{"meta":{"query_hash":"34fdd9bf00b3","filters":{"venue":"PSIG Annual Meeting"},"cohort_total":14,"direct_labels_cover":0,"predictions_cover":14,"exported":14,"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/34fdd9bf00b3","api":"https://metacan.xera.ac/api/v1/cohort?venue=PSIG+Annual+Meeting"},"results":[{"id":"W2287376783","doi":"","title":"Predicting Shut-in And In-Station Leak Detection Sensitivities","year":2012,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Leak; Leak detection; Shut down; Computer science; Environmental science","score_opus":0.042400482905198045,"score_gpt":0.3306827477946107,"score_spread":0.28828226488941266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2287376783","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":[0.96401435,0.00006555623,0.03296118,0.00011739622,0.000021871687,0.000025535259,0.0006981877,0.00045294888,0.0016429943],"genre_scores_gemma":[0.99689317,0.000020345256,0.0022718203,0.000008756596,0.0000056865233,0.000004453798,0.0002954274,0.000011982736,0.00048824985],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996094,0.000099320074,0.000021624292,0.00007736095,0.00010654828,0.00008584385],"domain_scores_gemma":[0.9952739,0.0033717584,0.0003994569,0.0001830077,0.000568449,0.0002034642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012875611,0.0009087265,0.0005792152,0.001132958,0.00021492278,0.00091486506,0.00044948145,0.00079201406,0.001701935],"category_scores_gemma":[0.0071129682,0.00043796666,0.00063076173,0.0005576757,0.00016650459,0.0009618505,0.00046506364,0.0006940925,0.00049855607],"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":[0.0005061098,0.0001762626,0.16866374,0.000053529664,0.00008448289,0.00020920688,0.000047750957,0.79354435,0.00868292,0.00044037044,0.0008734008,0.026717888],"study_design_scores_gemma":[0.000007031431,0.0001090168,0.030642338,0.0000045158336,0.000028722634,0.000026690199,0.000029096984,0.963815,0.004820729,0.00038130739,0.00012385401,0.000011694151],"about_ca_topic_score_codex":0.005665466,"about_ca_topic_score_gemma":0.005110635,"teacher_disagreement_score":0.005665466,"about_ca_system_score_codex":0.00070068,"about_ca_system_score_gemma":0.0005008772,"threshold_uncertainty_score":0.01126498},"labels":[],"label_agreement":null},{"id":"W2407673269","doi":"","title":"Markov Chain Monte Carlo Based Error-in-Variable Model (EVM) for the Internal Wall Roughness for Gas Networks","year":2016,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","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":"TransCanada (Canada); Nova Chemicals (Canada)","funders":"","keywords":"Markov chain Monte Carlo; Monte Carlo method; Markov chain; Variable (mathematics); Computer science; Statistical physics; Econometrics; Mathematics; Statistics; Physics; Mathematical analysis","score_opus":0.009426298152973045,"score_gpt":0.21707565362442363,"score_spread":0.20764935547145058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2407673269","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":[0.03740208,0.0006127201,0.9573736,0.00069873774,0.00014390996,0.00007724264,0.00046512645,0.0005550677,0.0026714983],"genre_scores_gemma":[0.8681753,0.00074216584,0.116129905,0.00037322644,0.00019931338,0.00048854307,0.0012453654,0.00045690517,0.012189215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982199,0.0008569678,0.00007481777,0.0002980048,0.0002338237,0.00031641175],"domain_scores_gemma":[0.98600405,0.011188274,0.00081096916,0.0005325005,0.00107992,0.0003842373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005083386,0.0012893276,0.0027791855,0.001544055,0.0013057702,0.0017980746,0.0040924535,0.004273235,0.0050210166],"category_scores_gemma":[0.015129776,0.001874288,0.0021380556,0.00153085,0.0027330322,0.0030183124,0.0025557945,0.0038976413,0.0007628691],"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":[0.000023074002,0.0000087809185,0.00021077823,0.00001115737,0.0000106175185,0.000014501497,0.0000128357115,0.9904525,0.000052578853,0.008143864,0.00017320031,0.00088619714],"study_design_scores_gemma":[0.0000033677563,0.0000029297073,0.000029036237,0.0000025740349,0.000002632444,0.0000020244836,0.0000017401732,0.99758565,0.000021147069,0.0022984697,0.000046920897,0.000003473186],"about_ca_topic_score_codex":0.039751153,"about_ca_topic_score_gemma":0.025834356,"teacher_disagreement_score":0.039751153,"about_ca_system_score_codex":0.0028674176,"about_ca_system_score_gemma":0.0030046157,"threshold_uncertainty_score":0.079039514},"labels":[],"label_agreement":null},{"id":"W2499820712","doi":"","title":"Does Current Simulation Software Provide the Right Tools For Planners","year":2000,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Simulation Techniques and Applications","field":"Decision 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":"TransCanada (Canada)","funders":"","keywords":"Current (fluid); Software; Computer science; Engineering; Programming language","score_opus":0.08550985676408333,"score_gpt":0.41560227094809676,"score_spread":0.3300924141840134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2499820712","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":[0.043026038,0.0034239963,0.74303263,0.083246276,0.0026176479,0.00022118149,0.003576084,0.012338813,0.10851735],"genre_scores_gemma":[0.56132096,0.007829537,0.40955633,0.004952971,0.0008184499,0.00025646345,0.0032783833,0.0034212607,0.008565678],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99009424,0.004638177,0.0008849322,0.0010203702,0.0026017937,0.0007604745],"domain_scores_gemma":[0.9543461,0.021286318,0.0036947236,0.009917151,0.008988035,0.0017676537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014363084,0.0006748945,0.0013974201,0.0018175687,0.0009946745,0.0071988604,0.001838142,0.0029018938,0.025972972],"category_scores_gemma":[0.071076,0.000945938,0.0014686756,0.0017840652,0.0017902845,0.015643856,0.002138138,0.0019194313,0.0111721195],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060198596,0.00055746856,0.02944834,0.0020477627,0.00039953695,0.00015926514,0.0009899123,0.12578288,0.0038429084,0.28567007,0.10592353,0.44457635],"study_design_scores_gemma":[0.00025573428,0.0002286408,0.004216468,0.0018252388,0.000226342,0.00021645005,0.0018931061,0.35766694,0.008495055,0.2657073,0.35905582,0.00021291901],"about_ca_topic_score_codex":0.007835689,"about_ca_topic_score_gemma":0.008065458,"teacher_disagreement_score":0.025972972,"about_ca_system_score_codex":0.0020546839,"about_ca_system_score_gemma":0.008325682,"threshold_uncertainty_score":0.086888194},"labels":[],"label_agreement":null},{"id":"W2505208117","doi":"","title":"Data Management And Exchange In a Pipeline Simulation Environment","year":2004,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Power Systems and Technologies","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":"TransCanada (Canada)","funders":"","keywords":"Pipeline (software); Computer science; Data science; Operating system","score_opus":0.02242440371350232,"score_gpt":0.2346760176362357,"score_spread":0.21225161392273337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2505208117","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":[0.110192195,0.00011902406,0.8044929,0.00078200165,0.00014396035,0.000412518,0.0016297715,0.074523136,0.0077045374],"genre_scores_gemma":[0.690536,0.0002236662,0.28810534,0.00030119688,0.00008167466,0.0004282249,0.0062681288,0.0060223867,0.008033392],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961312,0.0014336593,0.0005023962,0.0005231966,0.0011249101,0.00028463456],"domain_scores_gemma":[0.991055,0.0039031676,0.00026206963,0.003375208,0.00083545846,0.0005690029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008480125,0.00092519843,0.00092138664,0.0014071568,0.0014431593,0.0038060613,0.0033428783,0.001536896,0.006306465],"category_scores_gemma":[0.014689271,0.0010968304,0.00085271616,0.0016874815,0.0012452459,0.005537588,0.0034023102,0.0017925322,0.001333203],"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":[0.009764748,0.0019942143,0.028750267,0.00045048486,0.00051670516,0.0016139769,0.0037097826,0.46923143,0.041045833,0.089848526,0.046565417,0.30650854],"study_design_scores_gemma":[0.00035920105,0.00017332382,0.0009300073,0.00002718259,0.00009140712,0.00012991014,0.00014373215,0.921433,0.03826156,0.014937124,0.023438135,0.00007538855],"about_ca_topic_score_codex":0.006604234,"about_ca_topic_score_gemma":0.0034232375,"teacher_disagreement_score":0.008480125,"about_ca_system_score_codex":0.0010448298,"about_ca_system_score_gemma":0.0021671578,"threshold_uncertainty_score":0.044847786},"labels":[],"label_agreement":null},{"id":"W2512696704","doi":"","title":"Developing And Implementing a 'Full Scope' Operator Trainer Simulator For the TransCanada Keystone Pipeline","year":2010,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Power Systems and Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Trainer; Pipeline (software); Scope (computer science); Computer science; Simulation; Operator (biology); Keystone species; Engineering; Operating system","score_opus":0.011594682223907868,"score_gpt":0.24491566565244235,"score_spread":0.2333209834285345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2512696704","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5107961,0.000055488807,0.45285767,0.00033319902,0.00014844847,0.0011933711,0.00044688061,0.009785513,0.024383252],"genre_scores_gemma":[0.7407601,0.00008004088,0.24201283,0.00007205345,0.000010436446,0.0003122984,0.0007066975,0.0005648609,0.015480669],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996729,0.000057404402,0.000017881383,0.000059425765,0.00012845994,0.000063995525],"domain_scores_gemma":[0.99938524,0.00008682046,0.000026326057,0.00010019674,0.00024691463,0.00015445572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066231575,0.00046092278,0.00025402338,0.0002165391,0.00045779353,0.00058761716,0.0013045426,0.0005808145,0.0073605],"category_scores_gemma":[0.0012244806,0.00037966532,0.0002821013,0.0001348749,0.00029360145,0.00095441483,0.0011014421,0.0007448902,0.0013734958],"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":[0.0009149567,0.001273195,0.021738708,0.000315841,0.00009952093,0.0006212085,0.002469615,0.3714509,0.24969338,0.004766313,0.011959265,0.33469716],"study_design_scores_gemma":[0.0002508439,0.0021146587,0.009694658,0.00006703357,0.00006758471,0.00031319953,0.0009894872,0.8452805,0.07244542,0.0012709774,0.067389734,0.00011583102],"about_ca_topic_score_codex":0.008582053,"about_ca_topic_score_gemma":0.009093326,"teacher_disagreement_score":0.008582053,"about_ca_system_score_codex":0.00058104127,"about_ca_system_score_gemma":0.002785005,"threshold_uncertainty_score":0.024623275},"labels":[],"label_agreement":null},{"id":"W2605638422","doi":"","title":"A Novel Model for Prediction of Crack Propagation in Gas Transmission Pipelines","year":2014,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Geotechnical Engineering and Underground Structures","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":"University of British Columbia; Spectra Energy (Canada)","funders":"","keywords":"Pipeline transport; Environmental science; Forensic engineering; Petroleum engineering; Geology; Engineering","score_opus":0.011168466211730866,"score_gpt":0.21196500658708736,"score_spread":0.2007965403753565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605638422","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":[0.15418133,0.00064441253,0.8332904,0.0005880964,0.00032171072,0.00011989073,0.0004963876,0.0011886072,0.009169126],"genre_scores_gemma":[0.9235564,0.0005183985,0.06508496,0.000118035234,0.00017924036,0.00021216556,0.0003727352,0.00017625681,0.009781891],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998611,0.000026532058,0.0000083949735,0.00003655726,0.000043249926,0.000024152048],"domain_scores_gemma":[0.99960357,0.00018020147,0.000042459527,0.000026514856,0.000110555615,0.00003673837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003442813,0.00078117027,0.0011303755,0.00038194237,0.0005989279,0.00091116445,0.0017799488,0.0025806895,0.0021396026],"category_scores_gemma":[0.0012413097,0.0006649867,0.00081537955,0.00038869126,0.00058010744,0.0010491767,0.00081848213,0.0011557676,0.0003796291],"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":[0.000016812499,0.000024374269,0.00019810596,0.000015243257,0.000008305377,0.000030308418,0.000006859387,0.9951179,0.0009847208,0.000944779,0.00017586736,0.002476789],"study_design_scores_gemma":[0.0000025272225,0.0000032190771,0.000016954878,4.8331515e-7,9.932941e-7,0.0000016703091,5.0164164e-7,0.99979776,0.00004741243,0.000088610446,0.00003910998,8.0827743e-7],"about_ca_topic_score_codex":0.019031104,"about_ca_topic_score_gemma":0.009274215,"teacher_disagreement_score":0.019031104,"about_ca_system_score_codex":0.00075863174,"about_ca_system_score_gemma":0.0013895888,"threshold_uncertainty_score":0.037840664},"labels":[],"label_agreement":null},{"id":"W2608660467","doi":"","title":"Evaluation of Internal Leak Detection Techniques","year":2015,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","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":"TransCanada (Canada)","funders":"","keywords":"Leak; Leak detection; Computer science; Risk analysis (engineering); Business; Engineering","score_opus":0.044679181878038425,"score_gpt":0.31917667725898397,"score_spread":0.27449749538094553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608660467","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":[0.6911922,0.0016927362,0.28350997,0.00034389843,0.0002712155,0.00022033617,0.00080936647,0.015344733,0.0066154646],"genre_scores_gemma":[0.9105145,0.00037141665,0.085504875,0.000063827894,0.000044569126,0.00003221016,0.0010499298,0.00042717313,0.001991557],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9954091,0.00076470984,0.00032098993,0.00071085803,0.0024324737,0.00036196943],"domain_scores_gemma":[0.9809301,0.008391502,0.0016050102,0.0023741256,0.006243911,0.00045536587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028737083,0.0012292292,0.00094456284,0.002166633,0.00050321495,0.0014779578,0.0016056601,0.0010021037,0.0018641399],"category_scores_gemma":[0.016049858,0.00029652592,0.00082408584,0.0012370357,0.00049343635,0.0018492109,0.0012741084,0.00087760616,0.0008420801],"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":[0.003023045,0.0010854659,0.03393785,0.0006220212,0.00041378522,0.0003887412,0.00024930073,0.059738234,0.10184599,0.0015824584,0.005339631,0.79177356],"study_design_scores_gemma":[0.000117872536,0.0018340193,0.015434097,0.000060324317,0.0002885211,0.00079645147,0.00019744488,0.79411834,0.18328041,0.0011135224,0.0026997905,0.00005921342],"about_ca_topic_score_codex":0.0021211344,"about_ca_topic_score_gemma":0.0018907018,"teacher_disagreement_score":0.0028737083,"about_ca_system_score_codex":0.00070964947,"about_ca_system_score_gemma":0.0010329915,"threshold_uncertainty_score":0.015197754},"labels":[],"label_agreement":null},{"id":"W2611819112","doi":"","title":"Pipeline Optimization Using DRA Degradation Models","year":2015,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Smart Grid Energy Management","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":"SNC-Lavalin (Canada)","funders":"","keywords":"Pipeline (software); Degradation (telecommunications); Environmental science; Petroleum engineering; Computer science; Geology; Telecommunications","score_opus":0.03978984286566662,"score_gpt":0.23348487234388413,"score_spread":0.1936950294782175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2611819112","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":[0.06250697,0.00080778403,0.8920148,0.000989402,0.00011829463,0.00012541917,0.00075782277,0.0018182725,0.04086112],"genre_scores_gemma":[0.93209094,0.00036148322,0.048601825,0.00011269267,0.000034517463,0.000116098185,0.0004299264,0.0003146786,0.017937757],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997899,0.00007089016,0.000007857006,0.000044260843,0.00004813839,0.000038967268],"domain_scores_gemma":[0.9995023,0.00024589355,0.00004691797,0.000037144062,0.00014333874,0.000024415327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000558559,0.00079029665,0.0010535853,0.000545973,0.0004091413,0.0010413677,0.00071897334,0.0011337347,0.0050922707],"category_scores_gemma":[0.0016274715,0.0005888801,0.00083877344,0.0007034822,0.00032845928,0.0011326397,0.0006072547,0.0010074851,0.0006913069],"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":[0.000011925056,0.000006344666,0.00005320436,0.000011477647,0.0000041436997,0.000006896469,0.0000034414059,0.9955349,0.0001871508,0.0009591867,0.0002747994,0.0029465652],"study_design_scores_gemma":[0.0000012517426,0.0000037976074,0.000013621924,8.39664e-7,0.0000011727819,9.637248e-7,0.0000011021449,0.99946314,0.00006695783,0.0003137112,0.00013270958,7.670766e-7],"about_ca_topic_score_codex":0.018530397,"about_ca_topic_score_gemma":0.011447377,"teacher_disagreement_score":0.018530397,"about_ca_system_score_codex":0.0015559285,"about_ca_system_score_gemma":0.0013513635,"threshold_uncertainty_score":0.036845088},"labels":[],"label_agreement":null},{"id":"W2621318829","doi":"","title":"Fractional Factorial Analysis of Parameters Affecting Leak Detection Model Transient Resolution","year":2017,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Fault Detection and Control Systems","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":"TransCanada (Canada)","funders":"","keywords":"Fractional factorial design; Transient (computer programming); Leak; Mathematics; Resolution (logic); Factorial experiment; Computer science; Statistics; Environmental science; Artificial intelligence","score_opus":0.01652475481489866,"score_gpt":0.2505208379534217,"score_spread":0.23399608313852308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621318829","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":[0.6535248,0.00031184818,0.34221983,0.0001187586,0.00004640181,0.000024241208,0.0001530999,0.00042640406,0.0031745192],"genre_scores_gemma":[0.9927897,0.00003668238,0.0067911656,0.0000091225065,0.0000048247816,0.000009071313,0.00004201094,0.000025828609,0.00029161677],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936575,0.00020889279,0.000029723518,0.00016039616,0.00013923118,0.000096053715],"domain_scores_gemma":[0.99626994,0.0026863317,0.0003120288,0.0003171451,0.0003672617,0.00004732626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012374953,0.00044612607,0.0005571696,0.00042178773,0.00035212343,0.0008491037,0.0002944028,0.00055435864,0.0017093428],"category_scores_gemma":[0.0070304526,0.00016742382,0.00065033877,0.00047021892,0.00029166075,0.00065891905,0.00023121481,0.00040433998,0.00019516247],"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":[0.0028687355,0.0003805436,0.0088777235,0.00024196184,0.00019024496,0.00031595776,0.00017275248,0.52492344,0.29979292,0.013462408,0.00065961055,0.14811383],"study_design_scores_gemma":[0.00001814346,0.00030433346,0.010612081,0.000008957815,0.00010291251,0.00006497733,0.000036993813,0.92669743,0.059354898,0.0022088396,0.00054817257,0.0000422063],"about_ca_topic_score_codex":0.0016019356,"about_ca_topic_score_gemma":0.001365701,"teacher_disagreement_score":0.0017093428,"about_ca_system_score_codex":0.00063564,"about_ca_system_score_gemma":0.00048791082,"threshold_uncertainty_score":0.00654459},"labels":[],"label_agreement":null},{"id":"W2624446421","doi":"","title":"Pipeline Network Optimization - Application of Genetic Algorithm Methodologies","year":2005,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Water Systems and Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Pipeline (software); Computer science; Genetic algorithm; Algorithm; Mathematical optimization; Mathematics; Machine learning; Programming language","score_opus":0.01332804257481749,"score_gpt":0.23957649460900723,"score_spread":0.22624845203418975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624446421","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":[0.013112918,0.0004485586,0.9781892,0.00027519205,0.00007167279,0.000077149,0.000046050733,0.00021893192,0.0075603696],"genre_scores_gemma":[0.3504766,0.00083108747,0.6422965,0.00013037282,0.0001036375,0.00038342,0.00012422241,0.00020983884,0.0054443656],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996013,0.0002344391,0.000011406852,0.000037837453,0.00009052623,0.000024461726],"domain_scores_gemma":[0.9989293,0.00080792047,0.00005346556,0.00003850014,0.00015230237,0.000018450753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014412482,0.00089690724,0.0009589526,0.0010960653,0.00054657174,0.0008871821,0.0010179703,0.0017164438,0.002353675],"category_scores_gemma":[0.0039675315,0.00056609686,0.00071117515,0.0013139853,0.00058814837,0.0007924062,0.00070557604,0.0010444277,0.000332078],"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":[0.000013105384,0.000021776217,0.00010664061,0.000024535646,0.000019029565,0.000013031616,0.000011707662,0.9746377,0.00017719371,0.0051476494,0.00034523528,0.01948232],"study_design_scores_gemma":[0.000005579164,0.0000059184254,0.000022841263,0.0000032963121,0.0000032714056,0.0000024779476,0.000002195725,0.99791294,0.0000846949,0.0017530491,0.00020244469,0.0000012608195],"about_ca_topic_score_codex":0.009779811,"about_ca_topic_score_gemma":0.008062555,"teacher_disagreement_score":0.009779811,"about_ca_system_score_codex":0.0009585123,"about_ca_system_score_gemma":0.0013199584,"threshold_uncertainty_score":0.019445777},"labels":[],"label_agreement":null},{"id":"W2625718541","doi":"","title":"Statistical Modeling Techniques In the Design And Operation of Pipeline Systems","year":2002,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Water Systems 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":"TransCanada (Canada)","funders":"","keywords":"Pipeline (software); Computer science; Statistical model; Artificial intelligence","score_opus":0.022468861720671474,"score_gpt":0.21566563244637463,"score_spread":0.19319677072570315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2625718541","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":[0.0022168206,0.0005451052,0.9964528,0.00014473806,0.000026858856,0.000014688652,0.00001986427,0.00013993646,0.00043925797],"genre_scores_gemma":[0.4089445,0.004863638,0.58088267,0.00022304336,0.00041817004,0.00053971296,0.0003200963,0.00039433202,0.0034138327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970624,0.0017892459,0.00013327721,0.00018501341,0.00072169106,0.00010835814],"domain_scores_gemma":[0.99460876,0.00425345,0.00034563077,0.00020022668,0.0005365892,0.000055240907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004222592,0.001088893,0.0012985682,0.0011385558,0.0005296049,0.0011570774,0.0012393161,0.0008688705,0.0012415053],"category_scores_gemma":[0.00991792,0.0014379689,0.0012838641,0.0015480261,0.0008962648,0.0015251015,0.00085597206,0.0019361537,0.0004116489],"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":[0.00004340644,0.00003036535,0.0003259683,0.000091188675,0.00007710844,0.000020281403,0.00003575498,0.91194606,0.0007617926,0.04189428,0.00068312173,0.044090603],"study_design_scores_gemma":[0.000010855875,0.000028063392,0.00012087442,0.000010515204,0.000015205058,0.000008102762,0.000005636011,0.9755701,0.00039347782,0.022550894,0.001277912,0.000008300628],"about_ca_topic_score_codex":0.0051792017,"about_ca_topic_score_gemma":0.0052587613,"teacher_disagreement_score":0.0051792017,"about_ca_system_score_codex":0.0010108491,"about_ca_system_score_gemma":0.0026586433,"threshold_uncertainty_score":0.022331417},"labels":[],"label_agreement":null},{"id":"W2727791726","doi":"","title":"Successive Steady State Hydraulic Model Tuning Through Viscosity Analysis","year":2014,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Hydraulic and Pneumatic Systems","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":"TransCanada (Canada)","funders":"","keywords":"Steady state (chemistry); Viscosity; Control theory (sociology); State (computer science); Environmental science; Mathematics; Computer science; Thermodynamics; Physics; Control (management); Chemistry; Algorithm","score_opus":0.012303408295236474,"score_gpt":0.2360015981087001,"score_spread":0.22369818981346365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2727791726","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":[0.044640046,0.00005265438,0.9454274,0.00009587671,0.00006255702,0.00004432464,0.00004438263,0.0021496431,0.007483051],"genre_scores_gemma":[0.88955617,0.00003854572,0.10653341,0.000060060203,0.000014852368,0.00007366665,0.000084725776,0.00043804565,0.0032005757],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965155,0.00006989594,0.000024192163,0.000068272115,0.00013309943,0.000053003863],"domain_scores_gemma":[0.998982,0.0004990569,0.00007317397,0.0002454807,0.00016512717,0.000035073448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007734531,0.00062968384,0.0006671075,0.00062534877,0.00062767544,0.0011765412,0.00067859323,0.000763469,0.004968309],"category_scores_gemma":[0.0031867537,0.0006327619,0.0006286333,0.00024035417,0.00046123285,0.0013078419,0.0017476586,0.001133325,0.0010134272],"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":[0.000474396,0.00028336747,0.0014569372,0.00023593493,0.00011146148,0.0001972715,0.0003661198,0.7037429,0.0783823,0.018737935,0.00254273,0.19346862],"study_design_scores_gemma":[0.0000085410575,0.000030434294,0.00017290612,0.0000045320307,0.0000066401835,0.000015462287,0.000012169451,0.989321,0.007323618,0.0022879748,0.00080653734,0.000010212601],"about_ca_topic_score_codex":0.0015797918,"about_ca_topic_score_gemma":0.0020972136,"teacher_disagreement_score":0.004968309,"about_ca_system_score_codex":0.000405725,"about_ca_system_score_gemma":0.0006091578,"threshold_uncertainty_score":0.016620696},"labels":[],"label_agreement":null},{"id":"W2784820820","doi":"","title":"TransCanada's Use of Pipeline Simulations to Support Short Notice Services","year":2007,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Radiology practices and education","field":"Medicine","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":"TransCanada (Canada)","funders":"","keywords":"Notice; Pipeline (software); Computer science; Business; Political science; Operating system","score_opus":0.0429688568362267,"score_gpt":0.3484372368710336,"score_spread":0.3054683800348069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2784820820","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":[0.376623,0.00021602146,0.24816813,0.0031500245,0.0010898856,0.00148663,0.0018503518,0.07542327,0.29199266],"genre_scores_gemma":[0.8449623,0.000128088,0.11732136,0.00028785327,0.00004638894,0.00021987702,0.0016796164,0.0018637646,0.033490695],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992933,0.00024789228,0.000040220064,0.00013224955,0.00019425212,0.000091895425],"domain_scores_gemma":[0.9965559,0.0012897503,0.000106666426,0.00071788806,0.00087047514,0.0004593688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012777628,0.0005051668,0.00021539154,0.00055157446,0.00076597335,0.0015494063,0.0012318364,0.0006567827,0.021578416],"category_scores_gemma":[0.006266686,0.00029967263,0.00027078105,0.00042175298,0.000345907,0.0012512208,0.0013429489,0.0008931098,0.0028094917],"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":[0.0034884785,0.0022395172,0.028366417,0.00025490264,0.000107826294,0.0012931599,0.0028324327,0.11121098,0.034340743,0.022381412,0.14299954,0.6504846],"study_design_scores_gemma":[0.0006074146,0.00077772647,0.0066485843,0.00008631855,0.000064402106,0.00082560536,0.0010364852,0.64077055,0.021812696,0.0063279,0.32089987,0.00014239886],"about_ca_topic_score_codex":0.012372575,"about_ca_topic_score_gemma":0.0139507195,"teacher_disagreement_score":0.021578416,"about_ca_system_score_codex":0.001291436,"about_ca_system_score_gemma":0.0021732645,"threshold_uncertainty_score":0.07218695},"labels":[],"label_agreement":null},{"id":"W2968117686","doi":"","title":"Guided, Accelerated Parametric Studies","year":2019,"lang":"en","type":"article","venue":"PSIG Annual Meeting","topic":"Statistical and numerical algorithms","field":"Mathematics","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":"TransCanada (Canada)","funders":"","keywords":"Computer science","score_opus":0.1535538478133831,"score_gpt":0.4056718833579625,"score_spread":0.2521180355445794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968117686","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":[0.016752912,0.00031236102,0.97453237,0.00033558925,0.00011357071,0.0000738825,0.00010176686,0.000733855,0.007043728],"genre_scores_gemma":[0.37234926,0.00053776946,0.6058089,0.00039486482,0.00023360665,0.0003851844,0.00040110177,0.00086574384,0.01902354],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998137,0.0008267194,0.000052357387,0.00024862832,0.0006073862,0.00012784469],"domain_scores_gemma":[0.99326515,0.0034591076,0.0004241624,0.0016570314,0.00097441685,0.00022019277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035064647,0.0010530961,0.0012537111,0.0011286384,0.0005719398,0.0022495387,0.0017448431,0.0018368757,0.010810951],"category_scores_gemma":[0.022694452,0.00060620595,0.0009451547,0.0010176135,0.0010891203,0.0025630153,0.004226491,0.0020906406,0.0022760504],"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":[0.0010674336,0.00025236793,0.0031202165,0.00040345133,0.00017112587,0.0004884192,0.0005511734,0.24869482,0.015664844,0.33851355,0.014641863,0.3764307],"study_design_scores_gemma":[0.00009325995,0.00025046716,0.0010003019,0.000051536354,0.00004795669,0.0003776904,0.00008486598,0.808301,0.0051142755,0.16987862,0.014767265,0.000032778058],"about_ca_topic_score_codex":0.00089578074,"about_ca_topic_score_gemma":0.0011755241,"teacher_disagreement_score":0.010810951,"about_ca_system_score_codex":0.00056027377,"about_ca_system_score_gemma":0.0017147085,"threshold_uncertainty_score":0.03616619},"labels":[],"label_agreement":null}]}