{"meta":{"query_hash":"a082d3cc7bd4","filters":{"topic":"Engineering Diagnostics and Reliability"},"cohort_total":171,"direct_labels_cover":0,"predictions_cover":171,"exported":171,"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/a082d3cc7bd4","api":"https://metacan.xera.ac/api/v1/cohort?topic=Engineering+Diagnostics+and+Reliability"},"results":[{"id":"W119764546","doi":"10.5006/c2008-08143","title":"Evaluation of Classification and Prioritization Criteria Based on the Results of Direct Examinations","year":2008,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Spectra Energy (Canada); Union Gas (Canada)","funders":"","keywords":"Prioritization; Computer science; Reliability engineering; Engineering; Management science","score_opus":0.04800527808493418,"score_gpt":0.26296918661910024,"score_spread":0.21496390853416605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W119764546","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92162293,0.0007152756,0.06171374,0.0005214357,0.000094389776,0.001015021,0.0006784893,0.0004076303,0.013231074],"genre_scores_gemma":[0.93553174,0.00014074333,0.06190856,0.000039683076,0.000016419443,0.00013353502,0.000447829,0.00003609741,0.0017454802],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9675624,0.012324253,0.003334383,0.0015442068,0.014081741,0.0011530861],"domain_scores_gemma":[0.85574055,0.05403829,0.007792356,0.0033051441,0.07668734,0.0024363468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03118698,0.00094635086,0.0010942098,0.008192438,0.0011075162,0.003701391,0.0014436665,0.00070493954,0.0016752381],"category_scores_gemma":[0.08910756,0.0003118924,0.00060689135,0.002916719,0.00088760746,0.0014406424,0.0015577927,0.00061685545,0.0004942038],"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":[0.0019326067,0.0008262362,0.52938586,0.00073492574,0.00034577685,0.00037386964,0.0026138779,0.032517806,0.023827542,0.002740277,0.0049116844,0.39978954],"study_design_scores_gemma":[0.0003710347,0.0032463148,0.50909096,0.0005133791,0.00050315954,0.0006185009,0.007129851,0.3860524,0.07597829,0.003779589,0.01234124,0.00037534122],"about_ca_topic_score_codex":0.036319587,"about_ca_topic_score_gemma":0.043495405,"teacher_disagreement_score":0.036319587,"about_ca_system_score_codex":0.004313912,"about_ca_system_score_gemma":0.004422103,"threshold_uncertainty_score":0.16493452},"labels":[],"label_agreement":null},{"id":"W14208934","doi":"10.1007/978-3-319-04019-6_4","title":"General Methods for Performing Human Reliability and Error Analysis in Power Plants","year":2014,"lang":"en","type":"book-chapter","venue":"Springer series in reliability engineering","topic":"Engineering Diagnostics and Reliability","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 Ottawa","funders":"","keywords":"Human reliability; Reliability (semiconductor); Reliability engineering; Human error; Computer science; Power (physics); Engineering; Physics","score_opus":0.009507224764416998,"score_gpt":0.2614830934984906,"score_spread":0.25197586873407357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W14208934","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":[0.00013553454,0.00022718532,0.9982948,0.000018803716,0.000028780838,0.000029804918,0.00007913029,0.0003807698,0.00080526486],"genre_scores_gemma":[0.0126586715,0.0013827586,0.9728645,0.00007051106,0.00013380549,0.0004928072,0.00051794876,0.00045151683,0.0114274835],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987973,0.00033837208,0.000091611255,0.00023415896,0.00047025958,0.00006825425],"domain_scores_gemma":[0.99798536,0.0011675281,0.00006945585,0.00041899222,0.00032781519,0.000030857107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015266257,0.0017283709,0.0011556393,0.0012291202,0.00058792724,0.0014483877,0.0032666153,0.001768473,0.016112434],"category_scores_gemma":[0.0052448064,0.00082892034,0.0015054331,0.0013094116,0.0010278295,0.0015552427,0.0016300506,0.0020892245,0.007466436],"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":[0.00008471231,0.00014593765,0.00064668345,0.0011639375,0.00012392597,0.00023725866,0.0003482249,0.15058275,0.0125834765,0.13440183,0.024618246,0.6750629],"study_design_scores_gemma":[0.000030248566,0.00006760277,0.0008943796,0.00016821764,0.0000487701,0.00045927503,0.00010185756,0.6806046,0.009806333,0.26048613,0.047261845,0.000070784896],"about_ca_topic_score_codex":0.0030548484,"about_ca_topic_score_gemma":0.0035004034,"teacher_disagreement_score":0.016112434,"about_ca_system_score_codex":0.0004958634,"about_ca_system_score_gemma":0.001023001,"threshold_uncertainty_score":0.053901494},"labels":[],"label_agreement":null},{"id":"W1427644118","doi":"10.1115/gt2015-44101","title":"Health Monitoring and Degradation Prognostics in Gas Turbine Engines Using Dynamic Neural Networks","year":2015,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Prognostics; Nonlinear autoregressive exogenous model; Akaike information criterion; Artificial neural network; Computer science; Recurrent neural network; Metric (unit); Degradation (telecommunications); Gas turbines; Condition monitoring; Turbine; Network architecture; Artificial intelligence; Data mining; Machine learning; Engineering","score_opus":0.016695986230230088,"score_gpt":0.24923609884837475,"score_spread":0.23254011261814467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1427644118","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.105542,0.0015825767,0.8906216,0.0002458114,0.00005662743,0.00003491078,0.000057857367,0.00043844822,0.0014201902],"genre_scores_gemma":[0.9590791,0.0005360619,0.039496865,0.000042117474,0.000028565697,0.00003457313,0.00006686452,0.000010759356,0.0007051157],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973553,0.00007008759,0.000024763338,0.000058793215,0.00008587581,0.000024880586],"domain_scores_gemma":[0.99935883,0.0003249011,0.00013711519,0.00003476725,0.00012980505,0.0000144995865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008713706,0.00072341383,0.0005449007,0.0005308416,0.00019303327,0.0005872639,0.00053390657,0.00075572927,0.00035477406],"category_scores_gemma":[0.0024805004,0.00021033364,0.00034382503,0.00030462694,0.0003900234,0.0008483407,0.00036868488,0.00046079076,0.00008039959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012430757,0.000051240557,0.003211046,0.000102751066,0.000037841124,0.000101359205,0.000049362836,0.90314007,0.008340644,0.001606531,0.00020529909,0.083029486],"study_design_scores_gemma":[0.0000019556005,0.00002823402,0.0005825828,0.0000058966853,0.000006830418,0.000016886755,0.000004394914,0.99707687,0.0016026873,0.00057252654,0.0000959074,0.000005284479],"about_ca_topic_score_codex":0.0022017122,"about_ca_topic_score_gemma":0.0017156124,"teacher_disagreement_score":0.0022017122,"about_ca_system_score_codex":0.00053310127,"about_ca_system_score_gemma":0.00033270608,"threshold_uncertainty_score":0.004608333},"labels":[],"label_agreement":null},{"id":"W1493770628","doi":"10.5539/mas.v9n8p204","title":"Features of Aboveground Pipeline Compensation Part Stress-Deformed Study at Permafrost","year":2015,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Engineering Diagnostics and Reliability","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":"Pipeline transport; Pipeline (software); Permafrost; Environmental science; Piping; Stress (linguistics); Deformation (meteorology); Geotechnical engineering; Geology; Marine engineering; Mining engineering; Computer science; Engineering","score_opus":0.017375638728902437,"score_gpt":0.2323628129422455,"score_spread":0.21498717421334307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1493770628","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925241,0.00022852566,0.0032235996,0.000030896925,0.000009024463,0.000013003768,0.0003324052,0.00008277913,0.0035557398],"genre_scores_gemma":[0.9986298,0.000071324204,0.00031710273,0.0000036792558,0.0000020091368,0.000002613291,0.00012784121,0.000006916622,0.0008386859],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99986625,0.000007840748,0.000007845049,0.00003671352,0.000055579058,0.000025823723],"domain_scores_gemma":[0.9998555,0.000017762944,0.000026834472,0.000019548557,0.00006578432,0.000014482906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000119310054,0.00020592062,0.00017332552,0.00075179874,0.00038191382,0.00035543286,0.00029945042,0.0003034958,0.0022927707],"category_scores_gemma":[0.0002880833,0.00016195481,0.00023288812,0.00067552185,0.0002966854,0.00034892315,0.0001905828,0.00014617683,0.0002695488],"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":[0.00082901475,0.00029001525,0.34748456,0.0005542605,0.00008594839,0.0065396754,0.0032420238,0.045434408,0.41687652,0.002387065,0.0023672355,0.17390926],"study_design_scores_gemma":[0.000009500983,0.00058110873,0.8645933,0.000045954865,0.00006616497,0.0018636578,0.002053904,0.040916942,0.08289214,0.0007064401,0.006217841,0.000052929146],"about_ca_topic_score_codex":0.0064493977,"about_ca_topic_score_gemma":0.0075235763,"teacher_disagreement_score":0.0064493977,"about_ca_system_score_codex":0.00028477926,"about_ca_system_score_gemma":0.0002507264,"threshold_uncertainty_score":0.012823701},"labels":[],"label_agreement":null},{"id":"W1510952876","doi":"10.1088/0957-0233/26/6/065604","title":"A framework with nonlinear system model and nonparametric noise for gas turbine degradation state estimation","year":2015,"lang":"en","type":"article","venue":"Measurement Science and Technology","topic":"Engineering Diagnostics and Reliability","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":"Life Prediction Technologies (Canada); Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonparametric statistics; Nonlinear system; Degradation (telecommunications); Gas turbines; Noise (video); Estimation; State (computer science); Turbine; Computer science; Environmental science; Control theory (sociology); Mathematics; Econometrics; Algorithm; Physics; Artificial intelligence; Engineering; Thermodynamics; Telecommunications; Mechanical engineering","score_opus":0.022581849544307534,"score_gpt":0.22769754798175376,"score_spread":0.20511569843744623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1510952876","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018975836,0.00014317216,0.9973521,0.00006159397,0.000025191719,0.000009412452,0.00003866735,0.00010826792,0.00036405522],"genre_scores_gemma":[0.71812814,0.001633766,0.26894748,0.00024081668,0.0004083889,0.00052917795,0.0008454743,0.00017405444,0.00909274],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914813,0.000254713,0.000044917684,0.00026862803,0.00019679053,0.0000868985],"domain_scores_gemma":[0.9984987,0.0008742549,0.00021035814,0.00010526731,0.00026895516,0.000042414093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017122111,0.0013909698,0.0012631364,0.0007081058,0.00040859604,0.00095079566,0.0015775266,0.0012873429,0.0013502461],"category_scores_gemma":[0.0050459765,0.00070950575,0.0012324912,0.0007295899,0.0009498286,0.0012012194,0.0012637122,0.0019875197,0.00047352354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004240807,0.00002421331,0.00063358404,0.00007394004,0.000053694683,0.0000921886,0.00004917359,0.9598752,0.001048915,0.01966367,0.0005471358,0.017895881],"study_design_scores_gemma":[0.0000023843793,0.0000096204285,0.000072233626,0.0000022538343,0.0000059296253,0.000007991879,0.0000021494716,0.99751943,0.000096877346,0.0020247945,0.00025135287,0.00000483722],"about_ca_topic_score_codex":0.013576485,"about_ca_topic_score_gemma":0.007585295,"teacher_disagreement_score":0.013576485,"about_ca_system_score_codex":0.0008029879,"about_ca_system_score_gemma":0.0014480719,"threshold_uncertainty_score":0.026994884},"labels":[],"label_agreement":null},{"id":"W1524857579","doi":"10.5006/c2004-04424","title":"Testing Methods and Standards for Oil Field Corrosion Inhibitors","year":2004,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Natural Resources Canada","funders":"","keywords":"Corrosion; Oil field; Materials science; Field (mathematics); Metallurgy; Computer science; Petroleum engineering; Engineering","score_opus":0.010140665807216422,"score_gpt":0.2870731332394356,"score_spread":0.2769324674322192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1524857579","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":[0.056163836,0.03532883,0.8481567,0.002028012,0.0015605811,0.0038661014,0.0014774187,0.0023204056,0.049098212],"genre_scores_gemma":[0.12691556,0.022696298,0.8207845,0.0008511949,0.00045276628,0.0060598208,0.0031357568,0.00044956166,0.018654635],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.96461105,0.010512135,0.0039070486,0.0012454245,0.019222407,0.000501988],"domain_scores_gemma":[0.9712243,0.0063908854,0.0037588913,0.0032744182,0.014892352,0.0004592748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017365351,0.0012873883,0.0010049796,0.007046682,0.0012216409,0.0016230621,0.003861705,0.0023070714,0.0032669755],"category_scores_gemma":[0.023571676,0.0007623843,0.00075505977,0.0020624697,0.0015695863,0.0015747561,0.0016190505,0.0022740327,0.0032782634],"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":[0.00030807065,0.0006356297,0.004134946,0.0042236,0.00006141894,0.00021931976,0.00051525893,0.0038361114,0.59907454,0.020814208,0.008857568,0.35731936],"study_design_scores_gemma":[0.0000659458,0.0021583806,0.0056211962,0.0015983393,0.00009760091,0.0013948005,0.0003935347,0.004464117,0.75279456,0.0058212406,0.22547482,0.000115423456],"about_ca_topic_score_codex":0.0013694938,"about_ca_topic_score_gemma":0.0019251133,"teacher_disagreement_score":0.017365351,"about_ca_system_score_codex":0.0010383135,"about_ca_system_score_gemma":0.0027500417,"threshold_uncertainty_score":0.09183788},"labels":[],"label_agreement":null},{"id":"W1586907968","doi":"10.4271/2007-01-1070","title":"Parametric Analysis of Catalytic Converter Plugging Caused by Manganese-Based Gasoline Additives","year":2007,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":9,"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":"Gasoline; Manganese; Parametric statistics; Catalytic converter; Catalysis; Petroleum engineering; Environmental science; Automotive engineering; Process engineering; Waste management; Materials science; Computer science; Chemistry; Metallurgy; Engineering; Organic chemistry; Mathematics; Statistics","score_opus":0.006340309078778187,"score_gpt":0.22314212790305765,"score_spread":0.21680181882427946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1586907968","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971982,0.000061607316,0.0017998478,0.000007873314,0.000004587342,0.000010578811,0.00017404948,0.000068081776,0.0006751274],"genre_scores_gemma":[0.9989993,0.000028067085,0.00047854855,0.000002581685,0.0000012658759,0.000007696199,0.00008492483,0.000009304128,0.00038837863],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997528,0.000024187439,0.000018772831,0.000048106547,0.00011868563,0.00003739973],"domain_scores_gemma":[0.9992398,0.0003731901,0.00011013818,0.00009224497,0.00015970225,0.000024852483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003133221,0.00029738547,0.00025894312,0.0005145687,0.00013650034,0.00025842717,0.000445536,0.0002529964,0.0014374501],"category_scores_gemma":[0.00092149427,0.00017075145,0.0002707196,0.0004909498,0.0002292493,0.00024388284,0.00024775957,0.00024629576,0.00016300725],"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":[0.0008645148,0.00014208198,0.014683477,0.00015021682,0.000046221186,0.00056344044,0.00031383056,0.011278911,0.9440759,0.00011462931,0.00026452547,0.027502254],"study_design_scores_gemma":[0.000012929068,0.00085585646,0.07693678,0.00000933995,0.000057847217,0.0002848505,0.00024956287,0.026853066,0.8938986,0.00006842524,0.0007396554,0.000033165936],"about_ca_topic_score_codex":0.0009843773,"about_ca_topic_score_gemma":0.0011853628,"teacher_disagreement_score":0.0014374501,"about_ca_system_score_codex":0.00021027368,"about_ca_system_score_gemma":0.00008969003,"threshold_uncertainty_score":0.0048087835},"labels":[],"label_agreement":null},{"id":"W1793993009","doi":"","title":"Principal component analysis of distal radial fracture kinematics during cyclic activities of daily living","year":2006,"lang":"en","type":"article","venue":"CentAUR (University of Reading)","topic":"Engineering Diagnostics and Reliability","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 New Brunswick","funders":"","keywords":"Kinematics; Fracture (geology); Component (thermodynamics); Principal component analysis; Mathematics; Geology; Physics; Statistics; Geotechnical engineering","score_opus":0.002563517501225561,"score_gpt":0.15796056235327918,"score_spread":0.15539704485205363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1793993009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9709199,0.0002694786,0.026064616,0.000071306575,0.000047616122,0.00009056666,0.0011823097,0.00019787691,0.0011564182],"genre_scores_gemma":[0.98763067,0.00018312107,0.00897227,0.0000149229245,0.000017784274,0.00010626653,0.0011618152,0.000051725514,0.0018613391],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99977535,0.000048585665,0.000014285045,0.000051764175,0.000058617905,0.000051366434],"domain_scores_gemma":[0.99953806,0.00015161978,0.000040520314,0.000029572047,0.00020973053,0.000030563242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035175317,0.0004650761,0.00034633168,0.0007669437,0.00029041187,0.00039608573,0.00021222928,0.00021459126,0.0022040515],"category_scores_gemma":[0.0017492324,0.00018316912,0.000458642,0.0008838734,0.0001418623,0.00015065646,0.00029217065,0.0002348676,0.0005092463],"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":[0.0059155463,0.0004920815,0.20289834,0.0004478873,0.00047616436,0.00029708227,0.0016511623,0.019734263,0.10387101,0.00067563687,0.005022679,0.65851814],"study_design_scores_gemma":[0.00003779567,0.000578421,0.9559868,0.000036993268,0.00016479213,0.0003685075,0.00035925445,0.03610589,0.004481303,0.0003256878,0.0014939136,0.000060723047],"about_ca_topic_score_codex":0.011521772,"about_ca_topic_score_gemma":0.014701866,"teacher_disagreement_score":0.011521772,"about_ca_system_score_codex":0.00018975377,"about_ca_system_score_gemma":0.00057736266,"threshold_uncertainty_score":0.022909403},"labels":[],"label_agreement":null},{"id":"W1829529754","doi":"","title":"Complex shock loading on submarine oil pipelines","year":2002,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":1,"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":"Killam Trusts; Dalhousie University","keywords":"Submarine; Shock (circulatory); Pipeline transport; Shock wave; Submarine pipeline; Pipeline (software); Structural engineering; Marine engineering; Petroleum engineering; Engineering; Geology; Geotechnical engineering; Acoustics; Mechanics; Physics; Mechanical engineering; Aerospace engineering","score_opus":0.01705419883721636,"score_gpt":0.19067051652798722,"score_spread":0.17361631769077085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1829529754","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98924863,0.000048425285,0.009101568,0.00003157564,0.000008721544,0.000009418078,0.000040853967,0.00007574393,0.0014349231],"genre_scores_gemma":[0.99885595,0.00003341382,0.00039581102,0.0000045074,0.0000023920525,0.0000029126895,0.000020654013,0.000007568023,0.0006767629],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998223,0.000021673313,0.0000060800103,0.000024700836,0.0000744035,0.000050861734],"domain_scores_gemma":[0.9997842,0.000067037625,0.00004567816,0.000026767588,0.000049564882,0.000026804577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000120866345,0.00049766724,0.00034317715,0.00045750538,0.00033791564,0.00034760952,0.00020940077,0.00040921956,0.0027407282],"category_scores_gemma":[0.00060880167,0.00023448971,0.00020684686,0.00025739757,0.00071061077,0.0003753337,0.0005382444,0.00022449983,0.00030038715],"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":[0.0008805526,0.000056164965,0.0072680376,0.00014578355,0.000031734027,0.0024770997,0.0005659233,0.15025377,0.8079215,0.0018256716,0.00042740648,0.02814642],"study_design_scores_gemma":[0.000064683,0.0013046273,0.074423134,0.00003395136,0.000060989958,0.00095929805,0.0009483557,0.40396187,0.51191026,0.0029886365,0.003256912,0.00008732201],"about_ca_topic_score_codex":0.0012446109,"about_ca_topic_score_gemma":0.0009115313,"teacher_disagreement_score":0.0027407282,"about_ca_system_score_codex":0.00031919387,"about_ca_system_score_gemma":0.0001441966,"threshold_uncertainty_score":0.0091686845},"labels":[],"label_agreement":null},{"id":"W1905427462","doi":"10.1109/imtc.2002.1006949","title":"Combining partial least squares and feed forward neural network technologies in a fault detection system with large number of correlated sensors","year":2003,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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; Kinectrics (Canada)","funders":"","keywords":"Stator; Fault detection and isolation; Artificial neural network; Fault (geology); Electromagnetic coil; Process (computing); Electric power system; Computer science; Field (mathematics); Least-squares function approximation; Electronic engineering; Control engineering; Control theory (sociology); Power (physics); Engineering; Artificial intelligence; Electrical engineering; Mathematics; Physics; Statistics","score_opus":0.003292080757679787,"score_gpt":0.1825273811909049,"score_spread":0.1792353004332251,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1905427462","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03233244,0.0003264506,0.9658481,0.00016673704,0.00004409311,0.00003807656,0.000016222806,0.0004894725,0.00073846325],"genre_scores_gemma":[0.5627073,0.00052573346,0.43430758,0.00017671018,0.00011572017,0.00012221705,0.0000668353,0.000035084326,0.0019428651],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932754,0.000253513,0.000032867443,0.00009987062,0.00023016587,0.000056094774],"domain_scores_gemma":[0.9987949,0.00076683034,0.000104728904,0.00010549093,0.00020589732,0.000022078342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011164529,0.0010376119,0.00080477924,0.00045974329,0.00029872076,0.0006565155,0.0005744433,0.0009946579,0.00065240415],"category_scores_gemma":[0.0029109812,0.00057174277,0.0003383358,0.00064773986,0.0005738115,0.0014952089,0.00068155775,0.0006984147,0.00024321036],"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":[0.00038337603,0.00018657616,0.0023759191,0.00020974621,0.00019364787,0.0003158817,0.00014241517,0.44249645,0.041170206,0.004986827,0.00068249454,0.5068565],"study_design_scores_gemma":[0.000017338238,0.00021264954,0.00069154194,0.000013741009,0.000048814516,0.00010111363,0.000014957832,0.982106,0.012952737,0.0032504767,0.0005695781,0.000021061782],"about_ca_topic_score_codex":0.0013785069,"about_ca_topic_score_gemma":0.002755934,"teacher_disagreement_score":0.0013785069,"about_ca_system_score_codex":0.00032061755,"about_ca_system_score_gemma":0.00046917435,"threshold_uncertainty_score":0.005904436},"labels":[],"label_agreement":null},{"id":"W1968646709","doi":"10.1016/s0262-1762(08)70143-3","title":"Preventive maintenance for heat transfer systems","year":2008,"lang":"en","type":"article","venue":"World Pumps","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":2,"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":"Preventive maintenance; Heat transfer; Engineering; Reliability engineering; Mechanics; Physics","score_opus":0.00857139573281055,"score_gpt":0.19053899254310502,"score_spread":0.18196759681029448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968646709","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":[0.29789093,0.015053112,0.6236383,0.003894768,0.002688751,0.0007140775,0.0008951027,0.0232513,0.031973694],"genre_scores_gemma":[0.95103675,0.00095625006,0.038879428,0.00031809727,0.00033966135,0.00013553123,0.0004899227,0.0002371804,0.007607132],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988172,0.0001694742,0.00007370914,0.0001874601,0.0005989077,0.00015332006],"domain_scores_gemma":[0.995805,0.0011483175,0.00059993117,0.0013119557,0.0009366321,0.00019811273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012439834,0.0008079,0.0004954757,0.0011496838,0.0012405177,0.001040313,0.0023212128,0.0010551251,0.00712555],"category_scores_gemma":[0.006756033,0.00034090516,0.00052119495,0.00037863047,0.0005419111,0.0013992324,0.000890295,0.000997186,0.0017324449],"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":[0.0015810123,0.00064067956,0.015408938,0.0022449177,0.00016143997,0.0011030809,0.0010513995,0.020642197,0.07077929,0.02164463,0.031808387,0.8329341],"study_design_scores_gemma":[0.00079775497,0.0052988604,0.08573908,0.0018119371,0.0012398093,0.013327026,0.0009971187,0.28189337,0.24540304,0.06858563,0.2944501,0.00045625347],"about_ca_topic_score_codex":0.0014718875,"about_ca_topic_score_gemma":0.0009999565,"teacher_disagreement_score":0.00712555,"about_ca_system_score_codex":0.00064178545,"about_ca_system_score_gemma":0.0009403491,"threshold_uncertainty_score":0.023837388},"labels":[],"label_agreement":null},{"id":"W1986413971","doi":"10.1134/s0040601510010039","title":"Diagnostics of steam turbine disks using the metal magnetic memory method","year":2010,"lang":"en","type":"article","venue":"Thermal Engineering","topic":"Engineering Diagnostics and Reliability","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":"Cytodiagnostics (Canada)","funders":"","keywords":"Steam turbine; Magnetic memory; Nuclear engineering; Engineering; Turbine; Mechanical engineering; Materials science; Composite material","score_opus":0.005918966899016806,"score_gpt":0.21549702506809798,"score_spread":0.20957805816908118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986413971","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8796722,0.0065316404,0.10753256,0.00023519073,0.00014231,0.00008212858,0.00008201416,0.0005715536,0.005150477],"genre_scores_gemma":[0.96779263,0.0007843565,0.029983414,0.00005492707,0.000028582417,0.000016197391,0.000027906919,0.000011089145,0.001300853],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978167,0.00005427906,0.000011517947,0.000034420726,0.00009636368,0.000021611997],"domain_scores_gemma":[0.9996387,0.00016563266,0.0000494906,0.000033449833,0.00008909421,0.000023629778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021572798,0.00032924433,0.00025645545,0.00083787687,0.00014922132,0.00029581832,0.00049719616,0.0005609035,0.0010017825],"category_scores_gemma":[0.0007772934,0.00016789653,0.0001612248,0.00018320125,0.00033553754,0.00034782215,0.00023675757,0.00020296605,0.00034416592],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063489267,0.000040140265,0.0047450266,0.00023207365,0.000017117269,0.00045624096,0.00006922103,0.00041206245,0.9419225,0.00048099874,0.0002200826,0.05076973],"study_design_scores_gemma":[0.00007517752,0.0014784434,0.010825611,0.000044279215,0.00011328605,0.0071159373,0.00023082204,0.018724188,0.95618224,0.00082777184,0.0043445085,0.000037613805],"about_ca_topic_score_codex":0.00024498237,"about_ca_topic_score_gemma":0.0003523563,"teacher_disagreement_score":0.0010017825,"about_ca_system_score_codex":0.00008727799,"about_ca_system_score_gemma":0.00011668456,"threshold_uncertainty_score":0.0033512712},"labels":[],"label_agreement":null},{"id":"W1994785592","doi":"10.5539/emr.v2n2p56","title":"An Expert System for Diagnosing and Proffer Solutions to Causes of Overheating of a Bulldozer Engine (Case Study Model D60s-6 Komatsu Products)","year":2013,"lang":"en","type":"article","venue":"Engineering Management Research","topic":"Engineering Diagnostics and Reliability","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":"Overheating (electricity); Troubleshooting; Flowchart; Automotive industry; Engineering; Automotive engineering; Computer science; Reliability engineering; Systems engineering","score_opus":0.047364376600697214,"score_gpt":0.31702126653687424,"score_spread":0.26965688993617704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994785592","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12215994,0.00035725505,0.80627203,0.00034807783,0.00012140753,0.0023994248,0.0030998879,0.045715936,0.019526059],"genre_scores_gemma":[0.3121278,0.0002859963,0.66143,0.00017630865,0.000038151058,0.0014307043,0.002807487,0.00046528506,0.021238213],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955004,0.00011756635,0.00004881755,0.00015321936,0.000092770366,0.00003741969],"domain_scores_gemma":[0.9983872,0.000885213,0.00007617874,0.00013720847,0.00042267737,0.0000915684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012403487,0.00097331894,0.00055715715,0.0011461802,0.00030294454,0.0005867637,0.0009015408,0.0008041422,0.015707668],"category_scores_gemma":[0.0026858323,0.00043139356,0.00029021758,0.000512974,0.00018544929,0.0005800837,0.00052059814,0.0005611984,0.0032771837],"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":[0.0015368869,0.0014096153,0.0076804524,0.0015793869,0.000096259835,0.0022326487,0.0015627308,0.06276424,0.118158266,0.0038708993,0.036823332,0.76228535],"study_design_scores_gemma":[0.0014155665,0.0022237857,0.017171938,0.00042742598,0.00036982523,0.0031552184,0.0007861833,0.7913188,0.08614726,0.0037855008,0.093008004,0.00019052172],"about_ca_topic_score_codex":0.0024376938,"about_ca_topic_score_gemma":0.0025993192,"teacher_disagreement_score":0.015707668,"about_ca_system_score_codex":0.00036420376,"about_ca_system_score_gemma":0.0009421123,"threshold_uncertainty_score":0.052547395},"labels":[],"label_agreement":null},{"id":"W1996204213","doi":"10.1108/13552510110407087","title":"Genetic algorithms for reliability assessment of mining equipment","year":2001,"lang":"en","type":"article","venue":"Journal of Quality in Maintenance Engineering","topic":"Engineering Diagnostics and Reliability","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":"Laurentian University","funders":"","keywords":"Reliability (semiconductor); Reliability engineering; Genetic algorithm; Computer science; Algorithm; Engineering; Machine learning","score_opus":0.022284099874276618,"score_gpt":0.30768453870495727,"score_spread":0.28540043883068067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996204213","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010179212,0.001886888,0.98280084,0.0003913989,0.000049529386,0.00006286283,0.00008350042,0.00035661634,0.004189036],"genre_scores_gemma":[0.33772862,0.0028472377,0.6522561,0.0002218803,0.00018793043,0.00044232633,0.00038546257,0.00018374079,0.005746795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951947,0.00024716125,0.000022603692,0.000065020606,0.0001142674,0.00003144785],"domain_scores_gemma":[0.99860317,0.0010670712,0.00008004786,0.000047640566,0.00018100721,0.000021028454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016713246,0.0009790387,0.0008949729,0.0015221005,0.00041601554,0.0009659238,0.0010409391,0.0013180777,0.001840842],"category_scores_gemma":[0.005096604,0.00042826665,0.00071608496,0.001269321,0.00064416125,0.00084866927,0.0005085054,0.0011131221,0.0003942312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000112562675,0.000012934663,0.00029688448,0.000027912294,0.00003141039,0.000015779277,0.00002104595,0.94834816,0.00014579945,0.014853635,0.0006296909,0.035605464],"study_design_scores_gemma":[0.0000068367244,0.0000089244595,0.00008604833,0.0000143708785,0.000007037041,0.000007451575,0.000005496208,0.9815097,0.00008797909,0.01735428,0.0009077639,0.000004170828],"about_ca_topic_score_codex":0.0071875,"about_ca_topic_score_gemma":0.0055932337,"teacher_disagreement_score":0.0071875,"about_ca_system_score_codex":0.0012651647,"about_ca_system_score_gemma":0.00099225,"threshold_uncertainty_score":0.0142912865},"labels":[],"label_agreement":null},{"id":"W2030219163","doi":"10.1016/j.pnucene.2015.03.005","title":"Corrigendum to “Fuzzy logic-based safety design for high performance air compressors” [Prog. Nuclear Energy 80C (2014) 136–150]","year":2015,"lang":"en","type":"erratum","venue":"Progress in Nuclear Energy","topic":"Engineering Diagnostics and Reliability","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":"Fuzzy logic; Gas compressor; Nuclear engineering; Computer science; Mechanical engineering; Engineering; Artificial intelligence","score_opus":0.015841358209900343,"score_gpt":0.2160427677925046,"score_spread":0.20020140958260424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030219163","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":[0.0002955938,0.0059129423,0.003555439,0.06265981,0.9054325,0.00009256479,0.001195478,0.0005261159,0.020329522],"genre_scores_gemma":[0.015385751,0.018159468,0.008828746,0.07679152,0.17793112,0.00029955004,0.0031681003,0.0010250079,0.69841075],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970572,0.00038328322,0.00035459147,0.00039653174,0.0015890369,0.00021938025],"domain_scores_gemma":[0.989874,0.0017968472,0.00021990862,0.00044378004,0.0074624848,0.00020299194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020167688,0.001982833,0.0020008895,0.0031282268,0.0036538667,0.0025685055,0.0037117393,0.0061355443,0.07285114],"category_scores_gemma":[0.01661872,0.00091460237,0.0021998745,0.0019365556,0.0019262964,0.0022282964,0.0015811537,0.006087127,0.032008644],"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":[0.000033456137,0.000010193081,0.000036976104,0.00014306394,0.000012124639,0.00016148605,0.00002477449,0.00017499513,0.0001509786,0.0020255053,0.98992854,0.0072979205],"study_design_scores_gemma":[0.000037879272,0.000052021805,0.0010043429,0.00021434012,0.000046513942,0.0002359433,0.00007924635,0.0012428698,0.00089850824,0.0056005674,0.9905201,0.00006768191],"about_ca_topic_score_codex":0.056559876,"about_ca_topic_score_gemma":0.06537262,"teacher_disagreement_score":0.07285114,"about_ca_system_score_codex":0.004868787,"about_ca_system_score_gemma":0.002896536,"threshold_uncertainty_score":0.24371135},"labels":[],"label_agreement":null},{"id":"W2039523597","doi":"10.1115/power2014-32207","title":"Improve Boiler Reliability With Unit Specific Strategic Planning","year":2014,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Risk analysis (engineering); Preventive maintenance; Strategic planning; Reliability engineering; Operations management; Computer science; Engineering; Business; Marketing","score_opus":0.010588939392459279,"score_gpt":0.19559100631013396,"score_spread":0.18500206691767468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039523597","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0668167,0.0020219004,0.8815026,0.0017569456,0.00020939326,0.0005499105,0.0006024223,0.0037562305,0.04278386],"genre_scores_gemma":[0.70254236,0.0011141559,0.2891474,0.0004104988,0.000040916522,0.00028410528,0.0010144621,0.00045616197,0.004989878],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988494,0.00027981857,0.000057633573,0.00015298615,0.0004593637,0.00020079275],"domain_scores_gemma":[0.9978758,0.0007328761,0.0002834594,0.00020885226,0.00067338784,0.00022562315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019570123,0.0013806216,0.00057659496,0.0013192055,0.0006256653,0.0023054837,0.0013368381,0.00069048454,0.0076922392],"category_scores_gemma":[0.0053097066,0.00063642743,0.0006852484,0.0010147546,0.0006048365,0.0025056326,0.002226269,0.0016965606,0.0014495109],"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":[0.00023529322,0.0002595573,0.005136822,0.00034089462,0.00007591292,0.00033310818,0.00049588876,0.74473476,0.011211747,0.022701355,0.009746883,0.20472784],"study_design_scores_gemma":[0.000084545696,0.00050035113,0.003093646,0.00016601876,0.000100373785,0.00016697923,0.0008292072,0.928863,0.0067762,0.033846367,0.025475174,0.000098214456],"about_ca_topic_score_codex":0.011876215,"about_ca_topic_score_gemma":0.021589335,"teacher_disagreement_score":0.011876215,"about_ca_system_score_codex":0.0016204579,"about_ca_system_score_gemma":0.004544798,"threshold_uncertainty_score":0.025733113},"labels":[],"label_agreement":null},{"id":"W2043562752","doi":"10.2118/149938-ru","title":"Trenching of Pipelines for Protection in Ice Environments (Russian)","year":2011,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Intecsea (Canada)","funders":"","keywords":"Pipeline transport; Computer science; Geology; Engineering; Mechanical engineering","score_opus":0.01809777232332555,"score_gpt":0.18708306093705676,"score_spread":0.16898528861373122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043562752","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91217285,0.001123864,0.040425755,0.0005255132,0.00017480933,0.00013189162,0.00074545806,0.0004675085,0.044232238],"genre_scores_gemma":[0.9835073,0.0003506299,0.0039252643,0.000023403754,0.0000104792825,0.00001531544,0.00027033026,0.000038755545,0.011858729],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99957114,0.000053289452,0.000019352818,0.00011209716,0.00010279171,0.00014137634],"domain_scores_gemma":[0.99972624,0.000039760816,0.000039240742,0.00005373916,0.00010815318,0.000032847205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003733704,0.00030347207,0.00026483837,0.0008445007,0.0020359715,0.0011131676,0.0004978739,0.0005742295,0.004390446],"category_scores_gemma":[0.0007189596,0.00025985003,0.00043391908,0.0009013505,0.00096356065,0.0011580851,0.0011092927,0.00046956472,0.0010334044],"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":[0.00237595,0.00026742378,0.13836847,0.0008243975,0.00013940335,0.0066107684,0.006402087,0.28211427,0.17042047,0.05632616,0.011192373,0.32495824],"study_design_scores_gemma":[0.00017288282,0.0029753656,0.36512318,0.00054009707,0.00028912,0.0047718887,0.013121413,0.20825085,0.19670515,0.03458063,0.17318447,0.00028487795],"about_ca_topic_score_codex":0.0155258775,"about_ca_topic_score_gemma":0.01737625,"teacher_disagreement_score":0.0155258775,"about_ca_system_score_codex":0.0011128548,"about_ca_system_score_gemma":0.0028663422,"threshold_uncertainty_score":0.030871034},"labels":[],"label_agreement":null},{"id":"W2045950278","doi":"10.1115/2000-gt-0623","title":"Steady State Performance Simulation of Auxiliary Power Unit With Faults for Component Diagnosis","year":2000,"lang":"en","type":"article","venue":"Volume 1: Aircraft Engine; Marine; Turbomachinery; Microturbines and Small Turbomachinery","topic":"Engineering Diagnostics and Reliability","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":"Queen's University","funders":"","keywords":"Fault (geology); Steady state (chemistry); Power (physics); Component (thermodynamics); Turbine; Computer science; Baseline (sea); Automotive engineering; Control theory (sociology); Simulation; Engineering; Mechanical engineering","score_opus":0.0060913737935562,"score_gpt":0.18865360729862043,"score_spread":0.18256223350506423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045950278","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9316722,0.00011524556,0.05891246,0.000118498574,0.00003062213,0.00007296254,0.00051980553,0.00077942054,0.0077788197],"genre_scores_gemma":[0.99644476,0.000029968607,0.002356144,0.0000059161575,0.0000018742351,0.000033650937,0.00012447423,0.00001992526,0.0009833411],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988496,0.000031471176,0.000005238787,0.000014820744,0.0000377912,0.000025673582],"domain_scores_gemma":[0.99932563,0.00038226708,0.000048722184,0.000057195968,0.0001461024,0.000040122708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028149385,0.00047838368,0.00054307876,0.0003362603,0.00028590256,0.00039136142,0.00065629213,0.0007325861,0.002607346],"category_scores_gemma":[0.0010612372,0.00021361446,0.0003918811,0.00025502854,0.00037558627,0.0003721524,0.00024472395,0.0005414991,0.00032104208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009074578,0.00004790173,0.0012720814,0.000025361302,0.000008648446,0.00006070848,0.000040719166,0.99289834,0.0028410477,0.0006253032,0.0001958171,0.0018932777],"study_design_scores_gemma":[0.0000056615477,0.000038531507,0.00034774136,0.0000012601948,0.0000028008124,0.0000049069135,0.0000058732326,0.9983664,0.0010444539,0.00010574335,0.000074562966,0.0000020983596],"about_ca_topic_score_codex":0.008201381,"about_ca_topic_score_gemma":0.0048170527,"teacher_disagreement_score":0.008201381,"about_ca_system_score_codex":0.00050626445,"about_ca_system_score_gemma":0.00049352145,"threshold_uncertainty_score":0.016307294},"labels":[],"label_agreement":null},{"id":"W2053167414","doi":"10.1520/jai101244","title":"Measurement of Corrosion Potentials of the Internal Surface of Operating High-Pressure Oil and Gas Pipelines","year":2008,"lang":"en","type":"article","venue":"Journal of ASTM International","topic":"Engineering Diagnostics and Reliability","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":"Natural Resources Canada; Devon Energy (Canada)","funders":"","keywords":"Pipeline transport; Corrosion; Materials science; Internal pressure; Petroleum engineering; Environmental science; Metallurgy; Composite material; Geology; Environmental engineering","score_opus":0.008089240603051938,"score_gpt":0.20011688793093477,"score_spread":0.19202764732788283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053167414","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864042,0.00026286524,0.0104116695,0.000057317473,0.000020085203,0.0000137430025,0.00020454521,0.00014559487,0.0024799814],"genre_scores_gemma":[0.9973124,0.00012554968,0.0018947413,0.000011276175,0.0000046266296,0.0000043295117,0.00009534543,0.000010776623,0.00054090784],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996087,0.000042476797,0.0000101464875,0.000042728734,0.00024687752,0.0000490744],"domain_scores_gemma":[0.99948955,0.00009649339,0.00009654733,0.000032786636,0.00023482302,0.00004978094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002035038,0.0003756758,0.00022874014,0.00050056796,0.00025808933,0.00039596626,0.0002670285,0.0003618656,0.00081860257],"category_scores_gemma":[0.0006252278,0.00011275243,0.00017838369,0.0004498638,0.0003109601,0.00036913488,0.0003926782,0.00054329284,0.0002864515],"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":[0.00008586753,0.00002203566,0.00694145,0.00007021274,0.000011929162,0.00012428907,0.00013927204,0.00059094816,0.9789842,0.000140449,0.00018915381,0.012700199],"study_design_scores_gemma":[0.000005323459,0.00040508204,0.049347475,0.000011918917,0.00002126382,0.00046394762,0.00026014636,0.0039935596,0.9440415,0.00014888811,0.0012853387,0.000015650083],"about_ca_topic_score_codex":0.0008759333,"about_ca_topic_score_gemma":0.0008369185,"teacher_disagreement_score":0.0008759333,"about_ca_system_score_codex":0.00021109791,"about_ca_system_score_gemma":0.00015772552,"threshold_uncertainty_score":0.0027385354},"labels":[],"label_agreement":null},{"id":"W2059668416","doi":"10.1007/s11015-014-9949-4","title":"The Repairs Project as a Tool for Improving the Productivity of Equipment","year":2014,"lang":"en","type":"article","venue":"Metallurgist","topic":"Engineering Diagnostics and Reliability","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":"EVRAZ (Canada)","funders":"","keywords":"Productivity; Realization (probability); Manufacturing engineering; Engineering; Computer science; Systems engineering; Operations management; Mathematics","score_opus":0.0075258985630210235,"score_gpt":0.2205953578942758,"score_spread":0.2130694593312548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059668416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69225264,0.0031420665,0.06903711,0.012442936,0.0010470161,0.00091321755,0.0011856662,0.0057501784,0.21422909],"genre_scores_gemma":[0.90618634,0.0012092176,0.042776283,0.0005431815,0.0001286693,0.00017792638,0.00053582207,0.0002892344,0.04815331],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99725986,0.0010719567,0.000062292514,0.0001636622,0.0012700288,0.00017221195],"domain_scores_gemma":[0.9966235,0.0009911348,0.0003558058,0.0004938019,0.0008227202,0.00071303104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033237753,0.0007251639,0.00020385647,0.001786528,0.0015337565,0.0014948273,0.0007041969,0.0008673242,0.0061148587],"category_scores_gemma":[0.005484141,0.00027657053,0.0002752311,0.00062615896,0.0010751336,0.0013261612,0.0017726085,0.0011105424,0.0008997049],"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":[0.000884693,0.00182687,0.02090168,0.00064151164,0.000108647124,0.001482638,0.0022391393,0.007106082,0.03173819,0.029018665,0.062303115,0.8417488],"study_design_scores_gemma":[0.0011151357,0.016637238,0.2647511,0.001107263,0.00037003699,0.0072564688,0.009284516,0.035018686,0.10155522,0.022988526,0.5395467,0.0003690752],"about_ca_topic_score_codex":0.0030670771,"about_ca_topic_score_gemma":0.0056692036,"teacher_disagreement_score":0.0061148587,"about_ca_system_score_codex":0.00082072784,"about_ca_system_score_gemma":0.0046813246,"threshold_uncertainty_score":0.020456254},"labels":[],"label_agreement":null},{"id":"W2063632721","doi":"10.1016/s1001-6058(06)60004-8","title":"Fault Caused by Water Pressure in the Head-Cover Chamber","year":2006,"lang":"en","type":"article","venue":"Journal of Hydrodynamics","topic":"Engineering Diagnostics and Reliability","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":"Vernon Jubilee Hospital","funders":"","keywords":"Head (geology); Fault (geology); Cover (algebra); Hydropower; Hydraulic head; Hydroelectricity; Environmental science; Geology; Marine engineering; Geotechnical engineering; Mechanical engineering; Seismology; Engineering; Electrical engineering; Geomorphology","score_opus":0.002445241734904293,"score_gpt":0.18643858802088484,"score_spread":0.18399334628598055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063632721","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99328494,0.00011089687,0.004191815,0.00039075816,0.0001693333,0.000012694029,0.00015190888,0.00052127155,0.0011663958],"genre_scores_gemma":[0.9992231,0.000015954194,0.00026178054,0.000022601947,0.000010370421,0.0000016358218,0.000047219128,0.0000071950017,0.00041012897],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997216,0.000024072797,0.000015478221,0.000043463268,0.000095899224,0.00009938845],"domain_scores_gemma":[0.99954224,0.00014111445,0.00008625272,0.00004324182,0.000076759694,0.000110377216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014056708,0.00032614399,0.00044668076,0.00037241075,0.00072661834,0.0003175533,0.00046254342,0.0010825414,0.0028920413],"category_scores_gemma":[0.00078084465,0.00018399919,0.00029939902,0.00018579992,0.0005283547,0.00048422487,0.0004970517,0.00051298644,0.00024209569],"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":[0.0067215124,0.00019391203,0.048250403,0.0003564191,0.0001527113,0.030701619,0.0013807868,0.037269387,0.83241147,0.0021633392,0.006978211,0.03342022],"study_design_scores_gemma":[0.00026950345,0.0018334836,0.10830901,0.000045095665,0.00023380705,0.0048260987,0.00087004,0.20816547,0.67016244,0.0010598024,0.004062252,0.00016313522],"about_ca_topic_score_codex":0.0028600635,"about_ca_topic_score_gemma":0.0014725983,"teacher_disagreement_score":0.0028920413,"about_ca_system_score_codex":0.00043768642,"about_ca_system_score_gemma":0.00037786874,"threshold_uncertainty_score":0.009674847},"labels":[],"label_agreement":null},{"id":"W2072761185","doi":"10.2478/v10012-007-0067-0","title":"A discrete model of the plate heat exchanger","year":2008,"lang":"en","type":"article","venue":"Polish Maritime Research","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":2,"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":"Heat exchanger; Correctness; Mechanical engineering; Plate heat exchanger; Mechanics; Computer science; Engineering; Physics; Algorithm","score_opus":0.053196255638220266,"score_gpt":0.29132741603182455,"score_spread":0.23813116039360427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072761185","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023940073,0.0006154128,0.9335253,0.00043014006,0.00017420764,0.00007183064,0.0007040656,0.0004791083,0.040059794],"genre_scores_gemma":[0.8668922,0.0010299473,0.08158818,0.00014954187,0.00013230911,0.00031078662,0.0008057241,0.00011523851,0.04897609],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997565,0.00004564977,0.0000131472325,0.00006300707,0.00010071469,0.000020952155],"domain_scores_gemma":[0.99981755,0.00006145016,0.00002246938,0.000037852962,0.00004009452,0.000020582282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022354144,0.0006829616,0.0006110266,0.00038764166,0.00045126956,0.001346933,0.0012163625,0.0012582318,0.0077035017],"category_scores_gemma":[0.00042733987,0.0003727928,0.000593075,0.0004530097,0.0011319029,0.0010283676,0.0006615978,0.0014649176,0.0013065707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007228921,0.000059817427,0.0002993334,0.00014536489,0.000014820741,0.00018801301,0.0001107313,0.8273312,0.012121055,0.15065113,0.0010676406,0.007938539],"study_design_scores_gemma":[0.000026666894,0.00004613747,0.00016136689,0.000008524747,0.000008604669,0.00005352765,0.000018478348,0.9773985,0.0014158933,0.015893158,0.0049546524,0.000014404586],"about_ca_topic_score_codex":0.0042851144,"about_ca_topic_score_gemma":0.0014915692,"teacher_disagreement_score":0.0077035017,"about_ca_system_score_codex":0.00057611126,"about_ca_system_score_gemma":0.00083460775,"threshold_uncertainty_score":0.025770843},"labels":[],"label_agreement":null},{"id":"W2074668057","doi":"10.1115/detc2010-29126","title":"EMD, Ranking Mutual Information and PCA Based Condition Monitoring","year":2010,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Mutual information; Condition monitoring; Ranking (information retrieval); Monotonic function; Impeller; Data mining; Computer science; Artificial intelligence; Fault (geology); Pattern recognition (psychology); Feature (linguistics); Fault detection and isolation; Information fusion; Feature extraction; Machine learning; Engineering; Mathematics","score_opus":0.0023616914695392824,"score_gpt":0.18253845360421614,"score_spread":0.18017676213467684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074668057","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013220475,0.0009030355,0.9822657,0.00018889115,0.00005471836,0.000059828508,0.00021878349,0.0008946321,0.0021939871],"genre_scores_gemma":[0.5284841,0.0012629764,0.46452987,0.00014658873,0.0001800683,0.00021972129,0.00083111285,0.00013086118,0.004214644],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980108,0.0006177733,0.00009935454,0.00032999855,0.00083800586,0.000104118786],"domain_scores_gemma":[0.99861336,0.0006991371,0.00022714322,0.0001665369,0.0002490767,0.000044823566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013272371,0.0009542347,0.0009406691,0.0020220466,0.00033521396,0.0011962338,0.00075336464,0.0006079157,0.0015864953],"category_scores_gemma":[0.0047190366,0.00034278195,0.000622245,0.002019432,0.00083375495,0.0017541117,0.0011376721,0.0007531744,0.00053267414],"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":[0.00039613617,0.00015116746,0.002986474,0.00030467435,0.0001756906,0.00017377181,0.00010719593,0.19867702,0.014739463,0.025018143,0.00428221,0.75298804],"study_design_scores_gemma":[0.000010339476,0.00008533217,0.002815018,0.000011361585,0.00002525028,0.00018669837,0.000019225345,0.97655606,0.00887373,0.008612415,0.002746392,0.000058129695],"about_ca_topic_score_codex":0.0019332414,"about_ca_topic_score_gemma":0.0014154386,"teacher_disagreement_score":0.0020220466,"about_ca_system_score_codex":0.00066431693,"about_ca_system_score_gemma":0.00058214157,"threshold_uncertainty_score":0.007019162},"labels":[],"label_agreement":null},{"id":"W2078164134","doi":"10.1006/jsvi.2000.3520","title":"DEVELOPMENT OF OPTIMALLY DISORDERED CRITICAL RANDOM EXCITATION","year":2001,"lang":"en","type":"article","venue":"Journal of Sound and Vibration","topic":"Engineering Diagnostics and Reliability","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 Waterloo","funders":"","keywords":"Mathematical optimization; Principle of maximum entropy; Gaussian; Mathematics; Gaussian process; Maximization; Spectral density; Excitation; Optimization problem; Pareto principle; Electric power system; Applied mathematics; Statistical physics; Power (physics); Physics; Statistics","score_opus":0.009824819430227493,"score_gpt":0.23641140334733354,"score_spread":0.22658658391710604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078164134","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.085967846,0.00032120114,0.89581674,0.0001723198,0.000091989124,0.00008690546,0.000057062138,0.00042487297,0.017061086],"genre_scores_gemma":[0.7990575,0.00036807673,0.19278196,0.00009494055,0.000044230015,0.000114766815,0.00012923703,0.00020197911,0.0072072907],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978644,0.000054525233,0.000010884849,0.000044652523,0.00006893799,0.000034626897],"domain_scores_gemma":[0.99894804,0.00051324203,0.0001299642,0.00009435757,0.00022071865,0.00009380005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005177075,0.00051272416,0.0005806866,0.0006150631,0.00031591332,0.0005512126,0.00055449706,0.0005474156,0.002475384],"category_scores_gemma":[0.0027750323,0.0004571697,0.00024917076,0.00018873104,0.0008046673,0.0005739289,0.0014424716,0.00056510867,0.00043729504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021621687,0.00012756072,0.0022573234,0.0003335912,0.000042590473,0.00039075222,0.00028008,0.47377643,0.0579952,0.3952533,0.0025211396,0.06680577],"study_design_scores_gemma":[0.000018210007,0.000089339825,0.0001708703,0.000022388782,0.000012889341,0.00008309561,0.000019520468,0.96530515,0.008677175,0.023616027,0.001973692,0.000011621085],"about_ca_topic_score_codex":0.00055078795,"about_ca_topic_score_gemma":0.00075234706,"teacher_disagreement_score":0.002475384,"about_ca_system_score_codex":0.00038116617,"about_ca_system_score_gemma":0.00062187394,"threshold_uncertainty_score":0.0082809925},"labels":[],"label_agreement":null},{"id":"W2083923231","doi":"10.1108/14714171211244541","title":"Significance ranking of parameters impacting construction labour productivity","year":2012,"lang":"en","type":"article","venue":"Construction Innovation","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":70,"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":"Ranking (information retrieval); Productivity; Labour economics; Economics; Econometrics; Environmental science; Computer science; Information retrieval; Economic growth","score_opus":0.01142623255572148,"score_gpt":0.21943365548993735,"score_spread":0.20800742293421587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083923231","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9660465,0.00055305986,0.029943943,0.00015226738,0.000038640694,0.0001616651,0.000507315,0.00015762582,0.0024389166],"genre_scores_gemma":[0.995407,0.00005290252,0.0041926336,0.0000056763615,0.000008757145,0.000021480342,0.00020014177,0.000010629768,0.00010082705],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9922787,0.004008659,0.00076596986,0.0006146962,0.0019211685,0.00041086832],"domain_scores_gemma":[0.95258,0.039198797,0.002888106,0.0018464084,0.0029925527,0.0004942081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077168792,0.0009806639,0.0009793531,0.004726204,0.00053964107,0.0022813787,0.00046768232,0.00060680683,0.0024817206],"category_scores_gemma":[0.03334648,0.0002531998,0.0014950864,0.0034384325,0.0008689541,0.0008312169,0.00083670043,0.00074293505,0.00032860402],"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":[0.001205876,0.0003533024,0.77592564,0.0006964747,0.0010257206,0.0005517492,0.0005966992,0.053747687,0.017470911,0.001294911,0.0006851461,0.14644589],"study_design_scores_gemma":[0.00004762009,0.0015911459,0.85583127,0.00014448357,0.00068474025,0.00041176064,0.0025160394,0.11770126,0.015890017,0.003424023,0.0015844976,0.00017310701],"about_ca_topic_score_codex":0.0023113538,"about_ca_topic_score_gemma":0.0019438417,"teacher_disagreement_score":0.0077168792,"about_ca_system_score_codex":0.0006629277,"about_ca_system_score_gemma":0.001173132,"threshold_uncertainty_score":0.04081124},"labels":[],"label_agreement":null},{"id":"W2095100844","doi":"10.3103/s1068364x13100074","title":"Upgrading the equipment for raw-benzene rectification","year":2013,"lang":"en","type":"article","venue":"Coke and Chemistry","topic":"Engineering Diagnostics and Reliability","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":"EVRAZ (Canada)","funders":"","keywords":"Rectification; Benzene; Raw material; Waste management; Pulp and paper industry; Environmental science; Process engineering; Chemistry; Engineering; Organic chemistry; Electrical engineering","score_opus":0.0042926292186938496,"score_gpt":0.17043987387696538,"score_spread":0.16614724465827152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095100844","genre_codex":"empirical","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":[0.9159987,0.002713864,0.048387088,0.0010160577,0.00040244518,0.0007908128,0.0017493847,0.0028442852,0.026097352],"genre_scores_gemma":[0.9471578,0.0010912623,0.022265367,0.000112133945,0.00006373146,0.00009318439,0.0014894118,0.00036644068,0.027360654],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992021,0.00008972176,0.000035223515,0.00009058289,0.00045410058,0.00012833811],"domain_scores_gemma":[0.9989236,0.00019064068,0.000043332344,0.00020629771,0.00055767625,0.000078385834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013128133,0.00078647636,0.0007540315,0.0017025094,0.001884285,0.00073137996,0.0010198656,0.00077056076,0.012218953],"category_scores_gemma":[0.0014713794,0.00026978814,0.00080379826,0.001299266,0.000502758,0.00097650103,0.0008294497,0.0013320715,0.0038623966],"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":[0.0013953333,0.00040267943,0.01886348,0.0012639636,0.00006730222,0.0015393472,0.0011802495,0.0075487676,0.5896818,0.0009785097,0.0039686393,0.37310997],"study_design_scores_gemma":[0.00015049039,0.002315282,0.08372892,0.0001457243,0.00015386255,0.0017532847,0.0009382876,0.0057614753,0.79538435,0.0008368981,0.10871849,0.000112949034],"about_ca_topic_score_codex":0.008082801,"about_ca_topic_score_gemma":0.008653954,"teacher_disagreement_score":0.012218953,"about_ca_system_score_codex":0.00093975227,"about_ca_system_score_gemma":0.0015796159,"threshold_uncertainty_score":0.04087645},"labels":[],"label_agreement":null},{"id":"W2110189591","doi":"10.1061/(asce)hy.1943-7900.0000316","title":"Analysis of the Stability of Floating Ice Blocks","year":2011,"lang":"en","type":"article","venue":"Journal of Hydraulic Engineering","topic":"Engineering Diagnostics and Reliability","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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Geology; Stability (learning theory); Hydrology (agriculture); Geotechnical engineering; Environmental science; Geomorphology; Computer science","score_opus":0.010559852296199398,"score_gpt":0.18570042112697335,"score_spread":0.17514056883077395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110189591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969091,0.000049158352,0.0023185192,0.0000053616836,0.0000015758632,0.000004809355,0.00008681845,0.000015662405,0.0006090232],"genre_scores_gemma":[0.9992036,0.000030027717,0.00050987105,0.000001124187,0.0000014149374,0.000002765994,0.000083395375,0.0000022058127,0.00016560432],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99992096,0.000003175236,0.0000033698504,0.000012876237,0.00004214051,0.000017426633],"domain_scores_gemma":[0.99978024,0.000056618846,0.00006180166,0.000015096321,0.00006137711,0.000024797224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010682409,0.00014367944,0.0001449855,0.000718938,0.00022132859,0.0001761101,0.00017664944,0.00013565602,0.0007300743],"category_scores_gemma":[0.00047743312,0.000073852505,0.0001100395,0.00024475684,0.00023998438,0.00018776608,0.0001688716,0.00013619105,0.00009685516],"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":[0.00038268292,0.00004520036,0.056168225,0.00007397008,0.000039945062,0.00044168037,0.00021753293,0.028900243,0.88332593,0.0006612143,0.00014010133,0.029603338],"study_design_scores_gemma":[0.000017001837,0.00065370515,0.42902714,0.000014107444,0.000041044143,0.0005145012,0.0003361797,0.22962381,0.33793733,0.00048554828,0.0013076528,0.00004199144],"about_ca_topic_score_codex":0.0025160438,"about_ca_topic_score_gemma":0.0022712152,"teacher_disagreement_score":0.0025160438,"about_ca_system_score_codex":0.00021151113,"about_ca_system_score_gemma":0.0001234201,"threshold_uncertainty_score":0.0050027966},"labels":[],"label_agreement":null},{"id":"W2214078153","doi":"10.3968/8045","title":"Discussions of General Methods for Measurement and Monitoring of Corrosion in the Oil & Gas Industry","year":2015,"lang":"en","type":"article","venue":"Advances in petroleum exploration and development","topic":"Engineering Diagnostics and Reliability","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":"Pipeline transport; Corrosion; Leakage (economics); Petroleum engineering; Engineering; Pipeline (software); Forensic engineering; Crude oil; Petroleum industry; Fossil fuel; Waste management; Environmental science; Mechanical engineering; Environmental engineering; Metallurgy; Materials science","score_opus":0.0520831185147057,"score_gpt":0.32310555627135334,"score_spread":0.27102243775664764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2214078153","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036416277,0.43774572,0.47506455,0.017478183,0.007406177,0.00086942705,0.00084624847,0.0009976047,0.05595047],"genre_scores_gemma":[0.055033628,0.4937935,0.37352845,0.01155874,0.0063768355,0.0027123035,0.00092734944,0.0003526743,0.05571652],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99588335,0.001253106,0.00045018617,0.00066578906,0.0015733773,0.0001741942],"domain_scores_gemma":[0.99830794,0.00078820204,0.00022343136,0.00019878312,0.00044024515,0.00004152899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046144123,0.0019066092,0.0012867012,0.0045452616,0.0013054264,0.0027533863,0.0030793415,0.005206584,0.003598137],"category_scores_gemma":[0.004311309,0.0012424262,0.0017287689,0.003903924,0.0033556614,0.0037363076,0.002018913,0.005085173,0.0042510997],"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":[0.000144862,0.00040319498,0.0035734538,0.010013965,0.00014371767,0.0015838394,0.0022330456,0.0062119947,0.046808053,0.43949798,0.086135276,0.4032507],"study_design_scores_gemma":[0.000010038171,0.0002635972,0.0036378086,0.0020448081,0.00005008848,0.0028311359,0.00044372128,0.0047160657,0.015772576,0.07398372,0.8961153,0.00013112943],"about_ca_topic_score_codex":0.0020449872,"about_ca_topic_score_gemma":0.001796539,"teacher_disagreement_score":0.005206584,"about_ca_system_score_codex":0.0018711123,"about_ca_system_score_gemma":0.001191638,"threshold_uncertainty_score":0.024403632},"labels":[],"label_agreement":null},{"id":"W2232198394","doi":"10.5539/mas.v10n2p172","title":"New Flow Stabilizers as a Method to Improve the Reliability and Efficiency of Power Equipment","year":2016,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Engineering Diagnostics and Reliability","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":"Ministry of Education and Science of the Russian Federation","keywords":"Reliability (semiconductor); Flow (mathematics); Flow resistance; Pipeline (software); Turbine; Computer science; Environmental science; Power (physics); Steam turbine; Reliability engineering; Automotive engineering; Mechanical engineering; Mechanics; Engineering","score_opus":0.00447956266160309,"score_gpt":0.22655225739455495,"score_spread":0.22207269473295185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2232198394","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":[0.39024356,0.009104548,0.5905675,0.00043375383,0.00036424285,0.00020215489,0.00012882582,0.0019118069,0.007043552],"genre_scores_gemma":[0.9271196,0.0014149622,0.06732393,0.00006233118,0.00012591026,0.000046303725,0.000069292895,0.00006565607,0.0037720166],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996935,0.000059807582,0.000022695116,0.00005292709,0.00015171496,0.000019430923],"domain_scores_gemma":[0.99975175,0.00006861205,0.000082841616,0.00002941628,0.000054837587,0.000012570699],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040656806,0.00043988886,0.00030462726,0.0009413913,0.000259519,0.00050789065,0.00040102142,0.0003576299,0.0014546611],"category_scores_gemma":[0.0005956446,0.00019346259,0.00027837366,0.00027786085,0.00047592103,0.00090943626,0.00029028894,0.00033189726,0.00024954687],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000465099,0.000116998555,0.0015105143,0.00054053526,0.00003674928,0.00024318384,0.00027299343,0.013123645,0.8041079,0.007927737,0.0010264964,0.17062815],"study_design_scores_gemma":[0.00009214929,0.0023930878,0.0039650607,0.0001080757,0.00013098003,0.00064062385,0.000091891634,0.08561355,0.8716138,0.0018431976,0.03343129,0.00007632147],"about_ca_topic_score_codex":0.00023224908,"about_ca_topic_score_gemma":0.00039098834,"teacher_disagreement_score":0.0014546611,"about_ca_system_score_codex":0.0002799098,"about_ca_system_score_gemma":0.00018768375,"threshold_uncertainty_score":0.004866302},"labels":[],"label_agreement":null},{"id":"W2233390774","doi":"","title":"Social sustainability through occupational health and safety prevention in the construction industry","year":2010,"lang":"en","type":"article","venue":"Espace ÉTS (ETS)","topic":"Engineering Diagnostics and Reliability","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":"Rebar; Installation; Engineering; Work (physics); Occupational safety and health; Agency (philosophy); Forensic engineering; Architectural engineering; Mechanical engineering; Structural engineering; Political science; Sociology; Law","score_opus":0.00835735562990002,"score_gpt":0.2769486700916218,"score_spread":0.26859131446172174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2233390774","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":[0.15645723,0.11806175,0.0070540896,0.23883325,0.002580206,0.00044995706,0.000831444,0.000498398,0.4752336],"genre_scores_gemma":[0.8730053,0.074491225,0.005356374,0.01391833,0.0009351586,0.00040523487,0.00048639128,0.000056876477,0.03134512],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99697435,0.0016522106,0.00011276509,0.00019631894,0.00051765493,0.00054657715],"domain_scores_gemma":[0.997027,0.0010685086,0.0004486458,0.00012141217,0.0004775821,0.0008569017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004887045,0.00035500788,0.00039449157,0.0037093246,0.0028263382,0.0073723444,0.0006675912,0.001758458,0.009127073],"category_scores_gemma":[0.004889362,0.00019825867,0.0006844576,0.003274708,0.0029678238,0.0026574086,0.006828995,0.001217492,0.0010807815],"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":[0.00009144035,0.0013269793,0.037374005,0.0041992916,0.00020717357,0.00035586677,0.028613372,0.0006128453,0.0005532047,0.06045196,0.060511947,0.8057019],"study_design_scores_gemma":[0.0001070908,0.00041664112,0.114222325,0.010761684,0.0002646938,0.00026433787,0.06555673,0.00052307366,0.0011687736,0.08025,0.7263978,0.00006679386],"about_ca_topic_score_codex":0.016993465,"about_ca_topic_score_gemma":0.02348637,"teacher_disagreement_score":0.016993465,"about_ca_system_score_codex":0.0050015445,"about_ca_system_score_gemma":0.022639485,"threshold_uncertainty_score":0.036288917},"labels":[],"label_agreement":null},{"id":"W2235090753","doi":"10.1038/529156e","title":"Monitor safety of aged fuel pipelines","year":2016,"lang":"en","type":"letter","venue":"Nature","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":58,"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":"Pipeline transport; Business; Forensic engineering; Environmental science; Engineering; Environmental engineering","score_opus":0.0032076917688115816,"score_gpt":0.20081517390551198,"score_spread":0.1976074821367004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2235090753","genre_codex":"commentary","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051186224,0.000795916,0.001623266,0.97020155,0.009025381,0.000022292104,0.000067309076,0.00011525822,0.013030423],"genre_scores_gemma":[0.08542614,0.0011776375,0.001983364,0.85443604,0.0136465905,0.000059967108,0.00005070308,0.000079276026,0.043140307],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980185,0.0005129303,0.00019603824,0.00022336617,0.0007864623,0.0002627057],"domain_scores_gemma":[0.99416566,0.0032865428,0.00054116134,0.00029116418,0.001168433,0.00054703304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022535697,0.00035403026,0.00033482877,0.0002649187,0.0021689353,0.0017845419,0.0010805941,0.03163025,0.002962226],"category_scores_gemma":[0.01929909,0.0003847411,0.0004967379,0.00017598284,0.0014040819,0.0015021489,0.00089771603,0.01519619,0.0021732831],"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":[0.00024764476,0.00015870605,0.0061248527,0.00009119704,0.000040784944,0.008079665,0.0009411892,0.0008107277,0.004364126,0.014306068,0.9085486,0.056286477],"study_design_scores_gemma":[0.000097583295,0.00023807403,0.003759437,0.00020845026,0.00005997227,0.0045467177,0.0009090413,0.0036457817,0.0049266666,0.03251667,0.9490166,0.00007501247],"about_ca_topic_score_codex":0.0045982464,"about_ca_topic_score_gemma":0.0093044285,"teacher_disagreement_score":0.03163025,"about_ca_system_score_codex":0.002121823,"about_ca_system_score_gemma":0.0020457134,"threshold_uncertainty_score":0.015394986},"labels":[],"label_agreement":null},{"id":"W2245107911","doi":"10.1109/tdei.2015.005179","title":"Strategies to maximize life of rotating machines windings","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Dielectrics and Electrical Insulation","topic":"Engineering Diagnostics and Reliability","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":"Manitoba Hydro","funders":"","keywords":"Electromagnetic coil; Reliability (semiconductor); Reliability engineering; Engineering; Quality (philosophy); Automotive engineering; Computer science; Electrical engineering; Power (physics)","score_opus":0.016420505971173345,"score_gpt":0.232377384285557,"score_spread":0.21595687831438365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2245107911","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13977917,0.0062632365,0.7523809,0.0023341503,0.00023377649,0.000268895,0.00010619056,0.0012863508,0.09734733],"genre_scores_gemma":[0.9259159,0.0019801029,0.06116614,0.0004011862,0.00012721452,0.00015672173,0.00006459287,0.0002032812,0.009984744],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994535,0.00015574665,0.00003133674,0.00009378971,0.00017904681,0.00008654737],"domain_scores_gemma":[0.999186,0.00022090875,0.00014746208,0.000080841244,0.00028031302,0.00008458044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091987354,0.0009978005,0.0004991997,0.0010286625,0.00047222813,0.0010788209,0.00083037536,0.00071081327,0.0039057676],"category_scores_gemma":[0.0025784294,0.00022773324,0.00025796928,0.0003335884,0.00042636532,0.0017812533,0.0010168125,0.00043339183,0.0015939578],"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":[0.00066685467,0.00023572845,0.0026311395,0.000947973,0.00009116223,0.00048188496,0.0010101286,0.19426335,0.14363997,0.1626782,0.009959096,0.48339456],"study_design_scores_gemma":[0.00034824884,0.0030847767,0.005742986,0.0008720052,0.0002239392,0.00209708,0.0013920949,0.38545746,0.18995638,0.25064012,0.16001056,0.00017434715],"about_ca_topic_score_codex":0.00027058725,"about_ca_topic_score_gemma":0.0005747845,"teacher_disagreement_score":0.0039057676,"about_ca_system_score_codex":0.0006940422,"about_ca_system_score_gemma":0.00060470996,"threshold_uncertainty_score":0.013066113},"labels":[],"label_agreement":null},{"id":"W2249658000","doi":"","title":"A Statistical Analysis and Model of the Residual Value of Different Types of Heavy Construction Equipment","year":2003,"lang":"en","type":"dissertation","venue":"VTechWorks (Virginia Tech)","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":24,"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":"Residual; Statistics; Value (mathematics); Econometrics; Mathematics; Engineering; Computer science; Algorithm","score_opus":0.003973096745061567,"score_gpt":0.20995543873183564,"score_spread":0.20598234198677406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2249658000","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40820432,0.0006089654,0.5760291,0.001087241,0.00016912232,0.0007646851,0.007541092,0.0013006981,0.0042948164],"genre_scores_gemma":[0.90706533,0.00041058997,0.072747245,0.00013700612,0.000085476946,0.0012705371,0.009136063,0.00017628462,0.008971475],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99297535,0.0024886674,0.00047920045,0.002410971,0.0010721881,0.00057361915],"domain_scores_gemma":[0.95345235,0.03440626,0.004929661,0.0036554665,0.0030821948,0.00047399767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021446377,0.0009870459,0.0012872308,0.0027767944,0.00054736837,0.00286559,0.0035234904,0.001331055,0.0048252726],"category_scores_gemma":[0.038363975,0.0006166547,0.0031808987,0.003987891,0.0018992679,0.002931241,0.0013821675,0.0026117929,0.001680025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074259227,0.0006081312,0.3631211,0.00049616705,0.0016890253,0.00086340413,0.001529125,0.4217346,0.0028597023,0.08434761,0.010474724,0.111533865],"study_design_scores_gemma":[0.000029838766,0.0004957969,0.07713329,0.000085522646,0.00013272725,0.00021105478,0.00046218734,0.8956785,0.0009487232,0.020256149,0.0045023775,0.00006385418],"about_ca_topic_score_codex":0.012881488,"about_ca_topic_score_gemma":0.005724368,"teacher_disagreement_score":0.021446377,"about_ca_system_score_codex":0.0024591954,"about_ca_system_score_gemma":0.0026080506,"threshold_uncertainty_score":0.113420665},"labels":[],"label_agreement":null},{"id":"W2333671411","doi":"10.1115/gt2014-27312","title":"Risk Based Assessment of Gas Turbines in Pipeline Service","year":2014,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Pipeline (software); Reliability engineering; Risk assessment; Risk analysis (engineering); Computer science; Work (physics); Gas pipeline; Service (business); Engineering; Petroleum engineering; Mechanical engineering; Business; Computer security","score_opus":0.0034191062051229138,"score_gpt":0.20875742651508059,"score_spread":0.20533832030995766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2333671411","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38174224,0.0015931966,0.6105746,0.00018517632,0.000030429155,0.00013048066,0.00037003524,0.00037738465,0.0049964627],"genre_scores_gemma":[0.97758114,0.0004199216,0.02080498,0.000013971778,0.000013064516,0.000048273458,0.00016942194,0.000025921801,0.00092336553],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989219,0.00043930512,0.000053308144,0.000087017885,0.00045080588,0.000047607347],"domain_scores_gemma":[0.9980708,0.0011189119,0.00037873763,0.00008604349,0.0003012128,0.00004432909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001994951,0.0009809798,0.00058520294,0.0014494212,0.00020738262,0.00085836067,0.00062126666,0.0007862981,0.00089030183],"category_scores_gemma":[0.0052032555,0.00027259503,0.00050830864,0.0006460281,0.00040660915,0.0012149388,0.00068477145,0.0004060715,0.00013488391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054559412,0.000019891135,0.0035405618,0.00004812611,0.00003108814,0.00010064809,0.00005166675,0.9744931,0.0033512495,0.0040023043,0.00014824225,0.014158573],"study_design_scores_gemma":[0.000003849704,0.0001353309,0.0038113222,0.000016084352,0.000020069674,0.00015164586,0.000062906336,0.98710895,0.002341704,0.005665211,0.00065957604,0.000023284028],"about_ca_topic_score_codex":0.0015373125,"about_ca_topic_score_gemma":0.0010914999,"teacher_disagreement_score":0.001994951,"about_ca_system_score_codex":0.00086687924,"about_ca_system_score_gemma":0.0005038331,"threshold_uncertainty_score":0.010550439},"labels":[],"label_agreement":null},{"id":"W2343564205","doi":"10.5267/j.esm.2016.1.001","title":"Campbell diagram analysis of open cracked rotor","year":2016,"lang":"en","type":"article","venue":"Engineering Solid Mechanics","topic":"Engineering Diagnostics and Reliability","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":"Diagram; Rotor (electric); Materials science; Structural engineering; Engineering drawing; Computer science; Mechanical engineering; Engineering; Database","score_opus":0.006774997904466819,"score_gpt":0.23100447032451346,"score_spread":0.22422947242004665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2343564205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48531726,0.001926844,0.45727497,0.0003308335,0.00018140157,0.00016151494,0.0010447336,0.002518991,0.051243484],"genre_scores_gemma":[0.97657555,0.0002618101,0.016057808,0.0000266574,0.00001098401,0.00002497465,0.00022812672,0.00009423321,0.006719933],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997508,0.00002028832,0.000006182604,0.000041906285,0.00015866177,0.000022147704],"domain_scores_gemma":[0.99938977,0.00019143852,0.00007912415,0.000033936558,0.0002813433,0.000024388703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018483125,0.00021129243,0.0002507795,0.0012573615,0.0002569038,0.00042038804,0.00042064782,0.0006291338,0.006432767],"category_scores_gemma":[0.0011725064,0.00016033776,0.00015879497,0.0005214327,0.00029497794,0.0005707339,0.00021068871,0.00027718558,0.0006931971],"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":[0.0005766057,0.00010500259,0.009765897,0.0006195422,0.00003309013,0.0022162045,0.0008988249,0.26095286,0.4644826,0.10749836,0.011649113,0.14120178],"study_design_scores_gemma":[0.000013926468,0.00018195916,0.010238435,0.000040461462,0.0000102756885,0.00073506124,0.00023836015,0.9280954,0.037308555,0.008717746,0.0143597545,0.000060075334],"about_ca_topic_score_codex":0.0027915346,"about_ca_topic_score_gemma":0.0018523566,"teacher_disagreement_score":0.006432767,"about_ca_system_score_codex":0.00038534586,"about_ca_system_score_gemma":0.00035211354,"threshold_uncertainty_score":0.02151978},"labels":[],"label_agreement":null},{"id":"W2344645139","doi":"10.14288/1.0076365","title":"Telematics data-driven prognostics system for construction heavy equipment health monitoring and assessment","year":2015,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Engineering Diagnostics and Reliability","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 British Columbia","funders":"","keywords":"Prognostics; Telematics; Computer science; Engineering; Systems engineering; Reliability engineering; Telecommunications","score_opus":0.02378521400790841,"score_gpt":0.22496644550948353,"score_spread":0.20118123150157513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2344645139","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13782418,0.00039496648,0.80175626,0.0003312789,0.00020907489,0.00040502485,0.0036836383,0.049897056,0.0054985518],"genre_scores_gemma":[0.9270171,0.00016851324,0.06666967,0.00016930417,0.000061674946,0.00029000724,0.0019808167,0.00015048547,0.0034924166],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997235,0.000037591406,0.000024655468,0.00007508312,0.000121931786,0.000017193031],"domain_scores_gemma":[0.99924386,0.00016037581,0.00012385534,0.0001371542,0.00028956516,0.00004522098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005420408,0.0005948319,0.00049677055,0.0010951343,0.00021817756,0.0004435828,0.0008542744,0.0004616776,0.004757972],"category_scores_gemma":[0.0013874221,0.00018108905,0.00020371852,0.00055151084,0.00014142579,0.00052545685,0.00044932312,0.00041032326,0.0012945043],"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":[0.0019135101,0.0006818228,0.047450814,0.00048581752,0.00016679017,0.00064918643,0.0004360176,0.11145792,0.08056471,0.003402193,0.026163671,0.7266275],"study_design_scores_gemma":[0.00012869819,0.0004942635,0.016138606,0.000059625236,0.000081259626,0.00035335193,0.000065702705,0.9277266,0.0407318,0.0018841528,0.012274057,0.00006184011],"about_ca_topic_score_codex":0.0017834286,"about_ca_topic_score_gemma":0.0017557414,"teacher_disagreement_score":0.004757972,"about_ca_system_score_codex":0.00049134233,"about_ca_system_score_gemma":0.00051740586,"threshold_uncertainty_score":0.015917003},"labels":[],"label_agreement":null},{"id":"W23512826","doi":"10.1007/978-1-4614-6555-3_52","title":"Condition Assessment of a Coal Mine Shiploader","year":2013,"lang":"en","type":"book-chapter","venue":"Conference proceedings of the Society for Experimental Mechanics","topic":"Engineering Diagnostics and Reliability","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","funders":"","keywords":"Mining engineering; Coal mining; Coal; Forensic engineering; Environmental science; Geology; Petroleum engineering; History; Engineering; Archaeology","score_opus":0.016268533389762432,"score_gpt":0.2464470606665197,"score_spread":0.23017852727675725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W23512826","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97241694,0.00020735296,0.016824575,0.00020702773,0.000059815113,0.000108090564,0.00053429545,0.00083329994,0.008808623],"genre_scores_gemma":[0.99101615,0.000056858156,0.0018157049,0.000023807484,0.000006341289,0.000015291465,0.00021485463,0.000025674753,0.006825234],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99982554,0.000014573749,0.0000080810605,0.000036767487,0.00009682972,0.000018295603],"domain_scores_gemma":[0.999866,0.000032080137,0.000012007473,0.00001220203,0.000059576283,0.000018104945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019887969,0.0004196763,0.00043783226,0.00073626963,0.0006040593,0.0005821288,0.00058885425,0.00075566303,0.0062715695],"category_scores_gemma":[0.00038081803,0.00017869406,0.00023821465,0.0002979891,0.00026942522,0.00048718232,0.00043669555,0.00034998235,0.001029167],"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":[0.0046506408,0.000715174,0.059765004,0.00033857356,0.000093280236,0.0040673856,0.0012673377,0.115427114,0.49608424,0.00093352987,0.009933253,0.30672446],"study_design_scores_gemma":[0.0001443143,0.002992076,0.1993839,0.000065384396,0.00016440536,0.00092561665,0.0015596591,0.6533872,0.13157867,0.0011748928,0.008496634,0.00012721113],"about_ca_topic_score_codex":0.0049728584,"about_ca_topic_score_gemma":0.0076912423,"teacher_disagreement_score":0.0062715695,"about_ca_system_score_codex":0.0004168804,"about_ca_system_score_gemma":0.00027340295,"threshold_uncertainty_score":0.020980477},"labels":[],"label_agreement":null},{"id":"W2372381197","doi":"","title":"Discussing on Pipelines Synthesis in Residence Quarter Works","year":2007,"lang":"en","type":"article","venue":"Municipal Engineering Technology","topic":"Engineering Diagnostics and Reliability","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":"Quarter (Canadian coin); Residence; Pipeline transport; Forensic engineering; Environmental science; Engineering; Geography; Archaeology; Environmental engineering; Sociology; Demography","score_opus":0.0059126099797634345,"score_gpt":0.21415883973094593,"score_spread":0.2082462297511825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2372381197","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":[0.17885348,0.00450417,0.08711852,0.033668093,0.0024778368,0.00033014404,0.00064658246,0.0015611753,0.69084],"genre_scores_gemma":[0.6754609,0.0018009084,0.015076003,0.0021875508,0.00031311423,0.000038352235,0.00027010596,0.00030499004,0.30454805],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99912554,0.0002496343,0.000044752476,0.00013076565,0.00029935065,0.00015002555],"domain_scores_gemma":[0.99927276,0.00023367286,0.00004879889,0.000096284224,0.0002872132,0.000061291576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013569955,0.00032094293,0.0002322823,0.0011564493,0.0048263106,0.0025436203,0.0006833968,0.0017771553,0.026994765],"category_scores_gemma":[0.0025653495,0.0003144164,0.00069488434,0.001364959,0.0012621123,0.0023856019,0.0011104594,0.0011706728,0.0022538076],"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":[0.0004946573,0.00021576125,0.015617125,0.00080864225,0.000039348015,0.0036666978,0.03234489,0.021728454,0.02090686,0.37399772,0.12570241,0.4044774],"study_design_scores_gemma":[0.000024813518,0.00013418258,0.00915356,0.00017363987,0.00005353105,0.00054922333,0.018805312,0.0057293125,0.019769602,0.031944364,0.91361237,0.000050038238],"about_ca_topic_score_codex":0.02533684,"about_ca_topic_score_gemma":0.047698848,"teacher_disagreement_score":0.026994765,"about_ca_system_score_codex":0.0038706188,"about_ca_system_score_gemma":0.0027721003,"threshold_uncertainty_score":0.09030646},"labels":[],"label_agreement":null},{"id":"W2373176032","doi":"","title":"The study of field diesel gen-sets' reliability","year":2003,"lang":"en","type":"article","venue":"Movable Power Station & Vehicle","topic":"Engineering Diagnostics and Reliability","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":"Reliability (semiconductor); Field (mathematics); Reliability engineering; Diesel fuel; Environmental science; Engineering; Automotive engineering; Mathematics; Physics","score_opus":0.005501293158529525,"score_gpt":0.21616492420836098,"score_spread":0.21066363104983146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2373176032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96170783,0.0005511276,0.028832693,0.00012995076,0.00004968296,0.00003279168,0.000195918,0.00012965477,0.008370374],"genre_scores_gemma":[0.9975479,0.00010853639,0.0009837052,0.000009484464,0.000014604742,0.000007694859,0.00007508065,0.0000088648585,0.0012440347],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.999574,0.0000980836,0.000013825693,0.00007042592,0.00020798067,0.000035772002],"domain_scores_gemma":[0.9979716,0.0012041208,0.0001500609,0.00013019402,0.0005089618,0.0000350605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076248427,0.00032024542,0.00020689123,0.00073920266,0.00024723288,0.00023458473,0.0003140922,0.00033426489,0.0013610427],"category_scores_gemma":[0.002544454,0.0001673496,0.00027448006,0.0003664601,0.00029779773,0.00050337944,0.00018046351,0.00036282866,0.00025227017],"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":[0.0011577108,0.0002901515,0.12233543,0.0006948355,0.00031296193,0.0020747252,0.0016016723,0.36020434,0.21611851,0.036708176,0.006101758,0.25239965],"study_design_scores_gemma":[0.00007482096,0.0027161979,0.18011653,0.00010448008,0.0001505347,0.0025943944,0.00058686634,0.60874283,0.170105,0.012459408,0.022248436,0.00010044514],"about_ca_topic_score_codex":0.0015486033,"about_ca_topic_score_gemma":0.0015673648,"teacher_disagreement_score":0.0015486033,"about_ca_system_score_codex":0.0006002028,"about_ca_system_score_gemma":0.00023446779,"threshold_uncertainty_score":0.004553139},"labels":[],"label_agreement":null},{"id":"W2464547027","doi":"10.1007/s11665-016-2202-5","title":"Erratum to: Initiation of Stress Corrosion Cracks in X80 and X100 Pipe Steels in Near-Neutral pH Environment","year":2016,"lang":"en","type":"erratum","venue":"Journal of Materials Engineering and Performance","topic":"Engineering Diagnostics and Reliability","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":"Natural Resources Canada","funders":"","keywords":"Materials science; Metallurgy; Corrosion; Stress (linguistics); Stress corrosion cracking; Forensic engineering; Engineering","score_opus":0.004670775996286877,"score_gpt":0.18597503289318526,"score_spread":0.18130425689689839,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2464547027","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":[0.005064374,0.003041335,0.0013838859,0.020861903,0.9579351,0.00006949976,0.0014268963,0.00046618504,0.009750773],"genre_scores_gemma":[0.07347123,0.025001906,0.014331019,0.038956992,0.12871262,0.0003033895,0.008415805,0.001393713,0.7094133],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981894,0.00007900304,0.00042513496,0.00019778646,0.00095434225,0.00015428221],"domain_scores_gemma":[0.9943445,0.0009573355,0.0006738527,0.00040134796,0.0032679327,0.00035510218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001038637,0.0025746857,0.0016297974,0.0023675065,0.0029990815,0.0014051669,0.0024237852,0.0055691698,0.033032645],"category_scores_gemma":[0.009357442,0.0010985845,0.0012340043,0.0018252035,0.0013404359,0.0015600949,0.0012705517,0.0031214962,0.027830882],"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":[0.00030687233,0.00010986403,0.00067765516,0.0006317971,0.00002717648,0.003852075,0.00013082646,0.00030750452,0.0028273857,0.00085853465,0.9652062,0.025064059],"study_design_scores_gemma":[0.00010803626,0.0003677849,0.008709608,0.000612185,0.00017307086,0.0043822043,0.0006757513,0.00080299395,0.011467423,0.0017202949,0.97083426,0.00014635675],"about_ca_topic_score_codex":0.008290673,"about_ca_topic_score_gemma":0.013732262,"teacher_disagreement_score":0.033032645,"about_ca_system_score_codex":0.0017223221,"about_ca_system_score_gemma":0.002864014,"threshold_uncertainty_score":0.11050522},"labels":[],"label_agreement":null},{"id":"W2464730673","doi":"10.2316/journal.206.2016.4.206-4112","title":"A CONTROL APPROACH FOR HUMAN-MECHATRONIC-HYDRAULICCOUPLED EXOSKELETON IN OVERLOAD-CARRYING CONDITION","year":2016,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":9,"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":"Exoskeleton; Mechatronics; Computer science; Control (management); Control engineering; Engineering; Artificial intelligence; Simulation","score_opus":0.005740779590923214,"score_gpt":0.23669542477373853,"score_spread":0.23095464518281533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2464730673","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018843377,0.0002640496,0.9725811,0.00012521542,0.00010988482,0.000113730086,0.000018600555,0.0002484757,0.007695638],"genre_scores_gemma":[0.9342683,0.00029004904,0.056341916,0.0000972694,0.000081639686,0.00023093296,0.000035592748,0.000027799719,0.008626513],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999754,0.000036703903,0.000018086592,0.0000853292,0.00007704911,0.000028880195],"domain_scores_gemma":[0.9998492,0.000034721266,0.000021245603,0.0000121071935,0.00007096465,0.000011855843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004659071,0.0007132568,0.00054058374,0.00035377083,0.0006648758,0.00084433943,0.000860676,0.0008337216,0.0029289243],"category_scores_gemma":[0.00036063165,0.00021218011,0.00043524432,0.00021444052,0.00048747525,0.0004796823,0.0010214512,0.00034856139,0.00035356163],"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":[0.00041559624,0.00031844788,0.001004256,0.0010353571,0.00017161004,0.0009108732,0.0009532104,0.4799473,0.20800266,0.026762925,0.0025811505,0.27789664],"study_design_scores_gemma":[0.000037779577,0.0004840916,0.0006688571,0.000027486565,0.00006492245,0.00012609069,0.00010010253,0.9825612,0.009815008,0.0029266889,0.0031679745,0.000019811485],"about_ca_topic_score_codex":0.0037542935,"about_ca_topic_score_gemma":0.004105817,"teacher_disagreement_score":0.0037542935,"about_ca_system_score_codex":0.0002669562,"about_ca_system_score_gemma":0.0005324107,"threshold_uncertainty_score":0.009798169},"labels":[],"label_agreement":null},{"id":"W2510323784","doi":"10.1016/j.cjca.2015.07.340","title":"COMPARISON OF A NOVEL FREE BREATHING STEADY STATE FREE PRECESSION (SSFP) SEQUENCE WITH TRADITIONAL BREATH HELD SSFP IN THE QUALITATIVE ASSESSMENT OF LEFT VENTRICULAR FUNCTION","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Toronto Public Health","funders":"","keywords":"Steady-state free precession imaging; Medicine; Coronary artery disease; Magnetic resonance imaging; Image quality; Gating; Nuclear medicine; Cardiology; Radiology; Artificial intelligence; Image (mathematics); Computer science","score_opus":0.06092176582226039,"score_gpt":0.3194570847735192,"score_spread":0.2585353189512588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2510323784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8778059,0.0032680773,0.11588719,0.00040315534,0.00023860912,0.00021554073,0.00023086465,0.0002045839,0.0017461338],"genre_scores_gemma":[0.90544593,0.001898198,0.09099519,0.00023306045,0.00019458894,0.000099251236,0.00024194224,0.00010072331,0.0007910388],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9995871,0.00015437923,0.0000376585,0.000077845456,0.00011067722,0.00003232279],"domain_scores_gemma":[0.99833256,0.0007386762,0.000100136254,0.00007773493,0.0005199655,0.00023100335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024535041,0.00033269625,0.00036553928,0.0006761534,0.00023418294,0.00089009403,0.00047323052,0.0015759463,0.0011564272],"category_scores_gemma":[0.0043910122,0.00024980825,0.0001937936,0.00022617845,0.0004565241,0.0014072211,0.00047958948,0.00058247795,0.0002448696],"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":[0.0077356854,0.0004196266,0.008713912,0.0008233052,0.00015383118,0.0010769363,0.00031622787,0.0018032872,0.8515645,0.0005773309,0.00052094494,0.1262944],"study_design_scores_gemma":[0.0014472629,0.019070927,0.20828933,0.00050735724,0.0012997986,0.049469218,0.0010871975,0.16242842,0.54509497,0.0021965187,0.008713899,0.0003951287],"about_ca_topic_score_codex":0.0006425379,"about_ca_topic_score_gemma":0.001426423,"teacher_disagreement_score":0.0024535041,"about_ca_system_score_codex":0.00018502523,"about_ca_system_score_gemma":0.00044750076,"threshold_uncertainty_score":0.012975514},"labels":[],"label_agreement":null},{"id":"W2518636877","doi":"10.5220/0005921600150023","title":"A Systematic Assessment of Operational Metrics for Modeling Operator Functional State","year":2016,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Université Laval; Thales (Canada)","funders":"","keywords":"Computer science; Operator (biology)","score_opus":0.01482058113305096,"score_gpt":0.23789580581518446,"score_spread":0.2230752246821335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2518636877","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":[0.097909145,0.0011960649,0.89350295,0.00044573046,0.000042346997,0.0007799032,0.0013260926,0.0014579134,0.0033397488],"genre_scores_gemma":[0.5118943,0.0005608715,0.48492882,0.00004962759,0.000022898455,0.0005105666,0.0015526946,0.0001494754,0.00033072286],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9826182,0.007818067,0.0019989808,0.0012170919,0.006013235,0.00033441986],"domain_scores_gemma":[0.9323078,0.03073244,0.008969506,0.009364691,0.017941263,0.0006842823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01839279,0.0020764917,0.0016326482,0.008110611,0.00084404217,0.003961779,0.0019368394,0.0012336592,0.0006967334],"category_scores_gemma":[0.07779413,0.00056508475,0.0014006058,0.0038042197,0.0008873732,0.0051368563,0.0019943055,0.0011645756,0.00022010862],"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":[0.0002884249,0.0007650378,0.110538885,0.0014702494,0.0007445602,0.00018698757,0.0008551356,0.27885678,0.014950331,0.044132803,0.0037734364,0.54343736],"study_design_scores_gemma":[0.000034798944,0.00095794495,0.021789718,0.00058538484,0.0002851817,0.0002633988,0.0004677359,0.93976086,0.009313308,0.022584282,0.0038535697,0.00010383222],"about_ca_topic_score_codex":0.0048539587,"about_ca_topic_score_gemma":0.006554173,"teacher_disagreement_score":0.01839279,"about_ca_system_score_codex":0.0021471526,"about_ca_system_score_gemma":0.005780191,"threshold_uncertainty_score":0.0972715},"labels":[],"label_agreement":null},{"id":"W2527718235","doi":"10.36001/phmconf.2015.v7i1.2724","title":"A New Generic Approach to Convert FMEA in Causal Trees for the Purpose of Hydro-Generator Rotor Failure Mechanisms Identification","year":2015,"lang":"en","type":"article","venue":"Annual Conference of the PHM Society","topic":"Engineering Diagnostics and Reliability","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":"Hydro-Québec; École de Technologie Supérieure","funders":"","keywords":"Identification (biology); Generator (circuit theory); Failure mode and effects analysis; Stator; Computer science; Reliability engineering; Fault tree analysis; Root cause; Rotor (electric); Component (thermodynamics); Root cause analysis; Data mining; Artificial intelligence; Engineering; Mechanical engineering","score_opus":0.025290178323483178,"score_gpt":0.22357158286180134,"score_spread":0.19828140453831816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527718235","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003507254,0.000040229002,0.99548775,0.00003939526,0.000031789186,0.00006951585,0.00045293165,0.0024758764,0.0010517954],"genre_scores_gemma":[0.012669062,0.0001482084,0.9825517,0.00008627524,0.000039401228,0.00023355735,0.0013988565,0.00081276236,0.0020601165],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887615,0.00026666172,0.00015360133,0.00029927507,0.00033318545,0.000071091454],"domain_scores_gemma":[0.99782026,0.0009374237,0.0001634507,0.0006172049,0.00040931808,0.000052367835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020821057,0.0014156624,0.0007046866,0.0032642176,0.00066940987,0.0024547812,0.0017456391,0.0012354673,0.02148139],"category_scores_gemma":[0.007140716,0.00074848003,0.0030573225,0.0021336693,0.00096411066,0.002385334,0.0016861237,0.0022847326,0.0062859543],"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":[0.00014834541,0.00021713268,0.0022290298,0.0014755963,0.00030363846,0.00084905716,0.001272512,0.070464216,0.023549765,0.2656804,0.024739986,0.60907036],"study_design_scores_gemma":[0.000079708436,0.00017882138,0.0017638672,0.0004968763,0.00022978228,0.0013917417,0.0003873967,0.44123003,0.02008503,0.2631548,0.270871,0.00013092863],"about_ca_topic_score_codex":0.0028366984,"about_ca_topic_score_gemma":0.0037056224,"teacher_disagreement_score":0.02148139,"about_ca_system_score_codex":0.00071594917,"about_ca_system_score_gemma":0.0011852534,"threshold_uncertainty_score":0.0718624},"labels":[],"label_agreement":null},{"id":"W2534770783","doi":"10.3303/cet1648040","title":"Developing a quantitative risk-based methodology for maintenance scheduling using Bayesian Network","year":2016,"lang":"en","type":"article","venue":"eCite Digital Repository (University of Tasmania)","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":48,"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":"Bayesian network; Computer science; Bayesian probability; Scheduling (production processes); Artificial intelligence; Engineering; Operations management","score_opus":0.033315415291414914,"score_gpt":0.2318608815976587,"score_spread":0.19854546630624378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2534770783","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":[0.0032185998,0.000107819564,0.9958548,0.000067499175,0.000008465143,0.00004087435,0.000040860006,0.00006503837,0.0005959898],"genre_scores_gemma":[0.3660537,0.00071803655,0.6290587,0.00009613519,0.00008748911,0.0006542947,0.00040758913,0.00011553332,0.0028084952],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989704,0.0005140672,0.00004921586,0.00015448054,0.0002365768,0.000075321266],"domain_scores_gemma":[0.996123,0.0030773983,0.0002773351,0.00006965062,0.0003790696,0.00007347941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031084174,0.0010073363,0.0011145041,0.0017930748,0.00043564322,0.0013058088,0.0015223925,0.0011927509,0.0025554455],"category_scores_gemma":[0.0073552066,0.0009207478,0.0011562273,0.0012179607,0.00060142047,0.0013037694,0.00090475316,0.0013680207,0.00032256133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013606049,0.00001569339,0.00028807262,0.00003210348,0.00002451629,0.00001868464,0.000020039368,0.9831849,0.00029747564,0.004910802,0.00015979832,0.011034284],"study_design_scores_gemma":[0.0000030709994,0.0000067379474,0.000055415625,0.0000055260225,0.000006614868,0.0000056235735,0.0000033021756,0.99644226,0.00008017059,0.0032388526,0.00014910256,0.0000032652451],"about_ca_topic_score_codex":0.012531265,"about_ca_topic_score_gemma":0.0097558005,"teacher_disagreement_score":0.012531265,"about_ca_system_score_codex":0.0020698572,"about_ca_system_score_gemma":0.0023735927,"threshold_uncertainty_score":0.024916649},"labels":[],"label_agreement":null},{"id":"W2580712357","doi":"10.5006/c2013-02118","title":"Corrosion of a Shell-and-Tube Heat Exchanger","year":2013,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Nova Chemicals (Canada)","funders":"","keywords":"Shell and tube heat exchanger; Corrosion; Heat exchanger; Materials science; Tube (container); Shell (structure); Metallurgy; Composite material; Mechanical engineering; Engineering","score_opus":0.004615188964200362,"score_gpt":0.1749468823780875,"score_spread":0.17033169341388715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2580712357","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99860966,0.000030358087,0.0008702247,0.000013202019,0.000007821281,0.000010756139,0.000057063815,0.00005684796,0.00034401348],"genre_scores_gemma":[0.9965424,0.00003692622,0.0014463103,0.000010053638,0.0000029933879,0.0000057050893,0.00012266144,0.00001127581,0.0018217101],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998418,0.000011709856,0.000009075761,0.000032577358,0.00007852922,0.000026311975],"domain_scores_gemma":[0.9998617,0.000016242539,0.00002740036,0.000015772413,0.000053739317,0.000025116613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000186572,0.00029918502,0.0002640598,0.00018403218,0.00022615475,0.00024260773,0.00030988434,0.0003533717,0.0015056697],"category_scores_gemma":[0.00021394996,0.00015459833,0.00027447272,0.00012426339,0.00012102966,0.0002311789,0.0002473055,0.00020848792,0.00037180542],"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":[0.0001225089,0.000026103286,0.0030318443,0.000018465445,0.000007048273,0.00022405914,0.00004282157,0.00043332105,0.99399215,0.000024758418,0.00005640638,0.0020206047],"study_design_scores_gemma":[0.000012991833,0.00090367545,0.071226895,0.000007112855,0.000022880751,0.00036453232,0.00010023778,0.014644932,0.91150826,0.000019890558,0.0011732705,0.000015237272],"about_ca_topic_score_codex":0.0012015811,"about_ca_topic_score_gemma":0.0012875004,"teacher_disagreement_score":0.0015056697,"about_ca_system_score_codex":0.00018723226,"about_ca_system_score_gemma":0.0001353178,"threshold_uncertainty_score":0.00503695},"labels":[],"label_agreement":null},{"id":"W2610872340","doi":"","title":"INTERGENERATIONAL TRANSMISSION OF INSULIN RESISTANCE","year":2009,"lang":"en","type":"article","venue":"Research Portal (King's College London)","topic":"Engineering Diagnostics and Reliability","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":"Women's Health Research Institute","funders":"","keywords":"Insulin resistance; Transmission (telecommunications); Resistance (ecology); Computer science; World Wide Web; Insulin; Telecommunications; Medicine; Biology; Internal medicine; Ecology","score_opus":0.015825464794938043,"score_gpt":0.2806008788557916,"score_spread":0.2647754140608536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610872340","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96555626,0.0032630262,0.0029599248,0.0034302606,0.00006564024,0.000020659762,0.00096811756,0.000038435966,0.023697693],"genre_scores_gemma":[0.99294394,0.0022663623,0.0006727816,0.00014828281,0.000031994117,0.00002426454,0.00021279522,0.000011864384,0.003687642],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99930143,0.0003877717,0.000026647916,0.00010551001,0.000081722144,0.000096835276],"domain_scores_gemma":[0.99821115,0.0007650568,0.00034752712,0.0003854942,0.0001604991,0.0001303515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008157098,0.00035705368,0.000256268,0.00078019156,0.000513776,0.0011913145,0.00033162718,0.0007922624,0.009108433],"category_scores_gemma":[0.00442389,0.00032272437,0.00020330073,0.00075266964,0.00058027584,0.0007845769,0.0012039876,0.0010034622,0.0006131381],"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":[0.0016206059,0.00087011367,0.69385153,0.00020625713,0.0009032022,0.010176036,0.013758746,0.0017135425,0.011073564,0.09381502,0.0068941996,0.16511725],"study_design_scores_gemma":[0.000060867515,0.0002611617,0.9281757,0.00027932596,0.0002538339,0.008626958,0.0050022868,0.0017864446,0.0012880377,0.04356642,0.010620315,0.00007865072],"about_ca_topic_score_codex":0.003959264,"about_ca_topic_score_gemma":0.0027460742,"teacher_disagreement_score":0.009108433,"about_ca_system_score_codex":0.0004563324,"about_ca_system_score_gemma":0.0002486074,"threshold_uncertainty_score":0.030470729},"labels":[],"label_agreement":null},{"id":"W2615269501","doi":"10.1149/ma2011-01/2/5","title":"Study of the Cracking of Metal Hydride Electrodes by Acoustic Emission Measurements","year":2011,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Engineering Diagnostics and Reliability","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":"Institut National de la Recherche Scientifique","funders":"","keywords":"Cracking; Hydride; Acoustic emission; Electrode; Materials science; Metal; Composite material; Metallurgy; Chemistry","score_opus":0.02264173007928724,"score_gpt":0.22119657738787685,"score_spread":0.1985548473085896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615269501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921022,0.00041755752,0.004724623,0.00005622889,0.000019943955,0.000038898874,0.00019746454,0.00006410937,0.0023789864],"genre_scores_gemma":[0.99618787,0.00014824027,0.0019388453,0.00001061074,0.000007325283,0.000016269174,0.00010336223,0.000011521617,0.0015758716],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987125,0.000009792043,0.000004954535,0.000026039848,0.00006916281,0.000018721525],"domain_scores_gemma":[0.9995365,0.00018505413,0.000050457467,0.000047200796,0.00016191954,0.000018976361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017037592,0.00019533525,0.00018333232,0.00023430621,0.00021556433,0.0001851168,0.00032309687,0.00035543862,0.0025780115],"category_scores_gemma":[0.0005390327,0.000122866,0.00011599895,0.00015731815,0.0002881874,0.00021819961,0.00018105986,0.00040230074,0.0003747197],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006268747,0.000014223149,0.00055549515,0.00003628145,0.000004725555,0.000059241534,0.00005368006,0.00006791027,0.9968437,0.00004842158,0.00005057339,0.0022029392],"study_design_scores_gemma":[0.000010206974,0.000244343,0.010582137,0.000007141338,0.000010926418,0.00016218695,0.000089002155,0.0029221724,0.984672,0.000038585684,0.0012549903,0.000006300742],"about_ca_topic_score_codex":0.00063759583,"about_ca_topic_score_gemma":0.0005691173,"teacher_disagreement_score":0.0025780115,"about_ca_system_score_codex":0.000090237874,"about_ca_system_score_gemma":0.000059360118,"threshold_uncertainty_score":0.008624315},"labels":[],"label_agreement":null},{"id":"W2624905986","doi":"10.5006/c2015-05473","title":"Corrosion of a Vertical Shell and Tube Heat Exchanger","year":2015,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Nova Chemicals (Canada)","funders":"","keywords":"Corrosion; Heat exchanger; Materials science; Shell and tube heat exchanger; Tube (container); Metallurgy; Shell (structure); Composite material; Mechanical engineering; Engineering","score_opus":0.011895196739495722,"score_gpt":0.20379697367456967,"score_spread":0.19190177693507396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624905986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973346,0.000053401796,0.0016258067,0.000014784746,0.000008744932,0.000012705829,0.00009318315,0.00008858598,0.00076832715],"genre_scores_gemma":[0.9944411,0.000048634683,0.0015793543,0.000009489442,0.0000025491402,0.000007124507,0.00019743369,0.000015630756,0.0036986335],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998543,0.000012534972,0.0000075042285,0.00003172242,0.00006773499,0.000026164467],"domain_scores_gemma":[0.9998529,0.000017365524,0.00002900777,0.000013711149,0.000064049,0.000023000406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017606912,0.00030162602,0.00019402102,0.00025644468,0.00028618454,0.0002460674,0.0002327698,0.00037711282,0.0021651294],"category_scores_gemma":[0.00021979008,0.00018406622,0.00030851568,0.00016516352,0.00012969303,0.00019644022,0.0002484676,0.00019250612,0.00051337655],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016510964,0.000030315428,0.008352058,0.00003066552,0.0000073506276,0.00038338779,0.00011132483,0.0005375527,0.9842079,0.000059818653,0.00010873022,0.006005676],"study_design_scores_gemma":[0.000012010901,0.0015263043,0.14217539,0.000017540442,0.00003467253,0.000874859,0.00022641046,0.014235265,0.8380473,0.000042538057,0.0027870496,0.000020675478],"about_ca_topic_score_codex":0.001640187,"about_ca_topic_score_gemma":0.0014850426,"teacher_disagreement_score":0.0021651294,"about_ca_system_score_codex":0.0001656749,"about_ca_system_score_gemma":0.00012166005,"threshold_uncertainty_score":0.007243097},"labels":[],"label_agreement":null},{"id":"W263738382","doi":"10.5006/c2008-08027","title":"Insights into Atlas Cell Testing for Selection of Linings for Oil and Gas Production Vessels and Tanks","year":2008,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Encana (Canada)","funders":"","keywords":"Atlas (anatomy); Selection (genetic algorithm); Petroleum engineering; Production (economics); Oil production; Environmental science; Forensic engineering; Marine engineering; Engineering; Computer science; Geology; Artificial intelligence","score_opus":0.009842228506006696,"score_gpt":0.19592011118318137,"score_spread":0.18607788267717468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W263738382","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98089266,0.0003598373,0.015059297,0.00015665083,0.000032304535,0.00007269769,0.00019795986,0.0002731737,0.002955494],"genre_scores_gemma":[0.9875051,0.00016611,0.01117403,0.000050859308,0.000006974742,0.00001734179,0.00012044569,0.000037931703,0.0009211438],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974872,0.00054907694,0.00012494966,0.00014876097,0.0015243455,0.00016563642],"domain_scores_gemma":[0.9966798,0.0013253862,0.00039972467,0.00029704548,0.0011737212,0.00012434825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023648883,0.00036149682,0.0005608019,0.0008346889,0.00068274036,0.0008982012,0.001160554,0.0005947038,0.0014722779],"category_scores_gemma":[0.0030300524,0.00027905844,0.00025104193,0.000421117,0.0008239606,0.0008210983,0.00069308013,0.0005305128,0.00043880328],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036177997,0.00009412328,0.023726856,0.00019736718,0.000012199715,0.00070426037,0.0011657786,0.0045525073,0.94833475,0.0009523714,0.00067153457,0.01922647],"study_design_scores_gemma":[0.000020944664,0.0012625011,0.031968117,0.000027740081,0.000035103825,0.0012264791,0.0016878301,0.0107145505,0.9456348,0.00044877242,0.006909331,0.00006393531],"about_ca_topic_score_codex":0.002200821,"about_ca_topic_score_gemma":0.007167079,"teacher_disagreement_score":0.0023648883,"about_ca_system_score_codex":0.00063098,"about_ca_system_score_gemma":0.00072892726,"threshold_uncertainty_score":0.012506902},"labels":[],"label_agreement":null},{"id":"W2732076768","doi":"10.4050/f-0073-2017-12171","title":"Method to Assess the Effects of a Flaw with Residual Stress for Rotorcraft Metallic Structures","year":2017,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Residual stress; Stress (linguistics); Materials science; Metal; Residual; Composite material; Computer science; Metallurgy; Algorithm","score_opus":0.01175433122513612,"score_gpt":0.279326004213539,"score_spread":0.26757167298840284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2732076768","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":[0.019248663,0.00008901102,0.9754735,0.00005910849,0.00004817747,0.00040297242,0.00027436943,0.0016205212,0.0027836591],"genre_scores_gemma":[0.27559298,0.00013755476,0.717373,0.00007395745,0.000015537078,0.00080541987,0.0003354582,0.00025189747,0.005414119],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993801,0.00005904124,0.000024378958,0.00013147079,0.00038242142,0.000022477181],"domain_scores_gemma":[0.99905246,0.0002026461,0.00016392402,0.00012538023,0.00042740512,0.000028190745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065011694,0.0006480526,0.00032572512,0.0011863773,0.00038231103,0.00045309178,0.00082693977,0.0007669046,0.0053056204],"category_scores_gemma":[0.0021598644,0.00028683874,0.00031621283,0.0003856452,0.00044056444,0.00054987374,0.00062044716,0.00054423243,0.0012470155],"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":[0.00029930755,0.00024656433,0.016731177,0.0008776557,0.000089893714,0.00033100197,0.00050745864,0.034169354,0.3374296,0.01526229,0.005247051,0.5888087],"study_design_scores_gemma":[0.00013419102,0.0009158437,0.019874092,0.00014855208,0.000099002515,0.0016232261,0.00034032261,0.6852972,0.2571432,0.010311018,0.023906609,0.0002066779],"about_ca_topic_score_codex":0.0013600107,"about_ca_topic_score_gemma":0.0018592876,"teacher_disagreement_score":0.0053056204,"about_ca_system_score_codex":0.00035564962,"about_ca_system_score_gemma":0.0010693113,"threshold_uncertainty_score":0.017749071},"labels":[],"label_agreement":null},{"id":"W2732521767","doi":"10.1093/geroni/igx004.3651","title":"DETECTION OF COGNITIVE FRAILTY WITH THE COMPREHENSIVE FRAILTY ASSESSMENT INSTRUMENT","year":2017,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Engineering Diagnostics and Reliability","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":"Cronbach's alpha; Montreal Cognitive Assessment; Cognition; Gerontology; Psychology; Reliability (semiconductor); Multivariate analysis; Cognitive decline; Economic shortage; Cognitive Assessment System; Clinical psychology; Cognitive impairment; Medicine; Psychometrics; Psychiatry; Dementia; Disease","score_opus":0.02607360620195651,"score_gpt":0.28448015353099565,"score_spread":0.2584065473290391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2732521767","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.991926,0.00033937822,0.004330427,0.000059798163,0.000018089137,0.0004207894,0.0008717862,0.000052217605,0.0019814407],"genre_scores_gemma":[0.9873175,0.00021851805,0.009944093,0.000052548763,0.000014285317,0.00040128463,0.0010620144,0.000007482833,0.0009823489],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99912137,0.0002617057,0.00015245141,0.00012867984,0.00025135922,0.00008448427],"domain_scores_gemma":[0.9985305,0.00039861188,0.0003249245,0.00013048627,0.00049093756,0.00012446124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002328315,0.000371238,0.0005055549,0.0017661335,0.00029269423,0.00050359307,0.00028805254,0.00027715758,0.0012252722],"category_scores_gemma":[0.007249808,0.00018535437,0.00063603057,0.00096379704,0.00021675807,0.00045787162,0.0008718781,0.0004527904,0.00028131597],"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":[0.0004178637,0.00028089783,0.93693674,0.000083033075,0.00016886635,0.0000702749,0.0008147605,0.00056233193,0.0019764958,0.00019485728,0.0013427826,0.05715113],"study_design_scores_gemma":[0.000029030813,0.00060469564,0.99564976,0.00001821556,0.00004901602,0.00018468857,0.00015704181,0.0012144896,0.0008518439,0.00021587074,0.0010068419,0.000018424375],"about_ca_topic_score_codex":0.0037637684,"about_ca_topic_score_gemma":0.0058388477,"teacher_disagreement_score":0.0037637684,"about_ca_system_score_codex":0.00031062352,"about_ca_system_score_gemma":0.000443564,"threshold_uncertainty_score":0.012313485},"labels":[],"label_agreement":null},{"id":"W2761971436","doi":"10.2495/safe-v7-n2-103-112","title":"Statistical analysis of failure consequences for oil and gas pipelines","year":2017,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Engineering Diagnostics and Reliability","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":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pipeline transport; Statistical analysis; Forensic engineering; Environmental science; Petroleum engineering; Engineering; Statistics; Environmental engineering; Mathematics","score_opus":0.005946409513554729,"score_gpt":0.24420998656198953,"score_spread":0.2382635770484348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2761971436","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98545015,0.00023733596,0.008691719,0.000094177856,0.000023834611,0.00008637203,0.004031063,0.00013647435,0.0012488764],"genre_scores_gemma":[0.9948402,0.0000694193,0.00090660935,0.000011844945,0.000016682206,0.000054509095,0.0037179189,0.000014578135,0.00036815388],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9952171,0.0013869769,0.00042102998,0.0009839282,0.0016082204,0.00038266307],"domain_scores_gemma":[0.94939154,0.03369789,0.009755792,0.0035052907,0.0027247653,0.0009247858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074393954,0.000428374,0.0005512872,0.0034855404,0.00040852866,0.00075770874,0.000725864,0.0005407891,0.002771399],"category_scores_gemma":[0.025594374,0.00016104027,0.0019535024,0.0026845336,0.0008195857,0.0008471047,0.0008166358,0.0009885762,0.0003570404],"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":[0.0006010882,0.00013159825,0.9518453,0.00006629986,0.00059524254,0.00034773778,0.00011654333,0.028054167,0.0007769774,0.0012009299,0.0012425071,0.015021654],"study_design_scores_gemma":[0.000014466378,0.00060815946,0.929391,0.000012545519,0.00017562017,0.00045161162,0.00030250536,0.06524666,0.00073852803,0.0017725314,0.0012486187,0.000037775128],"about_ca_topic_score_codex":0.003495814,"about_ca_topic_score_gemma":0.0028652656,"teacher_disagreement_score":0.0074393954,"about_ca_system_score_codex":0.00068244146,"about_ca_system_score_gemma":0.00068098644,"threshold_uncertainty_score":0.039343715},"labels":[],"label_agreement":null},{"id":"W2766334243","doi":"10.11575/prism/27911","title":"Studies of Aqueous Hydrogen Sulfide Corrosion in Producing SAGD Wells","year":2017,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Engineering Diagnostics and Reliability","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":"Suncor Energy (Canada)","funders":"","keywords":"Hydrogen sulfide; Corrosion; Aqueous solution; Sulfide; Metallurgy; Materials science; Hydrogen; Anaerobic corrosion; Petroleum engineering; Chemistry; Geology; Sulfur; Organic chemistry","score_opus":0.010559723085938432,"score_gpt":0.20150049557197472,"score_spread":0.19094077248603628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766334243","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99795145,0.00015583445,0.0013484765,0.000015944166,0.0000042368315,0.000015124741,0.000044837365,0.000018211414,0.00044590278],"genre_scores_gemma":[0.99451584,0.00026302543,0.0037720045,0.000013415632,0.0000033856752,0.000009159945,0.00010341484,0.000008111903,0.0013115595],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99977034,0.000035019006,0.000017237902,0.000040165265,0.00010601573,0.000031138497],"domain_scores_gemma":[0.9997669,0.000042832853,0.00005592054,0.00001789825,0.000092503695,0.000023968283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028691068,0.0002868084,0.00021911296,0.00027372115,0.00020920519,0.00030451923,0.0003097113,0.00024470923,0.00055103033],"category_scores_gemma":[0.00028170945,0.0001672078,0.0002417202,0.0001753437,0.00022346663,0.0002153289,0.00022131298,0.0002470305,0.00017980482],"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":[0.000082956365,0.000033189208,0.0021823412,0.000055823803,0.000008665521,0.000088611974,0.00008831392,0.00026851086,0.9952468,0.000030704396,0.00001562955,0.0018985623],"study_design_scores_gemma":[0.000008847732,0.0011251939,0.007876105,0.0000041891726,0.000013761205,0.00012666812,0.00020617699,0.0012427146,0.98873794,0.000027892243,0.0006241361,0.000006354903],"about_ca_topic_score_codex":0.0034006324,"about_ca_topic_score_gemma":0.0059920507,"teacher_disagreement_score":0.0034006324,"about_ca_system_score_codex":0.00030885765,"about_ca_system_score_gemma":0.00018940201,"threshold_uncertainty_score":0.00676167},"labels":[],"label_agreement":null},{"id":"W2775784809","doi":"10.17073/0368-0797-2017-8-603-608","title":"EXPERIENCE AND DEVELOPMENT OF METHODS TO ESTIMATE BLAST FURNACE REFRACTORY LINING CONDITIONS","year":2017,"lang":"en","type":"article","venue":"Izvestiya Ferrous Metallurgy","topic":"Engineering Diagnostics and Reliability","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":"Hatch (Canada)","funders":"","keywords":"Refractory (planetary science); Blast furnace; Metallurgy; Forensic engineering; Materials science; Engineering","score_opus":0.03706003252558426,"score_gpt":0.3757817760820695,"score_spread":0.3387217435564852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2775784809","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":[0.043260593,0.009770616,0.9376671,0.00026024974,0.000092819326,0.0003116306,0.00017884775,0.0007264714,0.00773167],"genre_scores_gemma":[0.15264654,0.006062809,0.83440715,0.00013166496,0.00008038307,0.00023410183,0.00039271175,0.00015629026,0.0058883536],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9960316,0.0011207042,0.00024455736,0.0009753078,0.001473074,0.0001547347],"domain_scores_gemma":[0.99420047,0.002141259,0.00023641466,0.000815624,0.0024212347,0.00018505362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070677805,0.0012300928,0.00076182984,0.003275124,0.00049414684,0.0010690882,0.0023890452,0.0014828736,0.0018821321],"category_scores_gemma":[0.0058759023,0.00048485416,0.0006496022,0.0016602167,0.0012637989,0.0016665149,0.0013313605,0.0012994318,0.0013343666],"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":[0.00013717724,0.00025164863,0.014835664,0.001022066,0.00007709725,0.00019017333,0.001711568,0.009406791,0.10384768,0.0044220183,0.0012555266,0.86284256],"study_design_scores_gemma":[0.00009562953,0.0029001136,0.056237813,0.0014006891,0.00027474447,0.0048027667,0.0031919573,0.10054144,0.57658553,0.0122709125,0.24121796,0.00048044138],"about_ca_topic_score_codex":0.0021108787,"about_ca_topic_score_gemma":0.0015821696,"teacher_disagreement_score":0.0070677805,"about_ca_system_score_codex":0.00064640754,"about_ca_system_score_gemma":0.0011807886,"threshold_uncertainty_score":0.03737849},"labels":[],"label_agreement":null},{"id":"W2785227036","doi":"10.4314/jfas.v10i1.18","title":"A great reliability, causes a decrease of failures in the rotating machines","year":2018,"lang":"en","type":"article","venue":"Journal of Fundamental and Applied Sciences","topic":"Engineering Diagnostics and Reliability","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":"Ministère des Transports","funders":"","keywords":"Mean time between failures; Reliability engineering; Spare part; Reliability (semiconductor); Weibull distribution; Engineering; Work (physics); Failure rate; Computer science; Operations management; Mechanical engineering; Statistics; Mathematics","score_opus":0.010726487005204862,"score_gpt":0.24213845329502295,"score_spread":0.23141196628981808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785227036","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24297525,0.014180317,0.7090471,0.002493451,0.0004568877,0.00010544596,0.00059217814,0.0014734443,0.028675867],"genre_scores_gemma":[0.9542778,0.0047470676,0.034230866,0.0002583503,0.00026601236,0.00006335568,0.00020841193,0.00011134261,0.005836799],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99933964,0.00010948791,0.000032798234,0.00016289337,0.00029979085,0.000055437216],"domain_scores_gemma":[0.9986922,0.00038946245,0.0003311656,0.000160574,0.00038007266,0.000046552843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069774844,0.00041737047,0.0003668785,0.00096650375,0.00038559813,0.0008309329,0.00037898135,0.0006454702,0.0017695718],"category_scores_gemma":[0.0024446354,0.00018213826,0.00036596681,0.000726696,0.00079344027,0.0008330354,0.00046480837,0.00062073814,0.0009109193],"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":[0.00039177205,0.0001883813,0.036440443,0.0020239304,0.00018942474,0.0012193065,0.0009838652,0.10689051,0.32385314,0.08177551,0.009545812,0.4364979],"study_design_scores_gemma":[0.00008746517,0.0026363363,0.1624025,0.00063956354,0.00038799722,0.016127797,0.0018479059,0.24606319,0.23895192,0.16031717,0.17018029,0.00035789498],"about_ca_topic_score_codex":0.00047591078,"about_ca_topic_score_gemma":0.00038743974,"teacher_disagreement_score":0.0017695718,"about_ca_system_score_codex":0.00047072588,"about_ca_system_score_gemma":0.0005423064,"threshold_uncertainty_score":0.005919814},"labels":[],"label_agreement":null},{"id":"W2791096214","doi":"","title":"Development of Equipment Failure Prognostic Model based on Logical Analysis of Data (LAD)","year":2012,"lang":"en","type":"article","venue":"Library and Archives Canada (Government of Canada)","topic":"Engineering Diagnostics and Reliability","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":"Computer science; Risk analysis (engineering); Business","score_opus":0.008984716547035388,"score_gpt":0.1628394506623266,"score_spread":0.15385473411529121,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791096214","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032053865,0.00024157904,0.9636976,0.00043796154,0.00004800981,0.00009841715,0.00074152125,0.00125328,0.0014276869],"genre_scores_gemma":[0.73826796,0.0006189693,0.25415954,0.00025919505,0.00010306341,0.0004150082,0.0021229784,0.00007909663,0.0039741783],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960285,0.00009352807,0.000037826972,0.000119159784,0.00010464353,0.000042059586],"domain_scores_gemma":[0.9991542,0.0004220996,0.000110281144,0.00006541616,0.00021700129,0.00003091898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001300488,0.00050520076,0.00055893575,0.0013044209,0.00023774021,0.00095291005,0.0010985343,0.0006092048,0.0012991132],"category_scores_gemma":[0.0031709701,0.00032567978,0.00073045533,0.0007496107,0.00024570167,0.0010009072,0.0006433872,0.00078549935,0.00057880575],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009198789,0.000110022884,0.014506229,0.000101698344,0.00008018185,0.00010886725,0.000069573965,0.83355445,0.0023321782,0.007258463,0.0032998333,0.13848642],"study_design_scores_gemma":[0.0000029705006,0.00001910321,0.00062926474,0.0000051962766,0.000008579026,0.000016073343,0.000005353718,0.9972144,0.00026947545,0.0013607527,0.0004640536,0.0000048216034],"about_ca_topic_score_codex":0.007491965,"about_ca_topic_score_gemma":0.0066116904,"teacher_disagreement_score":0.007491965,"about_ca_system_score_codex":0.0008163506,"about_ca_system_score_gemma":0.0012477926,"threshold_uncertainty_score":0.01489675},"labels":[],"label_agreement":null},{"id":"W2800684940","doi":"10.17122/ogbus-2018-2-129-142","title":"THE METHOD OF FORCING THE INDUSTRIAL SAFETY STRENGTHENING","year":2018,"lang":"en","type":"article","venue":"Oil and Gas Business","topic":"Engineering Diagnostics and Reliability","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":"Forcing (mathematics); Environmental science; Climatology; Geology","score_opus":0.010439168854324969,"score_gpt":0.2189820834008599,"score_spread":0.20854291454653492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800684940","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":[0.021715468,0.0017777513,0.47812808,0.0091505265,0.0021702049,0.00084722723,0.0002680644,0.002114414,0.48382816],"genre_scores_gemma":[0.41586182,0.0020401864,0.32733735,0.0033307762,0.0007476782,0.0017085031,0.00023022435,0.0006824172,0.24806102],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966633,0.0011952507,0.00015039464,0.0007347955,0.0010067926,0.0002493884],"domain_scores_gemma":[0.9973456,0.0007117792,0.00022219653,0.0010278899,0.0005235848,0.00016887288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003164858,0.00059999776,0.0004284618,0.0020957743,0.0034036103,0.0030936643,0.0014775721,0.0016676133,0.022628255],"category_scores_gemma":[0.005254787,0.00039208456,0.0009562743,0.0011712757,0.008575284,0.0029554076,0.0043770573,0.0023809865,0.005296104],"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":[0.00006407919,0.00009691175,0.0007066565,0.00025038898,0.00002337077,0.0001380322,0.0024353808,0.0015297931,0.0035936895,0.8724867,0.012243027,0.1064319],"study_design_scores_gemma":[0.00008151984,0.0002352827,0.0014450522,0.0003586422,0.000048374965,0.00041318766,0.001639136,0.004090806,0.0065309457,0.3246786,0.66039336,0.00008512017],"about_ca_topic_score_codex":0.0023301179,"about_ca_topic_score_gemma":0.0024681732,"teacher_disagreement_score":0.022628255,"about_ca_system_score_codex":0.002128969,"about_ca_system_score_gemma":0.0054082596,"threshold_uncertainty_score":0.07569903},"labels":[],"label_agreement":null},{"id":"W2810639989","doi":"10.1007/978-3-319-74693-7_20","title":"A Rational Basis for Determining Vibration Signature of Shaft/Coupling Misalignment in Rotating Machinery","year":2018,"lang":"en","type":"book-chapter","venue":"Conference proceedings of the Society for Experimental Mechanics","topic":"Engineering Diagnostics and Reliability","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":"Quest University Canada","funders":"","keywords":"Vibration; Signature (topology); Basis (linear algebra); Coupling (piping); Drive shaft; Structural engineering; Physics; Engineering; Control theory (sociology); Computer science; Acoustics; Mechanical engineering; Mathematics; Geometry; Artificial intelligence","score_opus":0.015316397597620112,"score_gpt":0.23453561795385475,"score_spread":0.21921922035623465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810639989","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022007147,0.00043110506,0.9693601,0.00015387144,0.00010161517,0.00003945611,0.00009807818,0.0003517168,0.007456948],"genre_scores_gemma":[0.61143506,0.0010869203,0.3689678,0.0001718692,0.0002033653,0.00015564833,0.00050602533,0.0004469565,0.01702642],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999785,0.000040830684,0.000011363862,0.000054155662,0.0000833359,0.00002534026],"domain_scores_gemma":[0.99978775,0.00008887072,0.00001976907,0.000038220194,0.000053248517,0.000012162273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005503648,0.0006230613,0.00055623916,0.00069016975,0.0002946769,0.0009395172,0.000897844,0.00081366696,0.0039252704],"category_scores_gemma":[0.0009052253,0.00046796037,0.000633833,0.00035928184,0.0008257645,0.00068878726,0.0005364034,0.0007966301,0.0016010139],"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":[0.00018740934,0.00014347167,0.002039143,0.0002457801,0.000086042746,0.00037802546,0.00025374503,0.1637793,0.18699655,0.46136877,0.0050693797,0.1794524],"study_design_scores_gemma":[0.000009560972,0.000055723496,0.001108565,0.000024996209,0.000023066423,0.00009005808,0.000042238284,0.8991787,0.008770822,0.08736712,0.0032954684,0.000033755387],"about_ca_topic_score_codex":0.00078935694,"about_ca_topic_score_gemma":0.001092789,"teacher_disagreement_score":0.0039252704,"about_ca_system_score_codex":0.00033545116,"about_ca_system_score_gemma":0.0004547351,"threshold_uncertainty_score":0.0131313205},"labels":[],"label_agreement":null},{"id":"W2888678748","doi":"","title":"Goal-oriented formulation of boundary-value problems for accurate estimation of quantities of interest","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Engineering Diagnostics and Reliability","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":"Boundary value problem; Estimation; Computer science; Value (mathematics); Mathematical optimization; Mathematics; Mathematical analysis; Engineering; Machine learning; Systems engineering","score_opus":0.019663868981559068,"score_gpt":0.2458541481266239,"score_spread":0.22619027914506484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888678748","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":[0.0010223995,0.000058963156,0.9978795,0.000096052456,0.000021278458,0.000013108514,0.000014969552,0.000030024985,0.00086366624],"genre_scores_gemma":[0.1822857,0.00046822234,0.8116329,0.00030481353,0.000106950734,0.00032488708,0.00023036615,0.00024201316,0.004404127],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992286,0.00035190152,0.00003887107,0.000103806844,0.00022529902,0.00005156996],"domain_scores_gemma":[0.99838245,0.0010058362,0.00013017039,0.00008760638,0.00031032396,0.000083599225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025554674,0.001296618,0.0012296711,0.0007322615,0.0003435842,0.0020769977,0.0015562908,0.0022271539,0.0027039049],"category_scores_gemma":[0.0052757156,0.0007370682,0.0009718951,0.00054896116,0.0011358773,0.0013011519,0.0020771192,0.0022109267,0.00054208963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007595213,0.00007826886,0.00032831807,0.00033526676,0.000041922354,0.00014037645,0.00015919135,0.7304191,0.0063797776,0.23270674,0.00189732,0.027437773],"study_design_scores_gemma":[0.0000078752755,0.000014008582,0.000025780104,0.00001537103,0.000005496187,0.0000105620675,0.0000099694835,0.97304714,0.0005859735,0.025212342,0.0010611397,0.0000043741093],"about_ca_topic_score_codex":0.0019257839,"about_ca_topic_score_gemma":0.0018417177,"teacher_disagreement_score":0.0027039049,"about_ca_system_score_codex":0.00075977045,"about_ca_system_score_gemma":0.0012728792,"threshold_uncertainty_score":0.013514817},"labels":[],"label_agreement":null},{"id":"W2890710736","doi":"10.1007/978-3-030-48021-9_27","title":"Technico-Economic Modelling of Maintenance Cost for Hydroelectric Turbine Runners","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Engineering Diagnostics and Reliability","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":"Hydroelectricity; Turbine; Environmental science; Marine engineering; Reliability engineering; Engineering; Electrical engineering; Mechanical engineering","score_opus":0.010557050756866852,"score_gpt":0.1893100847519594,"score_spread":0.17875303399509254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890710736","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2765502,0.0052761547,0.5032997,0.0035440845,0.0005059096,0.0001692569,0.0027909435,0.00042312717,0.20744064],"genre_scores_gemma":[0.9438787,0.0011545253,0.00863886,0.000070871174,0.00007580141,0.00010475898,0.00038311424,0.00015350379,0.0455397],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971014,0.00011733459,0.0000113390115,0.000044864668,0.00006218669,0.00005412455],"domain_scores_gemma":[0.9990834,0.00067466387,0.00005988325,0.000037264785,0.00008856021,0.00005618198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007354148,0.0007160969,0.0009121855,0.00072940387,0.0005119875,0.0018474013,0.0021707087,0.0017898873,0.012932471],"category_scores_gemma":[0.0026957903,0.0008852932,0.0010097461,0.0011644639,0.00088196655,0.0020560592,0.00057740614,0.0013797573,0.0010137372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022027363,0.000017902057,0.00020373915,0.000023937171,0.000008095882,0.000035973037,0.000013093928,0.97748977,0.00016245562,0.018474005,0.0006658228,0.0028832646],"study_design_scores_gemma":[0.0000043602436,0.000008507407,0.0002539408,0.000007197387,0.0000047516596,0.000013161133,0.000011880661,0.9909079,0.000048334958,0.008128775,0.00060639007,0.000004828043],"about_ca_topic_score_codex":0.019422099,"about_ca_topic_score_gemma":0.016352419,"teacher_disagreement_score":0.019422099,"about_ca_system_score_codex":0.0025957846,"about_ca_system_score_gemma":0.0012393543,"threshold_uncertainty_score":0.043263435},"labels":[],"label_agreement":null},{"id":"W2901211456","doi":"","title":"Пожарная безопасность морских стационарных ледостойких нефтедобывающих платформ","year":2004,"lang":"ru","type":"article","venue":"Нефтяное хозяйство","topic":"Engineering Diagnostics and Reliability","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":"Submarine pipeline; Business; Computer science; Geology; Marine engineering; Engineering; Oceanography","score_opus":0.0035610824484974516,"score_gpt":0.1810675186066815,"score_spread":0.17750643615818404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901211456","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":[0.26455918,0.02651976,0.21154878,0.0035710698,0.0010460198,0.00024314995,0.0005248829,0.00061754155,0.49136955],"genre_scores_gemma":[0.8986209,0.010266467,0.056049187,0.000115117,0.00022410063,0.00018440346,0.00014240057,0.00010565211,0.034291767],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994112,0.00009649319,0.000026173682,0.000081592814,0.00030994712,0.00007449727],"domain_scores_gemma":[0.99945277,0.00014220347,0.00009562981,0.00009096163,0.00017731785,0.00004110513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005794366,0.00034898252,0.00020117922,0.0015000962,0.000986777,0.002192639,0.00025104985,0.000539816,0.007696397],"category_scores_gemma":[0.0014155889,0.0003277983,0.0002609546,0.0012336599,0.0015863102,0.00090875285,0.00070347916,0.000707066,0.0027435003],"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":[0.00024236,0.0000961897,0.006275145,0.0005315909,0.00004370556,0.001829001,0.0046567367,0.005295893,0.065290496,0.44684216,0.006441922,0.46245474],"study_design_scores_gemma":[0.000070945265,0.0004142965,0.020310523,0.00045525958,0.00013847936,0.0062924256,0.0042453483,0.009321111,0.059886634,0.1459438,0.7527185,0.00020274575],"about_ca_topic_score_codex":0.0026737752,"about_ca_topic_score_gemma":0.004195445,"teacher_disagreement_score":0.007696397,"about_ca_system_score_codex":0.0009402045,"about_ca_system_score_gemma":0.0015477652,"threshold_uncertainty_score":0.025747001},"labels":[],"label_agreement":null},{"id":"W2910725705","doi":"10.17122/ngdelo-2017-2-197-202","title":"ПОВЫШЕНИЕ ПОЖАРНОЙ БЕЗОПАСНОСТИ МАГИСТРАЛЬНЫХ НЕФТЕПРОВОДОВ ПУТЕМ СОВЕРШЕНСТВОВАНИЯ КАТОДНОЙ ЗАЩИТЫ","year":2017,"lang":"ru","type":"article","venue":"Нефтегазовое дело","topic":"Engineering Diagnostics and Reliability","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":"Pipeline transport; Hazardous waste; Product (mathematics); Environmental science; Russian federation; Engineering; Forensic engineering; Production (economics); Petroleum industry; Risk analysis (engineering); Waste management; Environmental engineering; Business","score_opus":0.008296845059040483,"score_gpt":0.22582903847286587,"score_spread":0.21753219341382538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910725705","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":[0.2038887,0.024924453,0.3387977,0.0040330626,0.0017189689,0.00037856196,0.0020324546,0.0011215191,0.42310458],"genre_scores_gemma":[0.74780846,0.016414598,0.15442082,0.000250336,0.00040206764,0.00034670546,0.0006618691,0.00034095097,0.07935424],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990957,0.00012136082,0.000052408275,0.00016174954,0.0004836983,0.000085142914],"domain_scores_gemma":[0.99929726,0.0001210996,0.00015262068,0.000115468996,0.0002647039,0.00004888505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006850417,0.0003125854,0.00029672642,0.0016284194,0.0009431945,0.0023176542,0.0003930975,0.0007516465,0.013741611],"category_scores_gemma":[0.0014990909,0.0005116989,0.0005125695,0.0013094173,0.0014542256,0.000991061,0.00090087275,0.000862422,0.005996844],"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":[0.0002231315,0.00011924669,0.006068404,0.0007332573,0.00007464958,0.0017205005,0.0023386066,0.0048936876,0.12686954,0.35664493,0.010138003,0.490176],"study_design_scores_gemma":[0.000057390167,0.00027263552,0.019079212,0.00024938094,0.00012654292,0.0035035203,0.0012886849,0.0059951055,0.060644448,0.105815396,0.8028102,0.00015738881],"about_ca_topic_score_codex":0.0041783457,"about_ca_topic_score_gemma":0.005049593,"teacher_disagreement_score":0.013741611,"about_ca_system_score_codex":0.00080840825,"about_ca_system_score_gemma":0.0016255071,"threshold_uncertainty_score":0.04597026},"labels":[],"label_agreement":null},{"id":"W2914669313","doi":"10.36001/phme.2018.v4i1.375","title":"Predictive Maintenance Approach for Complex Equipment","year":2018,"lang":"en","type":"article","venue":"PHM Society European Conference","topic":"Engineering Diagnostics and Reliability","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":"Hydro-Québec; École de Technologie Supérieure","funders":"Mitacs; Hydro-Québec","keywords":"Predictive maintenance; Computer science; Reliability engineering; Engineering","score_opus":0.030695705374271874,"score_gpt":0.2270922098196122,"score_spread":0.19639650444534032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914669313","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":[0.015503615,0.00082412217,0.9777184,0.00019835128,0.000086652595,0.000057568097,0.00013415769,0.00051349145,0.004963677],"genre_scores_gemma":[0.89421725,0.0008723683,0.09808729,0.00009019527,0.0001335467,0.00017793401,0.00028026607,0.000099365934,0.006041765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970585,0.00005557348,0.000013266467,0.00007287205,0.000116734394,0.000035623852],"domain_scores_gemma":[0.9995419,0.00023780864,0.000047167254,0.00003161418,0.00011958202,0.000021862656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005198647,0.0007544459,0.0009735554,0.0006900418,0.0003900223,0.0008732965,0.0016555169,0.0007758921,0.0045042858],"category_scores_gemma":[0.0015434272,0.00038437764,0.0006200771,0.0004807422,0.00027921225,0.00064675475,0.00076725986,0.0010353294,0.0005435176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059618153,0.00003878691,0.0005799902,0.00015078137,0.00004033812,0.00015508996,0.00007362702,0.9304702,0.0017711633,0.008027872,0.001692598,0.05693988],"study_design_scores_gemma":[0.0000029702644,0.000010681531,0.000072954106,0.000005069812,0.0000066583993,0.000018984772,0.0000049666255,0.99705803,0.00014406556,0.0022595753,0.00041373825,0.0000023534178],"about_ca_topic_score_codex":0.0067202286,"about_ca_topic_score_gemma":0.004865392,"teacher_disagreement_score":0.0067202286,"about_ca_system_score_codex":0.0005766595,"about_ca_system_score_gemma":0.0007075402,"threshold_uncertainty_score":0.015068352},"labels":[],"label_agreement":null},{"id":"W2936330814","doi":"","title":"Troubleshooting Fouling with a Deposit's Color, Texture, Location","year":2019,"lang":"en","type":"article","venue":"2019 Spring Meeting and 15th Global Congress on Process Safety","topic":"Engineering Diagnostics and Reliability","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":"Nalco (Canada)","funders":"","keywords":"Troubleshooting; Texture (cosmology); Fouling; Artificial intelligence; Computer vision; Computer science; Geology; Chemistry; Image (mathematics)","score_opus":0.002604785736607215,"score_gpt":0.19796687774831567,"score_spread":0.19536209201170845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936330814","genre_codex":"empirical","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":[0.7013099,0.0013529998,0.21518198,0.0021884541,0.0014006933,0.00085403706,0.0029747507,0.049215395,0.025521802],"genre_scores_gemma":[0.84042096,0.00049238786,0.12883243,0.0004993138,0.00012664852,0.00011863673,0.0012393147,0.0030681493,0.025202168],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988581,0.000092364106,0.000105601284,0.00014013774,0.0007092369,0.00009462301],"domain_scores_gemma":[0.9967463,0.00072127517,0.00032892104,0.0008208304,0.0011668628,0.00021586439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095733994,0.0009202938,0.0007881607,0.0015288296,0.00092258665,0.0009103791,0.0010060166,0.0007797758,0.009660203],"category_scores_gemma":[0.004915035,0.00036988838,0.0004690617,0.00060284865,0.00033343895,0.0009505547,0.0011880583,0.0006108755,0.0051531824],"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":[0.001829161,0.0002813366,0.046194457,0.00086682366,0.000106365194,0.0028230294,0.0013005511,0.0050788033,0.39633226,0.00046694942,0.041166976,0.50355333],"study_design_scores_gemma":[0.00010100388,0.00078465795,0.035616204,0.00024091004,0.00028177167,0.003997036,0.0019389279,0.07044201,0.7661771,0.0012584189,0.1189645,0.00019751006],"about_ca_topic_score_codex":0.002932394,"about_ca_topic_score_gemma":0.005773668,"teacher_disagreement_score":0.009660203,"about_ca_system_score_codex":0.00034844808,"about_ca_system_score_gemma":0.0006474674,"threshold_uncertainty_score":0.032316625},"labels":[],"label_agreement":null},{"id":"W2973734913","doi":"","title":"Determining the technical state of a combustion engine with the use of vibroacoustic signals","year":2016,"lang":"pl","type":"article","venue":"Zeszyty Naukowe / Wyższa Szkoła Oficerska Sił Powietrznych","topic":"Engineering Diagnostics and Reliability","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":"Transport Canada","funders":"","keywords":"State (computer science); Combustion; Computer science; Automotive engineering; Environmental science; Engineering; Chemistry","score_opus":0.016789870014853082,"score_gpt":0.20611845912102497,"score_spread":0.1893285891061719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973734913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81542856,0.00046257736,0.17995128,0.000091857684,0.000056287336,0.00005508579,0.00016757086,0.00026624478,0.0035205032],"genre_scores_gemma":[0.9801482,0.00018947736,0.018913357,0.00002178469,0.000015428886,0.000012285669,0.00008601907,0.000018104374,0.0005954567],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975497,0.000030203642,0.000013863623,0.00006089567,0.00011077004,0.00002938598],"domain_scores_gemma":[0.9996038,0.00018163807,0.000056182198,0.000034787612,0.00009435074,0.000029313023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031714063,0.0004092223,0.00029092844,0.0011622737,0.0002023352,0.000541913,0.00036197252,0.000513389,0.0006830677],"category_scores_gemma":[0.0012339895,0.00021363463,0.00022284663,0.0004070586,0.00030882112,0.0005739688,0.00041170028,0.0002913956,0.00018467905],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093821844,0.00015499121,0.04117297,0.00025961862,0.0001602562,0.00053532457,0.00029654807,0.015895408,0.7899316,0.0013064888,0.00027029967,0.14907835],"study_design_scores_gemma":[0.00007312281,0.0010858764,0.26844257,0.000084926,0.00036091745,0.0017319983,0.000564414,0.31706554,0.40445736,0.003788648,0.002150513,0.00019407544],"about_ca_topic_score_codex":0.0006393934,"about_ca_topic_score_gemma":0.0010154112,"teacher_disagreement_score":0.0011622737,"about_ca_system_score_codex":0.000092690505,"about_ca_system_score_gemma":0.00020623498,"threshold_uncertainty_score":0.0022851229},"labels":[],"label_agreement":null},{"id":"W2978304825","doi":"10.11575/prism/37163","title":"Treatment of Oil-Sands Produced Water by Electrocoagulation","year":2019,"lang":"en","type":"dissertation","venue":"PRISM (University of Calgary)","topic":"Engineering Diagnostics and Reliability","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":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Oil sands; Electrocoagulation; Environmental science; Petroleum engineering; Waste management; Geology; Environmental engineering; Engineering; Geography; Asphalt; Archaeology","score_opus":0.003072687955781733,"score_gpt":0.16698914140143511,"score_spread":0.1639164534456534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978304825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99280435,0.0009393587,0.0039387024,0.000064516986,0.000020930162,0.000055868673,0.00010935895,0.0000788006,0.0019880289],"genre_scores_gemma":[0.99135965,0.0008132066,0.005215724,0.000045992183,0.0000044715935,0.00001863189,0.00010565836,0.000015263773,0.0024214012],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980897,0.000016650705,0.000011578947,0.000032353713,0.000101262114,0.000029200808],"domain_scores_gemma":[0.9999429,0.000012428281,0.000013062717,0.0000025819263,0.000024169736,0.0000047195917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015004787,0.0003589383,0.00032774673,0.00028617991,0.000286581,0.0003546062,0.00031900432,0.00027659241,0.00071664475],"category_scores_gemma":[0.0001882693,0.00013081683,0.0002389813,0.0002977838,0.00023884622,0.00023353296,0.00024846167,0.0002844363,0.00016200208],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054948818,0.000013058248,0.0005357176,0.00010417523,0.000004399023,0.00009006652,0.000038415114,0.0002133946,0.9914739,0.00003311934,0.000047272944,0.0073914435],"study_design_scores_gemma":[0.0000042159345,0.00011213587,0.0027862748,0.0000061136384,0.000007684575,0.000054961965,0.000052769272,0.00090667274,0.9948172,0.00001810249,0.0012297919,0.0000039678534],"about_ca_topic_score_codex":0.010076147,"about_ca_topic_score_gemma":0.033930738,"teacher_disagreement_score":0.010076147,"about_ca_system_score_codex":0.0006875818,"about_ca_system_score_gemma":0.00038314148,"threshold_uncertainty_score":0.020034969},"labels":[],"label_agreement":null},{"id":"W2981437164","doi":"10.1108/ijqrm-01-2019-0035","title":"Reliability analysis of underground rock bolters using the renewal process, the non-homogeneous Poisson process and the Bayesian approach","year":2019,"lang":"en","type":"article","venue":"International Journal of Quality & Reliability Management","topic":"Engineering Diagnostics and Reliability","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":"Université du Québec à Chicoutimi; Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Reliability (semiconductor); Reliability engineering; Weibull distribution; Process (computing); Context (archaeology); Computer science; Renewal theory; Engineering; Statistics; Mathematics; Geology","score_opus":0.007967711367547621,"score_gpt":0.27602241288645235,"score_spread":0.2680547015189047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981437164","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13561727,0.00026142196,0.86193115,0.00009357528,0.000009801823,0.00005001278,0.00010137275,0.0001928101,0.001742597],"genre_scores_gemma":[0.95823145,0.0002610883,0.039881304,0.000013837266,0.0000136092085,0.00007501473,0.0001433719,0.000025378642,0.001355027],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992562,0.00023416692,0.00003978391,0.0001182766,0.00029560004,0.000055914363],"domain_scores_gemma":[0.9989986,0.00055510626,0.00018830877,0.00006191261,0.00017352567,0.000022596825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013004224,0.000349345,0.00038961723,0.0012506798,0.00021933872,0.0006663609,0.0007061744,0.0004367955,0.0010724482],"category_scores_gemma":[0.0029351527,0.00027471568,0.00084765546,0.0006754073,0.00033180552,0.00056444254,0.000439374,0.00036370655,0.00017989296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063126,0.000051860305,0.013260358,0.00011452704,0.000079876314,0.00028004765,0.0002565422,0.9090249,0.007776235,0.016671464,0.00047033752,0.051950846],"study_design_scores_gemma":[0.0000026279772,0.000028687587,0.0039011715,0.000010969753,0.000015090807,0.0000811919,0.000037579593,0.9908104,0.0010539233,0.0036992144,0.00034900638,0.000010228816],"about_ca_topic_score_codex":0.0043034316,"about_ca_topic_score_gemma":0.0027181557,"teacher_disagreement_score":0.0043034316,"about_ca_system_score_codex":0.00059706497,"about_ca_system_score_gemma":0.0006200922,"threshold_uncertainty_score":0.008556783},"labels":[],"label_agreement":null},{"id":"W2988299978","doi":"10.1201/9781482266481-127","title":"Evaluation methodology of industry equipment functional reliability","year":2008,"lang":"en","type":"book-chapter","venue":"","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":2,"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":"Reliability engineering; Reliability (semiconductor); Computer science; Engineering; Physics","score_opus":0.0957284028274127,"score_gpt":0.2776353844812382,"score_spread":0.18190698165382552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988299978","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":[0.034916807,0.0006822831,0.9399139,0.00008821997,0.00008206459,0.001606628,0.0022078604,0.0021291315,0.01837298],"genre_scores_gemma":[0.3629266,0.0005455648,0.6177428,0.000046578818,0.0000652098,0.0030325751,0.0060950094,0.00041265148,0.009133006],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98683965,0.0061645713,0.0011050997,0.0012364297,0.0041500865,0.0005040792],"domain_scores_gemma":[0.97978264,0.007094296,0.0012215467,0.00180503,0.009780792,0.00031562286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010885316,0.0013560228,0.0011552551,0.007328694,0.0006543978,0.0029748871,0.0012823011,0.0005740845,0.011030198],"category_scores_gemma":[0.026774159,0.00048195373,0.0019685042,0.0039436216,0.000547335,0.0016679775,0.0013583273,0.00079471036,0.0022257522],"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":[0.00043668473,0.00032608802,0.017094944,0.0014432595,0.0002695203,0.00014927881,0.00075143395,0.08428428,0.0069649485,0.023308363,0.008280848,0.85669035],"study_design_scores_gemma":[0.00015680799,0.0017489282,0.050633628,0.0008751495,0.0004313978,0.00047139957,0.0020384388,0.8317708,0.016692244,0.038557373,0.056489863,0.00013397053],"about_ca_topic_score_codex":0.005110378,"about_ca_topic_score_gemma":0.0038981708,"teacher_disagreement_score":0.011030198,"about_ca_system_score_codex":0.0017711418,"about_ca_system_score_gemma":0.0029395195,"threshold_uncertainty_score":0.057567716},"labels":[],"label_agreement":null},{"id":"W2990857799","doi":"10.2495/dne-v14-n4-249-263","title":"From nature and basic scientific results to modern engineering applications","year":2019,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Engineering Diagnostics and Reliability","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":"Engineering; Management science; Computer science; Systems engineering","score_opus":0.0037119505560499495,"score_gpt":0.21093169542153956,"score_spread":0.2072197448654896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990857799","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":[0.0068530734,0.27483565,0.16387317,0.09540211,0.013665451,0.00012328482,0.0006655618,0.00060988456,0.44397187],"genre_scores_gemma":[0.34294647,0.3187119,0.16993785,0.034865215,0.03765823,0.0011965303,0.0014428769,0.0009018565,0.09233906],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964812,0.0014133389,0.0003151974,0.0004908267,0.0011213876,0.00017815226],"domain_scores_gemma":[0.99486417,0.0032785523,0.00025371427,0.00074197067,0.00067026063,0.00019138357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056022345,0.0009713055,0.0013347276,0.0040300502,0.0016123188,0.005670892,0.0015889836,0.0028763372,0.011150664],"category_scores_gemma":[0.011381887,0.00052526954,0.0009502446,0.0028360835,0.01791409,0.009363038,0.0042397245,0.006664091,0.00437299],"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":[0.000011223228,0.000015769447,0.0001041299,0.00025890247,0.000015383024,0.000046763675,0.00026523028,0.0006395712,0.00015504113,0.9694957,0.010441081,0.018551216],"study_design_scores_gemma":[0.0000039884917,0.0000115440325,0.00009411211,0.00017867262,0.0000027120561,0.00003446405,0.000050973533,0.00043368078,0.000067156856,0.91606283,0.083051674,0.000008185172],"about_ca_topic_score_codex":0.0012092682,"about_ca_topic_score_gemma":0.0004941287,"teacher_disagreement_score":0.011150664,"about_ca_system_score_codex":0.0037562912,"about_ca_system_score_gemma":0.0020784123,"threshold_uncertainty_score":0.037302673},"labels":[],"label_agreement":null},{"id":"W2991905695","doi":"10.2175/193864704784138458","title":"STRESS-RESPONSE DYNAMICS OF AUTOTROPHS UNDER DIFFERENT PHYSICAL AND ENVIRONMENTAL CONDITIONS","year":2004,"lang":"en","type":"article","venue":"Proceedings of the Water Environment Federation","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":0,"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; University of Manitoba","keywords":"Autotroph; Environmental stress; Fight-or-flight response; Stress (linguistics); Environmental science; Environmental protection; Chemistry; Biology","score_opus":0.0024511420102667604,"score_gpt":0.15996621051621815,"score_spread":0.1575150685059514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991905695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994711,0.00007092685,0.00014876176,0.000023915394,0.0000022755803,0.0000013545866,0.00008572743,0.0000041101353,0.00019185092],"genre_scores_gemma":[0.9993625,0.00008188786,0.00011770986,0.000016301932,0.0000017095581,0.0000037185137,0.00015221056,0.0000031777602,0.0002608349],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999529,0.0000057393513,0.000003992707,0.000015603942,0.000009175167,0.000012670971],"domain_scores_gemma":[0.99984396,0.00004303031,0.000020703468,0.0000127734165,0.0000368553,0.00004266736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013914893,0.00014847617,0.00033846195,0.0001538991,0.00031000195,0.0005403921,0.0001604699,0.0003026844,0.0007466371],"category_scores_gemma":[0.00028327288,0.00016609991,0.00020255987,0.00019478472,0.0002878247,0.0003589667,0.0003026446,0.00029165018,0.00015722819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012627313,0.000092726004,0.056893516,0.00009495536,0.000081966784,0.00024089056,0.0005883698,0.008810718,0.9227964,0.0006847317,0.00029314938,0.008159866],"study_design_scores_gemma":[0.00008103479,0.000722445,0.80701876,0.00002483066,0.000091767026,0.00041628195,0.0017689392,0.07303095,0.111875676,0.0028279324,0.002051838,0.000089575864],"about_ca_topic_score_codex":0.0029784925,"about_ca_topic_score_gemma":0.0026204125,"teacher_disagreement_score":0.0029784925,"about_ca_system_score_codex":0.00032346084,"about_ca_system_score_gemma":0.0002336479,"threshold_uncertainty_score":0.0059223175},"labels":[],"label_agreement":null},{"id":"W3000630179","doi":"10.2316/j.2019.203-0164","title":"DISCRETE PREDICTIVE CONTROL OF A FLYWHEEL ENERGY STORAGE FOR TRANSIENT STABILITY AUGMENTATION","year":2019,"lang":"en","type":"article","venue":"International Journal of Power and Energy Systems","topic":"Engineering Diagnostics and Reliability","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":"Flywheel; Transient (computer programming); Model predictive control; Flywheel energy storage; Control theory (sociology); Stability (learning theory); Energy storage; Computer science; Control (management); Engineering; Automotive engineering; Physics; Artificial intelligence; Thermodynamics; Power (physics)","score_opus":0.0030892797959418735,"score_gpt":0.19539054904164072,"score_spread":0.19230126924569885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000630179","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3586631,0.0010610388,0.6108566,0.0008892937,0.0007966721,0.00014997496,0.00028137316,0.0014910958,0.025810784],"genre_scores_gemma":[0.9956955,0.000046971272,0.002693279,0.00001757681,0.000009814918,0.000015689833,0.000013340143,0.0000052003243,0.0015025621],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99992883,0.000012576716,0.0000043804434,0.000017544935,0.00002350359,0.000013186394],"domain_scores_gemma":[0.9998523,0.00006116224,0.000017658153,0.0000140871025,0.000044134922,0.00001074234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022352759,0.0003470848,0.0004162631,0.00019972627,0.0005483734,0.0008444529,0.0006465501,0.0003845222,0.0034159755],"category_scores_gemma":[0.00038995445,0.0001763334,0.00017518809,0.0002379536,0.00041107283,0.0003379791,0.00039481098,0.0004632015,0.00020360162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013988748,0.0003221889,0.000793927,0.00042379578,0.00009703405,0.00047335328,0.0001902349,0.80451506,0.06832786,0.011514456,0.003815435,0.10812784],"study_design_scores_gemma":[0.000025404972,0.00008629172,0.00015976367,0.0000054078187,0.00000905703,0.000012855032,0.000007693805,0.9956397,0.0030349714,0.00057116675,0.00044337215,0.000004368456],"about_ca_topic_score_codex":0.00545613,"about_ca_topic_score_gemma":0.008280791,"teacher_disagreement_score":0.00545613,"about_ca_system_score_codex":0.0003538695,"about_ca_system_score_gemma":0.00046733808,"threshold_uncertainty_score":0.011427581},"labels":[],"label_agreement":null},{"id":"W3017356264","doi":"10.22363/2312-8143-2019-20-4-293-301","title":"Comparative analysis of software for the study of statistical methods of control of product quality","year":2019,"lang":"en","type":"article","venue":"RUDN Journal of Engineering Researches","topic":"Engineering Diagnostics and Reliability","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":"Vétoquinol (Canada)","funders":"","keywords":"Software; Quality (philosophy); Pareto chart; Product (mathematics); Computer science; Control chart; MATLAB; Scatter plot; Statistical process control; Control (management); Plot (graphics); Industrial engineering; Data mining; Process (computing); Pareto principle; Engineering; Statistics; Operations management; Artificial intelligence; Machine learning; Mathematics","score_opus":0.060144658029014635,"score_gpt":0.41156155904310726,"score_spread":0.3514169010140926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3017356264","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":[0.013975141,0.005440013,0.94511276,0.0005949224,0.00091171556,0.0016976631,0.002089029,0.007087334,0.023091514],"genre_scores_gemma":[0.07127113,0.0026467969,0.91311634,0.00028355367,0.00028152796,0.004926724,0.002587995,0.0016141054,0.0032717993],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9601406,0.023086738,0.004696953,0.0023260298,0.009241848,0.0005077244],"domain_scores_gemma":[0.89946073,0.07885109,0.0040813396,0.0072465213,0.009642738,0.00071757013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02809868,0.0013183396,0.0014253408,0.008144026,0.0008809542,0.0027548424,0.0016222401,0.0010291169,0.014171953],"category_scores_gemma":[0.06756428,0.0005810432,0.0016751025,0.006622629,0.0017622369,0.0026758066,0.0025766396,0.0023842098,0.0029807466],"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":[0.0012021959,0.0005117623,0.01161594,0.005895473,0.0013326057,0.00086503266,0.0028957578,0.009975265,0.0148861855,0.118116885,0.03862813,0.7940748],"study_design_scores_gemma":[0.00038317178,0.0036631299,0.061171964,0.0052057644,0.0015947063,0.0038733075,0.0032793884,0.07688842,0.022870202,0.18939602,0.6311453,0.0005286122],"about_ca_topic_score_codex":0.00084746,"about_ca_topic_score_gemma":0.0007603535,"teacher_disagreement_score":0.02809868,"about_ca_system_score_codex":0.0013248791,"about_ca_system_score_gemma":0.0034593265,"threshold_uncertainty_score":0.14860183},"labels":[],"label_agreement":null},{"id":"W3088252452","doi":"10.15407/pmach2020.03.037","title":"Analysis of the Static Strength of the Emergency-Cooldown Heat Exchanger with the Use of the Design Tightness Value of Flange-Joint Pins","year":2020,"lang":"en","type":"article","venue":"Problemy mašinostroeniâ/Problemy mašinostroeniâ","topic":"Engineering Diagnostics and Reliability","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":"Response Biomedical (Canada)","funders":"","keywords":"Flange; Heat exchanger; Joint (building); Value (mathematics); Structural engineering; Engineering; Mechanical engineering; Computer science","score_opus":0.02835696925396775,"score_gpt":0.19345922033103463,"score_spread":0.16510225107706689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088252452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94704944,0.00019039206,0.046799432,0.000029871675,0.00001003522,0.000018712533,0.000114902,0.00013921823,0.005647927],"genre_scores_gemma":[0.9967674,0.000034162367,0.00242345,0.0000030790143,0.0000016592178,0.000007721582,0.00005938044,0.000007400788,0.00069577177],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995358,0.000076586206,0.000021158987,0.00006085463,0.00027059647,0.00003498706],"domain_scores_gemma":[0.9993736,0.0002544206,0.0000912956,0.00007305473,0.00019355187,0.0000140697675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000661577,0.00034121584,0.00029794313,0.0008203072,0.00016398098,0.00030137596,0.00042235566,0.00032041187,0.0011860705],"category_scores_gemma":[0.0013370082,0.00024262439,0.00035643656,0.00038464446,0.00031230127,0.00029763253,0.000218261,0.00016238594,0.00018742283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027887698,0.000048663125,0.026298372,0.00026317112,0.00009736613,0.00041456605,0.00014495452,0.70181525,0.20755686,0.0042543863,0.00026886776,0.058558732],"study_design_scores_gemma":[0.000018818339,0.00053432345,0.088433795,0.000034411423,0.00011794429,0.0004862018,0.00013913121,0.6971196,0.20922686,0.0008240599,0.0030247835,0.000040125233],"about_ca_topic_score_codex":0.0011284826,"about_ca_topic_score_gemma":0.0011810022,"teacher_disagreement_score":0.0011860705,"about_ca_system_score_codex":0.00037219992,"about_ca_system_score_gemma":0.00034901695,"threshold_uncertainty_score":0.0039678216},"labels":[],"label_agreement":null},{"id":"W3096448082","doi":"10.2118/202869-ms","title":"Artificial Intelligence Application for Just in Time Maintenance","year":2020,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Quest University Canada","funders":"","keywords":"Computer science; Process (computing); Field (mathematics); Scalability; Predictive maintenance; Asset management; Pipeline (software); Asset (computer security); Cost reduction; Operating cost; Industrial engineering; Reliability engineering; Artificial intelligence; Risk analysis (engineering); Engineering; Computer security","score_opus":0.017272540026882426,"score_gpt":0.22648184037794925,"score_spread":0.20920930035106683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096448082","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12072751,0.00095549715,0.83812803,0.0022570537,0.00030620102,0.00021653308,0.00027244992,0.0050226613,0.032114115],"genre_scores_gemma":[0.8064759,0.00033890942,0.18789516,0.00021519518,0.00004543648,0.00007513954,0.0001985241,0.00008083869,0.004674852],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995679,0.00013398471,0.000026362704,0.00007527287,0.0001711688,0.000025327752],"domain_scores_gemma":[0.9989761,0.00054456294,0.00008027716,0.00017255884,0.0001936065,0.00003284288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005780273,0.00037398541,0.0002696223,0.0004548372,0.0002375995,0.0011521023,0.0005734942,0.0005878379,0.004122919],"category_scores_gemma":[0.001872193,0.00011804182,0.0003370307,0.00038832496,0.00036489204,0.0007321959,0.00047685235,0.0006991279,0.0004956737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036944947,0.0005606748,0.0046537775,0.00037485108,0.00010990903,0.0004953471,0.0003479183,0.4979591,0.039624482,0.06008542,0.0068514044,0.38856772],"study_design_scores_gemma":[0.000010901043,0.00009691378,0.0004967755,0.000018626602,0.000014340007,0.000061322025,0.00003190238,0.9752926,0.005748985,0.012589623,0.005629094,0.0000087739],"about_ca_topic_score_codex":0.0016715499,"about_ca_topic_score_gemma":0.0011130802,"teacher_disagreement_score":0.004122919,"about_ca_system_score_codex":0.00058610446,"about_ca_system_score_gemma":0.00045681794,"threshold_uncertainty_score":0.013792515},"labels":[],"label_agreement":null},{"id":"W3111520856","doi":"10.28999/2541-9595-2020-10-4-432-439","title":"Review of the experience of product conformity assessment organizations in Canada","year":2020,"lang":"en","type":"article","venue":"SCIENCE & TECHNOLOGIES OIL AND OIL PRODUCTS PIPELINE TRANSPORTATION","topic":"Engineering Diagnostics and Reliability","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":"Conformity assessment; Conformity; Accreditation; Certification; Product (mathematics); Work (physics); Listing (finance); Business; Political science; Public relations; Accounting; Engineering; Law; Operations management","score_opus":0.0064040663564562976,"score_gpt":0.2099040974853704,"score_spread":0.2035000311289141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111520856","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":[0.11779955,0.7432608,0.0029462075,0.018936282,0.0014829786,0.00032454106,0.0023835918,0.00019716557,0.11266885],"genre_scores_gemma":[0.33663273,0.63797307,0.0038098723,0.0037017358,0.00020365468,0.00010634764,0.0018079417,0.00010028389,0.015664386],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.9849141,0.0020148149,0.0012402548,0.00094355596,0.009351223,0.0015361613],"domain_scores_gemma":[0.932879,0.0068067433,0.003947073,0.00061311654,0.051757343,0.003996681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008040376,0.0004970119,0.00060636573,0.010514019,0.005362904,0.005195499,0.0020207423,0.0009294199,0.0027531376],"category_scores_gemma":[0.016426051,0.00045204884,0.00047632062,0.028405335,0.0021721832,0.0016711282,0.0016449499,0.0012934561,0.00045707318],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002773746,0.00022476004,0.041929316,0.014489051,0.00014342299,0.0026052697,0.03364763,0.001333547,0.0022968852,0.010604511,0.10682996,0.78561836],"study_design_scores_gemma":[0.000012397369,0.00016174468,0.09098202,0.010434272,0.00018166186,0.0014270686,0.029862275,0.00028735911,0.0016645694,0.0003068077,0.8645459,0.00013397039],"about_ca_topic_score_codex":0.94670266,"about_ca_topic_score_gemma":0.96496606,"teacher_disagreement_score":0.9214656,"about_ca_system_score_codex":0.07853441,"about_ca_system_score_gemma":0.19225039,"threshold_uncertainty_score":0.5698097},"labels":[],"label_agreement":null},{"id":"W3118762265","doi":"10.4203/ccp.102.201","title":"Failure Prediction Model of Oil and Gas Pipelines","year":2013,"lang":"en","type":"article","venue":"Civil-comp proceedings","topic":"Engineering Diagnostics and Reliability","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":"Concordia University","funders":"","keywords":"Pipeline transport; Petroleum engineering; Fossil fuel; Computer science; Environmental science; Geology; Engineering; Waste management; Environmental engineering","score_opus":0.0049853762790066465,"score_gpt":0.16638574474686826,"score_spread":0.16140036846786163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118762265","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4621162,0.001231873,0.5217962,0.001143016,0.00013998269,0.00008828227,0.0011884941,0.0012128671,0.011083027],"genre_scores_gemma":[0.98805004,0.00025142534,0.0048238966,0.000032823635,0.000025127061,0.000048696333,0.00035918428,0.000026654345,0.0063821683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997367,0.000059772647,0.000012250751,0.00008388972,0.00005285815,0.000054468735],"domain_scores_gemma":[0.9994824,0.0002453139,0.00006616766,0.000023354998,0.00014649297,0.000036270583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066214625,0.00081931,0.0012205039,0.0007187746,0.0004625749,0.0007740935,0.0016150806,0.0014415435,0.0026999859],"category_scores_gemma":[0.0014826343,0.00048961554,0.0008391092,0.0006445355,0.00056270853,0.00068062794,0.00046824192,0.0009173803,0.00036239397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015408317,0.0000064545325,0.00033477007,0.000008227272,0.000006889606,0.00001914055,0.0000058555256,0.99727577,0.00013910694,0.0005509273,0.00012373217,0.0015137322],"study_design_scores_gemma":[0.000001112401,0.0000031471877,0.00008088547,5.13183e-7,0.0000019568022,0.0000017980342,7.8979957e-7,0.99968576,0.00002312019,0.00018389417,0.000015981825,0.0000010054836],"about_ca_topic_score_codex":0.056383513,"about_ca_topic_score_gemma":0.015837578,"teacher_disagreement_score":0.056383513,"about_ca_system_score_codex":0.0009395866,"about_ca_system_score_gemma":0.00132749,"threshold_uncertainty_score":0.112110674},"labels":[],"label_agreement":null},{"id":"W3119148821","doi":"10.4203/ccp.106.102","title":"Forecasting the Failure Consequences of Oil Pipelines","year":2014,"lang":"en","type":"article","venue":"Civil-comp proceedings","topic":"Engineering Diagnostics and Reliability","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":"Concordia University","funders":"","keywords":"Pipeline transport; Petroleum engineering; Computer science; Computer security; Environmental science; Engineering","score_opus":0.009806302738856434,"score_gpt":0.1865530410686054,"score_spread":0.17674673832974896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119148821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901751,0.00021187364,0.0061232178,0.00041652273,0.000048844464,0.000024875611,0.001288498,0.00020213018,0.0015088677],"genre_scores_gemma":[0.99804085,0.000106271276,0.00092699804,0.000008694524,0.000015686408,0.0000038591356,0.00058590795,0.0000061291457,0.00030561138],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996958,0.000056200548,0.00002234947,0.00007558177,0.00008791416,0.000062110994],"domain_scores_gemma":[0.9977349,0.0009926907,0.00047654443,0.00014563213,0.000427713,0.00022248177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010166735,0.0008905368,0.00049188663,0.0019958236,0.0003562757,0.0007754564,0.00065285666,0.0015649362,0.0011609758],"category_scores_gemma":[0.0054016304,0.0004416489,0.00050443184,0.0011619455,0.00035400258,0.0014009178,0.0003914549,0.0010803635,0.00029676943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021116246,0.00009956665,0.10011137,0.000033521115,0.000074894546,0.00025111414,0.000029994137,0.88156515,0.0016231844,0.0008841704,0.0013534667,0.013762459],"study_design_scores_gemma":[0.0000060676552,0.000048859496,0.022511523,0.0000054477114,0.000014618036,0.000028653552,0.000056664874,0.9756142,0.00044587892,0.0010615174,0.00019523644,0.000011296869],"about_ca_topic_score_codex":0.029277781,"about_ca_topic_score_gemma":0.02678425,"teacher_disagreement_score":0.029277781,"about_ca_system_score_codex":0.0009737163,"about_ca_system_score_gemma":0.0006311222,"threshold_uncertainty_score":0.058214724},"labels":[],"label_agreement":null},{"id":"W3119863467","doi":"","title":"Predictive risk-based model for oil and gas pipelines","year":2013,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Concordia University","funders":"","keywords":"Pipeline transport; Petroleum engineering; Environmental science; Engineering; Environmental engineering","score_opus":0.0050666773564778935,"score_gpt":0.18212837850543465,"score_spread":0.17706170114895675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119863467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14253984,0.0010752936,0.84687376,0.0011503139,0.000110003835,0.000069139256,0.000722694,0.00090834446,0.006550539],"genre_scores_gemma":[0.98130167,0.00031938977,0.011207338,0.000065849425,0.000042074,0.00006120411,0.0003497844,0.000048137248,0.0066046445],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993987,0.00018692247,0.00002711536,0.0001392132,0.00014589739,0.000102009195],"domain_scores_gemma":[0.9984566,0.00096108887,0.00018611844,0.00007270862,0.00025918818,0.000064177795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00157168,0.001047199,0.0015949673,0.000853671,0.00046701496,0.0015266648,0.0021294523,0.0020085673,0.0023836507],"category_scores_gemma":[0.004594782,0.000742075,0.00092549913,0.0007731793,0.0009187498,0.0013278998,0.00094405987,0.00176561,0.00035008046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012596345,0.0000042357,0.00012576317,0.0000053889753,0.000004954751,0.000013499659,0.000004692451,0.99743,0.000067445784,0.0012026838,0.000074289914,0.0010543471],"study_design_scores_gemma":[0.000001526338,0.0000029173223,0.000042431067,9.2136156e-7,0.0000021559042,0.000002929204,7.3795934e-7,0.9990107,0.000031551343,0.0008756471,0.000026674814,0.0000018565819],"about_ca_topic_score_codex":0.024982654,"about_ca_topic_score_gemma":0.010687832,"teacher_disagreement_score":0.024982654,"about_ca_system_score_codex":0.0015339566,"about_ca_system_score_gemma":0.0014456676,"threshold_uncertainty_score":0.04967451},"labels":[],"label_agreement":null},{"id":"W3120149862","doi":"10.1115/gt2020-15756","title":"An Ensemble of Recurrent Neural Networks for Real Time Performance Modelling of Three-Spool Aero-Derivative Gas Turbine Engine","year":2020,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Siemens (Canada); École de Technologie Supérieure","funders":"","keywords":"Nonlinear autoregressive exogenous model; Artificial neural network; Computer science; Autoregressive model; Generalization; MATLAB; Process (computing); Control theory (sociology); Control engineering; Artificial intelligence; Engineering; Mathematics","score_opus":0.01921054416359242,"score_gpt":0.20594532949643687,"score_spread":0.18673478533284446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120149862","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46909133,0.000960199,0.5234094,0.00025837342,0.00012710814,0.00007456563,0.00025940075,0.00135563,0.0044639986],"genre_scores_gemma":[0.9883732,0.00011250669,0.010520565,0.00001416336,0.000007245176,0.000039578623,0.00011011145,0.000016599295,0.0008060148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998275,0.000050824423,0.0000140110005,0.00004271144,0.00004331658,0.00002157627],"domain_scores_gemma":[0.999778,0.00008554701,0.000030445472,0.000018130648,0.000076139055,0.000011825144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064666104,0.0007930717,0.0006322134,0.0003771015,0.00028237794,0.00059556344,0.0006965532,0.0006876827,0.0006111882],"category_scores_gemma":[0.0008792253,0.00034389566,0.0007436047,0.0002578505,0.00017431514,0.0004516287,0.0003143903,0.0007211143,0.0001874391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000334775,0.00003352175,0.0006669693,0.000018008368,0.00003882836,0.000043282587,0.000019483223,0.9847801,0.0014653872,0.00022911736,0.00013424411,0.012537583],"study_design_scores_gemma":[4.571482e-7,0.0000067816113,0.00010206501,9.4540917e-7,0.0000028306843,0.000001320682,0.0000013191413,0.9996443,0.00018156765,0.000032374028,0.000024702114,0.000001271822],"about_ca_topic_score_codex":0.012196269,"about_ca_topic_score_gemma":0.008374468,"teacher_disagreement_score":0.012196269,"about_ca_system_score_codex":0.0005106576,"about_ca_system_score_gemma":0.00040416195,"threshold_uncertainty_score":0.024250567},"labels":[],"label_agreement":null},{"id":"W3126197344","doi":"10.26443/mjm.v7i1.535","title":"A MORE OBJECTIVE APPROACH FOR SELECTING THE JOURNAL TO WHICH ONE SUBMITS A MANUSCRIPT","year":2020,"lang":"en","type":"article","venue":"McGill Journal of Medicine","topic":"Engineering Diagnostics and Reliability","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":"School of Medicine, Emory University; Emory University","keywords":"Medicine","score_opus":0.031064876367863026,"score_gpt":0.2416598253506025,"score_spread":0.21059494898273945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126197344","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"evaluation","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"evaluation","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02033276,0.008504391,0.34217098,0.2839805,0.1560315,0.015772417,0.0034278757,0.008736203,0.16104342],"genre_scores_gemma":[0.083417006,0.0061308257,0.63094985,0.071367,0.06180574,0.0072998465,0.0020634225,0.004950755,0.13201557],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.90806574,0.036146738,0.025654605,0.0043610907,0.023345899,0.002425961],"domain_scores_gemma":[0.6497073,0.061320856,0.03780057,0.022335466,0.2008028,0.028032964],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.075091414,0.002000618,0.0029448126,0.014799369,0.008522569,0.017292459,0.002296666,0.0064596203,0.052233953],"category_scores_gemma":[0.23815432,0.0016490497,0.0024427578,0.004688464,0.003471438,0.0082473075,0.0052987547,0.007751498,0.039868042],"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":[0.001559341,0.00041802562,0.009053259,0.003527801,0.00037951875,0.0014134652,0.0011163595,0.00041595055,0.013139847,0.00888648,0.5931308,0.36695904],"study_design_scores_gemma":[0.0008328018,0.0009033075,0.021799145,0.0051755277,0.0005379612,0.007933437,0.0037950794,0.0049805706,0.010929485,0.02978489,0.91215354,0.0011742937],"about_ca_topic_score_codex":0.0018638498,"about_ca_topic_score_gemma":0.007571083,"teacher_disagreement_score":0.9249086,"about_ca_system_score_codex":0.0026159785,"about_ca_system_score_gemma":0.017309688,"threshold_uncertainty_score":0.39712608},"labels":[],"label_agreement":null},{"id":"W3127174605","doi":"10.5220/0010249503580365","title":"Determining the Required Size of a Military Training Pipeline","year":2021,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Department of National Defence","funders":"","keywords":"Pipeline (software); Computer science; Training (meteorology); Operating system; Physics","score_opus":0.01334458332178965,"score_gpt":0.21051505699410916,"score_spread":0.19717047367231952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127174605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5117737,0.00043131103,0.45701542,0.0012799539,0.0002763219,0.00054513203,0.0021255226,0.0031547912,0.023397852],"genre_scores_gemma":[0.93547124,0.000101626385,0.060824104,0.00006148745,0.0000189631,0.000107945336,0.0005621933,0.00018128338,0.0026711826],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908817,0.00015651908,0.000047366717,0.00017763443,0.00034540944,0.00018492067],"domain_scores_gemma":[0.995379,0.0022768644,0.00040832115,0.00031737622,0.0012655786,0.0003528399],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013043594,0.0006863003,0.00064999925,0.0012434698,0.0010380524,0.0009984671,0.0010027689,0.0011140062,0.010770384],"category_scores_gemma":[0.010132358,0.0006525534,0.0005753724,0.00034591858,0.00045491374,0.0024844313,0.0010522903,0.00074416684,0.0025385453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024836422,0.00048852066,0.04443187,0.0010833851,0.000077129145,0.0009987028,0.00055267283,0.3486258,0.34834403,0.011516445,0.010385575,0.23101217],"study_design_scores_gemma":[0.00014880527,0.0024159641,0.050569426,0.00019280997,0.00013986882,0.0008163586,0.0012167008,0.74727017,0.1721801,0.010031328,0.01488073,0.00013775288],"about_ca_topic_score_codex":0.0033403614,"about_ca_topic_score_gemma":0.0045232843,"teacher_disagreement_score":0.010770384,"about_ca_system_score_codex":0.0009007513,"about_ca_system_score_gemma":0.0023273528,"threshold_uncertainty_score":0.03603053},"labels":[],"label_agreement":null},{"id":"W3132228168","doi":"","title":"Advanced signal processing techniques to improve the detection of defects in pressure vessels by acoustic emission testing","year":2020,"lang":"en","type":"article","venue":"Espace ÉTS (ETS)","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":0,"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":"Acoustic emission; Signal processing; Acoustics; SIGNAL (programming language); Detection theory; Computer science; Digital signal processing; Telecommunications; Physics; Detector; Computer hardware","score_opus":0.004887365518921588,"score_gpt":0.2127555551052986,"score_spread":0.207868189586377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3132228168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09395388,0.0007958457,0.902082,0.00021437001,0.000093961746,0.000045729063,0.00012313756,0.0012818864,0.0014091185],"genre_scores_gemma":[0.5217179,0.0008564564,0.47218743,0.00016163428,0.00014307376,0.0000764991,0.00046459242,0.00018330802,0.00420909],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99955946,0.000077910816,0.000020256677,0.0000648487,0.00025036727,0.000027120705],"domain_scores_gemma":[0.9989606,0.0005361887,0.00007739226,0.00008600612,0.00031628314,0.000023542112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005573122,0.0007148189,0.00033188274,0.00075321895,0.0001152977,0.00047440457,0.0006643812,0.00076354,0.0024537258],"category_scores_gemma":[0.0017342139,0.00019568141,0.00029918362,0.0004370291,0.0002757096,0.0007478013,0.000417998,0.00069338235,0.000739047],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002831788,0.00013389795,0.001546687,0.0001590346,0.000038145667,0.00011340862,0.00006167908,0.008624758,0.6545936,0.0011862033,0.0007746149,0.3324847],"study_design_scores_gemma":[0.00006387834,0.0008765946,0.013749764,0.000048568327,0.000112168906,0.0008899754,0.00006766661,0.44428414,0.5307325,0.0024647173,0.006655035,0.00005501917],"about_ca_topic_score_codex":0.00034561942,"about_ca_topic_score_gemma":0.0005512683,"teacher_disagreement_score":0.0024537258,"about_ca_system_score_codex":0.00010585125,"about_ca_system_score_gemma":0.00018563699,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W3133715030","doi":"10.1088/1755-1315/688/1/012014","title":"Catode and Anode Processes in Sulfur Corrosion Destruction of Metal Constructions of Prolonged Exploitation in an Aggressive Environment","year":2021,"lang":"en","type":"article","venue":"IOP Conference Series Earth and Environmental Science","topic":"Engineering Diagnostics and Reliability","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 Manitoba","funders":"","keywords":"Corrosion; Anode; Cathode; Hydrogen; Cathodic protection; Electrolyte; Hydrogen embrittlement; Hydrogen sulfide; Materials science; Depolarization; Sulfide; Chemistry; Sulfur; Inorganic chemistry; Electrode; Metallurgy","score_opus":0.00806808137248714,"score_gpt":0.19066727013872167,"score_spread":0.18259918876623454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133715030","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99087965,0.0026620664,0.00275309,0.000057412657,0.0000184357,0.000017093364,0.000067106834,0.00003365852,0.003511564],"genre_scores_gemma":[0.9967775,0.0006524528,0.00053684943,0.00001010211,0.0000038976236,0.0000042489205,0.000047277816,0.000005964373,0.0019617013],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99976724,0.00003706727,0.000009360588,0.000036084508,0.00010537502,0.000044886237],"domain_scores_gemma":[0.999884,0.000023331986,0.000025767355,0.0000095197765,0.000046409732,0.0000110363735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023588062,0.00020171491,0.0002859568,0.00043795936,0.0002543804,0.00041828296,0.00028502947,0.00036718327,0.0013464963],"category_scores_gemma":[0.00020085779,0.00011949895,0.0003166856,0.00025067697,0.0003363246,0.00036673743,0.0003238966,0.0002540096,0.00034320657],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004046045,0.00004984824,0.0052991873,0.00038812243,0.000026383563,0.0006709129,0.00044846348,0.0013082117,0.9802106,0.0014794576,0.00014102341,0.009573168],"study_design_scores_gemma":[0.000012024169,0.0008191416,0.027322995,0.000027569966,0.000037318387,0.00070056476,0.00060072046,0.005874689,0.95953006,0.0010232027,0.004036042,0.000015823314],"about_ca_topic_score_codex":0.0012759501,"about_ca_topic_score_gemma":0.0011192801,"teacher_disagreement_score":0.0013464963,"about_ca_system_score_codex":0.00036952744,"about_ca_system_score_gemma":0.00022340742,"threshold_uncertainty_score":0.004504502},"labels":[],"label_agreement":null},{"id":"W3153484358","doi":"10.1007/s12541-021-00515-z","title":"Assessment of Geometrical Features of Internal Flaws with Artificial Neural Network","year":2021,"lang":"en","type":"article","venue":"International Journal of Precision Engineering and Manufacturing","topic":"Engineering Diagnostics and Reliability","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 Waterloo","funders":"Korea Electrotechnology Research Institute","keywords":"Artificial neural network; Artificial intelligence; Computer science; Engineering; Engineering drawing; Mechanical engineering","score_opus":0.006000986983745796,"score_gpt":0.23772412536672044,"score_spread":0.23172313838297465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153484358","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75586087,0.000475628,0.24054268,0.00009971027,0.00005960596,0.00007258498,0.00026794343,0.0007596449,0.0018613546],"genre_scores_gemma":[0.9771214,0.000106858555,0.022116242,0.000010845332,0.000009830334,0.000012435764,0.00015408895,0.000014298428,0.0004540107],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978787,0.00003153069,0.000020422634,0.000046219637,0.000089164976,0.000024834713],"domain_scores_gemma":[0.9992512,0.00024048865,0.00012434504,0.000050493745,0.00030154834,0.000031990745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055972213,0.00061036425,0.00043789615,0.0018808882,0.00015150972,0.00047659563,0.000432668,0.000676525,0.0005872933],"category_scores_gemma":[0.0013225538,0.0002469895,0.00053148356,0.00082526344,0.00025401323,0.0007193273,0.00034260994,0.00030264832,0.0001572198],"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":[0.0011932601,0.00032872692,0.07491506,0.0003815984,0.00026325832,0.00059384597,0.00014505081,0.410464,0.08672245,0.0010517606,0.0015224066,0.4224186],"study_design_scores_gemma":[0.000008691204,0.00007722973,0.018665524,0.000008624218,0.000037152964,0.00007020877,0.000029186232,0.97586775,0.004797023,0.0002759388,0.00014401042,0.000018727813],"about_ca_topic_score_codex":0.0018563537,"about_ca_topic_score_gemma":0.0019946082,"teacher_disagreement_score":0.0018808882,"about_ca_system_score_codex":0.00024843207,"about_ca_system_score_gemma":0.00026580621,"threshold_uncertainty_score":0.0036910176},"labels":[],"label_agreement":null},{"id":"W3194365380","doi":"10.5006/c2021-16245","title":"Challenges in Implementing SP21424-2018 AC Corrosion Criteria.","year":2021,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Alberta Energy","funders":"","keywords":"Corrosion; Materials science; Metallurgy; Computer science","score_opus":0.030805651757208816,"score_gpt":0.2637259279171846,"score_spread":0.23292027615997576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194365380","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.121915676,0.009153902,0.6892584,0.021246012,0.0027737785,0.0029687393,0.0012973062,0.005273032,0.14611316],"genre_scores_gemma":[0.45130637,0.0019174175,0.51985323,0.002051827,0.00047835358,0.0012014236,0.0012667701,0.00075075374,0.021173792],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.96608716,0.00832022,0.0031680202,0.0011944255,0.020280618,0.00094964594],"domain_scores_gemma":[0.9115042,0.008486834,0.0040873163,0.0036143856,0.071134105,0.0011730958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.031560197,0.0012492755,0.00081234606,0.002785545,0.0011427592,0.0040297955,0.0037185592,0.0022161365,0.004566617],"category_scores_gemma":[0.029654033,0.00051441276,0.0004664115,0.00090551464,0.0014276427,0.003768019,0.0027525392,0.002132694,0.0032862222],"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":[0.00045689996,0.0010248269,0.014042385,0.0030113137,0.00008125915,0.00073503965,0.0019000006,0.05146968,0.1812269,0.07001952,0.069004,0.6070281],"study_design_scores_gemma":[0.00014907251,0.0029905173,0.019736437,0.0018487308,0.00008823885,0.001677933,0.0057382598,0.130911,0.17133999,0.04058758,0.62453705,0.0003952265],"about_ca_topic_score_codex":0.00889557,"about_ca_topic_score_gemma":0.0113740135,"teacher_disagreement_score":0.031560197,"about_ca_system_score_codex":0.0034864347,"about_ca_system_score_gemma":0.0057072625,"threshold_uncertainty_score":0.16690826},"labels":[],"label_agreement":null},{"id":"W3198440767","doi":"","title":"Investigation of the impact of coatings on the corrosion of nuclear components","year":2015,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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 Nuclear Laboratories","funders":"","keywords":"Corrosion; Metallurgy; Materials science; Forensic engineering; Environmental science; Business; Engineering","score_opus":0.025591204147814548,"score_gpt":0.2134580701751961,"score_spread":0.18786686602738156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198440767","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954609,0.0009883194,0.0009847133,0.000048017067,0.000029002287,0.000017325607,0.00008262416,0.000016017639,0.0023731738],"genre_scores_gemma":[0.99651045,0.0007176954,0.0008859947,0.000030798285,0.000012687136,0.0000044782423,0.000108751374,0.000013267519,0.0017158772],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99958676,0.00004687086,0.000012182335,0.00004507028,0.00023096272,0.00007823975],"domain_scores_gemma":[0.9995161,0.00011188754,0.000060012233,0.000042556097,0.00024041803,0.000028910576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030197707,0.00033982995,0.00033723065,0.0002683894,0.00032896257,0.00044525045,0.00044215904,0.00060382875,0.0013620296],"category_scores_gemma":[0.00086483604,0.00019011181,0.00040070064,0.00020965388,0.00032286285,0.00026189353,0.00023015733,0.00045584567,0.00025876568],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065625575,0.00007491678,0.0026947686,0.00019067085,0.000034694014,0.00023893324,0.00008172412,0.0009213528,0.98805237,0.00012847387,0.0001618752,0.0067638536],"study_design_scores_gemma":[0.000017043818,0.001688778,0.018434025,0.00001195665,0.000058686852,0.00029764674,0.00012883647,0.005032306,0.97261107,0.000050823543,0.0016585023,0.000010389],"about_ca_topic_score_codex":0.0027228077,"about_ca_topic_score_gemma":0.00258753,"teacher_disagreement_score":0.0027228077,"about_ca_system_score_codex":0.00034035504,"about_ca_system_score_gemma":0.000290126,"threshold_uncertainty_score":0.00541389},"labels":[],"label_agreement":null},{"id":"W3215553514","doi":"","title":"Phased array ultrasonic technology contribution to engineering critical assessment (ECA) of economizer piping welds","year":2006,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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 Power Generation","funders":"","keywords":"Piping; Economizer; Engineering; Phased array ultrasonics; Nondestructive testing; Phased array; Ultrasonic testing; Forensic engineering; Mechanical engineering; Acoustics; Ultrasonic sensor; Electrical engineering; Physics","score_opus":0.0022071275655500384,"score_gpt":0.2179298113782959,"score_spread":0.21572268381274587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215553514","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08893692,0.006694396,0.88818556,0.00064743654,0.00040676325,0.00011701717,0.000063390566,0.00065695145,0.014291521],"genre_scores_gemma":[0.79731655,0.0044966056,0.18995053,0.00016023274,0.0004015798,0.000060218128,0.000065345586,0.0001026414,0.00744634],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991271,0.00018318575,0.000035237063,0.00013053347,0.00048171787,0.000042308595],"domain_scores_gemma":[0.9980842,0.0008650639,0.00008545006,0.00011860433,0.00080218917,0.00004451261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011345893,0.0005568593,0.00032487072,0.0012729167,0.00033724346,0.0011779845,0.0005683564,0.00081139494,0.0019352997],"category_scores_gemma":[0.0024927207,0.00044798324,0.00025585026,0.00064777164,0.0006037516,0.0011520995,0.0006708941,0.00084449793,0.0004716896],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004240303,0.00011715346,0.0052028,0.00037077157,0.000044096883,0.0001826404,0.00032068303,0.028071746,0.48194736,0.014264545,0.001057638,0.46799645],"study_design_scores_gemma":[0.00004956549,0.0009016764,0.009745915,0.00006974626,0.00015844735,0.0009369623,0.00025051215,0.2950344,0.65080774,0.010447189,0.031508975,0.00008885421],"about_ca_topic_score_codex":0.0006881387,"about_ca_topic_score_gemma":0.000664981,"teacher_disagreement_score":0.0019352997,"about_ca_system_score_codex":0.0004943673,"about_ca_system_score_gemma":0.0007160034,"threshold_uncertainty_score":0.0064742565},"labels":[],"label_agreement":null},{"id":"W3217650763","doi":"10.36001/phmconf.2021.v13i1.3052","title":"On failure prediction and failure identification modeling in a gas turbine system: a survey of classification approaches in a three-class problem","year":2021,"lang":"en","type":"article","venue":"Annual Conference of the PHM Society","topic":"Engineering Diagnostics and Reliability","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":"National Research Council Canada","funders":"Ministère de la Défense Nationale; University of Toronto; National Research Council Canada; Defence Research and Development Canada","keywords":"Computer science; Identification (biology); Class (philosophy); Data collection; Set (abstract data type); Warning system; Data set; Data mining; Machine learning; Event (particle physics); Artificial intelligence; Reliability engineering; Engineering","score_opus":0.04441908455242971,"score_gpt":0.2144957241773948,"score_spread":0.17007663962496508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3217650763","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":[0.019637698,0.0099110715,0.96546304,0.0015547818,0.00016141252,0.000100512385,0.00014440858,0.00033445517,0.00269251],"genre_scores_gemma":[0.6274471,0.026544593,0.33202052,0.0013221801,0.0022839254,0.00057948264,0.0011096274,0.00019869609,0.008493772],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99819595,0.0007710418,0.00014342634,0.0004263593,0.00034298797,0.000120371864],"domain_scores_gemma":[0.99377584,0.005102495,0.0003172963,0.00015525537,0.000569196,0.00007990803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038061228,0.0017921927,0.0021356337,0.0022324072,0.00067064445,0.002118025,0.0020967457,0.0025909438,0.0013879124],"category_scores_gemma":[0.005348078,0.00045063958,0.0015187466,0.0032111227,0.0011029562,0.002311422,0.00088918617,0.0025026703,0.00049544434],"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":[0.0001624777,0.0005219046,0.0075864866,0.0006075545,0.00019099745,0.00014553535,0.00028249607,0.6185743,0.00094969594,0.0141256,0.0050648134,0.3517882],"study_design_scores_gemma":[0.0000047577737,0.00005853856,0.0007508265,0.00005860537,0.000016019036,0.000028442348,0.000045139168,0.99079585,0.00022817233,0.0070428094,0.0009527176,0.000018094288],"about_ca_topic_score_codex":0.012479159,"about_ca_topic_score_gemma":0.004880707,"teacher_disagreement_score":0.012479159,"about_ca_system_score_codex":0.0009393234,"about_ca_system_score_gemma":0.0008287702,"threshold_uncertainty_score":0.024813056},"labels":[],"label_agreement":null},{"id":"W4200372379","doi":"10.33423/jabe.v23i7.4867","title":"IPO Underpricing and Prospectus Readability: A Machine Learning Approach","year":2021,"lang":"en","type":"article","venue":"Journal of Applied Business and Economics","topic":"Engineering Diagnostics and Reliability","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":"Prospectus; Initial public offering; Business; Readability; Stock exchange; Monetary economics; Accounting; Finance; Economics; Computer science","score_opus":0.004972010358045508,"score_gpt":0.15657577292407548,"score_spread":0.15160376256602998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200372379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92000437,0.0013198721,0.072844945,0.0011586939,0.00006794472,0.00012597413,0.000845818,0.00028814044,0.0033442432],"genre_scores_gemma":[0.99050844,0.0002720807,0.007686489,0.00003936811,0.000068148925,0.000030115882,0.00050453935,0.000005054938,0.0008856862],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99948394,0.00017203696,0.000054862332,0.00011245796,0.00010636446,0.00007029142],"domain_scores_gemma":[0.9953178,0.0033795838,0.00047587536,0.00013307344,0.0005143416,0.00017927338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001775008,0.00073433766,0.0006120297,0.0035266965,0.0003679861,0.0013736095,0.00062009745,0.0008663367,0.0013318977],"category_scores_gemma":[0.0058506844,0.00021404892,0.00066700927,0.001780604,0.00040670298,0.0010065943,0.00049933605,0.0011878326,0.00034304627],"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":[0.0007205616,0.0016717698,0.5349914,0.00017427318,0.00043394446,0.0005531702,0.00036367853,0.18859768,0.0020030334,0.0028213444,0.004017692,0.26365146],"study_design_scores_gemma":[0.0000064906453,0.000091339665,0.037094478,0.000017632436,0.000038217077,0.000050238425,0.00008316095,0.9604367,0.00032078667,0.0016464833,0.00020039239,0.00001405409],"about_ca_topic_score_codex":0.00593234,"about_ca_topic_score_gemma":0.0036372133,"teacher_disagreement_score":0.00593234,"about_ca_system_score_codex":0.0006516895,"about_ca_system_score_gemma":0.00056610414,"threshold_uncertainty_score":0.01179558},"labels":[],"label_agreement":null},{"id":"W4205517757","doi":"10.3390/ma15020560","title":"Study on the P-S-N Curve of Sucker Rod Based on Three-Parameter Weibull Distribution","year":2022,"lang":"en","type":"article","venue":"Materials","topic":"Engineering Diagnostics and Reliability","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 Calgary","funders":"National Natural Science Foundation of China","keywords":"Sucker rod; Sucker; Weibull distribution; Rod; Concentric; Structural engineering; Shape parameter; Fatigue limit; Materials science; Reliability (semiconductor); Mathematics; Composite material; Engineering; Statistics; Geometry; Physics; Anatomy","score_opus":0.01303713806651685,"score_gpt":0.21173237560697517,"score_spread":0.1986952375404583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205517757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5935967,0.0035616867,0.38605994,0.00036521387,0.00006361611,0.0000815457,0.0005245358,0.001834536,0.013912181],"genre_scores_gemma":[0.98784155,0.0005602333,0.008708001,0.000038032777,0.000013508211,0.00002139109,0.00026311202,0.000091904454,0.0024623345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9991518,0.00009578701,0.00003856697,0.00021314542,0.0004094389,0.00009113044],"domain_scores_gemma":[0.9973755,0.0009912954,0.00037129063,0.00029881636,0.00090157567,0.000061450024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011524749,0.0005373056,0.00036235494,0.0016350035,0.00025765045,0.00043180046,0.000914744,0.00077383016,0.0013037949],"category_scores_gemma":[0.0030078357,0.00025090962,0.0006948082,0.0014354105,0.000504719,0.0010463918,0.000309913,0.0005211162,0.0005237717],"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":[0.0005429895,0.000105509695,0.045228764,0.0006461355,0.00015064311,0.0022453303,0.0013713517,0.56325275,0.15691446,0.015215347,0.0035533404,0.21077335],"study_design_scores_gemma":[0.000008236873,0.00028303944,0.03009378,0.000054598684,0.000050550505,0.0012599876,0.00020523019,0.93872666,0.020236617,0.003152358,0.0058178087,0.00011113017],"about_ca_topic_score_codex":0.0037609213,"about_ca_topic_score_gemma":0.002361845,"teacher_disagreement_score":0.0037609213,"about_ca_system_score_codex":0.0007253803,"about_ca_system_score_gemma":0.00033470494,"threshold_uncertainty_score":0.0074780583},"labels":[],"label_agreement":null},{"id":"W4206045309","doi":"10.15593/2224-9982/2021.66.01","title":"PERM SCIENTIFIC SCHOOL OF BEARINGS FOUNDED BY PROFESSOR BORIS ALEXANDROVICH IVANOV","year":2021,"lang":"en","type":"article","venue":"Perm National Research Polytechnic University Aerospace Engineering Bulletin","topic":"Engineering Diagnostics and Reliability","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":"Quarter (Canadian coin); Section (typography); Management; Engineering; Sociology; History; Computer science","score_opus":0.01749741323122016,"score_gpt":0.25690573506579395,"score_spread":0.23940832183457378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206045309","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":[0.01157126,0.20979913,0.016654452,0.035616014,0.053740356,0.00015800168,0.00317298,0.0019932697,0.66729456],"genre_scores_gemma":[0.08626271,0.07414159,0.0090897735,0.0023910936,0.011606771,0.0001603404,0.0021747344,0.00073032355,0.81344265],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913496,0.00007544498,0.000056367997,0.00028433156,0.00036054692,0.00008840943],"domain_scores_gemma":[0.99949634,0.00006962067,0.00005276084,0.000050558177,0.00016430556,0.00016638795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007459789,0.0010822177,0.000977648,0.0020193195,0.0012880603,0.002789726,0.0008299521,0.0016263879,0.07046462],"category_scores_gemma":[0.001332815,0.00033979383,0.00044041293,0.0009699567,0.0009748014,0.0014919491,0.001961543,0.002383603,0.04500553],"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":[0.00022628256,0.00006828174,0.0012289078,0.0008377323,0.000026179123,0.00041571134,0.00031919644,0.0012371923,0.0030211948,0.10463747,0.47952682,0.408455],"study_design_scores_gemma":[0.000005979543,0.000028042625,0.00064732454,0.000102760714,0.0000034684322,0.00023003056,0.000030270401,0.00017652469,0.00050942804,0.003427351,0.9948331,0.0000057647912],"about_ca_topic_score_codex":0.0011867954,"about_ca_topic_score_gemma":0.00093540415,"teacher_disagreement_score":0.07046462,"about_ca_system_score_codex":0.00148907,"about_ca_system_score_gemma":0.0025399015,"threshold_uncertainty_score":0.23572761},"labels":[],"label_agreement":null},{"id":"W4213144202","doi":"10.6000/1929-5030.2022.11.03","title":"Мultifunctional Inhibitors of \"INCORGAZ\" and \"AMDOR\" Series against Hydrosulfide and Carbon Dioxide Corrosion of Steel","year":2022,"lang":"en","type":"article","venue":"Journal of Applied Solution Chemistry and Modeling","topic":"Engineering Diagnostics and Reliability","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":"Corrosion; Hydrogen sulfide; Carbon dioxide; Carbon steel; Chemistry; Sulfide; Sulfate-reducing bacteria; Hydrogen; Metal; Carbon fibers; Hydrogen sulphide; Inorganic chemistry; Sulfate; Metallurgy; Materials science; Organic chemistry; Composite material; Sulfur","score_opus":0.005520974503241201,"score_gpt":0.1761929590485988,"score_spread":0.1706719845453576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213144202","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99570614,0.0016844197,0.0006863992,0.00002810452,0.000028280034,0.00003703395,0.00017269631,0.00004458512,0.0016123431],"genre_scores_gemma":[0.99472964,0.0019859842,0.0012638831,0.000033186006,0.000022075466,0.000029782319,0.0002877785,0.000012455985,0.0016352759],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99991286,0.000017632447,0.000007759154,0.0000136710105,0.000024690966,0.000023451203],"domain_scores_gemma":[0.9998889,0.000022941165,0.000029570638,0.000011281547,0.000019772238,0.000027549933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012247961,0.0003732026,0.00025828552,0.0002804189,0.00009233198,0.00015553931,0.00032769926,0.00019495863,0.0011785575],"category_scores_gemma":[0.0002272437,0.00008602157,0.00020441275,0.00016813734,0.000105835614,0.00012591467,0.00011755444,0.00025003462,0.0002359947],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015677853,0.0002275582,0.00058562966,0.00024424816,0.000052540025,0.000084186744,0.000026397223,0.000549494,0.9828116,0.00028419073,0.00016800978,0.013398288],"study_design_scores_gemma":[0.000108241984,0.00388137,0.0026907588,0.000020990172,0.00009489236,0.0001348969,0.000016829492,0.0010276969,0.9884869,0.000027803748,0.0034983638,0.000011192537],"about_ca_topic_score_codex":0.0005547902,"about_ca_topic_score_gemma":0.0006253845,"teacher_disagreement_score":0.0011785575,"about_ca_system_score_codex":0.000120789504,"about_ca_system_score_gemma":0.0001565217,"threshold_uncertainty_score":0.0039426684},"labels":[],"label_agreement":null},{"id":"W4220727637","doi":"10.1007/978-3-030-96794-9_29","title":"A Case Study on Probabilistic Technico-Economic Analysis Including Maintenance Cost for Hydroelectric Turbine Fatigue Risk","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Engineering Diagnostics and Reliability","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":"Hydro-Québec","funders":"","keywords":"Regret; Reliability engineering; Deferral; Turbine; Operations research; Probabilistic logic; Net present value; Hydroelectricity; Risk analysis (engineering); Planned maintenance; Unit (ring theory); Engineering; Computer science; Operations management; Production (economics); Business","score_opus":0.01939167681799378,"score_gpt":0.24561503390710326,"score_spread":0.22622335708910948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220727637","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7894415,0.0022684624,0.14742018,0.0016898037,0.00012038141,0.0002686043,0.0010184607,0.00020950548,0.057563115],"genre_scores_gemma":[0.98312336,0.00042563124,0.011140575,0.00002930039,0.000035935387,0.000053367028,0.00012799581,0.000036010828,0.005027924],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993573,0.0003384262,0.000022045357,0.00005644682,0.00014172215,0.00008399923],"domain_scores_gemma":[0.99554527,0.0039183605,0.00012434502,0.00013287808,0.00019956878,0.00007952042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018383388,0.00076726975,0.00085013866,0.001280112,0.0008655471,0.0013066747,0.0012808479,0.002451066,0.004840345],"category_scores_gemma":[0.0045176107,0.00045724967,0.0013470075,0.001869655,0.00077336613,0.0012778754,0.0006921877,0.0011937381,0.00021116696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015283619,0.00021408523,0.002978367,0.000095488234,0.00005092026,0.0016620728,0.000086055996,0.95303303,0.0008229929,0.026715988,0.0014521716,0.012736059],"study_design_scores_gemma":[0.00003381977,0.00016556223,0.003078083,0.0000225049,0.000057569596,0.00059805217,0.00014976686,0.9808005,0.00058972236,0.013001278,0.0014747657,0.00002834776],"about_ca_topic_score_codex":0.00955656,"about_ca_topic_score_gemma":0.009522665,"teacher_disagreement_score":0.00955656,"about_ca_system_score_codex":0.0016786044,"about_ca_system_score_gemma":0.0007239067,"threshold_uncertainty_score":0.019001901},"labels":[],"label_agreement":null},{"id":"W4226474509","doi":"10.5267/j.msl.2022.2.004","title":"Selecting maintenance strategy in a combined cycle power plant: An AHP model utilizing BOCR technique","year":2022,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Engineering Diagnostics and Reliability","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":"Preventive maintenance; Predictive maintenance; Reliability engineering; Proactive maintenance; Computer science; Analytic hierarchy process; Condition-based maintenance; Planned maintenance; Rank (graph theory); Reliability (semiconductor); Total productive maintenance; Plan (archaeology); Operations research; Risk analysis (engineering); Operations management; Power (physics); Production (economics); Engineering; Business; Mathematics","score_opus":0.006992505336940253,"score_gpt":0.20603834891093997,"score_spread":0.1990458435739997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226474509","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23849593,0.00022676607,0.7541406,0.0004341062,0.000036160112,0.0005195425,0.00034559087,0.00017732523,0.005623929],"genre_scores_gemma":[0.8900782,0.00015293811,0.10790858,0.000049949427,0.000015735925,0.00043633673,0.00019494857,0.000012576165,0.0011506658],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999188,0.00040016786,0.000048424678,0.00010384738,0.00017177178,0.00008773462],"domain_scores_gemma":[0.998315,0.0012402836,0.00012297611,0.00002229012,0.00024650866,0.000053013526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018823069,0.0006622558,0.0006491622,0.0010619982,0.00059846055,0.0009952651,0.0009664965,0.0007794077,0.0020174617],"category_scores_gemma":[0.0025352826,0.0002934839,0.00083270133,0.0008247623,0.0003870145,0.0005671132,0.00058005605,0.00084661815,0.00012707514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000106017105,0.00009511344,0.0016150799,0.00013588168,0.000057345347,0.000101268786,0.00022524336,0.97804844,0.001224791,0.0026267879,0.00026604062,0.01549801],"study_design_scores_gemma":[0.000014464111,0.000045610916,0.00020726876,0.000007713825,0.000011065592,0.0000070015276,0.00007500923,0.9985122,0.00013663083,0.00086141826,0.00011630838,0.000005313625],"about_ca_topic_score_codex":0.016626341,"about_ca_topic_score_gemma":0.011279062,"teacher_disagreement_score":0.016626341,"about_ca_system_score_codex":0.0010678418,"about_ca_system_score_gemma":0.0015369077,"threshold_uncertainty_score":0.03305912},"labels":[],"label_agreement":null},{"id":"W4232646332","doi":"10.1520/stp48754s","title":"Measurement of Corrosion Potentials of the Internal Surface of Operating High-Pressure Oil and Gas Pipelines","year":2009,"lang":"en","type":"book-chapter","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Natural Resources Canada; Devon Energy (Canada)","funders":"","keywords":"Corrosion; Petroleum engineering; Pipeline transport; Materials science; Environmental science; Metallurgy; Geology; Environmental engineering","score_opus":0.007910531249336099,"score_gpt":0.1840394486747783,"score_spread":0.1761289174254422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232646332","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31745225,0.041035663,0.35123673,0.0019645789,0.0013257379,0.00021262022,0.0031442656,0.0027290292,0.28089917],"genre_scores_gemma":[0.6790175,0.028744662,0.12590295,0.00058807083,0.00027447593,0.000089525216,0.0022328158,0.00048361532,0.16266643],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995437,0.000026739313,0.00000841109,0.00006935524,0.000333745,0.000017927323],"domain_scores_gemma":[0.99979454,0.00005453587,0.00002395142,0.000023380368,0.00009395701,0.000009714336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024005667,0.00047073016,0.00029339662,0.00068767875,0.00017758216,0.00067572977,0.00056028686,0.00054136413,0.0019625672],"category_scores_gemma":[0.00038357617,0.00020832122,0.00019832561,0.0007864337,0.0003079808,0.0007981395,0.0004731651,0.0008317236,0.0021885494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041198804,0.00005478689,0.0019249937,0.00044652735,0.00001565906,0.00024017863,0.00024970647,0.0011482281,0.74793035,0.0038864585,0.008675426,0.23538648],"study_design_scores_gemma":[0.000004019808,0.00023392367,0.016638992,0.00011792523,0.000023461413,0.002128221,0.00023357858,0.004276934,0.8739549,0.0034220952,0.098919,0.00004695674],"about_ca_topic_score_codex":0.00044368475,"about_ca_topic_score_gemma":0.00072318537,"teacher_disagreement_score":0.0019625672,"about_ca_system_score_codex":0.0002681577,"about_ca_system_score_gemma":0.00018066597,"threshold_uncertainty_score":0.0065654516},"labels":[],"label_agreement":null},{"id":"W4232800508","doi":"10.1115/1.4051112","title":"An Ensemble of Recurrent Neural Networks for Real Time Performance Modeling of Three-Spool Aero-Derivative Gas Turbine Engine","year":2021,"lang":"en","type":"article","venue":"Journal of Engineering for Gas Turbines and Power","topic":"Engineering Diagnostics and Reliability","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":"Siemens (Canada); École de Technologie Supérieure","funders":"","keywords":"Nonlinear autoregressive exogenous model; Artificial neural network; Autoregressive model; Computer science; Generalization; Weighting; MATLAB; Nonlinear system; Control theory (sociology); Control engineering; Artificial intelligence; Engineering; Mathematics","score_opus":0.008593154951357368,"score_gpt":0.21405592001252965,"score_spread":0.20546276506117228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232800508","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48199123,0.00084900064,0.5114757,0.00023321339,0.00011599766,0.000067715766,0.00022460533,0.0012461304,0.0037964175],"genre_scores_gemma":[0.9867057,0.000105524115,0.012257174,0.000014010752,0.000007622419,0.00003823088,0.00010989957,0.000016835878,0.00074506126],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982965,0.000050569637,0.000013358547,0.000042308,0.000043196753,0.000020939304],"domain_scores_gemma":[0.999785,0.00008018272,0.000028953315,0.000019149205,0.00007472156,0.000011957341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000676233,0.00077921647,0.00062069646,0.00038554962,0.00028448974,0.0005411965,0.0006714471,0.0006279306,0.0005410327],"category_scores_gemma":[0.0008639659,0.00034165574,0.0007376461,0.00025954994,0.0001602595,0.00043972177,0.00031391706,0.0006816224,0.00017001435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037831793,0.000038405316,0.00075518474,0.000016692702,0.000045140154,0.000042783187,0.000020062596,0.98190755,0.0017564591,0.00022400887,0.00014055894,0.015015448],"study_design_scores_gemma":[4.4982306e-7,0.000006865609,0.00010424873,8.0192996e-7,0.0000030494298,0.0000012013943,0.0000012456928,0.99963284,0.00019646341,0.000029354997,0.000022222777,0.0000012157415],"about_ca_topic_score_codex":0.01156862,"about_ca_topic_score_gemma":0.008191842,"teacher_disagreement_score":0.01156862,"about_ca_system_score_codex":0.00048386637,"about_ca_system_score_gemma":0.00039273326,"threshold_uncertainty_score":0.023002565},"labels":[],"label_agreement":null},{"id":"W4238390934","doi":"10.5957/josr.10180092","title":"Influence of Ship Speed and Heading Profiles on Fatigue Damage Accumulation for a Naval Vessel","year":2019,"lang":"en","type":"article","venue":"Journal of Ship Research","topic":"Engineering Diagnostics and Reliability","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":"Defence Research and Development Canada","funders":"","keywords":"Heading (navigation); Marine engineering; Aeronautics; Structural engineering; Engineering; Environmental science; Forensic engineering; Aerospace engineering","score_opus":0.10510148988403624,"score_gpt":0.39375538209694533,"score_spread":0.2886538922129091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238390934","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99934417,0.000055881173,0.00023470445,0.000011808587,0.0000052575438,0.0000022075772,0.000069342655,0.00001370552,0.0002628773],"genre_scores_gemma":[0.9996729,0.000028376833,0.00007323589,0.0000033525018,0.0000014478817,9.360163e-7,0.000066846944,0.0000040892483,0.00014901756],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986076,0.000024989338,0.000010452643,0.000024061274,0.000027683664,0.000052053005],"domain_scores_gemma":[0.99825925,0.0010822599,0.00014767658,0.00005885854,0.0003168107,0.00013523277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003900805,0.0002665028,0.00032083402,0.0006076597,0.0003495817,0.00039258986,0.00017459295,0.00043606496,0.0013964415],"category_scores_gemma":[0.0015977451,0.0001908734,0.0003789833,0.00034064462,0.00020224357,0.00027886426,0.0002239267,0.00028954295,0.00022463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011445914,0.00091033627,0.33161312,0.00033528853,0.000415046,0.0026703784,0.00041623335,0.38491723,0.20600408,0.0002351714,0.0018202517,0.059216984],"study_design_scores_gemma":[0.000058704347,0.0036276844,0.70709014,0.000037249156,0.00032808204,0.00049760484,0.0006325352,0.24215901,0.04487596,0.000095713076,0.0005136388,0.0000836825],"about_ca_topic_score_codex":0.006346516,"about_ca_topic_score_gemma":0.007856361,"teacher_disagreement_score":0.006346516,"about_ca_system_score_codex":0.00030183632,"about_ca_system_score_gemma":0.00026109247,"threshold_uncertainty_score":0.012619138},"labels":[],"label_agreement":null},{"id":"W4244789362","doi":"10.4018/978-1-4666-2770-3.ch015","title":"Generating Indicators for Diagnosis of Fault Levels by Integrating Information from Two or More Sensors","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Engineering Diagnostics and Reliability","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":"Fault (geology); SIGNAL (programming language); Information fusion; Impeller; Feature (linguistics); Computer science; Real-time computing; Artificial intelligence; Data mining; Task (project management); Engineering; Control engineering; Pattern recognition (psychology); Systems engineering; Mechanical engineering","score_opus":0.011461810651900849,"score_gpt":0.2351510307118854,"score_spread":0.22368922005998454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244789362","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009691511,0.00596338,0.9592768,0.00040457078,0.00034509873,0.00013479468,0.00064920686,0.0029006652,0.02063403],"genre_scores_gemma":[0.11273579,0.006599865,0.8567414,0.00026284123,0.00022159978,0.00016509395,0.0015899568,0.0005326585,0.02115068],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995234,0.000037650432,0.000024257486,0.00011235552,0.00027479118,0.000027572136],"domain_scores_gemma":[0.99936646,0.00029110868,0.00006327352,0.000078278244,0.00018204056,0.000018879202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062803057,0.0011302081,0.0009166154,0.0024097105,0.00025754757,0.001541722,0.0011251421,0.0012503309,0.00503133],"category_scores_gemma":[0.0012344539,0.0004861991,0.00072834914,0.002203914,0.0005205793,0.0019707258,0.0006963232,0.0013097266,0.0035202794],"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":[0.00013601707,0.000096555916,0.0015109275,0.0008907131,0.00006339162,0.0002860838,0.000289879,0.015067166,0.077527896,0.022560086,0.012349367,0.86922187],"study_design_scores_gemma":[0.000088469074,0.0007136622,0.0119267395,0.0010707026,0.00044861552,0.0034541893,0.0005847463,0.33074504,0.27364925,0.09008268,0.28682086,0.00041499455],"about_ca_topic_score_codex":0.00039529774,"about_ca_topic_score_gemma":0.00054285955,"teacher_disagreement_score":0.00503133,"about_ca_system_score_codex":0.0004045081,"about_ca_system_score_gemma":0.00037227463,"threshold_uncertainty_score":0.016831458},"labels":[],"label_agreement":null},{"id":"W4255633960","doi":"10.1196/annals.1454.040","title":"Protecting Health","year":2008,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Engineering Diagnostics and Reliability","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":"Chemistry; Salt (chemistry); Aqueous solution; Reagent; Mercury (programming language); Sulfide; Solubility; Hazardous waste; Metal; Nickel; Precipitation; Metal ions in aqueous solution; Inorganic chemistry; Environmental chemistry; Organic chemistry; Waste management","score_opus":0.08888929550033998,"score_gpt":0.3120537816938634,"score_spread":0.22316448619352341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255633960","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":[0.007403051,0.01732439,0.004959399,0.14077632,0.010359624,0.00027886833,0.0020375007,0.00083220133,0.8160286],"genre_scores_gemma":[0.1209849,0.03088398,0.009159194,0.1535532,0.0061523067,0.000621344,0.0033281122,0.00035888192,0.67495817],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977653,0.0007788575,0.00009346107,0.00034696434,0.00052080204,0.00049455336],"domain_scores_gemma":[0.9964678,0.00044672188,0.00029286582,0.0009984062,0.00094567914,0.0008484972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032967047,0.00089965045,0.00040364542,0.0008760297,0.0020271083,0.0035766386,0.0011883791,0.0049370155,0.14347744],"category_scores_gemma":[0.006748076,0.00024902375,0.00062637386,0.00059759844,0.001960368,0.002448655,0.0056085284,0.0029278076,0.06345782],"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":[0.00014548571,0.00016985726,0.0053791287,0.0005134595,0.00006990894,0.00034211832,0.0012059114,0.00014926428,0.0034684655,0.07652102,0.5359681,0.3760673],"study_design_scores_gemma":[0.0000119298065,0.00007476673,0.0019504465,0.00033431183,0.00001098779,0.00030554275,0.00029507035,0.000017999082,0.0004018935,0.005780664,0.9908083,0.000008083574],"about_ca_topic_score_codex":0.0028674423,"about_ca_topic_score_gemma":0.002720825,"teacher_disagreement_score":0.14347744,"about_ca_system_score_codex":0.0012519563,"about_ca_system_score_gemma":0.004842318,"threshold_uncertainty_score":0.47997987},"labels":[],"label_agreement":null},{"id":"W4283780054","doi":"10.47119/ijrp1001041720223498","title":"Worksheets for the Improvement of Technical Drafting Skills of Electrical Installation and Maintenance Students","year":2022,"lang":"en","type":"article","venue":"International Journal of Research Publications","topic":"Engineering Diagnostics and Reliability","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":"Worksheet; Mathematics education; Quarter (Canadian coin); Component (thermodynamics); Psychology; Academic year; Computer science; Geography; Physics","score_opus":0.01714197849457643,"score_gpt":0.3569992201542717,"score_spread":0.3398572416596953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283780054","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":[0.99416274,0.0003990973,0.00224013,0.00016960342,0.000036493373,0.00019112501,0.00009402439,0.0000855307,0.0026213035],"genre_scores_gemma":[0.9623583,0.0007729819,0.030891182,0.00008873457,0.000037285878,0.00021775298,0.00027857246,0.00001739921,0.0053378013],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992337,0.00019432206,0.000081770944,0.00009231216,0.00033486527,0.00006315022],"domain_scores_gemma":[0.9979436,0.00064884924,0.00052687293,0.000096211006,0.00044818225,0.00033634048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074787263,0.0003607133,0.0003083819,0.0007354905,0.00032796146,0.0005162718,0.0006276305,0.00033158387,0.002309195],"category_scores_gemma":[0.0041897814,0.00011896493,0.00030877226,0.00042937585,0.00011421275,0.0002854164,0.00058110023,0.0004784172,0.00036267372],"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":[0.0009050064,0.008775844,0.07131798,0.0015370472,0.00007597373,0.0008323884,0.0050055333,0.0014669013,0.06551554,0.0003410721,0.0028728165,0.8413539],"study_design_scores_gemma":[0.00023013432,0.026475077,0.88469875,0.00071457593,0.00023144635,0.0012515702,0.008412912,0.0030805173,0.043282796,0.0008905424,0.030631285,0.000100459554],"about_ca_topic_score_codex":0.000587929,"about_ca_topic_score_gemma":0.0018682203,"teacher_disagreement_score":0.002309195,"about_ca_system_score_codex":0.00018935507,"about_ca_system_score_gemma":0.00047835973,"threshold_uncertainty_score":0.00772506},"labels":[],"label_agreement":null},{"id":"W4290638171","doi":"","title":"THE ROLE OF PSYCHOLOGICAL FACTORS IN THE FORMATION OF COMMITMENT TO PREVENTIVE AND REHABILITATIVE MEASURES IN THE ALUMINUM INDUSTRY WORKERS","year":2021,"lang":"en","type":"article","venue":"Медицина в Кузбассе (Nonprofit Partnership \"Publishing House\" Medicine and Enlightenment \")","topic":"Engineering Diagnostics and Reliability","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":"Psychology; Applied psychology; Social psychology; Demographic economics; Business; Economics","score_opus":0.034757998479258874,"score_gpt":0.29025054942723444,"score_spread":0.25549255094797557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290638171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995388,0.0001415122,0.000019201318,0.00004971545,0.0000026384182,0.000005298775,0.000017973764,6.0638376e-7,0.00022434244],"genre_scores_gemma":[0.99973315,0.000072865834,0.0000379886,0.000009331986,0.000003979563,0.0000050677795,0.000026511212,2.4016094e-7,0.000110987356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996099,0.00015929388,0.000029673505,0.000032118995,0.00009781538,0.00007120259],"domain_scores_gemma":[0.99862266,0.0003455346,0.0005414888,0.00004717419,0.0001393635,0.00030364635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006539545,0.0001464634,0.00014520327,0.00039307727,0.00033185424,0.00033378563,0.00014889626,0.00029128423,0.0016731437],"category_scores_gemma":[0.0020923205,0.00013569044,0.000205343,0.00021017506,0.00026708783,0.00012332977,0.00020322207,0.0003624351,0.00011374723],"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":[0.00006365952,0.00022951823,0.99468887,0.000022882878,0.000022651642,0.000047031226,0.00046822362,0.000027660599,0.00048390348,0.000018535678,0.0000555001,0.0038715103],"study_design_scores_gemma":[0.0000016798963,0.00007728846,0.9994711,0.0000049562473,0.0000035401183,0.000046742512,0.00027421606,0.000029521547,0.000028772905,0.000008283451,0.000052693034,0.0000011856441],"about_ca_topic_score_codex":0.0020568203,"about_ca_topic_score_gemma":0.0023899043,"teacher_disagreement_score":0.0020568203,"about_ca_system_score_codex":0.0002004629,"about_ca_system_score_gemma":0.0004934768,"threshold_uncertainty_score":0.005597174},"labels":[],"label_agreement":null},{"id":"W4294838499","doi":"10.1088/1742-6596/2317/1/012014","title":"Influence of the shape on the hydraulic resistance of bypass channels inside a smart pig for low pressure gas pipeline inspection","year":2022,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":2,"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; Diffuser (optics); Mechanics; Inlet; Flow (mathematics); Channel (broadcasting); Flow control (data); Engineering; Acoustics; Mechanical engineering; Materials science; Electrical engineering; Physics; Optics; Telecommunications","score_opus":0.009532507394812163,"score_gpt":0.19770856760486843,"score_spread":0.18817606021005628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294838499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99106044,0.00015870587,0.007655578,0.00004026064,0.000029471157,0.000008216581,0.00003883669,0.00027723704,0.0007312518],"genre_scores_gemma":[0.9991823,0.000021820033,0.00063419633,0.0000047328263,0.0000015677136,0.0000020830043,0.0000089034465,0.000009439999,0.00013500701],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972504,0.000052754145,0.000010926592,0.00007699135,0.00006036882,0.000073799914],"domain_scores_gemma":[0.9987078,0.0005825768,0.00028723042,0.00014510212,0.00016490732,0.0001124313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040937387,0.00025162927,0.0002747125,0.00025518273,0.00025829612,0.0007130339,0.0003858993,0.00048370147,0.0011653812],"category_scores_gemma":[0.0013938653,0.00019709629,0.0002528134,0.00012955867,0.00055335165,0.0003828939,0.0003078663,0.00021473432,0.00015881799],"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":[0.001562979,0.0001943803,0.022032248,0.00019089444,0.00004205341,0.00058443064,0.00029294455,0.060942676,0.88700384,0.00079167855,0.0006716441,0.025690291],"study_design_scores_gemma":[0.00012418431,0.0034614643,0.064978234,0.000059167756,0.00018470177,0.0006039904,0.0004743613,0.33330098,0.59257835,0.00033510776,0.0037471496,0.00015218894],"about_ca_topic_score_codex":0.0004071661,"about_ca_topic_score_gemma":0.00037955152,"teacher_disagreement_score":0.0011653812,"about_ca_system_score_codex":0.00036848336,"about_ca_system_score_gemma":0.00022559824,"threshold_uncertainty_score":0.0038986206},"labels":[],"label_agreement":null},{"id":"W4301380636","doi":"10.5957/icetech-2006-113","title":"Reliability of Arctic Offshore Installations","year":2006,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Reliability (semiconductor); Reliability engineering; Computer science; Submarine pipeline; Protocol (science); Work (physics); Function (biology); Reliability theory; Arctic; Risk analysis (engineering); Engineering; Failure rate; Business","score_opus":0.0033928071471477305,"score_gpt":0.17884313325931184,"score_spread":0.1754503261121641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301380636","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6558466,0.0016006031,0.30768347,0.0004214792,0.00010198619,0.00006314959,0.0016440466,0.0008075474,0.031831134],"genre_scores_gemma":[0.9899447,0.0004516054,0.0066937148,0.000016398211,0.000018362181,0.000023274903,0.000474681,0.00005931977,0.0023178803],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99867177,0.00025690027,0.000072289906,0.00020783399,0.0006577964,0.00013355345],"domain_scores_gemma":[0.9973573,0.00075063115,0.00046952226,0.00026728332,0.0010711878,0.000084018655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001325341,0.00047501002,0.00037895405,0.0013505914,0.000548329,0.0010453176,0.00050036114,0.00045718037,0.0019277435],"category_scores_gemma":[0.005753625,0.00029061656,0.0003045279,0.00087462267,0.0007179234,0.00076554064,0.0008478335,0.00045827925,0.00074794993],"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":[0.0006400196,0.00004170394,0.05679974,0.0004194938,0.00011976176,0.0012664953,0.001491333,0.7491514,0.027664313,0.044114158,0.0030112236,0.11528038],"study_design_scores_gemma":[0.000048542366,0.0010111239,0.13011327,0.0003794077,0.00018432418,0.0034458744,0.0018055444,0.7188364,0.034396645,0.07722957,0.032289896,0.00025943702],"about_ca_topic_score_codex":0.00450136,"about_ca_topic_score_gemma":0.0031716092,"teacher_disagreement_score":0.00450136,"about_ca_system_score_codex":0.0008062534,"about_ca_system_score_gemma":0.00066448504,"threshold_uncertainty_score":0.008950353},"labels":[],"label_agreement":null},{"id":"W4309879527","doi":"10.1007/s11668-022-01516-4","title":"Fatigue Fracture of Aircraft Engine Compressor Disks","year":2022,"lang":"en","type":"article","venue":"Journal of Failure Analysis and Prevention","topic":"Engineering Diagnostics and Reliability","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":"National Research Council Canada","funders":"","keywords":"Gas compressor; Solid mechanics; Low-cycle fatigue; Fatigue cracking; Materials science; Fatigue testing; Fracture (geology); Turbine; Gas turbines; Structural engineering; Cracking; Engineering; Mechanical engineering; Composite material","score_opus":0.00635453727482793,"score_gpt":0.22676278575748912,"score_spread":0.2204082484826612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309879527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984761,0.00024450195,0.00049505907,0.00003311168,0.000011486398,0.0000050740405,0.000077388,0.00002002654,0.0006373302],"genre_scores_gemma":[0.9988703,0.000036980127,0.00020410439,0.000008510735,0.0000034190832,0.0000027358926,0.00006563231,0.000003570067,0.0008046898],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99985063,0.000014132911,0.000008194993,0.000023243481,0.00006663312,0.00003715814],"domain_scores_gemma":[0.9992575,0.00025926475,0.00005597804,0.000059283473,0.00031809343,0.000049856175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023855218,0.00016786117,0.00033965212,0.00072031614,0.0008140738,0.00030925628,0.00073591707,0.00095799554,0.0028285324],"category_scores_gemma":[0.0012985626,0.00018451712,0.00018681408,0.00030401535,0.00048704376,0.0003508976,0.00021058689,0.00037419584,0.0003711446],"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":[0.009949835,0.00064023293,0.07374252,0.00040710976,0.00011590262,0.0062162043,0.0011995762,0.032790363,0.78324324,0.0014766231,0.0031470333,0.0870713],"study_design_scores_gemma":[0.00016360087,0.0033154592,0.43231395,0.00008414202,0.000101565915,0.0056579057,0.0016036213,0.17903237,0.37179646,0.0007142328,0.0051195435,0.00009706444],"about_ca_topic_score_codex":0.0079468265,"about_ca_topic_score_gemma":0.007664105,"teacher_disagreement_score":0.0079468265,"about_ca_system_score_codex":0.00046643926,"about_ca_system_score_gemma":0.00024564404,"threshold_uncertainty_score":0.015801132},"labels":[],"label_agreement":null},{"id":"W4311078569","doi":"10.18280/ijsse.120509","title":"Relationship Between Occupational Risk and Personal Protective Equipment on the Example of Ferroalloy Production","year":2022,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Engineering Diagnostics and Reliability","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":"Ferroalloy; Personal protective equipment; Production (economics); Occupational exposure; Forensic engineering; Environmental health; Risk analysis (engineering); Engineering; Business; Medicine; Metallurgy; Materials science; Economics; Internal medicine","score_opus":0.017913446495082766,"score_gpt":0.22789550422579516,"score_spread":0.20998205773071238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311078569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99872595,0.00013469116,0.00037613593,0.000023548098,0.0000015057057,0.000005920768,0.000032979424,0.000004650913,0.00069456204],"genre_scores_gemma":[0.9993063,0.000088230096,0.0002462015,0.0000039870324,0.0000032661533,0.000002634722,0.00003921255,0.0000011900258,0.0003089891],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995079,0.00013263834,0.00003955273,0.000051322637,0.00018574457,0.000082804436],"domain_scores_gemma":[0.9975852,0.0009812627,0.0007494827,0.00017997624,0.00035616034,0.00014797498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051053206,0.00022413964,0.00024225084,0.00079605076,0.00030500878,0.00033427638,0.00019283459,0.0003038192,0.0026033672],"category_scores_gemma":[0.0024230878,0.00008658332,0.00036110243,0.00041204187,0.00020534046,0.00020017104,0.00051304046,0.00023348845,0.0001979153],"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":[0.00030608635,0.00014948845,0.97736347,0.000059928767,0.00005779806,0.0008757256,0.00088868494,0.0007531691,0.004452328,0.00012648925,0.000067132394,0.01489982],"study_design_scores_gemma":[0.0000021412607,0.00049826223,0.99444556,0.000018924591,0.000056535806,0.0008551498,0.000833179,0.0005455208,0.0018364959,0.00018299685,0.00071464514,0.000010559192],"about_ca_topic_score_codex":0.001503429,"about_ca_topic_score_gemma":0.0017229067,"teacher_disagreement_score":0.0026033672,"about_ca_system_score_codex":0.00013566378,"about_ca_system_score_gemma":0.00025226153,"threshold_uncertainty_score":0.008709192},"labels":[],"label_agreement":null},{"id":"W4312675399","doi":"10.23977/acss.2022.060503","title":"The Spectral Properties of the Main Operator of a Kind of Pumping Well Production System with Early Warning Function","year":2022,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Engineering Diagnostics and Reliability","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":"Operator (biology); Eigenvalues and eigenvectors; Production (economics); Function (biology); Spectral function; Warning system; Point (geometry); Mathematics; Spectral power distribution; Computer science; Physics; Chemistry; Quantum mechanics; Economics; Telecommunications","score_opus":0.004789040903450808,"score_gpt":0.16140197465164152,"score_spread":0.1566129337481907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312675399","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27805924,0.00037191046,0.71002024,0.00043631185,0.00009871058,0.00005895402,0.000093325216,0.00016211407,0.010699116],"genre_scores_gemma":[0.9688131,0.00021507773,0.026363248,0.000066540844,0.000069351736,0.000052369407,0.000059116373,0.00004006959,0.004321148],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964046,0.00012781838,0.0000130440285,0.00006956553,0.00009496346,0.000054229175],"domain_scores_gemma":[0.9983841,0.0009165177,0.00018013809,0.000091291884,0.00033264933,0.00009519562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094938214,0.0007308505,0.0004958395,0.0007907761,0.0006220929,0.00083622895,0.00057582225,0.0008956962,0.0018478964],"category_scores_gemma":[0.002226872,0.0003341776,0.00060316187,0.00042044933,0.0017640046,0.0018903248,0.00079479103,0.001039415,0.00017662771],"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":[0.00042160248,0.00016646268,0.0032383471,0.00034611876,0.000118719225,0.0011037461,0.00083817996,0.14096914,0.11098625,0.72376025,0.001716252,0.016334925],"study_design_scores_gemma":[0.000027606844,0.00013424235,0.0016385759,0.000014560751,0.000021299882,0.00040523728,0.00012132055,0.8515171,0.005382687,0.14005479,0.0006057094,0.000076904886],"about_ca_topic_score_codex":0.00060429337,"about_ca_topic_score_gemma":0.00033238778,"teacher_disagreement_score":0.0018478964,"about_ca_system_score_codex":0.0004070654,"about_ca_system_score_gemma":0.0005185397,"threshold_uncertainty_score":0.006181836},"labels":[],"label_agreement":null},{"id":"W4313505949","doi":"10.1007/978-3-031-17425-4_94","title":"Imaging the Remaining Refractory Lining in Operating Furnaces","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Hatch (Canada)","funders":"","keywords":"Refractory (planetary science); Medicine; Forensic engineering; Geology; Materials science; Metallurgy; Engineering","score_opus":0.012739091622785807,"score_gpt":0.2130483232394401,"score_spread":0.2003092316166543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313505949","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":[0.1269527,0.06549137,0.29060504,0.006628687,0.0024604166,0.0002144198,0.0009920015,0.0043052644,0.5023501],"genre_scores_gemma":[0.3273222,0.027445085,0.19163577,0.002406833,0.00066143135,0.0000790391,0.0006545789,0.0017207242,0.44807437],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99990225,0.000011147178,0.0000027510407,0.000011797122,0.000061561186,0.000010513371],"domain_scores_gemma":[0.99985945,0.00008055753,0.0000106148445,0.000015312411,0.000022145256,0.00001191486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028684808,0.00036967595,0.000276488,0.0004977377,0.0003550566,0.0012307602,0.0006109401,0.0011429344,0.010565483],"category_scores_gemma":[0.0004826077,0.00033500374,0.00019440842,0.00023507238,0.00044448755,0.0010852519,0.00044568192,0.0011036457,0.0022779135],"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":[0.0003589048,0.00009289031,0.0018107431,0.0011438516,0.000023068309,0.0043527517,0.0009073432,0.005563669,0.46095002,0.026548196,0.061035555,0.437213],"study_design_scores_gemma":[0.00003219943,0.00037417546,0.00863978,0.00097302836,0.000068445785,0.036887262,0.0015288816,0.01677406,0.2701449,0.024210397,0.6402762,0.000090617315],"about_ca_topic_score_codex":0.0006960857,"about_ca_topic_score_gemma":0.002118908,"teacher_disagreement_score":0.010565483,"about_ca_system_score_codex":0.0002753623,"about_ca_system_score_gemma":0.00032891775,"threshold_uncertainty_score":0.035345078},"labels":[],"label_agreement":null},{"id":"W4320003664","doi":"10.18280/jesa.550614","title":"Real Time Assessment of Novel Predictive Maintenance System based on Artificial Intelligence for Rotating Machines","year":2022,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Engineering Diagnostics and Reliability","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":"Centre National pour la Recherche Scientifique et Technique","keywords":"Downtime; Predictive maintenance; Reliability (semiconductor); Process (computing); Artificial neural network; Reliability engineering; Computer science; Acceleration; Test bench; Engineering; Real-time computing; Artificial intelligence; Embedded system; Power (physics)","score_opus":0.014636740180574303,"score_gpt":0.25633808309111067,"score_spread":0.24170134291053635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320003664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8108858,0.00048193833,0.18133692,0.00017409214,0.00014488336,0.00014522007,0.00018039453,0.0026729116,0.003977831],"genre_scores_gemma":[0.99335194,0.000043150485,0.0060640723,0.000011049732,0.0000059843505,0.000020581087,0.000045263776,0.0000085350775,0.00044931646],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998104,0.000031069947,0.000010880646,0.000046270252,0.000083347164,0.000018094031],"domain_scores_gemma":[0.9997012,0.00008742386,0.00004591593,0.00003819211,0.000107300344,0.000019959498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034833598,0.0004787404,0.00040299798,0.00048014754,0.00018753439,0.000448861,0.0005604436,0.00048076786,0.00102162],"category_scores_gemma":[0.0007161198,0.00013541267,0.00020925287,0.00020807267,0.00016246183,0.00044394808,0.00021948935,0.00027083166,0.00017886415],"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":[0.0020656448,0.00087124656,0.036234174,0.0006011922,0.00027342976,0.00096920034,0.0003212855,0.2715224,0.25156212,0.0017628573,0.00375539,0.43006107],"study_design_scores_gemma":[0.00002674873,0.0007656086,0.015147281,0.000010930314,0.000049065657,0.00014688265,0.000028098164,0.96044475,0.022382854,0.00033801264,0.000641606,0.00001815237],"about_ca_topic_score_codex":0.0011960628,"about_ca_topic_score_gemma":0.0012272754,"teacher_disagreement_score":0.0011960628,"about_ca_system_score_codex":0.00033495395,"about_ca_system_score_gemma":0.00021503305,"threshold_uncertainty_score":0.0034176707},"labels":[],"label_agreement":null},{"id":"W4322708493","doi":"10.2139/ssrn.4373221","title":"A Convolutional Block Attention Module Based Lightweight Convolutional Neural Network Model for Rotating Machinery Fault Diagnosis","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Engineering Diagnostics and Reliability","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":"Hyperparameter; Convolutional neural network; Computer science; Artificial intelligence; Block (permutation group theory); Fault (geology); Pattern recognition (psychology); Fuse (electrical); Artificial neural network; Deep learning; Feature extraction; Feature (linguistics); Machine learning; Data mining; Engineering; Mathematics","score_opus":0.008163865465602048,"score_gpt":0.2157558644654996,"score_spread":0.20759199899989755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322708493","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05620745,0.0013517556,0.9308915,0.0003509154,0.00030985827,0.00007412036,0.0008426018,0.0053672316,0.00460462],"genre_scores_gemma":[0.83954704,0.0006825894,0.13830303,0.0003248764,0.00013370627,0.00009193837,0.002033871,0.00017629346,0.018706571],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988735,0.000009628736,0.000004987563,0.000032538883,0.00003558892,0.000029882374],"domain_scores_gemma":[0.9998567,0.000030863357,0.000012829212,0.000021038713,0.000066293964,0.00001228066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002242476,0.0006292981,0.00054214464,0.00042564128,0.000247401,0.00032128734,0.0010953315,0.0006443672,0.003342202],"category_scores_gemma":[0.00039398886,0.00028074151,0.0005266535,0.0003830808,0.00012580425,0.0005256552,0.00057680276,0.0007467613,0.0012494338],"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":[0.00043101484,0.00020663532,0.0018366672,0.00014762265,0.0001509831,0.00020004796,0.00003538908,0.30225414,0.053099655,0.003508481,0.013718183,0.6244112],"study_design_scores_gemma":[0.000003321379,0.000029329423,0.00040680513,0.0000038609255,0.000020760459,0.0000182366,0.0000019116287,0.99393207,0.0044431738,0.00043227084,0.00070357625,0.0000046223777],"about_ca_topic_score_codex":0.022110805,"about_ca_topic_score_gemma":0.029870488,"teacher_disagreement_score":0.022110805,"about_ca_system_score_codex":0.00058622315,"about_ca_system_score_gemma":0.0009455492,"threshold_uncertainty_score":0.043964267},"labels":[],"label_agreement":null},{"id":"W4323340165","doi":"10.5220/0010249500002859","title":"Determining the Required Size of a Military Training Pipeline","year":2021,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Department of National Defence","funders":"","keywords":"Pipeline (software); Training (meteorology); Computer science; Operating system","score_opus":0.01334458332178965,"score_gpt":0.21051505699410916,"score_spread":0.19717047367231952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323340165","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5117737,0.00043131103,0.45701542,0.0012799539,0.0002763219,0.00054513203,0.0021255226,0.0031547912,0.023397852],"genre_scores_gemma":[0.93547124,0.000101626385,0.060824104,0.00006148745,0.0000189631,0.000107945336,0.0005621933,0.00018128338,0.0026711826],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908817,0.00015651908,0.000047366717,0.00017763443,0.00034540944,0.00018492067],"domain_scores_gemma":[0.995379,0.0022768644,0.00040832115,0.00031737622,0.0012655786,0.0003528399],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013043594,0.0006863003,0.00064999925,0.0012434698,0.0010380524,0.0009984671,0.0010027689,0.0011140062,0.010770384],"category_scores_gemma":[0.010132358,0.0006525534,0.0005753724,0.00034591858,0.00045491374,0.0024844313,0.0010522903,0.00074416684,0.0025385453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024836422,0.00048852066,0.04443187,0.0010833851,0.000077129145,0.0009987028,0.00055267283,0.3486258,0.34834403,0.011516445,0.010385575,0.23101217],"study_design_scores_gemma":[0.00014880527,0.0024159641,0.050569426,0.00019280997,0.00013986882,0.0008163586,0.0012167008,0.74727017,0.1721801,0.010031328,0.01488073,0.00013775288],"about_ca_topic_score_codex":0.0033403614,"about_ca_topic_score_gemma":0.0045232843,"teacher_disagreement_score":0.010770384,"about_ca_system_score_codex":0.0009007513,"about_ca_system_score_gemma":0.0023273528,"threshold_uncertainty_score":0.03603053},"labels":[],"label_agreement":null},{"id":"W4387773786","doi":"10.3384/ecp200029","title":"A Deep Learning Approach for Fault Diagnosis of Hydrogen Fueled Micro Gas Turbines","year":2023,"lang":"en","type":"article","venue":"Linköping electronic conference proceedings","topic":"Engineering Diagnostics and Reliability","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 Manitoba","funders":"Research Executive Agency; European Commission; Universitetet i Stavanger","keywords":"Fault (geology); Flue gas; Context (archaeology); Artificial neural network; Fault detection and isolation; Engineering; Computer science; Environmental science; Artificial intelligence; Waste management","score_opus":0.009729156214212725,"score_gpt":0.2135426804833651,"score_spread":0.2038135242691524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387773786","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10342724,0.000761914,0.8919286,0.00025998428,0.00005259142,0.000046164205,0.00010572909,0.0007831366,0.0026346052],"genre_scores_gemma":[0.9307511,0.0002173003,0.066004135,0.00007813081,0.000025200725,0.00006047404,0.00015859203,0.000021008358,0.002684131],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999032,0.000016423824,0.000007723907,0.000023504983,0.000026423886,0.000022658996],"domain_scores_gemma":[0.9998084,0.00008932289,0.0000212615,0.000010888721,0.000061005358,0.0000091771135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024292043,0.00041426579,0.00039180025,0.00036737532,0.00019817344,0.00040266657,0.00054684305,0.00065083016,0.0010128586],"category_scores_gemma":[0.000596733,0.00022216098,0.0003495957,0.00024387818,0.00018985332,0.0003137938,0.00039351144,0.000642275,0.00016148697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007733172,0.000064362095,0.0009540887,0.00006358684,0.00003256761,0.000101632126,0.000037192312,0.8494178,0.005765113,0.0015215994,0.000591878,0.1413728],"study_design_scores_gemma":[8.4188383e-7,0.000009952873,0.000101457656,0.0000018205392,0.0000015333811,0.000004270394,0.0000024892033,0.99906534,0.00042747034,0.0003124052,0.000071506336,9.224258e-7],"about_ca_topic_score_codex":0.008283933,"about_ca_topic_score_gemma":0.0060996977,"teacher_disagreement_score":0.008283933,"about_ca_system_score_codex":0.00047610406,"about_ca_system_score_gemma":0.0005491703,"threshold_uncertainty_score":0.016471446},"labels":[],"label_agreement":null},{"id":"W4388566292","doi":"10.18280/ijsse.130511","title":"Assessing Occupational Risk: A Classification of Harmful Factors in the Production Environment and Labor Process","year":2023,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Engineering Diagnostics and Reliability","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":"Production (economics); Hazardous waste; Process (computing); Work (physics); Industrial production; Microclimate; Business; Identification (biology); Risk analysis (engineering); Occupational safety and health; Environmental science; Environmental resource management; Environmental economics; Engineering; Computer science; Waste management; Geography","score_opus":0.011597928124976205,"score_gpt":0.2538532662810767,"score_spread":0.24225533815610048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388566292","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":[0.5208768,0.016455417,0.40686858,0.0032318616,0.000490186,0.0023041335,0.0020816291,0.0008339399,0.046857465],"genre_scores_gemma":[0.8591932,0.0038622394,0.13296175,0.00023497018,0.00014866833,0.000463482,0.0011626894,0.00003243672,0.0019405553],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99614537,0.00085409376,0.00057523284,0.000347189,0.0017988925,0.00027916115],"domain_scores_gemma":[0.9952938,0.0011647958,0.0013894365,0.00034347386,0.001567878,0.00024043338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030714,0.0014624164,0.0009739358,0.008517003,0.0019214564,0.003804491,0.0012410725,0.0011435864,0.0011212257],"category_scores_gemma":[0.005893264,0.00024137383,0.0010860686,0.003104811,0.0018346241,0.0024018006,0.0030367232,0.000947922,0.00030796084],"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":[0.00026794235,0.00043318933,0.5169621,0.0016538501,0.00039936227,0.0011623201,0.0074219485,0.016062582,0.016060017,0.036104288,0.0032731434,0.40019926],"study_design_scores_gemma":[0.000038076545,0.0014399652,0.7719917,0.001927527,0.0008870426,0.0052508567,0.022096436,0.039550327,0.008540952,0.088664174,0.059248313,0.0003646291],"about_ca_topic_score_codex":0.0065173693,"about_ca_topic_score_gemma":0.006139809,"teacher_disagreement_score":0.008517003,"about_ca_system_score_codex":0.0017395795,"about_ca_system_score_gemma":0.0040106797,"threshold_uncertainty_score":0.016243279},"labels":[],"label_agreement":null},{"id":"W4389140207","doi":"10.1115/pvp2023-105480","title":"Proposal for the Design of a Dynamically Loaded Pressure Vessel With the Ratio of the Pulse Period to the Vessel Natural Vibration Period More Than 0.35","year":2023,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"General Fusion (Canada)","funders":"","keywords":"Pressure vessel; Vibration; Impulse (physics); Materials science; Period (music); Pulse (music); Stress (linguistics); Natural frequency; Structural engineering; Mechanics; Engineering; Physics; Acoustics; Electrical engineering; Composite material; Voltage","score_opus":0.005827933856849619,"score_gpt":0.20552047966431242,"score_spread":0.1996925458074628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389140207","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":[0.053829525,0.0004932411,0.9296613,0.0008590947,0.00028743924,0.00045944555,0.00022807292,0.0034220451,0.010759916],"genre_scores_gemma":[0.54939646,0.0003706546,0.4393386,0.00023755853,0.00018176659,0.00066166534,0.00033367984,0.00023771536,0.009241959],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992337,0.000111418456,0.00005571276,0.00020039416,0.000315877,0.00008284332],"domain_scores_gemma":[0.99929667,0.000058239217,0.00015670097,0.00007461607,0.00030108792,0.000112793554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009007028,0.0007748078,0.0007003586,0.00089365087,0.0006965655,0.0013801733,0.0029720073,0.0013709218,0.0031608606],"category_scores_gemma":[0.0008760389,0.0005067108,0.0005698153,0.0002946221,0.0006200815,0.0010627953,0.00086323434,0.0006385046,0.0018715461],"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":[0.0004897895,0.00046818494,0.003105871,0.0007075471,0.00009986615,0.0010563728,0.00045032887,0.027550234,0.7709086,0.021532506,0.007012116,0.16661845],"study_design_scores_gemma":[0.00044637444,0.00800052,0.009240577,0.00017091328,0.00043485485,0.002794318,0.00036669994,0.47067547,0.32594046,0.0047785407,0.17674902,0.00040233572],"about_ca_topic_score_codex":0.00064664596,"about_ca_topic_score_gemma":0.00059458107,"teacher_disagreement_score":0.0031608606,"about_ca_system_score_codex":0.00061693485,"about_ca_system_score_gemma":0.0010913148,"threshold_uncertainty_score":0.010574162},"labels":[],"label_agreement":null},{"id":"W4389353613","doi":"10.1130/abs/2023am-388522","title":"SEQUESTRATION OF METAL(LOID)S BY MINERAL-ORGANIC MATTER ASSOCIATIONS","year":2023,"lang":"en","type":"article","venue":"Abstracts with programs - Geological Society of America","topic":"Engineering Diagnostics and Reliability","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 Manitoba","funders":"","keywords":"Mineral; Environmental chemistry; Environmental science; Organic matter; Metal; Earth science; Geology; Chemistry; Metallurgy; Materials science","score_opus":0.010727252187736269,"score_gpt":0.2217802008107624,"score_spread":0.21105294862302615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389353613","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9962012,0.00027811996,0.00090931146,0.00008226324,0.000015451558,0.000010889802,0.00021639296,0.000052467378,0.0022339162],"genre_scores_gemma":[0.99603146,0.00016528966,0.00049431727,0.000020713322,0.0000070146248,0.0000061003775,0.00016936632,0.00000997158,0.0030956573],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999843,0.000013230229,0.000008356911,0.00005908357,0.000028265431,0.000048104193],"domain_scores_gemma":[0.99983644,0.00004073834,0.000034810444,0.000014121393,0.000047798127,0.000026072586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023868596,0.00021108684,0.00024909948,0.00041475237,0.0005640486,0.000899605,0.00031876782,0.0003681117,0.0039125895],"category_scores_gemma":[0.00038428474,0.0001742967,0.00023154994,0.00027139203,0.00031397335,0.00039164038,0.0004498104,0.00020939058,0.0009138867],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011456066,0.000034858567,0.032756444,0.0001464547,0.000057287434,0.0002472565,0.00012499666,0.00090309686,0.9519454,0.00082974695,0.0003640527,0.011444666],"study_design_scores_gemma":[0.00009257254,0.00055496243,0.12739909,0.000023901424,0.00010675355,0.0002742198,0.0007864033,0.007931246,0.8531511,0.0007659737,0.008889342,0.000024477753],"about_ca_topic_score_codex":0.00964251,"about_ca_topic_score_gemma":0.013725637,"teacher_disagreement_score":0.00964251,"about_ca_system_score_codex":0.00082497206,"about_ca_system_score_gemma":0.0006396991,"threshold_uncertainty_score":0.019172788},"labels":[],"label_agreement":null},{"id":"W4390910970","doi":"10.31224/3481","title":"Dynamic Mode Decomposition of Deformation Fields in Elastic and Elastic-Plastic Solids","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Decomposition; Deformation (meteorology); Materials science; Dynamic mode decomposition; Mode (computer interface); Composite material; Mechanics; Physics; Computer science; Chemistry","score_opus":0.0033022246072247786,"score_gpt":0.23800883591063013,"score_spread":0.23470661130340534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390910970","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1219408,0.00065928604,0.85942936,0.00033610297,0.00017766192,0.000038939408,0.000372446,0.00028509813,0.016760435],"genre_scores_gemma":[0.8519918,0.0011288525,0.10184551,0.00014211544,0.00016859961,0.000086083186,0.00066650775,0.0004723382,0.043498226],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999056,0.000021191861,0.0000036357555,0.000019969957,0.000032968725,0.000016501404],"domain_scores_gemma":[0.99980944,0.00006958871,0.000021574357,0.000028198978,0.00004773443,0.000023422652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002471902,0.00052921637,0.000270811,0.00081073254,0.00016851773,0.00081152254,0.00041962953,0.00047991256,0.004688324],"category_scores_gemma":[0.000797553,0.00025167872,0.0003942134,0.00033675,0.00035427877,0.0009158485,0.00048516388,0.0008032259,0.0007118152],"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":[0.00023143855,0.00019274274,0.002144387,0.00027418637,0.000066341025,0.0002693302,0.00032960437,0.31683955,0.06745339,0.44666448,0.007423001,0.15811156],"study_design_scores_gemma":[0.000005176876,0.000018416775,0.0010683598,0.0000134529055,0.000005837123,0.000068984285,0.00004803192,0.9092772,0.002658662,0.084676385,0.002147581,0.0000119293145],"about_ca_topic_score_codex":0.001046961,"about_ca_topic_score_gemma":0.00094729493,"teacher_disagreement_score":0.004688324,"about_ca_system_score_codex":0.00023927858,"about_ca_system_score_gemma":0.00026912687,"threshold_uncertainty_score":0.015684009},"labels":[],"label_agreement":null},{"id":"W4391127822","doi":"10.61091/jcmcc117-07","title":"Equipment Asset Management and Equipment Health Based on Fuzzy Algorithm Evaluation Model","year":2023,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Engineering Diagnostics and Reliability","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":"Fuzzy logic; Asset management; Algorithm; Mathematics; Computer science; Business; Artificial intelligence; Finance","score_opus":0.01855171572832239,"score_gpt":0.2717161077479521,"score_spread":0.2531643920196297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391127822","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033506017,0.00037553182,0.95885324,0.00023567444,0.000023365816,0.000055933295,0.000049935432,0.00008130613,0.0068189627],"genre_scores_gemma":[0.8734455,0.0005262724,0.12206055,0.00005897336,0.00004092464,0.00015759199,0.00009280502,0.000023225297,0.003594225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987214,0.0004907184,0.000059867376,0.00020101838,0.00041450598,0.00011236358],"domain_scores_gemma":[0.99866784,0.0007344465,0.00014701417,0.00007491754,0.0003242485,0.00005145203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020477448,0.00067087554,0.0006553102,0.001596796,0.0004702606,0.0019620126,0.0009825844,0.0008878671,0.0016939935],"category_scores_gemma":[0.0037892358,0.00019409838,0.0007261446,0.0012594477,0.0006654781,0.0019482574,0.0007142162,0.00059655897,0.00019340467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031219497,0.000041824533,0.0014125585,0.000042417712,0.000036870406,0.000053887175,0.00006997895,0.9129781,0.00083985913,0.05376624,0.00048016984,0.03024698],"study_design_scores_gemma":[0.0000024314713,0.000018640296,0.0001784362,0.000005176648,0.0000066861103,0.000011899506,0.0000066312828,0.9922724,0.00015318948,0.0070826565,0.00025761253,0.0000041592552],"about_ca_topic_score_codex":0.0048959,"about_ca_topic_score_gemma":0.002802939,"teacher_disagreement_score":0.0048959,"about_ca_system_score_codex":0.0018333687,"about_ca_system_score_gemma":0.0011468749,"threshold_uncertainty_score":0.013302028},"labels":[],"label_agreement":null},{"id":"W4391306850","doi":"10.1109/smc53992.2023.10394070","title":"Effect of Machine Reliability on the Cognitive Processes of the Task Performance","year":2023,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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","funders":"","keywords":"Reliability (semiconductor); Computer science; Task (project management); Cognition; Reliability engineering; Psychology; Engineering; Systems engineering; Neuroscience","score_opus":0.003380089462340961,"score_gpt":0.1975010134119333,"score_spread":0.19412092394959232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391306850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9844205,0.00033904717,0.012877135,0.000085528154,0.000039395385,0.00004559436,0.00007888283,0.00008941154,0.0020245393],"genre_scores_gemma":[0.9966995,0.000093274735,0.0027044036,0.000037845377,0.000020938087,0.000029317162,0.000064075066,0.00003320603,0.00031734514],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998381,0.0005236003,0.0001331326,0.00030173254,0.0005430399,0.00011738384],"domain_scores_gemma":[0.9757161,0.017950047,0.0028932772,0.0015105368,0.0013256549,0.0006043703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019622461,0.0006848034,0.00035096135,0.00042531232,0.0001594305,0.00065884687,0.0002609526,0.0004378298,0.0016699289],"category_scores_gemma":[0.023434034,0.0002521937,0.00030441675,0.00022922875,0.0004423574,0.00062259415,0.00068756606,0.0005589984,0.0002575979],"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":[0.012102509,0.0017490824,0.21075833,0.0010687824,0.00088789186,0.0006244068,0.003399694,0.033197295,0.4900561,0.001831478,0.0009320383,0.24339238],"study_design_scores_gemma":[0.000085097556,0.004448975,0.92415106,0.000050683593,0.0002570807,0.00029505725,0.00025079446,0.029659506,0.03747126,0.0024006213,0.0008471622,0.00008272879],"about_ca_topic_score_codex":0.0005858358,"about_ca_topic_score_gemma":0.00046516652,"teacher_disagreement_score":0.0019622461,"about_ca_system_score_codex":0.00017610924,"about_ca_system_score_gemma":0.0002753395,"threshold_uncertainty_score":0.010377467},"labels":[],"label_agreement":null},{"id":"W4391930220","doi":"10.1109/amcai59331.2023.10431528","title":"Gas Turbine Fault Diagnosis Based on Machine Learning Techniques","year":2023,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Computer science; Fault (geology); Gas turbines; Machine learning; Artificial intelligence; Reliability engineering; Engineering; Mechanical engineering; Geology","score_opus":0.006839405129372344,"score_gpt":0.21322413321612085,"score_spread":0.20638472808674851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391930220","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09318614,0.0035303214,0.89648044,0.00032282862,0.00016032858,0.00007467164,0.00013539352,0.0022841408,0.0038257102],"genre_scores_gemma":[0.8488559,0.0010588676,0.148463,0.00007315277,0.00008590092,0.000041884337,0.00016837344,0.000028102548,0.0012247397],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993325,0.00012895522,0.000054260414,0.00012184377,0.00031086223,0.00005165772],"domain_scores_gemma":[0.99913675,0.00041292145,0.00014528744,0.000047049187,0.00024258062,0.000015325732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072894007,0.00058263144,0.00072878797,0.0021736347,0.00028356578,0.0005996456,0.0005055727,0.0008096849,0.00060730474],"category_scores_gemma":[0.002246715,0.00014220481,0.0005251507,0.00082187366,0.00024766888,0.00081334723,0.00023193285,0.00043367324,0.0005140106],"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":[0.0002640223,0.00017042852,0.011746052,0.00038590955,0.0001271752,0.0003954775,0.00010795906,0.13829866,0.03617383,0.0026714534,0.0019814686,0.80767757],"study_design_scores_gemma":[0.000015448517,0.0001657954,0.0065043573,0.00006400717,0.000046678608,0.0003965431,0.000042896143,0.9714632,0.017029272,0.0023142456,0.0019299713,0.000027544058],"about_ca_topic_score_codex":0.0016760828,"about_ca_topic_score_gemma":0.001354897,"teacher_disagreement_score":0.0021736347,"about_ca_system_score_codex":0.00031946023,"about_ca_system_score_gemma":0.00031652531,"threshold_uncertainty_score":0.0038550496},"labels":[],"label_agreement":null},{"id":"W4392389624","doi":"10.1109/isgt59692.2024.10454170","title":"Stochastic Approach for Evaluating the Operation of Electric Power Distribution Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Computer science; Stochastic process; Power (physics); Distribution (mathematics); Mathematics; Physics; Statistics","score_opus":0.012768460568033586,"score_gpt":0.2553064380998819,"score_spread":0.24253797753184833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392389624","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020165376,0.0001882796,0.9765044,0.000087553555,0.000021467076,0.000079595586,0.00016679121,0.00010540669,0.0026811606],"genre_scores_gemma":[0.81683236,0.00053846696,0.18005396,0.000072764975,0.0000875653,0.00040280327,0.00049475575,0.00005050107,0.0014668674],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976987,0.0012126813,0.00009864888,0.00019058606,0.0006943269,0.00010510377],"domain_scores_gemma":[0.99601835,0.0029298412,0.00038577634,0.00017257576,0.00040296558,0.00009044888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002833533,0.0008942556,0.0006838213,0.0017204357,0.00039263553,0.001120412,0.00083531236,0.0006407077,0.0011264586],"category_scores_gemma":[0.009456582,0.0004129435,0.0006445914,0.0012229257,0.00062062696,0.0008029045,0.0007833652,0.00082626316,0.00013536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010342392,0.000012026665,0.0011492458,0.00002021386,0.00003328824,0.000026496957,0.000013976584,0.9787991,0.00043906693,0.01494373,0.00012387014,0.004428502],"study_design_scores_gemma":[0.0000020364514,0.000018435014,0.0003179529,0.000005046894,0.0000037582524,0.0000106476555,0.000008035486,0.9941367,0.00013289397,0.005081341,0.0002775028,0.000005607871],"about_ca_topic_score_codex":0.007853083,"about_ca_topic_score_gemma":0.005842367,"teacher_disagreement_score":0.007853083,"about_ca_system_score_codex":0.001515678,"about_ca_system_score_gemma":0.0012990433,"threshold_uncertainty_score":0.015614748},"labels":[],"label_agreement":null},{"id":"W4393053396","doi":"10.23977/jemm.2024.090105","title":"Identification of time-frequency maps of bearing faults based on hyperparameter optimization SSA-GoogleNet","year":2024,"lang":"en","type":"article","venue":"Journal of Engineering Mechanics and Machinery","topic":"Engineering Diagnostics and Reliability","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":"Hyperparameter; Identification (biology); Bearing (navigation); Computer science; Pattern recognition (psychology); Artificial intelligence; Biology","score_opus":0.003639432750727801,"score_gpt":0.1876567358341779,"score_spread":0.1840173030834501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393053396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51811355,0.0018565552,0.45831615,0.0004942626,0.00032534357,0.00021635836,0.002141999,0.01184568,0.0066900873],"genre_scores_gemma":[0.9532546,0.00029373448,0.040695723,0.00007011831,0.000043528606,0.000103936654,0.0026281257,0.00016523874,0.00274498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973637,0.000028387676,0.000017815382,0.00009534056,0.00006845878,0.000053670152],"domain_scores_gemma":[0.9997961,0.000041236784,0.000028171668,0.000023090082,0.00009747123,0.00001395916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034153412,0.0016036875,0.0009727148,0.002310563,0.00033308024,0.0006920413,0.00095902936,0.0010697243,0.0014597902],"category_scores_gemma":[0.0013348853,0.00036142446,0.00091069844,0.0013945032,0.0003162086,0.0011683176,0.0005136215,0.0005107567,0.0006169904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003236571,0.00016336156,0.008872099,0.00018409584,0.00014588117,0.00031074634,0.00009779579,0.7488267,0.00841834,0.0013877351,0.00859269,0.22267693],"study_design_scores_gemma":[0.0000055199703,0.000013336772,0.001240283,0.0000039628253,0.0000071624313,0.000019299508,0.00001540303,0.9966503,0.0013255537,0.00042656675,0.00028785225,0.0000048436173],"about_ca_topic_score_codex":0.02158439,"about_ca_topic_score_gemma":0.013892015,"teacher_disagreement_score":0.02158439,"about_ca_system_score_codex":0.0006589652,"about_ca_system_score_gemma":0.00070585747,"threshold_uncertainty_score":0.04291749},"labels":[],"label_agreement":null},{"id":"W4394624992","doi":"10.1109/reepe60449.2024.10479711","title":"Analysis of Regulatory Requirements for Providing Personal Protective Equipment to Electric Power Industry Employees in Russia, the USA and Canada","year":2024,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":5,"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":"Electric power industry; Business; Personal protective equipment; Electric power; Power (physics); Telecommunications; Engineering; Electrical engineering; Electricity; Medicine","score_opus":0.009826430695535472,"score_gpt":0.23425391383674907,"score_spread":0.2244274831412136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394624992","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98813885,0.00065560633,0.00065124856,0.0004659093,0.000015612603,0.00004297921,0.0015439343,0.000023164193,0.008462701],"genre_scores_gemma":[0.99670535,0.0004234028,0.0004079412,0.00011249903,0.000008615532,0.000027937229,0.0011854077,0.0000068726627,0.0011219298],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9940467,0.00083501043,0.0005019188,0.00042361554,0.003473634,0.0007191707],"domain_scores_gemma":[0.97270423,0.008704407,0.0055896705,0.000918873,0.010732468,0.0013503577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036878022,0.000095061085,0.00017870581,0.0023297255,0.0011718454,0.001009459,0.0010512372,0.0003894776,0.0008058843],"category_scores_gemma":[0.018301537,0.00019098863,0.0002632338,0.002342177,0.0005139092,0.00020057952,0.00040741387,0.00042439884,0.00013945485],"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":[0.00015649587,0.00007930809,0.96324986,0.00014506749,0.00005891406,0.00019036309,0.0026435263,0.0018426226,0.0022979141,0.003702415,0.002067731,0.023565637],"study_design_scores_gemma":[0.0000023704595,0.00003053224,0.99424523,0.000035526846,0.0000124180815,0.00006295215,0.0008371101,0.00040310938,0.00029576596,0.000043700184,0.0040230844,0.000008272864],"about_ca_topic_score_codex":0.56564134,"about_ca_topic_score_gemma":0.61935043,"teacher_disagreement_score":0.43435866,"about_ca_system_score_codex":0.006561004,"about_ca_system_score_gemma":0.015413569,"threshold_uncertainty_score":0.87383336},"labels":[],"label_agreement":null},{"id":"W4395666702","doi":"10.18280/mmep.110414","title":"Comparative Analysis of SVM and ANN for Machine Condition Monitoring and Fault Diagnosis in Gearboxes","year":2024,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Engineering Diagnostics and Reliability","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":"","keywords":"Support vector machine; Fault (geology); Computer science; Machine learning; Artificial intelligence; Engineering; Seismology; Geology","score_opus":0.02170628069246851,"score_gpt":0.25502492735978616,"score_spread":0.23331864666731764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395666702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6727636,0.0061848448,0.30882937,0.00056668004,0.00025183425,0.00011027874,0.00025630923,0.0017234746,0.0093136],"genre_scores_gemma":[0.97407156,0.0007661577,0.02392902,0.00003219608,0.00003158332,0.000028024377,0.00013972103,0.00003071735,0.0009709837],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992901,0.000263705,0.00005457936,0.00008731202,0.0002544498,0.00004978857],"domain_scores_gemma":[0.99716586,0.002052746,0.00012921917,0.00011926329,0.00048999523,0.000042940435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017501543,0.0005882285,0.0007258049,0.00089079817,0.00018096165,0.00067903963,0.00033252785,0.0005588444,0.00083853735],"category_scores_gemma":[0.004765621,0.00017808375,0.0003599541,0.00049864926,0.00017691679,0.0008880241,0.00029402273,0.00036177295,0.00018979647],"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":[0.0018047679,0.000321083,0.020162834,0.00056897604,0.00030463113,0.00022922554,0.000156853,0.42186755,0.016086645,0.0028273321,0.0013334373,0.53433675],"study_design_scores_gemma":[0.000006862335,0.00015733582,0.0040573957,0.00001608277,0.000032390453,0.000035042412,0.00003533167,0.9918355,0.0029499766,0.0005178683,0.00034724773,0.00000898127],"about_ca_topic_score_codex":0.0028216387,"about_ca_topic_score_gemma":0.0031074216,"teacher_disagreement_score":0.0028216387,"about_ca_system_score_codex":0.00046002516,"about_ca_system_score_gemma":0.00032652915,"threshold_uncertainty_score":0.0092558265},"labels":[],"label_agreement":null},{"id":"W4398213154","doi":"10.23977/jeis.2024.090207","title":"Fault diagnosis method for lightweight gearboxes based on depth-separable cascaded residual block and feature-weighted module","year":2024,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Engineering Diagnostics and Reliability","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":"Residual; Separable space; Feature (linguistics); Block (permutation group theory); Fault (geology); Computer science; Artificial intelligence; Pattern recognition (psychology); Algorithm; Mathematics; Geology; Geometry; Seismology","score_opus":0.0053889462653688176,"score_gpt":0.249780912437344,"score_spread":0.24439196617197517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398213154","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":[0.02991431,0.00023448559,0.9682113,0.00005313795,0.00002849042,0.000041376574,0.000048595324,0.00091610407,0.00055218354],"genre_scores_gemma":[0.74621063,0.00032110725,0.24905677,0.00007879539,0.00004273116,0.000089649504,0.00026861017,0.000077226265,0.0038546338],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997961,0.000016516224,0.000015555484,0.00006144533,0.000081387785,0.000028937211],"domain_scores_gemma":[0.9997534,0.000058680893,0.000041720767,0.000040008304,0.000091742164,0.00001436843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033400208,0.0008692117,0.00063603144,0.00079288124,0.00023603183,0.00035045532,0.0008975403,0.0006030874,0.0017008778],"category_scores_gemma":[0.0007896037,0.00026728294,0.0007255431,0.00033342274,0.00022510128,0.00093590724,0.0005426016,0.0005197391,0.0004070924],"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":[0.00034501872,0.000116580544,0.0037582899,0.0002389476,0.00011064236,0.00031772399,0.00014548797,0.20443824,0.09453357,0.0031893665,0.0018986512,0.6909074],"study_design_scores_gemma":[0.000008694664,0.00008751461,0.0012291279,0.000007706035,0.000028508513,0.00013729997,0.000014440552,0.978567,0.01839827,0.0008907769,0.00061991054,0.000010888165],"about_ca_topic_score_codex":0.0037752108,"about_ca_topic_score_gemma":0.0042285305,"teacher_disagreement_score":0.0037752108,"about_ca_system_score_codex":0.00035176342,"about_ca_system_score_gemma":0.0005540972,"threshold_uncertainty_score":0.0075064898},"labels":[],"label_agreement":null},{"id":"W4399049308","doi":"10.62110/sciencein.jist.2024.v12.823","title":"Improving the methodology for calculating the thrust force during underwater crossing by directional drilling method","year":2024,"lang":"en","type":"article","venue":"Journal of Integrated Science and Technology","topic":"Engineering Diagnostics and Reliability","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":"Thrust; Underwater; Drilling; Marine engineering; Directional drilling; Computer science; Geology; Aerospace engineering; Mechanical engineering; Engineering; Oceanography","score_opus":0.012873218066838455,"score_gpt":0.27964246982254615,"score_spread":0.2667692517557077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399049308","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":[0.008411091,0.00010256841,0.9899136,0.000020258882,0.000024283916,0.000048290556,0.000031587435,0.00044116165,0.001007009],"genre_scores_gemma":[0.16337009,0.00024391612,0.8351158,0.000019687455,0.000012054387,0.000114479604,0.000084905994,0.00010791647,0.000931137],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982589,0.00027969741,0.00014355197,0.00024970667,0.0009977119,0.00007053565],"domain_scores_gemma":[0.9978405,0.00060715195,0.0002768841,0.00023620333,0.001009074,0.000030073243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013709428,0.0005990749,0.00043665184,0.0018083128,0.00039111264,0.000586255,0.0011126534,0.00049436005,0.001947328],"category_scores_gemma":[0.004441874,0.0003493843,0.00051895203,0.00091394165,0.0003513599,0.00095042435,0.00062344206,0.0005616519,0.0006925589],"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":[0.00013614542,0.00006866516,0.010420812,0.0008579213,0.00005613327,0.00020270271,0.0006298471,0.065282345,0.12899524,0.011034256,0.001648698,0.7806672],"study_design_scores_gemma":[0.000067697736,0.0005665109,0.014352942,0.00021494056,0.000111652276,0.0011422121,0.00047880728,0.7613198,0.18111911,0.003759528,0.036685977,0.00018076658],"about_ca_topic_score_codex":0.0032876548,"about_ca_topic_score_gemma":0.0046983184,"teacher_disagreement_score":0.0032876548,"about_ca_system_score_codex":0.00035962742,"about_ca_system_score_gemma":0.0012689172,"threshold_uncertainty_score":0.007250309},"labels":[],"label_agreement":null},{"id":"W4399984597","doi":"10.18280/ijsse.140305","title":"An Expert Approach to Assessing Technogenic Risk at Enrichment Plants","year":2024,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Engineering Diagnostics and Reliability","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":"Environmental science; Risk assessment; Risk analysis (engineering); Environmental health; Computer science; Engineering; Medicine; Computer security","score_opus":0.004668635907899303,"score_gpt":0.23439654871570292,"score_spread":0.2297279128078036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399984597","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1596156,0.0005983231,0.80831623,0.0010550193,0.00008426779,0.0012558661,0.00018032402,0.00017209329,0.028722351],"genre_scores_gemma":[0.53246874,0.00047908013,0.46160674,0.0002532175,0.00006943356,0.0007750432,0.00013818852,0.000023438686,0.0041861483],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9785936,0.013671122,0.0011186386,0.0014121381,0.004770614,0.0004339735],"domain_scores_gemma":[0.97945213,0.011950611,0.001517007,0.0009678412,0.005724194,0.00038819195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015185482,0.0009209978,0.0007236352,0.005321087,0.0014254542,0.002511332,0.0017167624,0.0012018301,0.0027453743],"category_scores_gemma":[0.027195971,0.00041754084,0.0005887313,0.0018015337,0.0014496697,0.001516142,0.002095182,0.00094589975,0.00040189727],"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":[0.0007224801,0.0012416384,0.05647292,0.0026321006,0.00070373906,0.0021357918,0.04370146,0.06554778,0.03220291,0.10935268,0.0035622886,0.6817242],"study_design_scores_gemma":[0.00035651782,0.0026518486,0.08076272,0.0022006717,0.0010197131,0.0042901095,0.06741867,0.41691938,0.03315908,0.31899118,0.07140656,0.0008236071],"about_ca_topic_score_codex":0.0029451083,"about_ca_topic_score_gemma":0.0057247314,"teacher_disagreement_score":0.015185482,"about_ca_system_score_codex":0.0016000363,"about_ca_system_score_gemma":0.0032819533,"threshold_uncertainty_score":0.08030945},"labels":[],"label_agreement":null},{"id":"W4400478987","doi":"","title":"Separation of vibratory components in complex systems for condition monitoring","year":2024,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Engineering Diagnostics and Reliability","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":"European Commission","keywords":"Separation (statistics); Computer science; Environmental science; Machine learning","score_opus":0.018439826766126956,"score_gpt":0.24434994465187135,"score_spread":0.2259101178857444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400478987","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30867544,0.009600259,0.66899675,0.0010332193,0.00051840337,0.00018413865,0.00028488252,0.00068821694,0.010018646],"genre_scores_gemma":[0.88612175,0.003967349,0.09160188,0.0003430654,0.00037061045,0.00008619577,0.0003546789,0.0001299404,0.017024588],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999739,0.00003310481,0.000013151216,0.00007597087,0.000106893494,0.000031939344],"domain_scores_gemma":[0.9993593,0.00034062192,0.00008406968,0.000044317625,0.0001282198,0.000043406268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039481794,0.00047897978,0.0006798964,0.00080015714,0.0003575135,0.0010320167,0.0004546495,0.00087036577,0.008016619],"category_scores_gemma":[0.0010240552,0.00015861579,0.00026769814,0.0006153994,0.0005241962,0.0007000099,0.00053545355,0.0006313911,0.001449377],"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":[0.00033386692,0.000074611635,0.0010315021,0.0003099174,0.000019159988,0.00007275964,0.00008213623,0.003837017,0.84679383,0.0016093253,0.0008613674,0.14497454],"study_design_scores_gemma":[0.000076037824,0.0012267693,0.018193062,0.0001483929,0.00010227568,0.0007285746,0.00028535037,0.14256564,0.80658597,0.0072104745,0.02279699,0.00008039931],"about_ca_topic_score_codex":0.0004049512,"about_ca_topic_score_gemma":0.0007559018,"teacher_disagreement_score":0.008016619,"about_ca_system_score_codex":0.0002754424,"about_ca_system_score_gemma":0.00028302157,"threshold_uncertainty_score":0.026818275},"labels":[],"label_agreement":null},{"id":"W4400621311","doi":"10.5220/0012813000003758","title":"Reliability Analysis of Francis Turbine Cracking Using Gamma Frailty Model and Censored Historical Maintenance Data","year":2024,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Hydro-Québec; Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Reliability (semiconductor); Cracking; Reliability engineering; Computer science; Turbine; Data modeling; Engineering; Forensic engineering; Materials science; Mechanical engineering; Database; Physics; Thermodynamics","score_opus":0.0295785465463402,"score_gpt":0.2595562867518596,"score_spread":0.2299777402055194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400621311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.875213,0.00064535165,0.12271153,0.000102725186,0.000030911244,0.000023369732,0.00024134494,0.00019452903,0.00083719334],"genre_scores_gemma":[0.9966307,0.00010318367,0.0027016005,0.0000054350257,0.000007708347,0.0000067428286,0.00017585544,0.000013383244,0.00035540666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9995419,0.00015662631,0.000027701952,0.00009495147,0.00010329497,0.000075606025],"domain_scores_gemma":[0.99478036,0.0035130556,0.00044856753,0.0004431953,0.00073101814,0.00008377184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025924277,0.000560227,0.00060953386,0.0015500822,0.00027285065,0.0005235678,0.00092071533,0.0007374454,0.0007798089],"category_scores_gemma":[0.008283118,0.0003464197,0.0010224753,0.0007875031,0.00049458013,0.0007834301,0.00036221885,0.00064993754,0.00012115275],"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":[0.00028011182,0.000048830498,0.02167908,0.0001116778,0.00016908448,0.00034455626,0.00011312275,0.9465626,0.004419292,0.0049670003,0.000607719,0.02069691],"study_design_scores_gemma":[0.0000040683444,0.000043802193,0.007522506,0.00000691825,0.000029215165,0.000043958662,0.000017351094,0.99101514,0.0005437346,0.00069544185,0.000064242326,0.000013616122],"about_ca_topic_score_codex":0.014379936,"about_ca_topic_score_gemma":0.009881894,"teacher_disagreement_score":0.014379936,"about_ca_system_score_codex":0.00065655366,"about_ca_system_score_gemma":0.0004618939,"threshold_uncertainty_score":0.028592467},"labels":[],"label_agreement":null},{"id":"W4400652920","doi":"10.11159/jffhmt.2024.017","title":"Improving the Accuracy of Detecting Signs of Combustion Instability by Using Anomaly Detection","year":2024,"lang":"en","type":"article","venue":"Journal of Fluid Flow Heat and Mass Transfer","topic":"Engineering Diagnostics and Reliability","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":"Instability; Anomaly (physics); Anomaly detection; Combustion; Computer science; Artificial intelligence; Physics; Chemistry; Mechanics","score_opus":0.008042282012071484,"score_gpt":0.2063218275137958,"score_spread":0.1982795455017243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400652920","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2712488,0.000624779,0.72280544,0.00016226743,0.0001249179,0.00005592399,0.00015314577,0.0031789774,0.0016457995],"genre_scores_gemma":[0.7904967,0.0002411551,0.2079935,0.00006149217,0.000032934262,0.000024815079,0.00021855261,0.00011456117,0.0008162507],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993616,0.00009346208,0.000046189754,0.00019450174,0.00022964616,0.00007451624],"domain_scores_gemma":[0.99798584,0.0009381473,0.00023882055,0.00023027942,0.00055833516,0.000048587586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013909043,0.00093763747,0.0006712577,0.0015199488,0.000293877,0.00077243254,0.0008121429,0.00089511235,0.00065600855],"category_scores_gemma":[0.004609126,0.00029535586,0.00040774856,0.0005704348,0.00035415974,0.0011539365,0.00071233197,0.000784093,0.00038703624],"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":[0.00081416895,0.00028697323,0.037600167,0.00033942654,0.00017834401,0.00032822086,0.00025535116,0.0504817,0.32633454,0.0012444822,0.0012589013,0.58087766],"study_design_scores_gemma":[0.0000105204,0.0001182162,0.01780102,0.000022215745,0.00005311096,0.00024663433,0.000047097525,0.8683546,0.11148106,0.0007351403,0.0010937883,0.000036556627],"about_ca_topic_score_codex":0.0020559651,"about_ca_topic_score_gemma":0.0024513109,"teacher_disagreement_score":0.0020559651,"about_ca_system_score_codex":0.00033665771,"about_ca_system_score_gemma":0.00043626537,"threshold_uncertainty_score":0.007355869},"labels":[],"label_agreement":null},{"id":"W4401568085","doi":"10.1109/itc-egypt61547.2024.10620512","title":"Analytical and Simulation Methods for Assessing Breakdown Power in Guiding Structures","year":2024,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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; Apollo Microwaves (Canada)","funders":"","keywords":"Computer science; Power (physics); Reliability engineering; Engineering; Physics","score_opus":0.02285967853368133,"score_gpt":0.37402024229778763,"score_spread":0.3511605637641063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401568085","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006930148,0.00030508474,0.98536277,0.000082924984,0.000029214003,0.00010972834,0.000111102374,0.0005171806,0.0065519065],"genre_scores_gemma":[0.27613297,0.0018197773,0.71362776,0.00012648971,0.000063976,0.0011575446,0.00035904106,0.00039832306,0.006314195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915385,0.00018578877,0.000042545827,0.000059822858,0.00050650706,0.0000515605],"domain_scores_gemma":[0.9988263,0.0005610732,0.0001556798,0.0001545147,0.00027708098,0.000025389028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013331776,0.0008619201,0.0004956247,0.001499767,0.000508756,0.0008291352,0.00093511754,0.00095417746,0.0025678058],"category_scores_gemma":[0.0038821655,0.0004918339,0.00058251905,0.0010045881,0.00061086356,0.0008932179,0.0007185713,0.0009095091,0.0006829987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051450595,0.0001408304,0.0009966919,0.0003403982,0.000051736224,0.00013132795,0.0002485165,0.79283243,0.032968257,0.099947356,0.0016838746,0.07060705],"study_design_scores_gemma":[0.000010961586,0.00004276436,0.00020028607,0.000032186257,0.000008750797,0.00007414168,0.0000310193,0.9764815,0.0070625325,0.010701639,0.0053347233,0.000019501764],"about_ca_topic_score_codex":0.0023961768,"about_ca_topic_score_gemma":0.0016313493,"teacher_disagreement_score":0.0025678058,"about_ca_system_score_codex":0.00078396266,"about_ca_system_score_gemma":0.0009670716,"threshold_uncertainty_score":0.008590162},"labels":[],"label_agreement":null},{"id":"W4402043823","doi":"10.2139/ssrn.4941746","title":"Intelligent Rotor Imbalance Fault Classification Through Comprehensive Feature Fusion","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Engineering Diagnostics and Reliability","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":"Fault (geology); Fusion; Rotor (electric); Feature (linguistics); Artificial intelligence; Computer science; Pattern recognition (psychology); Engineering; Geology; Seismology; Electrical engineering","score_opus":0.0116729522803184,"score_gpt":0.25086134360329876,"score_spread":0.23918839132298036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402043823","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09662802,0.00066322787,0.8985797,0.00021943732,0.00010687955,0.00004447078,0.00028871105,0.0013955032,0.0020740533],"genre_scores_gemma":[0.8962904,0.0002677212,0.10031324,0.00007208326,0.00009046821,0.000033458815,0.00085026294,0.000072568844,0.0020097098],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965143,0.000037682337,0.00002260728,0.00009040885,0.0001306796,0.00006711814],"domain_scores_gemma":[0.99963224,0.00010024463,0.000056758854,0.00006876545,0.000119103985,0.000022945842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054539257,0.0008042817,0.0010213164,0.0012673349,0.0003242772,0.0008625499,0.00038761945,0.0006187697,0.001201129],"category_scores_gemma":[0.0012258616,0.00026381697,0.00063853327,0.0009381312,0.0002576996,0.0012351949,0.0009011612,0.0006504197,0.00075707864],"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":[0.0004975759,0.00018884681,0.004778364,0.00009260906,0.00012743403,0.00014367502,0.00007316554,0.076112926,0.071447216,0.0018668984,0.0041841636,0.8404871],"study_design_scores_gemma":[0.000013314491,0.00012148971,0.005954899,0.000011767985,0.000054451415,0.000112792935,0.000027508007,0.97770965,0.012005801,0.002858031,0.00111205,0.000018224422],"about_ca_topic_score_codex":0.0011379756,"about_ca_topic_score_gemma":0.0014048913,"teacher_disagreement_score":0.0012673349,"about_ca_system_score_codex":0.00019375038,"about_ca_system_score_gemma":0.00037650866,"threshold_uncertainty_score":0.004018128},"labels":[],"label_agreement":null},{"id":"W4402681860","doi":"10.51731/cjht.2024.982","title":"Optimal Team for Diagnostic Imaging Equipment Installation","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Health Technologies","topic":"Engineering Diagnostics and Reliability","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":"Computer science; Engineering","score_opus":0.009412333758549628,"score_gpt":0.23984359221717866,"score_spread":0.23043125845862902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402681860","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29151103,0.012450451,0.3277896,0.12292211,0.0076050027,0.008433184,0.0015188935,0.0038524682,0.22391726],"genre_scores_gemma":[0.6193808,0.0065210904,0.32357222,0.0080941245,0.0014473475,0.0033077437,0.0015649922,0.00051400077,0.035597682],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99188083,0.0031610453,0.00065275823,0.0007445922,0.0019791955,0.0015814266],"domain_scores_gemma":[0.9854252,0.0014189192,0.0014313865,0.00047350588,0.004195564,0.007055493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007116063,0.0006968188,0.0005042057,0.002793294,0.006067213,0.0042824214,0.002114227,0.0017427333,0.035268173],"category_scores_gemma":[0.019096868,0.0006750128,0.0008172301,0.0010434492,0.0009851997,0.0032108098,0.005339603,0.002733342,0.0074197706],"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":[0.0005371125,0.001931478,0.07870109,0.0015300894,0.00011989548,0.00739093,0.012939905,0.0056837304,0.006041714,0.016041895,0.21707106,0.65201104],"study_design_scores_gemma":[0.00047772902,0.0026755794,0.21668366,0.007727576,0.00025420776,0.023235176,0.12681551,0.021489182,0.006416184,0.059404537,0.5341734,0.00064730184],"about_ca_topic_score_codex":0.015792357,"about_ca_topic_score_gemma":0.03692392,"teacher_disagreement_score":0.035268173,"about_ca_system_score_codex":0.0064313775,"about_ca_system_score_gemma":0.022528702,"threshold_uncertainty_score":0.11798376},"labels":[],"label_agreement":null},{"id":"W4402936757","doi":"10.1115/1.4066674","title":"Measurement of Steam-Generator-Tube Vibration Damping Caused by Anti-Vibration-Bar Supports","year":2024,"lang":"en","type":"article","venue":"Journal of Pressure Vessel Technology","topic":"Engineering Diagnostics and Reliability","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":true,"ca_institutions":"Canadian Nuclear Laboratories; Intertek (Canada); Deep River Science Academy","funders":"","keywords":"Vibration; Bar (unit); Generator (circuit theory); Boiler (water heating); Tube (container); Structural engineering; Materials science; Acoustics; Engineering; Mechanical engineering; Physics; Power (physics); Thermodynamics; Waste management","score_opus":0.006255515169029223,"score_gpt":0.2092809057104129,"score_spread":0.2030253905413837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402936757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993999,0.00009331025,0.005529082,0.000009517382,0.000010137076,0.000013842967,0.00003733857,0.000078964986,0.0002288096],"genre_scores_gemma":[0.99596846,0.000030139883,0.0036838497,0.000007529662,0.0000025687864,0.000010855883,0.000040287217,0.000008318908,0.00024793774],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994746,0.000047078338,0.000020341837,0.00007944314,0.00033484443,0.000043774373],"domain_scores_gemma":[0.99909353,0.00027061478,0.00017180796,0.00007333696,0.00031249266,0.00007818652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038374696,0.00041419646,0.00028188407,0.00054295064,0.00018727778,0.00020957255,0.0006049451,0.00041033243,0.00095722964],"category_scores_gemma":[0.0010006645,0.00022853914,0.00016685599,0.00022674138,0.0002976274,0.0003242299,0.0003878701,0.00030193708,0.0002569704],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023279832,0.000038043745,0.0042829337,0.000043647124,0.000008201028,0.00007365569,0.000073196534,0.00051009655,0.98790425,0.000035413967,0.00003352687,0.0067642233],"study_design_scores_gemma":[0.000023165543,0.0013067828,0.035165105,0.00001201196,0.000022886794,0.0001522107,0.0001078893,0.010338716,0.95216805,0.00003038926,0.0006576841,0.000015053821],"about_ca_topic_score_codex":0.000498362,"about_ca_topic_score_gemma":0.0010811688,"teacher_disagreement_score":0.00095722964,"about_ca_system_score_codex":0.00023489875,"about_ca_system_score_gemma":0.00015372707,"threshold_uncertainty_score":0.0032022},"labels":[],"label_agreement":null},{"id":"W4403420693","doi":"10.1109/sdpc62810.2024.10707711","title":"Intelligent Faults Diagnosis of Variable Operating Condition Bearing Based on Order Analysis and Deep Residual Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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 Key Research and Development Program of China","keywords":"Residual; Bearing (navigation); Variable (mathematics); Computer science; Reliability engineering; Artificial intelligence; Engineering; Algorithm; Mathematics","score_opus":0.004796218950544321,"score_gpt":0.21703525269710808,"score_spread":0.21223903374656375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403420693","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2490149,0.00082348037,0.7444221,0.00029183234,0.00011999549,0.00005926627,0.0002723234,0.002510525,0.002485543],"genre_scores_gemma":[0.9528463,0.00022541791,0.04401792,0.000049291542,0.000024675415,0.000021373251,0.00037047078,0.000044083175,0.0024004995],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980503,0.000025106185,0.000012955938,0.0000546266,0.00006295355,0.000039382743],"domain_scores_gemma":[0.9997136,0.000086431224,0.000054343265,0.000031510313,0.000094625415,0.000019523837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029101444,0.00066584896,0.00043606872,0.0007807375,0.00018977677,0.0003840934,0.0005272821,0.00041634822,0.0007610516],"category_scores_gemma":[0.00091374177,0.00020763943,0.00050068606,0.00032089307,0.00022191158,0.00060237426,0.0003315257,0.0005653619,0.0002369145],"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":[0.00055677607,0.00024183773,0.011034599,0.00017133806,0.00010717524,0.0004087236,0.0001850286,0.45442343,0.052015726,0.00259372,0.0034878312,0.47477388],"study_design_scores_gemma":[0.0000043376454,0.00003638251,0.0012301076,0.0000031418488,0.000010045433,0.000033806704,0.000009710404,0.99373686,0.00412034,0.00057229237,0.00023748328,0.00000544883],"about_ca_topic_score_codex":0.010063753,"about_ca_topic_score_gemma":0.009406634,"teacher_disagreement_score":0.010063753,"about_ca_system_score_codex":0.00046859487,"about_ca_system_score_gemma":0.000433965,"threshold_uncertainty_score":0.020010352},"labels":[],"label_agreement":null},{"id":"W4403522210","doi":"10.55274/r0000095","title":"PR676-233801-R02 Pipeline Reliability Thresholds","year":2024,"lang":"en","type":"report","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Stantec (Canada)","funders":"","keywords":"Reliability (semiconductor); Pipeline (software); Computer science; Reliability engineering; Environmental science; Engineering; Physics; Operating system","score_opus":0.013846316858835372,"score_gpt":0.252459009697422,"score_spread":0.23861269283858666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403522210","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":[0.023772594,0.00039521063,0.046168964,0.0009513479,0.00023943986,0.001585471,0.010272574,0.006002002,0.9106124],"genre_scores_gemma":[0.3898286,0.0006845524,0.08630551,0.00068742246,0.00012440259,0.0017553794,0.018553654,0.0024060055,0.49965453],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99493057,0.0006594511,0.00019219256,0.0003995309,0.0033563133,0.00046202817],"domain_scores_gemma":[0.99371016,0.001020895,0.00034105807,0.0005062372,0.0041637355,0.00025795752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002747984,0.0007591246,0.00068352546,0.002311656,0.0009273735,0.00255305,0.0017528465,0.001717836,0.1236486],"category_scores_gemma":[0.007709267,0.00036049055,0.00036786683,0.00091339403,0.00049310015,0.0013082668,0.001207095,0.00084980257,0.06653878],"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":[0.00088790356,0.00072851777,0.011454636,0.00089524395,0.000040907922,0.00066088815,0.00028637986,0.021206642,0.0682439,0.06822584,0.3799007,0.4474684],"study_design_scores_gemma":[0.00018345736,0.0013184791,0.024234444,0.00041184048,0.000034720666,0.0010473706,0.000487449,0.03085959,0.07095666,0.011527034,0.8588313,0.0001076547],"about_ca_topic_score_codex":0.0137674585,"about_ca_topic_score_gemma":0.015141781,"teacher_disagreement_score":0.1236486,"about_ca_system_score_codex":0.0028218317,"about_ca_system_score_gemma":0.003394205,"threshold_uncertainty_score":0.41364574},"labels":[],"label_agreement":null},{"id":"W4404014929","doi":"10.23977/jeeem.2024.070303","title":"Optimization of Preventive Maintenance Strategies for Electrical Equipment on Offshore Oil Support Vessels Based on Predictive Maintenance Algorithms in an Intelligent Platform","year":2024,"lang":"en","type":"article","venue":"Journal of Electrotechnology Electrical Engineering and Management","topic":"Engineering Diagnostics and Reliability","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":"Preventive maintenance; Predictive maintenance; Submarine pipeline; Computer science; Proactive maintenance; Reliability engineering; Algorithm; Engineering; Marine engineering; Geotechnical engineering","score_opus":0.0059444076776927835,"score_gpt":0.22460051316970184,"score_spread":0.21865610549200906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404014929","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26280302,0.0004003645,0.7332761,0.00017691436,0.000045383353,0.00004789864,0.00004193561,0.00076719874,0.0024410167],"genre_scores_gemma":[0.9810006,0.000077649565,0.018289128,0.000026099942,0.0000072302464,0.00003065784,0.000030585914,0.000009508031,0.0005285165],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998692,0.000017251385,0.000009032318,0.000039248713,0.000039035305,0.000026212161],"domain_scores_gemma":[0.9998078,0.00006763689,0.000044521148,0.000015935511,0.00005317174,0.000010912354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029894695,0.0006286414,0.0004936064,0.0003292594,0.00023991069,0.0004946235,0.0006024405,0.00054011896,0.0004707196],"category_scores_gemma":[0.000761279,0.00025045717,0.00032615956,0.0002038627,0.00023144664,0.0005553235,0.00034989428,0.0004384433,0.000104763734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009395883,0.000094357696,0.0021686712,0.000057129793,0.00003400673,0.00010335728,0.000050287068,0.895531,0.01146409,0.00068917894,0.0003982206,0.089315705],"study_design_scores_gemma":[0.0000044437493,0.000041894946,0.0004611834,0.0000026059208,0.000009927489,0.000010666437,0.000007059383,0.9978811,0.0012879384,0.00020223236,0.00008804521,0.0000028459883],"about_ca_topic_score_codex":0.005105701,"about_ca_topic_score_gemma":0.0044445717,"teacher_disagreement_score":0.005105701,"about_ca_system_score_codex":0.00030897695,"about_ca_system_score_gemma":0.0006281919,"threshold_uncertainty_score":0.010151982},"labels":[],"label_agreement":null},{"id":"W4404851523","doi":"10.1142/s0218625x24400031","title":"COMPARISON OF THE PERFORMANCE OF INDIRECT EVALUATION OF FLANK WEAR FOR TURNING INCONEL-718 USING THE PROCESSED IMAGE AND ACOUSTIC WAVES","year":2024,"lang":"en","type":"article","venue":"Surface Review and Letters","topic":"Engineering Diagnostics and Reliability","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":"Inconel; Flank; Materials science; Metallurgy; Acoustics; Computer science; Physics","score_opus":0.02233676899463603,"score_gpt":0.29951135319875116,"score_spread":0.2771745842041151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404851523","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9860729,0.0007612719,0.011803203,0.00002090244,0.000039165097,0.000028004719,0.00008522134,0.000121531586,0.0010678269],"genre_scores_gemma":[0.9850568,0.00040497162,0.012596676,0.00002013977,0.000020109022,0.000030096557,0.0001537744,0.000039082526,0.0016784278],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99873585,0.000104430495,0.00007259799,0.00016283346,0.0008343806,0.00008995031],"domain_scores_gemma":[0.99701834,0.0010046985,0.00033923174,0.00026947798,0.001295808,0.00007239156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077781576,0.0004901715,0.0004652399,0.0007150648,0.00013941788,0.00052155,0.0004375971,0.0004038496,0.0011226166],"category_scores_gemma":[0.0026736825,0.00022189465,0.00040402808,0.00031787407,0.00029920615,0.00037403623,0.00035265507,0.00033946938,0.00023409184],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009522567,0.000112101225,0.009552994,0.0005645086,0.00006472447,0.00014615236,0.00044832117,0.0013291097,0.9106721,0.00006587716,0.00017166829,0.07592012],"study_design_scores_gemma":[0.000033309265,0.005214057,0.12702252,0.000046646193,0.00022142447,0.00065768405,0.0006509496,0.01352733,0.850668,0.00008764481,0.0017614855,0.00010899358],"about_ca_topic_score_codex":0.000556338,"about_ca_topic_score_gemma":0.0014761096,"teacher_disagreement_score":0.0011226166,"about_ca_system_score_codex":0.00014033205,"about_ca_system_score_gemma":0.00016493518,"threshold_uncertainty_score":0.0041134953},"labels":[],"label_agreement":null},{"id":"W4405362264","doi":"10.1115/ipc2024-133750","title":"Interpretation of the Safety Risk Tolerance Criteria for Integrated Asset Management of Pipelines","year":2024,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Pipeline transport; Interpretation (philosophy); Asset management; Risk management; Asset (computer security); Risk analysis (engineering); Computer science; Reliability engineering; Business; Computer security; Engineering; Finance; Programming language","score_opus":0.005090911013931957,"score_gpt":0.2395840408280984,"score_spread":0.23449312981416642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405362264","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04090624,0.0045565236,0.8261177,0.003050991,0.0005767879,0.000931165,0.0029119286,0.0012189518,0.11972985],"genre_scores_gemma":[0.6865143,0.0018002443,0.29958177,0.0006701326,0.0002547389,0.0007929483,0.0024620716,0.0003512325,0.0075724805],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9766001,0.0068632127,0.0028357136,0.0013576791,0.011388102,0.00095517276],"domain_scores_gemma":[0.96591026,0.010964863,0.0049474477,0.0017655866,0.015769793,0.0006421074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020114437,0.0016977984,0.0010040351,0.010781628,0.0011150377,0.0068797627,0.0034981687,0.0018822451,0.008422896],"category_scores_gemma":[0.053165536,0.00053345866,0.002104976,0.0043790736,0.0031968378,0.004157414,0.0041002114,0.0026046417,0.0014266709],"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":[0.00024083935,0.00016766206,0.014737148,0.0031393063,0.00034709254,0.00084996177,0.0029790702,0.19413956,0.0053848517,0.54032534,0.028106967,0.2095822],"study_design_scores_gemma":[0.000077606936,0.00053436204,0.017961025,0.0051734755,0.000347312,0.00080987805,0.0043961015,0.2481556,0.010642119,0.5351768,0.17631944,0.00040631028],"about_ca_topic_score_codex":0.011053343,"about_ca_topic_score_gemma":0.005415222,"teacher_disagreement_score":0.020114437,"about_ca_system_score_codex":0.0046536787,"about_ca_system_score_gemma":0.006056368,"threshold_uncertainty_score":0.10637659},"labels":[],"label_agreement":null},{"id":"W4405518994","doi":"10.2316/j.2025.201-0495","title":"THE APPLICATION OF DIGITAL TWIN MODEL IN FAULT PREDICTION OF TRACTION MOTOR OF MULTIPLE UNIT, 62-70.","year":2024,"lang":"en","type":"article","venue":"Mechatronic systems and control","topic":"Engineering Diagnostics and Reliability","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":"Traction (geology); Unit (ring theory); Computer science; Fault (geology); Motor unit; Automotive engineering; Engineering; Geology; Seismology; Mechanical engineering; Psychology; Neuroscience","score_opus":0.004929479345345313,"score_gpt":0.18801020255367604,"score_spread":0.18308072320833071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405518994","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7891731,0.0006400325,0.20223643,0.00037929084,0.00017636451,0.00007171604,0.0026191317,0.0017982814,0.0029056706],"genre_scores_gemma":[0.989293,0.00006831189,0.008504128,0.000017453664,0.000006230124,0.000015453654,0.0011511935,0.000021192574,0.0009230038],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990857,0.000015426205,0.0000074651757,0.000031747957,0.000024034674,0.000012689067],"domain_scores_gemma":[0.99971217,0.00012318006,0.000033860466,0.00004494437,0.00006453357,0.000021304146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039482527,0.00048730103,0.00034759723,0.0005721233,0.00021826224,0.00047651795,0.0005902028,0.00053823716,0.0011132122],"category_scores_gemma":[0.001753726,0.00023483313,0.00037121764,0.00038979627,0.00017265881,0.0005981794,0.00026106162,0.00052750955,0.00022637221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016226324,0.000074061885,0.008891306,0.00005166346,0.00005009419,0.00007132352,0.00001949103,0.9613992,0.0019013475,0.00079984247,0.0010746749,0.025504675],"study_design_scores_gemma":[0.0000018061448,0.00001397306,0.0007131699,9.498527e-7,0.000002450089,0.0000073659326,0.0000027002432,0.9985379,0.00043043873,0.0001558028,0.00013213258,0.0000013675296],"about_ca_topic_score_codex":0.0206093,"about_ca_topic_score_gemma":0.017813748,"teacher_disagreement_score":0.0206093,"about_ca_system_score_codex":0.00058963435,"about_ca_system_score_gemma":0.0005734294,"threshold_uncertainty_score":0.04097867},"labels":[],"label_agreement":null},{"id":"W4405857487","doi":"10.1007/978-3-031-77219-1_21","title":"Transformer and Reactor Mechanical Condition Assessment","year":2024,"lang":"en","type":"book-chapter","venue":"CIGRE green books","topic":"Engineering Diagnostics and Reliability","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":"Hydro-Québec","funders":"","keywords":"Transformer; Reliability engineering; Nuclear engineering; Materials science; Computer science; Engineering; Electrical engineering; Voltage","score_opus":0.008514190356636848,"score_gpt":0.21667695670909107,"score_spread":0.20816276635245423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405857487","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":[0.0054224385,0.013115401,0.14017735,0.001231388,0.0016316149,0.00014878488,0.0011325342,0.0039284714,0.83321196],"genre_scores_gemma":[0.05023887,0.008689927,0.02425605,0.0003945838,0.00036341854,0.00004144261,0.0012553559,0.00056163664,0.91419864],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961144,0.0000276446,0.000011554854,0.00004933149,0.00028093727,0.000019082008],"domain_scores_gemma":[0.9997204,0.00005334669,0.0000149624975,0.000042262203,0.00015723486,0.0000117986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035489822,0.00087644596,0.00058631116,0.0017467579,0.00050193944,0.0020247367,0.0008478202,0.000851562,0.040540885],"category_scores_gemma":[0.0006429027,0.00040567646,0.0003436276,0.0012798766,0.0004549441,0.0014315615,0.0005487318,0.001051418,0.020091305],"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":[0.00006600024,0.0000508287,0.00065400155,0.00022413144,0.000012680614,0.00013650679,0.00014067488,0.0053309496,0.010082726,0.028662259,0.16091758,0.7937217],"study_design_scores_gemma":[0.000007674539,0.00010758811,0.004049789,0.00017989324,0.000036526722,0.0007204491,0.00023810806,0.01366478,0.013865369,0.028959109,0.93813014,0.00004049611],"about_ca_topic_score_codex":0.004781274,"about_ca_topic_score_gemma":0.011721207,"teacher_disagreement_score":0.040540885,"about_ca_system_score_codex":0.00076604524,"about_ca_system_score_gemma":0.0008831902,"threshold_uncertainty_score":0.13562274},"labels":[],"label_agreement":null},{"id":"W4406391834","doi":"10.17073/0368-0797-2024-6-731-734","title":"Improving operation of a drawing mill","year":2024,"lang":"en","type":"article","venue":"Izvestiya Ferrous Metallurgy","topic":"Engineering Diagnostics and Reliability","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":"EVRAZ (Canada)","funders":"","keywords":"Mill; Engineering drawing; Engineering; Mechanical engineering","score_opus":0.00540274513360306,"score_gpt":0.19814727187659506,"score_spread":0.192744526742992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406391834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72168815,0.0011847991,0.25950766,0.00022888917,0.00012824357,0.000104175204,0.00012223545,0.0034739533,0.0135618765],"genre_scores_gemma":[0.9433617,0.00019630951,0.053512115,0.000028357877,0.000031755622,0.00002283662,0.00012073546,0.00022839422,0.0024978302],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991731,0.00013643719,0.00006160359,0.0001372251,0.0004027673,0.00008888574],"domain_scores_gemma":[0.9988366,0.0002852729,0.00012187009,0.00031113974,0.00039118968,0.000053968244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010541279,0.0005542487,0.0005387859,0.0005718065,0.00067468383,0.0010699007,0.001187811,0.0007793791,0.0035325377],"category_scores_gemma":[0.002178809,0.00021905784,0.00025516597,0.00046482586,0.0002558588,0.00091144315,0.0005835807,0.0004429108,0.0012003828],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00076603837,0.00024926555,0.008955666,0.00041566056,0.00003039263,0.000572705,0.0007322172,0.0365855,0.58618045,0.0037372028,0.0017090704,0.3600659],"study_design_scores_gemma":[0.0001714965,0.005816993,0.055612028,0.00013168041,0.0003267406,0.003035759,0.0010867957,0.2518176,0.60948926,0.00441298,0.06786411,0.00023457498],"about_ca_topic_score_codex":0.0005049348,"about_ca_topic_score_gemma":0.0004482639,"teacher_disagreement_score":0.0035325377,"about_ca_system_score_codex":0.00026169783,"about_ca_system_score_gemma":0.0003877344,"threshold_uncertainty_score":0.011817515},"labels":[],"label_agreement":null},{"id":"W4407074290","doi":"10.54093/bmra.v4i1.8197","title":"Leadership Style as a Predictor of Employee Safety Performance in the Oil and Gas Industry","year":2025,"lang":"en","type":"article","venue":"Business Management Research and Applications A Cross-Disciplinary Journal","topic":"Engineering Diagnostics and Reliability","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":"Style (visual arts); Petroleum industry; Leadership style; Gas industry; Business; Management; Psychology; Engineering; Economics; Natural gas; Art; Visual arts; Waste management","score_opus":0.03753145411629748,"score_gpt":0.33092205906544303,"score_spread":0.29339060494914554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407074290","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995309,0.000012130159,0.00004556271,0.000034778805,0.0000019833521,0.0000017323969,0.000011589712,0.0000013724189,0.0003598554],"genre_scores_gemma":[0.9997203,0.000010970142,0.000033530912,0.000009423957,0.000001257857,0.0000014024463,0.000020524067,5.54696e-7,0.00020184195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99937016,0.0001879736,0.00003572094,0.000049615803,0.00018824736,0.00016834681],"domain_scores_gemma":[0.99638295,0.0009659893,0.0008191899,0.00015034158,0.0007260244,0.00095552043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013233022,0.00016290284,0.000108334614,0.00042943886,0.00045671128,0.00064379786,0.00019707523,0.00020846885,0.0011387315],"category_scores_gemma":[0.0030849692,0.000077538396,0.00018717334,0.0003094129,0.00038392848,0.00016449855,0.00038637585,0.0005512725,0.0002044954],"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":[0.000028505852,0.00006383361,0.99622643,0.000002990901,0.0000129923155,0.000024752006,0.00036366354,0.000119909324,0.00024052216,0.000023194905,0.000080782105,0.0028124638],"study_design_scores_gemma":[0.0000015243716,0.000052681025,0.99867177,0.0000032045411,0.0000027409005,0.000010737161,0.00078610284,0.000308588,0.00006593443,0.000014334514,0.000080602855,0.0000018031493],"about_ca_topic_score_codex":0.05324747,"about_ca_topic_score_gemma":0.12347676,"teacher_disagreement_score":0.05324747,"about_ca_system_score_codex":0.0008474624,"about_ca_system_score_gemma":0.0018118488,"threshold_uncertainty_score":0.105875075},"labels":[],"label_agreement":null},{"id":"W4407074762","doi":"10.24251/hicss.2024.371","title":"Reliability Model of Joint Electricity and Natural Gas System Considering Electric Compressor Failures under Different Network Topologies","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences","topic":"Engineering Diagnostics and Reliability","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":"Gas compressor; Network topology; Reliability (semiconductor); Electricity; Reliability engineering; Natural gas; Joint (building); Computer science; Topology (electrical circuits); Engineering; Electrical engineering; Mechanical engineering; Structural engineering; Physics; Power (physics); Waste management; Computer network","score_opus":0.028707419707200088,"score_gpt":0.25593192903650924,"score_spread":0.22722450932930915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407074762","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27327093,0.0011017163,0.6882049,0.0020326695,0.00015056593,0.00018843067,0.0017597612,0.00084051455,0.032450568],"genre_scores_gemma":[0.9799192,0.00039050347,0.0075708264,0.00007021148,0.00004551626,0.00016538949,0.00035380165,0.0000704221,0.011414063],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918157,0.00026632237,0.00003937459,0.00018167426,0.00015347754,0.0001774944],"domain_scores_gemma":[0.99820614,0.0008026744,0.0003698824,0.00007971532,0.0004284267,0.000113281036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001700163,0.0012032635,0.0013385441,0.0010568217,0.00056635216,0.001725295,0.0022288784,0.0019068597,0.0034436383],"category_scores_gemma":[0.0032292828,0.00066807517,0.0010559426,0.0009113016,0.001398864,0.0018782672,0.001005605,0.0012894424,0.0005079096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025659087,0.000008322877,0.0002951742,0.000014674486,0.000011582057,0.000121827776,0.000036484496,0.9903019,0.00029714563,0.007985045,0.0002498633,0.00065226975],"study_design_scores_gemma":[0.000005549274,0.000009685604,0.00011161769,0.0000022324612,0.00000599502,0.000013635555,0.000012572375,0.9980959,0.00003104487,0.0016327904,0.00007519077,0.000003706922],"about_ca_topic_score_codex":0.03219894,"about_ca_topic_score_gemma":0.0151848765,"teacher_disagreement_score":0.03219894,"about_ca_system_score_codex":0.0019517546,"about_ca_system_score_gemma":0.0013546938,"threshold_uncertainty_score":0.06402302},"labels":[],"label_agreement":null},{"id":"W4407695112","doi":"10.1109/iccwamtip64812.2024.10873713","title":"Personalized Federated Learning with Kolmogorov-Arnold Enhanced CNN for Rotating Equipment Fault Diagnosis","year":2024,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"HEC Montréal","funders":"","keywords":"Computer science; Fault (geology); Artificial intelligence; Geology; Seismology","score_opus":0.007950664555694438,"score_gpt":0.22827342891179433,"score_spread":0.2203227643560999,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407695112","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17922132,0.000615636,0.8141733,0.0003614324,0.000090283334,0.000049932944,0.00020320027,0.0028488487,0.0024359524],"genre_scores_gemma":[0.96362036,0.000091384194,0.034661658,0.000108247914,0.000019706136,0.000023425442,0.00021152438,0.000024521712,0.001239081],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980825,0.000036645873,0.000010683206,0.00006637907,0.000041656065,0.00003626705],"domain_scores_gemma":[0.9996333,0.00013438301,0.000043936674,0.00007780852,0.00008916539,0.0000214319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051154575,0.0006792176,0.00048888754,0.0003911822,0.00020049157,0.00040691995,0.00078023144,0.00058435573,0.00070957706],"category_scores_gemma":[0.0016239733,0.00020366121,0.0003852384,0.00025058805,0.00029232778,0.0008772112,0.0007343979,0.000632481,0.00022743335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020899167,0.0001681991,0.006689296,0.000056391033,0.00007894137,0.00020585695,0.0000713908,0.7340694,0.008421775,0.0021987767,0.0019880931,0.24584287],"study_design_scores_gemma":[0.000002829729,0.000027763193,0.00036515982,0.000002281225,0.000008429854,0.00002570665,0.000006298634,0.996837,0.0015018329,0.0010701615,0.00014923731,0.0000031298089],"about_ca_topic_score_codex":0.0046474147,"about_ca_topic_score_gemma":0.006572931,"teacher_disagreement_score":0.0046474147,"about_ca_system_score_codex":0.000570126,"about_ca_system_score_gemma":0.00058725243,"threshold_uncertainty_score":0.009240687},"labels":[],"label_agreement":null},{"id":"W4407891827","doi":"10.18280/jesa.580110","title":"Classification of Bearing Fault Signals in Rotating Machinery Using Neural Networks","year":2025,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Engineering Diagnostics and Reliability","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":"Bearing (navigation); Artificial neural network; Fault (geology); Computer science; Pattern recognition (psychology); Artificial intelligence; Geology; Seismology","score_opus":0.01575065865595162,"score_gpt":0.25589861619162235,"score_spread":0.24014795753567073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407891827","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7911578,0.0012314167,0.20390871,0.00028885796,0.00027303124,0.000051790612,0.00023960302,0.00072408136,0.0021247093],"genre_scores_gemma":[0.9865102,0.00020638744,0.0118050985,0.000018762592,0.00004270499,0.000011578185,0.00021435125,0.000012258051,0.0011787274],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998215,0.000033934193,0.000018399061,0.00004069277,0.000050624712,0.000034878805],"domain_scores_gemma":[0.99942255,0.00029032986,0.00008192957,0.000036764974,0.00014266738,0.00002585326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004173426,0.00045298185,0.00038012382,0.0009953566,0.0001698175,0.0005427677,0.00031094562,0.000696528,0.00077063387],"category_scores_gemma":[0.0015544752,0.00015288798,0.00034561695,0.0005128747,0.00018360364,0.00044575095,0.00020948645,0.0004211698,0.0002834047],"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":[0.0012517623,0.0004351766,0.021350082,0.00020262696,0.00012397575,0.0003148363,0.0001086783,0.24836943,0.057426877,0.0009813601,0.002258502,0.66717666],"study_design_scores_gemma":[0.000007023673,0.000062122446,0.0073167915,0.000008783938,0.00001545287,0.000028849727,0.000015115217,0.9883979,0.0036595245,0.00027138912,0.00021056217,0.0000065838935],"about_ca_topic_score_codex":0.0033246046,"about_ca_topic_score_gemma":0.002296939,"teacher_disagreement_score":0.0033246046,"about_ca_system_score_codex":0.00027868222,"about_ca_system_score_gemma":0.00023169017,"threshold_uncertainty_score":0.0066105127},"labels":[],"label_agreement":null},{"id":"W4408625050","doi":"10.5006/mp2014_53_4-52","title":"Corrosion Risk Mitigation Strategies for the Foundations of Transmission and Distribution Structures—Part 2","year":2014,"lang":"en","type":"article","venue":"Materials performance","topic":"Engineering Diagnostics and Reliability","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":"BC Hydro (Canada)","funders":"","keywords":"Corrosion; Transmission (telecommunications); Engineering; Distribution (mathematics); Forensic engineering; Materials science; Metallurgy; Mathematics; Electrical engineering","score_opus":0.004548325426724582,"score_gpt":0.19712417562267837,"score_spread":0.19257585019595377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408625050","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12697454,0.017568817,0.6004334,0.023904033,0.00078234304,0.0011046492,0.00024481304,0.0010914559,0.22789595],"genre_scores_gemma":[0.8378298,0.011761061,0.09476112,0.00084399467,0.00027734536,0.00030200105,0.0001600943,0.00008133188,0.05398319],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99948883,0.00013406153,0.000016730424,0.000039952956,0.00023446458,0.00008601903],"domain_scores_gemma":[0.99954766,0.00008387538,0.000083958046,0.000025366448,0.00022825296,0.00003072421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007804805,0.0009834316,0.00030307597,0.0011850856,0.0008700412,0.0014362467,0.0009966936,0.0013051013,0.0056829667],"category_scores_gemma":[0.0012111646,0.0003528289,0.00038291377,0.00028918704,0.00048088064,0.0012368666,0.0015519445,0.00083659915,0.0008265824],"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":[0.00012793047,0.00025449463,0.0031662465,0.00091757235,0.00006806977,0.0009889195,0.0010436529,0.19901626,0.047309935,0.15983224,0.04773532,0.53953934],"study_design_scores_gemma":[0.00013948481,0.0018838451,0.012900932,0.0017761211,0.00023342315,0.0020361445,0.0050853803,0.33345774,0.06752439,0.13583174,0.43894953,0.00018126388],"about_ca_topic_score_codex":0.0040245093,"about_ca_topic_score_gemma":0.0065336786,"teacher_disagreement_score":0.0056829667,"about_ca_system_score_codex":0.0012357809,"about_ca_system_score_gemma":0.0019348292,"threshold_uncertainty_score":0.019011438},"labels":[],"label_agreement":null},{"id":"W4408897828","doi":"10.1109/rams48127.2025.10935127","title":"Risk-Based Optimization of Periodic Maintenance for Power Grid Equipment","year":2025,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Grid; Power grid; Computer science; Power (physics); Reliability engineering; Engineering; Mathematics; Physics","score_opus":0.0029679202044296618,"score_gpt":0.19923003799908284,"score_spread":0.1962621177946532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408897828","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14182036,0.00058141333,0.84027374,0.00067941763,0.000060657614,0.00016340052,0.00031808804,0.0004892801,0.015613661],"genre_scores_gemma":[0.9500436,0.0001912293,0.044377346,0.00007893071,0.000014724265,0.00014647258,0.00019636063,0.00011394108,0.0048372666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996284,0.00015507695,0.0000122571,0.0000592806,0.000083250736,0.00006165953],"domain_scores_gemma":[0.9983311,0.001224266,0.00017145925,0.00004713839,0.00014670273,0.00007920468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001515321,0.0009782386,0.0009387894,0.00051465654,0.00028163934,0.0010269847,0.0007747898,0.0009283525,0.003354011],"category_scores_gemma":[0.003827028,0.00069146673,0.0007277667,0.00035225184,0.0006981814,0.00069872895,0.00078058016,0.0010666787,0.00025857185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015732017,0.0000065543977,0.00011674325,0.00000841818,0.000005615659,0.000010211268,0.000004819507,0.99751115,0.00012368939,0.0011236123,0.000076593424,0.0009968758],"study_design_scores_gemma":[0.0000039733345,0.000009309813,0.000055258566,0.0000019727445,0.0000029852677,0.0000022428392,0.0000024568722,0.9990132,0.000057270747,0.0007854609,0.00006475166,0.0000011014533],"about_ca_topic_score_codex":0.006770229,"about_ca_topic_score_gemma":0.0038364723,"teacher_disagreement_score":0.006770229,"about_ca_system_score_codex":0.0011704576,"about_ca_system_score_gemma":0.0015340991,"threshold_uncertainty_score":0.013461649},"labels":[],"label_agreement":null},{"id":"W4409085222","doi":"10.18280/mmep.120330","title":"Alpha Power Type II-G Family: Adding a Power Parameter of Distributions","year":2025,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Engineering Diagnostics and Reliability","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":"Power (physics); Type (biology); Mathematics; Physics; Biology; Thermodynamics","score_opus":0.01103164307076366,"score_gpt":0.20664259123830703,"score_spread":0.19561094816754337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409085222","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":[0.009904312,0.000782117,0.9853119,0.0003503026,0.00013147309,0.00013428881,0.0002282222,0.00046402757,0.002693238],"genre_scores_gemma":[0.4999724,0.0042092856,0.478389,0.0013437746,0.0008950632,0.0019192795,0.0016071999,0.000887895,0.010776146],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9911607,0.0033915697,0.00046988504,0.002037654,0.0023696444,0.00057058677],"domain_scores_gemma":[0.9572796,0.028835647,0.0032441935,0.00566277,0.0042177797,0.0007599896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015541035,0.001965519,0.0020932427,0.003729466,0.0012327724,0.0042830417,0.0036164685,0.0030794498,0.0055872165],"category_scores_gemma":[0.05275137,0.0009353359,0.0030127098,0.0037064867,0.0041511194,0.006152511,0.0026092005,0.005052449,0.0023903036],"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":[0.0004857496,0.00017809554,0.038818214,0.0006233865,0.00054322876,0.0020089196,0.0014685962,0.16114591,0.004384272,0.511542,0.012664902,0.26613662],"study_design_scores_gemma":[0.000062606465,0.0004156208,0.006789986,0.00027336384,0.00016868448,0.0029700447,0.00044342398,0.55467325,0.0024993736,0.40000224,0.03152411,0.00017731031],"about_ca_topic_score_codex":0.0025363318,"about_ca_topic_score_gemma":0.001164149,"teacher_disagreement_score":0.015541035,"about_ca_system_score_codex":0.0018001205,"about_ca_system_score_gemma":0.0019272501,"threshold_uncertainty_score":0.0821898},"labels":[],"label_agreement":null},{"id":"W4409501462","doi":"10.5006/c2023-19195","title":"Advanced Inspection Technologies for Determining the Extent of Corrosion Damage in Fixed Equipment","year":2023,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Suncor Energy (Canada)","funders":"","keywords":"Corrosion; Reliability engineering; Computer science; Forensic engineering; Materials science; Engineering; Metallurgy","score_opus":0.010215091923638354,"score_gpt":0.23740796455194393,"score_spread":0.2271928726283056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409501462","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3746658,0.027455105,0.5886352,0.00033071576,0.0002772927,0.00023872574,0.0005030085,0.0013527586,0.006541491],"genre_scores_gemma":[0.7494106,0.009260645,0.2387008,0.00009131686,0.00012569249,0.00006750103,0.0002927534,0.00004504783,0.0020055857],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989937,0.00016328093,0.000033821805,0.00012522396,0.0006347927,0.00004921523],"domain_scores_gemma":[0.9990332,0.00024265032,0.00016197175,0.000088454566,0.000446091,0.000027650229],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007497979,0.0004954035,0.00045109238,0.002260271,0.00018492468,0.0004522626,0.0005481296,0.0006845738,0.0010666664],"category_scores_gemma":[0.0012503297,0.0002567549,0.00036319566,0.00080002943,0.0004076462,0.00074822793,0.00043904933,0.00045751233,0.00039086796],"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":[0.00030694134,0.00013504826,0.012919798,0.0008598131,0.000061217404,0.00017240383,0.00011541611,0.008937633,0.70983386,0.0015428902,0.0008957616,0.26421928],"study_design_scores_gemma":[0.000104527004,0.0039465367,0.102468565,0.00024972274,0.0002995196,0.0032541812,0.00020222159,0.13009872,0.7386214,0.0028503367,0.017701397,0.00020287606],"about_ca_topic_score_codex":0.0006976112,"about_ca_topic_score_gemma":0.001455535,"teacher_disagreement_score":0.002260271,"about_ca_system_score_codex":0.0003628456,"about_ca_system_score_gemma":0.00025489874,"threshold_uncertainty_score":0.003965378},"labels":[],"label_agreement":null},{"id":"W4409580648","doi":"10.61091/jcmcc127a-054","title":"Supervised Self-Encoder-Based Feature Learning Study for Fault Diagnosis of Variable Operating Condition Rotor Blade Systems","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Engineering Diagnostics and Reliability","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":"Blade (archaeology); Rotor (electric); Feature (linguistics); Fault (geology); Encoder; Variable (mathematics); Computer science; Artificial intelligence; Pattern recognition (psychology); Engineering; Mathematics; Structural engineering; Mechanical engineering; Operating system","score_opus":0.006250861287631398,"score_gpt":0.23412966299289817,"score_spread":0.22787880170526678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409580648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60879105,0.00024546398,0.38943258,0.00010771886,0.00003119742,0.000033065,0.000052922896,0.0003407483,0.00096528407],"genre_scores_gemma":[0.9866238,0.000030434103,0.012908288,0.000009242833,0.0000054884267,0.000009691128,0.00005202757,0.000008052445,0.00035300184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997837,0.00006081982,0.0000173198,0.00004252631,0.00006764151,0.00002795822],"domain_scores_gemma":[0.99841917,0.00090883806,0.00012698444,0.00011802773,0.0004023356,0.000024693096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073146884,0.00028015222,0.00034798682,0.00033599752,0.00016959467,0.00029405722,0.00031573838,0.00029863275,0.00040688424],"category_scores_gemma":[0.002257104,0.00013559317,0.00031114757,0.00020773686,0.0002740162,0.00041966388,0.00019472641,0.0004238603,0.00007069055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033539173,0.00026921788,0.008954068,0.00010803222,0.00007837774,0.00017279541,0.00021869276,0.8286722,0.017002545,0.0023526133,0.00059799734,0.14123806],"study_design_scores_gemma":[0.0000011923543,0.000023724797,0.00074496714,9.769914e-7,0.0000024398857,0.000008158472,0.000004290828,0.99771667,0.0013577973,0.00011192153,0.00002633316,0.0000015008324],"about_ca_topic_score_codex":0.0031672462,"about_ca_topic_score_gemma":0.0024246962,"teacher_disagreement_score":0.0031672462,"about_ca_system_score_codex":0.0003711253,"about_ca_system_score_gemma":0.00033563335,"threshold_uncertainty_score":0.0062975883},"labels":[],"label_agreement":null},{"id":"W4409581206","doi":"10.1117/12.3065093","title":"Fault diagnosis of bearings under variable working conditions based on strip pooling VGG19","year":2025,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Variable (mathematics); Pooling; Computer science; Fault (geology); Artificial intelligence; Geology; Mathematics","score_opus":0.00708303097245265,"score_gpt":0.21736239714823424,"score_spread":0.21027936617578158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409581206","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52730435,0.0009814614,0.46207428,0.00032511796,0.00013367906,0.00013145791,0.0010478266,0.003611912,0.004389886],"genre_scores_gemma":[0.96772635,0.00018846274,0.02941803,0.00004676156,0.000018270051,0.00002685362,0.0007382395,0.00005038522,0.0017866419],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999156,0.0000070269516,0.0000033475708,0.000025745423,0.000023794235,0.000024482817],"domain_scores_gemma":[0.99992585,0.000016766975,0.0000141212295,0.000012377964,0.000025148498,0.000005819299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019217124,0.0007426957,0.00035341954,0.00093430275,0.00016790902,0.00039899643,0.0006295869,0.00034093778,0.0012033439],"category_scores_gemma":[0.00036271143,0.00013301428,0.00034943328,0.0005283122,0.00027072607,0.0003931466,0.00032094202,0.00026040408,0.00035438093],"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":[0.00064135285,0.00016869266,0.011339863,0.000095404124,0.000108059096,0.00039278145,0.00011886638,0.3362512,0.07451947,0.0013891355,0.004818758,0.57015646],"study_design_scores_gemma":[0.000010483229,0.00010070153,0.0092838835,0.000008346098,0.000034328856,0.00015995759,0.000026944053,0.9670669,0.02098674,0.0009381775,0.00137199,0.000011607672],"about_ca_topic_score_codex":0.009744245,"about_ca_topic_score_gemma":0.008216471,"teacher_disagreement_score":0.009744245,"about_ca_system_score_codex":0.0005290726,"about_ca_system_score_gemma":0.0003375172,"threshold_uncertainty_score":0.019375086},"labels":[],"label_agreement":null},{"id":"W4409602112","doi":"10.61091/jcmcc127b-020","title":"Designing Novel Biofuels Using Generative Adversarial Networks","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Engineering Diagnostics and Reliability","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":"Biofuel; Adversarial system; Generative grammar; Computer science; Generative adversarial network; Biochemical engineering; Artificial intelligence; Biotechnology; Engineering; Biology; Deep learning","score_opus":0.010601869521252829,"score_gpt":0.23362088601250205,"score_spread":0.22301901649124922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409602112","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.081573375,0.0004172542,0.91003567,0.00041940273,0.00008136574,0.00007107155,0.00010142464,0.0005367215,0.0067636743],"genre_scores_gemma":[0.9361991,0.00023309933,0.058830425,0.00031263617,0.000024941208,0.00015078715,0.00014940825,0.00006388305,0.004035786],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983203,0.00004110359,0.0000055879696,0.000052637162,0.000035020967,0.000033564193],"domain_scores_gemma":[0.9996815,0.0002011577,0.00003769738,0.00002235563,0.000037925674,0.00001948779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053565466,0.0008106812,0.00046843165,0.00031167723,0.00023376264,0.00049952744,0.00080318877,0.00091726886,0.0016807457],"category_scores_gemma":[0.0011023144,0.00038244957,0.0007045674,0.00023421485,0.0006010947,0.00074275804,0.0008618519,0.0008897336,0.00023964139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002159209,0.000016129909,0.0003950824,0.000018343886,0.000015822758,0.000050362312,0.00001749932,0.98458153,0.002236938,0.002262316,0.00024826414,0.010136188],"study_design_scores_gemma":[0.0000012941113,0.0000073419883,0.000027479091,0.0000012453314,0.0000019334,0.000005107514,0.0000021502667,0.99872345,0.00033883157,0.0007901286,0.000099628414,0.0000013506244],"about_ca_topic_score_codex":0.0020090626,"about_ca_topic_score_gemma":0.0019440758,"teacher_disagreement_score":0.0020090626,"about_ca_system_score_codex":0.0005462978,"about_ca_system_score_gemma":0.00036894437,"threshold_uncertainty_score":0.0056226254},"labels":[],"label_agreement":null},{"id":"W4409794962","doi":"10.61091/jcmcc127b-415","title":"Research on the safety of oil and gas loading and unloading operations in enterprises based on data mining and correlation analysis algorithms","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Engineering Diagnostics and Reliability","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":"Correlation; Data mining; Computer science; Fossil fuel; Petroleum engineering; Algorithm; Engineering; Mathematics; Waste management","score_opus":0.02214121327603612,"score_gpt":0.2933135543041285,"score_spread":0.27117234102809235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409794962","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14060573,0.0014050376,0.8540507,0.0007536024,0.0000659369,0.00014136887,0.0002357086,0.00041631574,0.0023256438],"genre_scores_gemma":[0.89318824,0.0015486063,0.10339256,0.00010602421,0.00010073001,0.00015386731,0.00046238597,0.000030166106,0.0010173981],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99706465,0.0008173725,0.00032151517,0.00067749637,0.00087734434,0.00024171764],"domain_scores_gemma":[0.99221826,0.004707872,0.0008635231,0.0003729552,0.0016381368,0.0001992181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003789043,0.0011962907,0.0014174654,0.004299184,0.0008411334,0.0022258624,0.0013906036,0.0010053129,0.0006102104],"category_scores_gemma":[0.010365739,0.0004248921,0.0013518757,0.003775365,0.0007688261,0.003827893,0.00085224176,0.0010753236,0.00016149005],"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":[0.00023345917,0.00043218548,0.07471523,0.0004362561,0.00048598036,0.00027926845,0.00031263463,0.6167057,0.002618051,0.017808057,0.0025990733,0.28337413],"study_design_scores_gemma":[0.000005006516,0.00004427677,0.0030929912,0.0000141235405,0.000036033027,0.00003407864,0.000060606555,0.9921525,0.0009477355,0.003301696,0.00030014743,0.00001079249],"about_ca_topic_score_codex":0.009096347,"about_ca_topic_score_gemma":0.0039577917,"teacher_disagreement_score":0.009096347,"about_ca_system_score_codex":0.0016166469,"about_ca_system_score_gemma":0.0028024842,"threshold_uncertainty_score":0.020038605},"labels":[],"label_agreement":null},{"id":"W4410157187","doi":"10.3390/en18092395","title":"Analysis and Diagnosis of the Stator Turn-to-Turn Short-Circuit Faults in Wound-Rotor Synchronous Generators","year":2025,"lang":"en","type":"article","venue":"Energies","topic":"Engineering Diagnostics and Reliability","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":"China Scholarship Council","keywords":"Turn (biochemistry); Stator; Rotor (electric); Short circuit; Wound rotor motor; Electrical engineering; Control theory (sociology); Engineering; Computer science; Physics; Induction motor; Artificial intelligence; Voltage; Nuclear magnetic resonance","score_opus":0.003676740346470709,"score_gpt":0.20238802175754947,"score_spread":0.19871128141107877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410157187","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.116608,0.0002628075,0.8818873,0.00007719102,0.000016308852,0.00004778313,0.000064938096,0.00034534786,0.0006902384],"genre_scores_gemma":[0.9656293,0.000099260935,0.033871066,0.000014219536,0.000012381121,0.00001795782,0.0000788555,0.000012755782,0.00026403903],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971586,0.0000649836,0.000023522553,0.000057694026,0.00011408697,0.000023920613],"domain_scores_gemma":[0.9985826,0.00075295236,0.00028253166,0.00007708606,0.00026438397,0.00004047054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052459637,0.00062931614,0.0004904189,0.0009537161,0.00015571383,0.0004901343,0.00039496136,0.00048217914,0.0005507166],"category_scores_gemma":[0.0025209372,0.00016394391,0.0002493742,0.00028749474,0.0004209918,0.00067545555,0.0003161441,0.00031136032,0.00010634883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016522036,0.000045757122,0.016103366,0.00016828906,0.000057043115,0.0003714864,0.00012567012,0.8563735,0.021242984,0.0034619228,0.0004082839,0.101476505],"study_design_scores_gemma":[0.000004541616,0.000048598133,0.0033284961,0.000006908145,0.000008478247,0.00007005309,0.000024586961,0.9908434,0.0035801292,0.0019208859,0.00015713662,0.000006785852],"about_ca_topic_score_codex":0.0014913694,"about_ca_topic_score_gemma":0.0012179217,"teacher_disagreement_score":0.0014913694,"about_ca_system_score_codex":0.0004128111,"about_ca_system_score_gemma":0.00028201338,"threshold_uncertainty_score":0.0029951334},"labels":[],"label_agreement":null},{"id":"W4412352918","doi":"10.1109/ddcls66240.2025.11064990","title":"The Fault Diagnosis Model for Variable Speed Rolling Bearings Based on GCRA-FMD, COT, and Deep Convolutional Neural Networks","year":2025,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Convolutional neural network; Variable (mathematics); Computer science; Artificial intelligence; Fault (geology); Artificial neural network; Deep learning; Pattern recognition (psychology); Geology; Mathematics; Seismology","score_opus":0.00574519837252442,"score_gpt":0.2000598653128355,"score_spread":0.1943146669403111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412352918","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.090146385,0.0007188239,0.9042367,0.0003615432,0.00012318708,0.0000636424,0.00017858573,0.0011212039,0.0030499639],"genre_scores_gemma":[0.95060974,0.00028142432,0.04494865,0.000064024214,0.000022265967,0.000057557176,0.00016529464,0.000021399639,0.0038296727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999114,0.0000077478135,0.0000056100926,0.000031234234,0.000030186455,0.000013811077],"domain_scores_gemma":[0.99986494,0.00003098792,0.000025445937,0.000011462669,0.000058452668,0.000008788985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002325471,0.00057329494,0.00037589358,0.00042617068,0.00023613898,0.0003735783,0.0006973748,0.00046959473,0.0009785416],"category_scores_gemma":[0.00042067448,0.00024020803,0.00037334973,0.0002474871,0.00024635237,0.00048502933,0.00029738632,0.00064870086,0.00019239692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001440154,0.0000660884,0.0031111464,0.00008297284,0.000045144774,0.00011944079,0.000051539304,0.8487572,0.018092088,0.0027852228,0.0010760933,0.12566905],"study_design_scores_gemma":[0.0000014414936,0.000013613516,0.00024791912,0.0000016993031,0.000003964329,0.000012509679,0.0000013637431,0.99858993,0.0008069038,0.00018050267,0.00013800632,0.0000021031074],"about_ca_topic_score_codex":0.019922009,"about_ca_topic_score_gemma":0.02203344,"teacher_disagreement_score":0.019922009,"about_ca_system_score_codex":0.0007968158,"about_ca_system_score_gemma":0.0007747222,"threshold_uncertainty_score":0.039612114},"labels":[],"label_agreement":null},{"id":"W4412595829","doi":"10.3390/jmse13081398","title":"Deep Hybrid Model for Fault Diagnosis of Ship’s Main Engine","year":2025,"lang":"en","type":"article","venue":"Journal of Marine Science and Engineering","topic":"Engineering Diagnostics and Reliability","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":"Institute for Information and Communications Technology Promotion; Ministry of Science and ICT, South Korea; Korea Creative Content Agency; Ministry of Culture, Sports and Tourism","keywords":"Fault (geology); Environmental science; Marine engineering; Computer science; Geology; Engineering; Seismology","score_opus":0.006010805398969117,"score_gpt":0.21313872166458894,"score_spread":0.20712791626561983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412595829","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17948343,0.0012354181,0.8141842,0.00041968178,0.00011943774,0.000049434304,0.00020827471,0.0012750066,0.003025218],"genre_scores_gemma":[0.9818711,0.0001734513,0.014993649,0.000078578145,0.000021275271,0.000043829394,0.00015696822,0.000016540307,0.0026446416],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998814,0.000016682956,0.000006955327,0.000037866033,0.000028589406,0.0000284764],"domain_scores_gemma":[0.9997758,0.00009899917,0.000028465845,0.0000150007045,0.00007012652,0.000011617486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032149203,0.0006171974,0.0005621151,0.00041028118,0.00020217935,0.00050535443,0.0007962165,0.0007232919,0.0009955657],"category_scores_gemma":[0.00069091603,0.0002522572,0.0006040904,0.00021075421,0.00028306985,0.0005124772,0.000494682,0.00075390545,0.00017514669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016209653,0.00006328709,0.0017109545,0.00005024664,0.00005779113,0.00009833068,0.00004129299,0.926781,0.0060255732,0.001300123,0.00070636335,0.06300302],"study_design_scores_gemma":[0.0000012900518,0.000011434147,0.0001220649,0.0000010103604,0.0000034590873,0.0000045398656,0.0000014146184,0.9992956,0.00033692401,0.00018201116,0.000038972823,0.0000012263804],"about_ca_topic_score_codex":0.012693692,"about_ca_topic_score_gemma":0.010132119,"teacher_disagreement_score":0.012693692,"about_ca_system_score_codex":0.0006375846,"about_ca_system_score_gemma":0.0005943538,"threshold_uncertainty_score":0.025239646},"labels":[],"label_agreement":null},{"id":"W4412727434","doi":"10.3390/ijms26146561","title":"Predicting the Damaging Potential of Uncharacterized KCNQ1 and KCNE1 Variants","year":2025,"lang":"en","type":"article","venue":"International Journal of Molecular Sciences","topic":"Engineering Diagnostics and Reliability","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":"Computational biology; Biology; Computer science","score_opus":0.0032774234176691096,"score_gpt":0.2244369456172302,"score_spread":0.2211595221995611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412727434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9790773,0.0021406813,0.0046654623,0.00015564026,0.00006399486,0.000043699678,0.012158485,0.00096119917,0.0007336457],"genre_scores_gemma":[0.93688065,0.0007623699,0.012809956,0.00016491322,0.000050702587,0.000039515056,0.04870388,0.00019494932,0.00039309778],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919504,0.00014765622,0.000119717595,0.00029745052,0.000156691,0.00008348649],"domain_scores_gemma":[0.9982419,0.0010397553,0.0002829259,0.0001210638,0.00016512415,0.00014917056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010230815,0.0009226223,0.00076925854,0.0022567606,0.00041823077,0.0007540391,0.00062335294,0.0008295944,0.0014924656],"category_scores_gemma":[0.0032302374,0.00025644884,0.0009948901,0.0013216276,0.0002715797,0.00041336656,0.0006578279,0.00044930584,0.00079516973],"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":[0.003733748,0.00050682086,0.76790464,0.0015510761,0.001580682,0.00786171,0.00031895514,0.07057528,0.040213417,0.0010832552,0.020580707,0.08408977],"study_design_scores_gemma":[0.00086576736,0.0014243372,0.40916198,0.00035686963,0.0019271172,0.01602512,0.0005638327,0.5096489,0.0340084,0.004282378,0.021495927,0.00023929615],"about_ca_topic_score_codex":0.0018884435,"about_ca_topic_score_gemma":0.0038866966,"teacher_disagreement_score":0.0022567606,"about_ca_system_score_codex":0.00033780417,"about_ca_system_score_gemma":0.0005605245,"threshold_uncertainty_score":0.0054106712},"labels":[],"label_agreement":null},{"id":"W4413380692","doi":"10.18280/ts.420406","title":"Infrared Image-Based Fault Diagnosis and Condition Assessment of Power Equipment Using Deep Learning","year":2025,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Engineering Diagnostics and Reliability","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":"Fault (geology); Artificial intelligence; Infrared; Deep learning; Computer science; Power (physics); Image (mathematics); Computer vision; Reliability engineering; Pattern recognition (psychology); Engineering; Geology; Seismology; Optics; Physics","score_opus":0.00707228584199011,"score_gpt":0.2546499605117455,"score_spread":0.2475776746697554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413380692","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11756485,0.00042625208,0.877775,0.00019038736,0.00004371874,0.000057666213,0.00013390416,0.0015600132,0.002248139],"genre_scores_gemma":[0.9062504,0.00018511903,0.09144742,0.000110071815,0.00002967757,0.000050375136,0.0003068976,0.000029687875,0.0015903602],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980813,0.00002287853,0.000012124952,0.00006137309,0.000057327856,0.000038160877],"domain_scores_gemma":[0.99976796,0.00006195752,0.000045809167,0.000024034594,0.0000826758,0.000017598346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003792034,0.0007312124,0.0005204731,0.0009736347,0.00018296191,0.000503769,0.00087267265,0.0007281236,0.0010066878],"category_scores_gemma":[0.0009935749,0.00024975016,0.0005465684,0.0005625761,0.00028205666,0.0007957985,0.0006128124,0.00068249414,0.000264091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021848503,0.0002108872,0.004777113,0.0001030039,0.00006372424,0.0001574802,0.000089412846,0.5575882,0.020122215,0.0021536388,0.002056632,0.41245928],"study_design_scores_gemma":[0.000002359205,0.000013182679,0.00036199737,0.0000027495284,0.000004189349,0.0000069071807,0.000003907928,0.997474,0.0015965275,0.00045032316,0.000081448794,0.0000023884581],"about_ca_topic_score_codex":0.0058610193,"about_ca_topic_score_gemma":0.0052229045,"teacher_disagreement_score":0.0058610193,"about_ca_system_score_codex":0.0006410638,"about_ca_system_score_gemma":0.00057529315,"threshold_uncertainty_score":0.011653781},"labels":[],"label_agreement":null},{"id":"W4413556766","doi":"10.1109/isie62713.2025.11124781","title":"Zero-Sample Fault Diagnosis for Bearings Using an Hierachical Constrast Learning Approach","year":2025,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Zero (linguistics); Sample (material); Computer science; Fault (geology); Artificial intelligence; Control theory (sociology); Geology; Physics; Control (management)","score_opus":0.01451144627035178,"score_gpt":0.24680581385313538,"score_spread":0.2322943675827836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413556766","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":[0.08859133,0.00024837937,0.90848255,0.0001775165,0.000029274292,0.0000586727,0.0001174115,0.0010810721,0.0012138076],"genre_scores_gemma":[0.824122,0.00012529141,0.17295215,0.00017470487,0.00004989536,0.00007258368,0.0005933745,0.000069538466,0.0018403855],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99959,0.0000610146,0.000021963559,0.00014016953,0.00012995325,0.00005690789],"domain_scores_gemma":[0.99942076,0.0002384447,0.00006663331,0.000071487244,0.00017189882,0.000030808416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005143907,0.00068638596,0.00069384015,0.0011288556,0.00037990353,0.00052719016,0.00095508655,0.00077980285,0.0010716125],"category_scores_gemma":[0.0014058381,0.00020950001,0.00062092516,0.0005869796,0.00052963546,0.001157229,0.0009948466,0.00081878086,0.0003806939],"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":[0.00062464894,0.0004021386,0.006240743,0.00014463949,0.00008915434,0.00028636816,0.00028953716,0.22288997,0.032055188,0.006803346,0.0029053944,0.7272689],"study_design_scores_gemma":[0.000014537904,0.00011330541,0.00082303875,0.000004694717,0.000015263864,0.00005725743,0.00003818214,0.989805,0.004332851,0.0042832377,0.0005053322,0.0000073820097],"about_ca_topic_score_codex":0.0030344203,"about_ca_topic_score_gemma":0.0048281676,"teacher_disagreement_score":0.0030344203,"about_ca_system_score_codex":0.0005727382,"about_ca_system_score_gemma":0.00075339875,"threshold_uncertainty_score":0.00603348},"labels":[],"label_agreement":null},{"id":"W4413679939","doi":"10.1109/compsac65507.2025.00248","title":"Synthetic Fouling Image Data Generation for Heat Exchanger Predictive Maintenance","year":2025,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Western University","funders":"","keywords":"Fouling; Heat exchanger; Computer science; Artificial intelligence; Process engineering; Engineering; Mechanical engineering; Chemistry","score_opus":0.016461990394207867,"score_gpt":0.2452062710023595,"score_spread":0.22874428060815163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413679939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92331505,0.0007222519,0.053100683,0.00065552833,0.00032107887,0.0002856571,0.0159387,0.0023539779,0.0033071388],"genre_scores_gemma":[0.93943137,0.00023281542,0.036247537,0.00010458466,0.00003856609,0.00013346916,0.022748396,0.000089027315,0.00097426795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977654,0.00003879322,0.000012077496,0.00006650781,0.00007236691,0.000033745237],"domain_scores_gemma":[0.9993892,0.00021397641,0.00006900181,0.00009788596,0.00019494594,0.000035027624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042646186,0.0007440697,0.00031154236,0.00076727924,0.00023443985,0.00037001338,0.0008766004,0.0007875744,0.0006828445],"category_scores_gemma":[0.0015179602,0.00017989981,0.0005644563,0.0005812528,0.00040131537,0.00040297915,0.0003736752,0.00058569456,0.00023479886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011217583,0.0010365939,0.026692076,0.00053203694,0.00018842687,0.0010146934,0.00017048893,0.7799869,0.03865025,0.0013200631,0.024601717,0.12468499],"study_design_scores_gemma":[0.00004850315,0.00024232524,0.017240936,0.000031490436,0.000031160864,0.00022996278,0.00011500854,0.94809026,0.029161986,0.0007678296,0.0040043374,0.00003620264],"about_ca_topic_score_codex":0.009291116,"about_ca_topic_score_gemma":0.011358539,"teacher_disagreement_score":0.009291116,"about_ca_system_score_codex":0.0008144221,"about_ca_system_score_gemma":0.00041048505,"threshold_uncertainty_score":0.018474042},"labels":[],"label_agreement":null},{"id":"W4414009795","doi":"10.1109/iccsc66714.2025.11134853","title":"A New Framework Based on FOG Computing and Edge AI to Increase the Reliability of Predictive Maintenance of Rotating Machines","year":2025,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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":"Nexen (Canada)","funders":"","keywords":"Reliability (semiconductor); Computer science; Enhanced Data Rates for GSM Evolution; Edge computing; Reliability engineering; Predictive maintenance; Artificial intelligence; Engineering; Physics","score_opus":0.0023351673073519486,"score_gpt":0.22212804935720815,"score_spread":0.2197928820498562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414009795","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009373284,0.0011484377,0.979223,0.0005733619,0.00031509294,0.00011071292,0.00007041074,0.0013803837,0.007805244],"genre_scores_gemma":[0.54915804,0.0016039152,0.44225743,0.0008062116,0.0004135124,0.00023782463,0.0002141274,0.0001636599,0.0051452075],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996045,0.00007409226,0.000022642034,0.00011311532,0.00013095692,0.000054641852],"domain_scores_gemma":[0.9996747,0.000090934634,0.000027369799,0.0000574607,0.00010219922,0.000047301914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006141303,0.00050560356,0.0005185735,0.00061638973,0.00060801074,0.0013707484,0.0015522802,0.0006554148,0.0013038806],"category_scores_gemma":[0.0009430827,0.00016540197,0.0005199262,0.0005270691,0.00058871537,0.0020835635,0.0012611197,0.0011174695,0.00030496606],"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":[0.0005841263,0.00047396807,0.0027501907,0.00053412234,0.00025524723,0.0009527232,0.00062711845,0.15627064,0.05404188,0.31151474,0.028294131,0.44370112],"study_design_scores_gemma":[0.000023660668,0.00011736591,0.00061720045,0.00003151723,0.00005137464,0.00019273731,0.000059348793,0.91493726,0.0047581387,0.05976254,0.019419018,0.000029914765],"about_ca_topic_score_codex":0.0037141277,"about_ca_topic_score_gemma":0.0035569547,"teacher_disagreement_score":0.0037141277,"about_ca_system_score_codex":0.0005485629,"about_ca_system_score_gemma":0.00083168154,"threshold_uncertainty_score":0.0073850155},"labels":[],"label_agreement":null},{"id":"W4414199925","doi":"10.3390/technologies13090417","title":"Life Damage Online Monitoring Technology of a Steam Turbine Rotor Start-Up Based on an Empirical-Statistical Model","year":2025,"lang":"en","type":"article","venue":"Technologies","topic":"Engineering Diagnostics and Reliability","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":"Petro-Canada","funders":"","keywords":"Finite element method; Turbine; Rotor (electric); Steam turbine; Nonlinear system; Stress (linguistics)","score_opus":0.017653500946197463,"score_gpt":0.29299969936812126,"score_spread":0.2753461984219238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414199925","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21010427,0.00040244835,0.7842654,0.00020824895,0.000051059495,0.000060585287,0.00013025625,0.002561341,0.0022163577],"genre_scores_gemma":[0.9627408,0.00013101989,0.035739712,0.000039166916,0.00000993929,0.000055747852,0.00009968362,0.00003466431,0.0011492218],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966776,0.00004536939,0.000020404801,0.00009791195,0.00014514344,0.00002340308],"domain_scores_gemma":[0.99959344,0.00009366098,0.000071684,0.000059397815,0.00016463602,0.000017140928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045407497,0.0006165589,0.00043950576,0.00062127353,0.00023080077,0.00039377055,0.000585617,0.0004752666,0.0010109099],"category_scores_gemma":[0.0011022325,0.00030360027,0.0004099485,0.00032805186,0.0002531414,0.0008143135,0.00035643778,0.0005064534,0.00034593686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003784909,0.00026619888,0.026726931,0.00040194337,0.00011034442,0.0004264848,0.00042499314,0.47957754,0.15253298,0.0028398933,0.0025432364,0.33377102],"study_design_scores_gemma":[0.0000046715163,0.00008150109,0.0026150374,0.0000052230607,0.000013349553,0.00006441662,0.000016705237,0.98288673,0.013639862,0.00032034685,0.00034011947,0.000012107115],"about_ca_topic_score_codex":0.0018614393,"about_ca_topic_score_gemma":0.0021331606,"teacher_disagreement_score":0.0018614393,"about_ca_system_score_codex":0.00044292622,"about_ca_system_score_gemma":0.00038292163,"threshold_uncertainty_score":0.00370121},"labels":[],"label_agreement":null},{"id":"W4414954658","doi":"10.1115/pvp2025-154072","title":"Testing the Accuracy and Repeatability of Common Torquing Equipment","year":2025,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","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 Fasteners Institute","funders":"","keywords":"Wrench; Torque; Flange; Repeatability; Joint (building); Bolted joint","score_opus":0.01157647348678964,"score_gpt":0.238318884774351,"score_spread":0.22674241128756137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414954658","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8673058,0.0009147456,0.12588984,0.000089357134,0.00022688988,0.0003988778,0.00051040686,0.0012555403,0.0034085503],"genre_scores_gemma":[0.95967,0.00015287104,0.038243152,0.000042540767,0.000022149095,0.000101275145,0.0002606663,0.00016230879,0.0013449951],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9898739,0.001593055,0.0009671642,0.0017434226,0.0054787262,0.00034372695],"domain_scores_gemma":[0.976942,0.008942529,0.0025192548,0.004061128,0.007299908,0.00023524603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074749324,0.0008357673,0.0005408417,0.0016054567,0.0004801347,0.0009958835,0.001788747,0.0007648425,0.0019620864],"category_scores_gemma":[0.024851132,0.00035052962,0.0004285133,0.00095698074,0.00087583903,0.00080752553,0.0011083627,0.00040518076,0.0007494225],"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":[0.0014371607,0.0005367768,0.098450534,0.0012836085,0.00027942134,0.00038234494,0.0033864083,0.0120774675,0.5499542,0.0008941217,0.0015132828,0.32980478],"study_design_scores_gemma":[0.00010021584,0.008100517,0.3523407,0.000359383,0.00032371213,0.0017906702,0.0014494867,0.04021284,0.5816778,0.0010085863,0.012406181,0.00022996432],"about_ca_topic_score_codex":0.0010150374,"about_ca_topic_score_gemma":0.00263379,"teacher_disagreement_score":0.0074749324,"about_ca_system_score_codex":0.00041481404,"about_ca_system_score_gemma":0.00036829495,"threshold_uncertainty_score":0.03953165},"labels":[],"label_agreement":null},{"id":"W4415360450","doi":"10.59934/jaiea.v5i1.1680","title":"The Application of A Priori Algorithms in Determining the Relationship Between Maternal Age and Pregnancy Conditions","year":2025,"lang":"","type":"article","venue":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","topic":"Engineering Diagnostics and Reliability","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":"Kootenay Association for Science & Technology","funders":"","keywords":"Pregnancy; Confidence interval; Advanced maternal age; Hypertension in Pregnancy; Maternal health; Affect (linguistics); Health data","score_opus":0.028321667414940688,"score_gpt":0.29905619914909526,"score_spread":0.27073453173415457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415360450","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.067606784,0.0043754345,0.917282,0.001230522,0.00030291802,0.0005932889,0.0020724728,0.0015993385,0.0049371766],"genre_scores_gemma":[0.4249008,0.001968703,0.56659466,0.00038648836,0.0003351362,0.0005639519,0.0037291236,0.00009230478,0.0014288395],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.993753,0.0025788539,0.0011149938,0.00126592,0.0010667925,0.00022048209],"domain_scores_gemma":[0.96074045,0.03167007,0.0027047389,0.0014759756,0.0029880968,0.00042072101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012632673,0.0016433962,0.0016427861,0.0054080775,0.0010796635,0.0029612335,0.0019326038,0.0018877634,0.0021426415],"category_scores_gemma":[0.04182879,0.0010081404,0.0019700918,0.0023416781,0.0007615856,0.002786805,0.0013097965,0.0021781682,0.0011114109],"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":[0.0022250905,0.0010261155,0.18080954,0.0010499378,0.0013267698,0.0014846206,0.0006248403,0.20819686,0.0057494934,0.016006343,0.006353415,0.57514685],"study_design_scores_gemma":[0.00009538446,0.0006243879,0.018898174,0.0003378897,0.00038440854,0.0019825273,0.0002492973,0.93726385,0.0044287457,0.027916769,0.007707571,0.000111080764],"about_ca_topic_score_codex":0.0039027282,"about_ca_topic_score_gemma":0.0037116797,"teacher_disagreement_score":0.012632673,"about_ca_system_score_codex":0.0006869098,"about_ca_system_score_gemma":0.0027408507,"threshold_uncertainty_score":0.06680876},"labels":[],"label_agreement":null},{"id":"W4415370434","doi":"10.4171/rlm/1065","title":"The notions of skeleton and crack, and singularities of the oriented distance function","year":2025,"lang":"","type":"article","venue":"Rendiconti Lincei Matematica e Applicazioni","topic":"Engineering Diagnostics and Reliability","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 de Montréal","funders":"","keywords":"Gravitational singularity; Complement (music); Function (biology); Partition (number theory); Object (grammar); Signed distance function; Set function; Skeleton (computer programming)","score_opus":0.0017246681521564452,"score_gpt":0.1884452471101613,"score_spread":0.18672057895800487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415370434","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06640186,0.01566906,0.8589632,0.0020302958,0.0005475427,0.00009252807,0.00020824496,0.00015746057,0.0559298],"genre_scores_gemma":[0.56286633,0.010574403,0.40624872,0.000979787,0.00128877,0.0002195615,0.00030892907,0.00034323538,0.01717025],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99849856,0.00033567363,0.00014901608,0.0003992158,0.00050105125,0.00011657941],"domain_scores_gemma":[0.9974281,0.0013289283,0.0003647441,0.0003037083,0.00035547008,0.0002189355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019656536,0.0010566813,0.0007332003,0.003599486,0.001277023,0.0034712497,0.0010541284,0.0019533294,0.0019483152],"category_scores_gemma":[0.0066570113,0.0005342153,0.0009927588,0.0018715995,0.010580962,0.009272633,0.0031486917,0.0034901479,0.0006151584],"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":[0.000023186316,0.0000062947497,0.00033713522,0.00007462917,0.0000070055517,0.00009162385,0.0006029817,0.0010331573,0.0012468795,0.9771325,0.0007235153,0.018721096],"study_design_scores_gemma":[0.000005869975,0.000042535667,0.00096428156,0.000088010886,0.000011348659,0.0006102738,0.00034869253,0.005623926,0.0011475998,0.9650835,0.026035273,0.000038533355],"about_ca_topic_score_codex":0.0010826224,"about_ca_topic_score_gemma":0.00076182117,"teacher_disagreement_score":0.003599486,"about_ca_system_score_codex":0.0013398927,"about_ca_system_score_gemma":0.0006789225,"threshold_uncertainty_score":0.010395527},"labels":[],"label_agreement":null},{"id":"W4415452378","doi":"10.32370/ia_2025_03_5","title":"The Character of Modern Technical Systems of Varying Complexity","year":2025,"lang":"","type":"article","venue":"Intellectual Archive","topic":"Engineering Diagnostics and Reliability","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":"Process (computing); Multidisciplinary approach; Task (project management); Hierarchy; Character (mathematics); Modularity (biology); Software; Technical progress","score_opus":0.015959836134090796,"score_gpt":0.2364158297589812,"score_spread":0.2204559936248904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415452378","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18085517,0.006984199,0.485585,0.012110409,0.0004178822,0.0002591366,0.000507722,0.00079217413,0.31248832],"genre_scores_gemma":[0.91011924,0.002387955,0.07311217,0.0005870986,0.00042831013,0.00023736813,0.0002492548,0.00012625079,0.012752308],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99697804,0.00075111754,0.00014348516,0.0005133828,0.0013642864,0.0002497819],"domain_scores_gemma":[0.9960544,0.001522463,0.0006860358,0.0008803013,0.00060627586,0.00025043092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016345786,0.00051025936,0.00053475687,0.0025802967,0.0022391407,0.005776679,0.0010088413,0.0013953868,0.004229141],"category_scores_gemma":[0.0076961857,0.00040271875,0.0005726688,0.002222656,0.01035646,0.0077770404,0.00307489,0.0019761652,0.00086947513],"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":[0.000015423397,0.000013340254,0.0013362913,0.00012976432,0.000022436227,0.00021815988,0.0021206113,0.005456526,0.0010616533,0.973739,0.0013019427,0.014584787],"study_design_scores_gemma":[0.000009739203,0.000038670427,0.0032568718,0.0000714963,0.000019967776,0.0003912281,0.001044493,0.0112751145,0.00045860407,0.92897284,0.054427028,0.00003394217],"about_ca_topic_score_codex":0.00097343436,"about_ca_topic_score_gemma":0.00062222127,"teacher_disagreement_score":0.005776679,"about_ca_system_score_codex":0.0018169613,"about_ca_system_score_gemma":0.0013536975,"threshold_uncertainty_score":0.014147818},"labels":[],"label_agreement":null},{"id":"W4415452694","doi":"10.32370/ia_2025_03_9","title":"Stability and Safety of Energy-Generating Equipment Operation Within Smart Home Infrastructure","year":2025,"lang":"","type":"article","venue":"Intellectual Archive","topic":"Engineering Diagnostics and Reliability","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":"Production (economics); Control (management); Electricity; Control reconfiguration; SCADA; Software; Supervisory control; Control system; Energy management","score_opus":0.0057645929377790955,"score_gpt":0.20169536000444757,"score_spread":0.19593076706666848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415452694","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5528455,0.0012132744,0.39023185,0.00085564534,0.00022752746,0.00014162791,0.00052196794,0.0026101244,0.051352482],"genre_scores_gemma":[0.99392915,0.00012300335,0.0037585902,0.000020080626,0.00003612717,0.000033480716,0.0001095171,0.000059136135,0.0019309352],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931383,0.00009176691,0.000028315664,0.00015755421,0.00032566913,0.000082837636],"domain_scores_gemma":[0.99843794,0.00041771747,0.00027821353,0.0003304797,0.00045146412,0.00008422792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065719563,0.00024576893,0.00032568292,0.00044525278,0.0005385474,0.0010000513,0.00049571786,0.00042579995,0.0029263827],"category_scores_gemma":[0.002757684,0.00009935242,0.00019061733,0.0002160798,0.00095309794,0.0009115236,0.000899566,0.00038167633,0.0013882224],"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":[0.0016929923,0.00027223525,0.046091773,0.0007123859,0.00012150129,0.0013403806,0.0025643741,0.17816512,0.17203405,0.07538617,0.009929778,0.5116892],"study_design_scores_gemma":[0.00009640441,0.0010647975,0.104625404,0.0003194906,0.00011150444,0.001973979,0.0021747032,0.6126541,0.15451166,0.06795079,0.05435418,0.00016303026],"about_ca_topic_score_codex":0.0009505679,"about_ca_topic_score_gemma":0.00028343254,"teacher_disagreement_score":0.0029263827,"about_ca_system_score_codex":0.00042449555,"about_ca_system_score_gemma":0.0005797885,"threshold_uncertainty_score":0.009789705},"labels":[],"label_agreement":null},{"id":"W7031558047","doi":"","title":"Kapak-İçindekiler","year":2014,"lang":"tr","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Engineering Diagnostics and Reliability","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":"Technical university; Research method; Middle East; Statistical analysis","score_opus":0.13192479404018143,"score_gpt":0.4954443019130937,"score_spread":0.36351950787291226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7031558047","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":[0.045567654,0.009440914,0.052895673,0.008878142,0.008474588,0.00068200025,0.009458348,0.0117571475,0.85284567],"genre_scores_gemma":[0.20415637,0.009408926,0.07336446,0.002593787,0.0009903953,0.00057885307,0.017901754,0.005463849,0.6855416],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99773175,0.00031148246,0.00018031176,0.00049971,0.00091515225,0.00036165386],"domain_scores_gemma":[0.9971609,0.0003816412,0.00016562914,0.0004065859,0.0016626542,0.00022260669],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0020099902,0.0016226356,0.00092584663,0.0018043753,0.0022375262,0.008430191,0.0012844409,0.0017054927,0.17453155],"category_scores_gemma":[0.005820793,0.0006038512,0.0009066941,0.0018535419,0.0010873848,0.00514824,0.0026092452,0.0030173482,0.10831622],"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":[0.0010370814,0.000335233,0.006841591,0.0009558989,0.00008130295,0.0016466227,0.00296637,0.0014817979,0.006223324,0.06060625,0.32566184,0.5921627],"study_design_scores_gemma":[0.00005584607,0.00009309689,0.004461735,0.0002719355,0.000052696298,0.0012278405,0.002296191,0.001258588,0.004124843,0.007644486,0.9784575,0.000055152188],"about_ca_topic_score_codex":0.0054272986,"about_ca_topic_score_gemma":0.005165925,"teacher_disagreement_score":0.8254684,"about_ca_system_score_codex":0.0016010589,"about_ca_system_score_gemma":0.0033944822,"threshold_uncertainty_score":0.58386624},"labels":[],"label_agreement":null},{"id":"W7034670621","doi":"","title":"Validation of the Sensitivity to Pain Traumatization Scale","year":2020,"lang":"en","type":"other","venue":"York University Digital Library (York University)","topic":"Engineering Diagnostics and Reliability","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":"York University","funders":"","keywords":"Convergent validity; Confirmatory factor analysis; Chronic pain; Psychometrics; Anxiety; Scale (ratio); Reliability (semiconductor); Construct validity; Sample (material)","score_opus":0.003986928490903363,"score_gpt":0.12476634861934076,"score_spread":0.1207794201284374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7034670621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97497696,0.0007668289,0.006866043,0.0003882351,0.00023152925,0.0027783948,0.0016629806,0.000081078244,0.012247985],"genre_scores_gemma":[0.97556216,0.0010468527,0.01376448,0.0003773365,0.000105150946,0.0034564862,0.0023428474,0.00007286519,0.00327191],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9932198,0.0017457834,0.0009872103,0.0004782666,0.0033413586,0.00022750269],"domain_scores_gemma":[0.989504,0.0042993724,0.001511164,0.0009077068,0.0033225308,0.0004553137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010620782,0.00043085005,0.00059101824,0.0016967707,0.00065290084,0.00096180645,0.00078509975,0.00061494386,0.0027719776],"category_scores_gemma":[0.027753724,0.000520422,0.0014668488,0.00081710593,0.0007632286,0.0009180628,0.0016439048,0.0012603519,0.0013387799],"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":[0.0010112383,0.0016249893,0.8478878,0.00031959693,0.0004407015,0.00024064034,0.004615705,0.0008177157,0.0060461187,0.0011956773,0.0033758467,0.13242397],"study_design_scores_gemma":[0.00022165767,0.0023030427,0.98069096,0.00020851706,0.00009988465,0.0010722319,0.0015177253,0.0017945396,0.0016042074,0.00080718443,0.009625497,0.000054704404],"about_ca_topic_score_codex":0.0009024338,"about_ca_topic_score_gemma":0.0013753474,"teacher_disagreement_score":0.010620782,"about_ca_system_score_codex":0.00044670634,"about_ca_system_score_gemma":0.000992217,"threshold_uncertainty_score":0.056168795},"labels":[],"label_agreement":null},{"id":"W70468280","doi":"","title":"Исследование термолиза Сибирского усредненного мазута марки М-40","year":2014,"lang":"ru","type":"article","venue":"Vestnik Tomskogo gosudarstvennogo universiteta Filologiya","topic":"Engineering Diagnostics and Reliability","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":"Refining (metallurgy); Residual oil; Raw material; Coke; Cracking; Fuel oil; Thermal decomposition; Environmental science; Petroleum; Oil refinery; Fluid catalytic cracking; Waste management; Materials science; Metallurgy; Petroleum engineering; Chemistry; Engineering","score_opus":0.004655681993105334,"score_gpt":0.16882289403789016,"score_spread":0.16416721204478482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W70468280","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":[0.26657543,0.06518953,0.104129575,0.005132374,0.0015232535,0.0002946428,0.0027451871,0.0006643549,0.5537456],"genre_scores_gemma":[0.82232994,0.031032767,0.050716583,0.00021560262,0.0003588663,0.00031385853,0.0011449155,0.00023107477,0.09365646],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994073,0.00010886643,0.000037747435,0.00010861049,0.00025450368,0.00008304789],"domain_scores_gemma":[0.99954706,0.00012312493,0.00006488532,0.000095853226,0.00013043612,0.000038552393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006305892,0.0002762269,0.00032608927,0.0011085612,0.0009963475,0.0023060006,0.0002765982,0.00047003428,0.0153441895],"category_scores_gemma":[0.0010848091,0.00038924153,0.0002908089,0.0016212071,0.0011187216,0.0006652736,0.0007997002,0.00086848903,0.004946413],"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":[0.00027460116,0.00010563506,0.0071623037,0.00074687175,0.000040597515,0.0015514441,0.0040367125,0.0037477482,0.047391344,0.33158612,0.014580684,0.588776],"study_design_scores_gemma":[0.00002714327,0.000094675466,0.016959952,0.00022157632,0.00004609395,0.002259059,0.0012792774,0.0017867188,0.015443516,0.034750182,0.92705476,0.00007700401],"about_ca_topic_score_codex":0.0064135343,"about_ca_topic_score_gemma":0.007354068,"teacher_disagreement_score":0.0153441895,"about_ca_system_score_codex":0.0015248248,"about_ca_system_score_gemma":0.002322346,"threshold_uncertainty_score":0.05133146},"labels":[],"label_agreement":null},{"id":"W981603413","doi":"10.1007/s00521-015-1990-0","title":"Dynamic neural networks for gas turbine engine degradation prediction, health monitoring and prognosis","year":2015,"lang":"en","type":"article","venue":"Neural Computing and Applications","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":100,"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":"Artificial neural network; Computer science; Autoregressive model; Turbine; Gas turbines; Nonlinear autoregressive exogenous model; Artificial intelligence; Machine learning; Engineering; Mathematics","score_opus":0.013078606526969341,"score_gpt":0.25195310647120556,"score_spread":0.2388744999442362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W981603413","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13422003,0.00945257,0.84775424,0.000979203,0.00028421468,0.00005503771,0.00042556852,0.00088602793,0.0059431554],"genre_scores_gemma":[0.9588343,0.0014643386,0.03292102,0.00007812517,0.00009177695,0.000059679238,0.00026050792,0.0000263135,0.0062639415],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998536,0.000029406037,0.000014061832,0.000037364996,0.000045607423,0.00001990532],"domain_scores_gemma":[0.9995597,0.00023795012,0.00004890525,0.000025522198,0.00011736316,0.000010640504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050589256,0.00040384056,0.00045230208,0.00043914036,0.00019264162,0.00061787636,0.00059611,0.00066533574,0.0010245295],"category_scores_gemma":[0.0019854314,0.00023010268,0.00024509148,0.00052957964,0.00023242894,0.0006018818,0.00033422216,0.00061714475,0.00021649472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012843423,0.00007109655,0.0012884141,0.000069855065,0.00005277565,0.000044740074,0.000020130461,0.7999977,0.0033708825,0.0030412662,0.0012809894,0.19063361],"study_design_scores_gemma":[0.0000016177927,0.000007881,0.00024176939,0.0000025720635,0.000004185448,0.0000042268393,0.000002005262,0.99846196,0.00039147038,0.0007530315,0.00012689206,0.0000024862481],"about_ca_topic_score_codex":0.009013606,"about_ca_topic_score_gemma":0.0075869397,"teacher_disagreement_score":0.009013606,"about_ca_system_score_codex":0.0005915826,"about_ca_system_score_gemma":0.00037420815,"threshold_uncertainty_score":0.017922282},"labels":[],"label_agreement":null}]}