{"meta":{"query_hash":"069b72d88d68","filters":{"venue":"Archives of Advanced Engineering Science"},"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/069b72d88d68","api":"https://metacan.xera.ac/api/v1/cohort?venue=Archives+of+Advanced+Engineering+Science"},"results":[{"id":"W4385729047","doi":"10.47852/bonviewaaes32021329","title":"Tire Wear and Pollutants: An Overview of Research","year":2023,"lang":"en","type":"article","venue":"Archives of Advanced Engineering Science","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Natural rubber; Microplastics; Materials science; Environmental science; Automotive engineering; Forensic engineering; Composite material; Engineering","score_opus":0.042877282387636904,"score_gpt":0.3408073105638372,"score_spread":0.2979300281762003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385729047","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":[0.99799997,0.0008910604,0.0001544753,0.000018958752,0.000080843005,0.00006671466,0.000015575084,0.00013782905,0.00063458085],"genre_scores_gemma":[0.9906529,0.0027143,0.0065639457,0.0000013107997,0.000014073215,0.000003816737,7.015415e-7,0.000013508454,0.00003544662],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911505,0.000006536407,0.00015229805,0.00015362943,0.00025852091,0.00031394145],"domain_scores_gemma":[0.9994536,0.00014759757,0.00001395079,0.00024792165,0.000023007113,0.00011394281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034037765,0.00007658635,0.00012453133,0.0004222972,0.00006890564,0.000009657129,0.00028828703,0.000015901021,0.00000459902],"category_scores_gemma":[0.00010396348,0.000073211806,0.000016885364,0.0012810065,0.00030939293,0.00032065494,0.00009167926,0.00012934912,0.0000025153245],"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":[0.0000037498135,0.0000053734875,0.0002534514,0.0002954351,0.0000028581876,0.0000014144052,0.0009085393,0.18118039,0.7149171,0.0014958517,0.0000034429036,0.100932375],"study_design_scores_gemma":[0.00016404531,0.00010500466,0.07185613,0.0004477622,0.0000015703439,0.0000050935755,0.00029257665,0.81581795,0.11006951,0.0003657787,0.0007301472,0.00014440008],"about_ca_topic_score_codex":0.0000021675633,"about_ca_topic_score_gemma":4.203615e-7,"teacher_disagreement_score":0.6346376,"about_ca_system_score_codex":0.000008127696,"about_ca_system_score_gemma":0.000025274521,"threshold_uncertainty_score":0.2985491},"labels":[],"label_agreement":null},{"id":"W4387817937","doi":"10.47852/bonviewaaes32021471","title":"Machine Learning Insights into Hypersonics Research Evolution: A 21st Century Perspective","year":2023,"lang":"en","type":"article","venue":"Archives of Advanced Engineering Science","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","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":"Defence Research and Development Canada; National Research Council Canada","funders":"","keywords":"Data science; Field (mathematics); Computer science; Management science; Engineering","score_opus":0.012927668261380762,"score_gpt":0.28796640287966624,"score_spread":0.2750387346182855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387817937","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10525898,0.0027525157,0.8770429,0.0007124955,0.0011191977,0.00043439932,0.0000015540977,0.0014809651,0.0111970175],"genre_scores_gemma":[0.86644685,0.00033440816,0.13304359,0.0000053338704,0.000053165873,0.000014066506,0.0000013236927,0.000019434805,0.00008184476],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99707484,0.00010621962,0.0002566603,0.0007780137,0.0010137593,0.00077051664],"domain_scores_gemma":[0.9977756,0.0010794897,0.00009392929,0.0006372073,0.00022222655,0.00019154178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091406633,0.0001977996,0.00022885414,0.0014712824,0.0007199269,0.00009265868,0.002159531,0.000037700527,0.000001940626],"category_scores_gemma":[0.0031790098,0.00019926,0.00007611482,0.005502641,0.0007082965,0.0011605403,0.0013914558,0.00087104074,0.000026360934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006192357,0.000012656091,0.0002018593,0.000023825412,0.0000058220185,0.000009228556,0.008522452,0.62851286,0.037300315,0.31762242,7.5342484e-7,0.007781574],"study_design_scores_gemma":[0.00028855668,0.00014389132,0.005534539,0.0001165641,0.0000021979636,0.000008221606,0.0026152444,0.97392786,0.0021466739,0.013470864,0.0014912947,0.0002541159],"about_ca_topic_score_codex":0.000059800637,"about_ca_topic_score_gemma":0.0000032217374,"teacher_disagreement_score":0.76118785,"about_ca_system_score_codex":0.00024695875,"about_ca_system_score_gemma":0.00027624718,"threshold_uncertainty_score":0.8125587},"labels":[],"label_agreement":null},{"id":"W4392963434","doi":"10.47852/bonviewaaes42022009","title":"A Digital Twin Development Framework for an Electrical Submersible Pump (ESP)","year":2024,"lang":"en","type":"article","venue":"Archives of Advanced Engineering Science","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Memorial University of Newfoundland","keywords":"Multiphysics; Stator; Transient (computer programming); Rotor (electric); Heat transfer; Predictive maintenance; Time domain; Mechanical engineering; Engineering; Computer science; Mechanics; Reliability engineering; Structural engineering; Finite element method; Physics","score_opus":0.007580810579944385,"score_gpt":0.23116060129819943,"score_spread":0.22357979071825504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392963434","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11997507,0.000701828,0.8780477,0.0000073731953,0.00013973391,0.00013171279,0.0000048035668,0.00038455988,0.00060719176],"genre_scores_gemma":[0.7552906,0.00003393389,0.24451855,0.0000031172094,0.00003611478,0.000029147053,0.0000035872747,0.000024276618,0.00006064529],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988342,0.0000022502572,0.00020943276,0.00029105775,0.00021393903,0.00044911006],"domain_scores_gemma":[0.9993139,0.0003255099,0.00001288077,0.00018210281,0.000017176106,0.00014842278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011308156,0.00015308599,0.00016754014,0.00048840983,0.000058573452,0.000102475235,0.0003535599,0.000027686829,0.0000023686803],"category_scores_gemma":[0.0001311004,0.00015112113,0.000074712865,0.001172482,0.0000730442,0.000512133,0.000022727596,0.00014980423,0.0000032977803],"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":[0.000007916871,0.000020724387,0.00005132196,0.00016174176,0.000042528223,0.0000028900345,0.00056024955,0.22025968,0.22254421,0.011824948,0.0000057735374,0.544518],"study_design_scores_gemma":[0.00007934555,0.00009732529,0.000629426,0.0001302839,0.000010452869,0.0000044067324,0.000010656061,0.89885634,0.09558573,0.0020556746,0.0022846996,0.00025567165],"about_ca_topic_score_codex":2.2398115e-7,"about_ca_topic_score_gemma":1.469037e-7,"teacher_disagreement_score":0.6785966,"about_ca_system_score_codex":0.00005152127,"about_ca_system_score_gemma":0.000080484555,"threshold_uncertainty_score":0.61625403},"labels":[],"label_agreement":null},{"id":"W4394958701","doi":"10.47852/bonviewaaes42022765","title":"Using SMART Method for Multi-criteria Decision Making: Applications, Advantages, and Limitations","year":2024,"lang":"en","type":"article","venue":"Archives of Advanced Engineering Science","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","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":"University Canada West","funders":"","keywords":"Computer science; Risk analysis (engineering); Business","score_opus":0.16807156742400034,"score_gpt":0.48596069073795467,"score_spread":0.31788912331395436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394958701","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023030488,0.0016246235,0.97382236,0.000038158527,0.0006242195,0.0005692371,0.000050527677,0.00010771121,0.00013269448],"genre_scores_gemma":[0.3837804,0.00004434662,0.61602145,0.000016732185,0.0000350871,0.000050083123,0.000001132208,0.000020173775,0.000030616386],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969131,0.000046212303,0.0008045085,0.0008984725,0.00085942866,0.00047832995],"domain_scores_gemma":[0.9838811,0.0149274375,0.00015055593,0.0006676461,0.00018673508,0.00018651495],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002569495,0.00022796994,0.00034274367,0.00145879,0.000278486,0.00044427745,0.00095588755,0.000039216986,0.000006608013],"category_scores_gemma":[0.011100995,0.0001972686,0.00012339371,0.0017625296,0.00031630913,0.0013272723,0.00037565053,0.00013675899,0.0000053462977],"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":[0.000027238722,0.00002596193,0.0001342542,0.000053601714,0.000006660962,0.0000013749054,0.0007096353,0.041908104,0.29263464,0.011217261,0.000012971774,0.6532683],"study_design_scores_gemma":[0.00026016243,0.000034899193,0.005558982,0.0003501489,0.00001288545,0.00003395692,0.00030473733,0.96170163,0.0040430287,0.013764426,0.0136996135,0.0002355144],"about_ca_topic_score_codex":0.0000010963856,"about_ca_topic_score_gemma":0.0000013521889,"teacher_disagreement_score":0.91979355,"about_ca_system_score_codex":0.000041563737,"about_ca_system_score_gemma":0.00011158386,"threshold_uncertainty_score":0.9972289},"labels":[],"label_agreement":null},{"id":"W4402245056","doi":"10.47852/bonviewaaes42023106","title":"Analysis of the Effects of Wheel Spacers on the Roll Stability of the Vehicle","year":2024,"lang":"en","type":"article","venue":"Archives of Advanced Engineering Science","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Stability (learning theory); Automotive engineering; Materials science; Engineering; Computer science","score_opus":0.002139383735326912,"score_gpt":0.17689607614589936,"score_spread":0.17475669241057246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402245056","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":[0.9959852,0.00036360175,0.0025348524,0.000051620435,0.00029505268,0.00020680278,0.000018380437,0.000026257205,0.00051820365],"genre_scores_gemma":[0.99980485,0.000022659167,0.00013747759,0.0000025996528,0.0000056439094,0.000008563737,1.31636e-7,0.000009361279,0.000008724663],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991122,0.000022536746,0.00024444613,0.00014459212,0.00031002512,0.00016619128],"domain_scores_gemma":[0.99845076,0.00087016803,0.00006079376,0.00056812156,0.00002459769,0.000025573185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025607046,0.00009984627,0.0002280614,0.0001402356,0.000035273744,0.000008509437,0.0006322746,0.000014730621,0.000001178421],"category_scores_gemma":[0.00025476265,0.00005364707,0.00021351453,0.001462126,0.00032887002,0.00006826254,0.00008066617,0.00012581128,1.0441725e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002409741,0.000005411862,0.00089009607,0.00019498864,0.00006664806,6.268878e-8,0.0004735052,0.53669775,0.4581161,0.0025145456,2.3320227e-7,0.001038252],"study_design_scores_gemma":[0.000064479944,0.000026132326,0.085505955,0.00023515915,0.000056798068,1.3169816e-7,0.00006205571,0.7618455,0.15204935,0.0000983195,0.000009736947,0.000046367084],"about_ca_topic_score_codex":0.000016242215,"about_ca_topic_score_gemma":0.000008761611,"teacher_disagreement_score":0.30606675,"about_ca_system_score_codex":0.00002305232,"about_ca_system_score_gemma":0.00003116907,"threshold_uncertainty_score":0.21876639},"labels":[],"label_agreement":null},{"id":"W4403594251","doi":"10.47852/bonviewaaes42023902","title":"Unveiling Weak Signals of Emergence in Underwater Sensing Research Trends","year":2024,"lang":"en","type":"article","venue":"Archives of Advanced Engineering Science","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; National Research Council Canada","funders":"","keywords":"Underwater; Geography; Remote sensing; Archaeology","score_opus":0.12537371336303385,"score_gpt":0.43681542485037456,"score_spread":0.3114417114873407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403594251","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":[0.7635034,0.0024213698,0.22082819,0.00010719593,0.0007866406,0.00014373744,0.0000073262595,0.00006703139,0.012135153],"genre_scores_gemma":[0.9668243,0.000013536786,0.032419253,0.0000020344614,0.000028970631,0.0000018858815,1.4272374e-7,0.000012041061,0.0006978194],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955438,0.000089200315,0.0009856197,0.00070121896,0.0020962113,0.0005839694],"domain_scores_gemma":[0.9938604,0.005113708,0.00009713025,0.0006180935,0.00019464122,0.00011597418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054296367,0.00013848535,0.00035028535,0.0040389095,0.00010970178,0.00014557084,0.0010878191,0.00002497517,0.000071707545],"category_scores_gemma":[0.0029815328,0.00010778841,0.000112455105,0.0073825256,0.00052358845,0.0006008393,0.0004401257,0.00025808215,0.000016007649],"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":[0.00001007121,0.000008923373,0.00015673693,0.000030067598,0.0000024079184,0.000009267581,0.0013736496,0.34480208,0.5304576,0.010542073,0.000028779465,0.1125783],"study_design_scores_gemma":[0.0001595165,0.000101467,0.012090636,0.0011379705,0.0000018507293,0.000017046776,0.0017872747,0.8697506,0.06334188,0.04903988,0.002342827,0.0002290289],"about_ca_topic_score_codex":0.00002440011,"about_ca_topic_score_gemma":0.000012168104,"teacher_disagreement_score":0.52494854,"about_ca_system_score_codex":0.000028655095,"about_ca_system_score_gemma":0.00014087661,"threshold_uncertainty_score":0.43954837},"labels":[],"label_agreement":null}]}