{"meta":{"query_hash":"c04e3065348c","filters":{"venue":"The 31st International Ocean and Polar Engineering Conference"},"cohort_total":4,"direct_labels_cover":0,"predictions_cover":4,"exported":4,"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/c04e3065348c","api":"https://metacan.xera.ac/api/v1/cohort?venue=The+31st+International+Ocean+and+Polar+Engineering+Conference"},"results":[{"id":"W3184087145","doi":"","title":"High-fidelity FE Model of the Riser Subjected to the Slug-flow in the Arbitrary Lagrangian-Eulerian Description","year":2021,"lang":"en","type":"article","venue":"The 31st International Ocean and Polar Engineering Conference","topic":"Oil and Gas Production Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Eulerian path; Flow (mathematics); Lagrangian; Mechanics; Slug flow; Computer science; Mathematics; Applied mathematics; Physics; Two-phase flow","score_opus":0.01456519714953725,"score_gpt":0.1999594204705642,"score_spread":0.18539422332102695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184087145","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":[0.2307245,0.000795178,0.6313091,0.0012089661,0.00044032495,0.00032563935,0.004639905,0.0030603257,0.12749612],"genre_scores_gemma":[0.9449373,0.00035761137,0.027984617,0.00017660417,0.000050648247,0.0001928694,0.0012891191,0.00028516864,0.024726067],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999828,0.000035639077,0.000011906126,0.000029755707,0.000070947375,0.000023811535],"domain_scores_gemma":[0.9998399,0.000038146118,0.00002712438,0.000026021506,0.000050571216,0.00001817781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022747478,0.0006508224,0.0006720095,0.0005270188,0.00052191154,0.0009995883,0.0014272899,0.002568954,0.00834867],"category_scores_gemma":[0.0006894778,0.00052803,0.0005445072,0.00046883282,0.00077136233,0.0005486863,0.0006158483,0.00068804785,0.0013420212],"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":[0.000018758323,0.000020166932,0.00036189472,0.000027858647,0.000009676837,0.00010945552,0.000025752386,0.9939075,0.0015537965,0.0018447585,0.00032326538,0.0017970778],"study_design_scores_gemma":[0.000008191538,0.000012231957,0.00034230488,0.0000075126054,0.0000045371,0.000023694207,0.0000151153745,0.9982231,0.00032333878,0.00028562892,0.0007482518,0.0000060924517],"about_ca_topic_score_codex":0.015285003,"about_ca_topic_score_gemma":0.0100067,"teacher_disagreement_score":0.015285003,"about_ca_system_score_codex":0.0005315763,"about_ca_system_score_gemma":0.0011411313,"threshold_uncertainty_score":0.03039211},"labels":[],"label_agreement":null},{"id":"W3186491567","doi":"","title":"Fatigue Reliability Assessment of Drill String Due to Stick-Slip Vibrations and Wave-Frequency Vessel Motions","year":2021,"lang":"en","type":"article","venue":"The 31st International Ocean and Polar Engineering Conference","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Drill string; Vibration; Slip (aerodynamics); Structural engineering; Reliability (semiconductor); Engineering; Physics; Drill; Mechanics; Acoustics; Mechanical engineering; Aerospace engineering","score_opus":0.016207255385245648,"score_gpt":0.2550523425437472,"score_spread":0.23884508715850156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186491567","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":[0.9671543,0.00047475687,0.031023074,0.00004323801,0.000033705925,0.000038633494,0.00018161,0.00019779605,0.000852904],"genre_scores_gemma":[0.99860495,0.0000404033,0.0009854846,0.0000062261142,0.0000043029254,0.000009888619,0.0000672146,0.00000661173,0.0002749367],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993874,0.00011903495,0.00005363407,0.00009947734,0.00027176185,0.00006868013],"domain_scores_gemma":[0.9953122,0.0015035121,0.0005932376,0.0002947668,0.0021094752,0.00018670538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011033382,0.00045498594,0.00044812547,0.0014935341,0.00024883292,0.00021659135,0.0005014414,0.00085257116,0.0011057367],"category_scores_gemma":[0.0033568402,0.00031306082,0.00053492043,0.0004023849,0.0002925458,0.0004432624,0.0002967287,0.00027555195,0.00033189252],"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":[0.005615055,0.00039860356,0.12943624,0.0007970532,0.00042309662,0.0018723331,0.0011251599,0.2804233,0.40834764,0.0005831391,0.001814454,0.16916387],"study_design_scores_gemma":[0.000053555355,0.005627099,0.22065412,0.00007418242,0.000301989,0.00107747,0.00032328165,0.7096747,0.06090139,0.00034242184,0.0008812107,0.00008849613],"about_ca_topic_score_codex":0.0014887807,"about_ca_topic_score_gemma":0.0022612293,"teacher_disagreement_score":0.0014935341,"about_ca_system_score_codex":0.0003188608,"about_ca_system_score_gemma":0.00019140284,"threshold_uncertainty_score":0.005835116},"labels":[],"label_agreement":null},{"id":"W3201282959","doi":"","title":"Numerical Modelling of Frozen Soil and Permafrost Subsidence Effects","year":2021,"lang":"en","type":"article","venue":"The 31st International Ocean and Polar Engineering Conference","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SNC-Lavalin (Canada)","funders":"","keywords":"Permafrost; Subsidence; Geology; Geotechnical engineering; Hydrology (agriculture); Environmental science; Geomorphology; Oceanography","score_opus":0.027100875564812568,"score_gpt":0.20955488886335003,"score_spread":0.18245401329853744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3201282959","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":[0.96932507,0.0003355619,0.013384908,0.00033868724,0.00013932065,0.000030518735,0.00041225684,0.00022776629,0.015805885],"genre_scores_gemma":[0.9968927,0.00009114934,0.0012661809,0.00002069013,0.000012557675,0.000009485487,0.00011603184,0.000033253575,0.0015579045],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988544,0.00002483221,0.000009588316,0.000020405507,0.00002542841,0.000034371253],"domain_scores_gemma":[0.99959725,0.00018693606,0.00004588113,0.00003398163,0.00007827818,0.000057712707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002140177,0.00044270352,0.00065313705,0.0004659287,0.0005466213,0.0012888286,0.0011043525,0.0012728046,0.0027994756],"category_scores_gemma":[0.0015666949,0.00048499144,0.00052436563,0.00054192846,0.0010767115,0.00096139516,0.00070709933,0.00066679413,0.00019070058],"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":[0.0000333229,0.000022413493,0.0010466648,0.000011567113,0.000010366844,0.00006127365,0.000019756535,0.9958016,0.00096245646,0.0008985504,0.00008495807,0.0010470302],"study_design_scores_gemma":[0.000020289837,0.000010975337,0.0009353379,0.000002686884,0.00000388476,0.0000068342933,0.0000132531595,0.9982364,0.00017398711,0.00044124675,0.0001500535,0.000004940626],"about_ca_topic_score_codex":0.04571223,"about_ca_topic_score_gemma":0.024139721,"teacher_disagreement_score":0.04571223,"about_ca_system_score_codex":0.0011380743,"about_ca_system_score_gemma":0.000921068,"threshold_uncertainty_score":0.090892315},"labels":[],"label_agreement":null},{"id":"W3210581788","doi":"","title":"Modeling Subgouge Sand Deformations by Using Multi-Layer Perceptron Neural Network","year":2021,"lang":"en","type":"article","venue":"The 31st International Ocean and Polar Engineering Conference","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Artificial neural network; Layer (electronics); Perceptron; Artificial intelligence; Computer science; Geology; Pattern recognition (psychology); Materials science","score_opus":0.026919007035216727,"score_gpt":0.22922496445329116,"score_spread":0.20230595741807444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210581788","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":[0.35437092,0.00076632487,0.6357879,0.00036642267,0.00017523134,0.000059322894,0.00040855168,0.0021322337,0.0059330733],"genre_scores_gemma":[0.9734352,0.00016589541,0.02259359,0.000049586655,0.000023523678,0.000027628781,0.00021089496,0.00007140763,0.0034223273],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989796,0.00001272137,0.000006268593,0.000034379485,0.000024084624,0.000024536894],"domain_scores_gemma":[0.9998578,0.000051347408,0.000024798344,0.000014902515,0.00003684256,0.000014283471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020940717,0.00070458994,0.00062832725,0.00064442714,0.00038614313,0.0006591239,0.0009152609,0.0011718905,0.0013928263],"category_scores_gemma":[0.00053928915,0.000716889,0.0007154189,0.0005896891,0.00044767847,0.00093303237,0.00047525865,0.0007771849,0.00036198547],"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":[0.00002576923,0.000017493296,0.0007429108,0.0000076090196,0.000015887896,0.000030710533,0.0000066514685,0.9918779,0.0010176679,0.00026890083,0.00011679353,0.005871662],"study_design_scores_gemma":[4.575468e-7,8.8615917e-7,0.00006830822,2.7353175e-7,7.742999e-7,0.0000011029344,6.977581e-7,0.9998024,0.00005400528,0.000052545627,0.000017536997,8.723906e-7],"about_ca_topic_score_codex":0.036826886,"about_ca_topic_score_gemma":0.04113749,"teacher_disagreement_score":0.036826886,"about_ca_system_score_codex":0.00081130984,"about_ca_system_score_gemma":0.0008001743,"threshold_uncertainty_score":0.07322502},"labels":[],"label_agreement":null}]}