{"meta":{"query_hash":"fa96e9c22652","filters":{"venue":"WDSA / CCWI Joint Conference Proceedings"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"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/fa96e9c22652","api":"https://metacan.xera.ac/api/v1/cohort?venue=WDSA+%2F+CCWI+Joint+Conference+Proceedings"},"results":[{"id":"W2951428172","doi":"","title":"Three-Dimensional Simulation of Hydrodynamics and Water Quality in a Wastewater Stabilization Pond:","year":2018,"lang":"en","type":"article","venue":"WDSA / CCWI Joint Conference Proceedings","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":5,"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":"Alkalinity; Environmental science; Wastewater; Biogeochemical cycle; Water quality; Environmental engineering; Sewage treatment; Stabilization pond; Algae; Hydrology (agriculture); Ecology; Environmental chemistry; Chemistry; Engineering","score_opus":0.0243993136367882,"score_gpt":0.24739478077584456,"score_spread":0.22299546713905635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951428172","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":[0.99786943,0.000002344983,0.0009627029,0.00025569,0.000063584215,0.00024210813,0.0000053602726,0.000030953175,0.0005677983],"genre_scores_gemma":[0.9992163,0.0000024641206,0.0006314631,0.000045974262,0.000023663268,0.000009702565,0.000018339535,0.000012858584,0.00003922116],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985296,0.000012797856,0.00044047626,0.00039938657,0.00032621692,0.00029150874],"domain_scores_gemma":[0.9995952,0.00001922105,0.00011879879,0.00010448548,0.00008861758,0.00007364984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004594675,0.00016882883,0.00022198108,0.00008356993,0.00007099188,0.00004233988,0.000111851754,0.00010359781,0.00016807184],"category_scores_gemma":[0.000049718965,0.00012554404,0.000029867479,0.00015857752,0.00036170334,0.000452883,0.00025763892,0.00010428914,0.00004588436],"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":[0.00012110695,0.00013324912,0.94338965,0.00007122607,0.0000066831612,7.160108e-7,0.0056981146,0.0017871732,0.046538755,0.00043457918,0.000014463214,0.0018042817],"study_design_scores_gemma":[0.0006470624,0.00016195481,0.14808029,0.0000630854,0.000009912442,0.00000349406,0.00021717043,0.80602074,0.0146315405,0.029826561,0.000075525946,0.0002626409],"about_ca_topic_score_codex":0.0004445173,"about_ca_topic_score_gemma":0.00022284729,"teacher_disagreement_score":0.8042336,"about_ca_system_score_codex":0.00008958969,"about_ca_system_score_gemma":0.000008252717,"threshold_uncertainty_score":0.5119538},"labels":[],"label_agreement":null},{"id":"W2965775619","doi":"","title":"Physical Modelling of an Hydropower Generation Station and Simulating Turbine Energy Losses","year":2018,"lang":"en","type":"article","venue":"WDSA / CCWI Joint Conference Proceedings","topic":"Cavitation Phenomena in Pumps","field":"Engineering","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":"Hydropower; Inflow; Turbine; Inlet; Marine engineering; Spillway; Draft tube; Renewable energy; Electricity generation; Environmental science; Francis turbine; Engineering; Flow (mathematics); Meteorology; Power (physics); Geotechnical engineering; Mechanical engineering; Mechanics","score_opus":0.038533250236588476,"score_gpt":0.2433751780351169,"score_spread":0.20484192779852844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965775619","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":[0.88837004,0.000019970432,0.10991597,0.000026523825,0.00010176268,0.00009225243,0.0000067394635,0.00014455327,0.0013222029],"genre_scores_gemma":[0.9926289,0.00001599498,0.006805851,0.000027955159,0.00041482653,0.000014364717,0.000028067576,0.000035102035,0.000028958259],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989814,0.0000062383233,0.0003164818,0.00026008394,0.00023267261,0.00020308695],"domain_scores_gemma":[0.9991406,0.00002313692,0.00010561098,0.00008538506,0.00055777916,0.00008747228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012592901,0.00018143601,0.00021609702,0.00012900218,0.000075408476,0.00010950777,0.0000744138,0.000060134247,0.00003188637],"category_scores_gemma":[0.00004189226,0.00018992745,0.000026012978,0.00017067314,0.000110145564,0.000707372,0.000030280007,0.00010278245,0.0000045470733],"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":[0.000028644788,0.00010262298,0.00014801823,0.00024994175,0.00005210967,8.5222524e-7,0.019475805,0.10517174,0.83227134,0.019290425,0.00019800945,0.023010476],"study_design_scores_gemma":[0.000201823,0.00014311168,0.00006913268,0.000039911214,0.000014096667,0.0000023366028,0.00042562964,0.840154,0.1543595,0.0043546064,0.00005730038,0.00017853761],"about_ca_topic_score_codex":0.000041989893,"about_ca_topic_score_gemma":0.0000082304405,"teacher_disagreement_score":0.73498225,"about_ca_system_score_codex":0.000044268527,"about_ca_system_score_gemma":0.000023859606,"threshold_uncertainty_score":0.7745017},"labels":[],"label_agreement":null},{"id":"W2968818053","doi":"","title":"Performance Modelling of Etobicoke Exfiltration System (EES)","year":2018,"lang":"en","type":"article","venue":"WDSA / CCWI Joint Conference Proceedings","topic":"Urban Stormwater Management Solutions","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":"Stormwater; Sanitary sewer; Environmental science; Combined sewer; Storm Water Management Model; Storm; Surface runoff; Stormwater management; Low-impact development; Hydrology (agriculture); Civil engineering; Environmental engineering; Engineering; Meteorology","score_opus":0.04894755799927145,"score_gpt":0.20049376789725423,"score_spread":0.1515462098979828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968818053","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":[0.87385887,0.0000059185813,0.027227229,0.00011724581,0.00016228728,0.00034692138,0.0000033129788,0.00016042145,0.09811779],"genre_scores_gemma":[0.9938369,0.000015543796,0.0048294812,0.00004496081,0.00009590827,0.00004368343,0.000004232413,0.000019103476,0.00111019],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982565,0.000009034911,0.00044381,0.00043965274,0.0004603699,0.00039064072],"domain_scores_gemma":[0.9993055,0.000007078259,0.00026367413,0.00019560831,0.00012689656,0.00010126219],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00038018997,0.00020805132,0.00023096913,0.00009818577,0.00023743583,0.00007384544,0.00034145988,0.000083758845,0.00072804507],"category_scores_gemma":[0.000015859625,0.00019832785,0.000057617115,0.0003379769,0.0003822016,0.0008897597,0.00023870206,0.00013324709,0.0008361946],"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":[0.00026833682,0.00069567346,0.42748013,0.0019314298,0.0001941155,0.0000059158656,0.03207714,0.0037938557,0.43425187,0.059617057,0.02191326,0.017771201],"study_design_scores_gemma":[0.00059317215,0.0005331787,0.026707241,0.00043476428,0.000091860566,0.000021405416,0.002042977,0.8854086,0.077133276,0.00049817574,0.0058406848,0.0006946756],"about_ca_topic_score_codex":0.00018664167,"about_ca_topic_score_gemma":0.0000143180605,"teacher_disagreement_score":0.88161474,"about_ca_system_score_codex":0.00023302175,"about_ca_system_score_gemma":0.000018478244,"threshold_uncertainty_score":0.99994177},"labels":[],"label_agreement":null},{"id":"W2969093551","doi":"","title":"Monitoring Seasonal Variations in Treatment Performance of a Wastewater Stabilization Pond with Algal Blooms and pH Fluctuations","year":2018,"lang":"en","type":"article","venue":"WDSA / CCWI Joint Conference Proceedings","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":4,"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":"Environmental science; Effluent; Wastewater; Sewage treatment; Water quality; Nutrient; Algal bloom; Phosphorus; Nitrate; Environmental engineering; Eutrophication; Sewage; Ecology; Chemistry; Biology; Phytoplankton","score_opus":0.015255174205406393,"score_gpt":0.20787741594112244,"score_spread":0.19262224173571604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969093551","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":[0.9982727,0.000005191364,0.0002611407,0.00015127369,0.000042744676,0.00024198071,0.0000059562262,0.00002413654,0.0009948583],"genre_scores_gemma":[0.9976211,0.000043829674,0.0021159993,0.000006811196,0.000040674942,0.00005022986,0.000006556894,0.000010335056,0.00010444724],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99904215,0.0000063824104,0.00021603347,0.00028623952,0.00022685678,0.00022231329],"domain_scores_gemma":[0.99966896,0.000010468697,0.00009728854,0.00007551198,0.000076098455,0.000071697905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010827886,0.00014798739,0.00014978023,0.00007022129,0.00011273549,0.000053241278,0.000079497586,0.00004870442,0.00007461831],"category_scores_gemma":[0.000015729514,0.00011261598,0.000015724401,0.00025922144,0.00023336262,0.00046596318,0.00007159181,0.000060102615,0.000015731797],"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":[0.000043033953,0.00010453553,0.97709286,0.000019355879,0.000008691314,3.3491276e-7,0.006645971,0.00002345,0.011428349,0.00018269152,0.0000026836321,0.004448029],"study_design_scores_gemma":[0.0011502687,0.0009044051,0.85711247,0.00017715798,0.00003791842,0.000014891677,0.0009529756,0.08396489,0.05425637,0.0010944842,0.000077032506,0.0002571278],"about_ca_topic_score_codex":0.00014146003,"about_ca_topic_score_gemma":0.000027844666,"teacher_disagreement_score":0.119980395,"about_ca_system_score_codex":0.00013792505,"about_ca_system_score_gemma":0.000027049206,"threshold_uncertainty_score":0.45923463},"labels":[],"label_agreement":null},{"id":"W2969283176","doi":"","title":"Examining the Role of Layer Growth Duration on Layer Strength and Turbidity Response in a Full-Scale Laboratory Drinking Water Distribution System at Queen’s University:","year":2018,"lang":"en","type":"article","venue":"WDSA / CCWI Joint Conference Proceedings","topic":"Water Systems and Optimization","field":"Engineering","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":"Turbidity; Environmental science; Water flow; Water quality; Flow (mathematics); Duration (music); Hydrology (agriculture); Environmental engineering; Ecology; Geotechnical engineering; Engineering; Geology; Mechanics; Oceanography","score_opus":0.012466675019268224,"score_gpt":0.1751554518293262,"score_spread":0.16268877681005797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969283176","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":[0.99774,0.0000104649125,0.00087384856,0.000106851956,0.00010543206,0.00021881689,0.000021622403,0.000113041766,0.0008099307],"genre_scores_gemma":[0.9997274,0.000010446902,0.00007667582,0.0000063050684,0.00006918535,0.000008318976,0.000017526467,0.000015956717,0.00006817794],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990508,0.000047395686,0.0002706545,0.00022977641,0.0001821692,0.00021920164],"domain_scores_gemma":[0.999436,0.00002690274,0.00008686204,0.00009539123,0.00030554572,0.0000492728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005533569,0.00016104802,0.00019503772,0.00011100216,0.00012925996,0.000079010635,0.00010378007,0.0001157963,0.0000110001365],"category_scores_gemma":[0.000033335666,0.000120455974,0.000019433668,0.00017092394,0.000064640204,0.00031421226,0.00007937909,0.00013877822,0.000009910998],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015605786,0.00008192631,0.07119688,0.0008124304,0.00008643449,0.000011526178,0.040451936,0.0005246929,0.8750953,0.008552546,0.0010427546,0.0005829992],"study_design_scores_gemma":[0.0009821258,0.0004262132,0.065603256,0.0009973937,0.000042164065,0.000015330847,0.012045193,0.08473007,0.8321853,0.00007138319,0.0024296811,0.00047185633],"about_ca_topic_score_codex":0.00008583995,"about_ca_topic_score_gemma":0.00011963619,"teacher_disagreement_score":0.084205374,"about_ca_system_score_codex":0.00027634573,"about_ca_system_score_gemma":0.00001959835,"threshold_uncertainty_score":0.4912052},"labels":[],"label_agreement":null},{"id":"W2969685657","doi":"","title":"Impacts of the Integration of Water Demand Prediction in Real Time Control of Water Distribution Systems","year":2018,"lang":"en","type":"article","venue":"WDSA / CCWI Joint Conference Proceedings","topic":"Water Systems and Optimization","field":"Engineering","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":"Leakage (economics); Environmental science; Real-time Control System; Computer science; Control theory (sociology); Control (management); Artificial intelligence; Economics","score_opus":0.011082093856011575,"score_gpt":0.18932300186582102,"score_spread":0.17824090800980943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969685657","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":[0.9809221,0.000012931278,0.0173481,0.00004081314,0.00026493607,0.00046654543,0.000053314103,0.000045430992,0.00084585574],"genre_scores_gemma":[0.9997324,0.000011379454,0.000027995002,0.0000014445013,0.00007465923,0.00002151662,0.000047523914,0.000012892678,0.00007021611],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988327,0.000018134691,0.0006266786,0.00013055792,0.00019486154,0.00019708996],"domain_scores_gemma":[0.9991691,0.0000063214557,0.00013317425,0.00009975773,0.00055987085,0.000031749434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041647776,0.00013578073,0.0003090039,0.000088354376,0.000026682412,0.000029534054,0.00010448556,0.00012528914,0.000026230635],"category_scores_gemma":[0.000029059207,0.000074841104,0.000048515773,0.000107931686,0.00008308656,0.000287637,0.000026217484,0.00008460821,0.000007099626],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047412825,0.000026165848,0.008021757,0.00046832653,0.000029900337,8.925283e-8,0.0047839284,0.0011453934,0.9845716,0.00043913725,0.00038278583,0.00008351934],"study_design_scores_gemma":[0.0004969152,0.00013950394,0.008574829,0.00056885177,0.000025449222,0.0000038476906,0.00020710702,0.22557995,0.7642091,0.000075748736,0.000036307447,0.0000823727],"about_ca_topic_score_codex":0.0003045715,"about_ca_topic_score_gemma":0.000033556295,"teacher_disagreement_score":0.22443455,"about_ca_system_score_codex":0.00007075002,"about_ca_system_score_gemma":0.000014169836,"threshold_uncertainty_score":0.30519316},"labels":[],"label_agreement":null},{"id":"W2969981892","doi":"","title":"Hybrid Wavelet and Local Approximation Method for Urban Water Demand Forecasting – Chaotic Approach:","year":2018,"lang":"en","type":"article","venue":"WDSA / CCWI Joint Conference Proceedings","topic":"Energy Load and Power Forecasting","field":"Engineering","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":"Chaotic; Wavelet; Nonlinear system; Correlation dimension; Phase space; Demand forecasting; Econometrics; Time series; Dimension (graph theory); Mathematics; Computer science; Mathematical optimization; Statistics; Artificial intelligence; Fractal dimension; Operations research; Fractal; Mathematical analysis","score_opus":0.03654169349550443,"score_gpt":0.2240163506905229,"score_spread":0.18747465719501846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969981892","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":[0.20721102,0.000055907054,0.78320676,0.00007581235,0.00021535475,0.00039330334,0.0000089134155,0.0003261091,0.00850685],"genre_scores_gemma":[0.8960133,0.000008985484,0.103076674,0.000064444575,0.0004827299,0.00011733065,0.00003834789,0.000064799846,0.00013338384],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982521,0.000009497026,0.00042757342,0.00046450496,0.00018497657,0.000661367],"domain_scores_gemma":[0.99930656,0.000044491342,0.00007974546,0.00010436084,0.0002975241,0.00016732162],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00066637393,0.00035274573,0.0003860261,0.00016413024,0.00023936554,0.0002253262,0.00015249096,0.00012954893,0.000031709027],"category_scores_gemma":[0.00008796177,0.00028912502,0.00007256859,0.00010050083,0.00014698705,0.00042743192,0.00008909355,0.00021971879,0.00000992894],"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":[0.00030251773,0.00022019108,0.0012229959,0.009097029,0.00058844086,0.000012198044,0.054972757,0.0016121457,0.21344899,0.05865956,0.010049241,0.64981395],"study_design_scores_gemma":[0.00047482966,0.00014264304,0.000028729111,0.00016233361,0.000041827694,0.00011546818,0.00041502583,0.83454585,0.15832333,0.0030614196,0.0023050774,0.00038346348],"about_ca_topic_score_codex":0.000009040062,"about_ca_topic_score_gemma":0.0000021197536,"teacher_disagreement_score":0.8329337,"about_ca_system_score_codex":0.00005233079,"about_ca_system_score_gemma":0.000016768017,"threshold_uncertainty_score":0.9999561},"labels":[],"label_agreement":null}]}