{"meta":{"query_hash":"9aa56ac18c3e","filters":{"venue":"Discover Mechanical Engineering"},"cohort_total":6,"direct_labels_cover":0,"predictions_cover":6,"exported":6,"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/9aa56ac18c3e","api":"https://metacan.xera.ac/api/v1/cohort?venue=Discover+Mechanical+Engineering"},"results":[{"id":"W4362513452","doi":"10.1007/s44245-023-00011-w","title":"A review on the machining of polymer composites reinforced with carbon (CFRP), glass (GFRP), and natural fibers (NFRP)","year":2023,"lang":"en","type":"review","venue":"Discover Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Machining; Machinability; Fibre-reinforced plastic; Materials science; Composite material; Composite number; Delamination (geology); Aerospace; Carbon fiber reinforced polymer; Glass fiber; Automotive industry; Engineering; Metallurgy","score_opus":0.013451925549287156,"score_gpt":0.25064531725216993,"score_spread":0.23719339170288278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362513452","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000273084,0.98988616,0.008816863,0.000018714001,0.00023490739,0.0005777388,0.000027923612,0.00032082023,0.00008957586],"genre_scores_gemma":[0.00068323803,0.9981688,0.00056351605,0.000058595742,0.000066645895,0.000105099796,0.00009146635,0.0001988474,0.00006374882],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845475,0.00002869302,0.00057938823,0.00033389492,0.00026270802,0.00034054412],"domain_scores_gemma":[0.99886936,0.00048855814,0.00016759937,0.00036710396,0.000024428868,0.000082926155],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019262274,0.00056004734,0.0012448531,0.00012375934,0.0000471894,0.0000415152,0.0002780151,0.0001512074,0.00000482762],"category_scores_gemma":[0.0001200085,0.00035176348,0.00018896766,0.000509051,0.000023974138,0.00010365765,0.00010036688,0.0007295523,0.0000025866186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031701213,0.0000149757325,3.2900385e-7,0.24549668,0.0012448959,0.000026787537,0.00015754273,0.6499448,0.00008404715,0.019277917,0.000091202055,0.08362915],"study_design_scores_gemma":[0.00036298466,0.00016470319,5.3834225e-7,0.23099656,0.001292871,0.000056627363,0.000022221522,0.7308023,0.0002877118,0.000015964646,0.034724116,0.0012733833],"about_ca_topic_score_codex":0.00001153957,"about_ca_topic_score_gemma":0.0000017643257,"teacher_disagreement_score":0.08235577,"about_ca_system_score_codex":0.00006594488,"about_ca_system_score_gemma":0.000031468695,"threshold_uncertainty_score":0.9998934},"labels":[],"label_agreement":null},{"id":"W4387666804","doi":"10.1007/s44245-023-00025-4","title":"Interpolating across the impedance/admittance spectrum with Unified Interaction Control","year":2023,"lang":"en","type":"article","venue":"Discover Mechanical Engineering","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Admittance; Control theory (sociology); Controller (irrigation); Interpolation (computer graphics); Stability (learning theory); Electrical impedance; Weighting; Computer science; Hexapod; Impedance control; Robot; Control engineering; Control (management); Engineering; Physics; Acoustics; Telecommunications; Artificial intelligence","score_opus":0.01060152039817598,"score_gpt":0.2392186186866892,"score_spread":0.22861709828851323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387666804","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31963134,0.000043333413,0.67738175,0.00026896794,0.0008399213,0.00020671687,0.000002841411,0.0012810003,0.00034411915],"genre_scores_gemma":[0.99937373,0.000011270972,0.00016160637,0.000052858133,0.00019396438,0.000034207307,0.000009406047,0.000068035355,0.00009488986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998944,0.00001774481,0.00023439956,0.00019335382,0.00018866235,0.00042183595],"domain_scores_gemma":[0.9994786,0.00017133696,0.000036658384,0.00023177022,0.000013678875,0.00006799489],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022024574,0.00019757479,0.00018225233,0.000056715882,0.00010388029,0.00012532828,0.00017464354,0.000059647584,0.000032583932],"category_scores_gemma":[0.00007073551,0.00014563349,0.00006879528,0.00046482947,0.000011471151,0.0002947549,0.00003908701,0.00045988226,0.000089612826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017069582,0.0000030301587,0.000109650944,0.00002868672,0.000047679343,0.0000088232,0.0003939445,0.9876019,0.0074849566,0.003568538,0.000040547995,0.000695174],"study_design_scores_gemma":[0.0003989694,0.000027548904,0.002089267,0.00008915909,0.000010713839,0.000011807575,0.00042538374,0.9940655,0.0016510863,0.000047324113,0.0009776838,0.00020552031],"about_ca_topic_score_codex":0.00001153417,"about_ca_topic_score_gemma":0.000024841453,"teacher_disagreement_score":0.67974246,"about_ca_system_score_codex":0.00007896181,"about_ca_system_score_gemma":0.000007627826,"threshold_uncertainty_score":0.5938761},"labels":[],"label_agreement":null},{"id":"W4388015779","doi":"10.1007/s44245-023-00027-2","title":"Development and performance assessment of a new opensource Bayesian inference R platform for building energy model calibration","year":2023,"lang":"en","type":"article","venue":"Discover Mechanical Engineering","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Qatar National Research Fund","keywords":"Calibration; Building energy simulation; Sensitivity (control systems); Computer science; Bayesian inference; Markov chain Monte Carlo; Inference; Process (computing); Bayesian probability; Monte Carlo method; Uncertainty analysis; Energy consumption; Energy (signal processing); Reliability engineering; Data mining; Machine learning; Simulation; Artificial intelligence; Engineering; Energy performance; Statistics; Mathematics","score_opus":0.02058129943858256,"score_gpt":0.2429587738817574,"score_spread":0.22237747444317485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388015779","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25371203,0.000012533833,0.74593604,0.000008036431,0.000073600815,0.0000586336,0.0000027175354,0.00017234359,0.000024044368],"genre_scores_gemma":[0.87421703,0.000041662228,0.12555465,0.000009282754,0.000024771758,0.00004304892,0.000032547534,0.000031126125,0.0000458902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930406,0.0000014818243,0.00023115323,0.00014308552,0.00012168178,0.00019855771],"domain_scores_gemma":[0.9997507,0.000038634244,0.000025845196,0.00010104484,0.000011595481,0.00007220259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009513422,0.0001351473,0.00015752553,0.00010131021,0.000039056547,0.000030096142,0.00009269763,0.0000754861,0.0000022714069],"category_scores_gemma":[0.000013472983,0.00013995546,0.000027701557,0.00019266825,0.0000037401276,0.00028685367,0.00005319254,0.00006795463,6.877819e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004119478,0.0000037243628,0.000013209209,0.000088074885,0.000020612879,1.9280293e-7,0.000094839874,0.9432752,0.006532014,0.045044612,0.00001521966,0.004908164],"study_design_scores_gemma":[0.00021377896,0.000018337758,0.000064196356,0.000078833116,0.000008300041,7.160901e-7,0.000011542765,0.9679398,0.030938795,0.00033071553,0.00023111215,0.00016386535],"about_ca_topic_score_codex":0.000004690305,"about_ca_topic_score_gemma":0.0000035267376,"teacher_disagreement_score":0.620505,"about_ca_system_score_codex":0.000045907043,"about_ca_system_score_gemma":0.00004977143,"threshold_uncertainty_score":0.5707218},"labels":[],"label_agreement":null},{"id":"W4400915292","doi":"10.1007/s44245-024-00053-8","title":"From da Vinci to cybersecurity: tracing the evolution of autonomous vehicles and ensuring safe platooning operations","year":2024,"lang":"en","type":"article","venue":"Discover Mechanical Engineering","topic":"Traffic control and management","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of Waterloo","funders":"","keywords":"Platoon; Computer security; Safeguarding; Harmonization; Computer science; Law enforcement; Eavesdropping; Control (management); Law; Political science","score_opus":0.005130182479844161,"score_gpt":0.18995352079643157,"score_spread":0.18482333831658743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400915292","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66579837,0.0014378276,0.33146247,0.00014474751,0.0004992576,0.00017464808,0.00003147084,0.00033056558,0.00012066637],"genre_scores_gemma":[0.9984449,0.000018050718,0.0012848829,0.000012607297,0.00015172391,0.000031672826,0.0000051637485,0.000032601998,0.000018358285],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921393,0.0000081812905,0.00023840278,0.00020170838,0.00013351774,0.00020423625],"domain_scores_gemma":[0.9996396,0.00010937739,0.0000065995955,0.00016665953,0.000008841107,0.00006897412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014272086,0.00015029454,0.00016644703,0.0000906383,0.00004849617,0.00012829067,0.00011143082,0.00004840513,0.00001176634],"category_scores_gemma":[0.000030883093,0.00012665051,0.000058281046,0.00016585649,0.000008042519,0.00019322244,0.0000813537,0.00018268892,0.000007446585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000275174,0.000005274711,0.0000020803782,0.000075294614,0.000089297755,0.000006090501,0.0009605958,0.9005191,0.057317402,0.034636825,0.000022279648,0.006363014],"study_design_scores_gemma":[0.00013484406,0.000015677744,0.00059181475,0.0002165059,0.00005525382,0.0000023913658,0.0003449138,0.99422437,0.0027823546,0.00018239515,0.0012829913,0.00016648558],"about_ca_topic_score_codex":0.00023705809,"about_ca_topic_score_gemma":0.00010462898,"teacher_disagreement_score":0.33264658,"about_ca_system_score_codex":0.00014238429,"about_ca_system_score_gemma":0.00001628485,"threshold_uncertainty_score":0.5164658},"labels":[],"label_agreement":null},{"id":"W4406703370","doi":"10.1007/s44245-024-00085-0","title":"A coupled non-orthogonal hypoelastic constitutive model for woven fabrics","year":2025,"lang":"en","type":"article","venue":"Discover Mechanical Engineering","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Constitutive equation; Computer science; Engineering; Structural engineering; Finite element method","score_opus":0.016596392067864413,"score_gpt":0.26424601348944177,"score_spread":0.24764962142157734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406703370","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22064513,0.00002065092,0.77765554,0.00008507281,0.0008555705,0.0003335685,0.00016904507,0.00008392429,0.000151464],"genre_scores_gemma":[0.9887313,0.0000030845217,0.010554964,0.00012911597,0.000070831156,0.00022438496,0.000026297907,0.000017602195,0.00024238229],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887115,0.000009617089,0.00030597462,0.00030843363,0.000177371,0.00032743387],"domain_scores_gemma":[0.99940807,0.00019758733,0.00004662411,0.00020004876,0.00007367064,0.00007398621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030319567,0.00017162878,0.00026536075,0.00006954858,0.00010296544,0.00011203802,0.00019680419,0.00008592047,0.00010500616],"category_scores_gemma":[0.0003966318,0.00016022146,0.00009657378,0.00013365412,0.000028948896,0.00017143911,0.00011052445,0.00007411052,0.00003831354],"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":[0.000030647578,0.00003094436,0.0000013577712,0.00005561268,0.000013305868,8.48514e-7,0.000039370017,0.34413892,0.520428,0.13510473,0.00010028565,0.000055987803],"study_design_scores_gemma":[0.000577259,0.000024474217,0.00005452304,0.0000776272,0.000058394427,0.0000012256396,0.000015703481,0.9592813,0.034942303,0.0046343966,0.00015783521,0.00017495187],"about_ca_topic_score_codex":0.0000074630807,"about_ca_topic_score_gemma":0.000005038685,"teacher_disagreement_score":0.7680862,"about_ca_system_score_codex":0.0000758998,"about_ca_system_score_gemma":0.00020579732,"threshold_uncertainty_score":0.6533642},"labels":[],"label_agreement":null},{"id":"W4414612577","doi":"10.1007/s44245-025-00130-6","title":"Hydrodynamic lubrication effects in textured PEEK surfaces for friction reduction","year":2025,"lang":"en","type":"article","venue":"Discover Mechanical Engineering","topic":"Tribology and Wear Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Engineering and Physical Sciences Research Council","keywords":"Peek; Lubrication; Reduction (mathematics); Surface roughness; Surface finish; Texture (cosmology)","score_opus":0.002648560072707319,"score_gpt":0.20458343422876538,"score_spread":0.20193487415605807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414612577","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36577702,0.00042443545,0.6322898,0.000079196536,0.00081134564,0.00025829996,0.000004207091,0.00025109833,0.00010457153],"genre_scores_gemma":[0.9985162,0.000043956883,0.0011357877,0.000007989311,0.000041173767,0.000098440156,0.00003738648,0.000018693614,0.000100381396],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993497,0.000012846972,0.00019303783,0.00018505598,0.00006157403,0.00019778438],"domain_scores_gemma":[0.9997124,0.00009484294,0.000014848597,0.00013804504,0.000013721316,0.000026139338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012569719,0.00012843027,0.00018748194,0.00021638311,0.000030083287,0.00001797722,0.000080373306,0.00013397115,0.0000034828731],"category_scores_gemma":[0.000081231585,0.00013699029,0.00008471044,0.0004389192,0.0000050999574,0.00014455977,0.000013280239,0.00015766053,0.0000044791223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000138458045,0.000021725773,0.000051141687,0.00014755563,0.00007235933,8.018629e-7,0.00003674329,0.80636865,0.18483137,0.006444129,0.0001185228,0.0018931654],"study_design_scores_gemma":[0.00037090908,0.000016211168,0.0022764632,0.000056500776,0.000053949225,0.0000011362386,0.000015452313,0.96727574,0.028367225,0.0010867167,0.00034459948,0.00013507421],"about_ca_topic_score_codex":0.000015599353,"about_ca_topic_score_gemma":0.000017533159,"teacher_disagreement_score":0.6327392,"about_ca_system_score_codex":0.00012864581,"about_ca_system_score_gemma":0.000008919486,"threshold_uncertainty_score":0.55863017},"labels":[],"label_agreement":null}]}