{"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9948108,0.00030422324,0.0014412681,0.00026170243,0.0001723016,0.000058623882,0.0000052337136,0.000022247812,0.0029235557],"genre_scores_gemma":[0.9993241,0.00004755626,0.0003006748,0.000036474834,0.0001461156,0.0000039566507,0.0000011605282,0.0000059716867,0.00013397819],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981846,0.00036829055,0.00045764944,0.00023412834,0.00046834405,0.00028697372],"domain_scores_gemma":[0.9981836,0.0014039822,0.0001466011,0.00011440618,0.0000887402,0.000062669475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005040715,0.000087937486,0.00019154909,0.00039586,0.00014062606,0.000078178426,0.00007136623,0.000060533894,0.0000096960885],"category_scores_gemma":[0.0031159788,0.00007538621,0.000038383616,0.0006858566,0.00004072852,0.00087063335,0.000054670556,0.00014539243,0.00002264076],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032368764,0.000020210664,0.8212784,0.000004313955,0.0000043011714,0.0000035367034,0.019329552,0.002279594,0.0013681075,0.000029800762,0.000016481968,0.15563333],"study_design_scores_gemma":[0.0003141053,0.000031704083,0.8352707,0.000063025764,0.000010974869,0.000013636139,0.10763571,0.050782178,0.0026397537,0.0024933915,0.00055034866,0.00019449189],"about_ca_topic_score_codex":0.00076098775,"about_ca_topic_score_gemma":0.00907184,"teacher_disagreement_score":0.15543884,"about_ca_system_score_codex":0.000036075537,"about_ca_system_score_gemma":0.000009356325,"threshold_uncertainty_score":0.50622994},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11098163,0.00007890813,0.8859724,0.0010644235,0.00020505526,0.00069223216,0.00003599135,0.00003732453,0.00093207596],"genre_scores_gemma":[0.932487,0.00002566287,0.06290732,0.0007361393,0.000108869666,0.00030944965,0.0000030213205,0.000052048144,0.003370487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983623,0.00004603565,0.0003171289,0.00043434696,0.00021213006,0.0006280373],"domain_scores_gemma":[0.9989937,0.00050414907,0.00013284749,0.00026476668,0.000008495728,0.00009606139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008051766,0.00022939574,0.00020365663,0.000006185658,0.00022321478,0.000026747566,0.00042402343,0.00010793316,0.00007518812],"category_scores_gemma":[0.00008988947,0.00014610947,0.000113399205,0.00009696572,0.00015775155,0.0002156475,0.00019243716,0.000114186296,0.0000069287935],"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":[0.00017766876,0.000046029138,0.0153081985,0.000008184905,0.000011228465,0.0000011148626,0.00026012288,0.9600283,0.00027571537,0.000042130727,0.00073129695,0.023110004],"study_design_scores_gemma":[0.0009133968,0.00007248922,0.0014705382,0.00007558986,0.00002235309,0.0000016440913,0.00036811427,0.9933038,0.000050782262,0.0002784739,0.0032096847,0.00023318747],"about_ca_topic_score_codex":0.00076708366,"about_ca_topic_score_gemma":0.00024875274,"teacher_disagreement_score":0.82306504,"about_ca_system_score_codex":0.00033353528,"about_ca_system_score_gemma":0.000010927395,"threshold_uncertainty_score":0.5958171},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37075612,0.00049674255,0.59650046,0.012854797,0.0012132088,0.0058880555,0.0010582507,0.0013435198,0.009888845],"genre_scores_gemma":[0.98954165,0.000007897173,0.0074124974,0.00029833405,0.0003846003,0.00023661704,0.00002768451,0.000015239863,0.0020755047],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99822915,0.00009330431,0.0005267014,0.00037273453,0.0005533419,0.00022477243],"domain_scores_gemma":[0.9929131,0.0060416483,0.00018568356,0.00041314232,0.00038657954,0.000059845024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014936529,0.00011928001,0.00014418346,0.0000658919,0.00057398574,0.00042064855,0.000495066,0.000051716455,0.0003771052],"category_scores_gemma":[0.003731245,0.00005449329,0.000112189504,0.0003560847,0.000055950255,0.0005186322,0.000038709142,0.000102257574,0.00011051859],"study_design_candidate":"design_other","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":[0.000024821707,0.000026482405,0.0007455874,0.00000410579,0.000003606646,1.2506494e-7,0.00081988383,0.069138475,0.000016572794,0.000732293,0.006638135,0.9218499],"study_design_scores_gemma":[0.0001491405,0.000025673824,0.00083120586,0.00002577967,0.000009605055,3.7358225e-7,0.0004945735,0.0547051,0.00050853426,0.03043774,0.9126783,0.00013395934],"about_ca_topic_score_codex":0.000011088936,"about_ca_topic_score_gemma":0.000009023008,"teacher_disagreement_score":0.921716,"about_ca_system_score_codex":0.000024073317,"about_ca_system_score_gemma":0.000029628949,"threshold_uncertainty_score":0.44669184},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8728255,0.011775408,0.097704545,0.00036728993,0.000472194,0.00081956555,0.00017564456,0.0012124558,0.014647375],"genre_scores_gemma":[0.99691206,0.00023290138,0.0027482365,0.000007838553,0.000030465391,0.000009716144,0.000011927039,0.0000112296575,0.000035619883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994953,0.0000055095893,0.00013754873,0.00014897806,0.00007400902,0.00013863877],"domain_scores_gemma":[0.9997272,0.00001545572,0.000015437301,0.00022281465,0.0000023701905,0.000016751948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017238119,0.0000750924,0.00008029182,0.00007278829,0.000019812307,0.000012643468,0.000111668036,0.000037257352,0.0000030155163],"category_scores_gemma":[0.00001421239,0.00007501819,0.0000054490774,0.000059188507,0.000010769597,0.00012587418,0.0001755602,0.000058535912,0.000010347675],"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":[0.0000058328797,0.000045452434,0.002521874,0.0004156442,0.000030732346,0.00006904712,0.0020112938,0.83892584,0.00031131148,0.00040292097,0.0003989813,0.15486106],"study_design_scores_gemma":[0.0030199685,0.00009232126,0.021026451,0.0010328981,0.000045990568,0.000014009647,0.0068737403,0.6845725,0.0013111386,0.0020333685,0.27896798,0.0010096318],"about_ca_topic_score_codex":0.000036454672,"about_ca_topic_score_gemma":0.00003424254,"teacher_disagreement_score":0.278569,"about_ca_system_score_codex":0.000040633728,"about_ca_system_score_gemma":7.311956e-7,"threshold_uncertainty_score":0.3059153},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9214573,0.0021638956,0.072301164,0.00087978307,0.0010628847,0.00071662624,0.00011027494,0.0006479698,0.00066009414],"genre_scores_gemma":[0.9921665,0.000026658716,0.0073166373,0.000060369264,0.0002514079,0.00008504838,0.0000035303478,0.00004448564,0.000045326156],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988905,0.000010045559,0.00032509075,0.00019900373,0.00011422732,0.00046112316],"domain_scores_gemma":[0.9993999,0.00025354372,0.00004005916,0.0001762953,0.00007682099,0.000053392156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006119724,0.00018629123,0.00020539502,0.00005951167,0.0003138991,0.000084880645,0.00020296051,0.00009211731,0.000008797829],"category_scores_gemma":[0.00020528142,0.00013747643,0.00004563467,0.00013869655,0.00005271032,0.00013023555,0.000047321333,0.00021891687,0.0000014914033],"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":[0.00005738915,0.000037592086,0.0019395392,0.0016251256,0.00053618394,0.000023976854,0.012226641,0.009834471,0.59248465,0.01721362,0.009957085,0.35406372],"study_design_scores_gemma":[0.0022859387,0.00010335242,0.0005608358,0.0004301528,0.00011677111,0.000074130825,0.011548186,0.23661453,0.09848669,0.00027303625,0.6481845,0.0013218876],"about_ca_topic_score_codex":0.00020706498,"about_ca_topic_score_gemma":0.0018859436,"teacher_disagreement_score":0.6382274,"about_ca_system_score_codex":0.000022260045,"about_ca_system_score_gemma":0.00003244058,"threshold_uncertainty_score":0.5606126},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06792601,0.00007820094,0.93116397,0.000043767424,0.00008883228,0.00015391248,0.000028986684,0.00019226996,0.00032406577],"genre_scores_gemma":[0.97380286,0.000011364956,0.026018921,0.000005200862,0.00007721431,0.000024560823,0.000014212283,0.000022112139,0.000023560444],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934614,0.000007190836,0.00027374312,0.00011652961,0.00009911778,0.00015729792],"domain_scores_gemma":[0.99973524,0.00007076951,0.000028047543,0.00007854915,0.00005342917,0.00003397676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023668875,0.0001009471,0.00014031948,0.00008204392,0.000025048656,0.000007540209,0.00006185907,0.00009405894,6.820385e-7],"category_scores_gemma":[0.0001493998,0.000094570314,0.000041560284,0.00010027216,0.000009961295,0.00008724657,0.0000055953174,0.0001005898,2.2560832e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010063308,0.000010994254,0.000018372215,0.00021847396,0.0000031250115,2.8409927e-8,0.00029177192,0.8962577,0.08661794,0.00027735528,0.00004251628,0.016251635],"study_design_scores_gemma":[0.00037317397,0.00003669554,0.00029697755,0.000150347,0.0000075602975,0.0000014245072,0.000029767538,0.99036264,0.006783976,0.0015130354,0.0003597723,0.000084639236],"about_ca_topic_score_codex":0.000010277337,"about_ca_topic_score_gemma":0.000005540065,"teacher_disagreement_score":0.9058768,"about_ca_system_score_codex":0.000019531273,"about_ca_system_score_gemma":0.000006014806,"threshold_uncertainty_score":0.38564655},"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":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035840176,0.00007499931,0.9460198,0.0001166252,0.00011229616,0.0002148147,0.0000016754694,0.0004251578,0.017194439],"genre_scores_gemma":[0.96672094,0.0000024043698,0.033030678,0.000038338003,0.000081255064,0.00007774755,3.9446144e-7,0.000005866768,0.00004238499],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988142,0.00012566401,0.000236146,0.00019829728,0.0005140551,0.00011159869],"domain_scores_gemma":[0.9985492,0.000028364853,0.00017119742,0.0002490456,0.00094583054,0.000056309524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024327226,0.00007272328,0.00008777078,0.00011419615,0.00006300181,0.000033736123,0.00031230974,0.00005210886,0.0000033542271],"category_scores_gemma":[0.00024583863,0.000071095965,0.00004091008,0.00030686005,0.000026212621,0.00033782088,0.00011982058,0.000089035166,0.000010351183],"study_design_candidate":"design_other","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":[0.0000048938145,0.00004774775,0.00021528921,0.0000056796525,0.000010790755,2.898876e-7,0.00090181874,0.00013158211,0.022041662,0.0029097903,0.00041137228,0.9733191],"study_design_scores_gemma":[0.0001858849,0.00025260096,0.00035658246,0.000046587258,0.00002587529,0.000022213291,0.00044657904,0.09980031,0.8759049,0.015125962,0.0076679443,0.00016457075],"about_ca_topic_score_codex":0.00017449897,"about_ca_topic_score_gemma":0.000046595203,"teacher_disagreement_score":0.9731545,"about_ca_system_score_codex":0.00009280375,"about_ca_system_score_gemma":0.00006285933,"threshold_uncertainty_score":0.28992093},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043893605,0.00020972079,0.9306808,0.000044938173,0.00075858674,0.0000958692,0.000004315981,0.00050591864,0.023806244],"genre_scores_gemma":[0.8867928,0.000019351239,0.11227562,0.000051155836,0.00048121926,0.000010437657,0.000045046898,0.00006371752,0.00026068994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915576,0.000028923476,0.00022684425,0.0001498246,0.00021630547,0.00022233436],"domain_scores_gemma":[0.9995888,0.000020458534,0.00003749779,0.00014979213,0.00011552261,0.00008791371],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003204879,0.00013060561,0.0001119329,0.00010964552,0.00005227398,0.000043767308,0.00009704322,0.000049980925,0.000007249813],"category_scores_gemma":[0.00007214117,0.00014501029,0.000024595378,0.00022500005,0.000009908381,0.0004969133,0.00004854502,0.00007272407,0.000012733354],"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":[0.0000030018944,0.000006840809,0.000077311015,0.000013592177,0.000010222578,0.000001877242,0.0003730469,0.99566233,0.00007208359,0.00018065909,0.0023904827,0.0012085207],"study_design_scores_gemma":[0.000207904,0.000008087807,0.000006752725,0.00003334093,0.000018078623,0.0000023576179,0.0005100358,0.99684644,0.00062239624,0.00013787756,0.0014437037,0.00016300788],"about_ca_topic_score_codex":0.00007731188,"about_ca_topic_score_gemma":0.000007510177,"teacher_disagreement_score":0.84289914,"about_ca_system_score_codex":0.00013890282,"about_ca_system_score_gemma":0.000012039106,"threshold_uncertainty_score":0.5913348},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.818614,0.000049184946,0.17691493,0.000019201943,0.001656732,0.00013510158,0.000035920664,0.00020013379,0.0023747664],"genre_scores_gemma":[0.9994524,0.0000053191175,0.00025271994,0.0000043193427,0.0002155267,0.000016792175,0.0000045697566,0.00001976466,0.00002856404],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989001,0.000053425392,0.00034657717,0.00020041906,0.00027601418,0.00022347482],"domain_scores_gemma":[0.9993051,0.00010011995,0.0001894393,0.0002555326,0.0000869941,0.00006275714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042343116,0.00014358303,0.00029656244,0.0002548815,0.0003624242,0.00007189992,0.00012564202,0.00012162266,0.000005554784],"category_scores_gemma":[0.00023779151,0.00015221233,0.00023409745,0.00018318863,0.000029368995,0.00030672795,0.00001307998,0.00019053443,0.000004316317],"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":[0.00004882791,0.00001208199,0.00034512053,0.000026386359,0.00039359435,5.159599e-7,0.0008774268,0.94498307,0.047954854,0.0000097160955,0.000024239649,0.0053241886],"study_design_scores_gemma":[0.0003441826,0.000036244488,0.0029658966,0.000029741104,0.00026813115,0.000001382502,0.0005084372,0.9874831,0.007926691,0.000018118391,0.00026557888,0.00015252447],"about_ca_topic_score_codex":0.0005944254,"about_ca_topic_score_gemma":0.0011047089,"teacher_disagreement_score":0.18083839,"about_ca_system_score_codex":0.000104924475,"about_ca_system_score_gemma":0.000008536488,"threshold_uncertainty_score":0.62070394},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00077648764,0.0008780975,0.995315,0.00003514032,0.00019660594,0.00016215295,0.00000879552,0.00024814322,0.0023795727],"genre_scores_gemma":[0.15823941,0.00007143657,0.840813,0.000013951997,0.0006758541,0.000023863968,0.000024899487,0.000027310787,0.00011030979],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991501,0.000058360132,0.0003733162,0.00013152575,0.000106136715,0.0001805588],"domain_scores_gemma":[0.9995702,0.00006981602,0.00008802619,0.0001403524,0.000101349025,0.000030274861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035804976,0.000108934895,0.00016782492,0.000052241492,0.000044390843,0.000014436075,0.00009296863,0.000077484576,0.000007748988],"category_scores_gemma":[0.00004447873,0.00010781742,0.000032031625,0.00020051948,0.000014040219,0.00013023737,0.000023423054,0.000059026785,0.0000074031013],"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":[0.0000015312538,0.0000041104413,0.00016400484,0.000028739716,0.00000852387,1.4105989e-7,0.00028408074,0.9163506,0.00007252933,0.000014992646,0.0014888981,0.081581876],"study_design_scores_gemma":[0.000109519024,0.000012013355,0.00018284727,0.000030071746,0.000013976245,0.0000025441325,0.000102409256,0.9941343,0.0020671359,0.00003546504,0.003196242,0.00011346837],"about_ca_topic_score_codex":0.000031567797,"about_ca_topic_score_gemma":0.000012628169,"teacher_disagreement_score":0.15746292,"about_ca_system_score_codex":0.000026584197,"about_ca_system_score_gemma":0.0000041902704,"threshold_uncertainty_score":0.43966666},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011733293,0.0006233776,0.9860579,0.000021921618,0.000056102548,0.00023076768,0.0000058237615,0.00006244044,0.0012084044],"genre_scores_gemma":[0.9842129,0.000050216007,0.015622618,0.0000053503477,0.00005818416,0.00002085351,0.0000028969703,0.000010282155,0.000016736964],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999428,0.00008552949,0.00023919051,0.00007110218,0.000086091626,0.000090096044],"domain_scores_gemma":[0.99980533,0.000071269664,0.000017729973,0.000059599603,0.00003321026,0.000012881669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051380246,0.000061820865,0.00009905496,0.000045829976,0.000027385673,0.000033366756,0.000045413777,0.000037392667,0.0000018012662],"category_scores_gemma":[0.000037860125,0.000045542827,0.0000058971864,0.00006225345,0.000007502082,0.00010097266,0.0000070000788,0.00005776477,9.943707e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001211253,0.000005621923,0.00006891037,0.000069090194,0.000001814239,0.0000012613295,0.0023361489,0.9956977,0.0002627717,0.00022175987,0.00046898075,0.00086477457],"study_design_scores_gemma":[0.00005790196,0.000017327146,0.0000074703908,0.000092404945,0.0000035352189,0.0000053600966,0.00063732575,0.9985361,0.00050503627,0.000014256345,0.00007015252,0.000053089858],"about_ca_topic_score_codex":0.0000978935,"about_ca_topic_score_gemma":0.000009293291,"teacher_disagreement_score":0.9724796,"about_ca_system_score_codex":0.000010478975,"about_ca_system_score_gemma":0.0000011966116,"threshold_uncertainty_score":0.18571827},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3520942,0.00019003499,0.59816265,0.000052348565,0.00021649252,0.00013570646,0.00003602238,0.0004871066,0.048625454],"genre_scores_gemma":[0.997225,0.000016900693,0.002143735,0.00011518571,0.00015572457,0.000021443768,0.000025229805,0.000051700372,0.000245121],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99815005,0.00014448777,0.00052761944,0.00031825865,0.00034191244,0.00051769265],"domain_scores_gemma":[0.99896115,0.0003070123,0.00013136165,0.0003757727,0.00008826515,0.00013640878],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006729678,0.00028204723,0.0005444296,0.00015210475,0.0001907332,0.00008947451,0.00028350568,0.00009519731,0.000020091245],"category_scores_gemma":[0.00016503032,0.00027140247,0.00016442631,0.0006136449,0.00003427266,0.00038315478,0.000066978915,0.00022839181,0.00008304178],"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":[0.0000029614353,0.0000106994385,0.001353581,0.000097163545,0.00031569423,0.000002963684,0.012467211,0.9825128,0.00051114353,0.0001051377,0.00033965905,0.002280993],"study_design_scores_gemma":[0.00018695316,0.000018319906,0.00023818576,0.00009353806,0.00017804219,0.0000020547272,0.0011749071,0.9959389,0.0005746526,0.0003232368,0.0009375005,0.00033373872],"about_ca_topic_score_codex":0.00054246193,"about_ca_topic_score_gemma":0.00012762073,"teacher_disagreement_score":0.64513075,"about_ca_system_score_codex":0.00006811918,"about_ca_system_score_gemma":0.000013782458,"threshold_uncertainty_score":0.99997383},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935612,0.000035870824,0.0011793929,0.001991214,0.00026745748,0.00022106094,0.000030764535,0.000030392184,0.0026826274],"genre_scores_gemma":[0.9910513,0.0000053521967,0.006732952,0.0012889632,0.00032598377,0.0000018651521,0.000053982465,0.0000147902565,0.00052479655],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99900293,0.000028749448,0.00036546058,0.00017835683,0.00018188015,0.00024261269],"domain_scores_gemma":[0.9988142,0.00047800803,0.00007914898,0.00017636274,0.00027517357,0.00017705186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060340646,0.000092193586,0.00019062603,0.00012992784,0.000074194286,0.000009737294,0.000059277285,0.000074872485,0.00007615578],"category_scores_gemma":[0.00035596424,0.00008707363,0.000042367712,0.00024628363,0.000020953814,0.00022158143,0.00001142323,0.00012341017,0.000010535736],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012625708,0.0006284322,0.81042856,0.00059995207,0.00021067463,0.00007437682,0.025028186,0.01479631,0.06170842,0.00014183624,0.005666573,0.0794541],"study_design_scores_gemma":[0.0012326941,0.0013710406,0.6636934,0.0004938825,0.00096809084,0.00019011014,0.017283298,0.010516891,0.02337205,0.000024227678,0.28024974,0.00060452893],"about_ca_topic_score_codex":0.0018335511,"about_ca_topic_score_gemma":0.0019941377,"teacher_disagreement_score":0.27458316,"about_ca_system_score_codex":0.000032919754,"about_ca_system_score_gemma":0.00006949176,"threshold_uncertainty_score":0.35507596},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96977854,0.0011353912,0.003753645,0.0006733458,0.00097104075,0.0005232815,0.00005708872,0.00044331857,0.022664359],"genre_scores_gemma":[0.90280783,0.000060079146,0.09200986,0.000356716,0.0002688714,0.000029086004,0.00000508622,0.00004631775,0.004416165],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99856424,0.000086116066,0.00039139375,0.0002899304,0.00030309087,0.00036523034],"domain_scores_gemma":[0.99690115,0.002421031,0.00011710536,0.00019341361,0.00027275583,0.0000945425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041310448,0.00017242019,0.00038561484,0.00008336004,0.000089386944,0.000031120584,0.0001637364,0.000060872215,0.00023771195],"category_scores_gemma":[0.004797564,0.00012876993,0.00006512697,0.0006077793,0.000048882946,0.000098605575,0.00012242759,0.00016751101,0.00069762516],"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":[0.0003876339,0.0022561648,0.052905347,0.0036096962,0.002392984,0.00036689435,0.017173735,0.0002490875,0.0056801965,0.23781596,0.30798173,0.3691806],"study_design_scores_gemma":[0.004726694,0.001688838,0.00725117,0.0011439393,0.0004443961,0.00011527546,0.022348868,0.029790217,0.009840851,0.87719995,0.042298462,0.00315132],"about_ca_topic_score_codex":0.000031098272,"about_ca_topic_score_gemma":0.0000010177583,"teacher_disagreement_score":0.63938403,"about_ca_system_score_codex":0.000038033406,"about_ca_system_score_gemma":0.00001317232,"threshold_uncertainty_score":0.8966792},"labels":[],"label_agreement":null}]}