,0.0000073525225,0.00030447546],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997279,0.000019367191,0.00001044943,0.000047554156,0.00015424263,0.000040439325],"domain_scores_gemma":[0.9993924,0.00019845626,0.00012907207,0.00006483699,0.00017370998,0.000041624964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020858775,0.00019800683,0.00026782654,0.0006499336,0.00020928799,0.0002976964,0.0002609628,0.00029137422,0.000651038],"category_scores_gemma":[0.0008878891,0.00014355729,0.00020111688,0.00025838873,0.00029250508,0.00025704884,0.0001764984,0.00026483004,0.0001141706],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047117888,0.00003140671,0.012850314,0.00012527117,0.000013460471,0.00026335169,0.00057693274,0.0005011757,0.9670058,0.000051702456,0.00006999546,0.018039491],"study_design_scores_gemma":[0.000010339782,0.0016081842,0.26137277,0.000035506433,0.0000379129,0.0007626107,0.00079477415,0.009784667,0.7240123,0.000102301885,0.0014278771,0.0000506851],"about_ca_topic_score_codex":0.001050568,"about_ca_topic_score_gemma":0.0019228817,"teacher_disagreement_score":0.001050568,"about_ca_system_score_codex":0.0001869971,"about_ca_system_score_gemma":0.00010907088,"threshold_uncertainty_score":0.002177894},"labels":[],"label_agreement":null},{"id":"W4412021586","doi":"10.1109/icphm65385.2025.11062053","title":"Friction Modeling and Monitoring for Machine Tool Health Management","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Health management system; Machine tool; Engineering; Mechanical engineering; Medicine","score_opus":0.00924304233578052,"score_gpt":0.2679301017145154,"score_spread":0.25868705937873493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412021586","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012307091,0.00081772223,0.980411,0.00017203037,0.00008148777,0.00007721193,0.00022791255,0.0017006199,0.0042049265],"genre_scores_gemma":[0.7714284,0.0016063823,0.2156488,0.00011769216,0.00009390775,0.00019734779,0.00066775276,0.00035968097,0.009880074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966633,0.000045911132,0.000024243469,0.000069264664,0.00016148425,0.000032831897],"domain_scores_gemma":[0.9996201,0.00011559986,0.00006535953,0.000070634516,0.00011340688,0.000014959127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048180282,0.0008572858,0.0008394559,0.0007861823,0.00039167865,0.0011185458,0.0009160143,0.0010689201,0.00348259],"category_scores_gemma":[0.0018982675,0.0004126329,0.00083874346,0.0006902122,0.0002555828,0.0011536557,0.0006579032,0.00071127946,0.0011748099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018072022,0.00014581408,0.004003323,0.00037499313,0.000063521824,0.00017461,0.00015464955,0.77077824,0.030337838,0.011090026,0.0041824714,0.17851388],"study_design_scores_gemma":[0.000004525809,0.000029835806,0.00057476765,0.000016183065,0.000009135056,0.00003525169,0.000016973523,0.9906923,0.0028266462,0.0015024851,0.004280974,0.000011006818],"about_ca_topic_score_codex":0.0067925947,"about_ca_topic_score_gemma":0.0056930687,"teacher_disagreement_score":0.0067925947,"about_ca_system_score_codex":0.00062843086,"about_ca_system_score_gemma":0.0007611891,"threshold_uncertainty_score":0.0135061145},"labels":[],"label_agreement":null},{"id":"W4412573802","doi":"10.1007/s40808-025-02546-1","title":"Accurate torque prediction in drilling operations: an enhanced EP lubricity evaluation methodology","year":2025,"lang":"en","type":"article","venue":"Modeling Earth Systems and Environment","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Lubricity; Torque; Drilling; Petroleum engineering; Marine engineering; Computer science; Environmental science; Engineering; Geology; Mechanical engineering; Physics","score_opus":0.0476052527838217,"score_gpt":0.28903212453283905,"score_spread":0.24142687174901734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412573802","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035340592,0.00009233931,0.962447,0.000031049072,0.000020551757,0.000026835187,0.000041626776,0.00026823225,0.0017318352],"genre_scores_gemma":[0.838095,0.00011764648,0.15975215,0.000026773787,0.00002540581,0.00004846091,0.00010455565,0.00007304515,0.0017569183],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999724,0.000054293112,0.000021672358,0.000039006343,0.00013149081,0.000029614694],"domain_scores_gemma":[0.99949527,0.00014309215,0.000058366673,0.000054335072,0.00023041008,0.000018420249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005240214,0.0004897331,0.0005089772,0.0005353196,0.0002264184,0.0006257053,0.0009556691,0.00050789403,0.001331592],"category_scores_gemma":[0.0017038268,0.00024849933,0.0003399338,0.00042270587,0.00023632342,0.0008992798,0.00069308444,0.0005336018,0.00029088045],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009301637,0.00008624016,0.0019456735,0.00009192245,0.000022521066,0.00008391646,0.000038628692,0.8424949,0.011226602,0.003938267,0.0004379835,0.13954028],"study_design_scores_gemma":[0.0000017820197,0.000016001206,0.00013113288,0.0000019677698,0.000002150822,0.000005483315,0.000002368417,0.9981871,0.0012791398,0.00024437875,0.00012665623,0.0000018452146],"about_ca_topic_score_codex":0.0042803762,"about_ca_topic_score_gemma":0.0033546935,"teacher_disagreement_score":0.0042803762,"about_ca_system_score_codex":0.00025219275,"about_ca_system_score_gemma":0.0007406958,"threshold_uncertainty_score":0.008510947},"labels":[],"label_agreement":null},{"id":"W4412602566","doi":"10.3390/lubricants13080322","title":"Progress on Sustainable Cryogenic Machining of Hard-to-Cut Material and Greener Processing Techniques: A Combined Machinability and Sustainability Perspective","year":2025,"lang":"en","type":"article","venue":"Lubricants","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Machinability; Sustainability; Machining; Perspective (graphical); Materials processing; Manufacturing engineering; Materials science; Process engineering; Mechanical engineering; Engineering; Nanotechnology; Computer science","score_opus":0.004200996991258882,"score_gpt":0.2591799174977892,"score_spread":0.2549789205065303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412602566","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24108568,0.6128875,0.09801792,0.0049309256,0.0003840884,0.00007328715,0.00015073255,0.00018162075,0.04228821],"genre_scores_gemma":[0.55065733,0.35922694,0.079938725,0.0006446538,0.0005370578,0.0000614881,0.00030531312,0.00011566551,0.008512892],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995609,0.00007537989,0.00001643125,0.00007389843,0.00022283771,0.000050510553],"domain_scores_gemma":[0.99956864,0.00010963673,0.000097841854,0.00004189949,0.00015212875,0.000029773873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013746087,0.00047949166,0.00040740086,0.00090620905,0.00026354266,0.0010588933,0.0005271442,0.00061779656,0.0019621984],"category_scores_gemma":[0.00039901127,0.0001763694,0.00036673358,0.0007444233,0.00072523166,0.0016389429,0.0005278335,0.00065383984,0.00036752754],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017921497,0.00033946065,0.0032953657,0.005129219,0.00010413959,0.00029173458,0.00048595754,0.009509838,0.4107835,0.07598262,0.003551507,0.4903474],"study_design_scores_gemma":[0.000035994653,0.0020981824,0.014424569,0.001227534,0.00017271377,0.0016305612,0.0010395898,0.020074425,0.455589,0.030164579,0.47344327,0.00009953238],"about_ca_topic_score_codex":0.00050444267,"about_ca_topic_score_gemma":0.00087745703,"teacher_disagreement_score":0.0019621984,"about_ca_system_score_codex":0.00063198386,"about_ca_system_score_gemma":0.0008303544,"threshold_uncertainty_score":0.0072696805},"labels":[],"label_agreement":null},{"id":"W4412662137","doi":"10.52783/tangence.3","title":"Optimization of Heat Transfer in Mechanical Systems Using AI in Neural Networks","year":2025,"lang":"en","type":"article","venue":"Tangence","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Heat transfer; Computer science; Artificial intelligence; Physics; Thermodynamics","score_opus":0.010020468490202845,"score_gpt":0.25042363033601517,"score_spread":0.2404031618458123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412662137","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013035311,0.0013856703,0.9775129,0.00042928808,0.000087188135,0.000047149308,0.00003879214,0.0003053424,0.007158343],"genre_scores_gemma":[0.7802255,0.0025854055,0.20663096,0.00023875943,0.00021674228,0.00043504345,0.0001246201,0.00015389394,0.009389055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997042,0.00009891742,0.000016467178,0.00006121334,0.00009274133,0.000026458212],"domain_scores_gemma":[0.9993524,0.000496179,0.000047830832,0.000028402006,0.000062167215,0.0000130732915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006693339,0.0009306206,0.0008219218,0.0004445045,0.00047660744,0.001162267,0.00078496884,0.0012420695,0.0016059238],"category_scores_gemma":[0.0018684461,0.0005513823,0.00065897434,0.0006791581,0.0010451692,0.0010400084,0.000859348,0.0014525115,0.00030502595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000081840735,0.000007830314,0.00007649409,0.000040539904,0.000011674935,0.000010612686,0.000012285634,0.98663133,0.0005729725,0.0037402718,0.000120527366,0.008767207],"study_design_scores_gemma":[0.0000012510724,0.000004375467,0.000017221444,0.0000027517674,0.0000013724443,0.0000018219217,0.0000015498649,0.9981949,0.00014672609,0.0014243393,0.00020255405,0.0000012339418],"about_ca_topic_score_codex":0.0051556495,"about_ca_topic_score_gemma":0.005583072,"teacher_disagreement_score":0.0051556495,"about_ca_system_score_codex":0.0010292615,"about_ca_system_score_gemma":0.000793919,"threshold_uncertainty_score":0.010251284},"labels":[],"label_agreement":null},{"id":"W4412820101","doi":"10.1007/s00170-025-16195-2","title":"Modal identification of machine tool spindle units by output only operational modal analysis","year":2025,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; FedDev Ontario","keywords":"Modal; Modal analysis; Modal testing; Identification (biology); Operational Modal Analysis; Machine tool; Engineering; Modal analysis using FEM; Vibration; Computer science; Mechanical engineering; Structural engineering; Acoustics; Finite element method; Materials science; Physics","score_opus":0.0042893186857518185,"score_gpt":0.2385438178370889,"score_spread":0.23425449915133706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412820101","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42030573,0.00017907731,0.577578,0.000029108072,0.000020032929,0.00006573226,0.00010885812,0.00041325466,0.001300242],"genre_scores_gemma":[0.9507154,0.000055707886,0.048685323,0.0000062764975,0.000006071792,0.000035398676,0.00008363932,0.000020112433,0.00039205377],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997608,0.000033118857,0.00001277467,0.000042732794,0.00013484848,0.00001582708],"domain_scores_gemma":[0.9995266,0.00020516403,0.00009049978,0.000043825275,0.000120537734,0.000013278037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003088011,0.0003201725,0.00022427454,0.0005466281,0.00012334176,0.00022414715,0.0002737441,0.00019857519,0.00070487265],"category_scores_gemma":[0.00085089356,0.000115720766,0.0001722983,0.00027090602,0.0002452993,0.00039345218,0.00027381122,0.00020821081,0.000135137],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041030897,0.000105164385,0.010170845,0.0002898226,0.000028054894,0.00011279457,0.0002721318,0.0227689,0.6904471,0.00089755334,0.00035954505,0.2741377],"study_design_scores_gemma":[0.000043127096,0.00072225503,0.070604324,0.000045784556,0.000034770383,0.00044355963,0.0002643851,0.6582473,0.26489195,0.0013148494,0.0033205198,0.00006723998],"about_ca_topic_score_codex":0.00045111042,"about_ca_topic_score_gemma":0.000770313,"teacher_disagreement_score":0.00070487265,"about_ca_system_score_codex":0.00011419935,"about_ca_system_score_gemma":0.00013172835,"threshold_uncertainty_score":0.002358079},"labels":[],"label_agreement":null},{"id":"W4412890149","doi":"10.1016/j.ymssp.2025.113154","title":"Online tool condition monitoring based on optimized multi-sensor acoustic features for robotic abrasive belt grinding","year":2025,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Abrasive; Grinding; Acoustic sensor; Acoustic emission; Acoustics; Materials science; Robot; Mechanical engineering; Automotive engineering; Computer science; Engineering; Artificial intelligence; Composite material; Physics","score_opus":0.0169681136076726,"score_gpt":0.28587859013220596,"score_spread":0.26891047652453337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412890149","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41894022,0.0006630197,0.57458246,0.00009742446,0.000115861905,0.000106127874,0.00022330806,0.0020260725,0.0032455144],"genre_scores_gemma":[0.9500573,0.00007702644,0.04889144,0.00002721705,0.000016504244,0.00003316767,0.00006386227,0.000036338068,0.00079714],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995927,0.00003668024,0.000014531971,0.00010307379,0.00022693726,0.000026131045],"domain_scores_gemma":[0.9995788,0.000121764715,0.00011581721,0.00004292661,0.000121887286,0.000018870503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002523835,0.00062648964,0.00058873557,0.00051933754,0.00015471631,0.00041157118,0.0006895846,0.00040446853,0.0012074208],"category_scores_gemma":[0.00058546016,0.0002883952,0.00018720726,0.000368528,0.0001743193,0.00070385874,0.00038884324,0.0002815996,0.00035080293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072253577,0.00023224723,0.0043703453,0.00024432116,0.0000367315,0.000091198235,0.0000850327,0.01445222,0.7170614,0.0002660311,0.00083676446,0.2616011],"study_design_scores_gemma":[0.000085042586,0.0008872557,0.038221546,0.000021865997,0.00008673039,0.0003180709,0.000082011546,0.67082864,0.28629538,0.0007355026,0.0023541942,0.00008381255],"about_ca_topic_score_codex":0.00045794257,"about_ca_topic_score_gemma":0.0017366963,"teacher_disagreement_score":0.0012074208,"about_ca_system_score_codex":0.00019975998,"about_ca_system_score_gemma":0.00021865737,"threshold_uncertainty_score":0.0040391684},"labels":[],"label_agreement":null},{"id":"W4412909551","doi":"10.1007/s00170-025-16149-8","title":"Neural network-based modeling of CNC machines trajectory generation","year":2025,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Sandvik Coromant; Pratt and Whitney Canada","keywords":"Trajectory; Artificial neural network; Control engineering; Computer science; Engineering; Artificial intelligence; Industrial engineering; Manufacturing engineering; Physics","score_opus":0.008538062116429252,"score_gpt":0.244217603624701,"score_spread":0.23567954150827175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412909551","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15993005,0.0010094861,0.8077219,0.0006610486,0.0002353748,0.00011049854,0.00059038785,0.0008050275,0.02893621],"genre_scores_gemma":[0.9818843,0.00021353239,0.011029402,0.00003553484,0.000022018176,0.00006670195,0.000157961,0.00003842536,0.0065520527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985266,0.000031173182,0.000007387155,0.00003984036,0.000045150984,0.000023782799],"domain_scores_gemma":[0.9996766,0.00014263767,0.00004176087,0.0000156511,0.00010485504,0.000018599903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003585111,0.0004920813,0.00060887105,0.00046222095,0.00054939825,0.0008558497,0.0009786624,0.0012426404,0.0027879302],"category_scores_gemma":[0.001042385,0.00045235615,0.0003878551,0.0006597548,0.0004599197,0.00070959603,0.00038307844,0.00081874226,0.00044908913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006492984,0.000003628055,0.000074350944,0.0000040173118,0.0000022748652,0.000006540029,0.0000025206098,0.9980714,0.00011962767,0.00032686535,0.000051413503,0.0013308752],"study_design_scores_gemma":[3.4341676e-7,9.4354766e-7,0.000024031331,4.0728037e-7,3.5900845e-7,6.3062413e-7,2.7994957e-7,0.9998553,0.00002884893,0.00006561895,0.000022658516,5.003885e-7],"about_ca_topic_score_codex":0.050905548,"about_ca_topic_score_gemma":0.02817381,"teacher_disagreement_score":0.050905548,"about_ca_system_score_codex":0.0013740584,"about_ca_system_score_gemma":0.0012639818,"threshold_uncertainty_score":0.10121852},"labels":[],"label_agreement":null},{"id":"W4413110131","doi":"10.1115/msec2024-125456","title":"A General Analytical Approach to Predict Machining Process Damping","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Machining; Vibration; Mechanical engineering; Enhanced Data Rates for GSM Evolution; Discretization; Stability (learning theory); Face (sociological concept); Finite element method; Reduction (mathematics); Structural engineering; Computer science; Materials science; Engineering; Acoustics; Geometry; Mathematics; Mathematical analysis; Physics; Artificial intelligence","score_opus":0.012494033179430106,"score_gpt":0.2713467753317823,"score_spread":0.2588527421523522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413110131","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018983478,0.0002973755,0.9749746,0.000084913976,0.000038519578,0.00006699642,0.00007168519,0.0003486425,0.005133858],"genre_scores_gemma":[0.8705667,0.000999312,0.116867125,0.00007750907,0.00007627342,0.0002980599,0.00015608376,0.00015229153,0.01080653],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997398,0.000045831952,0.000011497426,0.000053364718,0.00012455352,0.000025032206],"domain_scores_gemma":[0.9997924,0.000071174785,0.000026331081,0.000024497922,0.00007884426,0.000006657267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036796718,0.0008944708,0.0004880269,0.00080926844,0.00032775142,0.0006082458,0.00125001,0.0013247366,0.0018098698],"category_scores_gemma":[0.001047655,0.00050788873,0.0009992593,0.0004909077,0.00044729284,0.0006293278,0.00048482043,0.00071477145,0.0006821193],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010015962,0.000027492186,0.000354706,0.000054240827,0.000013898932,0.000087055596,0.000048472823,0.9728478,0.007183735,0.0043083215,0.0002610337,0.01480317],"study_design_scores_gemma":[9.000144e-7,0.0000048766788,0.000045210145,0.0000023735754,0.0000015770548,0.0000066602984,0.0000024311726,0.99902165,0.00027549113,0.00036303408,0.0002741738,0.0000016898366],"about_ca_topic_score_codex":0.0046900287,"about_ca_topic_score_gemma":0.0025899876,"teacher_disagreement_score":0.0046900287,"about_ca_system_score_codex":0.00065689476,"about_ca_system_score_gemma":0.0006254635,"threshold_uncertainty_score":0.009325445},"labels":[],"label_agreement":null},{"id":"W4413110162","doi":"10.1115/msec2024-124638","title":"Operational Modal Analysis for Chatter Prediction in Milling","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Machining; Vibration; Modal analysis; Modal; Discretization; Process (computing); Computer science; Representation (politics); Machine tool; Work (physics); Stability (learning theory); Control theory (sociology); Mechanical engineering; Engineering; Control engineering; Mathematics; Acoustics; Artificial intelligence; Mathematical analysis; Machine learning; Materials science; Physics","score_opus":0.008496806697335596,"score_gpt":0.23833412138254512,"score_spread":0.22983731468520952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413110162","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05325454,0.00007062232,0.94540447,0.000028122498,0.000011320603,0.00003148279,0.000030737367,0.00029813094,0.00087048643],"genre_scores_gemma":[0.94927293,0.00005964153,0.05009212,0.000011803907,0.000007479565,0.00005351706,0.000035004883,0.000026276219,0.0004413032],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997286,0.000078764984,0.000015221745,0.00003519284,0.00012345846,0.000018692486],"domain_scores_gemma":[0.99867415,0.00089421537,0.00013682812,0.000079358855,0.00018721102,0.00002829495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006615417,0.0004531898,0.00032899113,0.0006896174,0.00021632385,0.000375763,0.00041985358,0.00031410088,0.001198541],"category_scores_gemma":[0.0023857336,0.00017461857,0.0002995532,0.00023380165,0.00048509246,0.0003731021,0.00047459477,0.0006051415,0.00011958056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001930928,0.00010619714,0.0035274345,0.00020801832,0.000045292112,0.00008487729,0.00029061313,0.8404285,0.052362673,0.013572993,0.00038528873,0.088795125],"study_design_scores_gemma":[6.499814e-7,0.000006794336,0.00013178196,0.0000017649296,8.38617e-7,0.00000234469,0.0000037140207,0.9988111,0.0006601145,0.00034063446,0.00003848549,0.000001736525],"about_ca_topic_score_codex":0.0024816191,"about_ca_topic_score_gemma":0.001884259,"teacher_disagreement_score":0.0024816191,"about_ca_system_score_codex":0.00033837967,"about_ca_system_score_gemma":0.00031646676,"threshold_uncertainty_score":0.0049343705},"labels":[],"label_agreement":null},{"id":"W4413381966","doi":"10.1007/s00170-025-16337-6","title":"Multi-class anomaly classification for three axis CNC milling machines","year":2025,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Class (philosophy); Anomaly (physics); Cnc milling; Numerical control; Engineering drawing; Engineering; Computer science; Manufacturing engineering; Mechanical engineering; Artificial intelligence; Machining; Physics","score_opus":0.01231540191528056,"score_gpt":0.2727024017217304,"score_spread":0.2603869998064498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413381966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5903745,0.000541222,0.40456447,0.00029569617,0.00026507062,0.000052071147,0.00031615762,0.0016567593,0.0019340572],"genre_scores_gemma":[0.96617484,0.000072825605,0.0321521,0.000021414548,0.00003542277,0.000016466429,0.0003024029,0.00003986246,0.0011847323],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991648,0.000083377025,0.00005361456,0.00018365886,0.00036880866,0.00014581496],"domain_scores_gemma":[0.9986016,0.00042131048,0.00016282898,0.00015936072,0.00058055995,0.000074250325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009609886,0.0005026181,0.00066589395,0.0013788209,0.00055036764,0.0007408935,0.00088255253,0.0009979379,0.00078875996],"category_scores_gemma":[0.0015111177,0.00018220444,0.00053583825,0.0008723476,0.00036112586,0.0006802188,0.00060398877,0.00074796024,0.0002437917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017541731,0.0004608108,0.031825945,0.00013857469,0.00012862813,0.0004395148,0.0001974791,0.104411855,0.06941672,0.0020252718,0.0053551984,0.7838459],"study_design_scores_gemma":[0.0000061780897,0.000050013736,0.011597283,0.0000042509646,0.000014938685,0.00011538268,0.00003935662,0.9790694,0.007724134,0.0007271815,0.0006391729,0.000012648131],"about_ca_topic_score_codex":0.0039883875,"about_ca_topic_score_gemma":0.004699407,"teacher_disagreement_score":0.0039883875,"about_ca_system_score_codex":0.0005485101,"about_ca_system_score_gemma":0.0006521145,"threshold_uncertainty_score":0.007930338},"labels":[],"label_agreement":null},{"id":"W4413391455","doi":"10.1115/omae2025-157480","title":"Investigation of PDC Drill Bit Wear and its Effect on Drilling Performance","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Drilling; Drill bit; Drill; Bit (key); Computer science; Engineering; Mechanical engineering; Computer security","score_opus":0.005438161871973527,"score_gpt":0.20785568909771104,"score_spread":0.20241752722573753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413391455","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981463,0.00033469484,0.0007856742,0.000016383134,0.000010070376,0.000016792743,0.00020077736,0.000025394254,0.00046392478],"genre_scores_gemma":[0.9983713,0.00013745879,0.00073694607,0.000006470089,0.0000023915052,0.00000843651,0.00012206311,0.0000058098867,0.00060914917],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99929476,0.00007457609,0.000073855575,0.00008342652,0.00042082585,0.000052482446],"domain_scores_gemma":[0.99728,0.0009504224,0.0005137472,0.00015151751,0.0010140319,0.00009026649],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049264514,0.00027527858,0.00034691772,0.0005861804,0.0001851998,0.0003561842,0.00027774615,0.00031174466,0.0009642279],"category_scores_gemma":[0.0017830831,0.00013674931,0.00020922555,0.00043880873,0.00018602434,0.00024134251,0.00022455226,0.00026670893,0.00021292755],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026879883,0.00043149377,0.09542079,0.0011954489,0.000079998325,0.0008136207,0.0006640154,0.008980933,0.8200205,0.00009670147,0.00045162626,0.06915691],"study_design_scores_gemma":[0.000029613338,0.018181933,0.3771468,0.0001079521,0.00014592303,0.0012394565,0.0011634214,0.014517583,0.5842979,0.00012707403,0.002966962,0.00007546456],"about_ca_topic_score_codex":0.0008014101,"about_ca_topic_score_gemma":0.0016011319,"teacher_disagreement_score":0.0009642279,"about_ca_system_score_codex":0.0001420724,"about_ca_system_score_gemma":0.00011314846,"threshold_uncertainty_score":0.0032256246},"labels":[],"label_agreement":null},{"id":"W4413904887","doi":"10.1115/1.4069662","title":"A Crystal Plasticity-Based Model for Orthogonal Machining Mechanics of Single-Crystal Materials","year":2025,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Crystal plasticity; Machining; Materials science; Plasticity; Single crystal; Mechanical engineering; Mechanics; Composite material; Engineering; Physics; Metallurgy; Crystallography; Chemistry","score_opus":0.010332394712449384,"score_gpt":0.2219562413186145,"score_spread":0.21162384660616512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413904887","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16550139,0.00085279654,0.81035894,0.00039023103,0.00010037448,0.00013057434,0.00021184809,0.00020826199,0.02224562],"genre_scores_gemma":[0.96934456,0.00049071753,0.023789136,0.000049618167,0.000022488624,0.0001442865,0.00008722631,0.000045933524,0.0060259155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998599,0.000022972377,0.000006231638,0.000021575981,0.0000685782,0.000020764028],"domain_scores_gemma":[0.9998275,0.000056833596,0.000033050488,0.000026388821,0.00004201423,0.0000142004055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002514885,0.00035564337,0.00052122696,0.0003794815,0.0002866564,0.0006697164,0.0010544604,0.0010883787,0.0011548459],"category_scores_gemma":[0.0004889584,0.00031745734,0.000608842,0.00038518204,0.00068398943,0.00064742175,0.0003482487,0.0005673078,0.00026067137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010663114,0.000034555105,0.0003559802,0.000029950166,0.000008822294,0.00009392327,0.000018132443,0.97631526,0.0072006816,0.012825902,0.0001854246,0.002920806],"study_design_scores_gemma":[0.0000010158029,0.0000031889808,0.000054855875,9.902461e-7,8.5385307e-7,0.000007384034,0.0000014860874,0.9991328,0.00020550551,0.00050394225,0.0000863279,0.0000016020466],"about_ca_topic_score_codex":0.0047789514,"about_ca_topic_score_gemma":0.003769618,"teacher_disagreement_score":0.0047789514,"about_ca_system_score_codex":0.000522898,"about_ca_system_score_gemma":0.0009223441,"threshold_uncertainty_score":0.009502292},"labels":[],"label_agreement":null},{"id":"W4413948239","doi":"10.1016/j.mfglet.2025.06.159","title":"A transfer learning approach for chatter detection in multi-posture robot machining","year":2025,"lang":"en","type":"article","venue":"Manufacturing Letters","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Transfer of learning; Machining; Artificial intelligence; Robot; Computer science; Computer vision; Human–computer interaction; Engineering; Mechanical engineering","score_opus":0.008908277963493512,"score_gpt":0.22217898824375143,"score_spread":0.21327071028025793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413948239","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07562168,0.00021067842,0.92162895,0.0000983721,0.000036236004,0.000055969704,0.00003647364,0.0010069585,0.0013046159],"genre_scores_gemma":[0.909961,0.00008290061,0.08732509,0.000063952466,0.000024523166,0.00009437636,0.000098817334,0.000052986506,0.0022964645],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996965,0.000050462128,0.00001811457,0.00010141414,0.00009635555,0.00003713683],"domain_scores_gemma":[0.999273,0.00027969494,0.00010215894,0.00008259169,0.0002241235,0.00003843292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006919915,0.0007800894,0.00054692564,0.0007234573,0.00033261316,0.00035458556,0.00096276967,0.0007680656,0.0011487718],"category_scores_gemma":[0.0021704528,0.00032353177,0.0004645891,0.00039346775,0.0004967644,0.0006711233,0.00065980415,0.0008441009,0.00029994815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022819736,0.00017621081,0.003175731,0.00007118041,0.000049498296,0.00019228259,0.00015096451,0.5626701,0.019026628,0.0013637941,0.0009387175,0.4119568],"study_design_scores_gemma":[0.0000017911359,0.00003836003,0.00045228552,0.0000025864872,0.0000024492551,0.00001460125,0.000008285154,0.9971391,0.0016915664,0.00054618675,0.00009847233,0.0000044769067],"about_ca_topic_score_codex":0.0033435773,"about_ca_topic_score_gemma":0.0030417673,"teacher_disagreement_score":0.0033435773,"about_ca_system_score_codex":0.00053494057,"about_ca_system_score_gemma":0.00043532648,"threshold_uncertainty_score":0.0066482425},"labels":[],"label_agreement":null},{"id":"W4414090142","doi":"10.1016/j.aei.2025.103803","title":"Physics-informed deep learning method for surface roughness prediction in milling process","year":2025,"lang":"en","type":"article","venue":"Advanced Engineering Informatics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Surface roughness; Mean squared error; Surface finish; Root mean square; Leverage (statistics); Process (computing); Artificial neural network; Mean absolute percentage error","score_opus":0.004591595288886932,"score_gpt":0.26101115784361106,"score_spread":0.25641956255472415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414090142","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08331984,0.0009049515,0.9101087,0.0003017873,0.000098082484,0.000036159654,0.0002716398,0.0017565837,0.0032021997],"genre_scores_gemma":[0.91614926,0.0003486925,0.07741711,0.00017798333,0.00006500238,0.000070660615,0.0004902598,0.00012181286,0.005159269],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989784,0.000013354542,0.000004974258,0.000029793111,0.000034335673,0.00001961241],"domain_scores_gemma":[0.9997811,0.00008827277,0.000022238666,0.00002331824,0.00006938899,0.000015692973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002702307,0.00046337058,0.0005733168,0.00039044526,0.00023348865,0.00047423775,0.0009900711,0.00087016844,0.0018920836],"category_scores_gemma":[0.0006623347,0.0003503242,0.0005694824,0.00037245353,0.00024020803,0.0007320009,0.00052638474,0.0010152739,0.00040853667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000102871985,0.00010809625,0.0013096354,0.000088749985,0.00005530249,0.00005200313,0.000022139831,0.87612695,0.007009105,0.0029231505,0.0019306018,0.11027138],"study_design_scores_gemma":[0.0000011353408,0.0000039845945,0.00006702549,8.284306e-7,0.0000015732385,0.0000020160808,5.8455265e-7,0.99925643,0.00027647847,0.00032845003,0.00006051537,9.929229e-7],"about_ca_topic_score_codex":0.0058452617,"about_ca_topic_score_gemma":0.006921354,"teacher_disagreement_score":0.0058452617,"about_ca_system_score_codex":0.00046397574,"about_ca_system_score_gemma":0.00086688914,"threshold_uncertainty_score":0.011622429},"labels":[],"label_agreement":null},{"id":"W4414558901","doi":"10.3390/jmmp9100323","title":"Bayesian Model Updating for Chatter in Milling","year":2025,"lang":"en","type":"article","venue":"Journal of Manufacturing and Materials Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Modal; Machining; Bayesian probability; Vibration; Machine tool; Modal analysis; Stability (learning theory)","score_opus":0.0069861012138076,"score_gpt":0.2460732364160108,"score_spread":0.2390871352022032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414558901","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013695948,0.00013499049,0.98521113,0.00007624694,0.000017745933,0.000023029712,0.00002053304,0.00020410406,0.00061616104],"genre_scores_gemma":[0.85041755,0.000248257,0.14651294,0.00015285588,0.000048595266,0.0001735591,0.00015259879,0.00013327699,0.0021604898],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987702,0.00044650654,0.00006419373,0.0002620702,0.00035523187,0.00010173594],"domain_scores_gemma":[0.99556786,0.0030411363,0.0004292352,0.00026815216,0.0006140512,0.0000795264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030724339,0.001121146,0.0015856827,0.00068350596,0.000573157,0.001014727,0.0016880463,0.00112911,0.0013009234],"category_scores_gemma":[0.012561469,0.0008893479,0.00064922165,0.00043805919,0.0009871414,0.0015536753,0.0013982061,0.0018433233,0.00030722652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000118548945,0.000053776872,0.0009756886,0.00010650958,0.00004922171,0.00005653176,0.00014404742,0.9350249,0.0031701967,0.008115729,0.0004103928,0.051774487],"study_design_scores_gemma":[0.0000042971615,0.000011937926,0.00013170706,0.0000041078283,0.0000041940925,0.0000064992278,0.0000035709825,0.99754024,0.0004224211,0.0017537135,0.0001106834,0.0000065844356],"about_ca_topic_score_codex":0.0065446664,"about_ca_topic_score_gemma":0.0075088926,"teacher_disagreement_score":0.0065446664,"about_ca_system_score_codex":0.00078829634,"about_ca_system_score_gemma":0.0009902064,"threshold_uncertainty_score":0.016248822},"labels":[],"label_agreement":null},{"id":"W4414699804","doi":"10.1088/1361-6501/ae0e3d","title":"Offline circular path error measurement and compensation for robotic machining applications","year":2025,"lang":"en","type":"article","venue":"Measurement Science and Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Machining; Compensation (psychology); Robot; Distortion (music); Rigidity (electromagnetism); Process (computing); Machine tool; Numerical control; Compensation methods","score_opus":0.024540494301152824,"score_gpt":0.2560033278011839,"score_spread":0.23146283350003108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414699804","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08765403,0.0002890736,0.9077587,0.000065017775,0.00007713699,0.00007307873,0.00008535739,0.0023294277,0.001668129],"genre_scores_gemma":[0.73387575,0.00015560436,0.26394856,0.000051769795,0.000031863256,0.00008279768,0.00016733886,0.00019220638,0.0014940217],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99831474,0.00020811781,0.0000709107,0.0002979229,0.0010269918,0.000081224964],"domain_scores_gemma":[0.9978301,0.0003991266,0.00054325286,0.00056284154,0.00061137666,0.00005332621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085953553,0.00088649517,0.00059025316,0.00063294894,0.00029344697,0.0006531887,0.0010799684,0.0006032024,0.0015299261],"category_scores_gemma":[0.0028907657,0.00037598034,0.0001981706,0.00067547424,0.0004462558,0.0008915811,0.0010931982,0.00065467384,0.00053520914],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007148999,0.00022117881,0.0055281,0.00034213,0.000049238082,0.00018610083,0.00027436318,0.03080535,0.6262134,0.0032416643,0.0021280826,0.3302954],"study_design_scores_gemma":[0.000047071066,0.00059687346,0.0077781077,0.00003319756,0.00002569373,0.00034807585,0.000071619725,0.35004368,0.63187927,0.0011858479,0.007882255,0.00010830924],"about_ca_topic_score_codex":0.0008823015,"about_ca_topic_score_gemma":0.0014709613,"teacher_disagreement_score":0.0015299261,"about_ca_system_score_codex":0.00041146038,"about_ca_system_score_gemma":0.00085331313,"threshold_uncertainty_score":0.0051181316},"labels":[],"label_agreement":null},{"id":"W4414744789","doi":"10.1051/matecconf/202541402006","title":"Discrimination of D2 steel roughness after hard milling","year":2025,"lang":"en","type":"article","venue":"MATEC Web of Conferences","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Surface roughness; Machining; Surface finish; Cluster analysis; Tool wear; Hardened steel; Surface (topology)","score_opus":0.010626320298748394,"score_gpt":0.2397702079458282,"score_spread":0.22914388764707982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414744789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9893385,0.00011485678,0.009466681,0.000011740747,0.000013465609,0.000019118423,0.00009096948,0.00009331782,0.000851375],"genre_scores_gemma":[0.99518126,0.00003981964,0.004175997,0.000008101006,0.0000037912205,0.0000054027514,0.00018649345,0.000014745637,0.00038439082],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99945205,0.0000698369,0.000034482662,0.00012774944,0.00024291695,0.00007294691],"domain_scores_gemma":[0.99877554,0.00055567117,0.00013843144,0.00015011564,0.00031373434,0.00006645402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005311931,0.00034614865,0.00035764356,0.0010700873,0.00020377505,0.00070818514,0.00025837467,0.00054108014,0.0009631384],"category_scores_gemma":[0.0018992289,0.0001678991,0.00034376423,0.0003795305,0.00033704002,0.00026066243,0.00028880133,0.0004196987,0.0003869195],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009876497,0.00005442431,0.013133828,0.00013802924,0.000023930545,0.000114938826,0.00019574477,0.0037417682,0.9391491,0.00010974999,0.00014285787,0.04220788],"study_design_scores_gemma":[0.000043357257,0.0013122202,0.31829184,0.000013691373,0.00005564708,0.0004151876,0.0004965721,0.04517262,0.6323479,0.0003204349,0.0014448884,0.000085677486],"about_ca_topic_score_codex":0.001129493,"about_ca_topic_score_gemma":0.0012716079,"teacher_disagreement_score":0.001129493,"about_ca_system_score_codex":0.00018323935,"about_ca_system_score_gemma":0.00011934408,"threshold_uncertainty_score":0.0032220483},"labels":[],"label_agreement":null},{"id":"W4415047157","doi":"10.3390/lubricants13100444","title":"Experimental Investigation and Modelling of High-Speed Turn-Milling of H13 Tool Steel: Surface Roughness and Tool Wear","year":2025,"lang":"en","type":"article","venue":"Lubricants","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Centre québécois de recherche et de développement de l’aluminium","keywords":"Surface roughness; Machining; Tool wear; Surface finish; Cutting tool; Machine tool; Face (sociological concept); Response surface methodology","score_opus":0.014138604299717398,"score_gpt":0.2307546529327737,"score_spread":0.2166160486330563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415047157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994187,0.00007657493,0.005043671,0.000009926685,0.000005715173,0.000026069512,0.0001615563,0.000044376622,0.00044518645],"genre_scores_gemma":[0.9977946,0.000049355276,0.0018164101,0.0000025425077,8.4651833e-7,0.000013288543,0.00006812152,0.000005017567,0.00024976008],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99965405,0.000035175854,0.000019539066,0.000058654074,0.00017880596,0.000053805634],"domain_scores_gemma":[0.99914205,0.0004024025,0.00009574416,0.00011746179,0.00021443883,0.000027892143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006102276,0.0003927875,0.0005305861,0.00032533347,0.00027743226,0.00041178253,0.00056667125,0.0009220427,0.000901778],"category_scores_gemma":[0.0007836896,0.00024578953,0.00067444146,0.00041476166,0.00034322965,0.00025039865,0.00017661003,0.00039196742,0.00018985658],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010183288,0.00060639775,0.017872626,0.0005581914,0.00006018202,0.00051939324,0.0005042822,0.17477094,0.7714566,0.0002774034,0.00038300888,0.03197262],"study_design_scores_gemma":[0.000053305466,0.0029082736,0.0642954,0.00002398373,0.00006371334,0.00017801733,0.00033960168,0.51157737,0.4194088,0.00017042024,0.0009164102,0.000064770284],"about_ca_topic_score_codex":0.0031939568,"about_ca_topic_score_gemma":0.0043649054,"teacher_disagreement_score":0.0031939568,"about_ca_system_score_codex":0.00037509608,"about_ca_system_score_gemma":0.000223612,"threshold_uncertainty_score":0.006350696},"labels":[],"label_agreement":null},{"id":"W4415207463","doi":"10.3390/mi16101169","title":"A Novel Tool Condition Monitoring Technique of Determining Insert Flank Wear Width of Indexable Face Milling Tools Using On-Machine Laser Tool Setters","year":2025,"lang":"en","type":"article","venue":"Micromachines","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Insert (composites); Flank; Tool wear; Machining; Machine tool; Cutting tool; Enhanced Data Rates for GSM Evolution","score_opus":0.012656247288420248,"score_gpt":0.2639299112001025,"score_spread":0.25127366391168227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415207463","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34260646,0.0022742928,0.6474917,0.00015671337,0.00025071113,0.00017723656,0.00023817125,0.003097572,0.0037070941],"genre_scores_gemma":[0.7636009,0.00059864076,0.23291625,0.00013076626,0.00007377014,0.00008064677,0.00015983434,0.000076716424,0.0023625025],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99902487,0.00004963973,0.000044981796,0.00022659647,0.0006021799,0.000051694744],"domain_scores_gemma":[0.9989691,0.00018013209,0.00026604385,0.00017204414,0.00037033143,0.000042380565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031261076,0.0005308692,0.0005881159,0.0010760757,0.00020158822,0.0005320959,0.0011807127,0.0007194953,0.00066379854],"category_scores_gemma":[0.0011627842,0.00032503088,0.00028451768,0.00052469084,0.00030077,0.00092823093,0.0003729739,0.00050563534,0.00028595765],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002563855,0.000072803596,0.006323016,0.00031962682,0.00003193337,0.0002790734,0.00024358017,0.0015101063,0.7680697,0.00046301686,0.00090046145,0.22153032],"study_design_scores_gemma":[0.000070164126,0.0008459646,0.043405473,0.000056732064,0.000114172435,0.0032835566,0.00020158562,0.10813755,0.8344604,0.00059512834,0.008649917,0.00017948712],"about_ca_topic_score_codex":0.00062969374,"about_ca_topic_score_gemma":0.0009271813,"teacher_disagreement_score":0.0011807127,"about_ca_system_score_codex":0.00026976655,"about_ca_system_score_gemma":0.00030806713,"threshold_uncertainty_score":0.002220571},"labels":[],"label_agreement":null},{"id":"W4415210300","doi":"10.3390/jcs9100558","title":"The Effect of Lubricant and Nanofiller Additives on Drilling Temperature in GFRP Composites","year":2025,"lang":"en","type":"article","venue":"Journal of Composites Science","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lubricant; Wax; Fibre-reinforced plastic; Thermal; Drilling; Graphene; Polymer","score_opus":0.0015987030712742972,"score_gpt":0.2243132152066022,"score_spread":0.2227145121353279,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415210300","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99818784,0.0007731584,0.000688071,0.000011538454,0.000010324396,0.0000060513325,0.0000461823,0.000016831169,0.00025984668],"genre_scores_gemma":[0.99726427,0.00053633057,0.0018597271,0.00000804866,0.0000027157118,0.000008757468,0.00003580218,0.000013899081,0.00027048096],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978775,0.000028593191,0.00002314772,0.000037974227,0.0000827332,0.0000398091],"domain_scores_gemma":[0.99973327,0.00007696277,0.000087224216,0.000015928976,0.0000648935,0.000021604419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024900996,0.00032762866,0.00022487088,0.000291705,0.00017233592,0.0002734762,0.00014960441,0.00018988029,0.00041510162],"category_scores_gemma":[0.0005152723,0.00020385977,0.0002592205,0.0002711673,0.00018367771,0.0003488754,0.00018004586,0.0003953516,0.000095966876],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001729295,0.000024974208,0.00047696533,0.00011346641,0.000009459318,0.000032107455,0.000038298,0.00047916788,0.9955941,0.000025655921,0.000016935566,0.0030159487],"study_design_scores_gemma":[0.0000028742643,0.00033409247,0.0027922112,0.000008146907,0.000024923735,0.000024294908,0.000036127916,0.0009833983,0.99538773,0.000008158522,0.0003909244,0.0000072302983],"about_ca_topic_score_codex":0.00081366586,"about_ca_topic_score_gemma":0.002649213,"teacher_disagreement_score":0.00081366586,"about_ca_system_score_codex":0.00015186278,"about_ca_system_score_gemma":0.000148402,"threshold_uncertainty_score":0.0016178489},"labels":[],"label_agreement":null},{"id":"W4415382958","doi":"10.1038/s41598-025-20454-3","title":"Multi-objective optimization of surface roughness and MRR in AISI 316L stainless steel processed by MQL end milling using taguchi, RSM, ANN, and RFR methods","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Surface roughness; Machining; Taguchi methods; Lubrication; Surface finish; Response surface methodology; Tool wear; Lubricant","score_opus":0.012404486588173724,"score_gpt":0.30290836963747253,"score_spread":0.2905038830492988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415382958","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74247617,0.0011003396,0.25419605,0.00008435385,0.00002985325,0.00008544388,0.000082900944,0.00020546805,0.0017393719],"genre_scores_gemma":[0.9002517,0.00026083397,0.09836247,0.000024458224,0.000005405595,0.000075022675,0.000068039626,0.000024615145,0.0009275388],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995178,0.00008107473,0.000041537784,0.00008009305,0.00023170168,0.000047732337],"domain_scores_gemma":[0.9994474,0.00022012522,0.00015242511,0.000028945498,0.0001340658,0.000017115817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001146841,0.00079295534,0.0007380272,0.0005716136,0.00019489006,0.0006363816,0.0005360229,0.000654516,0.00026520324],"category_scores_gemma":[0.0007765919,0.00036509597,0.0010220342,0.0003773984,0.00020261975,0.00030851242,0.00024066764,0.00033663108,0.00009274452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002768344,0.0003177911,0.0047004274,0.00072087045,0.00010871648,0.0001553438,0.00012639278,0.5285318,0.37616193,0.000518623,0.00023241348,0.088148855],"study_design_scores_gemma":[0.000020162632,0.0008972513,0.004824333,0.000013173486,0.00006458765,0.000054044624,0.000051502015,0.90986836,0.083491914,0.00018043502,0.00049213425,0.00004198488],"about_ca_topic_score_codex":0.0020507728,"about_ca_topic_score_gemma":0.004389414,"teacher_disagreement_score":0.0020507728,"about_ca_system_score_codex":0.0004610502,"about_ca_system_score_gemma":0.00046791797,"threshold_uncertainty_score":0.0060651302},"labels":[],"label_agreement":null},{"id":"W4415694158","doi":"10.1016/j.ymssp.2025.113568","title":"MFAformer: A novel framework for milling chatter detection via multi-source signal fusion","year":2025,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Department of Education of Liaoning Province; National Natural Science Foundation of China","keywords":"Machining; Robustness (evolution); Noise (video); Vibration; Machine tool; SIGNAL (programming language); Feature extraction; Grinding; Signal processing","score_opus":0.014239921883558224,"score_gpt":0.25228585498529205,"score_spread":0.23804593310173383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415694158","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00068869145,0.00006939135,0.99775875,0.000014966928,0.000015800328,0.000014608622,0.000050620973,0.0011029482,0.0002841699],"genre_scores_gemma":[0.068845816,0.00022041795,0.92640406,0.00009439479,0.00008695815,0.000092402326,0.00040683243,0.00055074383,0.0032983785],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991086,0.00014680118,0.000041316252,0.00019199234,0.0004382502,0.00007293952],"domain_scores_gemma":[0.9993777,0.00019060625,0.00007869943,0.00014449813,0.00017166158,0.000036770027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012204389,0.0015539645,0.0012326697,0.0014037064,0.00050336344,0.0012689021,0.0022284894,0.0015511342,0.005934303],"category_scores_gemma":[0.0022897795,0.0005233236,0.0008883596,0.00087969465,0.00063000293,0.0017123733,0.0019183268,0.0013775817,0.0026583401],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005972141,0.00017246757,0.00055161107,0.0003378787,0.00016156823,0.0002640719,0.00014622093,0.08114845,0.0904501,0.036221106,0.00850203,0.78144723],"study_design_scores_gemma":[0.000020480247,0.00008264747,0.0002870528,0.000023667453,0.000019134635,0.00016491053,0.000012599345,0.9538204,0.025907943,0.010903819,0.008717625,0.000039693172],"about_ca_topic_score_codex":0.0018558291,"about_ca_topic_score_gemma":0.0028509707,"teacher_disagreement_score":0.005934303,"about_ca_system_score_codex":0.00038617622,"about_ca_system_score_gemma":0.0006554217,"threshold_uncertainty_score":0.019852221},"labels":[],"label_agreement":null},{"id":"W4416026593","doi":"10.1007/s00170-025-16870-4","title":"On machining using nanofluid based minimum quantity lubricant: stability and tool wear analysis","year":2025,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; Academy of Scientific Research and Technology","keywords":"Nanofluid; Machining; Tool wear; Austenitic stainless steel; Austenite; Pulmonary surfactant; Work (physics)","score_opus":0.007465267038401352,"score_gpt":0.25532889315304674,"score_spread":0.24786362611464538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416026593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84781957,0.0017734123,0.14670283,0.00008617983,0.000039486607,0.000035913894,0.00004790632,0.00009569671,0.0033990354],"genre_scores_gemma":[0.99177855,0.00019267571,0.0067864293,0.000005888487,0.0000057881343,0.000006452544,0.000024774628,0.0000145763415,0.001184898],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999871,0.000022512662,0.000006680331,0.000024052895,0.000062709805,0.000013082246],"domain_scores_gemma":[0.9995383,0.0002735893,0.00005437541,0.000029678173,0.00009612968,0.000007987909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023029385,0.00023049397,0.00044119742,0.0003564303,0.00030901848,0.0003608908,0.0003102391,0.00034895638,0.00057536113],"category_scores_gemma":[0.0007611194,0.00012287279,0.000376751,0.00022077911,0.00037407974,0.00043441763,0.00021836133,0.00024761574,0.00007838629],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012367879,0.00015821721,0.0036633564,0.0007267851,0.00010295007,0.00030519132,0.00039338844,0.25326735,0.6745846,0.010214146,0.0005928533,0.054754388],"study_design_scores_gemma":[0.000010251033,0.00037598418,0.0020288366,0.000006517494,0.000018179462,0.00010066532,0.000033625663,0.93438494,0.061974,0.00060813606,0.00044486483,0.000013961002],"about_ca_topic_score_codex":0.001760981,"about_ca_topic_score_gemma":0.0013860791,"teacher_disagreement_score":0.001760981,"about_ca_system_score_codex":0.0002750973,"about_ca_system_score_gemma":0.00021078957,"threshold_uncertainty_score":0.0035014153},"labels":[],"label_agreement":null},{"id":"W4416799049","doi":"10.1109/icriset64803.2025.11252179","title":"Surface Roughness Classification Using Attention-Guided Convolutional Neural Networks on Real-Time Machining Sensor Data","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Machining; Convolutional neural network; Surface roughness; Python (programming language); Pattern recognition (psychology); Artificial neural network; Surface finish","score_opus":0.05644453446440733,"score_gpt":0.3232804374903993,"score_spread":0.26683590302599197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416799049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75596726,0.0009988035,0.23193784,0.00036364244,0.00014619209,0.00006727854,0.0012544636,0.0058980486,0.0033664994],"genre_scores_gemma":[0.9723674,0.0001329847,0.024315912,0.00008075719,0.000025601452,0.000024079207,0.0014247275,0.00005567468,0.0015727994],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977404,0.000018838296,0.000008523701,0.00008677293,0.000058340323,0.000053374486],"domain_scores_gemma":[0.9996942,0.00009289983,0.00005164982,0.0000484996,0.00009423949,0.000018484334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028862187,0.0009239308,0.00039748184,0.0007156006,0.00016605463,0.00040939043,0.00069868966,0.00048020587,0.0007659025],"category_scores_gemma":[0.0011299966,0.00018495801,0.00045162436,0.00045438757,0.00023017751,0.0005012294,0.00046420484,0.0005585087,0.00031508162],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067413057,0.00035935667,0.017595049,0.00014277475,0.00017078893,0.00029539046,0.00009544952,0.4427913,0.07694933,0.00083058135,0.0067255027,0.45337033],"study_design_scores_gemma":[0.000004674688,0.00002797891,0.0038944834,0.000003946379,0.000011151956,0.000017376196,0.000008397876,0.9890859,0.006414645,0.0002806495,0.00024476906,0.0000059715812],"about_ca_topic_score_codex":0.015631083,"about_ca_topic_score_gemma":0.02268519,"teacher_disagreement_score":0.015631083,"about_ca_system_score_codex":0.000653486,"about_ca_system_score_gemma":0.0004064723,"threshold_uncertainty_score":0.031080186},"labels":[],"label_agreement":null},{"id":"W4416818757","doi":"10.1016/j.cirpj.2025.11.011","title":"Modeling multi-directional CFRP cutting mechanics with ply-constraining effect","year":2025,"lang":"en","type":"article","venue":"CIRP journal of manufacturing science and technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fracture mechanics; Fracture (geology); Carbon fiber reinforced polymer; Stress (linguistics); Failure mode and effects analysis; Fibre-reinforced plastic; Damage mechanics; Strain rate; Chip formation","score_opus":0.0046501296919738665,"score_gpt":0.2262442965133561,"score_spread":0.22159416682138222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416818757","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4327765,0.00052503805,0.5572849,0.00010985981,0.00003462181,0.00007723222,0.00013899266,0.0002519017,0.00880098],"genre_scores_gemma":[0.9793144,0.00029445215,0.01823018,0.000016839003,0.000008827464,0.00007896073,0.000038253987,0.000030515786,0.0019875022],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998877,0.000016446893,0.0000046085006,0.000027109412,0.000041169278,0.0000229733],"domain_scores_gemma":[0.99984884,0.000047691625,0.000046060788,0.000021409349,0.000026158687,0.000009942931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018932132,0.0004762128,0.00032759993,0.00033970218,0.00021339358,0.00031290654,0.0005975173,0.00090144714,0.0005951478],"category_scores_gemma":[0.00035822214,0.00032102098,0.00054136675,0.00019980494,0.0003899128,0.0004765268,0.0003066401,0.0003206888,0.000115046525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011313784,0.000018683666,0.0008374018,0.000027799397,0.000008794344,0.000100021294,0.000030858293,0.98150176,0.012034409,0.0016344801,0.000053994303,0.0037404418],"study_design_scores_gemma":[0.0000018279012,0.000010997352,0.00035559168,0.0000015826923,0.0000029641878,0.000018844768,0.0000036539288,0.9986155,0.00062301685,0.00020808823,0.00015516348,0.000002700757],"about_ca_topic_score_codex":0.0046343547,"about_ca_topic_score_gemma":0.002822586,"teacher_disagreement_score":0.0046343547,"about_ca_system_score_codex":0.00030386116,"about_ca_system_score_gemma":0.00046994493,"threshold_uncertainty_score":0.009214759},"labels":[],"label_agreement":null},{"id":"W52598574","doi":"","title":"Effect of Stope Undercutting On Its Wall Overbreak","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Agnico Eagle (Canada); McGill University","funders":"","keywords":"Engineering; Geology; Environmental science; Forensic engineering; Geotechnical engineering","score_opus":0.006635391560770509,"score_gpt":0.25187457811208785,"score_spread":0.24523918655131735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W52598574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99568224,0.00015671748,0.00088901387,0.00004985306,0.000092791306,0.0000059454746,0.00012820047,0.00010486123,0.002890383],"genre_scores_gemma":[0.99793196,0.000056266745,0.00031544684,0.0000151007225,0.00000606605,0.0000027336666,0.00010000276,0.00003664917,0.0015357598],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997569,0.000014620397,0.00000742256,0.000046841073,0.000047598092,0.00012673302],"domain_scores_gemma":[0.9988356,0.0004211541,0.00013814341,0.00009565985,0.00021636186,0.00029314545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023798196,0.0004360361,0.0006361733,0.00041653163,0.0006734049,0.001131586,0.000515659,0.00091140677,0.012611201],"category_scores_gemma":[0.0011259012,0.00027047994,0.00041032425,0.00033201373,0.00053102477,0.00039447256,0.00051768677,0.00081851525,0.00085605687],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.014200791,0.00060725654,0.007992681,0.0003145218,0.00013381425,0.0015727847,0.00019255912,0.05925484,0.8876914,0.0012802102,0.001696219,0.025062885],"study_design_scores_gemma":[0.00023928635,0.0050678644,0.052026466,0.00004638114,0.0003562722,0.00046405365,0.0010834398,0.06015533,0.87555087,0.00054864475,0.004353533,0.00010794382],"about_ca_topic_score_codex":0.0016612603,"about_ca_topic_score_gemma":0.0015590258,"teacher_disagreement_score":0.012611201,"about_ca_system_score_codex":0.0002985149,"about_ca_system_score_gemma":0.0003605105,"threshold_uncertainty_score":0.042188704},"labels":[],"label_agreement":null},{"id":"W564193049","doi":"10.1007/s00170-015-7179-y","title":"Effect of rake angle on Johnson-Cook material constants and their impact on cutting process parameters of Al2024-T3 alloy machining simulation","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Machining; Rake angle; Finite element method; Constitutive equation; Chip formation; Materials science; Drilling; Rake; Mechanical engineering; Residual stress; Chip; Structural engineering; Tool wear; Engineering; Metallurgy","score_opus":0.008024234735001513,"score_gpt":0.28255782929176587,"score_spread":0.27453359455676435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W564193049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9822748,0.0003097747,0.0094871465,0.00007381804,0.000041079067,0.000021153297,0.00022127097,0.00023409328,0.0073367353],"genre_scores_gemma":[0.99774194,0.00006308595,0.0014587579,0.000010727521,0.0000021543863,0.0000074539175,0.000066945235,0.00004209237,0.0006069159],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997527,0.00005456803,0.000015154988,0.0000507776,0.000065161315,0.000061664614],"domain_scores_gemma":[0.99827385,0.0011928844,0.00014610765,0.0001241791,0.00021201969,0.000050938517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045527334,0.0004905199,0.00035086396,0.00043424906,0.00041425708,0.00054367434,0.00058769924,0.0010964585,0.0026161254],"category_scores_gemma":[0.0022601418,0.0003442683,0.0004310885,0.0004791141,0.00042392133,0.00057214266,0.00022907711,0.00049781124,0.0003087166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071698136,0.00017203744,0.0051902975,0.00016170548,0.000044319095,0.00024420436,0.00013356956,0.9511655,0.03137142,0.0007166269,0.00033462778,0.009748677],"study_design_scores_gemma":[0.00005718861,0.00043604148,0.011440173,0.000039642644,0.0000960714,0.00009867351,0.00019896947,0.93122274,0.05485477,0.00025471358,0.0012374696,0.00006356675],"about_ca_topic_score_codex":0.00376394,"about_ca_topic_score_gemma":0.0039048991,"teacher_disagreement_score":0.00376394,"about_ca_system_score_codex":0.00026824977,"about_ca_system_score_gemma":0.00036911498,"threshold_uncertainty_score":0.008751869},"labels":[],"label_agreement":null},{"id":"W586912333","doi":"10.1016/j.procir.2015.03.051","title":"A Solid Modeler Based Engagement Model for 5-axis Ball End Milling","year":2015,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of British Columbia; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"End milling; Ball (mathematics); Machining; Mechanical engineering; Process (computing); Solid surface; End mill; Engineering drawing; Engineering; Materials science; Computer science; Geometry; Mathematics; Physics","score_opus":0.05580163019437431,"score_gpt":0.2979919684833002,"score_spread":0.24219033828892586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W586912333","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04653455,0.00014003465,0.9444548,0.000056293648,0.000014805505,0.00004376242,0.00011014826,0.00033013403,0.008315462],"genre_scores_gemma":[0.8886653,0.00035942404,0.10232001,0.000033834567,0.000010456459,0.00014502612,0.0002859965,0.00014706388,0.008032855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979204,0.000032424763,0.00001052393,0.000024808776,0.000112873575,0.000027356702],"domain_scores_gemma":[0.99982387,0.00005834679,0.00003255227,0.000028158913,0.00004432436,0.000012778716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000232662,0.00036030466,0.00047952664,0.0002909137,0.00025291173,0.00075672125,0.0010180116,0.0009849041,0.00209224],"category_scores_gemma":[0.00044626155,0.00027722496,0.00053871656,0.0003098439,0.00043883087,0.0006857599,0.0005696798,0.00057382823,0.0007597455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022325847,0.000019853496,0.00022624621,0.00002325853,0.0000044727894,0.000053231586,0.00003561354,0.9810043,0.0060501606,0.0066782916,0.0001266354,0.0057556904],"study_design_scores_gemma":[0.0000018371607,0.0000080230175,0.00004291651,0.0000014945315,8.0405164e-7,0.000008142457,0.000002978155,0.99853957,0.00056771806,0.00040437104,0.0004198879,0.0000021837848],"about_ca_topic_score_codex":0.0027973212,"about_ca_topic_score_gemma":0.001981849,"teacher_disagreement_score":0.0027973212,"about_ca_system_score_codex":0.00037769155,"about_ca_system_score_gemma":0.00066727697,"threshold_uncertainty_score":0.006999254},"labels":[],"label_agreement":null},{"id":"W645047571","doi":"10.1007/s00170-015-7337-2","title":"Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Machining; Taguchi methods; Surface roughness; Mechanical engineering; Parametric statistics; Orthogonal array; Engineering; Design of experiments; Turret; Engineering drawing; Computer science; Materials science; Mathematics; Statistics; Machine learning; Composite material","score_opus":0.020131769982509002,"score_gpt":0.25168103653363705,"score_spread":0.23154926655112804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W645047571","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8538838,0.00061994675,0.08814093,0.00028034102,0.00009513341,0.00014669159,0.00025047205,0.00023370197,0.056348976],"genre_scores_gemma":[0.9912067,0.00007865572,0.0058747544,0.00001774766,0.0000055775495,0.00004713327,0.00006893883,0.00002649988,0.0026739258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974173,0.00006407957,0.000006503553,0.000030108742,0.00008395088,0.00007359157],"domain_scores_gemma":[0.99967504,0.00017526445,0.000038954615,0.00002449701,0.000062795225,0.000023444016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059460883,0.0006747549,0.00085739075,0.00066981534,0.0005743185,0.0009613947,0.000578119,0.0011313462,0.003952763],"category_scores_gemma":[0.0009211948,0.0005510393,0.0009523887,0.00034301996,0.0005083854,0.0002735607,0.0006544025,0.00059929333,0.00029456566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000099632474,0.000043340555,0.00036836346,0.00007584658,0.000016464912,0.000069893336,0.00003837403,0.98551416,0.006153876,0.00082781067,0.0002016447,0.0065905517],"study_design_scores_gemma":[0.00001977467,0.00023347045,0.000860397,0.0000073594074,0.00001559012,0.000021553078,0.00005410052,0.9956449,0.0021928411,0.0002742661,0.0006655306,0.000010234153],"about_ca_topic_score_codex":0.0057736924,"about_ca_topic_score_gemma":0.00555097,"teacher_disagreement_score":0.0057736924,"about_ca_system_score_codex":0.00051916006,"about_ca_system_score_gemma":0.0009095667,"threshold_uncertainty_score":0.01322335},"labels":[],"label_agreement":null},{"id":"W658105193","doi":"10.1299/jsmelem.2003.645","title":"403 Temperature Predictions in Machining","year":2003,"lang":"en","type":"article","venue":"Proceedings of International Conference on Leading Edge Manufacturing in 21st century LEM21","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada","keywords":"Machining; Rake; Chip; Chip formation; Mechanical engineering; Transient (computer programming); Heat transfer; Materials science; Rake angle; Steady state (chemistry); Energy balance; Mechanics; Tool wear; Engineering; Computer science; Physics; Thermodynamics","score_opus":0.013203023246861127,"score_gpt":0.24502033372812343,"score_spread":0.2318173104812623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W658105193","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2609615,0.0006872689,0.7255807,0.0001876271,0.0000997583,0.000047247442,0.00011355224,0.00059251883,0.011729859],"genre_scores_gemma":[0.97899306,0.00018802768,0.017734721,0.000020851217,0.000008358431,0.000026262258,0.0000606054,0.000052432053,0.002915692],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998709,0.000017479202,0.0000048348575,0.000029219584,0.00006406182,0.0000135189575],"domain_scores_gemma":[0.9997627,0.0001198064,0.000023623385,0.000026798403,0.000057100726,0.0000100558345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023509884,0.00029454264,0.00039671623,0.00021385818,0.00021821354,0.00055388646,0.0007064086,0.00082054373,0.0010221779],"category_scores_gemma":[0.0008250728,0.0003036324,0.00040623196,0.00018172142,0.00057770696,0.0006432299,0.00020686323,0.00042628995,0.00033588798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020717289,0.000014714594,0.0003602921,0.00002168645,0.0000034516172,0.000021743235,0.000022098893,0.9868203,0.0063685467,0.0017297765,0.00009014057,0.004526611],"study_design_scores_gemma":[0.0000031577106,0.000010416218,0.00012288138,0.000001926632,9.329084e-7,0.000005362285,0.0000022553002,0.997936,0.0012147785,0.00047447762,0.00022505736,0.0000027733868],"about_ca_topic_score_codex":0.004546138,"about_ca_topic_score_gemma":0.0023948231,"teacher_disagreement_score":0.004546138,"about_ca_system_score_codex":0.0006204273,"about_ca_system_score_gemma":0.00049142784,"threshold_uncertainty_score":0.009039342},"labels":[],"label_agreement":null},{"id":"W6885416328","doi":"10.13394/j.cnki.jgszz.2023.1003","title":"Comparative evaluation of the performances of single layer diamond tools in orbital drilling of composites","year":2023,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"","keywords":"Drilling; Diamond; Surface roughness; Machining; Surface finish; Diamond tool; Grain size","score_opus":0.3655098054434554,"score_gpt":0.5379074065449254,"score_spread":0.17239760110147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6885416328","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960866,0.0012710092,0.0018617483,0.000008791232,0.000013040614,0.000009581859,0.00006147898,0.00004883792,0.00063878426],"genre_scores_gemma":[0.9959596,0.0003707453,0.0031737955,0.0000027224728,0.0000025549618,0.000004104959,0.000050099854,0.00001805524,0.00041827155],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99941635,0.000063422995,0.00004214275,0.000077676654,0.00030870383,0.000091644695],"domain_scores_gemma":[0.9980889,0.00079828553,0.00033446949,0.00021088772,0.0004408291,0.00012668314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057296717,0.00041075985,0.0004523965,0.00092580286,0.00024396284,0.00052294636,0.00036975244,0.0004939587,0.0008266215],"category_scores_gemma":[0.0015318517,0.00023213131,0.0003256733,0.00054786867,0.00034260636,0.0005330904,0.00038271234,0.00022883482,0.00017646175],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017572036,0.00012377511,0.0037385132,0.0006644227,0.00004256287,0.00022018631,0.00023511806,0.0075355615,0.94120413,0.00013145719,0.00009995033,0.04424718],"study_design_scores_gemma":[0.000029233968,0.006546247,0.02392038,0.00003521887,0.00008402317,0.0004932621,0.00032135154,0.011628608,0.954646,0.00010233243,0.002132364,0.00006102628],"about_ca_topic_score_codex":0.0005394002,"about_ca_topic_score_gemma":0.0015174724,"teacher_disagreement_score":0.00092580286,"about_ca_system_score_codex":0.00017640537,"about_ca_system_score_gemma":0.0001732216,"threshold_uncertainty_score":0.003030181},"labels":[],"label_agreement":null},{"id":"W6907946932","doi":"10.25392/leicester.data.23977266.v1","title":"Growth, form and function in problematic Cambrian paraconodonts","year":2023,"lang":"en","type":"dissertation","venue":"Figshare","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Polyphyly; Taphonomy; Vertebrate; Assemblage (archaeology); Fossil Record; Basal (medicine)","score_opus":0.013902340791662518,"score_gpt":0.23287078066363537,"score_spread":0.21896843987197284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6907946932","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99931145,0.00013099845,0.000035984605,0.0000035151643,4.939618e-7,0.0000016617956,0.000042061925,0.0000014984123,0.00047237697],"genre_scores_gemma":[0.9989416,0.00012236065,0.00021231695,0.000006173412,0.0000015690019,0.0000054404163,0.00016512064,0.0000037584562,0.00054154533],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983394,0.000012985332,0.000012317855,0.00005963713,0.000048755614,0.000032393174],"domain_scores_gemma":[0.9997583,0.000038621085,0.000087342516,0.000018946283,0.00005340022,0.000043429063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014728605,0.00029737016,0.00030530876,0.0021648286,0.00066910463,0.00056964613,0.00039375984,0.00034808106,0.0013186685],"category_scores_gemma":[0.0007313333,0.00028931556,0.00014072198,0.0013688926,0.00091485196,0.00029235677,0.00050567894,0.0001731128,0.0002841108],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004120939,0.000043127922,0.8755811,0.00007008475,0.000026144866,0.00086821965,0.0028652274,0.00032819915,0.08985887,0.00026878688,0.000090809364,0.02958732],"study_design_scores_gemma":[0.000001141627,0.000032205862,0.99873513,0.0000040362215,0.0000034700724,0.00026805187,0.00033206155,0.000109627246,0.00024941112,0.000028791228,0.00023397742,0.0000020944476],"about_ca_topic_score_codex":0.028321283,"about_ca_topic_score_gemma":0.12111462,"teacher_disagreement_score":0.028321283,"about_ca_system_score_codex":0.000832407,"about_ca_system_score_gemma":0.0003254411,"threshold_uncertainty_score":0.05631292},"labels":[],"label_agreement":null},{"id":"W6920455113","doi":"10.60692/nvtm3-cg028","title":"The Use of Wavelet Transform To Evaluate The Sensitivity of Acoustic Emission Attributes To Variation of Cutting Parameters in Milling Aluminium Alloys","year":2021,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Polytechnique Montréal; University of British Columbia","funders":"","keywords":"Acoustic emission; SIGNAL (programming language); Wavelet transform; Signal processing; Sensitivity (control systems); Machining; Wavelet; Cutting tool; Entropy (arrow of time)","score_opus":0.04042499188424586,"score_gpt":0.22857722444207862,"score_spread":0.18815223255783275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6920455113","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97510684,0.00009074045,0.024367306,0.000010939506,0.0000072712533,0.000014474838,0.00003414541,0.00003446475,0.0003337682],"genre_scores_gemma":[0.99615085,0.000043245378,0.0036840288,0.0000029280309,0.0000017841295,0.0000065129434,0.000029481422,0.0000050361446,0.0000761596],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980193,0.000052378648,0.000015675949,0.00002826403,0.00008384672,0.000017966755],"domain_scores_gemma":[0.9990984,0.00057680806,0.00010637719,0.000044070403,0.00015016158,0.000024126744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072569906,0.00021872013,0.00021465633,0.00068826595,0.00010546688,0.0002682771,0.00013176615,0.00023582733,0.00038032208],"category_scores_gemma":[0.0020002858,0.00010936218,0.00021195771,0.0004250742,0.0001861141,0.0002555168,0.00015910143,0.00021364419,0.00006721282],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001628512,0.00030083072,0.06270306,0.00028879556,0.00015314168,0.0003288532,0.0003769373,0.054259166,0.72828346,0.00043961208,0.000162887,0.15107468],"study_design_scores_gemma":[0.000029536723,0.0017389696,0.2814107,0.000035433724,0.00013473537,0.00035567748,0.00038199092,0.45413238,0.26077452,0.00045199913,0.0004981034,0.00005604524],"about_ca_topic_score_codex":0.00053266424,"about_ca_topic_score_gemma":0.00036275518,"teacher_disagreement_score":0.00072569906,"about_ca_system_score_codex":0.00008199842,"about_ca_system_score_gemma":0.000078996665,"threshold_uncertainty_score":0.003837943},"labels":[],"label_agreement":null},{"id":"W6927478268","doi":"10.3389/fspas.2022.1040092.s003","title":"Video2_On the green isolated proton auroras during Canada thanksgiving geomagnetic storm.MP4","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Proton; Cyclotron; Earth's magnetic field; Ionosphere; Geomagnetic storm; Magnetosphere; Spectrograph; Spectral line; Range (aeronautics)","score_opus":0.007030297625444324,"score_gpt":0.19265046852087694,"score_spread":0.18562017089543262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6927478268","genre_codex":"other","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016985694,0.0015274497,0.0040440764,0.0026356927,0.0024440486,0.0005801289,0.36005357,0.0074037793,0.6043256],"genre_scores_gemma":[0.17653109,0.0034674727,0.02085436,0.0038943726,0.0016445499,0.00061300566,0.31388158,0.0033846253,0.47572887],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99993825,0.0000035953767,0.0000013160844,0.000007864064,0.00002343063,0.000025542726],"domain_scores_gemma":[0.999803,0.000032709242,0.0000094918005,0.000011302846,0.000081251776,0.00006223578],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009530752,0.00068016985,0.00027270682,0.0009730448,0.0011657581,0.00089312514,0.00072171545,0.00090929464,0.3651184],"category_scores_gemma":[0.00054347434,0.00018198341,0.00033185902,0.0011635998,0.0001981657,0.0005735688,0.00093925546,0.0006827309,0.06362191],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012175019,0.000027153706,0.0029128774,0.00021253483,0.000011362199,0.00042748873,0.0002543054,0.00040258397,0.0011385488,0.00055583037,0.9663786,0.027556978],"study_design_scores_gemma":[0.000054223703,0.000028771088,0.03329004,0.00035522267,0.000016539441,0.000458207,0.0010155065,0.0015601855,0.00074193726,0.0007081542,0.9617338,0.000037303318],"about_ca_topic_score_codex":0.23233424,"about_ca_topic_score_gemma":0.52730924,"teacher_disagreement_score":0.76766574,"about_ca_system_score_codex":0.0009777648,"about_ca_system_score_gemma":0.0011631564,"threshold_uncertainty_score":0.90558153},"labels":[],"label_agreement":null},{"id":"W6931580763","doi":"10.5683/sp2/euyayn","title":"Canadian Gallup Poll, February 1964, #306","year":2019,"lang":"en","type":"dataset","venue":"Borealis","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Respondent; Unemployment; Politics; Government (linguistics); Voting; Prime minister; Coalition government; Demographics; General Social Survey","score_opus":0.008287349430143828,"score_gpt":0.22474684727786465,"score_spread":0.2164594978477208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931580763","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000355024,0.00009197378,0.000032561344,0.00012958476,0.000043748478,0.000024035025,0.9968972,0.00014144623,0.002284351],"genre_scores_gemma":[0.00092769513,0.000074861695,0.0001635473,0.000058657948,0.000014268325,0.000057522855,0.99414104,0.000046250276,0.0045161895],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9976151,0.00017585311,0.00014596,0.0004004987,0.0011095217,0.00055312406],"domain_scores_gemma":[0.99397594,0.0003725209,0.00021185755,0.00061214215,0.0043139565,0.00051367923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016954512,0.0021968642,0.0015343539,0.0074138767,0.0039480426,0.0038926494,0.003415149,0.0016117563,0.041871995],"category_scores_gemma":[0.008566876,0.00086578587,0.0011469327,0.015359304,0.00071265583,0.0010716267,0.0017536993,0.0017747249,0.046592645],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003776407,0.000009805045,0.000851374,0.00007936488,0.0000111038025,0.000012390992,0.000020574073,0.00007704744,0.000021884805,0.00018325793,0.99700457,0.0016909704],"study_design_scores_gemma":[0.00014861023,0.000014100349,0.030481841,0.00014724687,0.0000362388,0.00003469905,0.0002621797,0.00065088994,0.00029604742,0.00030366427,0.9675752,0.000049344537],"about_ca_topic_score_codex":0.96108955,"about_ca_topic_score_gemma":0.98262995,"teacher_disagreement_score":0.041871995,"about_ca_system_score_codex":0.018636642,"about_ca_system_score_gemma":0.030102119,"threshold_uncertainty_score":0.1400758},"labels":[],"label_agreement":null},{"id":"W6957776300","doi":"10.60692/7fkt8-ne869","title":"Cutting force prediction for ball-end mills with non-horizontal and rotational cutting motions","year":2012,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Cutting tool; Process (computing); Chip; Work (physics); Rotational speed; Finite element method; Chip formation","score_opus":0.010624050718005306,"score_gpt":0.18930048268670824,"score_spread":0.17867643196870292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6957776300","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30267012,0.00019454297,0.693855,0.00005389491,0.000014775671,0.000060389724,0.00007129356,0.00023558036,0.0028443735],"genre_scores_gemma":[0.9709387,0.000087296554,0.027465818,0.000008467783,0.0000031696914,0.000035057772,0.00006735482,0.000017561508,0.0013766811],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998436,0.000023552477,0.0000074046366,0.000030472946,0.00007557037,0.000019400974],"domain_scores_gemma":[0.9996941,0.00016304193,0.00005758547,0.000028141621,0.00004529463,0.000011920619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004025326,0.0004726654,0.0004651288,0.00029175894,0.0002616704,0.00047660628,0.0006966903,0.0010162982,0.0007654319],"category_scores_gemma":[0.00066652254,0.0003438701,0.0005139239,0.00018614091,0.00032753372,0.00042940985,0.00034129506,0.0005702029,0.00020431571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003847507,0.000041627147,0.001572521,0.000028066965,0.0000059128542,0.000061926396,0.000030912255,0.97369295,0.011383633,0.0006773705,0.0000842689,0.012382386],"study_design_scores_gemma":[0.0000017121645,0.000014188719,0.00034014758,9.1858897e-7,6.980729e-7,0.000006504773,0.0000028042928,0.9987513,0.0007443754,0.00009358073,0.0000419893,0.0000018099693],"about_ca_topic_score_codex":0.0048381053,"about_ca_topic_score_gemma":0.004287752,"teacher_disagreement_score":0.0048381053,"about_ca_system_score_codex":0.0002843143,"about_ca_system_score_gemma":0.0004639514,"threshold_uncertainty_score":0.009619892},"labels":[],"label_agreement":null},{"id":"W6958073050","doi":"10.60692/n00rg-rbe20","title":"Cutting force prediction for ball-end mills with non-horizontal and rotational cutting motions","year":2012,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Machining; Cutting tool; Process (computing); Chip; Work (physics); Rotational speed; Finite element method; Chip formation","score_opus":0.010624050718005306,"score_gpt":0.18930048268670824,"score_spread":0.17867643196870292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958073050","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30267012,0.00019454297,0.693855,0.00005389491,0.000014775671,0.000060389724,0.00007129356,0.00023558036,0.0028443735],"genre_scores_gemma":[0.9709387,0.000087296554,0.027465818,0.000008467783,0.0000031696914,0.000035057772,0.00006735482,0.000017561508,0.0013766811],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998436,0.000023552477,0.0000074046366,0.000030472946,0.00007557037,0.000019400974],"domain_scores_gemma":[0.9996941,0.00016304193,0.00005758547,0.000028141621,0.00004529463,0.000011920619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004025326,0.0004726654,0.0004651288,0.00029175894,0.0002616704,0.00047660628,0.0006966903,0.0010162982,0.0007654319],"category_scores_gemma":[0.00066652254,0.0003438701,0.0005139239,0.00018614091,0.00032753372,0.00042940985,0.00034129506,0.0005702029,0.00020431571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003847507,0.000041627147,0.001572521,0.000028066965,0.0000059128542,0.000061926396,0.000030912255,0.97369295,0.011383633,0.0006773705,0.0000842689,0.012382386],"study_design_scores_gemma":[0.0000017121645,0.000014188719,0.00034014758,9.1858897e-7,6.980729e-7,0.000006504773,0.0000028042928,0.9987513,0.0007443754,0.00009358073,0.0000419893,0.0000018099693],"about_ca_topic_score_codex":0.0048381053,"about_ca_topic_score_gemma":0.004287752,"teacher_disagreement_score":0.0048381053,"about_ca_system_score_codex":0.0002843143,"about_ca_system_score_gemma":0.0004639514,"threshold_uncertainty_score":0.009619892},"labels":[],"label_agreement":null},{"id":"W6958151763","doi":"10.60770/p4kx-yh54","title":"The constitutionality of mandatory alcohol screening in Canada","year":2024,"lang":"en","type":"article","venue":"Mount Royal University Institutional Repository (Mount Royal University)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Mount Royal University","funders":"","keywords":"Constitutionality; Charter; Supreme court; Criminal code; Argument (complex analysis); Duty; Legislation; Warrant; Bill of rights","score_opus":0.005236099919330389,"score_gpt":0.1649539034678153,"score_spread":0.15971780354848492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958151763","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13921875,0.0055930396,0.004850196,0.069968894,0.0011594734,0.00047941535,0.0037877995,0.0003694086,0.774573],"genre_scores_gemma":[0.8864979,0.0025247023,0.0035651238,0.03676929,0.00027947864,0.00022374526,0.0007195511,0.000078378245,0.06934174],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.980685,0.0011174759,0.0006369321,0.0022264943,0.00820375,0.007130444],"domain_scores_gemma":[0.98572516,0.0030657023,0.0006719429,0.00082226127,0.0069346614,0.0027802484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005352872,0.00049669266,0.0007265748,0.0023657728,0.016945627,0.009640874,0.0032686717,0.0058664205,0.007475198],"category_scores_gemma":[0.01703626,0.0013395477,0.0010295023,0.0024724985,0.008177148,0.0016959711,0.0035085632,0.006140911,0.0005550015],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015557666,0.00007767227,0.008669111,0.0002074853,0.00009035741,0.0008738815,0.0033755489,0.0026873304,0.002086838,0.8831533,0.078007,0.020615777],"study_design_scores_gemma":[0.00036176544,0.00024607521,0.074275196,0.0015633709,0.0006562763,0.0005732322,0.0057143695,0.008265284,0.004911316,0.12066136,0.7817217,0.0010498848],"about_ca_topic_score_codex":0.990849,"about_ca_topic_score_gemma":0.9943131,"teacher_disagreement_score":0.13269481,"about_ca_system_score_codex":0.13269481,"about_ca_system_score_gemma":0.2233709,"threshold_uncertainty_score":0.9627727},"labels":[],"label_agreement":null},{"id":"W6958242211","doi":"10.6084/m9.figshare.22662488.v1","title":"Additional file 1 of Functional gradients of the medial parietal cortex in a healthy cohort with family history of sporadic Alzheimer’s disease","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Family history; Cohort; Disease; Parietal lobe; Cortex (anatomy); Cohort study","score_opus":0.0245949109224909,"score_gpt":0.21015584967691706,"score_spread":0.18556093875442614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958242211","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00082496717,0.000028961154,0.00037427552,0.00008253012,0.00001669661,0.000090882575,0.9975943,0.00018568072,0.00080169446],"genre_scores_gemma":[0.032081455,0.00019484707,0.005020061,0.00056997396,0.00015243312,0.003640077,0.94712365,0.00077486597,0.01044262],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9995395,0.00007024902,0.0000896106,0.00014973784,0.00009054256,0.000060433824],"domain_scores_gemma":[0.9863187,0.009851952,0.0009602192,0.0011284997,0.0014290437,0.0003114977],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001088945,0.0010824106,0.0011215487,0.0017081001,0.0009086897,0.0012446695,0.0014990226,0.0011627311,0.7852781],"category_scores_gemma":[0.02647718,0.00042184285,0.0007533722,0.0021980205,0.00024026964,0.001099077,0.0007515752,0.00074941356,0.07786316],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008777112,0.00018401862,0.0118490625,0.002111787,0.0001402757,0.00027997527,0.00011253232,0.0004912574,0.00024175577,0.0008363083,0.96765566,0.015219469],"study_design_scores_gemma":[0.017185107,0.0011522453,0.24505624,0.0062712217,0.0010398239,0.0069453544,0.0010587042,0.0055817175,0.002728473,0.032099072,0.68039566,0.0004864207],"about_ca_topic_score_codex":0.0059741084,"about_ca_topic_score_gemma":0.011208805,"teacher_disagreement_score":0.7852781,"about_ca_system_score_codex":0.0006747356,"about_ca_system_score_gemma":0.0010621677,"threshold_uncertainty_score":0.3062747},"labels":[],"label_agreement":null},{"id":"W6965293411","doi":"10.3389/fneur.2025.1510284.s001","title":"Table 1_Cerebrolysin as an adjuvant therapy after mechanical thrombectomy in large vessel occlusion cardioembolic stroke: a propensity score matching analysis.docx","year":2025,"lang":"en","type":"dataset","venue":"Figshare","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cerebrolysin; Modified Rankin Scale; Propensity score matching; Tissue plasminogen activator; Adverse effect; Stroke (engine); Occlusion; Plasminogen activator","score_opus":0.01664987493861445,"score_gpt":0.2656004256904031,"score_spread":0.24895055075178865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6965293411","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3723578,0.0026665924,0.017360322,0.0011320659,0.0006826371,0.0049104006,0.59108216,0.001003782,0.008804279],"genre_scores_gemma":[0.758504,0.0016372257,0.015096743,0.0010671183,0.0006227663,0.010045913,0.18390758,0.0006387209,0.028480023],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998796,0.0003406033,0.00021892006,0.0002564375,0.00026449974,0.00012355874],"domain_scores_gemma":[0.99535626,0.003277769,0.0006522008,0.0003208431,0.0002624971,0.00013033247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025232513,0.00051610207,0.0012972363,0.0020832068,0.000310988,0.00077153655,0.0007477447,0.00045521845,0.11221284],"category_scores_gemma":[0.011230267,0.00026166937,0.0012345957,0.0026214698,0.00017843253,0.0005408809,0.0003485064,0.0007022986,0.004926705],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.018347533,0.0010210901,0.6254363,0.0047003143,0.007121284,0.0009444223,0.00014459463,0.0044340617,0.0024105506,0.0014987295,0.22737361,0.10656747],"study_design_scores_gemma":[0.0054266104,0.0033116112,0.8960234,0.0005451175,0.0024761227,0.001386446,0.0002789014,0.019373242,0.0019102269,0.0021204236,0.067050315,0.000097627984],"about_ca_topic_score_codex":0.001522418,"about_ca_topic_score_gemma":0.0014149527,"teacher_disagreement_score":0.11221284,"about_ca_system_score_codex":0.00031131844,"about_ca_system_score_gemma":0.000669718,"threshold_uncertainty_score":0.37538934},"labels":[],"label_agreement":null},{"id":"W6976576500","doi":"10.60692/2k21q-s5518","title":"Experimental Investigation on Machinability of Polypropylene Reinforced with Miscanthus Fibers and Biochar","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; École de Technologie Supérieure","funders":"","keywords":"Machinability; Drill bit; Machining; Drilling; Drill; Polypropylene; Biocomposite; Factorial experiment; Fiber","score_opus":0.018654273526510598,"score_gpt":0.1858999957955418,"score_spread":0.16724572226903123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976576500","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987954,0.00009825342,0.0007959715,0.0000048129255,0.0000026072069,0.000016174296,0.000045455858,0.000006981201,0.00023430034],"genre_scores_gemma":[0.9962297,0.00014188068,0.0030410257,0.0000071912564,0.000003246854,0.000019656623,0.000062771156,0.000007975466,0.00048650702],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996593,0.00005494291,0.00003903574,0.00007179361,0.00012042733,0.000054434866],"domain_scores_gemma":[0.99915767,0.00042658695,0.00018161155,0.00008163024,0.00011562807,0.000036842262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046797373,0.00038751066,0.0003190895,0.00025403794,0.00022208472,0.00019089323,0.00027810174,0.00035907602,0.00072731957],"category_scores_gemma":[0.0006133716,0.00019313488,0.00030420875,0.0002087893,0.00026558278,0.00031730847,0.00019594691,0.00037948674,0.000112070375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024015317,0.00010506754,0.00053793215,0.000077533514,0.0000059236004,0.00003365589,0.000059277903,0.00044049794,0.99726355,0.000014553715,0.0000063403545,0.0012155251],"study_design_scores_gemma":[0.000014180421,0.0029003378,0.0051746434,0.000004196056,0.00001406654,0.000047110607,0.000043724867,0.0011102158,0.9904778,0.000010824357,0.00019645077,0.0000065110016],"about_ca_topic_score_codex":0.0004358391,"about_ca_topic_score_gemma":0.0010174138,"teacher_disagreement_score":0.00072731957,"about_ca_system_score_codex":0.00016509189,"about_ca_system_score_gemma":0.0000912482,"threshold_uncertainty_score":0.002474904},"labels":[],"label_agreement":null},{"id":"W6976763408","doi":"10.60692/rk606-1bf46","title":"Experimental Investigation on Machinability of Polypropylene Reinforced with Miscanthus Fibers and Biochar","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph; École de Technologie Supérieure","funders":"","keywords":"Machinability; Drill bit; Machining; Drilling; Drill; Polypropylene; Biocomposite; Factorial experiment; Fiber","score_opus":0.018654273526510598,"score_gpt":0.1858999957955418,"score_spread":0.16724572226903123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976763408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987954,0.00009825342,0.0007959715,0.0000048129255,0.0000026072069,0.000016174296,0.000045455858,0.000006981201,0.00023430034],"genre_scores_gemma":[0.9962297,0.00014188068,0.0030410257,0.0000071912564,0.000003246854,0.000019656623,0.000062771156,0.000007975466,0.00048650702],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996593,0.00005494291,0.00003903574,0.00007179361,0.00012042733,0.000054434866],"domain_scores_gemma":[0.99915767,0.00042658695,0.00018161155,0.00008163024,0.00011562807,0.000036842262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046797373,0.00038751066,0.0003190895,0.00025403794,0.00022208472,0.00019089323,0.00027810174,0.00035907602,0.00072731957],"category_scores_gemma":[0.0006133716,0.00019313488,0.00030420875,0.0002087893,0.00026558278,0.00031730847,0.00019594691,0.00037948674,0.000112070375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024015317,0.00010506754,0.00053793215,0.000077533514,0.0000059236004,0.00003365589,0.000059277903,0.00044049794,0.99726355,0.000014553715,0.0000063403545,0.0012155251],"study_design_scores_gemma":[0.000014180421,0.0029003378,0.0051746434,0.000004196056,0.00001406654,0.000047110607,0.000043724867,0.0011102158,0.9904778,0.000010824357,0.00019645077,0.0000065110016],"about_ca_topic_score_codex":0.0004358391,"about_ca_topic_score_gemma":0.0010174138,"teacher_disagreement_score":0.00072731957,"about_ca_system_score_codex":0.00016509189,"about_ca_system_score_gemma":0.0000912482,"threshold_uncertainty_score":0.002474904},"labels":[],"label_agreement":null},{"id":"W6981459885","doi":"","title":"Elite Container Homes: Revolutionizing Sustainable Housing Solutions – US and Canada Report","year":2024,"lang":"en","type":"other","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Elite; Container (type theory); Government (linguistics); Sustainability; Sustainable development","score_opus":0.004946542926410482,"score_gpt":0.20272803827416708,"score_spread":0.1977814953477566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6981459885","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026763111,0.008528947,0.0059994906,0.054735575,0.00326371,0.00049659534,0.045675736,0.0014995988,0.85303724],"genre_scores_gemma":[0.06630867,0.010183321,0.007550921,0.0038914245,0.00022436416,0.000107560074,0.018262256,0.00043423753,0.89303726],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978726,0.000048426373,0.000018319592,0.000057136447,0.0015249135,0.0004786066],"domain_scores_gemma":[0.9976381,0.000050785726,0.000032878474,0.000050634066,0.001692287,0.00053533376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016220479,0.0007992454,0.0002279809,0.0012024741,0.0034947016,0.004550239,0.0016024406,0.0020420416,0.034684107],"category_scores_gemma":[0.0017312643,0.00038870276,0.00055658177,0.002498965,0.0011212806,0.001389274,0.0020539204,0.0018089216,0.0045698173],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050603703,0.00008997526,0.0017111684,0.000069326015,0.000011885114,0.00005301119,0.00010292308,0.00085445115,0.00038328773,0.010880961,0.9414,0.044392448],"study_design_scores_gemma":[0.00003371792,0.000028291759,0.011244035,0.00009546248,0.000018197261,0.0000253701,0.00086504116,0.0015509512,0.00094603084,0.0012044649,0.98396194,0.000026524069],"about_ca_topic_score_codex":0.98203504,"about_ca_topic_score_gemma":0.9938903,"teacher_disagreement_score":0.034684107,"about_ca_system_score_codex":0.027890991,"about_ca_system_score_gemma":0.1197966,"threshold_uncertainty_score":0.20236427},"labels":[],"label_agreement":null},{"id":"W6981572303","doi":"","title":"Episode 0 - 2016 in Review","year":2016,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Politics; Power (physics); Agency (philosophy); Context (archaeology)","score_opus":0.0037425085457638402,"score_gpt":0.1902104409233364,"score_spread":0.18646793237757256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6981572303","genre_codex":"dataset","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006866275,0.23151666,0.0006390933,0.14330557,0.19107327,0.00662675,0.25373676,0.0015021049,0.17091326],"genre_scores_gemma":[0.009158862,0.25963876,0.002148847,0.2512335,0.064931884,0.012964538,0.12805608,0.0016231599,0.27024433],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.98810685,0.0014422493,0.0021708703,0.0007732072,0.0057398193,0.001767005],"domain_scores_gemma":[0.9530106,0.005590888,0.009612745,0.0023180924,0.02093067,0.0085371025],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.011328682,0.0015409038,0.003707151,0.009548304,0.002363649,0.012647985,0.00378898,0.0072736396,0.24131262],"category_scores_gemma":[0.06675133,0.0010563461,0.002695724,0.014125867,0.0011877596,0.007359257,0.009480433,0.00505447,0.08179348],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006502484,0.000007416603,0.00004561789,0.00940183,0.000023691993,0.00002767633,0.000028656024,0.000008355189,0.000031651005,0.0005749013,0.97929674,0.010488509],"study_design_scores_gemma":[0.00010673107,0.00001530272,0.0007216498,0.032625232,0.000053229905,0.00006499083,0.00009060948,0.0000076421975,0.00005789303,0.0004794039,0.9657628,0.0000145385675],"about_ca_topic_score_codex":0.032718904,"about_ca_topic_score_gemma":0.076667294,"teacher_disagreement_score":0.7586874,"about_ca_system_score_codex":0.013169285,"about_ca_system_score_gemma":0.036330145,"threshold_uncertainty_score":0.8072711},"labels":[],"label_agreement":null},{"id":"W6981750029","doi":"","title":"Exploitation of Mineral Resources in Inuit Lands and International Law","year":2022,"lang":"en","type":"book-chapter","venue":"Research Padua  Archive (University of Padua)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"International law; Mineral resource classification; Mineral exploration; Mineral; Work (physics)","score_opus":0.03360524798481185,"score_gpt":0.2631580950167622,"score_spread":0.22955284703195034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6981750029","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054592624,0.007201885,0.00068220514,0.0035967536,0.00011536766,0.000027138041,0.000042195003,0.0000164669,0.9337254],"genre_scores_gemma":[0.7220982,0.006457348,0.00084282923,0.0008788854,0.00010333263,0.000047323116,0.00004184032,0.00003213667,0.26949814],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99968505,0.000057013585,0.000009963874,0.000028718718,0.00007433321,0.00014489976],"domain_scores_gemma":[0.9998927,0.000048827816,0.000012214966,0.000011521821,0.00001748432,0.000017235705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003441978,0.00022784226,0.00019007627,0.0011363751,0.0052648666,0.0059846374,0.0008148739,0.0014078015,0.0069966987],"category_scores_gemma":[0.00064443937,0.00023232172,0.00014500915,0.0019454068,0.004988566,0.0019836181,0.0020512189,0.0017866571,0.00030563757],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008116892,0.00002738461,0.00060104456,0.000045110337,0.000003407301,0.00035161915,0.009342909,0.00016169104,0.00023499563,0.96366274,0.0074428977,0.018118093],"study_design_scores_gemma":[0.000007270468,0.00004210102,0.008126799,0.00047794875,0.000012821071,0.00084076106,0.034620192,0.000803982,0.00086257135,0.15970245,0.79447716,0.000025913703],"about_ca_topic_score_codex":0.073565,"about_ca_topic_score_gemma":0.23462498,"teacher_disagreement_score":0.926435,"about_ca_system_score_codex":0.006321663,"about_ca_system_score_gemma":0.003976026,"threshold_uncertainty_score":0.14627361},"labels":[],"label_agreement":null},{"id":"W6998475987","doi":"","title":"Analytical and experimental study of the effect of cutting tool microgeometry on the impact resistance of milling tools","year":2021,"lang":"en","type":"dissertation","venue":"e-scholar@UOIT (University of Ontario Institute of Technology)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Nucleofection; Gestational period; Diafiltration; TSG101; Articular cartilage damage; Fusible alloy; Liquation; Hemopericardium","score_opus":0.007507329436124142,"score_gpt":0.22929499928758607,"score_spread":0.22178766985146192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6998475987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9870609,0.0004614665,0.010228523,0.000036473735,0.00002313994,0.00006416167,0.000104298146,0.000089744935,0.0019312879],"genre_scores_gemma":[0.99558026,0.00022180556,0.0035835004,0.000012356934,0.0000054520906,0.000012517208,0.0000351434,0.000010855079,0.00053807715],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990656,0.00010719736,0.000053351618,0.00015545002,0.0004991653,0.00011924382],"domain_scores_gemma":[0.99637693,0.0020300755,0.0004382718,0.00042988543,0.0006667063,0.000058167432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008493035,0.00029797948,0.00036772556,0.0003300347,0.0003691588,0.00057151663,0.0005590559,0.0005585901,0.0015397356],"category_scores_gemma":[0.0039137322,0.0002876277,0.00020784962,0.00039738187,0.000565123,0.00050695764,0.00023008097,0.0003352635,0.0003264221],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027603915,0.00012443376,0.0020793912,0.0002349659,0.000013489797,0.00015047142,0.00036561416,0.0025957297,0.9766995,0.00019113271,0.000105750085,0.017163461],"study_design_scores_gemma":[0.000015203977,0.0012908168,0.015901623,0.000017521379,0.000027946078,0.00026858915,0.0003323821,0.010182825,0.9705084,0.00009035405,0.0013279393,0.000036364567],"about_ca_topic_score_codex":0.00048229264,"about_ca_topic_score_gemma":0.0007114479,"teacher_disagreement_score":0.0015397356,"about_ca_system_score_codex":0.00025707972,"about_ca_system_score_gemma":0.00018540828,"threshold_uncertainty_score":0.005150914},"labels":[],"label_agreement":null},{"id":"W7008266105","doi":"","title":"Binder / Lubricants in Green Machining","year":2007,"lang":"en","type":"article","venue":"NPARC","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"","score_opus":0.009162514307907483,"score_gpt":0.23986790237542074,"score_spread":0.23070538806751326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7008266105","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57859117,0.06276983,0.08871455,0.0038238906,0.00400572,0.00047625837,0.00034589783,0.0014664993,0.2598062],"genre_scores_gemma":[0.8624924,0.006700647,0.016930964,0.00017872856,0.00031030521,0.000035682973,0.000102015416,0.00029994868,0.11294936],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989631,0.00018858191,0.00003320757,0.000091831695,0.00061051955,0.000112658854],"domain_scores_gemma":[0.9992268,0.00019107138,0.00009287101,0.000063681015,0.00035352254,0.00007200798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009843052,0.00046710533,0.0008872404,0.0015146825,0.000858126,0.0016431864,0.00066876225,0.0012118414,0.016643142],"category_scores_gemma":[0.0023204873,0.00033472443,0.00027428358,0.0010207673,0.0009039587,0.0012969348,0.0007586715,0.0004349144,0.003633654],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00226808,0.00035609462,0.0034912606,0.0027410928,0.0001581051,0.0016722217,0.00046971685,0.05608935,0.20219812,0.10645966,0.029170852,0.5949254],"study_design_scores_gemma":[0.0002497313,0.0015074557,0.008622925,0.00031014514,0.00026019532,0.0012938955,0.00060243276,0.13519877,0.45864365,0.06864786,0.3244861,0.00017672904],"about_ca_topic_score_codex":0.0015420251,"about_ca_topic_score_gemma":0.002786552,"teacher_disagreement_score":0.016643142,"about_ca_system_score_codex":0.00063223817,"about_ca_system_score_gemma":0.0010872564,"threshold_uncertainty_score":0.055676818},"labels":[],"label_agreement":null},{"id":"W7008601745","doi":"","title":"Characterization of Different Lubrication Approaches to Improve Green Machinability","year":2007,"lang":"en","type":"article","venue":"NPARC","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Machinability; Characterization (materials science); Lubrication; Machining; Extrusion","score_opus":0.020924499009653152,"score_gpt":0.21883063421978463,"score_spread":0.19790613521013148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7008601745","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9846576,0.0014124562,0.011108096,0.000098440956,0.000048595175,0.0001009888,0.00013505909,0.0001920159,0.0022467985],"genre_scores_gemma":[0.9871394,0.00046884277,0.009586744,0.00004459342,0.000009336224,0.000035753998,0.00020602453,0.00008448523,0.0024248112],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994272,0.00007272796,0.000040292867,0.00007286028,0.00030533943,0.00008163941],"domain_scores_gemma":[0.99935466,0.00014817722,0.000062520354,0.00007840627,0.00031434646,0.00004182019],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059256,0.0003592695,0.00066936517,0.0008711196,0.00043330668,0.0006968925,0.0004426003,0.0005635754,0.0022006962],"category_scores_gemma":[0.0015354998,0.00020391226,0.0003608285,0.0006189239,0.00039028804,0.00076335337,0.00034707866,0.00036845665,0.00038493742],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000392641,0.000091304,0.0010339624,0.0002436044,0.000030473511,0.00007076551,0.000109099245,0.00095558236,0.97401863,0.00029124503,0.00019064572,0.022572123],"study_design_scores_gemma":[0.000012618716,0.0003151086,0.0012864672,0.000003297331,0.000028690292,0.00003760024,0.000031804935,0.0019191352,0.99465406,0.000044684955,0.0016605437,0.0000060626153],"about_ca_topic_score_codex":0.000565705,"about_ca_topic_score_gemma":0.0012196625,"teacher_disagreement_score":0.0022006962,"about_ca_system_score_codex":0.00026712855,"about_ca_system_score_gemma":0.00040190265,"threshold_uncertainty_score":0.0073620677},"labels":[],"label_agreement":null},{"id":"W7027047569","doi":"","title":"Caracterización de fases por procesamiento digital de imágenes en un aluminio soldado con gas y tungsteno","year":2024,"lang":"es","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nickel Institute","funders":"","keywords":"Semiconductor materials; Digital signal; Work (physics); Rise time","score_opus":0.08182550590784063,"score_gpt":0.48510673240965635,"score_spread":0.40328122650181575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7027047569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9871552,0.00057683437,0.008505711,0.000043184544,0.000020913752,0.000024543728,0.00022568679,0.00020203575,0.0032459483],"genre_scores_gemma":[0.98014534,0.0006097075,0.011488854,0.000025861818,0.000005923881,0.000034382287,0.00027856574,0.00007889128,0.007332492],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998764,0.000005746942,0.000003533063,0.000034972185,0.000045940797,0.00003342181],"domain_scores_gemma":[0.9998022,0.00005622379,0.000030810625,0.000016420396,0.00007356577,0.000020768652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015750728,0.00043673033,0.00019966703,0.00051968143,0.00023645032,0.00043539415,0.00024495833,0.00035307521,0.005488442],"category_scores_gemma":[0.0002799832,0.00030295318,0.00035539662,0.00041568058,0.0003862331,0.00043559613,0.00022447373,0.0003868354,0.00055733504],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013241301,0.000017015314,0.0011943021,0.00010100887,0.0000071580566,0.00012206408,0.00014887327,0.00063799345,0.99204856,0.00016383774,0.00006753243,0.0053591463],"study_design_scores_gemma":[0.000005468355,0.00013958615,0.0064162374,0.000008808068,0.0000125814095,0.00009463905,0.00023798132,0.0020796768,0.9891971,0.000072079,0.0017270666,0.000008788434],"about_ca_topic_score_codex":0.0019732898,"about_ca_topic_score_gemma":0.0022434955,"teacher_disagreement_score":0.005488442,"about_ca_system_score_codex":0.00032334708,"about_ca_system_score_gemma":0.00016282007,"threshold_uncertainty_score":0.018360734},"labels":[],"label_agreement":null},{"id":"W7032582164","doi":"","title":"Ekofickan","year":2020,"lang":"en","type":"other","venue":"Epsilon Archive for Student Projects (University of Southampton)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Public Safety Research and Treatment","funders":"","keywords":"Nucleofection; TSG101; Gestational period; Diafiltration; Hyporeflexia; Dysgeusia; Articular cartilage damage","score_opus":0.011071572846130237,"score_gpt":0.21529976810752655,"score_spread":0.2042281952613963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7032582164","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031473148,0.018516533,0.0016768622,0.0056875516,0.0030039363,0.000066592,0.0031509306,0.00054790406,0.9642024],"genre_scores_gemma":[0.009381859,0.011051437,0.0011660194,0.00070687116,0.00014183836,0.00005229824,0.0013528138,0.00040643773,0.9757405],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992285,0.00007142852,0.000060483384,0.00025005484,0.00026122032,0.00012824987],"domain_scores_gemma":[0.999464,0.00012362486,0.000066698754,0.00009907179,0.000144301,0.000102371385],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005201636,0.0014131328,0.00082166336,0.0018466867,0.0024066486,0.0074754525,0.0011833328,0.0023968655,0.5157802],"category_scores_gemma":[0.0018026205,0.0004596681,0.00051538186,0.002182543,0.0010746951,0.0044508404,0.004625266,0.0025387527,0.39062127],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025755877,0.00013480503,0.0014148533,0.001143108,0.000024445877,0.0010790785,0.0011116479,0.0004848607,0.0023353489,0.08576445,0.36729002,0.5389598],"study_design_scores_gemma":[0.000004929274,0.000009824285,0.00036319313,0.00019604567,0.0000033792696,0.0002546296,0.000203788,0.00004468025,0.00029097113,0.002653181,0.9959693,0.000006101463],"about_ca_topic_score_codex":0.0053740996,"about_ca_topic_score_gemma":0.008210839,"teacher_disagreement_score":0.4842198,"about_ca_system_score_codex":0.0018950665,"about_ca_system_score_gemma":0.0027350713,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W7034147757","doi":"","title":"Spring Hill United Methodist Church, Berkeley County","year":2014,"lang":"en","type":"article","venue":"Digital Commons - Wofford College (Wofford College)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Spring (device); Acre; New england; George (robot); Quarter (Canadian coin)","score_opus":0.010519372941570548,"score_gpt":0.2248445947216827,"score_spread":0.21432522178011215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7034147757","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037414087,0.004992869,0.00032813073,0.0053523076,0.0013895724,0.000053759926,0.0048034317,0.0003248827,0.97901374],"genre_scores_gemma":[0.0062385155,0.0013538846,0.00048033718,0.0002737858,0.00008457966,0.00002436447,0.0007992049,0.000120978475,0.99062437],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99966455,0.00002333385,0.000009647867,0.000077044424,0.00016191528,0.000063474996],"domain_scores_gemma":[0.9996024,0.000036554706,0.00002054593,0.00004525757,0.00014524846,0.00015002643],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00034650706,0.0004181636,0.00021131821,0.00069901935,0.004829039,0.0035332462,0.0007527192,0.0008350103,0.38972718],"category_scores_gemma":[0.00085925224,0.00048369964,0.00014896215,0.00097636535,0.0005587025,0.0010933747,0.0015396484,0.0020632157,0.062075537],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004239632,0.00004728948,0.0009104691,0.00007202922,0.000003617319,0.00013609715,0.0003904615,0.00005477395,0.00024405846,0.010750644,0.9115705,0.075777754],"study_design_scores_gemma":[0.0000042879005,0.0000031978886,0.0017791017,0.00003782246,9.749681e-7,0.000019800636,0.0002112668,0.000011728948,0.00004076628,0.0001960491,0.9976922,0.0000027580147],"about_ca_topic_score_codex":0.075352,"about_ca_topic_score_gemma":0.34922847,"teacher_disagreement_score":0.38972718,"about_ca_system_score_codex":0.0022707938,"about_ca_system_score_gemma":0.005017361,"threshold_uncertainty_score":0.8704801},"labels":[],"label_agreement":null},{"id":"W7066363735","doi":"","title":"Identification of the material constitutive equation for simulation of the metal cutting process","year":2008,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Machining; Finite element method; Process (computing); Heat transfer; Constitutive equation; Thermal; Cutting tool; Tribology; Identification (biology)","score_opus":0.016064019479018837,"score_gpt":0.2597233668521536,"score_spread":0.24365934737313474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7066363735","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010162598,0.0002462307,0.9741639,0.00023628636,0.0001355474,0.0001265615,0.00018958641,0.00023357452,0.01450565],"genre_scores_gemma":[0.3226882,0.0012121879,0.64993656,0.00024185519,0.00014238179,0.0012405787,0.0008279008,0.0004295383,0.02328084],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974316,0.000055236433,0.000013263902,0.00003129063,0.0001361611,0.000020940966],"domain_scores_gemma":[0.9997354,0.000118159885,0.000027617674,0.000030376255,0.00007686596,0.000011462757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065281213,0.00064995897,0.0006428766,0.00053776155,0.00044339825,0.00074296794,0.00095725013,0.0014348378,0.0034408348],"category_scores_gemma":[0.0017594545,0.00049339357,0.0006666321,0.0004909629,0.00035737193,0.00087727304,0.00049099704,0.0012088254,0.0015040804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017071745,0.000067648834,0.00063993956,0.00011497647,0.000014563045,0.00012527777,0.00010113212,0.87809175,0.011683255,0.08074189,0.0017813944,0.026621046],"study_design_scores_gemma":[0.0000045286088,0.000005997567,0.00007899567,0.000009460032,0.000002752181,0.000021196995,0.000008852467,0.99238163,0.0007285196,0.002728876,0.0040247277,0.0000044537205],"about_ca_topic_score_codex":0.0031076253,"about_ca_topic_score_gemma":0.0026050715,"teacher_disagreement_score":0.0034408348,"about_ca_system_score_codex":0.00058968324,"about_ca_system_score_gemma":0.001632865,"threshold_uncertainty_score":0.01151073},"labels":[],"label_agreement":null},{"id":"W7084121263","doi":"10.64628/aap.rv6grnv5e","title":"Comment votre microbiome contrôle votre vie","year":2019,"lang":"fr","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"","score_opus":0.004401075920123224,"score_gpt":0.21046660825798907,"score_spread":0.20606553233786584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7084121263","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020519137,0.04187064,0.01299949,0.74680173,0.08688984,0.00003700841,0.00044326016,0.0003426943,0.090096295],"genre_scores_gemma":[0.32656655,0.03544856,0.011679008,0.39187646,0.03931092,0.00017513841,0.00079270033,0.0007077747,0.19344285],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9947253,0.0014014066,0.00019311515,0.0010975885,0.0019979586,0.0005845437],"domain_scores_gemma":[0.99386346,0.002278442,0.00074997946,0.00072923175,0.0018815254,0.0004974181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004601882,0.000579901,0.0006602514,0.00044260581,0.0018264472,0.004063334,0.00091335096,0.006178237,0.015116565],"category_scores_gemma":[0.018429397,0.00022207943,0.0006623808,0.0004952439,0.0035786442,0.004009303,0.0023648716,0.007818655,0.0055942764],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008816095,0.00017300852,0.00507942,0.0022370964,0.00022142238,0.0016111495,0.0033557278,0.0017772743,0.055991184,0.2735786,0.4805062,0.17458726],"study_design_scores_gemma":[0.000025133704,0.00012224326,0.0014902315,0.00028812513,0.000022156866,0.0004721398,0.00081546436,0.00019227623,0.005441816,0.014639984,0.9764515,0.000039006252],"about_ca_topic_score_codex":0.004583962,"about_ca_topic_score_gemma":0.005411628,"teacher_disagreement_score":0.015116565,"about_ca_system_score_codex":0.0019682755,"about_ca_system_score_gemma":0.0022768886,"threshold_uncertainty_score":0.05056995},"labels":[],"label_agreement":null},{"id":"W7100405000","doi":"","title":"Reaching one’s potential: A discussion of individual human rights and people with developmental disabilities","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Human rights; Obligation; Perspective (graphical); Social model of disability; Fundamental rights; Variety (cybernetics); Medical model of disability; Inclusion (mineral)","score_opus":0.008434288491187311,"score_gpt":0.2120862882348004,"score_spread":0.2036519997436131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7100405000","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00076736684,0.032635644,0.00015290243,0.9130276,0.034217745,0.000013639006,0.000018324134,0.000008182197,0.019158695],"genre_scores_gemma":[0.049276598,0.04637198,0.00049949373,0.7786745,0.083655305,0.00010453974,0.000023168626,0.000059636564,0.04133491],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9931339,0.00322936,0.00029330907,0.000616415,0.0015513416,0.0011756489],"domain_scores_gemma":[0.98835063,0.009037214,0.00030975643,0.00013141315,0.0009814258,0.001189545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00901275,0.0011677331,0.0013705408,0.001472561,0.020416476,0.015417195,0.005523633,0.026213616,0.005802802],"category_scores_gemma":[0.014499723,0.00051894883,0.0011029263,0.0019492584,0.02668199,0.017004523,0.0057475865,0.031167205,0.000880116],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014105221,0.000028742506,0.00017802237,0.0003272344,0.000009299548,0.0007820251,0.0332995,0.000060172893,0.00004955317,0.12848076,0.82308286,0.013687728],"study_design_scores_gemma":[0.000009971311,0.000013868612,0.0004713222,0.0007966953,0.000008873771,0.0003586374,0.020176692,0.000054410968,0.000036965615,0.011179243,0.9668719,0.000021327973],"about_ca_topic_score_codex":0.08509757,"about_ca_topic_score_gemma":0.15124483,"teacher_disagreement_score":0.08509757,"about_ca_system_score_codex":0.018116012,"about_ca_system_score_gemma":0.024554778,"threshold_uncertainty_score":0.16920453},"labels":[],"label_agreement":null},{"id":"W7108073982","doi":"10.1139/tcsme-2024-0223","title":"Prediction method of residual stress and deformation in belt grinding of thin-walled ring workpieces","year":2025,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Chang'an University","keywords":"Residual stress; Finite element method; Deformation (meteorology); Rigidity (electromagnetism); Residual; Machining; Nonlinear system","score_opus":0.00770823309755963,"score_gpt":0.2231208724713476,"score_spread":0.21541263937378796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7108073982","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24815087,0.00019272725,0.75018704,0.00008258149,0.000015743588,0.000028150418,0.0000476675,0.0006650805,0.0006302155],"genre_scores_gemma":[0.973678,0.00011658623,0.025397422,0.000013278785,0.000005836615,0.0000275818,0.00006698202,0.00002797989,0.0006662671],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973875,0.000031606574,0.000017526047,0.00008264902,0.00010628003,0.000023106624],"domain_scores_gemma":[0.9995882,0.0001622298,0.0000759274,0.000045105433,0.00010865335,0.000019897227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005563911,0.0005630997,0.00054024404,0.00041147217,0.00019700236,0.00036187266,0.00074785406,0.00065818947,0.00053858256],"category_scores_gemma":[0.0011205737,0.00039050035,0.000627218,0.00023311851,0.0003259867,0.00063860934,0.00025618734,0.00049106753,0.0001641972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000095005984,0.000050136452,0.003670798,0.000059904265,0.000025614056,0.00007924644,0.00008199907,0.9223081,0.02262801,0.0005123415,0.00018821002,0.05030069],"study_design_scores_gemma":[0.0000019936344,0.000016842874,0.00056689954,0.0000013754719,0.0000023439486,0.000005152462,0.0000029086937,0.99758255,0.0017343394,0.000056191388,0.000025327156,0.0000040731506],"about_ca_topic_score_codex":0.0071497075,"about_ca_topic_score_gemma":0.0037295015,"teacher_disagreement_score":0.0071497075,"about_ca_system_score_codex":0.00034180173,"about_ca_system_score_gemma":0.0005907693,"threshold_uncertainty_score":0.014216185},"labels":[],"label_agreement":null},{"id":"W7127912923","doi":"10.5281/zenodo.18496030","title":"Study on the Effect of Cutting Fluids on Machining Performance in Milling Operations.","year":2015,"lang":"en","type":"article","venue":"Open MIND","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"Lubrication; Machining; Cutting fluid; Surface roughness; Surface finish; Tribology; Metalworking; Tool wear","score_opus":0.037880950388026184,"score_gpt":0.30765026834452747,"score_spread":0.2697693179565013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7127912923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99119544,0.0026110194,0.005083912,0.00003322638,0.000016331413,0.000024908843,0.000087275104,0.00004525088,0.00090276514],"genre_scores_gemma":[0.9946291,0.0006674404,0.0036837212,0.000017432114,0.000006787946,0.0000076215283,0.0001265894,0.000017341681,0.0008439422],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996996,0.000041842683,0.000019098712,0.00004510633,0.0001626386,0.00003176718],"domain_scores_gemma":[0.9990532,0.00050995423,0.00015425927,0.00004550407,0.00020447007,0.00003258611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003686176,0.0002678263,0.00033757192,0.00026926136,0.00021924922,0.00027362694,0.0002489352,0.00022492642,0.0009137427],"category_scores_gemma":[0.0010563793,0.00009988163,0.00019157154,0.00025826163,0.00014883139,0.00040232792,0.0001532384,0.00028960477,0.0002555246],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005452956,0.00013703218,0.0052018827,0.00038647707,0.000028191058,0.00008087869,0.00013486849,0.0017492437,0.9452433,0.00006735149,0.0001090509,0.04631644],"study_design_scores_gemma":[0.000011359118,0.0024617845,0.029182835,0.00002119226,0.000050284903,0.00022706213,0.00016120997,0.0045761666,0.96042824,0.000068914705,0.0027870757,0.000023905826],"about_ca_topic_score_codex":0.00067749113,"about_ca_topic_score_gemma":0.0009850857,"teacher_disagreement_score":0.0009137427,"about_ca_system_score_codex":0.00016040183,"about_ca_system_score_gemma":0.00018841692,"threshold_uncertainty_score":0.0030567646},"labels":[],"label_agreement":null},{"id":"W7127942406","doi":"10.5281/zenodo.18496029","title":"Study on the Effect of Cutting Fluids on Machining Performance in Milling Operations.","year":2015,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"Lubrication; Machining; Cutting fluid; Surface roughness; Surface finish; Tribology; Metalworking; Tool wear","score_opus":0.03433801785883622,"score_gpt":0.25600956230990635,"score_spread":0.22167154445107012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7127942406","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99023086,0.0028515463,0.0058000227,0.000032818058,0.00001747931,0.000025503483,0.00009125678,0.000051948024,0.0008984986],"genre_scores_gemma":[0.99424547,0.00070277695,0.0039777076,0.000017068434,0.0000074123272,0.000008242555,0.00014195828,0.00002072026,0.0008786174],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99968994,0.00004372251,0.000019353383,0.00004746898,0.00016695925,0.000032619882],"domain_scores_gemma":[0.9990753,0.0005002386,0.00014881519,0.000047450292,0.00019633138,0.0000317887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037837107,0.00027931476,0.00034919716,0.00026638134,0.00021600915,0.0002713866,0.00025164345,0.00022466578,0.000917807],"category_scores_gemma":[0.0010467746,0.00010188183,0.0001927083,0.00025380793,0.0001474724,0.00040031367,0.0001520861,0.00028323615,0.00027339932],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005153445,0.00012439063,0.0042295074,0.00036036386,0.000026983738,0.00007018419,0.0001218991,0.0017065295,0.9489966,0.00006654812,0.000106964544,0.043674584],"study_design_scores_gemma":[0.000011219828,0.002238449,0.02342626,0.000018879666,0.000047983587,0.00021245154,0.00012881895,0.0044316286,0.9666736,0.00006430437,0.00272499,0.000021520456],"about_ca_topic_score_codex":0.0005977121,"about_ca_topic_score_gemma":0.0008362529,"teacher_disagreement_score":0.000917807,"about_ca_system_score_codex":0.00015888417,"about_ca_system_score_gemma":0.00018346347,"threshold_uncertainty_score":0.0030702949},"labels":[],"label_agreement":null},{"id":"W7132056191","doi":"","title":"One-side cutting strategy for ultraprecise single point cutting of v-grooves case 2: constant cutting area","year":2019,"lang":"en","type":"article","venue":"NPARC","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Constant (computer programming); Single point; Cutting tool; Point (geometry); Groove (engineering); Current (fluid)","score_opus":0.024521008541774993,"score_gpt":0.2463879048845031,"score_spread":0.2218668963427281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132056191","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71777797,0.00051287754,0.27548337,0.000067535555,0.000037559457,0.00011872567,0.0000668582,0.0002660289,0.0056691086],"genre_scores_gemma":[0.91765386,0.000101958845,0.08033176,0.00001721634,0.0000041830594,0.00003181747,0.0000472528,0.000023130733,0.0017887707],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997118,0.000014270466,0.000013869055,0.000067198285,0.00014493418,0.00004793262],"domain_scores_gemma":[0.9997527,0.000032282795,0.00007202211,0.000058310707,0.00006670644,0.000017988757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016914992,0.00034327988,0.0004001336,0.00026268474,0.00021489103,0.00039474887,0.0007340627,0.00051651394,0.00089897437],"category_scores_gemma":[0.00024955592,0.00021360468,0.00033884906,0.0001680963,0.00029430346,0.0003152442,0.0003556574,0.00033245844,0.00032044397],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016993965,0.00009194348,0.0020162857,0.00027191004,0.00002819392,0.00038706794,0.00016678502,0.02856511,0.89959025,0.0024188762,0.00030941243,0.06598418],"study_design_scores_gemma":[0.00004028261,0.0020376677,0.0091303345,0.000038652615,0.00004172542,0.0017871092,0.00022870112,0.2824449,0.696619,0.0015379937,0.006030801,0.000062900785],"about_ca_topic_score_codex":0.00063079235,"about_ca_topic_score_gemma":0.0015590659,"teacher_disagreement_score":0.00089897437,"about_ca_system_score_codex":0.0001962717,"about_ca_system_score_gemma":0.00035852139,"threshold_uncertainty_score":0.003007412},"labels":[],"label_agreement":null},{"id":"W7134195870","doi":"10.1109/isrimt67769.2025.11413200","title":"Enhanced 6D pose estimation for complex workpieces via improved cloudAAE network with transformer integration","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Optech (Canada)","funders":"","keywords":"Pose; Transformer; 3D pose estimation; Pattern recognition (psychology)","score_opus":0.0071906700061850305,"score_gpt":0.25405313473968255,"score_spread":0.24686246473349752,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7134195870","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020676145,0.00014731848,0.97494066,0.00008195928,0.00006741234,0.000036564732,0.00017906538,0.0011743794,0.0026964075],"genre_scores_gemma":[0.4282448,0.00029899486,0.5627351,0.00017492077,0.00004464963,0.00012998041,0.0010842849,0.000246148,0.0070411274],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995459,0.00004895073,0.000013887107,0.00007133594,0.0002725133,0.00004730958],"domain_scores_gemma":[0.999676,0.00006185736,0.00003162301,0.000057682977,0.00015519396,0.000017710703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037914142,0.00069022994,0.00061838503,0.0007291968,0.00033699954,0.00061122526,0.00090756215,0.0004923107,0.006283932],"category_scores_gemma":[0.0010108665,0.00040149977,0.00037123536,0.0010132949,0.00019716039,0.0018458114,0.0012806235,0.0005929509,0.0018095106],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064573856,0.00023088008,0.003836803,0.00017718236,0.00008128881,0.00017545714,0.00014898865,0.13090347,0.11251232,0.0055676205,0.0075606024,0.73815966],"study_design_scores_gemma":[0.00001951988,0.0000682357,0.0017582645,0.000012673152,0.000020076666,0.00014368269,0.000040519066,0.953882,0.0366122,0.0013904461,0.0060262554,0.000026212345],"about_ca_topic_score_codex":0.003597706,"about_ca_topic_score_gemma":0.009003676,"teacher_disagreement_score":0.006283932,"about_ca_system_score_codex":0.0003510661,"about_ca_system_score_gemma":0.00072968163,"threshold_uncertainty_score":0.021021843},"labels":[],"label_agreement":null},{"id":"W7134937540","doi":"10.5281/zenodo.18955838","title":"Multi objective Optimization of CNC Turning Parameters for AA2024/SiC MMC's using Grey Relational Analysis","year":2020,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bow Valley College","funders":"","keywords":"Grey relational analysis; Multi-objective optimization; Machining; Surface roughness; Process (computing); Taguchi methods; Aluminium; Orthogonal array; Process variable","score_opus":0.056961384270323635,"score_gpt":0.26447294505330304,"score_spread":0.20751156078297942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7134937540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7063328,0.000917014,0.28207985,0.00011969901,0.000024999848,0.00011727193,0.00014219328,0.00016222389,0.010103941],"genre_scores_gemma":[0.9571279,0.00014843227,0.041804876,0.000013655826,0.0000025673442,0.000045617417,0.000061056475,0.00001885865,0.00077685766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978715,0.00004500955,0.000009787037,0.00003839297,0.00009037398,0.000029357627],"domain_scores_gemma":[0.9997843,0.00011382385,0.00003453745,0.0000084398425,0.00004998546,0.000008976183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006705854,0.00070683524,0.0005339093,0.00077340996,0.00026029808,0.0007340967,0.00032843393,0.0005771913,0.0007037843],"category_scores_gemma":[0.0005759831,0.00026079864,0.00066909887,0.0005457581,0.00024741705,0.00028817175,0.0002451831,0.00032524538,0.00009824825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009076175,0.00006212382,0.00081569824,0.0001581745,0.000040523555,0.00007794585,0.00004527905,0.94127965,0.037439283,0.0010472859,0.00014659965,0.01879671],"study_design_scores_gemma":[0.0000062798695,0.00014013579,0.0011453634,0.000006766602,0.000022554093,0.000017999515,0.000029783074,0.987313,0.010556635,0.00045710144,0.00029552498,0.000008829681],"about_ca_topic_score_codex":0.0034866633,"about_ca_topic_score_gemma":0.0052685137,"teacher_disagreement_score":0.0034866633,"about_ca_system_score_codex":0.0005992402,"about_ca_system_score_gemma":0.00053405185,"threshold_uncertainty_score":0.0069327354},"labels":[],"label_agreement":null},{"id":"W7134977799","doi":"10.5281/zenodo.18955837","title":"Multi objective Optimization of CNC Turning Parameters for AA2024/SiC MMC's using Grey Relational Analysis","year":2020,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bow Valley College","funders":"","keywords":"Grey relational analysis; Multi-objective optimization; Machining; Surface roughness; Process (computing); Taguchi methods; Aluminium; Orthogonal array; Process variable","score_opus":0.056961384270323635,"score_gpt":0.26447294505330304,"score_spread":0.20751156078297942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7134977799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7063328,0.000917014,0.28207985,0.00011969901,0.000024999848,0.00011727193,0.00014219328,0.00016222389,0.010103941],"genre_scores_gemma":[0.9571279,0.00014843227,0.041804876,0.000013655826,0.0000025673442,0.000045617417,0.000061056475,0.00001885865,0.00077685766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978715,0.00004500955,0.000009787037,0.00003839297,0.00009037398,0.000029357627],"domain_scores_gemma":[0.9997843,0.00011382385,0.00003453745,0.0000084398425,0.00004998546,0.000008976183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006705854,0.00070683524,0.0005339093,0.00077340996,0.00026029808,0.0007340967,0.00032843393,0.0005771913,0.0007037843],"category_scores_gemma":[0.0005759831,0.00026079864,0.00066909887,0.0005457581,0.00024741705,0.00028817175,0.0002451831,0.00032524538,0.00009824825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009076175,0.00006212382,0.00081569824,0.0001581745,0.000040523555,0.00007794585,0.00004527905,0.94127965,0.037439283,0.0010472859,0.00014659965,0.01879671],"study_design_scores_gemma":[0.0000062798695,0.00014013579,0.0011453634,0.000006766602,0.000022554093,0.000017999515,0.000029783074,0.987313,0.010556635,0.00045710144,0.00029552498,0.000008829681],"about_ca_topic_score_codex":0.0034866633,"about_ca_topic_score_gemma":0.0052685137,"teacher_disagreement_score":0.0034866633,"about_ca_system_score_codex":0.0005992402,"about_ca_system_score_gemma":0.00053405185,"threshold_uncertainty_score":0.0069327354},"labels":[],"label_agreement":null},{"id":"W808809506","doi":"10.1007/s00170-015-7461-z","title":"Automatic identification of feed marks in machined surface roughness profiles by correlating random variations","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Polytechnique Montréal","keywords":"Superposition principle; Identification (biology); Surface finish; Surface roughness; Process (computing); Surface (topology); Component (thermodynamics); Range (aeronautics); Texture (cosmology); Artificial intelligence; Quality (philosophy); Computer science; Engineering drawing; Engineering; Pattern recognition (psychology); Mathematics; Geometry; Mechanical engineering; Materials science; Mathematical analysis; Image (mathematics); Physics","score_opus":0.005805723982748665,"score_gpt":0.24107590902423653,"score_spread":0.23527018504148786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W808809506","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5958032,0.00040159564,0.4002572,0.000042215335,0.000057054196,0.00005322856,0.00017425696,0.0019639654,0.0012472584],"genre_scores_gemma":[0.9261298,0.00010769747,0.072706066,0.000018308088,0.000012653229,0.000022989629,0.0002017295,0.00009591481,0.00070486235],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99967873,0.0000449921,0.000011469696,0.00007689702,0.00015320213,0.000034700653],"domain_scores_gemma":[0.9993325,0.0002569408,0.00014812025,0.00007737811,0.00015835145,0.000026793285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029477582,0.00041333286,0.00033723254,0.0010803137,0.00015860869,0.00047636582,0.00034980674,0.00047145,0.00041473377],"category_scores_gemma":[0.0010483444,0.00026132783,0.00022635472,0.0006110598,0.0001948817,0.00043123524,0.00028953768,0.00038579942,0.00033033156],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008596517,0.00017776623,0.016016368,0.00014139766,0.00006403852,0.00017003453,0.00016921469,0.012531404,0.6673958,0.0006633839,0.0007636176,0.3010474],"study_design_scores_gemma":[0.00003534675,0.00036878447,0.080531456,0.00002113741,0.00007585481,0.00049935764,0.00008425889,0.5130265,0.40282762,0.00050985994,0.0019578368,0.000061961095],"about_ca_topic_score_codex":0.00052887393,"about_ca_topic_score_gemma":0.0013543192,"teacher_disagreement_score":0.0010803137,"about_ca_system_score_codex":0.00016789223,"about_ca_system_score_gemma":0.00023891956,"threshold_uncertainty_score":0.0015589595},"labels":[],"label_agreement":null},{"id":"W819105919","doi":"10.15866/ireme.v8i1.1260","title":"On Real Time Prediction of Cutting Forces Using ANN","year":2014,"lang":"en","type":"article","venue":"International Review of Mechanical Engineering (IREME)","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Machining; Artificial neural network; Profitability index; Focus (optics); Computer science; Process (computing); Agile software development; Mechanical engineering; Industrial engineering; Manufacturing engineering; Engineering; Machine learning","score_opus":0.008843206970762026,"score_gpt":0.24906121058054048,"score_spread":0.24021800360977846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W819105919","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28490213,0.0014335185,0.7000695,0.00036602875,0.00017349138,0.00007605488,0.00021023874,0.0015959861,0.011173146],"genre_scores_gemma":[0.94623214,0.00061975594,0.04977515,0.000049082515,0.000034672696,0.00007236742,0.00017755153,0.000034548193,0.0030048385],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998153,0.000055075405,0.000013033724,0.00004195982,0.00005531654,0.000019463392],"domain_scores_gemma":[0.9991841,0.00060663215,0.000054232336,0.00003280961,0.00011224167,0.00001009703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005174769,0.00069086236,0.00040769184,0.0003400544,0.00021087623,0.0006260593,0.00041696744,0.00072359317,0.0011010483],"category_scores_gemma":[0.0017308844,0.0002914634,0.00028296164,0.0004324488,0.00022681164,0.00059569086,0.0002805791,0.0006514924,0.0002626507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005307628,0.000028380333,0.00067239994,0.000036022084,0.000016401422,0.00003711957,0.000011760152,0.96125257,0.0020748691,0.0003715511,0.00022794031,0.035217877],"study_design_scores_gemma":[8.4931065e-7,0.000008446335,0.00012809284,0.000002190517,0.0000013204506,0.000002737718,0.0000013947855,0.999328,0.00037293255,0.00009192614,0.000060694663,0.000001353782],"about_ca_topic_score_codex":0.006334154,"about_ca_topic_score_gemma":0.0048502935,"teacher_disagreement_score":0.006334154,"about_ca_system_score_codex":0.0003117075,"about_ca_system_score_gemma":0.00029574332,"threshold_uncertainty_score":0.012594581},"labels":[],"label_agreement":null},{"id":"W831360126","doi":"10.1177/0954405415590562","title":"Burr formation and correlation with cutting force and acoustic emission signals","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Acoustic emission; SIGNAL (programming language); Machining; Acoustics; Work (physics); Materials science; Mechanical engineering; Engineering; Computer science; Physics","score_opus":0.007593415260273871,"score_gpt":0.19392250409494863,"score_spread":0.18632908883467475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W831360126","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77783525,0.00069819874,0.21924043,0.000024637375,0.000023009168,0.00010778315,0.0002885728,0.0005316608,0.0012504149],"genre_scores_gemma":[0.9585667,0.00021056422,0.040315285,0.000013897794,0.000016280306,0.00007112967,0.00036547365,0.000038840182,0.00040186272],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976534,0.00028207933,0.00015358516,0.0006322816,0.00115535,0.00012329928],"domain_scores_gemma":[0.9919086,0.004447257,0.0018569104,0.00047708052,0.0011982507,0.00011177199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023801746,0.00071563706,0.0005298177,0.0018009561,0.00014904284,0.00062836194,0.0004360845,0.0005615122,0.00079809385],"category_scores_gemma":[0.009610292,0.0004041325,0.0004145577,0.0010588609,0.00042674554,0.0008218913,0.0004998292,0.00047076045,0.00028528366],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010033619,0.00029976756,0.30480447,0.00072604243,0.000359013,0.0005931884,0.0009385349,0.033744678,0.42758435,0.0006407018,0.0002909634,0.22901498],"study_design_scores_gemma":[0.000026681939,0.0013643277,0.663972,0.00005654495,0.0001999362,0.001256811,0.000399272,0.1744761,0.15590014,0.00061928603,0.0015670022,0.00016196299],"about_ca_topic_score_codex":0.00048588336,"about_ca_topic_score_gemma":0.0007191251,"teacher_disagreement_score":0.0023801746,"about_ca_system_score_codex":0.00016049699,"about_ca_system_score_gemma":0.0002227591,"threshold_uncertainty_score":0.012587726},"labels":[],"label_agreement":null},{"id":"W864167668","doi":"10.1016/j.cirp.2015.05.002","title":"High performance cutting of advanced aerospace alloys and composite materials","year":2015,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":559,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; McGill University","funders":"","keywords":"Aerospace; Machining; Surface integrity; Context (archaeology); Coolant; Materials science; Mechanical engineering; Aerospace materials; Cutting tool; Tool wear; Manufacturing engineering; Titanium alloy; Engineering; Metallurgy; Aerospace engineering; Alloy","score_opus":0.01817368861860051,"score_gpt":0.24670694424422665,"score_spread":0.22853325562562615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W864167668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82882196,0.0068557076,0.09515757,0.00033507077,0.00027124985,0.000046605004,0.00018011587,0.00041931844,0.06791257],"genre_scores_gemma":[0.96195704,0.00077650935,0.027534204,0.000022863387,0.000037303616,0.000019080679,0.00020069352,0.00008671216,0.009365615],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996904,0.0000310693,0.0000068500267,0.000025851805,0.0002039298,0.00004195458],"domain_scores_gemma":[0.99972075,0.00009055207,0.000047728645,0.00003337002,0.00008956234,0.000017959335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050676777,0.0003134682,0.00031724432,0.0006290484,0.0004068664,0.00090622634,0.0004887918,0.00047097701,0.0027769],"category_scores_gemma":[0.0005930187,0.00029028507,0.0001991928,0.0004273584,0.00031453662,0.00054129993,0.00050915574,0.00054326095,0.0004340498],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007912588,0.00030071847,0.0035068877,0.0006826853,0.000093696035,0.000297927,0.00017664557,0.16309641,0.6087466,0.02934652,0.0036128538,0.18934777],"study_design_scores_gemma":[0.000069148766,0.0012954635,0.013444829,0.00006308092,0.000051475923,0.0004336324,0.00015903782,0.47509667,0.4803991,0.009078141,0.01986482,0.00004462247],"about_ca_topic_score_codex":0.00045194797,"about_ca_topic_score_gemma":0.0015456224,"teacher_disagreement_score":0.0027769,"about_ca_system_score_codex":0.00037465667,"about_ca_system_score_gemma":0.00046338254,"threshold_uncertainty_score":0.009289622},"labels":[],"label_agreement":null}]}