{"meta":{"query_hash":"cfc49d954865","filters":{"venue":"World Environmental and Water Resources Congress 2014"},"cohort_total":10,"direct_labels_cover":0,"predictions_cover":10,"exported":10,"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/cfc49d954865","api":"https://metacan.xera.ac/api/v1/cohort?venue=World+Environmental+and+Water+Resources+Congress+2014"},"results":[{"id":"W2095059834","doi":"10.1061/9780784413548.057","title":"Sensor Placement Optimization for Water Quality Model Calibration","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","topic":"Water Systems and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bentley (Canada)","funders":"","keywords":"Calibration; Intrusion; Water quality; Engineering; Computer science; Field (mathematics); Data quality; Data modeling; Wireless sensor network; Data mining; Remote sensing; Real-time computing; Database","score_opus":0.008249839022229867,"score_gpt":0.18452873911997753,"score_spread":0.17627890009774766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095059834","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":[0.67340666,0.00006762629,0.324347,0.0001875738,0.0003014424,0.00052909023,0.00004567376,0.0001621158,0.00095281255],"genre_scores_gemma":[0.99088067,0.000021876891,0.0023610482,0.0000770398,0.00011545684,0.00007568083,0.0003486077,0.00004202944,0.006077579],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906206,0.00004331721,0.0002809254,0.00022697728,0.00012675217,0.00025997462],"domain_scores_gemma":[0.999724,0.000013474462,0.000024570067,0.0001566722,0.000003820712,0.00007748556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018810647,0.00018433777,0.0001784596,0.00006652317,0.00012761395,0.00008782711,0.00006446353,0.000059016314,0.00012908007],"category_scores_gemma":[7.972259e-7,0.0001209495,0.000040441675,0.0000102234035,0.000045995537,0.00017730091,0.00004713247,0.000049584964,0.000023447183],"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":[0.000026358775,0.000013160785,0.0007646024,0.000072831936,0.000018941368,1.4886328e-7,0.0007283844,0.99092233,0.0064058234,0.000019529678,0.0008296979,0.00019816024],"study_design_scores_gemma":[0.00057259866,0.000024621278,0.00007805997,0.000011261314,0.000016644315,0.0000011142102,0.000035423924,0.9434778,0.0355088,0.000041465435,0.020009492,0.00022273311],"about_ca_topic_score_codex":0.000010286914,"about_ca_topic_score_gemma":0.000027992053,"teacher_disagreement_score":0.32198593,"about_ca_system_score_codex":0.000035436136,"about_ca_system_score_gemma":3.6032816e-7,"threshold_uncertainty_score":0.49321777},"labels":[],"label_agreement":null},{"id":"W2315985130","doi":"10.1061/9780784413548.039","title":"Challenges and Opportunities in Hydraulic Modeling during Business Transformation","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","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":"American Water (Canada)","funders":"","keywords":"SCADA; Computer science; Asset management; Geographic information system; Engineering; Business; Geography; Finance","score_opus":0.014492842637681193,"score_gpt":0.1599649600454638,"score_spread":0.1454721174077826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315985130","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":[0.9934818,0.0023345435,0.00035780706,0.00020325757,0.000078187884,0.00009829424,0.000002066972,0.000053919845,0.0033901378],"genre_scores_gemma":[0.99562305,0.003848706,0.000020340163,0.000015734124,0.000045625537,0.000016172553,0.000017154762,0.0000209851,0.00039223986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940664,0.000025973864,0.00018145452,0.00013642557,0.00007734462,0.00017219449],"domain_scores_gemma":[0.99985063,0.000005170099,0.000011763725,0.00007922086,0.0000016499207,0.000051590014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009312189,0.00013631614,0.000144215,0.00012738848,0.000055276258,0.000041517327,0.0000416621,0.00003891806,0.0000133149],"category_scores_gemma":[2.6296283e-7,0.00010672293,0.000011356692,0.000011259219,0.00003890387,0.00025078614,0.000029174822,0.000059046044,0.0000071353884],"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":[0.000055041597,0.000042404423,0.004373997,0.0012704942,0.00005037887,0.000014552636,0.032839175,0.8934197,0.0051054335,0.00017815208,0.000034695015,0.06261601],"study_design_scores_gemma":[0.0012551273,0.000021945027,0.028921464,0.00021791656,0.000018087469,0.000032911805,0.00082980626,0.9385656,0.0032030633,0.00015189835,0.02626351,0.00051866134],"about_ca_topic_score_codex":0.000023091705,"about_ca_topic_score_gemma":0.00020406676,"teacher_disagreement_score":0.062097352,"about_ca_system_score_codex":0.000016377344,"about_ca_system_score_gemma":2.083064e-7,"threshold_uncertainty_score":0.43520346},"labels":[],"label_agreement":null},{"id":"W2320260603","doi":"10.1061/9780784413548.048","title":"Development of a Methodology to Predict the Failure of Large-Diameter Cast Iron Water Mains","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","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":"Queen's University","funders":"","keywords":"Mains electricity; Monte Carlo method; Corrosion; Cast iron; Sensitivity (control systems); Cumulative distribution function; Structural engineering; Materials science; Environmental science; Probability density function; Engineering; Metallurgy; Mathematics; Statistics","score_opus":0.00863825015812735,"score_gpt":0.18562734486729984,"score_spread":0.17698909470917248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2320260603","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":[0.99191135,0.00006461371,0.0071328483,0.00011364991,0.00015681285,0.00021287755,0.000017943445,0.000024031358,0.0003658886],"genre_scores_gemma":[0.99302495,0.0000051894135,0.005365727,0.000046822177,0.00004885652,0.000026953678,0.000028662103,0.000026453123,0.001426374],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.999,0.00010076263,0.0003260343,0.00016950894,0.00013536046,0.00026832474],"domain_scores_gemma":[0.9996693,0.000027459515,0.00003138242,0.00020161254,0.0000035357666,0.00006666862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003715608,0.00016226893,0.0002478569,0.000092173475,0.00006753989,0.000015474961,0.00013981275,0.00005150041,0.00017880576],"category_scores_gemma":[0.0000013452035,0.000083429586,0.000038054357,0.000020739495,0.000082678125,0.000048139995,0.00015801775,0.00007161969,0.000043378343],"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":[0.000213151,0.00019502809,0.07450116,0.0010637483,0.0005187251,0.000008091068,0.121976815,0.097426906,0.6832423,0.00009907491,0.007844524,0.0129104685],"study_design_scores_gemma":[0.0006605499,0.00007366523,0.009432497,0.00006251332,0.000041989373,0.000009910876,0.00045408352,0.004677242,0.476224,0.00001963369,0.5080529,0.00029103304],"about_ca_topic_score_codex":0.000015356263,"about_ca_topic_score_gemma":0.00033070464,"teacher_disagreement_score":0.5002084,"about_ca_system_score_codex":0.000017924647,"about_ca_system_score_gemma":5.8496164e-7,"threshold_uncertainty_score":0.34021598},"labels":[],"label_agreement":null},{"id":"W2321925644","doi":"10.1061/9780784413548.064","title":"Multisite Statistical Downscaling of Daily Precipitation Processes","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","topic":"Climate variability and models","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":"McGill University","funders":"","keywords":"Downscaling; Precipitation; Climatology; Environmental science; Climate change; Singular value decomposition; Meteorology; Computer science; Geography; Geology; Artificial intelligence","score_opus":0.007050167844099076,"score_gpt":0.20254839882071884,"score_spread":0.19549823097661978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2321925644","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":[0.9961213,0.000046099518,0.0010072733,0.00010227095,0.00005621148,0.000176075,0.00004732705,0.000022553175,0.0024208948],"genre_scores_gemma":[0.99740547,0.000042130923,0.0012576272,0.0000928397,0.000026671465,0.000017283199,0.000057523554,0.000015074235,0.0010853857],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987459,0.000090688496,0.0002829788,0.00036491815,0.00025495747,0.0002605332],"domain_scores_gemma":[0.99948055,0.0001403391,0.00006973524,0.00019145865,0.0000020971072,0.00011583649],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00027393544,0.00016338498,0.00019920376,0.000038622817,0.00012361331,0.000033301476,0.00013371382,0.00004625898,0.002410373],"category_scores_gemma":[0.000015948692,0.000117522286,0.00002793845,0.000035739507,0.00053505786,0.00017689253,0.00025545538,0.00008590708,0.00027300755],"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":[0.00019851237,0.00035449705,0.8815214,0.000259755,0.00003412934,0.0000033159956,0.0061241486,0.0060582915,0.084556386,0.00013764987,0.0006512109,0.020100705],"study_design_scores_gemma":[0.0033210453,0.00055623986,0.5794158,0.00017280418,0.00019988605,0.000024872896,0.00052307267,0.043712355,0.08722806,0.0067255273,0.2766546,0.0014657304],"about_ca_topic_score_codex":0.00023207224,"about_ca_topic_score_gemma":0.00021779301,"teacher_disagreement_score":0.3021056,"about_ca_system_score_codex":0.000030691346,"about_ca_system_score_gemma":5.58073e-7,"threshold_uncertainty_score":0.99850154},"labels":[],"label_agreement":null},{"id":"W2321926410","doi":"10.1061/9780784413548.163","title":"Importance of Cash Contributions to the Sustainability of International Development Projects","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","topic":"Community Development and Social Impact","field":"Economics, Econometrics and Finance","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":"Engineers Without Borders Canada","funders":"","keywords":"Sustainability; Community development; Process management; Subject (documents); Business; Engineering management; Engineering ethics; Engineering; Political science; Management science; Computer science; Library science","score_opus":0.011124167894180432,"score_gpt":0.21598517852311852,"score_spread":0.20486101062893808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2321926410","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":[0.994704,0.00015231056,0.00012393131,0.0018813175,0.00010726813,0.0002156932,0.000073689196,0.0000057878638,0.002736008],"genre_scores_gemma":[0.997252,0.000022801682,0.0000921813,0.000114621005,0.000027569316,0.000018870487,0.000028493305,0.000006422146,0.0024370435],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920577,0.000030517946,0.00039492844,0.00014898898,0.00005517527,0.00016463724],"domain_scores_gemma":[0.99955845,0.00004165395,0.00014136414,0.00019092056,0.000013917407,0.000053706848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005620263,0.00009355557,0.00021116664,0.00009627905,0.00013303998,0.00002361527,0.0002295798,0.000024429975,0.00021623108],"category_scores_gemma":[0.00004000727,0.00006856768,0.000041066553,0.000041933,0.00017372603,0.00006489814,0.00025418965,0.00007554787,0.00003529953],"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":[0.000027724736,0.00008014341,0.9866783,0.000019582654,0.000054971235,3.479786e-7,0.007920524,0.00004524752,0.00009230075,0.0020967943,0.00040989782,0.0025741467],"study_design_scores_gemma":[0.0002906106,0.000028345607,0.60346806,0.000009565749,0.0000036075037,7.613444e-7,0.00035836393,0.00010974596,0.0017927836,0.0014124081,0.39240175,0.00012398798],"about_ca_topic_score_codex":0.00016271157,"about_ca_topic_score_gemma":0.00028280454,"teacher_disagreement_score":0.39199185,"about_ca_system_score_codex":0.00010358671,"about_ca_system_score_gemma":0.0000051447505,"threshold_uncertainty_score":0.27961087},"labels":[],"label_agreement":null},{"id":"W2323867912","doi":"10.1061/9780784413548.115","title":"Early Exploration and Mapping of the Columbia River","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","topic":"Archaeology and Natural History","field":"Social Sciences","cited_by":0,"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":"Geographer; Columbia university; Bay; Archaeology; Geography; George (robot); Oceanography; History; Cartography; Geology; Art history","score_opus":0.00800530143926028,"score_gpt":0.1876836807002797,"score_spread":0.1796783792610194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2323867912","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":[0.9965955,0.00051940564,0.000008512845,0.0006868934,0.00012947805,0.000095250376,0.0000021293683,0.000008094098,0.001954709],"genre_scores_gemma":[0.9861524,0.00019876035,0.00004597989,0.00011602744,0.000050531413,0.0000041402664,0.0000014477233,0.0000037375457,0.013426982],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99939114,0.00016556565,0.000085792955,0.00011999863,0.00011383455,0.00012365969],"domain_scores_gemma":[0.9998028,0.00003416279,0.00004143457,0.000076934906,0.0000019826782,0.000042679887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019611396,0.00005178024,0.00008140344,0.000024350542,0.0004803659,0.0000059623044,0.000089921705,0.00003999498,0.00013293457],"category_scores_gemma":[0.0000035577602,0.00003665236,0.000020919602,0.000017843537,0.0019684904,0.00011698332,0.00012928888,0.0000757374,0.000015038061],"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":[0.0000286123,0.000021382699,0.8659713,0.000014921125,0.000019535271,9.288054e-7,0.09738227,0.0000038653366,0.0031393273,0.00037166485,0.0016569489,0.03138919],"study_design_scores_gemma":[0.00021008145,0.000022068527,0.4126248,0.000015066092,0.000010487369,6.01926e-7,0.00047317924,0.000022995111,0.00043379058,0.004286984,0.58180946,0.0000904583],"about_ca_topic_score_codex":0.0012598756,"about_ca_topic_score_gemma":0.0026554689,"teacher_disagreement_score":0.5801525,"about_ca_system_score_codex":0.000013389167,"about_ca_system_score_gemma":9.810966e-7,"threshold_uncertainty_score":0.7252985},"labels":[],"label_agreement":null},{"id":"W2326165993","doi":"10.1061/9780784413548.116","title":"Grand Coulee Dam History","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","topic":"American Environmental and Regional History","field":"Environmental 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":"Hydrology (agriculture); Drainage basin; Geology; Structural basin; Geomorphology; Archaeology; Geography; Geotechnical engineering; Cartography","score_opus":0.004777085503806101,"score_gpt":0.15898428302781162,"score_spread":0.15420719752400552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2326165993","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":[0.9420159,0.0008478932,0.00006377918,0.00039233698,0.0003643711,0.00019643157,0.000009026475,0.000067221874,0.056043036],"genre_scores_gemma":[0.9209296,0.00016385077,0.00016501432,0.0014332513,0.00010929057,0.000027578262,0.000031436724,0.000042128846,0.07709781],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99810046,0.00011273201,0.00026397634,0.0006182406,0.00042853266,0.00047606044],"domain_scores_gemma":[0.9992304,0.00003658529,0.00008828413,0.000345042,5.4115196e-7,0.00029918778],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001889762,0.0003345486,0.0002861158,0.000064762746,0.00025344978,0.000013705299,0.00028077298,0.000068352296,0.014206651],"category_scores_gemma":[0.000001471676,0.00023774595,0.00009718127,0.000024793238,0.004419561,0.00018738989,0.00049220165,0.00019672686,0.0039660637],"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":[0.0004767952,0.0009995977,0.45638308,0.000076922785,0.00015657635,0.00009716719,0.012003907,0.0014442597,0.12834123,0.0001746837,0.3238775,0.07596825],"study_design_scores_gemma":[0.00052694435,0.00009349082,0.04374593,0.000008560684,0.00002776173,0.000026986596,0.000102977465,0.00024948907,0.00094622665,0.00012450828,0.9537408,0.0004063351],"about_ca_topic_score_codex":0.00018454861,"about_ca_topic_score_gemma":0.00006759569,"teacher_disagreement_score":0.62986326,"about_ca_system_score_codex":0.00039993908,"about_ca_system_score_gemma":0.0000010083908,"threshold_uncertainty_score":0.9982898},"labels":[],"label_agreement":null},{"id":"W2327739815","doi":"10.1061/9780784413548.197","title":"Classifying Streams on the Basis of Elevation above Mean Sea Level—A Universal Approach","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":0,"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":"Elevation (ballistics); STREAMS; Geology; Cobble; Sinuosity; Hydrology (agriculture); Digital elevation model; Range (aeronautics); Sea level; Channel (broadcasting); Geomorphology; Remote sensing; Geometry; Oceanography; Ecology; Mathematics; Geotechnical engineering","score_opus":0.011754726959621317,"score_gpt":0.17700117182638608,"score_spread":0.16524644486676476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2327739815","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":[0.98489785,0.000027776356,0.00016119765,0.00049444946,0.000049592694,0.00015490998,0.000023130026,0.000018750912,0.014172367],"genre_scores_gemma":[0.9961903,0.000031971686,0.000089606394,0.00037042005,0.000029873716,0.000011403096,0.000050388622,0.0000145829645,0.0032114303],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988038,0.000102889324,0.00019991717,0.00034283,0.00028735705,0.0002632341],"domain_scores_gemma":[0.9995521,0.000066462824,0.000077607685,0.00022530185,0.0000011867036,0.000077349236],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002892323,0.00019101685,0.00017533849,0.000045741257,0.00023715605,0.000018629784,0.00022998286,0.00006443125,0.002616153],"category_scores_gemma":[0.0000020421123,0.00011231499,0.00004953951,0.000048092952,0.0006845585,0.00013390376,0.00011077579,0.00015973733,0.00014679178],"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":[0.00025294317,0.0003605025,0.94445264,0.00004593856,0.000098795776,0.000004736543,0.0049937326,0.0037699623,0.022822393,0.00048384533,0.001708716,0.021005783],"study_design_scores_gemma":[0.002634969,0.0006595927,0.45824614,0.00008494811,0.00023951153,0.000015313344,0.0015462505,0.019076083,0.21473157,0.0012531256,0.3003266,0.001185909],"about_ca_topic_score_codex":0.00013762651,"about_ca_topic_score_gemma":0.00010744921,"teacher_disagreement_score":0.48620653,"about_ca_system_score_codex":0.000034311222,"about_ca_system_score_gemma":7.911859e-7,"threshold_uncertainty_score":0.9982956},"labels":[],"label_agreement":null},{"id":"W2329219963","doi":"10.1061/9780784413548.049","title":"Trunk Water Main Failure Consequence Modeling of Hydraulic Failure and Fire Flow","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","topic":"Water Systems and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Trunk; Index (typography); Environmental science; Range (aeronautics); Computer science; Engineering; Ecology","score_opus":0.0035154591464046166,"score_gpt":0.1452087320328131,"score_spread":0.14169327288640848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2329219963","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":[0.9972134,0.00033172796,0.0014190449,0.00025879862,0.000099791454,0.00015772675,0.000021070833,0.000059311405,0.00043910393],"genre_scores_gemma":[0.99777186,0.000058406484,0.00056878664,0.000041820447,0.00006787145,0.000014702957,0.000056119683,0.00003651323,0.0013839322],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900746,0.000045936275,0.00027017124,0.00024966607,0.00013362772,0.00029314702],"domain_scores_gemma":[0.9996743,0.0000116580295,0.000022245302,0.00018622009,0.000003021068,0.00010250903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000123862,0.00022653051,0.0002621556,0.000071856106,0.000093480965,0.00005941265,0.000098413555,0.00007888102,0.00016868237],"category_scores_gemma":[7.3643156e-7,0.00014687343,0.000036743302,0.000017047301,0.00014830753,0.00015434988,0.000096250435,0.00010923609,0.00004264094],"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":[0.000047905167,0.0000345167,0.008137354,0.00051236316,0.00012535373,0.000030074565,0.006414984,0.9235681,0.055380147,0.00002678362,0.0020278767,0.0036944957],"study_design_scores_gemma":[0.00066253537,0.000040751638,0.00027268403,0.00009429825,0.000031529602,0.00006094175,0.00014776546,0.9288953,0.0244288,0.00012438571,0.04488038,0.00036064946],"about_ca_topic_score_codex":0.00005162216,"about_ca_topic_score_gemma":0.00015726587,"teacher_disagreement_score":0.042852502,"about_ca_system_score_codex":0.000017811866,"about_ca_system_score_gemma":4.5691064e-7,"threshold_uncertainty_score":0.59893245},"labels":[],"label_agreement":null},{"id":"W2330787781","doi":"10.1061/9780784413548.114","title":"Effects of the Great Missoula Floods","year":2014,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2014","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":0,"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":"Geology; Hydrology (agriculture); EPIC; Glacial period; Archaeology; Physical geography; Geography; Geomorphology","score_opus":0.0023692225981245293,"score_gpt":0.15979393251234608,"score_spread":0.15742470991422156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2330787781","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":[0.9955172,0.00020547201,0.00001739295,0.00030717827,0.0001311866,0.00016958984,0.0000030985377,0.000017612238,0.0036312763],"genre_scores_gemma":[0.9927165,0.000040106643,0.000034239718,0.00043820613,0.000031199444,0.000014578772,0.0000047511626,0.000013932669,0.006706473],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989317,0.000094696996,0.00018475183,0.00029422538,0.00022453001,0.00027011128],"domain_scores_gemma":[0.99957865,0.000053695287,0.00005437142,0.00022397254,5.7618166e-7,0.000088749366],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00013935548,0.00017881855,0.00018653882,0.000024412608,0.0001928859,0.000012295034,0.0002726151,0.000060150407,0.0021671916],"category_scores_gemma":[0.000002675803,0.00009819379,0.00006538347,0.000036544727,0.0008528257,0.000090063746,0.00023057972,0.000122033845,0.0002458884],"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":[0.00006061323,0.0001249586,0.89681184,0.00008438552,0.000038165763,0.000005767585,0.0013243349,0.0003742804,0.093252234,0.000020298736,0.0007699558,0.007133137],"study_design_scores_gemma":[0.0007801896,0.00008645165,0.38963124,0.0000299318,0.000084159336,0.000008966795,0.000011924464,0.00024388636,0.26387396,0.00043053486,0.34457505,0.00024370615],"about_ca_topic_score_codex":0.00005901836,"about_ca_topic_score_gemma":0.00005495324,"teacher_disagreement_score":0.50718063,"about_ca_system_score_codex":0.000014444152,"about_ca_system_score_gemma":4.1744605e-7,"threshold_uncertainty_score":0.99874496},"labels":[],"label_agreement":null}]}