{"meta":{"query_hash":"56e305dcf027","filters":{"venue":"Modelling—International Open Access Journal of Modelling in Engineering Science"},"cohort_total":27,"direct_labels_cover":0,"predictions_cover":27,"exported":27,"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/56e305dcf027","api":"https://metacan.xera.ac/api/v1/cohort?venue=Modelling%E2%80%94International+Open+Access+Journal+of+Modelling+in+Engineering+Science"},"results":[{"id":"W3092694218","doi":"10.3390/modelling1020008","title":"A New Approach to Exploring the Relationship between Weather Phenomenon and Truck Traffic Volume in the Cold Region Highway Network","year":2020,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Regina","funders":"","keywords":"Snow; Truck; Traffic volume; Transport engineering; Meteorology; Environmental science; Volume (thermodynamics); Climatology; Computer science; Geography; Engineering; Automotive engineering; Geology","score_opus":0.18235846891265575,"score_gpt":0.3041748422387023,"score_spread":0.12181637332604653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092694218","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27349842,0.00052262127,0.71833754,0.0004224868,0.000031962907,0.00013818481,0.001041751,0.0001691278,0.0058379094],"genre_scores_gemma":[0.9098962,0.00054534985,0.08742719,0.0000502545,0.00009285945,0.00016990148,0.00046477173,0.00003235596,0.0013210437],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992005,0.0003644943,0.000048209175,0.00019777546,0.00012536414,0.00006361597],"domain_scores_gemma":[0.99736017,0.0017859873,0.0004061864,0.0002008162,0.00018755975,0.000059250022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010922229,0.0006524303,0.00062712235,0.002420643,0.0004001336,0.0012915332,0.00075482886,0.00043458928,0.0010221389],"category_scores_gemma":[0.0040114876,0.0003574222,0.00097463094,0.0022057635,0.0004952203,0.0017544265,0.0008903587,0.0009987544,0.00006893712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003217929,0.000549843,0.20638761,0.00048965606,0.0009010019,0.00060818094,0.0020534077,0.56115884,0.012845446,0.09923092,0.0014290748,0.11402418],"study_design_scores_gemma":[0.000014572481,0.00026997778,0.06287936,0.000039917315,0.00010947399,0.00019106083,0.0006133136,0.88448024,0.001986363,0.046165783,0.0031802834,0.00006959068],"about_ca_topic_score_codex":0.0058883606,"about_ca_topic_score_gemma":0.006044619,"teacher_disagreement_score":0.0058883606,"about_ca_system_score_codex":0.0006383768,"about_ca_system_score_gemma":0.00073278195,"threshold_uncertainty_score":0.0117082},"labels":[],"label_agreement":null},{"id":"W3096234675","doi":"10.3390/modelling1020010","title":"Stochastic Earthmoving Fleet Arrangement Optimization Considering Project Duration and Cost","year":2020,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"BIM and Construction Integration","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Duration (music); Operations research; Resource (disambiguation); Engineering; Cost estimate; Industrial engineering; Project management; Estimation; Computer science; Systems engineering","score_opus":0.07008758711287291,"score_gpt":0.3040871298391307,"score_spread":0.2339995427262578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096234675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6110917,0.0004164301,0.37904868,0.00036037905,0.000032071148,0.00014297798,0.00039704592,0.00018401787,0.008326692],"genre_scores_gemma":[0.9777868,0.00016956459,0.019073525,0.000021750846,0.0000057452744,0.00009392177,0.00017829443,0.000030688472,0.0026397635],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952996,0.00019716145,0.0000163956,0.000081454615,0.000059879916,0.00011502466],"domain_scores_gemma":[0.9989899,0.00060837495,0.00014687487,0.00004063508,0.00010020984,0.00011415296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012824233,0.0009151829,0.0009899216,0.00078975275,0.00041400065,0.0011333714,0.0008548745,0.0010586375,0.0022981896],"category_scores_gemma":[0.0020216617,0.0006780434,0.00094270706,0.0008808765,0.000501041,0.0010564991,0.0007453699,0.0007378475,0.00015993664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001077895,0.000005689405,0.0001637068,0.0000046145274,0.000003876553,0.000014231512,0.000002859007,0.9986786,0.000081501355,0.00029478862,0.000024563316,0.00071479887],"study_design_scores_gemma":[0.0000029705063,0.000018527284,0.00019521211,0.0000017945797,0.0000039073725,0.0000056872923,0.000009352861,0.99932694,0.00006091356,0.00031784203,0.0000545008,0.0000023786429],"about_ca_topic_score_codex":0.012928045,"about_ca_topic_score_gemma":0.009230378,"teacher_disagreement_score":0.012928045,"about_ca_system_score_codex":0.001457519,"about_ca_system_score_gemma":0.0016430957,"threshold_uncertainty_score":0.025705576},"labels":[],"label_agreement":null},{"id":"W3121841706","doi":"10.3390/modelling2010003","title":"Data Driven Modelling of Nuclear Power Plant Performance Data as Finite State Machines","year":2021,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nuclear power plant; Cluster analysis; Representation (politics); Computer science; Linear discriminant analysis; Feature (linguistics); Multivariable calculus; Finite-state machine; Principal component analysis; Data mining; Artificial intelligence; Machine learning; Control engineering; Algorithm; Engineering","score_opus":0.12741992646403963,"score_gpt":0.3558295882909587,"score_spread":0.22840966182691905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121841706","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10225769,0.00016010542,0.89000934,0.00033176673,0.000062573046,0.00013317316,0.0021779248,0.0022963032,0.0025710019],"genre_scores_gemma":[0.88712513,0.00024129207,0.10819729,0.000048438105,0.000022350641,0.00027287143,0.002317352,0.000092611415,0.0016826079],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955827,0.00011543782,0.000039733175,0.00011704086,0.00014443179,0.000025117326],"domain_scores_gemma":[0.99855167,0.0008815174,0.0001365858,0.00018904448,0.000216329,0.000024889854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070468365,0.0005935192,0.00046998364,0.0007339998,0.00024383357,0.0012226112,0.0008594262,0.00062329863,0.0015270225],"category_scores_gemma":[0.0031117243,0.00028099483,0.0006845326,0.0008046052,0.0004448114,0.0010355277,0.00041302622,0.0011987768,0.0004407186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005259652,0.00006490153,0.0027536377,0.0000808242,0.000029456121,0.00010633222,0.00012418923,0.9641782,0.0036905513,0.0071627204,0.0005726811,0.021183938],"study_design_scores_gemma":[0.0000016017057,0.000011951281,0.00051122386,0.0000040909176,0.000002458762,0.000016813714,0.000012250157,0.9954756,0.0010143202,0.00249442,0.00045003148,0.000005288959],"about_ca_topic_score_codex":0.0066097984,"about_ca_topic_score_gemma":0.0064739524,"teacher_disagreement_score":0.0066097984,"about_ca_system_score_codex":0.0006443187,"about_ca_system_score_gemma":0.0006880984,"threshold_uncertainty_score":0.013142645},"labels":[],"label_agreement":null},{"id":"W3154470020","doi":"10.3390/modelling2020013","title":"A Tutorial on Fire Domino Effect Modeling Using Bayesian Networks","year":2021,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Domino effect; Bayesian network; Computer science; Domino; Dynamic Bayesian network; Event (particle physics); SLCO1B1; Bayesian probability; Event tree; Pooling; Event tree analysis; Fault tree analysis; Probabilistic logic; Machine learning; Influence diagram; Artificial intelligence; Data mining; Reliability engineering; Decision tree; Engineering","score_opus":0.14631843561436547,"score_gpt":0.42979494767854676,"score_spread":0.2834765120641813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154470020","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":[0.0014180482,0.036750045,0.9270713,0.0015892673,0.00072836736,0.00014572432,0.0008993407,0.0007773924,0.030620597],"genre_scores_gemma":[0.04960303,0.16665865,0.71881646,0.0015491829,0.0038502188,0.0010540236,0.0028978037,0.0006378574,0.054932907],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968076,0.000119794066,0.000028309887,0.0000571272,0.00009477557,0.000019232471],"domain_scores_gemma":[0.9993818,0.00047593535,0.00003152104,0.000023947718,0.00006638556,0.000020416519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086136267,0.0018936413,0.0008953626,0.0013841003,0.00037086252,0.0013462866,0.00127182,0.0016399926,0.016698118],"category_scores_gemma":[0.0023886985,0.0008898218,0.0014104291,0.0018543933,0.0004755056,0.0026188341,0.0009835974,0.0020601253,0.0053441254],"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":[0.000073817806,0.00019181742,0.0008366013,0.001805989,0.00016293926,0.0010049902,0.00038234517,0.20656204,0.004431527,0.3492869,0.08454898,0.35071203],"study_design_scores_gemma":[0.0000159737,0.00010254349,0.00077363045,0.00086019374,0.000060915885,0.00085869874,0.00006728231,0.25875095,0.0011783727,0.33409286,0.4031513,0.00008729444],"about_ca_topic_score_codex":0.0027240175,"about_ca_topic_score_gemma":0.0026199142,"teacher_disagreement_score":0.016698118,"about_ca_system_score_codex":0.0007898268,"about_ca_system_score_gemma":0.00059576525,"threshold_uncertainty_score":0.055860758},"labels":[],"label_agreement":null},{"id":"W3204730924","doi":"10.3390/modelling2040022","title":"Quantifying the Impact of Inspection Processes on Production Lines through Stochastic Discrete-Event Simulation Modeling","year":2021,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Discrete event simulation; Flexibility (engineering); Production line; Computer science; Quality (philosophy); Production (economics); Reliability engineering; Probabilistic logic; Event (particle physics); Industrial engineering; Discrete manufacturing; Productivity; Key (lock); Overall equipment effectiveness; Manufacturing engineering; Engineering; Simulation; Artificial intelligence","score_opus":0.10582274452256493,"score_gpt":0.3842283926728565,"score_spread":0.27840564815029156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204730924","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23314996,0.00022911116,0.7576138,0.00028483462,0.00003067541,0.00017094707,0.00036312777,0.00040414574,0.0077534406],"genre_scores_gemma":[0.97471935,0.00016816743,0.02353336,0.000024850799,0.0000068510863,0.000111798676,0.00014157957,0.00002403748,0.001269998],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988412,0.0004969874,0.00005539932,0.0001355795,0.0003212019,0.00014959415],"domain_scores_gemma":[0.9962451,0.0027666874,0.0004417706,0.00019830199,0.0002521934,0.000095826035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016516305,0.00088105944,0.00068676414,0.0007253388,0.0003846566,0.0014097012,0.0010708026,0.0011010672,0.0013347879],"category_scores_gemma":[0.004228111,0.00043786527,0.0009715308,0.000655961,0.00065287657,0.00088421244,0.00071235705,0.00086772133,0.00014094704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007365878,0.0000086336795,0.00027839615,0.000004791784,0.000003769064,0.000009596805,0.000004806599,0.99786025,0.0001983755,0.0010817996,0.000013281751,0.000528849],"study_design_scores_gemma":[0.0000019407655,0.000009458874,0.00008946387,0.0000012127131,0.0000030134079,0.000002491769,0.0000026433129,0.9991437,0.00015475893,0.000541867,0.000047577705,0.0000017437573],"about_ca_topic_score_codex":0.012464541,"about_ca_topic_score_gemma":0.0050821416,"teacher_disagreement_score":0.012464541,"about_ca_system_score_codex":0.0015437094,"about_ca_system_score_gemma":0.0010951213,"threshold_uncertainty_score":0.024784029},"labels":[],"label_agreement":null},{"id":"W3212368723","doi":"10.3390/modelling2040032","title":"Generation of Custom Textual Model Editors","year":2021,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Model-Driven Software Engineering Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Personalization; Code generation; Domain (mathematical analysis); Software engineering; Architecture; Text generation; Formalism (music); Programming language; Software; Model-driven architecture; World Wide Web; Artificial intelligence; Software development; Key (lock)","score_opus":0.10477857511016209,"score_gpt":0.35143892698897633,"score_spread":0.24666035187881424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212368723","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":[0.014377388,0.000077852645,0.94000256,0.00023958883,0.00032137657,0.00034782276,0.0019116878,0.033392202,0.009329568],"genre_scores_gemma":[0.13945968,0.00027782607,0.8170621,0.00028752378,0.00010526791,0.00072475366,0.008119454,0.01467394,0.01928938],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987072,0.00027096143,0.00017912294,0.0002544695,0.0005255291,0.00006273252],"domain_scores_gemma":[0.99141824,0.0030806481,0.0004274567,0.003032546,0.0018063987,0.00023472022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028335534,0.0009574422,0.0005197681,0.0011253554,0.0003903515,0.0019008177,0.0018861091,0.0010998155,0.01121304],"category_scores_gemma":[0.012248253,0.00083268865,0.0011366544,0.00049399823,0.0005382592,0.0024152396,0.00240786,0.0014705943,0.0039186818],"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":[0.0008222082,0.0008191073,0.0053363293,0.0025519666,0.00029639064,0.003398701,0.0042350516,0.10008477,0.21919884,0.16342624,0.09906564,0.40076485],"study_design_scores_gemma":[0.00027642696,0.00015276409,0.0006855447,0.00019680354,0.0001709676,0.00090983155,0.0002582004,0.5114664,0.15390837,0.025946314,0.30589622,0.00013214856],"about_ca_topic_score_codex":0.0004764137,"about_ca_topic_score_gemma":0.0007894111,"teacher_disagreement_score":0.01121304,"about_ca_system_score_codex":0.00055973144,"about_ca_system_score_gemma":0.0008023129,"threshold_uncertainty_score":0.03751135},"labels":[],"label_agreement":null},{"id":"W4318484728","doi":"10.3390/modelling4010005","title":"Off-Design Analysis Method for Compressor Fouling Fault Diagnosis of Helicopter Turboshaft Engine","year":2023,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Turbomachinery Performance and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Mitacs; University of Windsor","keywords":"Gas compressor; Fouling; Airfoil; Turbojet; Fault (geology); Range (aeronautics); Environmental science; Computational fluid dynamics; Automotive engineering; Turbine; Marine engineering; Inlet; Axial compressor; Flow (mathematics); Mechanical engineering; Engineering; Structural engineering; Aerospace engineering; Mechanics; Geology","score_opus":0.07817598003781864,"score_gpt":0.3709502321602065,"score_spread":0.29277425212238783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318484728","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":[0.087835036,0.0003170971,0.9066956,0.00006645683,0.000043566662,0.00007702366,0.00007335252,0.001295532,0.003596355],"genre_scores_gemma":[0.8829329,0.0001336826,0.11408002,0.000039488285,0.000011817869,0.00010328409,0.00011557411,0.00007339313,0.0025098452],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984074,0.000039787752,0.000009154352,0.00002562641,0.00006726447,0.000017374128],"domain_scores_gemma":[0.99966085,0.0001351923,0.000049074293,0.000026719781,0.000113067654,0.000015054122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037889375,0.0005970966,0.0004410374,0.0006622605,0.00032561613,0.0004344178,0.00035475852,0.0006437077,0.0024124861],"category_scores_gemma":[0.00081852847,0.0002397289,0.00044993905,0.00017950845,0.00018701922,0.0002541232,0.00027472066,0.00033752347,0.00039210104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004703989,0.00020623693,0.0048870314,0.0003168613,0.000064976266,0.00026372005,0.00018334505,0.6467274,0.0693145,0.0017086973,0.0015973982,0.27425942],"study_design_scores_gemma":[0.000004767096,0.00005007868,0.00048844394,0.000004442659,0.0000059951567,0.000027088123,0.000009796476,0.995178,0.0036371797,0.00017163051,0.00041793092,0.0000046788837],"about_ca_topic_score_codex":0.0037053723,"about_ca_topic_score_gemma":0.0034094462,"teacher_disagreement_score":0.0037053723,"about_ca_system_score_codex":0.00031929126,"about_ca_system_score_gemma":0.0005841027,"threshold_uncertainty_score":0.008070588},"labels":[],"label_agreement":null},{"id":"W4319007997","doi":"10.3390/modelling4010006","title":"Nonlinear Modeling of an Automotive Air Conditioning System Considering Active Grille Shutters","year":2023,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Refrigeration and Air Conditioning Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Mitacs","keywords":"Automotive engineering; Gas compressor; Air conditioning; Engineering; Aerodynamics; Automotive industry; Nonlinear system; Airflow; Condenser (optics); Energy consumption; Power (physics); Refrigerant; Control theory (sociology); Simulation; Computer science; Mechanical engineering; Electrical engineering; Aerospace engineering","score_opus":0.05296328010703633,"score_gpt":0.32009928263876136,"score_spread":0.26713600253172504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319007997","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29691696,0.00035137878,0.66267705,0.00039234295,0.0001075837,0.00014161612,0.00047236445,0.00063450146,0.038306195],"genre_scores_gemma":[0.98395556,0.00020276244,0.0054297117,0.00002881092,0.0000144158985,0.000076907556,0.00012119212,0.000027688859,0.010142846],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986875,0.000027270544,0.000006013835,0.0000328314,0.000042344687,0.000022886072],"domain_scores_gemma":[0.9998816,0.000040149742,0.0000244825,0.0000106906555,0.000035491274,0.00000755065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015489962,0.0005934553,0.00048926164,0.00022492792,0.00044767352,0.00069738313,0.00072418986,0.00088132056,0.0024411539],"category_scores_gemma":[0.00030013183,0.00027717557,0.0006571283,0.00013773302,0.00054768415,0.0005875419,0.0006297553,0.00055015704,0.00038878873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036169924,0.000014561702,0.00060425577,0.000040241175,0.0000101967,0.000098698736,0.00006548022,0.98828554,0.006422383,0.0019542773,0.000115532996,0.0023527367],"study_design_scores_gemma":[0.0000024617636,0.000014799982,0.00014977032,0.0000017943049,0.0000031029313,0.000007228325,0.0000073767137,0.9988023,0.00053978333,0.00017128205,0.00029755232,0.0000024625315],"about_ca_topic_score_codex":0.01594047,"about_ca_topic_score_gemma":0.008277581,"teacher_disagreement_score":0.01594047,"about_ca_system_score_codex":0.0005221539,"about_ca_system_score_gemma":0.000786795,"threshold_uncertainty_score":0.031695366},"labels":[],"label_agreement":null},{"id":"W4324150167","doi":"10.3390/modelling4010007","title":"Hybrid Finite-Discrete Element Modeling of the Mode I Tensile Response of an Alumina Ceramic","year":2023,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Numerical methods in engineering","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Defence Research and Development Canada","keywords":"Ultimate tensile strength; Materials science; Composite material; Finite element method; Modulus; Perpendicular; Ceramic; Elastic modulus; Failure mode and effects analysis; Structural engineering; Geometry; Mathematics; Engineering","score_opus":0.06630013955134469,"score_gpt":0.36580543447497804,"score_spread":0.29950529492363337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4324150167","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30101818,0.00032095553,0.68127394,0.00024107296,0.000080825994,0.00010536099,0.00042715273,0.0005872474,0.015945291],"genre_scores_gemma":[0.95671016,0.00019363505,0.037877537,0.00004897584,0.000011084421,0.00015821707,0.00014704604,0.00004738624,0.004806031],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998623,0.000026689737,0.000008567895,0.000021167676,0.00006038949,0.00002076269],"domain_scores_gemma":[0.9997863,0.00009479696,0.00003372877,0.000019968891,0.000047091988,0.000018169365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002868571,0.00034200592,0.0005332474,0.00042183016,0.00029923525,0.00057926023,0.0010233345,0.0012445683,0.0014167008],"category_scores_gemma":[0.0004976487,0.00036100333,0.00072219496,0.0003226127,0.00062221655,0.0003953026,0.0004227939,0.00042650863,0.00024399214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002827578,0.000026483667,0.00053504546,0.000034762128,0.000012993685,0.00006449592,0.000058724596,0.98672235,0.008409276,0.0019935893,0.00007342227,0.0020405815],"study_design_scores_gemma":[0.000003302004,0.000011586101,0.00011967053,0.0000027421318,0.0000027992357,0.00001345123,0.000009176661,0.9987451,0.00068416866,0.00019813413,0.00020551414,0.0000043473037],"about_ca_topic_score_codex":0.006162806,"about_ca_topic_score_gemma":0.0034868326,"teacher_disagreement_score":0.006162806,"about_ca_system_score_codex":0.00046179772,"about_ca_system_score_gemma":0.00065762235,"threshold_uncertainty_score":0.012253821},"labels":[],"label_agreement":null},{"id":"W4362473031","doi":"10.3390/modelling4020009","title":"Traceability Management of Socio-Cyber-Physical Systems Involving Goal and SysML Models","year":2023,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Traceability; Systems Modeling Language; Computer science; Requirements traceability; Systems engineering; Cyber-physical system; Process management; Unified Modeling Language; Software engineering; Consistency (knowledge bases); Risk analysis (engineering); Requirements engineering; Engineering; Software; Requirement; Artificial intelligence","score_opus":0.131512622802541,"score_gpt":0.3815247470751968,"score_spread":0.2500121242726558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362473031","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":[0.03952216,0.00005047848,0.9523915,0.00035570146,0.000025685877,0.00029247333,0.00022487262,0.004184753,0.0029523675],"genre_scores_gemma":[0.4076807,0.00010112243,0.5881103,0.00012212813,0.00001828868,0.00040424944,0.0010632987,0.0007293279,0.0017705639],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98754996,0.0052072215,0.00094289065,0.0015517363,0.004162876,0.00058535027],"domain_scores_gemma":[0.96485525,0.01856171,0.0028763348,0.009296653,0.0037561858,0.0006539051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013172638,0.0013447944,0.00064449746,0.0039105974,0.0014967403,0.0046028276,0.0031211816,0.0015034741,0.002601079],"category_scores_gemma":[0.045510314,0.001098065,0.0016983398,0.0014906037,0.0026120015,0.0068496238,0.0059554633,0.0027914392,0.00042064238],"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":[0.00044821424,0.0008341941,0.021254461,0.00057539885,0.00028543177,0.0016496894,0.009347563,0.464756,0.01721827,0.19612554,0.0032904847,0.28421468],"study_design_scores_gemma":[0.00006834992,0.0001682175,0.0021781768,0.00014664722,0.000108489934,0.00017779294,0.00091588247,0.8940973,0.017562993,0.06969317,0.014794725,0.00008821448],"about_ca_topic_score_codex":0.014165932,"about_ca_topic_score_gemma":0.012248519,"teacher_disagreement_score":0.014165932,"about_ca_system_score_codex":0.003606599,"about_ca_system_score_gemma":0.0060745645,"threshold_uncertainty_score":0.06966442},"labels":[],"label_agreement":null},{"id":"W4372295521","doi":"10.3390/modelling4020012","title":"Molecular Dynamics Simulations Correlating Mechanical Property Changes of Alumina with Atomic Voids under Triaxial Tension Loading","year":2023,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Advanced ceramic materials synthesis","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; Government of Canada","keywords":"Nanoporous; Materials science; Composite material; Ceramic; Stiffness; Void (composites); Fracture (geology); Atomic units; Molecular dynamics; Cracking; Tension (geology); Fracture mechanics; Volume fraction; Ultimate tensile strength; Nanotechnology","score_opus":0.05613847242420843,"score_gpt":0.32735852936630233,"score_spread":0.2712200569420939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4372295521","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913891,0.00015982172,0.0038976467,0.00016993005,0.000032061856,0.000034267694,0.00065843243,0.000109059016,0.0035496824],"genre_scores_gemma":[0.9945052,0.00017897745,0.0037695947,0.00004275469,0.000007908296,0.00008328385,0.0006401869,0.000033510092,0.0007385577],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998971,0.000012940189,0.0000059515523,0.000019507208,0.00002720142,0.000037284222],"domain_scores_gemma":[0.99966514,0.00017608094,0.00003956182,0.0000205868,0.00005953121,0.000039063194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024889273,0.00047987275,0.00049522665,0.0005185078,0.0007100083,0.0005178247,0.00083810795,0.0010854546,0.002622239],"category_scores_gemma":[0.00082956464,0.00037036857,0.0006598466,0.00060594286,0.00048477424,0.00060455955,0.00033381043,0.00076925626,0.0001471833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019943103,0.00019874354,0.0047717583,0.00013996723,0.00006467968,0.00025620253,0.00017981252,0.97547907,0.012255648,0.0030401903,0.00049477484,0.0029197435],"study_design_scores_gemma":[0.000021338012,0.000045027107,0.0010686475,0.0000060977673,0.000009203281,0.0000108280565,0.000041416366,0.99691075,0.0013059068,0.0003387132,0.00023212977,0.000009993716],"about_ca_topic_score_codex":0.015982082,"about_ca_topic_score_gemma":0.01380586,"teacher_disagreement_score":0.015982082,"about_ca_system_score_codex":0.0008793129,"about_ca_system_score_gemma":0.00097558234,"threshold_uncertainty_score":0.031778157},"labels":[],"label_agreement":null},{"id":"W4381805360","doi":"10.3390/modelling4030018","title":"Modelling of the Solidifying Microstructure of Inconel 718: Quasi-Binary Approximation","year":2023,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Solidification and crystal growth phenomena","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Superalloy; Inconel; Microstructure; Materials science; Supercooling; Mesoscopic physics; Phase (matter); Thermodynamics; Eutectic system; Metastability; Precipitation; Alloy; Metallurgy; Mechanics; Condensed matter physics; Physics","score_opus":0.0885533888179524,"score_gpt":0.3294487444879368,"score_spread":0.24089535566998443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381805360","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92855185,0.00022265855,0.062445305,0.000100890844,0.00001632321,0.00004802263,0.00025195294,0.00017702387,0.008186055],"genre_scores_gemma":[0.990812,0.00011529968,0.0076304725,0.000008733745,0.0000027999401,0.000033236214,0.0000714834,0.000018593115,0.0013073148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999479,0.000008828611,0.000002536522,0.00001079301,0.000016989441,0.0000128845195],"domain_scores_gemma":[0.9998946,0.000032031654,0.000027085953,0.000015453112,0.00002199323,0.000008796072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001105282,0.00023613602,0.00032634274,0.00026044901,0.00027864025,0.000498262,0.00073408656,0.00071407435,0.0008907172],"category_scores_gemma":[0.00032866915,0.00027620583,0.00025674538,0.00021057946,0.0004051968,0.00036114117,0.0001851583,0.00023555722,0.00013690209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050038958,0.000044116412,0.0013737243,0.000077398145,0.000010289043,0.00014756173,0.00006992881,0.94170696,0.04716082,0.00726067,0.000098197226,0.0020002453],"study_design_scores_gemma":[0.000006540874,0.000011840265,0.000517708,0.0000016658441,0.0000016537225,0.000017237526,0.000006408577,0.99701107,0.00191189,0.00035191223,0.00015948927,0.0000025235936],"about_ca_topic_score_codex":0.010991265,"about_ca_topic_score_gemma":0.0052696383,"teacher_disagreement_score":0.010991265,"about_ca_system_score_codex":0.0007093425,"about_ca_system_score_gemma":0.00071260385,"threshold_uncertainty_score":0.02185458},"labels":[],"label_agreement":null},{"id":"W4386776822","doi":"10.3390/modelling4030023","title":"Investigating Ice Loads on Subsea Pipelines with Cohesive Zone Model in Abaqus","year":2023,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Structural Integrity and Reliability Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre For Cold Ocean Resources Engineering; Memorial University of Newfoundland","funders":"","keywords":"Subsea; Iceberg; Fracture (geology); Geology; Pipeline transport; Structural engineering; Mechanics; Position (finance); Geotechnical engineering; Engineering; Sea ice; Physics; Mechanical engineering","score_opus":0.06957058198433101,"score_gpt":0.3280009935080285,"score_spread":0.2584304115236975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386776822","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.918337,0.00022486759,0.06550428,0.00018063898,0.00006857557,0.00012825135,0.0018269954,0.0011425437,0.012586921],"genre_scores_gemma":[0.96047205,0.00016054993,0.03569134,0.000043303917,0.000007789447,0.00018259452,0.0007220162,0.00014218455,0.002578266],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999863,0.000032364907,0.000008684096,0.000022483882,0.000047946225,0.00002549024],"domain_scores_gemma":[0.9994343,0.00033411066,0.000062348015,0.000038992395,0.00010857697,0.000021753429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054168,0.0005709414,0.0006260211,0.0007436401,0.00041104812,0.0006319869,0.00085233885,0.00091779436,0.005709049],"category_scores_gemma":[0.0008262584,0.0005410046,0.0006431873,0.0005703228,0.00045276232,0.00036886436,0.00033576105,0.00057567767,0.0003494539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061298684,0.000100137666,0.0049776775,0.00013803586,0.000023637482,0.00015034623,0.00014662724,0.97968495,0.007042841,0.0014463043,0.00060555537,0.0056225876],"study_design_scores_gemma":[0.000009770824,0.000036053363,0.0013483578,0.000011784617,0.000006682724,0.000015265343,0.000042513504,0.9969266,0.0008875667,0.00024176257,0.00046637031,0.0000072149505],"about_ca_topic_score_codex":0.016062822,"about_ca_topic_score_gemma":0.014027363,"teacher_disagreement_score":0.016062822,"about_ca_system_score_codex":0.0004911742,"about_ca_system_score_gemma":0.00083524146,"threshold_uncertainty_score":0.031938672},"labels":[],"label_agreement":null},{"id":"W4389949354","doi":"10.3390/modelling5010001","title":"Machine Learning-Assisted Characterization of Pore-Induced Variability in Mechanical Response of Additively Manufactured Components","year":2023,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Porosity; Compression (physics); Volume fraction; Artificial neural network; Composite material; Characterization (materials science); Shear (geology); Plasticity; Stress (linguistics); Biological system; Computer science; Artificial intelligence; Nanotechnology","score_opus":0.0661586916772684,"score_gpt":0.31077497874093346,"score_spread":0.24461628706366506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389949354","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8512266,0.00016908588,0.1465592,0.000059646387,0.000021857468,0.000032931446,0.0002689162,0.00045121188,0.0012105765],"genre_scores_gemma":[0.98914844,0.000043864104,0.01043339,0.000008072834,0.0000025310892,0.00001550974,0.000116320734,0.000011290218,0.00022061147],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998282,0.000027889904,0.00001155369,0.000043322187,0.00007503041,0.000013868368],"domain_scores_gemma":[0.9993383,0.00033319753,0.0001144731,0.000102276455,0.00009783983,0.000013924641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047924515,0.00034180807,0.0002671393,0.00043708144,0.00009797722,0.00031211105,0.00034897288,0.0004214433,0.0006203428],"category_scores_gemma":[0.0012123095,0.00014953867,0.0002464952,0.00028710935,0.0002830504,0.00036179123,0.00019295671,0.00034340456,0.000132924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024282245,0.00022631662,0.01306129,0.00023369574,0.00005463169,0.00013122983,0.000114156326,0.6063602,0.2894037,0.0006793256,0.0002767083,0.08921597],"study_design_scores_gemma":[0.000001987643,0.0000759444,0.0076679,0.00000367057,0.000005654346,0.000043180546,0.000012256138,0.95297164,0.03880821,0.00021442349,0.00018374158,0.000011452196],"about_ca_topic_score_codex":0.00052242173,"about_ca_topic_score_gemma":0.0011413308,"teacher_disagreement_score":0.0006203428,"about_ca_system_score_codex":0.00022934745,"about_ca_system_score_gemma":0.00022189721,"threshold_uncertainty_score":0.0025345683},"labels":[],"label_agreement":null},{"id":"W4390535499","doi":"10.3390/modelling5010008","title":"Controller Design for Air Conditioner of a Vehicle with Three Control Inputs Using Model Predictive Control","year":2024,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Mitacs","keywords":"Controller (irrigation); Model predictive control; Automotive engineering; Air conditioning; Engineering; Energy consumption; Fuel efficiency; Control theory (sociology); Computer science; Control (management)","score_opus":0.054415997549158594,"score_gpt":0.3073175631488148,"score_spread":0.2529015655996562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390535499","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03255455,0.00091950095,0.94823194,0.00031716397,0.00025108858,0.0002397157,0.00009527804,0.0016108237,0.01577997],"genre_scores_gemma":[0.96745783,0.00036218716,0.02670688,0.00009369832,0.000057250858,0.00034937504,0.000102499725,0.000048894544,0.004821505],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941397,0.00007577716,0.00002541499,0.00015803019,0.0002591847,0.00006771659],"domain_scores_gemma":[0.999569,0.000120793025,0.00007702097,0.000024090068,0.00019076986,0.000018377617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067390274,0.0010743625,0.0009161692,0.00041350664,0.0009786466,0.0018333974,0.0012344809,0.00094784395,0.0032829393],"category_scores_gemma":[0.0009315654,0.00043065086,0.0006259734,0.00033504813,0.0006378751,0.0005349251,0.0006780121,0.0012803266,0.000608636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000210572,0.00008275796,0.00056387985,0.00037154648,0.00006691879,0.00018417845,0.00016519209,0.9231122,0.01579816,0.003941965,0.0016037321,0.05389881],"study_design_scores_gemma":[0.000029692126,0.0001313233,0.00023964937,0.000011458082,0.000019750192,0.000018886949,0.000012568888,0.99520373,0.0026990694,0.00033340818,0.0012928484,0.000007655756],"about_ca_topic_score_codex":0.01582182,"about_ca_topic_score_gemma":0.010705312,"teacher_disagreement_score":0.01582182,"about_ca_system_score_codex":0.00076641544,"about_ca_system_score_gemma":0.0015882379,"threshold_uncertainty_score":0.03145945},"labels":[],"label_agreement":null},{"id":"W4392110993","doi":"10.3390/modelling5010016","title":"Intent Identification by Semantically Analyzing the Search Query","year":2024,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Topic Modeling","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Web search query; Computer science; Identification (biology); Information retrieval; Query expansion; Web query classification; Query optimization; Search engine","score_opus":0.06832558378806373,"score_gpt":0.3581409375351658,"score_spread":0.28981535374710204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392110993","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1314804,0.0006902203,0.84979606,0.00044553218,0.000057534784,0.00038332518,0.0012463151,0.010540102,0.0053604445],"genre_scores_gemma":[0.744673,0.00040972052,0.24852169,0.00022592978,0.00006499701,0.00016497813,0.0026063733,0.00029545982,0.0030378758],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910504,0.00021954947,0.00008782828,0.00023645055,0.00025988359,0.000091265414],"domain_scores_gemma":[0.9984648,0.00057212624,0.00020360132,0.0003061961,0.00037732886,0.000075926735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010707078,0.0009800208,0.0010164052,0.0025957355,0.0003856141,0.0013877387,0.00073370605,0.00081868644,0.0016294632],"category_scores_gemma":[0.0045639924,0.00029064814,0.00096252206,0.0013060737,0.00040146534,0.0029745363,0.0017726506,0.0008830038,0.0017897886],"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":[0.0015676667,0.0006454832,0.025607709,0.00083491043,0.00019492491,0.00066732476,0.0029241038,0.015918665,0.2400777,0.0200131,0.009552957,0.6819955],"study_design_scores_gemma":[0.000042296157,0.00044155185,0.009354256,0.0000766184,0.00014419096,0.00094624946,0.0008360153,0.90215385,0.055058256,0.023087304,0.0077512874,0.00010810554],"about_ca_topic_score_codex":0.0027116179,"about_ca_topic_score_gemma":0.0029422154,"teacher_disagreement_score":0.0027116179,"about_ca_system_score_codex":0.00040350287,"about_ca_system_score_gemma":0.0007954323,"threshold_uncertainty_score":0.005662501},"labels":[],"label_agreement":null},{"id":"W4393934997","doi":"10.3390/modelling5020023","title":"Numerical Analysis of Crack Propagation in an Aluminum Alloy under Random Load Spectra","year":2024,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Chinese Aeronautical Establishment","keywords":"Alloy; Aluminium; Materials science; Spectral line; Structural engineering; Composite material; Engineering; Physics","score_opus":0.04767267607770023,"score_gpt":0.330858389994602,"score_spread":0.2831857139169017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393934997","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31362548,0.0001973271,0.68320197,0.00007824384,0.000019739024,0.00005716869,0.000044563847,0.00033453148,0.0024409718],"genre_scores_gemma":[0.89654994,0.000089550806,0.10243963,0.00001337823,0.0000053883605,0.00005532872,0.00003393058,0.00003246252,0.00078047335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998449,0.00003704287,0.000007612538,0.000026456535,0.0000682175,0.00001573684],"domain_scores_gemma":[0.9992906,0.00037777764,0.00009399459,0.00006456311,0.00015416414,0.000018902017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046277643,0.0003628712,0.000259666,0.00063071545,0.00023465721,0.0002566996,0.00052628765,0.0007332307,0.0006572007],"category_scores_gemma":[0.0017499218,0.00022102386,0.00034521206,0.00024622722,0.00039634484,0.0005096195,0.00029282624,0.00023697258,0.00012280601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003932548,0.000031518557,0.001754604,0.0000461143,0.000012889467,0.00008353048,0.00007244648,0.9575622,0.024641054,0.0031149099,0.00008799234,0.012553362],"study_design_scores_gemma":[0.0000013872577,0.0000064174483,0.000113333364,0.0000010126578,8.818763e-7,0.00000853476,0.0000024292906,0.99905497,0.0006566029,0.00012107578,0.00003186642,0.0000014546631],"about_ca_topic_score_codex":0.0025777663,"about_ca_topic_score_gemma":0.0021558057,"teacher_disagreement_score":0.0025777663,"about_ca_system_score_codex":0.0003129137,"about_ca_system_score_gemma":0.00038240437,"threshold_uncertainty_score":0.005125582},"labels":[],"label_agreement":null},{"id":"W4400119568","doi":"10.3390/modelling5030035","title":"Impact of Volute Throat Area and Gap Width on the Hydraulic Performance of Low-Specific-Speed Centrifugal Pump","year":2024,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Cavitation Phenomena in Pumps","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Volute; Centrifugal pump; Specific speed; Flow (mathematics); Reduction (mathematics); Volumetric flow rate; Mechanics; Engineering; Mechanical engineering; Impeller; Mathematics; Geometry; Physics","score_opus":0.06433574827514837,"score_gpt":0.3154204065236025,"score_spread":0.2510846582484541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400119568","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992397,0.00014611207,0.006120041,0.000024282717,0.000008975614,0.0000089143905,0.000034663015,0.00007360905,0.0011863912],"genre_scores_gemma":[0.9989436,0.000042654807,0.0008654498,0.0000038639196,0.0000012867744,0.0000037058446,0.000014072662,0.000007941227,0.00011738941],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99954283,0.00011528828,0.000029523215,0.00006061018,0.00015599336,0.000095717085],"domain_scores_gemma":[0.99873215,0.000734339,0.00027855998,0.000099314806,0.00010634103,0.000049284805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069302466,0.00031970092,0.00059983024,0.00036970346,0.00032122055,0.0008920026,0.00033984307,0.00048385528,0.0007978053],"category_scores_gemma":[0.0018011231,0.00018089956,0.00036000012,0.0002653636,0.0006748539,0.00045554468,0.00044032643,0.0002639903,0.00017106271],"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":[0.0014380045,0.00025944397,0.017494187,0.00035670208,0.000059209433,0.0006758831,0.00020399502,0.67208743,0.27265766,0.001366417,0.0003362578,0.03306478],"study_design_scores_gemma":[0.00011426332,0.0038000715,0.03833289,0.00004457375,0.00012419368,0.000392469,0.0003200448,0.5987282,0.35547623,0.0006018013,0.0019512185,0.00011415646],"about_ca_topic_score_codex":0.0006364235,"about_ca_topic_score_gemma":0.00051833387,"teacher_disagreement_score":0.0008920026,"about_ca_system_score_codex":0.00031521893,"about_ca_system_score_gemma":0.0003354379,"threshold_uncertainty_score":0.0036650896},"labels":[],"label_agreement":null},{"id":"W4400680436","doi":"10.3390/modelling5030043","title":"Creep Phenomena, Mechanisms, and Modeling of Complex Engineering Alloys","year":2024,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"High Temperature Alloys and Creep","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; National Research Council Canada","funders":"National Research Council Canada","keywords":"Creep; Materials science; Forensic engineering; Metallurgy; Engineering","score_opus":0.052536772961710304,"score_gpt":0.30462818240185896,"score_spread":0.25209140944014863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400680436","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17845863,0.10470755,0.66686106,0.0012643608,0.00049121206,0.00027532384,0.0012892176,0.0010039848,0.04564871],"genre_scores_gemma":[0.81303877,0.0806527,0.083656736,0.00020605739,0.00045034333,0.00065781217,0.0010799436,0.00031490854,0.019942842],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997882,0.00004052597,0.000023473252,0.000043141234,0.00008475176,0.000019878142],"domain_scores_gemma":[0.9998099,0.000057934834,0.000045751185,0.000028267785,0.000048733153,0.000009412567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004157063,0.00092889805,0.001028761,0.0010916023,0.00041002102,0.0012739622,0.0014826194,0.0016025191,0.00091665296],"category_scores_gemma":[0.0006618406,0.00051173306,0.0010731043,0.0011577217,0.0008772702,0.0014660835,0.00064329343,0.0007317652,0.00044217866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025813011,0.00006284846,0.0020467036,0.0011145417,0.00010208865,0.00038832583,0.0003271329,0.84926844,0.024275739,0.08867719,0.0014559145,0.032255318],"study_design_scores_gemma":[0.000011989837,0.00005734948,0.0020186135,0.00017343498,0.00003678139,0.0003451536,0.00007019212,0.9255135,0.0032522022,0.043766163,0.02471528,0.00003943584],"about_ca_topic_score_codex":0.0019713936,"about_ca_topic_score_gemma":0.0012494017,"teacher_disagreement_score":0.0019713936,"about_ca_system_score_codex":0.00047420815,"about_ca_system_score_gemma":0.0006298471,"threshold_uncertainty_score":0.0039197803},"labels":[],"label_agreement":null},{"id":"W4401908032","doi":"10.3390/modelling5030053","title":"Integrating Null Controllability and Model-Based Safety Assessment for Enhanced Reliability in Drone Design","year":2024,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Advanced Aircraft Design and Technologies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Office National d'études et de Recherches Aérospatiales; Natural Sciences and Engineering Research Council of Canada; Norges Teknisk-Naturvitenskapelige Universitet","keywords":"Drone; Controllability; Reliability engineering; Reliability (semiconductor); Computer science; Systems engineering; Distributed computing; Engineering","score_opus":0.03788321399457088,"score_gpt":0.3460823174965387,"score_spread":0.30819910350196783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401908032","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019077621,0.00011765874,0.9782033,0.000051090276,0.000012657892,0.00004304104,0.000022093238,0.00026891188,0.00220372],"genre_scores_gemma":[0.67442054,0.00025256322,0.32354897,0.000042320873,0.000016664444,0.0002070952,0.000095539974,0.00016207321,0.0012541886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924266,0.00027737312,0.00003863829,0.00008628776,0.00030326197,0.000051811992],"domain_scores_gemma":[0.99877876,0.0006400964,0.0002082916,0.00015281158,0.00018385283,0.00003621126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014384477,0.0010600468,0.0005384578,0.0009949788,0.00029691434,0.0009908712,0.0008718009,0.00060330477,0.0016279195],"category_scores_gemma":[0.0031454782,0.00049844943,0.001070591,0.00023957672,0.00096999353,0.0009480832,0.0015554655,0.00083579717,0.00020223952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033679793,0.000039046372,0.00090979517,0.000113540926,0.00003163067,0.00006276553,0.000096727745,0.9493779,0.009294262,0.0154854385,0.00014569005,0.024409574],"study_design_scores_gemma":[0.0000075018984,0.00007743493,0.00015411353,0.000019149005,0.000018062401,0.000034514753,0.000017429067,0.9867209,0.0029824234,0.008945943,0.0010116028,0.000010875287],"about_ca_topic_score_codex":0.0016619934,"about_ca_topic_score_gemma":0.0017054302,"teacher_disagreement_score":0.0016619934,"about_ca_system_score_codex":0.0005260966,"about_ca_system_score_gemma":0.0011793026,"threshold_uncertainty_score":0.007607341},"labels":[],"label_agreement":null},{"id":"W4402901213","doi":"10.3390/modelling5040069","title":"Novel Adaptive Hidden Markov Model Utilizing Expectation–Maximization Algorithm for Advanced Pipeline Leak Detection","year":2024,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Water Systems and Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Leak detection; Pipeline (software); Expectation–maximization algorithm; Leak; Maximization; Markov chain; Hidden Markov model; Algorithm; Forward algorithm; Markov model; Machine learning; Artificial intelligence; Maximum likelihood; Variable-order Markov model; Mathematical optimization; Engineering; Mathematics; Statistics; Programming language","score_opus":0.05123299499623737,"score_gpt":0.3072032868765379,"score_spread":0.25597029188030057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402901213","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008874884,0.00032367624,0.98947084,0.00014577757,0.000040944164,0.00001817245,0.000045604786,0.0004306521,0.0006494357],"genre_scores_gemma":[0.63377315,0.00076961174,0.35902247,0.0002954393,0.00012397046,0.00018070533,0.00050891086,0.0001575713,0.0051681856],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994844,0.0001537934,0.000033794815,0.00012806464,0.0001221702,0.00007773479],"domain_scores_gemma":[0.9990301,0.00066548696,0.00008036002,0.000029933963,0.00015835444,0.000035716483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010692491,0.00070266775,0.0011740023,0.0005297993,0.00036358816,0.00078177755,0.0013794341,0.0010193038,0.001933718],"category_scores_gemma":[0.002305382,0.00053017994,0.0011170466,0.00058309257,0.00038984758,0.0011517269,0.0007676314,0.0014703617,0.00059022894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025179025,0.00015130534,0.0033988766,0.00016283474,0.00014767032,0.00025479836,0.00012102719,0.8134625,0.0060807476,0.011198546,0.0027301626,0.16203979],"study_design_scores_gemma":[0.0000030149413,0.0000078260255,0.00006427015,0.00000202502,0.0000036667082,0.000012363828,0.0000022472054,0.99872774,0.00021310007,0.0008458608,0.00011455131,0.0000032959092],"about_ca_topic_score_codex":0.009290615,"about_ca_topic_score_gemma":0.007184514,"teacher_disagreement_score":0.009290615,"about_ca_system_score_codex":0.0005204451,"about_ca_system_score_gemma":0.0012426387,"threshold_uncertainty_score":0.01847303},"labels":[],"label_agreement":null},{"id":"W4403188257","doi":"10.3390/modelling5040074","title":"Acausal Fuel Cell Simulation Model for System Integration Analysis in Early Design Phases","year":2024,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Politecnico di Torino","keywords":"Systems engineering; Computer science; Environmental science; Engineering; Nuclear engineering","score_opus":0.08080170946626528,"score_gpt":0.3431669639605495,"score_spread":0.2623652544942843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403188257","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.077177934,0.0005513525,0.84767187,0.00057123107,0.000321491,0.00046780767,0.005004422,0.004292691,0.06394125],"genre_scores_gemma":[0.7562205,0.0009769206,0.1910097,0.0002782291,0.00009671155,0.002261787,0.0069170296,0.0008552857,0.04138384],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998118,0.000040409755,0.000010744263,0.000028372306,0.00007693653,0.000031656695],"domain_scores_gemma":[0.9996884,0.00011909863,0.000022825496,0.000048669826,0.00010325545,0.00001778109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034977106,0.0010236264,0.00079946854,0.00040377222,0.000688385,0.0010420112,0.001572919,0.0015823246,0.012100853],"category_scores_gemma":[0.00090600096,0.0004702252,0.0011581331,0.00042022936,0.00034134075,0.0009234899,0.00086133095,0.0014975651,0.0020016932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043196887,0.00004187289,0.0004929858,0.00007324104,0.00001882168,0.00007102489,0.000038966675,0.9826633,0.0031489602,0.006226875,0.0012187891,0.0059620603],"study_design_scores_gemma":[0.000015459213,0.000013787656,0.00008658598,0.00000680843,0.0000062959275,0.00001202458,0.000007633753,0.9912281,0.0011833891,0.001299323,0.0061352826,0.000005348097],"about_ca_topic_score_codex":0.008919246,"about_ca_topic_score_gemma":0.0075404225,"teacher_disagreement_score":0.012100853,"about_ca_system_score_codex":0.0007112087,"about_ca_system_score_gemma":0.0015743176,"threshold_uncertainty_score":0.04048139},"labels":[],"label_agreement":null},{"id":"W4403646651","doi":"10.3390/modelling5040083","title":"Squirrel Cage Induction Motors Accurate Modelling for Digital Twin Applications","year":2024,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Squirrel-cage rotor; Induction motor; Cage; Computer science; Automotive engineering; Engineering; Electrical engineering; Structural engineering","score_opus":0.08146797355793116,"score_gpt":0.34223718853535023,"score_spread":0.26076921497741906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403646651","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028082514,0.00031601905,0.9598459,0.00014326272,0.000046841596,0.00003080264,0.00007239721,0.00029908502,0.011163172],"genre_scores_gemma":[0.8452202,0.0007877562,0.14545368,0.000050688228,0.000023020106,0.00010682993,0.00015399979,0.00006810719,0.008135762],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998605,0.000022337214,0.000007466227,0.000019876396,0.00007912398,0.000010595003],"domain_scores_gemma":[0.9999267,0.00001757293,0.000011284922,0.000017284918,0.000023582797,0.000003553187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020469145,0.00029429814,0.00027893396,0.00027979878,0.00018934008,0.00049725425,0.0005927741,0.0005040082,0.0014554468],"category_scores_gemma":[0.00035070063,0.00013780987,0.00038486547,0.00023501054,0.00040129467,0.0006851726,0.00029827622,0.00044950843,0.00034472352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049040995,0.000022790831,0.00077699946,0.00015863194,0.000015210052,0.00009786677,0.00013683396,0.78671473,0.053939275,0.11627022,0.00091701635,0.040901285],"study_design_scores_gemma":[0.000003686356,0.000041000625,0.00027688214,0.0000143667785,0.000007890731,0.000042444288,0.00001898056,0.9776047,0.006418482,0.00620037,0.0093641905,0.0000070161063],"about_ca_topic_score_codex":0.0016119097,"about_ca_topic_score_gemma":0.0013811699,"teacher_disagreement_score":0.0016119097,"about_ca_system_score_codex":0.0004919924,"about_ca_system_score_gemma":0.00041027338,"threshold_uncertainty_score":0.004868984},"labels":[],"label_agreement":null},{"id":"W4406670624","doi":"10.3390/modelling6010008","title":"Design and Implementation of a Simulation Framework for a Bio–Neural Dust System","year":2025,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; University of Ottawa","funders":"","keywords":"Environmental science; Computer science; Neural system; Artificial neural network; Artificial intelligence; Biology","score_opus":0.08134809580768709,"score_gpt":0.39222591008735685,"score_spread":0.31087781427966976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406670624","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010625646,0.00009973905,0.9782339,0.0001734532,0.000079195,0.00021661687,0.00020245885,0.004395187,0.0059738406],"genre_scores_gemma":[0.30777615,0.0004647019,0.6806909,0.00020731968,0.00003871087,0.0014871461,0.0010069455,0.0012910104,0.007037182],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996038,0.00008794557,0.000031520856,0.00006182028,0.00015955487,0.000055360146],"domain_scores_gemma":[0.999589,0.00016136616,0.000029950708,0.00005180361,0.000109832574,0.00005803456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092824374,0.0008041046,0.00075745385,0.00062041526,0.0006987463,0.0013314544,0.0022503159,0.0014990952,0.0067638224],"category_scores_gemma":[0.0014996121,0.0005088152,0.001075486,0.00027879942,0.0008679847,0.0008872011,0.0014464566,0.0013770341,0.0012363673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010080454,0.00010485223,0.0015480034,0.00020401564,0.0000676458,0.00019642983,0.00020075502,0.9322,0.012087644,0.028811943,0.0019584128,0.022519452],"study_design_scores_gemma":[0.000025919895,0.000019479201,0.00009714526,0.000016560627,0.000009312645,0.000028340637,0.00001825422,0.98638123,0.0026386292,0.0030144525,0.0077377064,0.000012980722],"about_ca_topic_score_codex":0.0072082416,"about_ca_topic_score_gemma":0.0038388679,"teacher_disagreement_score":0.0072082416,"about_ca_system_score_codex":0.0009370682,"about_ca_system_score_gemma":0.0021883203,"threshold_uncertainty_score":0.022627234},"labels":[],"label_agreement":null},{"id":"W4411368369","doi":"10.3390/modelling6020050","title":"Evaluating the Uncertainty and Predictive Performance of Probabilistic Models Devised for Grade Estimation in a Porphyry Copper Deposit","year":2025,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Rio Tinto","keywords":"Kriging; Probabilistic logic; Computer science; Uncertainty quantification; Statistical model; Data mining; Gaussian process; Extrapolation; Machine learning; Benchmark (surveying); Predictive inference; Outlier; Interpolation (computer graphics); Artificial intelligence; Statistics; Gaussian; Bayesian inference; Mathematics; Geology; Bayesian probability","score_opus":0.07059121185115567,"score_gpt":0.36253774331904864,"score_spread":0.29194653146789296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411368369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92391145,0.0001719582,0.07381218,0.00023420487,0.000015755119,0.00006032681,0.00021632932,0.00038148375,0.0011963114],"genre_scores_gemma":[0.9860459,0.00006119479,0.013448624,0.000015584852,0.0000054115594,0.00002179636,0.00019526275,0.000020100095,0.00018607473],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924064,0.00031341918,0.000058253943,0.00016590717,0.00016017629,0.00006160564],"domain_scores_gemma":[0.9905896,0.007828838,0.0004934562,0.00046250448,0.0005013855,0.00012419738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003924249,0.0007596297,0.00057031406,0.0008584445,0.00044137493,0.0013076233,0.0009981128,0.0012688756,0.00040720514],"category_scores_gemma":[0.0125734825,0.00045715703,0.00072671915,0.00061491516,0.00078331184,0.001006308,0.0008610443,0.0010400738,0.000106703745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000679672,0.00002689251,0.0051028854,0.00002293006,0.000021339092,0.00003083885,0.000039872717,0.987689,0.000393126,0.00052660186,0.00006347727,0.006014963],"study_design_scores_gemma":[0.0000042298593,0.000042050935,0.0016248322,0.000006788586,0.0000061184533,0.00001332486,0.000024909199,0.9971752,0.0006083837,0.0004230957,0.00006224791,0.000008765868],"about_ca_topic_score_codex":0.031272363,"about_ca_topic_score_gemma":0.018366814,"teacher_disagreement_score":0.031272363,"about_ca_system_score_codex":0.0012615799,"about_ca_system_score_gemma":0.0013693966,"threshold_uncertainty_score":0.06218064},"labels":[],"label_agreement":null},{"id":"W4414179217","doi":"10.3390/modelling6030103","title":"Evaluating Carsharing Fleet Management Strategies Using Discrete Event Simulation: A Case Study","year":2025,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"Fleet management; Discrete event simulation; Event (particle physics); Measure (data warehouse); Quality (philosophy); Incident management","score_opus":0.1654793898955486,"score_gpt":0.4738706523335897,"score_spread":0.3083912624380411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414179217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98671734,0.000061676554,0.010016006,0.00010863934,0.000016048987,0.00019208297,0.00022933635,0.000065386535,0.002593521],"genre_scores_gemma":[0.9928566,0.00006182896,0.006073625,0.000015992044,0.0000036411714,0.00008916712,0.00014592499,0.0000068696754,0.00074630306],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917275,0.00038230905,0.00003279019,0.000089742236,0.00013431981,0.00018807524],"domain_scores_gemma":[0.99443394,0.0041952576,0.0003718751,0.00020892757,0.000462581,0.00032744958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017861981,0.0010767889,0.0007142393,0.0007987916,0.0006553324,0.001291898,0.0013170481,0.0016008881,0.0015421303],"category_scores_gemma":[0.0030530554,0.00036797978,0.0008760176,0.00080359343,0.00055551884,0.0008037649,0.000529432,0.0009663809,0.00013128945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001693545,0.00046188824,0.005151481,0.000043047545,0.000040646784,0.00016789722,0.000073086034,0.98921835,0.0008813985,0.00082388794,0.00017185978,0.002797157],"study_design_scores_gemma":[0.00004009719,0.00030532668,0.0014421161,0.000005851299,0.00001893239,0.000016996606,0.00018835116,0.9966995,0.00084230833,0.0002313809,0.0001959252,0.000013212024],"about_ca_topic_score_codex":0.03903077,"about_ca_topic_score_gemma":0.029131385,"teacher_disagreement_score":0.03903077,"about_ca_system_score_codex":0.0025085576,"about_ca_system_score_gemma":0.0016057089,"threshold_uncertainty_score":0.077607155},"labels":[],"label_agreement":null},{"id":"W4416228059","doi":"10.3390/modelling6040148","title":"Winding Numbers in Discrete Dynamics: From Circle Maps and Fractals to Chaotic Poincaré Sections","year":2025,"lang":"en","type":"article","venue":"Modelling—International Open Access Journal of Modelling in Engineering Science","topic":"Quantum chaos and dynamical systems","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; University of Regina","keywords":"Quasiperiodic function; Chaotic; Quasiperiodicity; Fractal; Multifractal system; Dynamical systems theory; Winding number; Standard map; Planar","score_opus":0.019126995789297115,"score_gpt":0.3248030388771127,"score_spread":0.3056760430878156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416228059","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87603873,0.000924829,0.11499461,0.00022050549,0.000072557814,0.000040031922,0.00011753755,0.0002504146,0.0073408666],"genre_scores_gemma":[0.9877592,0.00020097735,0.01163049,0.000014288274,0.000020085692,0.000014645339,0.0000663162,0.000032299322,0.00026164285],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997404,0.00008424585,0.000017228382,0.000052371528,0.00007903168,0.000026603293],"domain_scores_gemma":[0.9984126,0.0007021504,0.0003252923,0.0003084723,0.00013046924,0.0001210681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085468835,0.00037456898,0.00029699955,0.0017337698,0.00029970947,0.0009922774,0.00027731908,0.00031819666,0.000914479],"category_scores_gemma":[0.005568454,0.00021175934,0.00022374807,0.00065679115,0.0016211964,0.0016051679,0.0008429728,0.00048852584,0.00015032267],"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":[0.00072471873,0.00011898752,0.04147913,0.0005919412,0.0001359864,0.00072587316,0.0038258363,0.24658382,0.070599444,0.45540583,0.0021245535,0.1776839],"study_design_scores_gemma":[0.000026901589,0.00021241925,0.027806267,0.00012950895,0.00003497023,0.00039483706,0.0005765727,0.643573,0.020840898,0.3019006,0.0043934234,0.00011060903],"about_ca_topic_score_codex":0.00048582663,"about_ca_topic_score_gemma":0.00024351779,"teacher_disagreement_score":0.0017337698,"about_ca_system_score_codex":0.00037884677,"about_ca_system_score_gemma":0.00019549885,"threshold_uncertainty_score":0.0045200586},"labels":[],"label_agreement":null}]}