{"meta":{"query_hash":"97e5c95617f1","filters":{"venue":"EPiC series in engineering"},"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/97e5c95617f1","api":"https://metacan.xera.ac/api/v1/cohort?venue=EPiC+series+in+engineering"},"results":[{"id":"W2908743399","doi":"10.29007/2k64","title":"Shape Optimization of Hydraulic Structures: an Example of an Optimum Design of a Fish Passage","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Water Systems and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BGC Engineering (Canada)","funders":"","keywords":"Computer science; Mathematical optimization; Optimization problem; Numerical analysis; Function (biology); Orientation (vector space); Optimal design; A priori and a posteriori; Position (finance); Shape optimization; Algorithm; Mathematics; Finite element method; Engineering; Geometry; Structural engineering","score_opus":0.017013076199943956,"score_gpt":0.20088713026427316,"score_spread":0.1838740540643292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2908743399","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":[0.35296062,0.000053139396,0.6460966,0.000002995969,0.00034595103,0.0002138035,0.000010289093,0.00011541587,0.00020123678],"genre_scores_gemma":[0.9088379,0.00001835958,0.0909802,0.0000027553108,0.00007844219,0.000010545083,0.000023294786,0.000040436316,0.000008056911],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990939,0.000028229946,0.000443582,0.00014394715,0.00012314385,0.0001672091],"domain_scores_gemma":[0.99948907,0.000027660572,0.00007419511,0.00029819095,0.00006844346,0.000042420746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018087828,0.00014601613,0.00028429297,0.00019281804,0.000012553619,0.00001003822,0.00016558765,0.00010062233,0.00008143981],"category_scores_gemma":[0.000028453438,0.00015706553,0.000024703508,0.00029200772,0.00003866398,0.00046412146,0.000021238942,0.00006273195,1.8185492e-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":[0.000014452729,0.00001312709,0.00008536168,0.00023726249,0.000017490776,0.0000010419009,0.0018582739,0.9929124,0.0043901834,0.00018974097,0.000017200187,0.00026346423],"study_design_scores_gemma":[0.0002302698,0.0002063574,0.00080327387,0.00008655622,0.000007557512,0.0000042810666,0.0001228343,0.953837,0.044478748,0.000036160847,0.000051667106,0.0001353248],"about_ca_topic_score_codex":0.00012593054,"about_ca_topic_score_gemma":0.000068721965,"teacher_disagreement_score":0.5558773,"about_ca_system_score_codex":0.000026530666,"about_ca_system_score_gemma":0.00001079355,"threshold_uncertainty_score":0.64049464},"labels":[],"label_agreement":null},{"id":"W2909091414","doi":"10.29007/kwml","title":"Superhuman Sports Games in Laval Virtual","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Persona Design and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Event (particle physics); Function (biology); Computer science; Human–computer interaction; Jumper; Simulation; Engineering; Physical medicine and rehabilitation; Psychology; Medicine; Physics","score_opus":0.00740457361612075,"score_gpt":0.21090268912551452,"score_spread":0.20349811550939376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909091414","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":[0.8798223,0.00008436572,0.11752948,0.00035412863,0.0003381333,0.00008866436,6.344514e-7,0.00018870352,0.0015935526],"genre_scores_gemma":[0.9883552,0.000013495474,0.011275692,0.00004893116,0.00009831093,0.00002229105,7.171146e-7,0.000006356623,0.00017896866],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99939996,0.000006334647,0.0001263111,0.000181158,0.000094625175,0.0001916076],"domain_scores_gemma":[0.99968237,0.00002129283,0.000010494849,0.0002428015,0.000009807991,0.000033231256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011885994,0.000077190685,0.00008695327,0.00012015706,0.000022303302,0.000032115222,0.0003048577,0.00003224497,0.000019937022],"category_scores_gemma":[0.000022237518,0.000083984545,0.000014941665,0.00033312332,0.00003035375,0.00031155083,0.00007243899,0.00008553736,0.00001347247],"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":[0.000018813678,0.0002127295,0.041061252,0.00006355876,0.000017628581,0.00024553994,0.028230447,0.011962102,0.043911427,0.8044112,0.0013379914,0.06852732],"study_design_scores_gemma":[0.0012608264,0.0003609753,0.48955944,0.0003043585,0.0000043115506,0.00015130095,0.0008243519,0.3767369,0.039641608,0.0060654883,0.083688274,0.0014021287],"about_ca_topic_score_codex":0.00002103236,"about_ca_topic_score_gemma":0.000038934275,"teacher_disagreement_score":0.7983457,"about_ca_system_score_codex":0.000033426117,"about_ca_system_score_gemma":0.000018468354,"threshold_uncertainty_score":0.34247905},"labels":[],"label_agreement":null},{"id":"W2909274434","doi":"10.29007/nfk8","title":"A Spatio-Temporal Statistical Downscaling Approach to Deriving Extreme Rainfall IDF Relations at Ungauged Sites in the Context of Climate Change","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Climate variability and models","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Downscaling; Climatology; Context (archaeology); Environmental science; GCM transcription factors; Scale (ratio); Climate change; Jackknife resampling; Meteorology; General Circulation Model; Precipitation; Computer science; Statistics; Mathematics; Geography; Geology; Cartography","score_opus":0.038925728963608734,"score_gpt":0.24051600719991556,"score_spread":0.20159027823630682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909274434","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":[0.9851746,0.000017298202,0.011771941,0.00020657662,0.00006696794,0.0003631879,0.000024179131,0.000027712074,0.0023475674],"genre_scores_gemma":[0.98427296,0.000009990744,0.015459122,0.000091041715,0.000036529804,0.00008055986,0.00002636848,0.00001154256,0.0000118746],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898446,0.000054903216,0.00030142703,0.00021664532,0.00015934117,0.00028320626],"domain_scores_gemma":[0.99947524,0.000224049,0.0000376338,0.00021397835,0.000005538088,0.000043577234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065608893,0.000113601745,0.00015999786,0.00006005438,0.000068863614,0.00001574239,0.00016212113,0.000053145544,0.00028509993],"category_scores_gemma":[0.000254469,0.000099440906,0.00002294343,0.0002866775,0.00010668564,0.00021198024,0.00018565402,0.00011444368,0.000025041754],"study_design_candidate":"observational","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":[0.00011129028,0.00020678197,0.8139927,0.00017590495,0.00001082558,0.000008496444,0.07016737,0.091058776,0.0064704516,0.01607306,0.00008878919,0.0016355702],"study_design_scores_gemma":[0.00058648904,0.00014573251,0.49042547,0.00015098871,0.000014269758,0.000015606818,0.002497306,0.5022095,0.00053896673,0.00067536416,0.002310741,0.00042954707],"about_ca_topic_score_codex":0.00041689692,"about_ca_topic_score_gemma":0.0024236618,"teacher_disagreement_score":0.41115072,"about_ca_system_score_codex":0.00015875473,"about_ca_system_score_gemma":0.000003465727,"threshold_uncertainty_score":0.40550825},"labels":[],"label_agreement":null},{"id":"W2912482102","doi":"10.29007/v979","title":"Risk Informed Decision-Making Framework for Operating Reservoirs Under Flooding Conditions: Accounting for Uncertainty and Risk","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Risk analysis (engineering); Computer science; Risk management; Decision support system; Flood myth; Hydropower; Decision analysis; Flooding (psychology); Multiple-criteria decision analysis; Process (computing); Probabilistic logic; Risk management plan; Risk assessment; Operations research; Management science; Engineering; IT risk management; Business; Data mining; Computer security","score_opus":0.01608483633349839,"score_gpt":0.3198108192835469,"score_spread":0.3037259829500485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912482102","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":[0.46954066,0.00023986367,0.52887034,0.000009798046,0.0006595017,0.00032579823,0.000038683156,0.0002695806,0.00004580301],"genre_scores_gemma":[0.57799304,0.00017700154,0.4211884,0.0000092253895,0.00037337685,0.00017544493,0.0000100547995,0.00006744185,0.000006013268],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99829805,0.000027059088,0.0006047358,0.00032095856,0.0001641728,0.00058503053],"domain_scores_gemma":[0.9946024,0.004767401,0.00008581612,0.00033195585,0.00012520821,0.00008725073],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010508773,0.0003225635,0.0003770245,0.00034045475,0.00034345055,0.00019193089,0.00021668538,0.00023636484,0.000021920225],"category_scores_gemma":[0.008188686,0.0003504274,0.00008962158,0.0004376546,0.00005428165,0.0006186642,0.00007011426,0.00041158698,0.0000017420333],"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":[0.000028162878,0.0000035104122,0.002711121,0.00025280332,0.00006464736,6.006077e-7,0.00080893736,0.9902944,0.00011578375,0.0031373245,0.00003968527,0.0025430177],"study_design_scores_gemma":[0.0006817041,0.0000636415,0.0037236002,0.0007355743,0.000029790346,0.000005231971,0.00067953655,0.9798518,0.00045238633,0.012315298,0.0010513469,0.0004100818],"about_ca_topic_score_codex":0.000013959854,"about_ca_topic_score_gemma":0.000055592987,"teacher_disagreement_score":0.108452365,"about_ca_system_score_codex":0.00017339834,"about_ca_system_score_gemma":0.00002656482,"threshold_uncertainty_score":0.9998948},"labels":[],"label_agreement":null},{"id":"W2913758759","doi":"10.29007/1xw5","title":"Spatially Distributed Hydrological Modelling of a Western Africa Basin","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Universidad Autónoma del Estado de México","keywords":"Environmental science; Precipitation; Surface runoff; Rain gauge; Tributary; Meteorology; Climatology; Structural basin; Drainage basin; Hydrological modelling; Calibration; Hydrology (agriculture); Geography; Geology; Statistics; Mathematics","score_opus":0.01549995143712321,"score_gpt":0.19403013009957842,"score_spread":0.1785301786624552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913758759","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":[0.875768,0.000019420675,0.12101269,0.00026595275,0.00012138126,0.000079838625,0.0000027498772,0.000049040973,0.002680893],"genre_scores_gemma":[0.9971973,0.000014021699,0.00261526,0.000026222884,0.00002995687,0.000010495084,0.0000023337627,0.0000060533507,0.00009835995],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993553,0.000014751286,0.00016398278,0.00016003511,0.00008541479,0.00022051846],"domain_scores_gemma":[0.9997967,0.000027708194,0.000026646067,0.00012302716,0.000002817888,0.000023117822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014707641,0.000092915616,0.00014636324,0.000031207102,0.000036145804,0.0000039225315,0.00013302708,0.00004805494,0.00022725653],"category_scores_gemma":[0.000029734041,0.00008413243,0.000021069613,0.00014724351,0.00016750522,0.000112836664,0.0001975657,0.000072088784,0.00003755312],"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":[0.00003466316,0.000029853245,0.1106049,0.000015461632,0.000016155538,0.000014502685,0.0010419373,0.8874162,0.00041619083,0.00018927317,0.00007203058,0.0001488236],"study_design_scores_gemma":[0.00093611644,0.0006824535,0.17179856,0.00008300009,0.00003885906,0.000011618523,0.00013001684,0.7858276,0.006717789,0.0025027264,0.03061429,0.0006569614],"about_ca_topic_score_codex":0.00005448362,"about_ca_topic_score_gemma":0.000036219917,"teacher_disagreement_score":0.121429265,"about_ca_system_score_codex":0.000031671618,"about_ca_system_score_gemma":0.0000010500835,"threshold_uncertainty_score":0.34308207},"labels":[],"label_agreement":null},{"id":"W2914966301","doi":"10.29007/5xqt","title":"Scale-Invariance Generalized Logistic (GLO) Model for Estimating Extreme Design Rainfalls in the Context of Climate Change","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Climate variability and models","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Robustness (evolution); Climate change; Context (archaeology); Climate model; Scaling; Scale (ratio); Computer science; Statistical model; Environmental science; Range (aeronautics); Climatology; Extreme value theory; Meteorology; Econometrics; Statistics; Mathematics; Geography; Machine learning; Engineering; Cartography; Geology","score_opus":0.10508369378597239,"score_gpt":0.2785086049054781,"score_spread":0.1734249111195057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914966301","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":[0.22302848,0.00003286158,0.7753075,0.000285885,0.00020392999,0.0007852872,0.000019991656,0.00003728737,0.00029881322],"genre_scores_gemma":[0.78754735,0.000028879193,0.21198797,0.0001431226,0.00005368442,0.00021175593,0.00000288441,0.000013230282,0.000011088211],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893486,0.00004393076,0.0003284582,0.00022595133,0.000123463,0.00034331743],"domain_scores_gemma":[0.9993797,0.00026409564,0.00006291753,0.00025740167,0.000009009753,0.00002688258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010692836,0.00013498888,0.00021489525,0.000038450442,0.00005147432,0.000017070484,0.00025990454,0.00006259101,0.00005706447],"category_scores_gemma":[0.00031038997,0.00010551882,0.000035699177,0.0001920618,0.00014402095,0.0002607713,0.00009566131,0.00008267535,0.0000044389717],"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":[0.00006855,0.000045302506,0.0021252637,0.00012021814,0.000003237562,0.0000019431623,0.010454788,0.97634315,0.004577124,0.0025400908,0.00001654461,0.0037037702],"study_design_scores_gemma":[0.00038852714,0.000051086223,0.0009809409,0.00008050989,0.0000053831463,0.0000031823172,0.00013503408,0.9956704,0.00048809362,0.0020216512,0.000047953217,0.00012727607],"about_ca_topic_score_codex":0.0001562438,"about_ca_topic_score_gemma":0.00027355994,"teacher_disagreement_score":0.56451887,"about_ca_system_score_codex":0.000091167756,"about_ca_system_score_gemma":0.0000061364626,"threshold_uncertainty_score":0.43029323},"labels":[],"label_agreement":null},{"id":"W2915040712","doi":"10.29007/2bg2","title":"\"Real Baby - Real Family\": Holdable tangible baby VR","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Grief, Bereavement, and Mental Health","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Exhibition; Anime; Virtual reality; Multimedia; Human–computer interaction; Computer science; Visual arts; Art; Artificial intelligence","score_opus":0.021232426100992612,"score_gpt":0.29968950695264773,"score_spread":0.2784570808516551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2915040712","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":[0.8177436,0.00023863907,0.00039891948,0.000082308405,0.0039406978,0.00027554977,0.000023846284,0.00026017535,0.17703629],"genre_scores_gemma":[0.98888206,0.0002938097,0.0016179335,0.0001674636,0.0007763837,0.00009092648,0.000031991913,0.000063664986,0.008075764],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99830145,0.00003609048,0.00035920442,0.0003798143,0.0001663378,0.0007571125],"domain_scores_gemma":[0.99926126,0.0000516596,0.000053877047,0.00045084956,0.000026300879,0.00015602329],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029417992,0.0002345964,0.00027391454,0.00017261977,0.00009167343,0.000024509447,0.00022369054,0.00014970348,0.0008704059],"category_scores_gemma":[0.00001593386,0.00024950525,0.000051434563,0.00033039035,0.00008184252,0.00020055292,0.000080167,0.00022669593,0.00026860725],"study_design_candidate":"observational","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":[0.0017234702,0.0021247694,0.18318024,0.002753409,0.0008250052,0.001148454,0.092493236,0.0020513728,0.09604509,0.4796416,0.0897474,0.048265953],"study_design_scores_gemma":[0.006227041,0.0029994948,0.5730155,0.00075167336,0.000075599804,0.00020477938,0.015717726,0.0018250068,0.017147077,0.0018370341,0.37779787,0.00240119],"about_ca_topic_score_codex":0.0027007635,"about_ca_topic_score_gemma":0.0003210639,"teacher_disagreement_score":0.47780457,"about_ca_system_score_codex":0.0001930263,"about_ca_system_score_gemma":0.000037218226,"threshold_uncertainty_score":0.9999957},"labels":[],"label_agreement":null},{"id":"W2917428835","doi":"10.29007/qht4","title":"Simulation of Extreme Hydrometeorological Events under Tropical Conditions Using a Distributed Hydrological Model","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"École de Technologie Supérieure; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","funders":"","keywords":"Hydrometeorology; Environmental science; Calibration; Streamflow; Structural basin; Hydrology (agriculture); Climatology; Drainage basin; Meteorology; Precipitation; Geography; Statistics; Mathematics; Geology; Cartography","score_opus":0.03476182419907358,"score_gpt":0.2563272468901102,"score_spread":0.22156542269103663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917428835","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":[0.811087,0.000006178801,0.1884453,0.000107603,0.00006187951,0.00008371395,0.0000043359514,0.000036589558,0.00016739339],"genre_scores_gemma":[0.99728835,0.0000029208968,0.0025892959,0.000052475974,0.000022954217,0.000010138377,0.000007933603,0.000006108648,0.000019825968],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992112,0.000027822427,0.00021403775,0.00019777885,0.00011223731,0.00023695428],"domain_scores_gemma":[0.99973863,0.00006692831,0.000036193895,0.000120981786,0.00000465291,0.000032617343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009357571,0.000110620866,0.00017271748,0.000047484224,0.00006981483,0.0000034629932,0.00011039318,0.000089264104,0.00039102315],"category_scores_gemma":[0.00009640707,0.000098395234,0.00003458492,0.00019063728,0.00024379116,0.00019620755,0.00018293754,0.00009628687,0.000015226604],"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":[0.000023325156,0.000038691138,0.038429685,0.00000453149,0.000013056532,0.0000033179265,0.000077650584,0.9587132,0.0022729186,0.00040733698,0.0000058216806,0.000010478278],"study_design_scores_gemma":[0.00019779275,0.00008597279,0.109764785,0.0000066181988,0.000011204249,0.0000017804871,0.00001592017,0.8858126,0.00023266912,0.0037442036,0.00003637106,0.00009008625],"about_ca_topic_score_codex":0.000009073731,"about_ca_topic_score_gemma":0.000008881552,"teacher_disagreement_score":0.18620135,"about_ca_system_score_codex":0.00007609736,"about_ca_system_score_gemma":0.0000018229149,"threshold_uncertainty_score":0.42814294},"labels":[],"label_agreement":null},{"id":"W2921594966","doi":"10.29007/r6xs","title":"Development of Decision Support Tool for Evaluation of Urban Water System Metabolism Efficiency","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Sustainability and Ecological Systems Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Sustainability; Decision support system; Redevelopment; Greenhouse gas; Stormwater; Neighbourhood (mathematics); Sustainable development; Process (computing); Environmental planning; Environmental economics; Computer science; Environmental resource management; Environmental science; Engineering; Civil engineering","score_opus":0.010365567325309565,"score_gpt":0.23131525137010325,"score_spread":0.22094968404479368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921594966","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":[0.9757654,0.00001373176,0.023526944,0.000005135451,0.00016576286,0.00028677325,8.3987567e-7,0.000012246492,0.00022314084],"genre_scores_gemma":[0.9878669,3.129929e-7,0.012004495,0.0000015858352,0.0000226921,0.00007097747,0.0000023692187,0.000004517221,0.000026194253],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989283,0.000021194706,0.00042933895,0.00015561725,0.00028784448,0.00017770333],"domain_scores_gemma":[0.99969184,0.000047348,0.000050001814,0.00014585102,0.000044123666,0.000020820995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020039103,0.00007333194,0.00019816995,0.00005151091,0.000038873193,0.0000043483733,0.00011791583,0.000049047714,0.00050565146],"category_scores_gemma":[0.00025846311,0.000053440555,0.00004379496,0.00017290945,0.0000473876,0.000108601715,0.00007692575,0.00002368325,0.0000099379195],"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":[0.0003102993,0.00042234245,0.09401432,0.0015446135,0.0001593964,0.0000043297846,0.03971679,0.68985915,0.097823806,0.0028470529,0.00013824292,0.073159665],"study_design_scores_gemma":[0.0020491807,0.0003319605,0.32682163,0.00017444967,0.00016191322,0.000008126908,0.0053263167,0.31530404,0.33330315,0.0004047015,0.01550219,0.0006123287],"about_ca_topic_score_codex":0.000022910772,"about_ca_topic_score_gemma":0.000032926408,"teacher_disagreement_score":0.3745551,"about_ca_system_score_codex":0.0002609034,"about_ca_system_score_gemma":0.000013049996,"threshold_uncertainty_score":0.5536529},"labels":[],"label_agreement":null},{"id":"W2921803332","doi":"10.29007/93gh","title":"Extracting High Resolution Snow Distribution Information with Inexpensive Autonomous Cameras","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital","funders":"","keywords":"Snow; Computer science; Silhouette; Computer vision; Artificial intelligence; Remote sensing; Projection (relational algebra); Cluster analysis; Distortion (music); Matching (statistics); Digital elevation model; Elevation (ballistics); Filter (signal processing); Geography; Meteorology; Mathematics","score_opus":0.007058745859789427,"score_gpt":0.1806929167694069,"score_spread":0.17363417090961747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921803332","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":[0.9734036,0.0001236574,0.024586344,0.00030121152,0.0006300627,0.0001402301,0.000036159643,0.00010070086,0.0006780761],"genre_scores_gemma":[0.9954008,0.000028483726,0.004077354,0.000048586153,0.00017248081,0.000003816235,0.00024103238,0.000002421551,0.000025010351],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99940646,0.000007945077,0.0001790206,0.00009602763,0.00010410435,0.00020645736],"domain_scores_gemma":[0.9996776,0.0000747384,0.000056212462,0.00009721691,0.00006212119,0.00003212244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000950456,0.000094400086,0.00009880016,0.000029086546,0.00014032585,0.00004036895,0.000059016136,0.000036857255,0.00023352115],"category_scores_gemma":[0.00017707537,0.000083736995,0.000012179962,0.00030266173,0.000044562286,0.0008283526,0.000009446534,0.00009599602,0.00003138991],"study_design_candidate":"observational","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":[0.00016471869,0.000015238971,0.3325052,0.00006607842,0.00004822562,0.000017344697,0.004366911,0.59603095,0.00004375411,0.0026099107,0.00087749015,0.06325418],"study_design_scores_gemma":[0.00018295577,0.00013391927,0.9151425,0.000044516448,0.0000049278688,0.0000147684395,0.0009914406,0.06158041,0.00011540733,0.00003205836,0.021612182,0.00014495933],"about_ca_topic_score_codex":0.002149135,"about_ca_topic_score_gemma":0.0020642856,"teacher_disagreement_score":0.58263725,"about_ca_system_score_codex":0.000027818634,"about_ca_system_score_gemma":0.000020332272,"threshold_uncertainty_score":0.34146956},"labels":[],"label_agreement":null},{"id":"W2922941270","doi":"10.29007/4fcr","title":"On-line Measuring Sensors for Smart Water Network Monitoring","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Cloud computing; General partnership; Smart city; Information and Communications Technology; Big data; Computer science; Telecommunications; Work (physics); Computer security; Engineering; Business; Internet of Things; World Wide Web","score_opus":0.03670574235515049,"score_gpt":0.24678336636907267,"score_spread":0.21007762401392216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922941270","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":[0.99330485,0.000014524955,0.0036519829,0.00022513371,0.0018819333,0.00019231589,9.960073e-7,0.0004265581,0.00030170896],"genre_scores_gemma":[0.97566986,0.000005524609,0.023294806,0.000009418233,0.0006540153,0.00007162508,0.0000012280395,0.0000363375,0.00025720784],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99868965,0.00001415346,0.00023590366,0.00029942268,0.00017819549,0.0005826845],"domain_scores_gemma":[0.9995157,0.00008990612,0.000022533153,0.00032087855,0.000007577409,0.00004339317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042600953,0.00018367125,0.00017160209,0.000058028654,0.000103566636,0.000030236262,0.00027751797,0.000096424716,0.000053498745],"category_scores_gemma":[0.00020012229,0.00015934187,0.000039403993,0.00016182591,0.00009883072,0.00019635205,0.00023653985,0.0001628585,0.00009910309],"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":[0.00008068022,0.00003223091,0.06046727,0.00006776452,0.000025919135,0.000015990563,0.0012811179,0.90473455,0.030309852,0.000605035,0.0003019481,0.0020776433],"study_design_scores_gemma":[0.00039139757,0.00031277124,0.011894015,0.00019667289,0.0000073396627,0.0000086857945,0.00012930596,0.008590148,0.9645732,0.0037607828,0.009627038,0.0005086542],"about_ca_topic_score_codex":0.0000434184,"about_ca_topic_score_gemma":0.000008747395,"teacher_disagreement_score":0.93426335,"about_ca_system_score_codex":0.00021908747,"about_ca_system_score_gemma":0.0000016802425,"threshold_uncertainty_score":0.6497773},"labels":[],"label_agreement":null},{"id":"W2935760136","doi":"10.29007/xlv7","title":"Assessing the Effect of Streamflow Estimation at Potential Station Locations In Entropy-Based Hydrometric Network Design","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Interpolation (computer graphics); Streamflow; Multivariate interpolation; Computer science; Entropy (arrow of time); Network planning and design; Data mining; Artificial intelligence; Geography; Bilinear interpolation; Computer network; Cartography","score_opus":0.006071666667628589,"score_gpt":0.2247150787275477,"score_spread":0.2186434120599191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2935760136","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":[0.7096504,0.000022219943,0.28979468,0.000100867095,0.00014006712,0.00017358646,2.6488652e-7,0.00001745485,0.00010043473],"genre_scores_gemma":[0.9915563,0.0000045904494,0.008341008,0.000011422443,0.000022342818,0.000034128712,0.0000054610123,0.000005893799,0.000018872563],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938476,0.00008355677,0.00015246827,0.00011433534,0.00009815426,0.00016672768],"domain_scores_gemma":[0.999657,0.00018205594,0.00004249922,0.000105414554,0.000002337271,0.0000107051255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048613336,0.0000788866,0.000096721495,0.0000889928,0.00008849074,0.00001117735,0.00008429422,0.000029444245,0.000108145694],"category_scores_gemma":[0.00010717008,0.00006256452,0.000014578818,0.0005187363,0.000102295904,0.00021851576,0.000062202795,0.000056781257,0.000017101926],"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":[0.000015142353,0.0000061235623,0.055255953,0.00001483833,0.0000058007504,0.0000018078164,0.00014046782,0.94312215,0.0004900982,0.000012999943,0.000042002834,0.000892629],"study_design_scores_gemma":[0.00025349553,0.00012865265,0.19159105,0.000025227528,0.0000121695775,7.160266e-7,0.000015665955,0.8031449,0.004629976,0.00009930625,0.000035049783,0.000063816005],"about_ca_topic_score_codex":0.000053833406,"about_ca_topic_score_gemma":0.000038807284,"teacher_disagreement_score":0.28190586,"about_ca_system_score_codex":0.00012475016,"about_ca_system_score_gemma":0.0000021328572,"threshold_uncertainty_score":0.2551307},"labels":[],"label_agreement":null},{"id":"W2941722777","doi":"10.29007/hd8l","title":"Impacts of Regional Climate Model Spatial Resolution on Summer Flood Simulation","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ouranos; École de Technologie Supérieure","funders":"","keywords":"Flood myth; Environmental science; Climate model; Precipitation; Streamflow; Climatology; Climate change; General Circulation Model; Meteorology; Geography; Drainage basin; Geology; Cartography","score_opus":0.016189754924488854,"score_gpt":0.23826149088595902,"score_spread":0.22207173596147017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2941722777","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":[0.98336226,0.000009376097,0.014356147,0.0001677361,0.00012939541,0.000077719196,0.0000014741333,0.000029373155,0.0018664959],"genre_scores_gemma":[0.9989487,0.0000202102,0.00089160784,0.000056285884,0.000041301173,0.00000485699,0.000002773246,0.0000060029784,0.00002824487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994892,0.00000901195,0.000121055,0.000117617834,0.00009259487,0.00017054658],"domain_scores_gemma":[0.99983644,0.000020653975,0.000026542133,0.0000970759,0.0000030452866,0.000016210592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012751382,0.000070525806,0.00007962651,0.000043544558,0.000043408927,0.0000023755617,0.000056516532,0.000036301102,0.000070870294],"category_scores_gemma":[0.000033015294,0.000067890505,0.000015870093,0.0000787081,0.00008356885,0.00014015501,0.000060452676,0.00004931497,0.000029691033],"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":[0.000071845905,0.000013945739,0.015733862,0.000010538342,0.000005393774,9.256537e-7,0.0004219535,0.9823152,0.0009108169,0.00029125187,0.00005254693,0.00017171247],"study_design_scores_gemma":[0.00017983968,0.0000947236,0.09509191,0.000021429556,0.0000043465425,3.366233e-7,0.0000151276945,0.90261406,0.001379285,0.0002417393,0.00028258117,0.00007461974],"about_ca_topic_score_codex":0.00007997385,"about_ca_topic_score_gemma":0.00013379136,"teacher_disagreement_score":0.07970115,"about_ca_system_score_codex":0.000048393722,"about_ca_system_score_gemma":0.0000011381708,"threshold_uncertainty_score":0.27684945},"labels":[],"label_agreement":null},{"id":"W4244301662","doi":"10.29007/wrn8","title":"Comparison of Two Data-Driven Streamflow Forecast Approaches in an Adaptive Optimal Reservoir Operation Model","year":2018,"lang":"en","type":"article","venue":"EPiC series in engineering","topic":"Water resources management and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Adaptive neuro fuzzy inference system; Inflow; Streamflow; Computer science; Data mining; Fuzzy logic; Fuzzy control system; Artificial intelligence; Meteorology","score_opus":0.11326523586614887,"score_gpt":0.290371155848482,"score_spread":0.17710591998233313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244301662","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":[0.7396773,0.000051964227,0.2591943,0.000008347655,0.00009213802,0.00017921331,0.000009570803,0.00010437306,0.00068277324],"genre_scores_gemma":[0.9154067,0.0000074587992,0.08428015,0.0000012653811,0.000081193735,0.00001936686,0.00015585206,0.000032172917,0.00001585076],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999139,0.000015540958,0.00031061162,0.00020792295,0.00011428412,0.00021263734],"domain_scores_gemma":[0.99955153,0.000012165577,0.000026840811,0.0003605433,0.000017424396,0.000031495612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014210705,0.00015101793,0.00021931404,0.00021940786,0.000020331585,0.00004205064,0.00031936122,0.000054239852,0.000011450896],"category_scores_gemma":[0.000012859461,0.00016686152,0.000013697781,0.00022898287,0.000032815296,0.0011482356,0.00012952136,0.00012511062,0.0000016642823],"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":[0.000028037597,0.000026607686,0.0039357217,0.00006222308,0.000012422908,0.0000011755876,0.0030347826,0.9916499,0.0002475915,0.00045220176,0.000014954531,0.00053436216],"study_design_scores_gemma":[0.00031917222,0.00008974503,0.00073393417,0.000052665226,0.00000641557,4.2029606e-7,0.00046941158,0.9957017,0.0024121949,0.00001748732,0.00003571159,0.00016117006],"about_ca_topic_score_codex":0.000021965121,"about_ca_topic_score_gemma":0.00044741476,"teacher_disagreement_score":0.1757294,"about_ca_system_score_codex":0.00006087427,"about_ca_system_score_gemma":0.0000055690657,"threshold_uncertainty_score":0.6804415},"labels":[],"label_agreement":null}]}