{"meta":{"query_hash":"8e34f391692d","filters":{"venue":"Computers in Industry"},"cohort_total":53,"direct_labels_cover":1,"predictions_cover":53,"exported":53,"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/8e34f391692d","api":"https://metacan.xera.ac/api/v1/cohort?venue=Computers+in+Industry"},"results":[{"id":"W1100957899","doi":"10.1016/j.compind.2015.07.002","title":"Challenges and current developments for Sensing, Smart and Sustainable Enterprise Systems","year":2015,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Collaboration in agile enterprises","field":"Business, Management and Accounting","cited_by":139,"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":"National Research Council Canada; European Commission; Université de Lorraine","keywords":"Enterprise integration; Enterprise systems engineering; Interoperability; Enterprise software; Enterprise modelling; Enterprise information system; Enterprise life cycle; Enterprise planning system; Computer science; Integrated enterprise modeling; Enterprise architecture; Enterprise system; Reference model; Enterprise application integration; Engineering management; Process management; Knowledge management; Systems engineering; Engineering; World Wide Web","score_opus":0.05704012675876444,"score_gpt":0.2724060342297912,"score_spread":0.21536590747102677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1100957899","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014865399,0.4746277,0.031832132,0.37957105,0.005152196,0.00008296992,0.00022702354,0.0002953773,0.09334613],"genre_scores_gemma":[0.3423541,0.55214155,0.048823405,0.02140155,0.009849668,0.0002878357,0.00048681698,0.000115887386,0.024539141],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961073,0.001199873,0.0002962984,0.00041865185,0.0012878727,0.00069004146],"domain_scores_gemma":[0.9813402,0.011746156,0.00081510184,0.00064781227,0.0033122108,0.0021384568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011805391,0.00059408427,0.00095536635,0.0013586306,0.0022095933,0.012460074,0.0027146228,0.00783365,0.019988827],"category_scores_gemma":[0.01003613,0.00046294215,0.00065642415,0.0023215439,0.005739121,0.01993209,0.003946775,0.0056355456,0.002608945],"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":[0.0002227487,0.00033590675,0.0019249057,0.003383688,0.000035254885,0.00027222306,0.0015933173,0.0035839418,0.0020602231,0.5552184,0.055005316,0.37636414],"study_design_scores_gemma":[0.000037955102,0.00032981436,0.0014883879,0.0032068738,0.00003720693,0.00046967922,0.011333516,0.011188505,0.0013056304,0.28499645,0.6854938,0.000112171474],"about_ca_topic_score_codex":0.0027117196,"about_ca_topic_score_gemma":0.0039577545,"teacher_disagreement_score":0.019988827,"about_ca_system_score_codex":0.0028086528,"about_ca_system_score_gemma":0.008209224,"threshold_uncertainty_score":0.06686932},"labels":[],"label_agreement":null},{"id":"W1968070149","doi":"10.1016/j.compind.2013.07.009","title":"Design of a feature-based order acceptance and scheduling module in an ERP system","year":2013,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Lister Institute of Preventive Medicine","keywords":"Computer science; Build to order; Scheduling (production processes); Systems engineering; Material requirements planning; Software engineering; Industrial engineering; Process management; Manufacturing engineering; Engineering; Production (economics); Operations management","score_opus":0.013351992121968895,"score_gpt":0.21941794679175441,"score_spread":0.20606595466978553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968070149","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08100975,0.000080038204,0.9138385,0.00011660248,0.000050829014,0.00024874837,0.00006510144,0.0021449546,0.0024454184],"genre_scores_gemma":[0.7249397,0.000050761002,0.27210775,0.000107165484,0.00003596283,0.00020750651,0.00007052927,0.00008271517,0.00239789],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968755,0.0000491453,0.000019789402,0.000107357526,0.00008836659,0.000047738078],"domain_scores_gemma":[0.9996356,0.00006891123,0.0000475058,0.000033305056,0.00018519236,0.000029469467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042118487,0.00038646258,0.0005403084,0.0003995767,0.00045916453,0.00070154434,0.0014793455,0.0006335558,0.002482605],"category_scores_gemma":[0.0005240406,0.0003917076,0.00036657052,0.00037560237,0.00019033908,0.0005111441,0.0003085089,0.00036173678,0.00060083956],"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":[0.00080166594,0.00059814996,0.0045582578,0.000378189,0.00017809439,0.00041564344,0.00025042723,0.22093748,0.37240168,0.008977597,0.003467217,0.38703555],"study_design_scores_gemma":[0.000069310365,0.00057207723,0.0025420089,0.000009607042,0.000086493645,0.0001456147,0.000032908625,0.9349823,0.057357155,0.0007432946,0.0034293698,0.000029890893],"about_ca_topic_score_codex":0.0026494635,"about_ca_topic_score_gemma":0.0022315735,"teacher_disagreement_score":0.0026494635,"about_ca_system_score_codex":0.0005333542,"about_ca_system_score_gemma":0.001076875,"threshold_uncertainty_score":0.008305073},"labels":[],"label_agreement":null},{"id":"W1971511464","doi":"10.1016/s0166-3615(01)00097-5","title":"CLOVER: an agent-based approach to systems interoperability in cooperative design systems","year":2001,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Interoperability; Key (lock); Systems engineering; Computer science; Multi-agent system; Focus (optics); Software engineering; Engineering management; Engineering; Process management; Computer security; World Wide Web; Artificial intelligence","score_opus":0.08971995263449721,"score_gpt":0.2888771465816943,"score_spread":0.19915719394719705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971511464","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013190212,0.000099716075,0.9918526,0.00023130243,0.000035868492,0.00013710007,0.000025822099,0.0023540705,0.0039445376],"genre_scores_gemma":[0.08682481,0.0003217298,0.90343434,0.0003481674,0.000049281207,0.00053978036,0.00021290974,0.00090104516,0.0073679457],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948738,0.0029471763,0.00023480003,0.00039102524,0.0012818845,0.00027126048],"domain_scores_gemma":[0.9953874,0.002615928,0.00025627355,0.0010869872,0.0003958314,0.00025759672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005405441,0.0012291453,0.001745649,0.0024322292,0.0026554477,0.007070233,0.0033386773,0.004063442,0.007746735],"category_scores_gemma":[0.011061754,0.0011927235,0.0014566871,0.002125396,0.0033587054,0.009312986,0.0075901216,0.0035948048,0.0018895647],"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":[0.00033392213,0.00031513424,0.0006647075,0.0005962424,0.00023302385,0.0007434055,0.0023532712,0.09966859,0.006278299,0.68077546,0.013085224,0.19495268],"study_design_scores_gemma":[0.00019285902,0.00012429726,0.0001385324,0.00016174668,0.00012317729,0.00027339548,0.00040421073,0.54838854,0.0073097437,0.36261213,0.08017914,0.00009220197],"about_ca_topic_score_codex":0.0039461264,"about_ca_topic_score_gemma":0.0049983794,"teacher_disagreement_score":0.007746735,"about_ca_system_score_codex":0.0011321364,"about_ca_system_score_gemma":0.0027615028,"threshold_uncertainty_score":0.028587043},"labels":[],"label_agreement":null},{"id":"W1979275066","doi":"10.1016/s0166-3615(03)00019-8","title":"Automated surface subdivision and tool path generation for -axis CNC machining of sculptured parts","year":2003,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University; University of Victoria","keywords":"Machining; Numerical control; Tool path; Cutter location; Engineering drawing; Machine tool; Surface (topology); Path (computing); Computer-aided manufacturing; Engineering; Mechanical engineering; Computer science; CAD; Geometry; Mathematics","score_opus":0.017667875428006748,"score_gpt":0.26090994189562455,"score_spread":0.2432420664676178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979275066","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08327597,0.0000921227,0.9102714,0.000060877832,0.000022570945,0.000091773785,0.0000976558,0.0026379465,0.0034496367],"genre_scores_gemma":[0.43348736,0.000055327135,0.5636503,0.000021931854,0.000006693227,0.00006606268,0.00033531483,0.00027366844,0.0021033175],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996673,0.000056256267,0.000015734315,0.000045669556,0.00017677537,0.00003828559],"domain_scores_gemma":[0.99948955,0.00020878343,0.000033539418,0.00010409332,0.00014778257,0.000016341426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037116,0.0004131599,0.00053199043,0.0005720017,0.00044713935,0.0004609797,0.0009107136,0.0005127168,0.0031010776],"category_scores_gemma":[0.0010528313,0.00034707604,0.00036957095,0.00052782666,0.00037626215,0.0004338829,0.0005986428,0.00052503456,0.00043872235],"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":[0.00041200995,0.0001257892,0.0022984224,0.0001426839,0.000025143714,0.00011135923,0.00049863075,0.17192958,0.08236032,0.008493652,0.0046676453,0.7289348],"study_design_scores_gemma":[0.00002127989,0.00004521899,0.0009612559,0.0000057226707,0.0000067055103,0.00005565729,0.000028131544,0.97996795,0.014794766,0.0019550268,0.0021496601,0.000008508145],"about_ca_topic_score_codex":0.0082544,"about_ca_topic_score_gemma":0.012960359,"teacher_disagreement_score":0.0082544,"about_ca_system_score_codex":0.00044378373,"about_ca_system_score_gemma":0.00088848406,"threshold_uncertainty_score":0.016412735},"labels":[],"label_agreement":null},{"id":"W1981667848","doi":"10.1016/j.compind.2004.07.005","title":"Integration of reverse logistics activities within a supply chain information system","year":2004,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":122,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Centre for Interdisciplinary Research in Rehabilitation","funders":"Natural Sciences and Engineering Research Council of Canada; Université Laval","keywords":"Integrated logistics support; Reverse logistics; Process management; Redistribution (election); Supply chain; Logistics center; Supply chain management; Information system; Humanitarian Logistics; Materials management; Engineering management; Business; Systems engineering; Knowledge management; Computer science; Operations management; Engineering; Operations research","score_opus":0.015573910112036427,"score_gpt":0.21112630309166527,"score_spread":0.19555239297962884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981667848","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41413382,0.00071266136,0.52732754,0.00096504396,0.00018395367,0.000840352,0.0009817133,0.022389531,0.03246545],"genre_scores_gemma":[0.80391556,0.00033671927,0.18497294,0.000188139,0.00007237747,0.00008938755,0.0020135297,0.0003657724,0.008045543],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985043,0.00041517217,0.00023454166,0.00023267648,0.00047137126,0.00014207448],"domain_scores_gemma":[0.9959733,0.0011286107,0.0002835597,0.0014208074,0.001019571,0.0001742149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018753926,0.0004299679,0.0004673655,0.0017637426,0.0005697148,0.0024692512,0.00063279696,0.00061622437,0.0023613945],"category_scores_gemma":[0.003834501,0.00040804408,0.00038285283,0.0015385975,0.00024620938,0.002149659,0.000831443,0.00055178005,0.0007836299],"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":[0.002034542,0.0014648973,0.033909954,0.00028154018,0.0001855993,0.0006348249,0.0013265576,0.036653515,0.06937915,0.008441576,0.0059119426,0.8397759],"study_design_scores_gemma":[0.00020693931,0.0009774547,0.023108833,0.00020704097,0.00073769136,0.0008050006,0.00047562976,0.61487454,0.25894502,0.0060607158,0.093364134,0.00023690729],"about_ca_topic_score_codex":0.0047096172,"about_ca_topic_score_gemma":0.005463854,"teacher_disagreement_score":0.0047096172,"about_ca_system_score_codex":0.0005805104,"about_ca_system_score_gemma":0.0014532731,"threshold_uncertainty_score":0.009918094},"labels":[],"label_agreement":null},{"id":"W1982958264","doi":"10.1016/j.compind.2013.08.003","title":"Maintaining consistency between CAD elements in collaborative design using association management and propagation","year":2013,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"CAD; Consistency (knowledge bases); Association (psychology); Engineering; Computer Aided Design; Computer science; Engineering drawing; Systems engineering; Mechanical engineering; Artificial intelligence; Psychology","score_opus":0.020537211526645918,"score_gpt":0.23213478414562455,"score_spread":0.21159757261897863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982958264","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019291226,0.00008342767,0.97929984,0.000048941427,0.000023473802,0.000039834813,0.00001532322,0.0005429011,0.0006549581],"genre_scores_gemma":[0.4327762,0.00013024351,0.56474006,0.000075819175,0.000041160925,0.00014565967,0.00019679412,0.0003223518,0.0015715987],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9864676,0.0043537333,0.0010759671,0.002333775,0.005198457,0.00057045906],"domain_scores_gemma":[0.94760233,0.026426747,0.0040892614,0.015318171,0.005812148,0.0007513424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012722019,0.0009914332,0.0016506158,0.0028365771,0.0019461641,0.003562027,0.004033955,0.0018709368,0.0016773264],"category_scores_gemma":[0.045143846,0.002281536,0.0012042479,0.0030622534,0.0021429362,0.0066716014,0.0062560844,0.0027677221,0.00067489763],"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":[0.0007470844,0.0007337021,0.011919673,0.00022092157,0.00022742411,0.00029258852,0.0016744616,0.37459087,0.019099573,0.044864208,0.0017423673,0.5438871],"study_design_scores_gemma":[0.00007159003,0.00019861574,0.0011046343,0.000037797963,0.00011938927,0.00012968881,0.00019878022,0.94905996,0.0140228905,0.032575265,0.0024357873,0.000045551933],"about_ca_topic_score_codex":0.0032222283,"about_ca_topic_score_gemma":0.0037898857,"teacher_disagreement_score":0.012722019,"about_ca_system_score_codex":0.00076705846,"about_ca_system_score_gemma":0.0022968506,"threshold_uncertainty_score":0.067281246},"labels":[],"label_agreement":null},{"id":"W1983103322","doi":"10.1016/j.compind.2013.02.012","title":"Optimal strategies for corrective assembly approach applied to a high-quality relay production system","year":2013,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Relay; Range (aeronautics); Production (economics); Selection (genetic algorithm); Reliability engineering; Machining; Production rate; Engineering; Quality (philosophy); Batch production; Process engineering; Computer science; Mechanical engineering","score_opus":0.018459967672350697,"score_gpt":0.23298542888792403,"score_spread":0.21452546121557334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983103322","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.062786974,0.0003008745,0.9276161,0.0002044463,0.00006018568,0.00012205916,0.000031282998,0.0002535198,0.008624566],"genre_scores_gemma":[0.94741666,0.00014949011,0.049221285,0.00003687989,0.00001956705,0.00011937719,0.000029167582,0.00004115458,0.0029664084],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996112,0.0001390228,0.000016365455,0.00006068327,0.000105854495,0.00006696558],"domain_scores_gemma":[0.9994405,0.0002440666,0.00008405447,0.000026861835,0.0001771409,0.000027371269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085332827,0.0012851543,0.0010690668,0.00077009795,0.00084652856,0.0013979818,0.0010297892,0.0016528639,0.002650449],"category_scores_gemma":[0.0013771672,0.0006033622,0.0007194757,0.0005339694,0.0005543829,0.0005272406,0.0006183403,0.0008058532,0.00026974882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008425264,0.000033867484,0.00015382086,0.000086326094,0.000023269968,0.00009944548,0.00006374424,0.9817863,0.004435408,0.0029279902,0.00029793312,0.010007721],"study_design_scores_gemma":[0.000011786577,0.000062515915,0.000088458444,0.0000046130185,0.0000142376375,0.000010379272,0.000011429205,0.99832743,0.0007234356,0.00052836444,0.00021286133,0.000004568385],"about_ca_topic_score_codex":0.010423841,"about_ca_topic_score_gemma":0.005764082,"teacher_disagreement_score":0.010423841,"about_ca_system_score_codex":0.00097436266,"about_ca_system_score_gemma":0.0011854504,"threshold_uncertainty_score":0.020726323},"labels":[],"label_agreement":null},{"id":"W1986073166","doi":"10.1016/j.compind.2008.03.003","title":"Optimizing customer's selection for configurable product in B2C e-commerce application","year":2008,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Product (mathematics); Wizard; The Internet; Software; Selection (genetic algorithm); E-commerce; Software engineering; World Wide Web","score_opus":0.02421663792490512,"score_gpt":0.2315221257878543,"score_spread":0.2073054878629492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986073166","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9806488,0.0001593185,0.009870439,0.000110544715,0.000013389305,0.00006106181,0.000112518595,0.00067296135,0.008350925],"genre_scores_gemma":[0.9902688,0.000042463576,0.0074142236,0.00003125766,0.0000061020055,0.00001102274,0.00013595627,0.00004467766,0.0020454936],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963725,0.00010049785,0.00002255334,0.000068061745,0.00010716258,0.00006456025],"domain_scores_gemma":[0.9992155,0.00032552468,0.00007545113,0.000059431553,0.00024923735,0.00007495562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033002056,0.00042438266,0.00039380885,0.00074964,0.00042966942,0.0010186669,0.0003789257,0.00043460168,0.004596413],"category_scores_gemma":[0.0014299796,0.00021739597,0.00022047263,0.0008098288,0.00008090936,0.0004961551,0.00020782482,0.00023625472,0.0007701515],"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":[0.006106929,0.0019622063,0.10244886,0.00019789854,0.00012458151,0.0013173441,0.00032609224,0.08544916,0.20106687,0.0012093257,0.011156027,0.5886347],"study_design_scores_gemma":[0.00011798867,0.0009623029,0.094608046,0.0000110947285,0.00015866818,0.0006126478,0.00037053457,0.81643623,0.083612405,0.00041422478,0.0026401433,0.00005578814],"about_ca_topic_score_codex":0.0055680685,"about_ca_topic_score_gemma":0.0073849456,"teacher_disagreement_score":0.0055680685,"about_ca_system_score_codex":0.00041723225,"about_ca_system_score_gemma":0.00044394788,"threshold_uncertainty_score":0.015376508},"labels":[],"label_agreement":null},{"id":"W1986863519","doi":"10.1016/j.compind.2008.07.002","title":"Collaborative design: New methodologies and technologies","year":2008,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Innovative Approaches in Technology and Social Development","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Systems engineering; Engineering; Computer science; Management science; Engineering management","score_opus":0.11034230823656542,"score_gpt":0.2856825924791058,"score_spread":0.1753402842425404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986863519","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005742113,0.03028299,0.88855654,0.007656804,0.0011267961,0.00036349858,0.000093083145,0.0007718443,0.06540632],"genre_scores_gemma":[0.1476615,0.023461776,0.80203664,0.0017333449,0.0012323475,0.0021654873,0.00019117165,0.000322157,0.021195615],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98098445,0.012566242,0.0007651846,0.0013966531,0.003913997,0.00037349423],"domain_scores_gemma":[0.9725658,0.021383125,0.0006365729,0.0031342139,0.0013857626,0.0008943901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013579851,0.0013651872,0.0014403894,0.0036636998,0.0022172343,0.014554026,0.0034242105,0.004107982,0.0110456105],"category_scores_gemma":[0.016842166,0.0010725842,0.0010956263,0.0038015805,0.013482113,0.013955552,0.0064572454,0.0030226447,0.0019274555],"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":[0.000036069025,0.00010204155,0.0005373616,0.0016000741,0.000068375346,0.00010326526,0.0054763514,0.0021579238,0.0009117813,0.80191636,0.008231722,0.17885873],"study_design_scores_gemma":[0.00006959802,0.000083984385,0.00034532975,0.00091654726,0.000052742766,0.00041531364,0.0022745114,0.0069454736,0.0011715788,0.7387647,0.24891439,0.000045784618],"about_ca_topic_score_codex":0.0011560736,"about_ca_topic_score_gemma":0.0013007591,"teacher_disagreement_score":0.014554026,"about_ca_system_score_codex":0.0031263253,"about_ca_system_score_gemma":0.0046062367,"threshold_uncertainty_score":0.071817935},"labels":[],"label_agreement":null},{"id":"W2011892838","doi":"10.1016/s0166-3615(03)00015-0","title":"A simplified and efficient representation for evaluation and selection of assembly sequences","year":2003,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":93,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Table (database); Representation (politics); Selection (genetic algorithm); Sequence (biology); Computer science; Assembly modelling; CAD; State (computer science); Theoretical computer science; Engineering drawing; Algorithm; Engineering; Artificial intelligence; Data mining; Mathematics","score_opus":0.02879957882095219,"score_gpt":0.287724839917682,"score_spread":0.2589252610967298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011892838","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0041260403,0.000081370155,0.9921943,0.00003939553,0.000022214175,0.000055461107,0.00033062953,0.0012231386,0.0019274435],"genre_scores_gemma":[0.109286144,0.00021404173,0.8824038,0.00007225661,0.000047392517,0.00028217208,0.00166496,0.00044989598,0.0055793435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988876,0.0002331348,0.00007933942,0.00012693211,0.0005646764,0.00010833477],"domain_scores_gemma":[0.99841285,0.0007097985,0.00011499826,0.00025081472,0.00046469527,0.000046838326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010248945,0.0012089367,0.0014043361,0.0017349875,0.0005176525,0.0023344706,0.0016447119,0.0012637819,0.0101692155],"category_scores_gemma":[0.0047646826,0.0005323369,0.00092948455,0.0019428162,0.00044181442,0.001373955,0.0008727184,0.0009803682,0.002872121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022251897,0.00011839461,0.0006541743,0.000208621,0.00003573573,0.00020484244,0.000078327226,0.6743736,0.008232299,0.032333046,0.007854896,0.27568343],"study_design_scores_gemma":[0.000015771036,0.00002243706,0.00009328542,0.000009682989,0.000011689331,0.000044129716,0.000007422712,0.98614883,0.0019203685,0.008839337,0.0028798,0.000007279428],"about_ca_topic_score_codex":0.0068823462,"about_ca_topic_score_gemma":0.007543349,"teacher_disagreement_score":0.0101692155,"about_ca_system_score_codex":0.0008333677,"about_ca_system_score_gemma":0.0016889555,"threshold_uncertainty_score":0.03401941},"labels":[],"label_agreement":null},{"id":"W2013303975","doi":"10.1016/s0166-3615(00)00087-7","title":"A multi-sensor approach to automating co-ordinate measuring machine-based reverse engineering","year":2001,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; Toronto Metropolitan University","funders":"","keywords":"Reverse engineering; Coordinate-measuring machine; Process (computing); Artificial intelligence; CAD; Computer science; Computer vision; Engineering drawing; Object (grammar); Structured light; Engineering; Mechanical engineering","score_opus":0.07989917297549166,"score_gpt":0.2821283821100538,"score_spread":0.20222920913456216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013303975","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042638383,0.00010472513,0.99331516,0.000054187763,0.000050779356,0.00004673866,0.000020714062,0.0009483201,0.0011956035],"genre_scores_gemma":[0.12949237,0.00011026537,0.8676672,0.00010237333,0.000024666328,0.00006873086,0.000045203553,0.00006200605,0.0024272199],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998376,0.00023004322,0.0000646247,0.00033822548,0.0009064219,0.00008463818],"domain_scores_gemma":[0.998982,0.00020791519,0.00009126036,0.00025879213,0.00041824474,0.00004176124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007966787,0.0009436224,0.0008386544,0.0011258428,0.0007742171,0.0012425575,0.0015266037,0.0013743261,0.0026555944],"category_scores_gemma":[0.0015274464,0.0006768539,0.00070653856,0.00085134775,0.0005992679,0.001652568,0.0011246047,0.0011272201,0.0010305685],"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":[0.00028075094,0.0003477908,0.0013978254,0.00020136959,0.00010394187,0.0002342527,0.00019038361,0.030689564,0.45579138,0.014177606,0.0022098098,0.49437532],"study_design_scores_gemma":[0.000027107868,0.00039315215,0.0013525764,0.000023114613,0.00006605723,0.0006271018,0.0000767353,0.68546796,0.29273492,0.005731465,0.01341509,0.0000847131],"about_ca_topic_score_codex":0.00181514,"about_ca_topic_score_gemma":0.004123379,"teacher_disagreement_score":0.0026555944,"about_ca_system_score_codex":0.0006379915,"about_ca_system_score_gemma":0.0009141506,"threshold_uncertainty_score":0.008883834},"labels":[],"label_agreement":null},{"id":"W2018966225","doi":"10.1016/j.compind.2010.04.002","title":"Corrigendum to “Supporting conflict management in collaborative design: An approach to assess engineering change impacts” [Comput. Ind. 59 (December(9)) (2008) 882–893, doi:10.1016/j.compind.2008.07.010]","year":2010,"lang":"en","type":"erratum","venue":"Computers in Industry","topic":"Construction Project Management and Performance","field":"Decision Sciences","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":"McGill University","funders":"","keywords":"Operations research; Engineering management; Computer science; Industrial engineering; Engineering","score_opus":0.20556995142108056,"score_gpt":0.3766268689250872,"score_spread":0.17105691750400662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018966225","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":[0.00020563054,0.0020826359,0.0015437212,0.07083488,0.90398926,0.00011298022,0.0014164948,0.0005931296,0.019221297],"genre_scores_gemma":[0.008073103,0.010363133,0.0048763244,0.088061854,0.17622684,0.000510153,0.004057565,0.0012392162,0.70659184],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.995518,0.0007874815,0.00066202896,0.0005310509,0.0021085707,0.00039275893],"domain_scores_gemma":[0.96556205,0.0074120434,0.00090013567,0.0014183525,0.023886465,0.0008209017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031718232,0.0029002193,0.002712238,0.0046650297,0.0049983794,0.0043941215,0.004448076,0.008857576,0.15706395],"category_scores_gemma":[0.04752325,0.001370097,0.002347467,0.003964712,0.0025215358,0.0032431907,0.0031091857,0.007299961,0.09323599],"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":[0.00001482604,0.0000097980765,0.0000459152,0.00007488388,0.0000055838623,0.00009285542,0.000018728166,0.000058180744,0.000032334476,0.00047383708,0.9953939,0.0037792071],"study_design_scores_gemma":[0.00003130119,0.000039085586,0.0015833165,0.00028041238,0.000033862936,0.00021213156,0.00016910877,0.00045139084,0.00032119098,0.0017444292,0.9950708,0.00006284558],"about_ca_topic_score_codex":0.063236676,"about_ca_topic_score_gemma":0.08544947,"teacher_disagreement_score":0.15706395,"about_ca_system_score_codex":0.0062665134,"about_ca_system_score_gemma":0.0035692626,"threshold_uncertainty_score":0.5254313},"labels":[],"label_agreement":null},{"id":"W2029372867","doi":"10.1016/j.compind.2009.05.005","title":"Study of the performance of multi-behaviour agents for supply chain planning","year":2009,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Université Laval; Université du Québec à Rimouski","funders":"Natural Sciences and Engineering Research Council of Canada; Université Laval","keywords":"Supply chain; Computer science; Engineering; Business; Manufacturing engineering; Operations management; Marketing","score_opus":0.19233177657411832,"score_gpt":0.42216528827467864,"score_spread":0.22983351170056032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029372867","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94097376,0.00041907263,0.053680513,0.00047230115,0.000042417127,0.000057254467,0.00004623622,0.00008118262,0.004227262],"genre_scores_gemma":[0.994348,0.00006690337,0.004859446,0.000012332016,0.000007806419,0.000012801236,0.00002083648,0.000010531868,0.00066138903],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894804,0.0006136204,0.00004308008,0.0000910251,0.00015151653,0.00015273155],"domain_scores_gemma":[0.9773167,0.01928467,0.0008169177,0.0006679937,0.0012037115,0.0007099792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042409166,0.0006219231,0.0008583586,0.00065554044,0.0005823805,0.001141346,0.0008459698,0.0011356117,0.0018642809],"category_scores_gemma":[0.021952963,0.000298929,0.00033898363,0.00058648136,0.00084180414,0.0013143609,0.00065964414,0.0011053776,0.00014726163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004477303,0.0001538191,0.0017179413,0.000048604812,0.00005987943,0.000039817154,0.000074368654,0.9790132,0.0014736691,0.008169677,0.00029737112,0.008503931],"study_design_scores_gemma":[0.00001542284,0.00009185588,0.00026219987,0.0000023521159,0.0000077729865,0.000006760253,0.000020638452,0.99773127,0.00038240597,0.0014356213,0.000040646555,0.000003162897],"about_ca_topic_score_codex":0.006998634,"about_ca_topic_score_gemma":0.0024025606,"teacher_disagreement_score":0.006998634,"about_ca_system_score_codex":0.0015065387,"about_ca_system_score_gemma":0.0012393969,"threshold_uncertainty_score":0.022428393},"labels":[],"label_agreement":null},{"id":"W2034431671","doi":"10.1016/j.compind.2009.10.005","title":"Parametric design with neural network relationships and fuzzy relationships considering uncertainties","year":2009,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Process Optimization and Integration","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Western Economic Diversification Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Parametric statistics; Fuzzy logic; Artificial neural network; Reliability (semiconductor); Mathematical optimization; Optimal design; Computer science; Engineering; Artificial intelligence; Machine learning; Mathematics; Statistics","score_opus":0.05607639612834352,"score_gpt":0.22948595567694116,"score_spread":0.17340955954859766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034431671","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0076195723,0.00018679297,0.989449,0.000077943194,0.000022005488,0.000023328032,0.000008711639,0.000032391657,0.002580242],"genre_scores_gemma":[0.79177177,0.000683711,0.20181409,0.00008947117,0.00009119825,0.0002838492,0.00004655735,0.000056456967,0.00516297],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991449,0.00036325882,0.000041681542,0.00016003895,0.00024387507,0.000046139376],"domain_scores_gemma":[0.9991535,0.00052815553,0.00012202496,0.000045380708,0.00013157116,0.000019380223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018127054,0.0008733498,0.0009730323,0.00060646085,0.0004144036,0.0011140094,0.0011397304,0.0017638139,0.0020766824],"category_scores_gemma":[0.0046814135,0.00084575015,0.00073833286,0.00085112883,0.00070384226,0.0019173595,0.001110924,0.00088443735,0.000253473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030712363,0.000020448582,0.000051734398,0.00005155812,0.000015123548,0.000020734444,0.000024486542,0.97200376,0.0012318356,0.008965839,0.00008709743,0.017496683],"study_design_scores_gemma":[0.000004809571,0.000031151594,0.000029099156,0.000004532709,0.000006627581,0.0000055223204,0.0000030487583,0.995001,0.00034850306,0.0042848443,0.0002767238,0.0000039704305],"about_ca_topic_score_codex":0.0011565324,"about_ca_topic_score_gemma":0.0010999443,"teacher_disagreement_score":0.0020766824,"about_ca_system_score_codex":0.0005563073,"about_ca_system_score_gemma":0.00069389003,"threshold_uncertainty_score":0.009586632},"labels":[],"label_agreement":null},{"id":"W2036016299","doi":"10.1016/j.compind.2009.10.004","title":"Managing the full ERP life-cycle: Considerations of maintenance and support requirements and IT governance practice as integral elements of the formula for successful ERP adoption","year":2009,"lang":"en","type":"article","venue":"Computers in Industry","topic":"ERP Systems Implementation and Impact","field":"Business, Management and Accounting","cited_by":131,"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 of Edmonton","funders":"","keywords":"Enterprise resource planning; Process management; Implementation; Order (exchange); Critical success factor; Business; Manufacturing resource planning; Resource (disambiguation); Knowledge management; Computer science; Operations management; Engineering; Software engineering","score_opus":0.03422876537115586,"score_gpt":0.31423806386109093,"score_spread":0.28000929848993505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036016299","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3697348,0.0048367954,0.36296058,0.092440456,0.00036522566,0.00046043468,0.00014354195,0.00042143726,0.16863674],"genre_scores_gemma":[0.9397903,0.00069427246,0.05489247,0.00093946356,0.00011136107,0.00013995382,0.00003512131,0.00006114211,0.0033358706],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.996858,0.00120935,0.00018504042,0.00015449798,0.001192205,0.0004009399],"domain_scores_gemma":[0.98207456,0.0101516,0.0022263003,0.001128054,0.0032173672,0.0012021209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070153517,0.00040120538,0.00036285134,0.0011332164,0.0017192297,0.008217843,0.0018601727,0.0026382152,0.0024205926],"category_scores_gemma":[0.025540736,0.0006209094,0.0003288337,0.00096460414,0.0030826866,0.011204615,0.002074791,0.0026219634,0.00040923848],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011170593,0.00041801293,0.013928398,0.00038607168,0.000054309767,0.0010907816,0.0052255928,0.032918878,0.008138018,0.6850246,0.010661322,0.24204233],"study_design_scores_gemma":[0.000059966376,0.00051860954,0.034014747,0.0006653933,0.00008793077,0.001853812,0.0115090925,0.10137515,0.005237698,0.77543604,0.06907982,0.00016185919],"about_ca_topic_score_codex":0.003450615,"about_ca_topic_score_gemma":0.0071527376,"teacher_disagreement_score":0.008217843,"about_ca_system_score_codex":0.0021160678,"about_ca_system_score_gemma":0.006489422,"threshold_uncertainty_score":0.03710115},"labels":[],"label_agreement":null},{"id":"W2037119974","doi":"10.1016/s0166-3615(01)00133-6","title":"Schema-based conversation modeling for agent-oriented manufacturing systems","year":2001,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Athabasca University","funders":"","keywords":"Conversation; Computer science; Thread (computing); Schema (genetic algorithms); Java; Petri net; Negotiation; Distributed computing; Programming language; Software engineering; Human–computer interaction; Artificial intelligence; Information retrieval","score_opus":0.05471654747391824,"score_gpt":0.27331267386495445,"score_spread":0.2185961263910362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037119974","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011656595,0.0001876423,0.9815787,0.0005790714,0.000055730856,0.00023259534,0.00044107303,0.001222274,0.0040463503],"genre_scores_gemma":[0.45687777,0.0005426823,0.53601205,0.00025471277,0.0000556628,0.0007081872,0.0016318345,0.00035946525,0.0035576287],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958054,0.002742356,0.00032790774,0.00035626057,0.00055897736,0.00020912613],"domain_scores_gemma":[0.9934036,0.004862272,0.00024195445,0.0006272584,0.0006858799,0.0001790247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004882002,0.000622369,0.0008242091,0.0010896258,0.0012915443,0.003933019,0.0026995596,0.0021062281,0.005162441],"category_scores_gemma":[0.0128582325,0.0009916187,0.0018912706,0.0011542845,0.0011263867,0.0049460772,0.0020767832,0.0020221504,0.0010532341],"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":[0.00033752568,0.00021266782,0.0018659104,0.00035249238,0.00020557307,0.00048408002,0.003739885,0.43575424,0.0031005417,0.49786475,0.0049505616,0.051131763],"study_design_scores_gemma":[0.000027010732,0.000016498248,0.000062456544,0.000024409681,0.000049698963,0.000052165888,0.00018312309,0.93124723,0.0011815447,0.0616342,0.005503509,0.000018140998],"about_ca_topic_score_codex":0.015066952,"about_ca_topic_score_gemma":0.011480221,"teacher_disagreement_score":0.015066952,"about_ca_system_score_codex":0.0015519068,"about_ca_system_score_gemma":0.0022119335,"threshold_uncertainty_score":0.029958487},"labels":[],"label_agreement":null},{"id":"W2041673980","doi":"10.1016/j.compind.2009.05.008","title":"ADVICE: A virtual environment for Engineering Change Management","year":2009,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":72,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Process (computing); Computer science; Configuration Management (ITSM); Advice (programming); Prioritization; Change management (ITSM); Human–computer interaction; Engineering design process; Software engineering; Systems engineering; Engineering; Process management; Manufacturing engineering","score_opus":0.0170449251165793,"score_gpt":0.20023579486816748,"score_spread":0.1831908697515882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041673980","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05715145,0.0014018026,0.39674568,0.0055450588,0.0020674488,0.0012122777,0.019144671,0.31006205,0.20666958],"genre_scores_gemma":[0.26946703,0.0020272555,0.4552766,0.0023729457,0.0007835659,0.0023507648,0.021261983,0.024197675,0.22226222],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958783,0.00015268574,0.000021179874,0.000047124595,0.00014681081,0.000044305445],"domain_scores_gemma":[0.99755377,0.0012243001,0.00007894535,0.0004170796,0.0002039186,0.0005220097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00106768,0.00080769206,0.00034725972,0.0008991727,0.0006786547,0.0018259907,0.0016420378,0.0010574325,0.08103633],"category_scores_gemma":[0.0043407865,0.00045251637,0.00037150353,0.0006078282,0.0003692452,0.0026307679,0.0031293523,0.0010767838,0.013423159],"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":[0.00080650515,0.0004828935,0.0016807136,0.0005104785,0.000046738518,0.0005004754,0.001640182,0.0048363893,0.0076053287,0.010622847,0.5911178,0.3801496],"study_design_scores_gemma":[0.00088468834,0.00043934863,0.003609213,0.00018150685,0.00008572354,0.0003838424,0.00055006007,0.025490342,0.00374221,0.019759513,0.94473964,0.00013389374],"about_ca_topic_score_codex":0.0015703337,"about_ca_topic_score_gemma":0.003994805,"teacher_disagreement_score":0.08103633,"about_ca_system_score_codex":0.00031180945,"about_ca_system_score_gemma":0.00081746536,"threshold_uncertainty_score":0.27109355},"labels":[],"label_agreement":null},{"id":"W2050920716","doi":"10.1016/s0166-3615(01)00101-4","title":"An architecture for metamorphic control of holonic manufacturing systems","year":2001,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Flexible and Reconfigurable Manufacturing Systems","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Distributed control system; Control system; Industrial control system; Engineering; Process control; Software; Embedded system; Software architecture; Block (permutation group theory); Control engineering; Process (computing); Computer science; Systems engineering; Operating system","score_opus":0.014921812164643077,"score_gpt":0.22594291582864343,"score_spread":0.21102110366400034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050920716","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07403341,0.00036733592,0.8977539,0.0002984626,0.00015724274,0.00009401588,0.00008655427,0.006113624,0.021095416],"genre_scores_gemma":[0.80808264,0.0003193737,0.18107562,0.00017714595,0.00004757989,0.00009531259,0.00016808092,0.00015100252,0.00988325],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99987376,0.000018555127,0.000011922852,0.000028225493,0.000038772207,0.000028764134],"domain_scores_gemma":[0.99985814,0.00001985835,0.000014318117,0.000050746305,0.000037435897,0.000019513815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020391693,0.0002519721,0.00021257336,0.0003249581,0.0004424719,0.0009381298,0.00080204953,0.00042226125,0.0030094576],"category_scores_gemma":[0.00025530127,0.0002198561,0.00024650863,0.00021967651,0.00040137809,0.00079697254,0.0007907569,0.0006285021,0.0005684567],"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":[0.0006903111,0.00023174979,0.00129204,0.00032050197,0.000084953645,0.00068124535,0.0007300469,0.106840976,0.24195316,0.2748801,0.007872432,0.36442244],"study_design_scores_gemma":[0.00013495127,0.00048765138,0.0011335207,0.000086597436,0.00010832094,0.00052881683,0.000096702744,0.756076,0.1102253,0.075767055,0.055286437,0.000068572765],"about_ca_topic_score_codex":0.0010598368,"about_ca_topic_score_gemma":0.0020870732,"teacher_disagreement_score":0.0030094576,"about_ca_system_score_codex":0.00036945843,"about_ca_system_score_gemma":0.00038847604,"threshold_uncertainty_score":0.010067701},"labels":[],"label_agreement":null},{"id":"W2070988975","doi":"10.1016/s0166-3615(99)00078-0","title":"A strategic framework for networked manufacturing","year":2000,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":134,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Agile software development; Interdependence; Agile manufacturing; Plan (archaeology); Process management; Computer-integrated manufacturing; Integrated Computer-Aided Manufacturing; Computer science; Manufacturing engineering; Engineering; Systems engineering; Software engineering","score_opus":0.03083284829018391,"score_gpt":0.23672005933697682,"score_spread":0.20588721104679292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070988975","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":[0.013341252,0.0013699845,0.33713692,0.01900899,0.00044527557,0.0002821496,0.000105415915,0.00019967393,0.6281103],"genre_scores_gemma":[0.747255,0.0016477781,0.19146203,0.0016815007,0.0002703864,0.0006967244,0.00015231676,0.00009354539,0.056740645],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99747187,0.0011854332,0.00011155928,0.00025323633,0.0005362889,0.00044160607],"domain_scores_gemma":[0.9989887,0.00031331478,0.00009647236,0.00009376702,0.00022151547,0.00028628611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028883945,0.0010586814,0.00043645923,0.0023001188,0.0056235655,0.015518531,0.0025470983,0.0060518347,0.010576904],"category_scores_gemma":[0.0025990906,0.0006425502,0.00079641305,0.0027687922,0.010550106,0.012561743,0.005797591,0.0036003257,0.0018177469],"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":[0.0000011192643,0.0000037376403,0.000024866147,0.000004679962,6.661765e-7,0.00003239961,0.00017852802,0.00088807277,0.000028663948,0.99698144,0.0005092031,0.0013465667],"study_design_scores_gemma":[0.0000087351455,0.000016687361,0.000083310304,0.00007388222,0.000003922046,0.00007696938,0.0016047014,0.00580239,0.00012516869,0.92915714,0.063033015,0.000014036282],"about_ca_topic_score_codex":0.017702976,"about_ca_topic_score_gemma":0.02574149,"teacher_disagreement_score":0.017702976,"about_ca_system_score_codex":0.009963522,"about_ca_system_score_gemma":0.01284961,"threshold_uncertainty_score":0.07229078},"labels":[],"label_agreement":null},{"id":"W2078151974","doi":"10.1016/j.compind.2009.02.006","title":"Distributed search for supply chain coordination","year":2009,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Université Laval","funders":"","keywords":"Heuristics; Supply chain; Computer science; Tree (set theory); Mathematical optimization; Quality (philosophy); Process (computing); Computation; Search tree; Key (lock); Industrial engineering; Search algorithm; Engineering; Algorithm; Mathematics","score_opus":0.03105888814480912,"score_gpt":0.2569298925371706,"score_spread":0.22587100439236146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078151974","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14148296,0.0013060461,0.836238,0.0014661023,0.00019396681,0.00019886169,0.00031412512,0.0013379334,0.017461905],"genre_scores_gemma":[0.8961687,0.0003134867,0.093516216,0.00011572136,0.00009833976,0.00014074286,0.00024429202,0.0001254244,0.00927707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857104,0.0005476595,0.000075071905,0.00033432292,0.00025948673,0.00021232422],"domain_scores_gemma":[0.99184036,0.0061012716,0.00027046973,0.0010045865,0.0005021813,0.00028114105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020843013,0.0006949161,0.0025149982,0.0018698535,0.0020734328,0.002415921,0.0019336417,0.002382915,0.010516946],"category_scores_gemma":[0.014567293,0.00091936317,0.0007859834,0.0036567613,0.0018548295,0.005656662,0.0030596997,0.0015341947,0.0008193646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016012909,0.00034859672,0.0016010281,0.00024994617,0.00011568548,0.00015866497,0.0004023779,0.73108613,0.002001228,0.1349055,0.008209135,0.11932041],"study_design_scores_gemma":[0.00012618038,0.000030785977,0.00014754881,0.000008049023,0.000019173785,0.000022955108,0.0000575935,0.91012454,0.00038598385,0.08830054,0.00076894456,0.000007727061],"about_ca_topic_score_codex":0.007818899,"about_ca_topic_score_gemma":0.0063130995,"teacher_disagreement_score":0.010516946,"about_ca_system_score_codex":0.0020941494,"about_ca_system_score_gemma":0.0026832256,"threshold_uncertainty_score":0.035182655},"labels":[],"label_agreement":null},{"id":"W2078174931","doi":"10.1016/j.compind.2012.08.017","title":"Evaluating alternative approaches to mobile object localization in wireless sensor networks with passive architecture","year":2012,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Trilateration; Wireless sensor network; Real-time computing; Computer science; Kalman filter; Key distribution in wireless sensor networks; Mobile wireless sensor network; Wireless; Wireless network; Node (physics); Computer network; Engineering; Artificial intelligence; Telecommunications","score_opus":0.05490122736423183,"score_gpt":0.2632087997271447,"score_spread":0.2083075723629129,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078174931","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.701763,0.0038466707,0.2846805,0.0006186448,0.00019081295,0.00046064644,0.00019664278,0.00032188205,0.007921236],"genre_scores_gemma":[0.928857,0.0009269113,0.06862728,0.000059595954,0.000058357942,0.0001664938,0.00013751932,0.00003749011,0.0011294058],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99225134,0.004897889,0.00032595595,0.00043191251,0.0017446592,0.0003481593],"domain_scores_gemma":[0.9739058,0.021759422,0.000782909,0.0010297585,0.0023000047,0.00022209292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069835223,0.0014719323,0.0009798206,0.002731032,0.00075203343,0.0018318467,0.002066295,0.0018418088,0.0014815313],"category_scores_gemma":[0.020795172,0.00047045742,0.001168192,0.0020213549,0.0015450898,0.0037221047,0.0015724817,0.0006623009,0.00018271733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030012075,0.0005805859,0.0054348344,0.0006881638,0.00040944974,0.00007677245,0.00013296804,0.8690869,0.004474388,0.0073267133,0.0002646752,0.108523265],"study_design_scores_gemma":[0.00019227393,0.0025706398,0.0020661806,0.000033500073,0.00029402692,0.00006514218,0.00021906605,0.98767287,0.002634742,0.0038169213,0.00040033108,0.00003427704],"about_ca_topic_score_codex":0.006858943,"about_ca_topic_score_gemma":0.010239734,"teacher_disagreement_score":0.0069835223,"about_ca_system_score_codex":0.0038240221,"about_ca_system_score_gemma":0.001375971,"threshold_uncertainty_score":0.036932826},"labels":[],"label_agreement":null},{"id":"W2088486464","doi":"10.1016/s0166-3615(01)00100-2","title":"A fuzzy mathematics based optimal delivery scheduling approach","year":2001,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"University of Tokyo; Tianjin University","keywords":"Smalltalk; Scheduling (production processes); Computer science; Cluster analysis; Fuzzy logic; Job shop scheduling; Mathematical optimization; Object-oriented programming; Mathematics; Artificial intelligence; Programming language; Operating system; Schedule","score_opus":0.021583752455602487,"score_gpt":0.22347558087933211,"score_spread":0.20189182842372963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088486464","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":[0.005317903,0.0002593367,0.9885024,0.00019340705,0.00009389104,0.00003887456,0.000026628632,0.00007163271,0.005495988],"genre_scores_gemma":[0.45308593,0.0009872764,0.5324655,0.00015252052,0.00021948862,0.0001946389,0.00009911201,0.000070764036,0.012724754],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996063,0.00008318516,0.000018974717,0.000054928314,0.00020027455,0.0000363444],"domain_scores_gemma":[0.99968886,0.00015778012,0.0000289985,0.000018710274,0.00008903193,0.000016654263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060656085,0.00058766594,0.0010496946,0.0012814709,0.0007205018,0.0011935488,0.0013543249,0.0009045368,0.0038562939],"category_scores_gemma":[0.0011849378,0.00042235386,0.0009962693,0.0010568339,0.00051607203,0.0011174616,0.00063505385,0.00081439735,0.00050338835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051678275,0.00007795875,0.00015368954,0.000080508944,0.000043192405,0.00006132711,0.000047483925,0.85355663,0.0031286897,0.07933421,0.0012696402,0.06219502],"study_design_scores_gemma":[0.0000068205823,0.000019567768,0.000042283107,0.0000041554367,0.000008427758,0.000012244086,0.0000065756553,0.9868571,0.00035259992,0.011615846,0.0010691966,0.000005082741],"about_ca_topic_score_codex":0.0068918564,"about_ca_topic_score_gemma":0.0048431475,"teacher_disagreement_score":0.0068918564,"about_ca_system_score_codex":0.0016143795,"about_ca_system_score_gemma":0.0013810291,"threshold_uncertainty_score":0.013703465},"labels":[],"label_agreement":null},{"id":"W2103983035","doi":"10.1016/j.compind.2010.01.005","title":"Will Model-based Definition replace engineering drawings throughout the product lifecycle? A global perspective from aerospace industry","year":2010,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":188,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Product lifecycle; Aerospace; Certification; Manufacturing engineering; Product (mathematics); Engineering; Quality (philosophy); Systems engineering; Product management; Computer science; New product development","score_opus":0.012184625808006501,"score_gpt":0.23872069611286373,"score_spread":0.22653607030485723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103983035","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019137627,0.0063600377,0.8919138,0.035135217,0.00087329675,0.00005203751,0.0001244929,0.00044295922,0.045960497],"genre_scores_gemma":[0.51126057,0.010146089,0.4601761,0.004842814,0.00074088306,0.00020470594,0.00040987972,0.000846052,0.011372883],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9915998,0.004792633,0.00050227414,0.000754348,0.0019079973,0.0004429211],"domain_scores_gemma":[0.9807093,0.008796803,0.0013855061,0.004816618,0.0038875772,0.00040413358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014681316,0.0013614006,0.0016237932,0.0024982376,0.0014203895,0.010028846,0.0042880247,0.00497502,0.0035698393],"category_scores_gemma":[0.020148495,0.0010405381,0.001771307,0.0040886677,0.009689053,0.028474472,0.003455666,0.0052750898,0.0011230027],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045134475,0.00004558531,0.00068448664,0.00020871722,0.000020429557,0.000101731806,0.00096983823,0.017040048,0.00053938257,0.9226579,0.003154188,0.054532643],"study_design_scores_gemma":[0.000038129165,0.000113085516,0.00088218664,0.000530407,0.00008049351,0.00037052395,0.0015039674,0.05634846,0.002208209,0.81841004,0.11943578,0.00007865289],"about_ca_topic_score_codex":0.0071191904,"about_ca_topic_score_gemma":0.004713014,"teacher_disagreement_score":0.014681316,"about_ca_system_score_codex":0.00428763,"about_ca_system_score_gemma":0.0031980264,"threshold_uncertainty_score":0.0776431},"labels":[],"label_agreement":null},{"id":"W2113099002","doi":"10.1016/j.compind.2012.03.007","title":"Product decomposition using design structure matrix for intellectual property protection in supply chain outsourcing","year":2012,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Outsourcing; Intellectual property; Supply chain; Risk analysis (engineering); Profitability index; Leakage (economics); Information leakage; Business; New product development; Product design; Product (mathematics); Computer science; Computer security; Economics; Marketing; Finance","score_opus":0.04685903697161294,"score_gpt":0.26207972318737316,"score_spread":0.2152206862157602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113099002","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":[0.020621622,0.00007964963,0.9766272,0.0000671662,0.000017925056,0.000066862245,0.0001028608,0.0002271956,0.0021894954],"genre_scores_gemma":[0.4143017,0.00015558118,0.58167064,0.000040893327,0.000019758547,0.00021270658,0.0003960829,0.00011758138,0.0030850247],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991487,0.00041437612,0.000028750952,0.00010498825,0.00021622934,0.00008700271],"domain_scores_gemma":[0.9984528,0.0008082913,0.00010536482,0.0001624878,0.00043525812,0.000035788078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013195876,0.0007783062,0.0005760989,0.0008481701,0.00045224532,0.0006664898,0.00037525344,0.0004940597,0.0066823824],"category_scores_gemma":[0.0035389673,0.00036320585,0.00096612715,0.0008576457,0.00031852568,0.00064294215,0.00043979156,0.00069437234,0.0006592325],"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":[0.00029440885,0.00027336605,0.002060485,0.00032060174,0.000117201824,0.00017893757,0.00020197136,0.6101903,0.014295896,0.037085745,0.004047711,0.33093342],"study_design_scores_gemma":[0.000017940407,0.0000978478,0.00052637164,0.000012643579,0.000027023483,0.00002186914,0.000036039408,0.98829913,0.0021438617,0.00767294,0.0011352368,0.000009197698],"about_ca_topic_score_codex":0.005174646,"about_ca_topic_score_gemma":0.005921984,"teacher_disagreement_score":0.0066823824,"about_ca_system_score_codex":0.0005599171,"about_ca_system_score_gemma":0.0016275065,"threshold_uncertainty_score":0.022354841},"labels":[],"label_agreement":null},{"id":"W2114174259","doi":"10.1016/j.compind.2005.05.003","title":"Integrating cross-sectional imaging based reverse engineering with rapid prototyping","year":2005,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Delaunay triangulation; Rapid prototyping; Artificial intelligence; Computer vision; Preprocessor; Reverse engineering; Stereolithography; Triangulation; Computer graphics (images); Cross section (physics); Engineering; Algorithm; Mathematics; Geometry","score_opus":0.00999479768574686,"score_gpt":0.21986924726221213,"score_spread":0.20987444957646528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114174259","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":[0.014904901,0.00026327156,0.979412,0.00008702185,0.00009216108,0.00009033536,0.000024257497,0.0016286693,0.0034973766],"genre_scores_gemma":[0.11692471,0.00030848914,0.8798736,0.000056882946,0.000027954253,0.00007492941,0.000057950347,0.00033367495,0.0023419664],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99854714,0.0002384952,0.00009093417,0.00016163128,0.0008532407,0.0001084567],"domain_scores_gemma":[0.99447834,0.0025454063,0.00046044102,0.0015119779,0.0009033074,0.000100486875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00202342,0.001348316,0.00079197553,0.0011078761,0.00032220266,0.0015722368,0.0014950146,0.0011455134,0.0037593117],"category_scores_gemma":[0.0038221302,0.0014375356,0.0007148495,0.00051251356,0.0008056425,0.0019357825,0.001443894,0.0011133787,0.0011996272],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018461951,0.00016047427,0.00095215376,0.00044858412,0.000064574895,0.0004805492,0.00025340338,0.023551608,0.7804471,0.013372951,0.0011453462,0.17893858],"study_design_scores_gemma":[0.000051898234,0.00067615253,0.0012718053,0.00006294245,0.00007391043,0.0032897482,0.00008981264,0.14850903,0.82220626,0.004376493,0.019247118,0.0001448905],"about_ca_topic_score_codex":0.0003619791,"about_ca_topic_score_gemma":0.0006079195,"teacher_disagreement_score":0.0037593117,"about_ca_system_score_codex":0.000339943,"about_ca_system_score_gemma":0.00053784717,"threshold_uncertainty_score":0.012576222},"labels":[],"label_agreement":null},{"id":"W2120058199","doi":"10.1016/j.compind.2007.06.012","title":"Collaborative process planning and manufacturing in product lifecycle management","year":2007,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":124,"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":"Singapore Institute of Manufacturing Technology; National Science Foundation","keywords":"Product lifecycle; Product management; Application lifecycle management; Process management; New product development; Product design specification; Product (mathematics); System lifecycle; Product cost management; Business; Product engineering; Innovation management; Product design; Manufacturing engineering; Knowledge management; Engineering; Computer science; Marketing","score_opus":0.007943637006094436,"score_gpt":0.24130143707743837,"score_spread":0.23335780007134393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120058199","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013343213,0.010738796,0.95323193,0.0014473689,0.00030652984,0.000062117244,0.00003710343,0.00014637707,0.020686515],"genre_scores_gemma":[0.62701744,0.010719169,0.34844092,0.00031133424,0.0005595752,0.00026629245,0.00017008651,0.00010733392,0.012407884],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99533856,0.002534087,0.0002248581,0.00058992184,0.0010704697,0.00024201594],"domain_scores_gemma":[0.98887295,0.009078275,0.0005861599,0.0008328418,0.0004690422,0.00016078504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004180062,0.0008988912,0.0014233685,0.0017210812,0.0016374611,0.0050515216,0.002200333,0.003420462,0.0051796585],"category_scores_gemma":[0.014265335,0.00083591667,0.001119247,0.004639293,0.004354635,0.0077086864,0.0021151346,0.0017573837,0.000707006],"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":[0.00013226742,0.0001384094,0.0010138351,0.0003222719,0.000070432114,0.00021270846,0.0006158743,0.15160644,0.00062254304,0.7024611,0.0027909796,0.1400131],"study_design_scores_gemma":[0.000041305695,0.00009456564,0.000719494,0.00011676006,0.00007110658,0.00018519434,0.00028828226,0.3364196,0.0016692433,0.64230084,0.018047627,0.00004590443],"about_ca_topic_score_codex":0.0060332934,"about_ca_topic_score_gemma":0.0044648647,"teacher_disagreement_score":0.0060332934,"about_ca_system_score_codex":0.0018027149,"about_ca_system_score_gemma":0.0022870568,"threshold_uncertainty_score":0.022106528},"labels":[],"label_agreement":null},{"id":"W2131822530","doi":"10.1016/j.compind.2010.05.004","title":"A semantic approach to a framework for business domain software systems","year":2010,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"University of Toronto; Yale University","keywords":"Semantics of Business Vocabulary and Business Rules; Computer science; Business rule; Business logic; Business domain; Software engineering; Business information; Ontology; Business process modeling; Domain (mathematical analysis); Information extraction; Artifact-centric business process model; Business process; Knowledge management; Programming language; Information retrieval; Engineering","score_opus":0.028148894930556456,"score_gpt":0.26972225651512755,"score_spread":0.2415733615845711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131822530","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031499513,0.0006780543,0.97622377,0.00365441,0.00020849233,0.00017660276,0.00025641304,0.00070421014,0.014948177],"genre_scores_gemma":[0.083048515,0.0009055021,0.9073076,0.0007025328,0.00025311764,0.00040580414,0.0007692156,0.00031045926,0.006297151],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971437,0.0010613995,0.00047282534,0.0003779179,0.0006789498,0.0002650853],"domain_scores_gemma":[0.997825,0.00072749617,0.00014779644,0.00057055725,0.00048300732,0.00024604413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045899167,0.0011137982,0.001112779,0.004507049,0.0039576585,0.008417593,0.0035095469,0.0036532294,0.0044306326],"category_scores_gemma":[0.0053383466,0.0013537168,0.0038167979,0.004247924,0.009009902,0.016091123,0.0044392957,0.0052550435,0.0013321165],"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":[0.000005008756,0.000012547096,0.000046606732,0.000029914769,0.00000812627,0.00005517601,0.00030722743,0.0011357599,0.00018354839,0.99303484,0.0011659599,0.0040152776],"study_design_scores_gemma":[0.000013468669,0.000011814228,0.000075412485,0.00007020828,0.000029667592,0.000108345186,0.00025516094,0.011937925,0.00043339937,0.932514,0.054532606,0.000017923057],"about_ca_topic_score_codex":0.013203294,"about_ca_topic_score_gemma":0.013011203,"teacher_disagreement_score":0.013203294,"about_ca_system_score_codex":0.0037299637,"about_ca_system_score_gemma":0.0062320475,"threshold_uncertainty_score":0.027062953},"labels":[],"label_agreement":null},{"id":"W2157747875","doi":"10.1016/j.compind.2009.02.013","title":"Collaborative feature-based design via operations with a fine-grain product database","year":2009,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Interoperability; Feature (linguistics); Computer science; Collaborative engineering; Key (lock); Product (mathematics); Concurrent engineering; Database; Scheme (mathematics); Systems engineering; Product design; CAD; Software engineering; Distributed computing; Engineering; Engineering drawing; World Wide Web; Work in process; Operating system","score_opus":0.011601419547573806,"score_gpt":0.22145782752336393,"score_spread":0.20985640797579014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157747875","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027302312,0.00009169332,0.9658156,0.000078178615,0.000016961058,0.00012414639,0.00013981602,0.003607633,0.0028236194],"genre_scores_gemma":[0.41914392,0.00012694602,0.57759315,0.000056233082,0.000017809407,0.00015968674,0.0006114126,0.00025737562,0.0020335193],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833065,0.00030579197,0.00014085499,0.00041632386,0.0007018397,0.00010451882],"domain_scores_gemma":[0.9974952,0.00077761855,0.00014839602,0.0012615022,0.00020473612,0.00011257465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016253485,0.00090583053,0.0015326899,0.0013178199,0.00072223257,0.0027123336,0.002448457,0.0010058441,0.0059183245],"category_scores_gemma":[0.004541897,0.0008842781,0.001223218,0.0016440902,0.0005244064,0.0029319727,0.0029820576,0.0008256442,0.001220547],"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":[0.0009914625,0.0008446573,0.004425466,0.00022936563,0.00020941325,0.00050776894,0.0006752665,0.30996007,0.037487287,0.019828083,0.0061322968,0.6187088],"study_design_scores_gemma":[0.00008663294,0.000198098,0.00076659047,0.000013603401,0.000097034106,0.00018620148,0.00010076065,0.9607501,0.014229594,0.016637927,0.00689353,0.000040028557],"about_ca_topic_score_codex":0.0025482143,"about_ca_topic_score_gemma":0.0036112608,"teacher_disagreement_score":0.0059183245,"about_ca_system_score_codex":0.000549057,"about_ca_system_score_gemma":0.0010087962,"threshold_uncertainty_score":0.019798756},"labels":[],"label_agreement":null},{"id":"W2503313501","doi":"10.1016/j.compind.2016.05.006","title":"Design, modelling, simulation and integration of cyber physical systems: Methods and applications","year":2016,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Flexible and Reconfigurable Manufacturing Systems","field":"Engineering","cited_by":300,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Cyber-physical system; Systems engineering; Mechatronics; Process (computing); Cloud computing; Computer science; System integration; Physical system; Engineering; Control engineering; Database","score_opus":0.04760516188997784,"score_gpt":0.30362964042705337,"score_spread":0.25602447853707555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2503313501","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":[0.0043613315,0.001044459,0.9914562,0.00012616608,0.00006249135,0.000046750465,0.00004259472,0.00032867302,0.0025313925],"genre_scores_gemma":[0.2614287,0.0034907965,0.72913,0.00007121079,0.00010102606,0.0005450026,0.0002501391,0.00025098573,0.004732092],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995689,0.00016556251,0.00002285282,0.000049257465,0.00017138783,0.000022062393],"domain_scores_gemma":[0.9994393,0.00028546518,0.000056449302,0.00010406377,0.000093206574,0.00002146771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072528253,0.00077685725,0.00081927096,0.0006522102,0.00029959148,0.0016045077,0.0010709439,0.0008186447,0.0018190105],"category_scores_gemma":[0.0014883513,0.00058281864,0.0008720796,0.0006930653,0.00089941476,0.001133399,0.0006791701,0.0010061307,0.00050671323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040023115,0.000057294776,0.0006985046,0.00042744426,0.000069656984,0.00004825762,0.00011663325,0.858001,0.0060828524,0.049668875,0.0009646132,0.08382482],"study_design_scores_gemma":[0.000015365154,0.000021800914,0.00015880869,0.000033933262,0.000013889312,0.00002677383,0.000016748309,0.9746131,0.0023104963,0.015168669,0.0076100766,0.000010321246],"about_ca_topic_score_codex":0.0024498436,"about_ca_topic_score_gemma":0.002462364,"teacher_disagreement_score":0.0024498436,"about_ca_system_score_codex":0.0005475531,"about_ca_system_score_gemma":0.0013712484,"threshold_uncertainty_score":0.006085217},"labels":[],"label_agreement":null},{"id":"W2766455075","doi":"10.1016/j.compind.2017.10.002","title":"Simulation-optimisation based framework for Sales and Operations Planning taking into account new products opportunities in a co-production context","year":2017,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Operations Management Techniques","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Production (economics); Context (archaeology); Plan (archaeology); Product (mathematics); Production planning; Order (exchange); Sales and operations planning; Operations research; Commodity; Decision maker; Engineering; Manufacturing engineering; Computer science; Business; Economics; Mathematics","score_opus":0.4119907441989462,"score_gpt":0.4757350862610759,"score_spread":0.0637443420621297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766455075","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011316636,0.0003763202,0.9791301,0.00033685466,0.00007353373,0.000072013456,0.00020401488,0.00021984417,0.008270597],"genre_scores_gemma":[0.74251443,0.0009386117,0.24647203,0.00014424081,0.00014210699,0.000524114,0.00053829735,0.00014370945,0.008582572],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937844,0.00027231,0.000031972646,0.00008650499,0.00014746138,0.00008332235],"domain_scores_gemma":[0.9992513,0.0004673404,0.000060422044,0.000032817763,0.00012208709,0.000065989174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009914903,0.0010424242,0.0021084445,0.0011664184,0.0006500782,0.0019199764,0.0022185748,0.0021006684,0.005401328],"category_scores_gemma":[0.0018833114,0.0009293986,0.0016374025,0.001522586,0.0010290939,0.0010321357,0.0012888998,0.0014310832,0.0005217678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000067408187,0.000011346361,0.00006137348,0.000012117018,0.000013968366,0.000019574807,0.0000058211936,0.99302304,0.00007814503,0.0054072677,0.0000802052,0.001280405],"study_design_scores_gemma":[0.0000032273974,0.0000037554685,0.000021530095,0.0000024423973,0.0000035493283,0.000003137135,0.0000023504774,0.9973815,0.000025710955,0.0023897805,0.00016082042,0.0000021143414],"about_ca_topic_score_codex":0.025587715,"about_ca_topic_score_gemma":0.015150373,"teacher_disagreement_score":0.025587715,"about_ca_system_score_codex":0.001602448,"about_ca_system_score_gemma":0.003177666,"threshold_uncertainty_score":0.05087757},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"agree"},{"id":"W3014699476","doi":"10.1016/j.compind.2020.103229","title":"A systematic design method of adaptive augmented reality work instruction for complex industrial operations","year":2020,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Northwestern Polytechnical University","keywords":"Augmented reality; Computer science; Work (physics); Manufacturing engineering; Engineering; Systems engineering; Software engineering; Industrial engineering; Human–computer interaction; Mechanical engineering","score_opus":0.2416774249793546,"score_gpt":0.3458808672436372,"score_spread":0.1042034422642826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014699476","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025598558,0.000021878886,0.99588263,0.0000075517723,0.000009462248,0.00011221434,0.000008459479,0.0002501009,0.0011479117],"genre_scores_gemma":[0.15200381,0.00007611452,0.8450532,0.000022516348,0.000007953023,0.00059036247,0.000047181373,0.00008443844,0.0021144024],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991233,0.00024940763,0.000053566793,0.00018578877,0.00034227097,0.00004560737],"domain_scores_gemma":[0.999236,0.00023130525,0.00005921315,0.00010937085,0.00034442203,0.00001978503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077167444,0.00080180774,0.00055461074,0.0007081999,0.00051507127,0.00077892543,0.0010389695,0.00055223645,0.005276306],"category_scores_gemma":[0.0015247733,0.0005283442,0.00060966477,0.00034601122,0.00050406874,0.00056814007,0.0008186498,0.00050998514,0.00070197566],"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":[0.0003979408,0.00038419708,0.0013518161,0.001018879,0.000116498384,0.0001543235,0.0010337384,0.16045745,0.1406435,0.029487314,0.0019635905,0.66299075],"study_design_scores_gemma":[0.00013961467,0.0010449567,0.0017041378,0.00010119293,0.00017679743,0.00023602806,0.00026270235,0.9118807,0.058413163,0.0056352005,0.020332834,0.00007269965],"about_ca_topic_score_codex":0.0014748472,"about_ca_topic_score_gemma":0.0021181905,"teacher_disagreement_score":0.005276306,"about_ca_system_score_codex":0.00030339716,"about_ca_system_score_gemma":0.0011920898,"threshold_uncertainty_score":0.017650962},"labels":[],"label_agreement":null},{"id":"W3161526324","doi":"10.1016/j.compind.2021.103467","title":"Improving aircraft conceptual design through parametric CAD modellers – A case study for thermal analysis of aircraft systems","year":2021,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bombardier (Canada); Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec","keywords":"CAD; Parametric statistics; Conceptual design; Systems engineering; Engineering; Parametric design; Computer Aided Design; Computer science; Manufacturing engineering; Aerospace engineering; Engineering drawing; Mechanical engineering; Mathematics","score_opus":0.06014688102861573,"score_gpt":0.2863997120968466,"score_spread":0.22625283106823088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161526324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6176826,0.0003570802,0.36117688,0.00038615853,0.000031358886,0.00031388598,0.00021970202,0.0009713858,0.018860938],"genre_scores_gemma":[0.8411295,0.00018511561,0.15511541,0.000027620668,0.000005931653,0.00008482844,0.0001229627,0.00018496033,0.0031437061],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992749,0.00035816268,0.000024262004,0.000051911447,0.00022854612,0.00006210486],"domain_scores_gemma":[0.9976993,0.0014694732,0.00007496232,0.00043970704,0.00027278348,0.000043746903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013107599,0.00066131604,0.00038752804,0.00042295802,0.00065851945,0.0012792764,0.0010122157,0.0011107911,0.0026741961],"category_scores_gemma":[0.0030924424,0.0004690677,0.0005886491,0.0005351474,0.0007442027,0.001003804,0.0006170748,0.00088183506,0.00038029635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015750289,0.00026979292,0.0020353806,0.0002444695,0.00001960618,0.00049089734,0.00095256546,0.8796322,0.02835555,0.006369606,0.0010696079,0.08040289],"study_design_scores_gemma":[0.000028969054,0.00023163258,0.001429616,0.000037464724,0.000025786212,0.00023879515,0.0003912895,0.96924007,0.0189212,0.0023874436,0.0070384643,0.000029302428],"about_ca_topic_score_codex":0.0034238575,"about_ca_topic_score_gemma":0.0064832643,"teacher_disagreement_score":0.0034238575,"about_ca_system_score_codex":0.0007310936,"about_ca_system_score_gemma":0.0009587954,"threshold_uncertainty_score":0.008946061},"labels":[],"label_agreement":null},{"id":"W3183258307","doi":"10.1016/j.compind.2021.103510","title":"A machine learning framework with dataset-knowledgeability pre-assessment and a local decision-boundary crispness score: An industry 4.0-based case study on composite autoclave manufacturing","year":2021,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Context (archaeology); Computer science; Machine learning; Process (computing); Artificial intelligence; Domain (mathematical analysis); Pipeline (software); Engineering; Manufacturing engineering; Data mining; Mechanical engineering","score_opus":0.026021557321244386,"score_gpt":0.34459631584574285,"score_spread":0.31857475852449846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183258307","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.112485416,0.00047307723,0.8756198,0.0013398353,0.000040795734,0.0004389907,0.0014352973,0.00177953,0.0063872077],"genre_scores_gemma":[0.6015502,0.00011943793,0.39372286,0.00017137549,0.00003285345,0.00027011408,0.0019921106,0.00007557983,0.0020654162],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981933,0.00073582673,0.0001136257,0.00042647388,0.0003858283,0.00014495465],"domain_scores_gemma":[0.9970354,0.0017612787,0.00020593958,0.00021669191,0.0006434701,0.00013713133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004811145,0.0005772647,0.0007112266,0.0018271114,0.0005436686,0.0018860364,0.0019834614,0.001718383,0.0019992646],"category_scores_gemma":[0.006663415,0.0002750637,0.0007822888,0.0016332562,0.0006019977,0.0016263082,0.001294532,0.0011628186,0.0004229054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044787244,0.00096833624,0.010353304,0.00032694195,0.00018618556,0.00045443565,0.00035346384,0.6939813,0.0042219087,0.0222245,0.006437624,0.26004413],"study_design_scores_gemma":[0.000017568214,0.000059064325,0.0011774804,0.000021813094,0.000015981723,0.00003589607,0.000048144735,0.9893104,0.00097298494,0.0068486487,0.0014782617,0.000013724154],"about_ca_topic_score_codex":0.016754063,"about_ca_topic_score_gemma":0.019882837,"teacher_disagreement_score":0.016754063,"about_ca_system_score_codex":0.0016393797,"about_ca_system_score_gemma":0.002357308,"threshold_uncertainty_score":0.033313096},"labels":[],"label_agreement":null},{"id":"W3212409379","doi":"10.1016/j.compind.2021.103554","title":"Data-driven strategies for predictive maintenance: Lesson learned from an automotive use case","year":2021,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":47,"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":"General Motors of Canada","keywords":"Predictive maintenance; Automotive industry; Model predictive control; Prognostics; Exploit; Interpretability; Machine learning; Pipeline (software); Component (thermodynamics); Engineering; Computer science; Artificial intelligence; Reliability engineering; Control (management); Computer security","score_opus":0.12893889931500505,"score_gpt":0.32495274899048165,"score_spread":0.1960138496754766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212409379","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12948743,0.0033673034,0.8206115,0.013287808,0.00021423723,0.00019505277,0.00029321184,0.0007558899,0.031787645],"genre_scores_gemma":[0.7660994,0.0015582266,0.22808497,0.00029114072,0.00005938616,0.00009018079,0.00015980132,0.000090764996,0.0035662518],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99936956,0.00021671919,0.000041155243,0.000089274756,0.0002349431,0.00004848667],"domain_scores_gemma":[0.996089,0.0026979852,0.0001015605,0.00029832532,0.0007246355,0.00008846935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019161752,0.00070349296,0.0004327437,0.0007099938,0.00038967683,0.0014989753,0.0015901333,0.0012433378,0.002085349],"category_scores_gemma":[0.0072133485,0.00027965556,0.00041470377,0.00051831704,0.00065895985,0.0020849998,0.0007606982,0.0016645145,0.00035845954],"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":[0.00023393559,0.0006252383,0.011780062,0.00062865467,0.00012550133,0.0012174719,0.001586239,0.3302687,0.006140205,0.08372897,0.012420567,0.55124444],"study_design_scores_gemma":[0.00006992224,0.0002328835,0.0028333515,0.00028342122,0.0000662668,0.0005882439,0.0010479698,0.8474717,0.010584493,0.11333331,0.023417557,0.00007083213],"about_ca_topic_score_codex":0.0065444345,"about_ca_topic_score_gemma":0.008296834,"teacher_disagreement_score":0.0065444345,"about_ca_system_score_codex":0.00089209265,"about_ca_system_score_gemma":0.0010120657,"threshold_uncertainty_score":0.013012707},"labels":[],"label_agreement":null},{"id":"W4210345702","doi":"10.1016/j.compind.2022.103608","title":"Risk knowledge modeling for offer definition in customer-supplier relationships in Engineer-To-Order situations","year":2022,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Agence Nationale de la Recherche","keywords":"Risk analysis (engineering); Risk management; Identification (biology); Computer science; Order (exchange); Knowledge management; Process (computing); Management science; Engineering; Business","score_opus":0.04014210992784486,"score_gpt":0.2406306676674973,"score_spread":0.20048855773965243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210345702","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06228571,0.0002921485,0.9290312,0.000723448,0.00004402827,0.00014411843,0.00022765853,0.00021349493,0.0070381947],"genre_scores_gemma":[0.88818425,0.00027017097,0.10652895,0.00010303331,0.000043208354,0.00014013558,0.00032733602,0.00005358313,0.0043494515],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971712,0.0011125207,0.00021383775,0.00043101888,0.00068529625,0.00038605346],"domain_scores_gemma":[0.9935942,0.0046824305,0.00053043355,0.00023674824,0.00071233534,0.00024390634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004163719,0.0008080119,0.0010424446,0.0019447395,0.0010248115,0.0039742547,0.001947353,0.0018714623,0.0035248436],"category_scores_gemma":[0.013434637,0.00059638877,0.0017016107,0.0012989976,0.0012924039,0.0049172067,0.0021126503,0.0016305612,0.0003731697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013023571,0.0001397092,0.0032443798,0.00008604953,0.00006213368,0.00029828458,0.0006159038,0.8639515,0.00057973474,0.10437567,0.0009823282,0.025533976],"study_design_scores_gemma":[0.0000036696836,0.000010818363,0.00019299443,0.000013002765,0.0000170729,0.000021737937,0.000074996846,0.98057,0.00014323127,0.018617447,0.0003262347,0.000008756534],"about_ca_topic_score_codex":0.022725306,"about_ca_topic_score_gemma":0.015522443,"teacher_disagreement_score":0.022725306,"about_ca_system_score_codex":0.0030276105,"about_ca_system_score_gemma":0.0024410367,"threshold_uncertainty_score":0.045186102},"labels":[],"label_agreement":null},{"id":"W4237726444","doi":"10.1016/j.compind.2006.04.004","title":"Editorial","year":2006,"lang":"en","type":"editorial","venue":"Computers in Industry","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Engineering","score_opus":0.00947621132092905,"score_gpt":0.2675340192766364,"score_spread":0.2580578079557073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237726444","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000050740684,0.0052637956,0.000101900274,0.025461111,0.9613624,0.000050507115,0.00007558423,0.000085574175,0.0075483746],"genre_scores_gemma":[0.0007551747,0.005330691,0.0002212962,0.024653919,0.9181668,0.0000624668,0.00012403545,0.00008357324,0.05060212],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.996114,0.0007175635,0.00039885385,0.00047828376,0.0019140238,0.00037723273],"domain_scores_gemma":[0.9840168,0.0030867106,0.0014618307,0.000827037,0.007595647,0.003011945],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0040780064,0.0036359574,0.0032749493,0.004847797,0.0033850602,0.0072469283,0.0029915685,0.011695555,0.04818767],"category_scores_gemma":[0.018756323,0.0012865076,0.0023107238,0.0016720282,0.0016300776,0.00282109,0.0018499654,0.011580185,0.036526337],"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":[0.000016240097,0.0000067678725,0.000011020725,0.00006296622,0.00000599127,0.00006948673,0.0000029130613,0.000006890342,0.000020733642,0.00005683838,0.9965988,0.0031412228],"study_design_scores_gemma":[0.00004807009,0.000017048236,0.00016424447,0.00020238901,0.00003060038,0.0002248384,0.000015238236,0.000053876473,0.00008384964,0.0002697528,0.99888176,0.000008375273],"about_ca_topic_score_codex":0.001600044,"about_ca_topic_score_gemma":0.0044979635,"teacher_disagreement_score":0.9518123,"about_ca_system_score_codex":0.0026620885,"about_ca_system_score_gemma":0.0025950577,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4252786238","doi":"10.1016/s0166-3615(00)00080-4","title":"Letter to the Editor","year":2001,"lang":"en","type":"letter","venue":"Computers in Industry","topic":"Veterinary Practice and Education Studies","field":"Health Professions","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":"Memorial University of Newfoundland","funders":"Engineering and Physical Sciences Research Council","keywords":"Computer science; Engineering","score_opus":0.2674932681070271,"score_gpt":0.47182941124826583,"score_spread":0.2043361431412387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252786238","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00079404726,0.0015942174,0.00007377476,0.9154551,0.056895815,0.000033195887,0.00006152981,0.000032004682,0.025060358],"genre_scores_gemma":[0.0054662977,0.0009282143,0.000103165075,0.9005826,0.025112655,0.00004813024,0.000032167805,0.000025349096,0.067701496],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977944,0.0005313924,0.00019011273,0.0003237441,0.0006882111,0.0004722087],"domain_scores_gemma":[0.9954288,0.0018956246,0.0002814321,0.00015556806,0.0012098178,0.0010287832],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002632132,0.0007720142,0.0012763657,0.00090628373,0.005263288,0.004789268,0.0016381321,0.047006246,0.014537635],"category_scores_gemma":[0.020310974,0.0007965045,0.0010645164,0.0006115183,0.0014961032,0.0025279906,0.0012102622,0.023892265,0.009495445],"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":[0.00003808632,0.000020775375,0.00034249914,0.000025987158,0.0000065857835,0.0015751761,0.000087863635,0.000029040411,0.000044855686,0.0008572353,0.9941332,0.0028388707],"study_design_scores_gemma":[0.000069673035,0.000038108086,0.0015346168,0.00022377446,0.000021432426,0.0015662163,0.0006369958,0.00021147217,0.0001274474,0.0028880185,0.9926468,0.000035423454],"about_ca_topic_score_codex":0.009209748,"about_ca_topic_score_gemma":0.015500257,"teacher_disagreement_score":0.98546237,"about_ca_system_score_codex":0.0037001814,"about_ca_system_score_gemma":0.005065143,"threshold_uncertainty_score":0.048633218},"labels":[],"label_agreement":null},{"id":"W4308529607","doi":"10.1016/j.compind.2022.103801","title":"Secure Intelligent Fuzzy Blockchain Framework: Effective Threat Detection in IoT Networks","year":2022,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":220,"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; Brandon University; University of Guelph","funders":"","keywords":"Blockchain; Computer science; Computer security; Ambiguity; Fuzzy logic; Internet of Things; Artificial intelligence","score_opus":0.009739335810811418,"score_gpt":0.24352174797113554,"score_spread":0.23378241216032414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308529607","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06539178,0.00024888394,0.9275014,0.00034796973,0.000059845956,0.00012111718,0.00012308551,0.00037520798,0.005830801],"genre_scores_gemma":[0.9523889,0.00016514017,0.044511415,0.000046260604,0.000024868437,0.00006454234,0.000099451936,0.00001429295,0.0026852393],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931204,0.00017093838,0.000038155336,0.00011534391,0.0002521609,0.00011140243],"domain_scores_gemma":[0.9990779,0.00035482386,0.00009234699,0.00013675114,0.0002576394,0.00008056061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011914241,0.0003348013,0.00064327073,0.00054614374,0.0010053527,0.0012406223,0.0010985719,0.0009348882,0.0032234737],"category_scores_gemma":[0.0020088607,0.00017295439,0.0003093477,0.0005206428,0.00076759484,0.0018757337,0.0012669687,0.0007204981,0.00030985865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005298664,0.00020221045,0.0023846026,0.00019985938,0.00007876557,0.00047028114,0.0003163544,0.6539101,0.014895375,0.17156115,0.0030660278,0.15238538],"study_design_scores_gemma":[0.000013645948,0.000031090556,0.000103109145,0.000007687252,0.000008717645,0.000036951733,0.000026027745,0.9713064,0.0018582202,0.025813483,0.0007879095,0.0000066428843],"about_ca_topic_score_codex":0.003827817,"about_ca_topic_score_gemma":0.004244704,"teacher_disagreement_score":0.003827817,"about_ca_system_score_codex":0.00076641986,"about_ca_system_score_gemma":0.001997377,"threshold_uncertainty_score":0.010783613},"labels":[],"label_agreement":null},{"id":"W4321179097","doi":"10.1016/j.compind.2023.103874","title":"Parametrization of a demand-driven operating model using reinforcement learning","year":2023,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Polytechnique Montréal","keywords":"Reinforcement learning; Computer science; Time horizon; Industrial engineering; Production (economics); Set (abstract data type); Production planning; Spike (software development); Variety (cybernetics); Customer satisfaction; Parametrization (atmospheric modeling); Operations research; Artificial intelligence; Mathematical optimization; Engineering; Mathematics; Economics","score_opus":0.06038673375545812,"score_gpt":0.2688890041927244,"score_spread":0.20850227043726627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321179097","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21240738,0.00027206092,0.77478456,0.0007239472,0.000082194194,0.00012088851,0.00029361917,0.0011038434,0.010211455],"genre_scores_gemma":[0.98710746,0.000036345107,0.010239704,0.000034934783,0.000009312127,0.000068619105,0.00008017009,0.000052640295,0.0023708374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972516,0.00011178315,0.00001304593,0.00005961489,0.00003876175,0.000051726143],"domain_scores_gemma":[0.9984061,0.0011515152,0.00014262658,0.00007682008,0.00015011923,0.00007295694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083346455,0.0006298159,0.0008354083,0.00040228327,0.00033880322,0.0010593988,0.0009119726,0.001416609,0.0035795576],"category_scores_gemma":[0.0038889218,0.0007162614,0.0005570013,0.0002627679,0.0006921043,0.00081582495,0.0008345641,0.0016031319,0.0004286354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013880504,0.0000075621965,0.00009731713,0.00000497268,0.0000032219739,0.000010273558,0.0000067664178,0.99820495,0.000111068875,0.0005397049,0.000054966567,0.00094535894],"study_design_scores_gemma":[0.0000024630458,0.000002166412,0.000021490825,7.358077e-7,7.8922056e-7,0.0000010243394,6.43213e-7,0.9997315,0.00002531883,0.00019340692,0.000019545687,8.868682e-7],"about_ca_topic_score_codex":0.016305368,"about_ca_topic_score_gemma":0.008436148,"teacher_disagreement_score":0.016305368,"about_ca_system_score_codex":0.0010772388,"about_ca_system_score_gemma":0.00094228546,"threshold_uncertainty_score":0.032420874},"labels":[],"label_agreement":null},{"id":"W4376561185","doi":"10.1016/j.compind.2023.103939","title":"Full-cycle data purification strategy for multi-type weld seam classification with few-shot learning","year":2023,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Welding Techniques and Residual Stresses","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Welding; Computer science; Artificial intelligence; Shot (pellet); Key (lock); Randomness; Volume (thermodynamics); Pattern recognition (psychology); Data mining; Computer vision; Engineering; Mathematics; Mechanical engineering","score_opus":0.2035916618725392,"score_gpt":0.34926818153318884,"score_spread":0.14567651966064965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376561185","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":[0.024842273,0.00040290272,0.9705338,0.00011643959,0.000073945776,0.00010867989,0.00022503838,0.0024879235,0.001208964],"genre_scores_gemma":[0.38885918,0.00035551414,0.5963417,0.0003649426,0.000086023356,0.00030535366,0.0027227702,0.0005812375,0.010383197],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999374,0.000050045543,0.000044312277,0.00019558467,0.00022242537,0.0001136249],"domain_scores_gemma":[0.9992099,0.00016885794,0.000034902645,0.0001633423,0.00036923352,0.00005377865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009558581,0.001022828,0.0013601565,0.0015708265,0.0009880216,0.00088513416,0.002416727,0.0012906626,0.004860456],"category_scores_gemma":[0.0016292467,0.0005988762,0.0013383605,0.0012617866,0.0005316439,0.0016475932,0.0020897605,0.0015951851,0.002529885],"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":[0.00030365394,0.00028524885,0.0023898464,0.00015722921,0.000083178886,0.00009859564,0.00013557884,0.024974566,0.042497728,0.0018361136,0.0051960587,0.9220422],"study_design_scores_gemma":[0.00001986873,0.00012429913,0.002553434,0.000015926606,0.00006948566,0.0001286152,0.00010383897,0.96352416,0.0251352,0.00428516,0.004001538,0.000038527123],"about_ca_topic_score_codex":0.0100651225,"about_ca_topic_score_gemma":0.017081266,"teacher_disagreement_score":0.0100651225,"about_ca_system_score_codex":0.0004388677,"about_ca_system_score_gemma":0.002345404,"threshold_uncertainty_score":0.020013034},"labels":[],"label_agreement":null},{"id":"W4379744505","doi":"10.1016/j.compind.2023.103957","title":"A similarity-assisted multi-fidelity approach to conceptual design space exploration","year":2023,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","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":"McGill University","funders":"Horizon 2020; HORIZON EUROPE Framework Programme; Horizon 2020 Framework Programme; Cleansky; VINNOVA; European Commission","keywords":"Similarity (geometry); Fidelity; Metric (unit); Data mining; Computer science; Reuse; Surrogate model; Conceptual design; Software; Visualization; Machine learning; Artificial intelligence; Engineering; Image (mathematics); Human–computer interaction","score_opus":0.15164267006233353,"score_gpt":0.3277300605853636,"score_spread":0.17608739052303005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379744505","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":[0.002234038,0.000047901343,0.9966928,0.000051478,0.000009119631,0.000051489198,0.000017865963,0.00015643655,0.00073902553],"genre_scores_gemma":[0.17311813,0.000120958684,0.8247449,0.00008641346,0.000027215978,0.0003888226,0.00012772641,0.00016640611,0.0012193943],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970528,0.0012358865,0.00015237245,0.00030885733,0.0011313651,0.00011866858],"domain_scores_gemma":[0.99173486,0.004883682,0.00088609505,0.0012252707,0.0010750676,0.00019507129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051033786,0.0012147559,0.0012019479,0.00224124,0.0007059123,0.0020127392,0.0020083322,0.0018485219,0.0035154698],"category_scores_gemma":[0.013965551,0.001021165,0.0014584541,0.0012288861,0.001192417,0.0019847173,0.0033234719,0.0021622994,0.00064086955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010127387,0.00014511697,0.0010483731,0.0002744924,0.00006982937,0.00010831746,0.0003200884,0.86726654,0.0071986658,0.02555692,0.00081550184,0.097094856],"study_design_scores_gemma":[0.000009906351,0.00006771008,0.000117252785,0.000018079412,0.000007125111,0.000047607613,0.00001980287,0.9892848,0.0016545011,0.0074592847,0.0013008285,0.000013057193],"about_ca_topic_score_codex":0.0015813924,"about_ca_topic_score_gemma":0.0017207544,"teacher_disagreement_score":0.0051033786,"about_ca_system_score_codex":0.000910616,"about_ca_system_score_gemma":0.0015596034,"threshold_uncertainty_score":0.02698958},"labels":[],"label_agreement":null},{"id":"W4380767889","doi":"10.1016/j.compind.2023.103964","title":"An image is worth 10,000 points: Neural network architectures and alternative log representations for lumber production prediction","year":2023,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"FPInnovations; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial neural network; Computer science; Artificial intelligence; Machine learning; Process (computing); Object (grammar); Multilayer perceptron; Production (economics); Function (biology); Data mining; Residual; Perceptron; Point (geometry); Pattern recognition (psychology); Algorithm; Mathematics","score_opus":0.019536675193292528,"score_gpt":0.2853657979884285,"score_spread":0.26582912279513593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380767889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75868565,0.0017516159,0.2301671,0.0014784673,0.00024178301,0.00004413454,0.00094746734,0.0010887674,0.00559513],"genre_scores_gemma":[0.9686396,0.000302318,0.02686393,0.000059401213,0.000049515835,0.000024362078,0.0005175261,0.000029857074,0.0035134563],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999918,0.000016776217,0.0000047551425,0.000028230563,0.000018072935,0.00001411522],"domain_scores_gemma":[0.9996313,0.00020357168,0.000036267444,0.000028429067,0.00008692859,0.000013644176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044638474,0.0004332809,0.00028676767,0.00043955873,0.00018209677,0.0007138226,0.0005493603,0.0006763799,0.0016090354],"category_scores_gemma":[0.0021993606,0.00023650916,0.00022235593,0.00060273113,0.00022814226,0.001043301,0.00030246863,0.0007168873,0.00027644716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061100005,0.00021532642,0.0064796107,0.000052438914,0.00004708616,0.00009551844,0.000039701605,0.6733548,0.0025395642,0.0021787686,0.0035323969,0.31085378],"study_design_scores_gemma":[0.0000022903166,0.000008057304,0.0007501521,0.0000029922028,0.0000034621723,0.0000038703297,0.000005083728,0.9980525,0.00023923656,0.0008631239,0.00006718958,0.0000020459668],"about_ca_topic_score_codex":0.012435615,"about_ca_topic_score_gemma":0.01262949,"teacher_disagreement_score":0.012435615,"about_ca_system_score_codex":0.00056550204,"about_ca_system_score_gemma":0.00032271203,"threshold_uncertainty_score":0.02472645},"labels":[],"label_agreement":null},{"id":"W4385128451","doi":"10.1016/j.compind.2023.103989","title":"Non data hungry smart composite manufacturing using active transfer learning with sigma point sampling (SPSATL)","year":2023,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Fault Detection and Control Systems","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":"Western University; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"USable; Transfer of learning; Automation; Six Sigma; Computer science; Machine learning; Sampling (signal processing); Artificial intelligence; Active learning (machine learning); Industrial engineering; Data mining; Manufacturing engineering; Engineering","score_opus":0.038920638878952,"score_gpt":0.25925652571993746,"score_spread":0.22033588684098546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385128451","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04348959,0.00015525507,0.9537191,0.0000791483,0.000055989083,0.000029870642,0.000028287888,0.00080488645,0.0016377966],"genre_scores_gemma":[0.8485993,0.000075004544,0.14850236,0.00009516584,0.000029678382,0.000054701966,0.000072530136,0.000044017776,0.002527351],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996878,0.00005774558,0.00001550287,0.00006152121,0.00015028758,0.000027175893],"domain_scores_gemma":[0.99961483,0.00014472054,0.000044371336,0.00006383698,0.00011237062,0.000019857303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038549668,0.0004204245,0.0006361136,0.0002446066,0.0002902704,0.0005780548,0.0006414778,0.00047420562,0.0015948527],"category_scores_gemma":[0.0005992071,0.00022411831,0.00037495914,0.0003730107,0.00035854394,0.0007577311,0.00081212865,0.000607395,0.0004220053],"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":[0.0007374272,0.00028040475,0.0020110041,0.00023746498,0.0001056295,0.00021365195,0.0001677703,0.23878941,0.08885826,0.004551655,0.0017600703,0.6622873],"study_design_scores_gemma":[0.000011549082,0.0001312011,0.00036059026,0.000005190623,0.000009994763,0.000036917605,0.00001037847,0.9902872,0.007930195,0.00073425943,0.0004757822,0.0000067199394],"about_ca_topic_score_codex":0.0018452721,"about_ca_topic_score_gemma":0.0026899164,"teacher_disagreement_score":0.0018452721,"about_ca_system_score_codex":0.0002780649,"about_ca_system_score_gemma":0.0005674227,"threshold_uncertainty_score":0.0053352714},"labels":[],"label_agreement":null},{"id":"W4387993769","doi":"10.1016/j.compind.2023.104037","title":"Fundamental requirements of a machine learning operations platform for industrial metal additive manufacturing","year":2023,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Process (computing); Computer science; Manufacturing engineering; Systems engineering; Layer (electronics); Engineering; Process management; Nanotechnology","score_opus":0.0671934046165912,"score_gpt":0.2760625882412048,"score_spread":0.20886918362461357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387993769","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":[0.026519286,0.00016474805,0.9549867,0.001065811,0.00016750532,0.00049653853,0.00029750165,0.0024707154,0.013831221],"genre_scores_gemma":[0.49914122,0.0003400328,0.48646623,0.0003509936,0.000273366,0.0009400792,0.0012756624,0.00046172758,0.010750808],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961915,0.00033277294,0.00028407606,0.0005510525,0.002188795,0.00045177425],"domain_scores_gemma":[0.9954196,0.0016309192,0.0003323382,0.0009567101,0.0013663028,0.000294121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028603438,0.001046145,0.0010422366,0.00081383873,0.0012234377,0.0054346416,0.0031266287,0.00233746,0.007246404],"category_scores_gemma":[0.010609234,0.00086008897,0.0007745554,0.00065302744,0.0016829858,0.006005204,0.003597311,0.0035059035,0.0055825845],"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":[0.0009287429,0.0010685718,0.002695389,0.0006607175,0.0000839121,0.0010554963,0.0005153433,0.1856634,0.09426276,0.5375796,0.008063331,0.16742288],"study_design_scores_gemma":[0.00007158651,0.0003911778,0.0008553921,0.00009341887,0.000026076961,0.00028337244,0.00012599136,0.767826,0.06713465,0.14745094,0.015688794,0.000052684507],"about_ca_topic_score_codex":0.0015404248,"about_ca_topic_score_gemma":0.000895768,"teacher_disagreement_score":0.007246404,"about_ca_system_score_codex":0.0008557747,"about_ca_system_score_gemma":0.0035687082,"threshold_uncertainty_score":0.024241626},"labels":[],"label_agreement":null},{"id":"W4388440352","doi":"10.1016/j.compind.2023.104036","title":"Deep reinforcement learning for continuous wood drying production line control","year":2023,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reinforcement learning; Exploit; Heuristic; Production line; Production (economics); Computer science; Process (computing); Routing (electronic design automation); Control (management); Process engineering; Industrial engineering; Productivity; Continuous production; Manufacturing engineering; Artificial intelligence; Engineering; Mechanical engineering; Embedded system","score_opus":0.012750909355779303,"score_gpt":0.23353483585435914,"score_spread":0.22078392649857984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388440352","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061563663,0.0006511879,0.9323342,0.00038505372,0.00011266501,0.000034514032,0.00009727654,0.00069438014,0.004127009],"genre_scores_gemma":[0.96528673,0.00010005298,0.03025837,0.00013385735,0.00004194571,0.00005196406,0.00009464275,0.00004570296,0.003986785],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997969,0.000049851275,0.00000844855,0.000053074404,0.000042998832,0.00004868579],"domain_scores_gemma":[0.99922514,0.00047215578,0.00007258778,0.000041900355,0.00014606316,0.000042188403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072131254,0.00068218587,0.00089589774,0.00026746726,0.00025755638,0.0006157605,0.000830684,0.0011080686,0.0026574642],"category_scores_gemma":[0.0018210219,0.00042895792,0.0003329761,0.0002751424,0.0006277385,0.00057279685,0.0007692021,0.0014488202,0.00030357655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005506992,0.000040290128,0.00021432513,0.000024327353,0.000011846845,0.000018035744,0.0000132282175,0.96976936,0.00087172753,0.0019034697,0.00072329835,0.026354946],"study_design_scores_gemma":[0.0000020407183,0.0000062234444,0.000017629014,0.000001066116,7.438057e-7,7.71203e-7,5.4121585e-7,0.9994923,0.0000643728,0.00037587734,0.000037809088,6.6965976e-7],"about_ca_topic_score_codex":0.011201583,"about_ca_topic_score_gemma":0.009758938,"teacher_disagreement_score":0.011201583,"about_ca_system_score_codex":0.00074527506,"about_ca_system_score_gemma":0.0009310929,"threshold_uncertainty_score":0.022272766},"labels":[],"label_agreement":null},{"id":"W4390047559","doi":"10.1016/j.compind.2023.104063","title":"Neural semantic tagging for natural language-based search in building information models: Implications for practice","year":2023,"lang":"en","type":"article","venue":"Computers in Industry","topic":"BIM and Construction Integration","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Computer science; Semantic search; Natural language; Information extraction; Artificial intelligence; Deep learning; Schema (genetic algorithms); Information retrieval; Data science; Natural language processing; Semantic Web","score_opus":0.029952105593646434,"score_gpt":0.30156472329395007,"score_spread":0.27161261770030365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390047559","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08507079,0.0016490482,0.8912869,0.0057726307,0.00015545102,0.00021067735,0.00084156566,0.002489986,0.012522955],"genre_scores_gemma":[0.773935,0.00060877536,0.22204259,0.00048301878,0.00007644129,0.00017030766,0.00090503815,0.00017598548,0.001602852],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99713814,0.0016486367,0.00023141695,0.0005154751,0.0003522403,0.00011405563],"domain_scores_gemma":[0.9617935,0.03278287,0.0005847755,0.0023923581,0.0020714474,0.00037510248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007865889,0.0007126392,0.0011254482,0.0020624266,0.0010375007,0.0043362305,0.0024035126,0.0026870538,0.006867722],"category_scores_gemma":[0.06064787,0.0005496963,0.0005963797,0.0026316263,0.0018167512,0.013345011,0.0024000476,0.0021749642,0.0012484643],"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":[0.00079545175,0.000993348,0.013230082,0.0008743088,0.00023755697,0.00019765852,0.0011753879,0.1523472,0.0043383,0.12666716,0.011295415,0.6878481],"study_design_scores_gemma":[0.000057994283,0.00005544973,0.0010856992,0.00012616445,0.000042605014,0.000088007786,0.00034396903,0.7732812,0.0022655844,0.22042716,0.0021898642,0.000036348665],"about_ca_topic_score_codex":0.0135907335,"about_ca_topic_score_gemma":0.015916994,"teacher_disagreement_score":0.0135907335,"about_ca_system_score_codex":0.0022390352,"about_ca_system_score_gemma":0.002518659,"threshold_uncertainty_score":0.041599333},"labels":[],"label_agreement":null},{"id":"W4402448297","doi":"10.1016/j.compind.2024.104184","title":"Virtual warehousing through digitalized inventory and on-demand manufacturing: A case study","year":2024,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"Manufacturing Academy of Denmark; Aalborg Universitet","keywords":"Warehouse; Manufacturing engineering; Computer science; Inventory management; Inventory theory; Engineering; Operations management; Engineering drawing; Operations research; Industrial engineering; Business; Marketing","score_opus":0.02746602938444329,"score_gpt":0.26901793856173817,"score_spread":0.24155190917729488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402448297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9353816,0.00049740047,0.035801124,0.0012773253,0.000041072773,0.00042176284,0.00036031706,0.00021609006,0.026003387],"genre_scores_gemma":[0.9557458,0.0005777557,0.038804363,0.00011655647,0.000013260566,0.00011983689,0.00024683407,0.000042678497,0.004332988],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976799,0.0009913208,0.00012899218,0.0001840696,0.0007089376,0.0003067132],"domain_scores_gemma":[0.99620134,0.002116652,0.00030890273,0.00067751494,0.00030775712,0.00038796736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029728806,0.0004653805,0.00030225734,0.00133289,0.0018840751,0.0035563973,0.0019324558,0.0021227673,0.0022910652],"category_scores_gemma":[0.004007451,0.00034834695,0.00063773955,0.0024563111,0.0019210606,0.0029238237,0.0028078305,0.0012406033,0.00041484152],"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":[0.0015458234,0.006463187,0.09568948,0.0016480002,0.0002527242,0.09463805,0.04266614,0.19545227,0.02163327,0.16656539,0.014807072,0.35863855],"study_design_scores_gemma":[0.0007709723,0.0033762888,0.06408135,0.0009907206,0.0002954158,0.03155225,0.09412975,0.41684753,0.073643096,0.042533837,0.2713669,0.00041194152],"about_ca_topic_score_codex":0.010653134,"about_ca_topic_score_gemma":0.013481918,"teacher_disagreement_score":0.010653134,"about_ca_system_score_codex":0.002411698,"about_ca_system_score_gemma":0.0017853004,"threshold_uncertainty_score":0.021182239},"labels":[],"label_agreement":null},{"id":"W4402738631","doi":"10.1016/j.compind.2024.104189","title":"Development of immersive bridge digital twin platform to facilitate bridge damage assessment and asset model updates","year":2024,"lang":"en","type":"article","venue":"Computers in Industry","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; Okanagan College","funders":"","keywords":"Bridge (graph theory); Asset (computer security); Computer science; Engineering; Construction engineering; Human–computer interaction; Forensic engineering; Computer security","score_opus":0.10188965483970067,"score_gpt":0.28939905624028206,"score_spread":0.1875094014005814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402738631","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14617634,0.00025505832,0.82129127,0.00028614703,0.0002297705,0.0015850652,0.0016698069,0.01170548,0.016801227],"genre_scores_gemma":[0.4512559,0.00028759515,0.5310292,0.0002530755,0.00004213955,0.0017907942,0.002328759,0.00068547245,0.012327096],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996747,0.000049542483,0.00001747394,0.000060538852,0.00014389738,0.000053855976],"domain_scores_gemma":[0.9996538,0.00007529909,0.000021497497,0.00006428705,0.000101333535,0.000083907085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000569187,0.00085680484,0.00037899867,0.00068504136,0.0001665538,0.0007375509,0.0013364257,0.0006110878,0.010456329],"category_scores_gemma":[0.0011403635,0.00036815947,0.0005613613,0.0002285156,0.00024308516,0.0012119446,0.0022550519,0.00059648056,0.0016960711],"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":[0.0013266765,0.0014002451,0.013206842,0.0013178412,0.00020214735,0.0019813757,0.0028991764,0.0397321,0.3596771,0.013892047,0.027078282,0.53728616],"study_design_scores_gemma":[0.00057747104,0.003531168,0.033086468,0.00033768982,0.00028002867,0.0026803114,0.0011890151,0.6554773,0.15146562,0.009807164,0.14119187,0.00037587597],"about_ca_topic_score_codex":0.0011886406,"about_ca_topic_score_gemma":0.0017572248,"teacher_disagreement_score":0.010456329,"about_ca_system_score_codex":0.00016572782,"about_ca_system_score_gemma":0.0006081918,"threshold_uncertainty_score":0.03497988},"labels":[],"label_agreement":null},{"id":"W4403929559","doi":"10.1016/j.compind.2024.104201","title":"Developing a BIM-enabled robotic manufacturing framework to facilitate mass customization of prefabricated buildings","year":2024,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Innovations in Concrete and Construction Materials","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of New Brunswick","funders":"","keywords":"Mass customization; Personalization; Engineering; Building information modeling; Manufacturing engineering; Prefabrication; Systems engineering; Construction engineering; Computer science; Architectural engineering; Civil engineering; Operations management; World Wide Web","score_opus":0.03366030959614994,"score_gpt":0.2504978095885853,"score_spread":0.21683749999243537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403929559","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011475085,0.00014183603,0.97518665,0.00024115297,0.0000295928,0.00030528873,0.00019508984,0.0046145986,0.007810652],"genre_scores_gemma":[0.15322474,0.00030214933,0.84137356,0.00008527213,0.000009591953,0.00044919897,0.0008276133,0.00029507885,0.0034328573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988128,0.00024787468,0.00008387207,0.00016484778,0.0005204895,0.00017023331],"domain_scores_gemma":[0.9995067,0.0001269231,0.000059867332,0.00012410941,0.00012247518,0.000059917656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020420058,0.00089495233,0.00039807206,0.0015049608,0.000794677,0.0015764206,0.002239034,0.0010084853,0.002533189],"category_scores_gemma":[0.0016662951,0.0006090922,0.0011318414,0.0007775401,0.0008189986,0.0022901872,0.0034007519,0.0011847273,0.0009894624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012699254,0.0005002968,0.0032380952,0.0008331667,0.000070418246,0.0016678892,0.0020985538,0.43042374,0.04814024,0.19477321,0.009031833,0.30909553],"study_design_scores_gemma":[0.000049612692,0.00012560541,0.0016099865,0.00020137819,0.00004865453,0.0005565832,0.00054382015,0.8206411,0.029237509,0.023537481,0.12335453,0.00009378665],"about_ca_topic_score_codex":0.007898673,"about_ca_topic_score_gemma":0.008385618,"teacher_disagreement_score":0.007898673,"about_ca_system_score_codex":0.0010262477,"about_ca_system_score_gemma":0.002666933,"threshold_uncertainty_score":0.015705407},"labels":[],"label_agreement":null},{"id":"W4405273113","doi":"10.1016/j.compind.2024.104215","title":"Intelligent prediction and soft-sensing of comprehensive production indicators for iron ore sintering: A review","year":2024,"lang":"en","type":"review","venue":"Computers in Industry","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Sintering; Production (economics); Iron ore; Process engineering; Computer science; Environmental science; Metallurgy; Engineering; Materials science","score_opus":0.062270167505928474,"score_gpt":0.32266063246355486,"score_spread":0.2603904649576264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405273113","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":[0.0008774965,0.99462515,0.0035206268,0.00014632857,0.00014660503,0.000010390307,0.000055543143,0.00002905603,0.0005887068],"genre_scores_gemma":[0.007514416,0.9882504,0.003187152,0.00015391158,0.00024966573,0.000016986287,0.00009533894,0.0000056510503,0.0005265937],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997185,0.000030347886,0.000032554773,0.000099604484,0.00009916736,0.000019888075],"domain_scores_gemma":[0.99935025,0.00035738357,0.000097519056,0.00002361474,0.00015176255,0.000019462355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008728049,0.0013019969,0.0018978133,0.0015094092,0.00018326119,0.0010334502,0.0011146903,0.0010967907,0.0012994163],"category_scores_gemma":[0.0011321628,0.0004515157,0.0010579368,0.0022149074,0.00040176703,0.0012523618,0.0006396601,0.00087166333,0.0007262373],"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":[0.0000928281,0.00017661112,0.0008959914,0.016106257,0.00028992505,0.000087260414,0.00005114656,0.0037346045,0.004379613,0.0022101174,0.007858529,0.96411705],"study_design_scores_gemma":[0.000105914274,0.0018917057,0.0125006335,0.012510652,0.003538748,0.0019307102,0.00041120956,0.03676282,0.029569136,0.011659003,0.888642,0.00047737735],"about_ca_topic_score_codex":0.0021661362,"about_ca_topic_score_gemma":0.0020367324,"teacher_disagreement_score":0.0021661362,"about_ca_system_score_codex":0.00027775488,"about_ca_system_score_gemma":0.0007567956,"threshold_uncertainty_score":0.004615903},"labels":[],"label_agreement":null},{"id":"W4409142136","doi":"10.1016/j.compind.2025.104286","title":"Generative Manufacturing: A requirements and resource-driven approach to part making","year":2025,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"Lockheed Martin Corporation; Lockheed Martin","keywords":"Generative grammar; Resource (disambiguation); Computer science; Engineering; Systems engineering; Manufacturing engineering; Software engineering; Artificial intelligence","score_opus":0.02722049803014417,"score_gpt":0.25219444183533385,"score_spread":0.22497394380518967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409142136","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":[0.0045516035,0.000080486854,0.99122506,0.00015493148,0.000014495504,0.00011549711,0.000042015956,0.0005948127,0.003221033],"genre_scores_gemma":[0.077071,0.00021475294,0.920292,0.000114663635,0.000013089499,0.00027099694,0.00017927133,0.00036256586,0.0014815764],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980829,0.000785942,0.000078464225,0.00024031244,0.0006712403,0.00014120678],"domain_scores_gemma":[0.99693716,0.0021795942,0.00015871198,0.0004617067,0.00019734514,0.00006544217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027258329,0.0012451867,0.0008092418,0.0013845732,0.0010270497,0.0023870626,0.002918922,0.0014997749,0.00453224],"category_scores_gemma":[0.0050454983,0.0014814981,0.0028998223,0.0010512923,0.0030894554,0.0017677929,0.002393157,0.0019390613,0.0007671706],"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":[0.000098110824,0.00011954151,0.0011110911,0.00035583132,0.000081240214,0.0004351861,0.0009573072,0.72119284,0.009326548,0.18586268,0.0027917635,0.07766787],"study_design_scores_gemma":[0.00005538288,0.00010037262,0.0002643591,0.000099791454,0.000058423844,0.00029588668,0.00017687942,0.84595376,0.0073208595,0.12365034,0.021973941,0.00004997027],"about_ca_topic_score_codex":0.0034915842,"about_ca_topic_score_gemma":0.0061768405,"teacher_disagreement_score":0.00453224,"about_ca_system_score_codex":0.0017653593,"about_ca_system_score_gemma":0.0029453028,"threshold_uncertainty_score":0.015161872},"labels":[],"label_agreement":null},{"id":"W4414159111","doi":"10.1016/j.compind.2025.104361","title":"Data issues in industrial AI systems: A meta-review and research strategy","year":2025,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"HORIZON EUROPE Widening Participation and Strengthening the European Research Area; Manufacturing Academy of Denmark; European Commission; Double Thousand Plan of Jiangxi Province","keywords":"Domain (mathematical analysis); Data governance; Industry 4.0; Usability; Subject-matter expert; Big data; Excellence; Data management; Data exchange","score_opus":0.5069356076250422,"score_gpt":0.4590583404119505,"score_spread":0.04787726721309171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414159111","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034260793,0.9917464,0.0018618861,0.0043276567,0.00042691812,0.00006518673,0.00006988261,0.000016731665,0.0011426392],"genre_scores_gemma":[0.005893827,0.9874917,0.003523969,0.0021470976,0.00038680222,0.00018878041,0.000119690856,0.000019183473,0.0002288711],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.98306644,0.0072423434,0.0042229574,0.0014258103,0.0035697494,0.00047266806],"domain_scores_gemma":[0.83149433,0.13941729,0.008424212,0.003380759,0.016103923,0.0011795305],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.031708535,0.0016850019,0.0035553342,0.040438112,0.0020094402,0.011061259,0.0035838818,0.0044786814,0.003008156],"category_scores_gemma":[0.07371986,0.0017068124,0.00495692,0.031083912,0.0048142374,0.015173721,0.004248666,0.006742827,0.0008073663],"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":[0.00015854732,0.00014805082,0.0020950516,0.23487629,0.0014803042,0.00041472926,0.0068288106,0.0017223788,0.00089994323,0.080626294,0.02455216,0.64619744],"study_design_scores_gemma":[0.000028126407,0.0001861333,0.0023878415,0.45703375,0.0031055359,0.00087896286,0.0043921582,0.00073170837,0.00088038563,0.023579072,0.50668067,0.00011567237],"about_ca_topic_score_codex":0.009784666,"about_ca_topic_score_gemma":0.0151367625,"teacher_disagreement_score":0.96829146,"about_ca_system_score_codex":0.013146383,"about_ca_system_score_gemma":0.030013224,"threshold_uncertainty_score":0.16769278},"labels":[],"label_agreement":null},{"id":"W4416221854","doi":"10.1016/j.compind.2025.104410","title":"Integrating static and dynamic hierarchical clustering and its application to retail segmentation","year":2025,"lang":"en","type":"article","venue":"Computers in Industry","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Ministerio de Ciencia e Innovación","keywords":"Cluster analysis; Profiling (computer programming); Hierarchical clustering; Variety (cybernetics); Big data; Key (lock); Identification (biology); Market segmentation; Dynamic data","score_opus":0.016353627886842876,"score_gpt":0.32588103996101325,"score_spread":0.3095274120741704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416221854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049468476,0.00061009405,0.94319695,0.00039132877,0.000058187296,0.00014164098,0.00047108013,0.0012215207,0.004440688],"genre_scores_gemma":[0.5300956,0.0004848127,0.4646967,0.00013954945,0.00013248489,0.0001359792,0.0016612043,0.00023117951,0.0024224587],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979601,0.0008008375,0.000112291855,0.00048540367,0.00047369514,0.00016765554],"domain_scores_gemma":[0.99781346,0.0008176323,0.00021386285,0.0004469923,0.0006007206,0.00010734375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023361202,0.0006713207,0.00070934044,0.0041181836,0.0010101936,0.0017813346,0.0010507656,0.00096634816,0.0010877252],"category_scores_gemma":[0.0059241685,0.0003567058,0.0010695027,0.0064202566,0.00057379896,0.0015167212,0.001752314,0.00078983395,0.00059381913],"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":[0.0002097057,0.0002786837,0.028164517,0.00027780884,0.00040680743,0.00036480278,0.001418885,0.35585645,0.009457813,0.038352933,0.0061043617,0.5591073],"study_design_scores_gemma":[0.000007238236,0.000052508916,0.008415196,0.000031617667,0.00006283937,0.00011776328,0.0005494256,0.9603095,0.0024477576,0.020031951,0.007924185,0.0000499544],"about_ca_topic_score_codex":0.020229729,"about_ca_topic_score_gemma":0.018786673,"teacher_disagreement_score":0.020229729,"about_ca_system_score_codex":0.0012116861,"about_ca_system_score_gemma":0.001492725,"threshold_uncertainty_score":0.040223956},"labels":[],"label_agreement":null}]}