{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":247,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":247,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"cd7c884b67e5","filters":{"venue":"Journal of Hydrometeorology"}},"results":[{"id":"W2169973869","doi":"10.1175/2010jhm1202.1","title":"Estimating Snow Water Equivalent Using Snow Depth Data and Climate Classes","year":2010,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":597,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Environment and Climate Change Canada","funders":"Cold Regions Research and Engineering Laboratory; National Science Foundation","keywords":"Snow; Water equivalent; Environmental science; Range (aeronautics); Snowpack; Meteorology; Climatology; Atmospheric sciences; Geology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.05363916705412664,"gpt":0.2892214425152269,"spread":0.2355822754611003,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007752324,0.0001090844,0.0002705894,0.00006062175,0.0002396851,0.00005339688,0.0003200574,0.00006685042,0.0008814269],"category_scores_gemma":[0.0002853371,0.00006865134,0.00003867821,0.00008899689,0.0001287341,0.0003527818,0.0001114106,0.0003034722,0.00001280639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002437007,"about_ca_system_score_gemma":0.00002795162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001854353,"about_ca_topic_score_gemma":0.0021682,"domain_scores_codex":[0.9989024,0.00004921,0.0003928213,0.0001644352,0.000159401,0.000331673],"domain_scores_gemma":[0.9990983,0.0002924809,0.0002204038,0.0002208286,0.00006253983,0.000105428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005026549,0.00002678783,0.9554426,0.00002255533,0.0001042622,0.00008865992,0.0002602742,0.004188795,0.003760897,0.00001596533,0.000444051,0.03559488],"study_design_scores_gemma":[0.000639466,0.0005148029,0.6913334,0.00003278625,0.0001735329,0.001905037,0.0002321801,0.2932817,0.0002141316,0.0007741833,0.01067644,0.0002223266],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961282,0.0004352813,0.0008311858,0.0006999655,0.001638946,0.00004435976,0.00003063892,0.000007292037,0.0001841139],"genre_scores_gemma":[0.9498639,0.0001479822,0.04937885,0.0001991386,0.0003726189,8.753084e-8,0.00002431339,0.000003924269,0.000009191929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.289093,"threshold_uncertainty_score":0.9651006,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1994193211","doi":"10.1175/jhm531.1","title":"Impact of Climate Change on River Discharge Projected by Multimodel Ensemble","year":2006,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":393,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Grains Research and Development Corporation","keywords":"Environmental science; Surface runoff; Precipitation; Snowmelt; Discharge; Climate change; Mediterranean climate; Streamflow; Northern Hemisphere; Climatology; Latitude; Hydrology (agriculture); Drainage basin; Geography; Oceanography; Geology; Ecology; Meteorology","retraction":null,"screen_n_in":null,"score":{"opus":0.01246831489667436,"gpt":0.2531751152799804,"spread":0.2407068003833061,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003520271,0.0001621977,0.0003792072,0.0001505776,0.00008117868,0.000003945587,0.0002086783,0.00009466273,0.0004215528],"category_scores_gemma":[0.00001996228,0.0001107913,0.000177165,0.000166109,0.0002700483,0.0002136226,0.0001334945,0.0001844948,0.00009203399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000079975,"about_ca_system_score_gemma":0.000003642744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004998498,"about_ca_topic_score_gemma":0.00003005469,"domain_scores_codex":[0.998732,0.0001155151,0.0004058862,0.000169118,0.0002004453,0.0003769962],"domain_scores_gemma":[0.9993166,0.00005292414,0.0004264923,0.0001397087,0.00001441158,0.00004989297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001167866,0.001705787,0.8992733,0.0000255506,0.0004112887,0.0001180244,0.001012516,0.007099877,0.05237403,0.0001886797,0.03224679,0.004376264],"study_design_scores_gemma":[0.002832126,0.005500103,0.9810517,0.0000221477,0.0001694241,0.00009774109,0.00001809383,0.003108206,0.002125435,0.002457457,0.002302807,0.0003147449],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947989,0.00007538129,0.0001201246,0.0004248375,0.0001435311,0.0001580646,0.0000176668,0.000009729386,0.004251739],"genre_scores_gemma":[0.9990928,0.0001763572,0.0003390811,0.0001558591,0.00005355888,0.000007022401,0.000004938723,0.00001154642,0.0001588607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08177839,"threshold_uncertainty_score":0.4615707,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2114688600","doi":"10.1175/2011jhm1365.1","title":"The Second Phase of the Global Land–Atmosphere Coupling Experiment: Soil Moisture Contributions to Subseasonal Forecast Skill","year":2011,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":391,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada; University of Guelph","funders":"","keywords":"Environmental science; Forecast skill; Initialization; Precipitation; Climatology; Water content; Anomaly (physics); Atmosphere (unit); Moisture; Atmospheric sciences; Madden–Julian oscillation; Data assimilation; Meteorology; Geology; Geography; Computer science; Convection","retraction":null,"screen_n_in":null,"score":{"opus":0.01772400704192533,"gpt":0.2748569299520488,"spread":0.2571329229101235,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007481492,0.000115059,0.0002398195,0.000006254613,0.000224016,0.00001275339,0.0004950548,0.00009549876,0.001687238],"category_scores_gemma":[0.000163728,0.00006370081,0.0001745619,0.000197067,0.000318095,0.0001063925,0.0001985604,0.0002084314,0.00001645168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000194998,"about_ca_system_score_gemma":0.00004370954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001459663,"about_ca_topic_score_gemma":0.00125314,"domain_scores_codex":[0.9988078,0.00008412894,0.0004344506,0.0001342385,0.0002505172,0.0002888276],"domain_scores_gemma":[0.9991034,0.0001244311,0.0003311575,0.0002477748,0.00005339381,0.0001398139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005157522,0.007119433,0.797662,0.00005632101,0.001071018,0.0001414786,0.01086183,0.05589632,0.08990373,0.01636722,0.01209449,0.00366864],"study_design_scores_gemma":[0.02838842,0.01223069,0.5217531,0.0001980944,0.0009528386,0.004028782,0.00264453,0.04868343,0.09786005,0.1403492,0.1412488,0.001662061],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959413,0.0002081583,0.0004219066,0.0008254923,0.0004095756,0.0001505145,0.0001092073,0.000004100222,0.001929783],"genre_scores_gemma":[0.9993209,0.00001676648,0.0002806841,0.0002312196,0.00004958943,0.000005460688,9.165452e-7,0.000005589595,0.00008883028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2759089,"threshold_uncertainty_score":0.9992254,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2740614026","doi":"10.1175/jhm-d-17-0063.1","title":"Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using In Situ Measurements","year":2017,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":348,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Agriculture and Agri-Food Canada; University of Guelph","funders":"Canadian Space Agency; National Centers for Environmental Information; Goddard Space Flight Center; National Oceanic and Atmospheric Administration; Monash University; Agricultural Research Service; Environment and Climate Change Canada; U.S. Department of Agriculture; National Aeronautics and Space Administration","keywords":"Environmental science; Water content; Moisture; DNS root zone; Data assimilation; Remote sensing; Soil science; Standard deviation; Atmospheric sciences; Soil water; Meteorology; Geology; Mathematics; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.04852128038684413,"gpt":0.2959240354902016,"spread":0.2474027551033575,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001210575,0.000128612,0.0003508291,0.00005083015,0.0001984497,0.00002640508,0.0003847427,0.00008623979,0.00001152623],"category_scores_gemma":[0.0001541962,0.00008187162,0.00008014345,0.00009398125,0.0003715687,0.000191817,0.0002608713,0.0003637542,0.00000102739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001478018,"about_ca_system_score_gemma":0.00004934273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00113871,"about_ca_topic_score_gemma":0.008985631,"domain_scores_codex":[0.9985695,0.0001904842,0.0004074208,0.0001805888,0.0004328761,0.0002190659],"domain_scores_gemma":[0.9987017,0.00003367568,0.0007993155,0.0003750919,0.00003159574,0.00005863163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001462918,0.00004986261,0.5928749,0.000006425293,0.00002992611,0.00001935235,0.0001198478,0.004008425,0.4008266,0.000001367303,0.00003858459,0.002010085],"study_design_scores_gemma":[0.0005992452,0.0001090403,0.9800144,0.00004349557,0.00004934324,0.0003556575,0.00002736878,0.000306438,0.01808889,0.0002012909,0.000123266,0.00008152134],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944306,0.0001956164,0.00008496249,0.001059396,0.0005797221,0.000101057,4.486453e-7,0.000001623326,0.003546557],"genre_scores_gemma":[0.9966051,0.00001570665,0.003165217,0.00006037428,0.00006264095,6.142685e-8,1.011275e-7,0.000009812162,0.00008099971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3871395,"threshold_uncertainty_score":0.5014193,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1965068681","doi":"10.1175/jhm-d-14-0008.1","title":"Why Should Ensemble Spread Match the RMSE of the Ensemble Mean?","year":2014,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":261,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval; Environment and Climate Change Canada","funders":"","keywords":"Ensemble average; Mean squared error; Standard deviation; Variance (accounting); Ensemble forecasting; Statistics; Ensemble learning; Square root; Mathematics; Mean square; Computer science; Climatology; Geology; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.02997681188336996,"gpt":0.2401226036334407,"spread":0.2101457917500707,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001652825,0.0001403179,0.0004042601,0.0001056148,0.0002198992,0.00002380062,0.0007426497,0.0001225059,0.001560345],"category_scores_gemma":[0.0004065792,0.00006263573,0.0002331273,0.0003176538,0.0002698391,0.0001263045,0.00003577802,0.0004088143,0.00004165378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004603984,"about_ca_system_score_gemma":0.00003816265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002844394,"about_ca_topic_score_gemma":0.0007197711,"domain_scores_codex":[0.9978821,0.0006617127,0.0006128226,0.0001407837,0.0003963918,0.0003061982],"domain_scores_gemma":[0.9976541,0.001223251,0.0005333187,0.0003680369,0.0001114199,0.0001098145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009708236,0.0003566187,0.5937467,0.00008310811,0.000644788,0.00006173785,0.002881624,0.2717462,0.02582548,0.006351789,0.02378227,0.07354883],"study_design_scores_gemma":[0.001966261,0.004069983,0.6629032,0.00004025856,0.0003767633,0.0008897934,0.000271626,0.03413773,0.003145591,0.1827393,0.1090382,0.0004212923],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829471,0.0004091731,0.001143347,0.005921837,0.0008166056,0.0001136869,0.00000688616,0.00000704604,0.008634308],"genre_scores_gemma":[0.9955798,0.0000348012,0.000499356,0.00350691,0.0001888621,3.868354e-7,0.000001762198,0.000004064786,0.0001841064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2376085,"threshold_uncertainty_score":0.9993523,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1975106412","doi":"10.1175/jhm-d-13-0162.1","title":"An Enhanced Model of Land Water and Energy for Global Hydrologic and Earth-System Studies","year":2014,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":229,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Environmental science; Water cycle; Earth system science; Hydrological modelling; Hydrometeorology; Earth (classical element); Meteorology; Hydrology (agriculture); Climatology; Geology; Precipitation; Geography; Oceanography","retraction":null,"screen_n_in":null,"score":{"opus":0.01519113830835327,"gpt":0.2375653702365373,"spread":0.222374231928184,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004820607,0.0001644008,0.0005711629,0.00005792708,0.0001016906,0.000007722854,0.0001573616,0.00009616144,0.0000063985],"category_scores_gemma":[0.00003814977,0.0001011341,0.00005906465,0.00004884497,0.0003891262,0.0001756819,0.0001819011,0.00005700663,7.389182e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003875328,"about_ca_system_score_gemma":0.000004040988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003991471,"about_ca_topic_score_gemma":0.0001603579,"domain_scores_codex":[0.9987526,0.0001381195,0.0004248787,0.0002247182,0.0001606316,0.0002990826],"domain_scores_gemma":[0.9993933,0.00009206175,0.0002438075,0.0001332956,0.00003742698,0.0001001197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001400505,0.0003138014,0.01495037,0.0001776504,0.0009047578,0.00002918235,0.00200581,0.05022101,0.9009773,0.01773054,0.0003386482,0.0109504],"study_design_scores_gemma":[0.007870752,0.02312909,0.006709481,0.00008064535,0.00067992,0.001435482,0.0007386709,0.326416,0.2361178,0.3930107,0.00285562,0.0009557779],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924394,0.0004765775,0.005014298,0.0003146706,0.0001395872,0.00003812621,0.000009331638,0.000009285413,0.001558742],"genre_scores_gemma":[0.9972782,0.0000683235,0.002355566,0.0001530577,0.00005664141,0.000007202375,9.694818e-7,0.000008924282,0.00007109583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6648595,"threshold_uncertainty_score":0.412413,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2113427476","doi":"10.1175/jhm-387.1","title":"Realistic Initialization of Land Surface States: Impacts on Subseasonal Forecast Skill","year":2004,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":207,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"NASA Headquarters; National Aeronautics and Space Administration","keywords":"Initialization; Forecast skill; Environmental science; Climatology; Predictability; Data assimilation; Precipitation; Meteorology; Context (archaeology); Quantitative precipitation forecast; Forcing (mathematics); Atmospheric sciences; Mathematics; Computer science; Statistics; Geography; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.01712268188458156,"gpt":0.2574602749376801,"spread":0.2403375930530986,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006714742,0.0001014679,0.0002714187,0.00006518204,0.00003906481,0.000008106495,0.000156897,0.00008666477,0.0005697897],"category_scores_gemma":[0.0002176822,0.00008086761,0.00007992958,0.0001762734,0.0001734558,0.000170344,0.00004473489,0.000147601,0.00002377936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001639305,"about_ca_system_score_gemma":0.00003757422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000320029,"about_ca_topic_score_gemma":0.0002133256,"domain_scores_codex":[0.9988489,0.00009842683,0.0004388225,0.0001209046,0.0002824943,0.0002104302],"domain_scores_gemma":[0.9991698,0.0001630317,0.0003874491,0.0001293812,0.00003223213,0.0001180726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000495863,0.0006779126,0.05265341,0.00002706736,0.00004739985,0.00006940337,0.001040911,0.9359909,0.007744038,0.0007628789,0.0002421696,0.0002480528],"study_design_scores_gemma":[0.02252218,0.02642606,0.5358135,0.0005284075,0.0005925198,0.003440042,0.0003989972,0.04224114,0.02316568,0.3396693,0.00382683,0.001375349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968743,0.00002443523,0.00147945,0.0004780896,0.000164207,0.00007160599,0.00003187301,0.000004963304,0.0008710871],"genre_scores_gemma":[0.9988276,0.0001097075,0.0007883279,0.0002134904,0.00002909405,4.067564e-7,0.00001077511,0.000009283518,0.00001134265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8937498,"threshold_uncertainty_score":0.6238797,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2090919214","doi":"10.1175/1525-7541(2004)005<0735:vatcow>2.0.co;2","title":"Vegetation and Topographic Control of Wind-Blown Snow Distributions in Distributed and Aggregated Simulations for an Arctic Tundra Basin","year":2004,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":200,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Natural Environment Research Council; Canada Research Chairs","keywords":"Snow; Shrub; Environmental science; Snow field; Fetch; Snowmelt; Tundra; Wind speed; Vegetation (pathology); Arctic; Hydrology (agriculture); Atmospheric sciences; Physical geography; Geology; Snow cover; Meteorology; Geomorphology; Ecology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.0207071931193926,"gpt":0.2522301827182325,"spread":0.2315229895988399,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002972742,0.00008437127,0.0002758196,0.0002460172,0.00007686177,0.00001929027,0.00006091351,0.00008064626,0.00007736337],"category_scores_gemma":[0.000181809,0.00007121912,0.00004541917,0.0002476712,0.0001521013,0.0002555102,0.000003446281,0.0001137493,3.593327e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007169751,"about_ca_system_score_gemma":0.00003459005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007014939,"about_ca_topic_score_gemma":0.01099136,"domain_scores_codex":[0.9992059,0.00007665282,0.0003647788,0.0001025021,0.00008213014,0.0001680697],"domain_scores_gemma":[0.9991054,0.000393102,0.0002404153,0.00006179067,0.0001032283,0.0000960649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002912118,0.00009144936,0.9780893,0.00004924152,0.00005077185,0.00001682751,0.0003887094,0.01637026,0.0027414,0.0001695494,0.000004373544,0.001736874],"study_design_scores_gemma":[0.002923982,0.001471483,0.975144,0.00005284165,0.00007951296,0.0002001154,0.00007851612,0.01157694,0.0001007055,0.008152056,0.0001369871,0.00008289354],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949942,0.0009324518,0.001321901,0.0007620563,0.0001011904,0.000147683,0.001732452,0.000002962798,0.000005115322],"genre_scores_gemma":[0.9988292,0.0001602628,0.0001642667,0.00006330434,0.00003855597,4.533649e-7,0.0007411077,0.000002246711,6.057036e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01028987,"threshold_uncertainty_score":0.6133439,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1593674196","doi":"10.1175/jhm-d-15-0026.1","title":"Gridded Ensemble Precipitation and Temperature Estimates for the Contiguous United States","year":2015,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":194,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Hydrometeorology; Environmental science; Precipitation; Streamflow; Data assimilation; Climatology; Proxy (statistics); Forcing (mathematics); Meteorology; Hydrological modelling; Statistics; Drainage basin; Mathematics; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.01680296401333739,"gpt":0.2475605214754882,"spread":0.2307575574621508,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007559755,0.00009240199,0.0001871253,0.00007727005,0.0001375248,0.00001792025,0.0001376785,0.00006107074,0.00002926638],"category_scores_gemma":[0.0002493262,0.00005370105,0.00003562992,0.0001159482,0.0002589593,0.0001424633,0.00007989944,0.0001222166,0.000009334847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002515802,"about_ca_system_score_gemma":0.000004905025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000347811,"about_ca_topic_score_gemma":0.00002743589,"domain_scores_codex":[0.9993308,0.00007159601,0.0002136783,0.0001002538,0.0001091978,0.0001745209],"domain_scores_gemma":[0.9992933,0.0003585994,0.0001742699,0.00007699886,0.00003637685,0.00006046355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004335875,0.0005593812,0.2641759,0.00009268162,0.002664698,0.0002139757,0.02795932,0.2231034,0.03192583,0.001551555,0.4319417,0.01147567],"study_design_scores_gemma":[0.01687892,0.01659003,0.3103172,0.00005800944,0.002212822,0.001686439,0.007307058,0.06801935,0.00870544,0.2176329,0.3494557,0.00113619],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899629,0.0005968105,0.000885149,0.007860322,0.0003411729,0.000175432,0.000002448432,0.000008488723,0.0001672251],"genre_scores_gemma":[0.9970454,0.0001685552,0.001545884,0.0009715098,0.00004421305,0.0000103753,0.000005487552,0.000006633644,0.0002019602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2160813,"threshold_uncertainty_score":0.2189865,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2063683139","doi":"10.1175/jhm409.1","title":"Downscaling Precipitation and Temperature with Temporal Neural Networks","year":2005,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":189,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Université Laval; McMaster University","funders":"Cure Cancer Australia Foundation","keywords":"Downscaling; Environmental science; Climatology; Precipitation; Climate change; Geopotential height; Climate model; Meteorology; Geography; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.006899843346242327,"gpt":0.2158870558386259,"spread":0.2089872124923836,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004572439,0.0000874364,0.0001779508,0.00004571482,0.00006358451,0.00002087148,0.00009242259,0.00008994453,0.0002892508],"category_scores_gemma":[0.00002633813,0.00006003155,0.00003430032,0.0001067656,0.00013452,0.0003381727,0.00004232343,0.0002573946,0.000003927399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004405083,"about_ca_system_score_gemma":0.000005440659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001771433,"about_ca_topic_score_gemma":0.00009260749,"domain_scores_codex":[0.9992323,0.00008133967,0.0002582474,0.0001229598,0.0001363252,0.0001688307],"domain_scores_gemma":[0.9995651,0.00007481961,0.0001764077,0.00008178558,0.00001314085,0.0000887268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004175856,0.0001384568,0.1546381,0.000007244254,0.00004258915,0.00003673317,0.0007746659,0.8230258,0.01241021,0.00005794282,0.0005669044,0.007883743],"study_design_scores_gemma":[0.003820157,0.004421841,0.2555464,0.00004006983,0.000201056,0.004812004,0.0001786206,0.7196179,0.0004948021,0.001896669,0.008418956,0.0005514827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971734,0.0001177134,0.0005477605,0.00175956,0.00009287848,0.00006115164,8.179259e-7,0.000006452554,0.0002402912],"genre_scores_gemma":[0.9951823,0.00002994773,0.004225064,0.00039762,0.0001187187,0.000001134797,0.000001364043,0.000006705685,0.00003719765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1034079,"threshold_uncertainty_score":0.3167093,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1999267907","doi":"10.1175/jhm-d-14-0020.1","title":"Relationship between Surface Temperature and Extreme Rainfalls: A Multi-Time-Scale and Event-Based Analysis*","year":2014,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":181,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Environmental science; Climatology; Scale (ratio); Scale analysis (mathematics); Event (particle physics); Meteorology; Atmospheric sciences; Geology; Geography; Cartography; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.02506209004735067,"gpt":0.2544841570961612,"spread":0.2294220670488105,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001669469,0.0001247863,0.000403429,0.0001312319,0.0001133536,0.00002676036,0.0001274053,0.000166346,0.0002844962],"category_scores_gemma":[0.0002653438,0.0001020827,0.0001046119,0.000329761,0.000225337,0.000178095,0.0000727188,0.0002827249,0.00001450577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004161807,"about_ca_system_score_gemma":0.00001083735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004637505,"about_ca_topic_score_gemma":0.0001361659,"domain_scores_codex":[0.9986455,0.0003566806,0.0004084909,0.0002154953,0.0001773903,0.0001963767],"domain_scores_gemma":[0.998683,0.0007074687,0.0002539756,0.0001702478,0.00001683068,0.0001684198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002928123,0.00005189863,0.963973,0.000006741198,0.00005532804,0.000002674765,0.0001606304,0.02482157,0.01071414,0.00001135507,0.00006715353,0.0001062197],"study_design_scores_gemma":[0.001042139,0.0003394796,0.9222808,0.000006003297,0.0004381156,0.0000356083,0.00001462245,0.074115,0.0001357345,0.0009628503,0.0004948206,0.0001347858],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99476,0.00007981023,0.003844173,0.001082577,0.00003263906,0.00007249026,0.000007960309,0.000007922467,0.0001123701],"genre_scores_gemma":[0.9919351,0.0000066393,0.007700194,0.0001802604,0.00002676143,7.440303e-7,0.000005035156,0.000007663726,0.0001375524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04929342,"threshold_uncertainty_score":0.416281,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2133557877","doi":"10.1175/1525-7541(2004)005<0774:assodn>2.0.co;2","title":"A Sensitivity Study of Daytime Net Radiation during Snowmelt to Forest Canopy and Atmospheric Conditions","year":2004,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":166,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"Cold Regions Research and Engineering Laboratory; Rocky Mountain Research Station; Natural Environment Research Council; U.S. Forest Service; Aberystwyth University; U.S. Department of Agriculture; National Aeronautics and Space Administration","keywords":"Environmental science; Snowmelt; Shortwave radiation; Canopy; Atmospheric sciences; Longwave; Snow; Albedo (alchemy); Tree canopy; Shortwave; Overcast; Irradiance; Meteorology; Radiation; Sky; Radiative transfer; Geography; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.003536318790883083,"gpt":0.2040450428185678,"spread":0.2005087240276847,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000231786,0.00007358253,0.0001966161,0.00003988205,0.00006195736,0.000007655862,0.00005949447,0.00004332379,0.00005014099],"category_scores_gemma":[0.00002923593,0.00006491468,0.00002984152,0.0001968557,0.00005517099,0.0001445895,0.00005702864,0.000107802,0.000008364939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001061669,"about_ca_system_score_gemma":0.00001249323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004944101,"about_ca_topic_score_gemma":0.0009656552,"domain_scores_codex":[0.999275,0.00007172797,0.0002758479,0.0001012686,0.0001461729,0.0001299873],"domain_scores_gemma":[0.9995704,0.00003749524,0.0002026157,0.00008626554,0.00001141658,0.00009179814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00005852447,0.0002557222,0.3820653,0.00000285623,0.00005133635,0.0001375929,0.0009829979,0.5748211,0.04139558,0.0000270519,0.00001212954,0.0001898417],"study_design_scores_gemma":[0.001278633,0.001107804,0.9919323,0.000006088429,0.00005382963,0.0008772047,0.00007239686,0.003607053,0.000368114,0.0005672497,0.00005083062,0.00007843597],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990943,0.00001332415,0.0003919829,0.0001798879,0.0000773924,0.0001279217,0.000008471738,0.000004026127,0.0001026706],"genre_scores_gemma":[0.999167,0.0000113482,0.0007291899,0.0000403344,0.00001621236,0.000001864948,0.000001960777,0.000005547633,0.00002658042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6098671,"threshold_uncertainty_score":0.2647144,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2168060352","doi":"10.1175/jhm421.1","title":"The Role of Northern Lakes in a Regional Energy Balance","year":2005,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":165,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Environment and Climate Change Canada; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Churchill Northern Studies Centre; National Aeronautics and Space Administration","keywords":"Environmental science; Wetland; Water balance; Hydrology (agriculture); Energy balance; Latitude; Climate change; Evaporation; Physical geography; Geology; Ecology; Geography; Meteorology; Oceanography","retraction":null,"screen_n_in":null,"score":{"opus":0.006972502788765945,"gpt":0.2087069946607684,"spread":0.2017344918720025,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006139171,0.00006026638,0.0001702263,0.00004339774,0.00003620951,0.000004037239,0.0002671945,0.00005516009,0.0002397264],"category_scores_gemma":[0.00005530763,0.00003968408,0.00007006006,0.0001211075,0.0002107294,0.0001112024,0.00005762648,0.0001257446,0.00001165614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007092171,"about_ca_system_score_gemma":0.00001661557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001621674,"about_ca_topic_score_gemma":0.004342601,"domain_scores_codex":[0.9990904,0.00009890158,0.0003817633,0.00008266151,0.0001769006,0.000169366],"domain_scores_gemma":[0.9993749,0.0001925203,0.0002510467,0.0001278498,0.00001236447,0.00004130268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006143079,0.0007313419,0.6961891,0.000005532589,0.00007300083,0.0000299871,0.001592719,0.09681784,0.1215304,0.005028909,0.0008075364,0.07657936],"study_design_scores_gemma":[0.00221366,0.001296532,0.150254,0.00003252946,0.00004456249,0.0009484678,0.0003283459,0.05409598,0.004507576,0.1124047,0.6735501,0.0003235499],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951133,0.0005672637,0.00004115431,0.00213709,0.00005095781,0.00002066726,0.000001071802,0.000001768226,0.002066789],"genre_scores_gemma":[0.9990789,0.0002923833,0.0003174184,0.0001924482,0.00004544218,0.000001460549,2.673273e-7,0.00000406319,0.00006760736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6727425,"threshold_uncertainty_score":0.2624836,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2078493400","doi":"10.1175/jhm627.1","title":"Evaluation of the Hydrological Cycle over the Mississippi River Basin as Simulated by the Canadian Regional Climate Model (CRCM)","year":2007,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":163,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Ouranos; Université du Québec à Montréal","funders":"Canadian Foundation for Climate and Atmospheric Sciences; U.S. Department of Energy","keywords":"Evapotranspiration; Water cycle; Environmental science; Precipitation; Climate model; Surface runoff; Annual cycle; Climatology; Drainage basin; Climate change; Structural basin; Hydrology (agriculture); Meteorology; Geology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.03295782041319554,"gpt":0.2862770010303336,"spread":0.253319180617138,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009238929,0.0001385806,0.0002307604,0.00005792356,0.0004022017,0.00001682884,0.0006834314,0.0002026117,0.00149814],"category_scores_gemma":[0.0004393919,0.00006468136,0.0001943635,0.0002729844,0.0008718495,0.0001360412,0.0001435591,0.0004620414,0.00002290529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004253849,"about_ca_system_score_gemma":0.0001664884,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01393949,"about_ca_topic_score_gemma":0.01737278,"domain_scores_codex":[0.9971262,0.0006716568,0.0005625125,0.0001841017,0.001028698,0.0004268929],"domain_scores_gemma":[0.9985,0.0004316727,0.0004570053,0.0003685289,0.00008373506,0.0001590379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000222389,0.0001694837,0.01327977,0.000002292428,0.00008626732,0.00000745902,0.0009295911,0.9725169,0.007005799,0.0003282562,0.003624347,0.001827444],"study_design_scores_gemma":[0.0009086651,0.0002346427,0.1176999,0.000007743806,0.0002822857,0.000241216,0.00004160059,0.8379258,0.0002996018,0.03785345,0.004386061,0.0001190546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988562,0.00009654527,0.00008068185,0.007424796,0.0001509571,0.0002382107,0.00001298194,0.000003608218,0.003430231],"genre_scores_gemma":[0.9968892,0.00002735829,0.00008096072,0.002910727,0.00003147282,0.000001516772,0.000001656478,0.000008969691,0.00004815677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1345911,"threshold_uncertainty_score":0.9994146,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2084580533","doi":"10.1175/2010jhm1212.1","title":"Global Evaluation of the ISBA-TRIP Continental Hydrological System. Part II: Uncertainties in River Routing Simulation Related to Flow Velocity and Groundwater Storage","year":2010,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":154,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Agence Nationale de la Recherche; Grains Research and Development Corporation; ArcticNet","keywords":"Streamflow; Environmental science; Routing (electronic design automation); Groundwater; Hydrology (agriculture); Flow routing; Groundwater flow; Surface runoff; Drainage basin; Biosphere; Flow (mathematics); Water storage; Geology; Aquifer; Geomorphology; Geography; Geotechnical engineering; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.02071555953683223,"gpt":0.2471032831785226,"spread":0.2263877236416904,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002729803,0.0000995827,0.0002693248,0.00008186522,0.0001164153,0.00001717723,0.0001599571,0.0001184066,0.0001060966],"category_scores_gemma":[0.0002868567,0.0000635262,0.00006910441,0.0002320131,0.0001131065,0.0001457029,0.00003066622,0.0002463292,0.000003796356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002301584,"about_ca_system_score_gemma":0.00004670765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006444543,"about_ca_topic_score_gemma":0.001318735,"domain_scores_codex":[0.9983089,0.0004015024,0.0004659361,0.0001350497,0.0005006605,0.0001879296],"domain_scores_gemma":[0.9991978,0.00009723964,0.0003424239,0.0001019474,0.0001945167,0.00006608525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009875265,0.00003178173,0.5202863,0.000005429236,0.00002884021,0.000004489208,0.0003101731,0.4762594,0.0002932072,0.00002345946,0.000007671272,0.002650516],"study_design_scores_gemma":[0.0005728881,0.000306117,0.6472492,0.0000143658,0.00004253269,0.00003449272,0.0000446088,0.3503956,0.00002075574,0.00123067,0.00004144938,0.00004733443],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983535,0.00005325682,0.00003403327,0.0002137125,0.001017837,0.0001833746,0.00001334847,0.00000332602,0.000127582],"genre_scores_gemma":[0.9997764,0.000001014505,0.0001066079,0.00004975716,0.00005142296,4.16781e-7,0.000004754774,0.000001538769,0.000008073944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1269628,"threshold_uncertainty_score":0.2590523,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2019874943","doi":"10.1175/jhm-d-14-0089.1","title":"The Canadian Land Data Assimilation System (CaLDAS): Description and Synthetic Evaluation Study","year":2015,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":149,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Environment and Climate Change Canada","funders":"National Aeronautics and Space Administration","keywords":"Data assimilation; Environmental science; Ensemble Kalman filter; Precipitation; Forcing (mathematics); Global Precipitation Measurement; Climatology; Numerical weather prediction; Meteorology; Precipitable water; Land cover; Atmospheric sciences; Kalman filter; Mathematics; Geology; Land use; Extended Kalman filter; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.07477796592368695,"gpt":0.2834995082582455,"spread":0.2087215423345585,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003714698,0.00006491772,0.0001242145,0.00006865847,0.0002116312,0.00005866804,0.0001934505,0.00005861453,0.000005956853],"category_scores_gemma":[0.0002988552,0.00003939113,0.00001385907,0.0001063147,0.00009280142,0.0002128033,0.00007272556,0.0001385735,0.00001433555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003902017,"about_ca_system_score_gemma":0.0000812075,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02399845,"about_ca_topic_score_gemma":0.4850989,"domain_scores_codex":[0.9986777,0.0004065034,0.0002514999,0.0001262433,0.0003950162,0.000143048],"domain_scores_gemma":[0.9992831,0.00007316442,0.0002012329,0.0002392758,0.00004630951,0.0001568658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001873366,0.0001325733,0.8126056,0.000006912118,0.0001709747,0.0001702652,0.002670833,0.00576202,0.0007114739,0.00002329447,0.006597499,0.1709612],"study_design_scores_gemma":[0.0009406997,0.0007243897,0.9167269,0.00001311827,0.0002385657,0.001316235,0.001208555,0.07407627,0.00001021464,0.000458611,0.00419509,0.00009128752],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942937,0.000232147,0.00006674258,0.000946675,0.0007087528,0.0001661963,6.223283e-7,0.000003933679,0.003581176],"genre_scores_gemma":[0.9996721,0.000006457071,0.0001675864,0.00004062453,0.00008501979,2.954958e-7,0.000002172145,0.000005324708,0.00002038333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4611005,"threshold_uncertainty_score":0.9825009,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1995797217","doi":"10.1175/2008jhm960.1","title":"Probabilistic Multisite Precipitation Downscaling by an Expanded Bernoulli–Gamma Density Network","year":2008,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":146,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Division of Ocean Sciences; University of British Columbia","keywords":"Downscaling; Precipitation; Environmental science; Bernoulli distribution; Gamma distribution; Conditional probability distribution; Probabilistic logic; Climatology; Autoregressive model; Meteorology; Mathematics; Statistics; Geography; Geology; Random variable","retraction":null,"screen_n_in":null,"score":{"opus":0.01815060435732493,"gpt":0.2405176133812678,"spread":0.2223670090239428,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001188849,0.0001451285,0.0003452536,0.00004823962,0.0001938973,0.00001212071,0.000226993,0.0001510704,0.0004999743],"category_scores_gemma":[0.0002289838,0.000125806,0.0001049316,0.00018172,0.0002455694,0.0005312061,0.00008518893,0.0002761609,0.00004549175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00016167,"about_ca_system_score_gemma":0.00001401665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001515393,"about_ca_topic_score_gemma":0.00009828746,"domain_scores_codex":[0.9981843,0.0003323678,0.0005589548,0.0002178684,0.0003084387,0.0003980656],"domain_scores_gemma":[0.9989173,0.0002327315,0.0003813362,0.0002090336,0.00003262968,0.0002269438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006022741,0.00119926,0.6332104,0.00002130591,0.0000956373,0.0001056806,0.004027967,0.2900457,0.06126226,0.00008640885,0.006267706,0.003075493],"study_design_scores_gemma":[0.005223342,0.005747311,0.8216557,0.00006645757,0.0003626551,0.007684621,0.0001875067,0.1136153,0.004547071,0.02760292,0.01203153,0.001275591],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950357,0.00008017784,0.003906015,0.0001698963,0.0003683817,0.000154731,0.000004212803,0.0000170668,0.0002637832],"genre_scores_gemma":[0.9937552,0.00008120378,0.005681457,0.0002308456,0.0001525548,0.000003983934,0.000008794553,0.00001278674,0.00007321341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1884454,"threshold_uncertainty_score":0.5474368,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2580791415","doi":"10.1175/jhm-d-16-0187.1","title":"Evaluation of Integrated Multisatellite Retrievals for GPM (IMERG) over Southern Canada against Ground Precipitation Observations: A Preliminary Assessment","year":2017,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":141,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Centrum fÖr Personcentrerad Vård","keywords":"Hydrometeorology; Environmental science; Global Precipitation Measurement; Precipitation; Climatology; Meteorology; Geography; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.07601916754362864,"gpt":0.3079233442144686,"spread":0.23190417667084,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004955091,0.0001253266,0.0003481498,0.0002102559,0.0002385103,0.00005918472,0.0003440195,0.0000832665,0.0004059163],"category_scores_gemma":[0.00189361,0.0001010719,0.0001378929,0.0001401758,0.00007161663,0.0004915162,0.000008603093,0.0001399875,0.00000192774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007554307,"about_ca_system_score_gemma":0.0009927691,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03542959,"about_ca_topic_score_gemma":0.2080097,"domain_scores_codex":[0.9974669,0.0004376335,0.0007525576,0.0001530102,0.001012192,0.0001776759],"domain_scores_gemma":[0.9960647,0.0003632492,0.001743455,0.0002263479,0.001522163,0.00008012678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006242468,0.0001097281,0.8272252,0.00005806974,0.001067854,0.000006323148,0.0007801529,0.03408712,0.007361789,0.00003199412,0.0008045007,0.127843],"study_design_scores_gemma":[0.001243783,0.0005374857,0.8457121,0.00004096235,0.0004675673,0.000003420084,0.0003198528,0.1491245,0.000182581,0.001818153,0.0004499848,0.00009953923],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963662,0.0007347684,0.00112048,0.0004612301,0.0006323048,0.0002876926,0.0001581915,0.000003356227,0.0002358021],"genre_scores_gemma":[0.9943147,0.00006357978,0.005199513,0.00008133487,0.00008444868,0.000003291705,0.0001642651,0.000004591637,0.00008423373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1725802,"threshold_uncertainty_score":0.9709936,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2037281510","doi":"10.1175/jhm414.1","title":"Evaluation of 10 Methods for Initializing a Land Surface Model","year":2005,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":140,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"National Aeronautics and Space Administration","keywords":"Initialization; Forcing (mathematics); Spurious relationship; Environmental science; Meteorology; Computer science; Climatology; Climate model; Moisture; Geology; Climate change; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.09731252853815048,"gpt":0.4022015205117775,"spread":0.304888991973627,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009007473,0.00007132782,0.0002571177,0.00005400336,0.00003516695,0.000004889843,0.0001523587,0.0000852552,0.001173963],"category_scores_gemma":[0.0005714085,0.00006014974,0.00010638,0.00008910851,0.00008654899,0.0002118095,0.00005211828,0.00009066763,0.000007466218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001342063,"about_ca_system_score_gemma":0.00004783952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001754992,"about_ca_topic_score_gemma":0.00003150574,"domain_scores_codex":[0.9986027,0.0003793838,0.0004583764,0.000108504,0.0002969209,0.0001541346],"domain_scores_gemma":[0.9990684,0.0003002857,0.0003560669,0.0001192873,0.0001020598,0.00005386523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009758376,0.0001035627,0.0006416403,0.000005459434,0.00003337938,2.245447e-7,0.0003214182,0.8989509,0.08217606,0.00005624583,0.0001843542,0.01742912],"study_design_scores_gemma":[0.001017798,0.0003359803,0.0003373981,0.000004872175,0.0002009949,0.00004137814,0.000009549221,0.9699847,0.004866167,0.02145691,0.001683103,0.00006114615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9163478,0.0001233894,0.08108936,0.0005164339,0.00008364557,0.0001381208,0.000004880879,0.000003022547,0.001693352],"genre_scores_gemma":[0.7940372,0.00001708825,0.2057906,0.00007904071,0.00003087877,0.000002451032,8.393041e-7,0.00000586357,0.00003594405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1247013,"threshold_uncertainty_score":0.9997391,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2115661221","doi":"10.1175/1525-7541(2004)005<0745:pobsia>2.0.co;2","title":"Parameterization of Blowing-Snow Sublimation in a Macroscale Hydrology Model","year":2004,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":137,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Washington; National Aeronautics and Space Administration; National Science Foundation","keywords":"Snow; Fetch; Environmental science; Snowpack; Permafrost; Snowmelt; Hydrology (agriculture); Sublimation (psychology); Terrain; Arctic; Tundra; Hydrological modelling; Atmospheric sciences; Geology; Climatology; Geomorphology","retraction":null,"screen_n_in":null,"score":{"opus":0.0168854118738597,"gpt":0.2281893675365429,"spread":0.2113039556626832,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003789741,0.00008133068,0.0003114284,0.0001712836,0.0000413712,0.000007231905,0.0001443032,0.00008490934,0.0001667877],"category_scores_gemma":[0.0001759793,0.00006805569,0.00007798763,0.0003846836,0.00008789436,0.0002039217,0.000009692743,0.0001394833,0.000005395851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001155768,"about_ca_system_score_gemma":0.00006541685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003077223,"about_ca_topic_score_gemma":0.001209455,"domain_scores_codex":[0.9989589,0.00005160064,0.0005558022,0.00009702296,0.0001477309,0.0001888773],"domain_scores_gemma":[0.9993125,0.0001197769,0.0003633516,0.00008529838,0.00007369467,0.00004533284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001007616,0.00004620576,0.2024817,0.000009443398,0.00002796482,0.00001769889,0.0004367193,0.7922924,0.001273493,0.0001463,0.0000199727,0.003147381],"study_design_scores_gemma":[0.001866424,0.001341829,0.7557865,0.00002899371,0.00004616327,0.0001770555,0.0001255048,0.2169588,0.0004380711,0.02289134,0.000206162,0.0001331766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911677,0.0003971692,0.006891179,0.001024426,0.0002737987,0.00006260366,0.000009679906,0.000004145311,0.0001693222],"genre_scores_gemma":[0.9922926,0.000183122,0.007276217,0.0001806545,0.00004221231,4.421741e-7,0.00001085259,0.000002548027,0.00001131351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5753336,"threshold_uncertainty_score":0.277523,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2084010789","doi":"10.1175/jhm591.1","title":"Northern Lake Impacts on Local Seasonal Climate","year":2007,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":136,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"McGill University; Université du Québec à Montréal; Bedford Institute of Oceanography; Fisheries and Oceans Canada; Dalhousie University","funders":"Canadian Foundation for Climate and Atmospheric Sciences","keywords":"Environmental science; Climate model; Atmosphere (unit); Climatology; Water cycle; Mesoscale meteorology; Seasonality; Storm; Surface water; Climate change; Atmospheric sciences; Geology; Oceanography; Meteorology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.007136416558441917,"gpt":0.2209927075692168,"spread":0.2138562910107749,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006362331,0.00007091382,0.0001469158,0.0001010698,0.00005204496,0.000007227176,0.0001182364,0.00006332881,0.002554942],"category_scores_gemma":[0.00004547074,0.00004974722,0.00007382636,0.00008581905,0.00008694876,0.00006352591,0.000005273067,0.00023276,0.0004460199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007750112,"about_ca_system_score_gemma":0.00004796381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001732077,"about_ca_topic_score_gemma":0.001191252,"domain_scores_codex":[0.9992364,0.00003134129,0.0002185123,0.00006429274,0.000179138,0.0002702818],"domain_scores_gemma":[0.9994497,0.0001635192,0.0001527095,0.00005844724,0.00004288433,0.000132723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005256707,0.00005065188,0.8250632,0.00001235122,0.0000760918,0.0007817287,0.0001258666,0.001997269,0.00002569607,0.0003647902,0.0005609494,0.1704157],"study_design_scores_gemma":[0.0005585352,0.00188679,0.9568133,0.00002035668,0.00004169302,0.002262185,0.0001315439,0.003148626,0.00002129961,0.001620168,0.0333444,0.0001511371],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808224,0.00008406696,0.001179881,0.0003489919,0.0006588123,0.00001925794,0.00001431747,0.000006199342,0.01686605],"genre_scores_gemma":[0.9985774,0.00005796752,0.0004207235,0.0006434782,0.0002207234,1.185881e-8,0.00000779769,0.000002636672,0.00006925385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1702646,"threshold_uncertainty_score":0.9983569,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1882439680","doi":"10.1175/jhm-d-14-0191.1","title":"Performance Evaluation of the Canadian Precipitation Analysis (CaPA)","year":2015,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":135,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Precipitation; Environmental science; Meteorology; Quantitative precipitation estimation; Numerical weather prediction; Climatology; Quantitative precipitation forecast; Radar; National weather service; Satellite; Computer science; Geography; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.0607525631418683,"gpt":0.2602682118734719,"spread":0.1995156487316036,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004274803,0.00005690581,0.0002020897,0.0006244484,0.00007717883,0.00001426044,0.0002322669,0.00005119346,0.0006790421],"category_scores_gemma":[0.0004504784,0.00003634911,0.0001489203,0.001032935,0.00005850202,0.0002204404,0.000003180378,0.0001041586,0.00001436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003579399,"about_ca_system_score_gemma":0.0005514108,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01161197,"about_ca_topic_score_gemma":0.3514272,"domain_scores_codex":[0.9981752,0.0004279496,0.0003710092,0.00006720839,0.0008347928,0.0001238218],"domain_scores_gemma":[0.9983606,0.00005055772,0.0004825806,0.0001178809,0.0008555756,0.0001327995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001521754,0.00000506691,0.8348704,0.000001378973,0.0002649924,2.61521e-7,0.0002872997,0.1574121,0.00004302623,0.000003284068,0.0001504148,0.006946617],"study_design_scores_gemma":[0.000282936,0.0001464042,0.8683382,0.00000350408,0.0009993443,0.000005422992,0.00007328389,0.1294748,0.00009912018,0.0003821261,0.0001581844,0.00003663693],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948152,0.0002808479,0.00002655222,0.0005253572,0.0003638663,0.00005385859,0.000005283672,0.000001300662,0.003927727],"genre_scores_gemma":[0.9995726,0.00001026353,0.0002543919,0.00006531856,0.00004972894,2.437727e-7,0.00001028603,0.000001005276,0.00003619671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3398153,"threshold_uncertainty_score":0.9949698,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2159923592","doi":"10.1175/1525-7541(2003)004<0720:iasvot>2.0.co;2","title":"Interannual and Seasonal Variability of the Surface Energy Balance and Temperature of Central Great Slave Lake","year":2003,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":129,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Latent heat; Sensible heat; Environmental science; Energy balance; Climatology; Atmospheric sciences; Atmosphere (unit); Water cycle; Energy budget; Shore; Water balance; Heat flux; Meteorology; Heat transfer; Geology; Oceanography; Geography; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.003043205658537872,"gpt":0.1694681851143245,"spread":0.1664249794557866,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004216881,0.00009204209,0.0002939921,0.00001466977,0.00004305671,0.000008389926,0.0001316612,0.00008064616,0.0002792441],"category_scores_gemma":[0.000149026,0.00005361947,0.0000608685,0.0001965563,0.0003393932,0.0001175301,0.00001089451,0.0001619467,7.503057e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001192323,"about_ca_system_score_gemma":0.00007478717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003849907,"about_ca_topic_score_gemma":0.0002193862,"domain_scores_codex":[0.9990752,0.0002264608,0.0002842403,0.0001048535,0.0001483334,0.0001609109],"domain_scores_gemma":[0.9992612,0.0002230709,0.000273041,0.00007996105,0.0000836377,0.0000790718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008504173,0.00001864976,0.9979843,0.00002963942,0.00005240823,0.00000570381,0.0001303827,0.0003119946,0.0004156314,0.0001652936,0.00007701405,0.0007239729],"study_design_scores_gemma":[0.0005172977,0.0005285275,0.9918665,0.00002885731,0.00004792824,0.0005965205,0.00008200811,0.0005572345,0.0008833339,0.002787562,0.002028621,0.00007559946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965442,0.002590256,0.00003552269,0.0001811358,0.0002470796,0.00002398946,0.00004231019,0.000001514157,0.0003339253],"genre_scores_gemma":[0.9987333,0.0004095142,0.000696144,0.00009349762,0.00002345729,2.811505e-8,0.000001194544,0.000001581102,0.00004127819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006117757,"threshold_uncertainty_score":0.3057527,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2054442182","doi":"10.1175/2010jhm1211.1","title":"Global Evaluation of the ISBA-TRIP Continental Hydrological System. Part I: Comparison to GRACE Terrestrial Water Storage Estimates and In Situ River Discharges","year":2010,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":122,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Agence Nationale de la Recherche; Center for Neuroscience and Regenerative Medicine; Grains Research and Development Corporation; Centre National de la Recherche Scientifique; ArcticNet","keywords":"Environmental science; Evapotranspiration; Context (archaeology); Biosphere; Surface runoff; Precipitation; Water storage; Water cycle; Hydrology (agriculture); Forcing (mathematics); Climatology; Discharge; Meteorology; Geology; Oceanography; Drainage basin; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.02682472408179708,"gpt":0.2640632346766215,"spread":0.2372385105948244,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001858841,0.0001108746,0.0003600336,0.00007677767,0.00006299376,0.00002235579,0.0002244376,0.00009031585,0.00008788234],"category_scores_gemma":[0.0001806459,0.00005883512,0.00007343796,0.0001182999,0.0001333769,0.0001125762,0.00003014671,0.0002294483,0.000009533751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009548651,"about_ca_system_score_gemma":0.0000321786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004154945,"about_ca_topic_score_gemma":0.002585978,"domain_scores_codex":[0.9983841,0.0003066674,0.0004492638,0.0001375597,0.0005019439,0.0002204734],"domain_scores_gemma":[0.9993715,0.00008377655,0.0002584922,0.0001124917,0.00007849506,0.00009526958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002731742,0.0000622519,0.97108,0.000006997066,0.00003146652,0.000007385704,0.0001515508,0.01832754,0.009192043,0.000006576834,0.00006036817,0.0008006562],"study_design_scores_gemma":[0.001116998,0.000443186,0.9760289,0.00001771227,0.00008744146,0.00007904474,0.00004426287,0.01985918,0.001244843,0.0008834978,0.0001222413,0.00007265701],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997585,0.00009887273,0.00001508043,0.0004832633,0.001503131,0.0002005724,0.00002191364,0.000002632744,0.00008956096],"genre_scores_gemma":[0.9997364,0.000001343094,0.000106591,0.00003595905,0.0001083489,7.405237e-7,0.000006469941,0.000001517284,0.000002604673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007947201,"threshold_uncertainty_score":0.2399227,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2135025425","doi":"10.1175/2008jhm1074.1","title":"Northwest Territories and Nunavut Snow Characteristics from a Subarctic Traverse: Implications for Passive Microwave Remote Sensing","year":2008,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":121,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Environment and Climate Change Canada","funders":"U.S. Geological Survey","keywords":"Snow; Snowpack; Snowmelt; Geology; Physical geography; Environmental science; Tundra; Arctic; Snow field; Climatology; Snow cover; Geomorphology; Oceanography; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.02196499968755991,"gpt":0.2251094728165332,"spread":0.2031444731289733,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009563327,0.0001098908,0.0003118842,0.00004971276,0.0003386176,0.00001991771,0.00009278639,0.00006944234,0.00005434251],"category_scores_gemma":[0.0002188647,0.00009146147,0.00008295064,0.0001159584,0.0001852771,0.0001092148,0.000009474837,0.0001351171,0.00000240116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009179132,"about_ca_system_score_gemma":0.00006189484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002778054,"about_ca_topic_score_gemma":0.0110141,"domain_scores_codex":[0.9991823,0.00003619445,0.0003704987,0.0001350395,0.00007624397,0.0001997147],"domain_scores_gemma":[0.9986749,0.0006246295,0.0003364974,0.0001017337,0.000163089,0.00009913688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001393563,0.00001729978,0.9038193,0.00001059563,0.0002001127,0.00007039385,0.001235255,0.00003991311,0.001027804,0.00001880112,0.0005663444,0.09285486],"study_design_scores_gemma":[0.0004043607,0.0003442756,0.9870157,0.00001033228,0.00008543442,0.0007258074,0.0001694483,0.001130045,0.00003634668,0.001974895,0.008007367,0.00009602855],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915885,0.0005198099,0.004376144,0.002406599,0.0006250959,0.00009478682,0.0003613266,0.000006335717,0.00002134652],"genre_scores_gemma":[0.9814441,0.0007779289,0.01688096,0.0003183571,0.0004540488,1.407271e-7,0.00009812631,0.000004393759,0.00002195183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09275883,"threshold_uncertainty_score":0.6146128,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2399798019","doi":"10.1175/jhm-d-15-0138.1","title":"Can Precipitation and Temperature from Meteorological Reanalyses Be Used for Hydrological Modeling?","year":2016,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":120,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Environmental science; Precipitation; Climatology; Forcing (mathematics); Subtropics; Watershed; Climate Forecast System; Streamflow; Water cycle; Global Precipitation Measurement; Meteorology; Drainage basin; Geology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.02382028688656319,"gpt":0.2577415547789972,"spread":0.2339212678924341,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008011799,0.0001933956,0.0004972956,0.0001138151,0.000155731,0.00001416099,0.0002517317,0.0002440843,0.0003711078],"category_scores_gemma":[0.0004124318,0.0001051066,0.00013928,0.0001001973,0.0003877231,0.0002103148,0.0001750333,0.0001753645,0.00000936107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005545331,"about_ca_system_score_gemma":0.000006888122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004852932,"about_ca_topic_score_gemma":0.0001290475,"domain_scores_codex":[0.9983977,0.0002301507,0.0004830974,0.000338881,0.0002127092,0.0003374329],"domain_scores_gemma":[0.9988523,0.0005771421,0.0002693969,0.0001545748,0.00002779761,0.0001188597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.004236798,0.0007502871,0.3232398,0.00002626572,0.002566719,0.0003332211,0.002790415,0.01907604,0.6217788,0.001683093,0.0154846,0.008033905],"study_design_scores_gemma":[0.02327587,0.02474835,0.2061716,0.00009334016,0.00353547,0.0007182427,0.0005777695,0.03668223,0.01345208,0.6553089,0.03314096,0.002295209],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9727303,0.0001465553,0.001993872,0.02459793,0.0001988461,0.0001665031,0.00002103656,0.00001783212,0.0001270867],"genre_scores_gemma":[0.9953374,0.0001784381,0.002754903,0.001454909,0.0001041916,0.00001680225,0.000004802467,0.00001083968,0.0001376607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6536258,"threshold_uncertainty_score":0.4286124,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2181040308","doi":"10.1175/1525-7541(2004)005<0129:tcaebo>2.0.co;2","title":"Thermal Characteristics and Energy Balance of Various-Size Canadian Shield Lakes in the Mackenzie River Basin","year":2004,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":104,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"McMaster University","funders":"","keywords":"Environmental science; Wind speed; Energy balance; Energy budget; Hydrology (agriculture); Fetch; Atmospheric sciences; Structural basin; Evaporation; Climatology; Geology; Meteorology; Oceanography; Geomorphology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.004779077078874867,"gpt":0.1877441798387238,"spread":0.1829651027598489,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005207564,0.00008805306,0.0002589115,0.00006095605,0.00003841456,0.00000888455,0.0002467606,0.00008544717,0.0002512966],"category_scores_gemma":[0.00006863568,0.00006015098,0.00004047406,0.0001246564,0.0001686691,0.00008157412,0.0000273045,0.0001735847,0.000004515875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000811944,"about_ca_system_score_gemma":0.00005203152,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03597,"about_ca_topic_score_gemma":0.1205273,"domain_scores_codex":[0.9990996,0.0001036739,0.0003628697,0.00008735704,0.0001480166,0.0001984737],"domain_scores_gemma":[0.9993495,0.0001641616,0.0002724207,0.000121862,0.000008063107,0.00008404633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009860688,0.0001505369,0.9790857,0.00002286632,0.00006447049,0.0006357185,0.004176467,0.003101885,0.003942717,0.004658797,0.0003072625,0.003754979],"study_design_scores_gemma":[0.0007276214,0.0004820578,0.9868028,0.00002835409,0.00002702301,0.0006525154,0.00008705205,0.001202652,0.00007217964,0.003827482,0.005967753,0.0001224684],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997246,0.00007264022,0.0001010569,0.0009387052,0.000148548,0.00003124855,0.00002076333,0.000001058932,0.001440039],"genre_scores_gemma":[0.998711,0.00006395131,0.0003815885,0.000758548,0.00004165129,0.000001058257,0.000001430069,0.000005741438,0.00003503378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08455727,"threshold_uncertainty_score":0.9704496,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2128095597","doi":"10.1175/jhm-d-14-0189.1","title":"Comparing Evapotranspiration from Eddy Covariance Measurements, Water Budgets, Remote Sensing, and Land Surface Models over Canadaa,b","year":2015,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":103,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of British Columbia; Natural Resources Canada","funders":"Natural Resources Canada","keywords":"Evapotranspiration; Environmental science; Eddy covariance; Precipitation; Land cover; Climatology; Data assimilation; Offset (computer science); Atmospheric sciences; Meteorology; Land use; Ecosystem; Geography; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.04077117225632732,"gpt":0.2222387102904945,"spread":0.1814675380341672,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006051477,0.0001164558,0.00025348,0.00004331032,0.00005847336,0.00002869392,0.0001109633,0.00008750635,0.00004880462],"category_scores_gemma":[0.00001147676,0.00008653287,0.00003230391,0.0000584066,0.00006913201,0.0002934666,0.0000493793,0.0001867213,0.00001008494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001549945,"about_ca_system_score_gemma":0.00002148019,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01268931,"about_ca_topic_score_gemma":0.008042503,"domain_scores_codex":[0.9988459,0.0001140308,0.0003328929,0.0001539757,0.0003400936,0.0002131582],"domain_scores_gemma":[0.9995229,0.00002126033,0.0001540066,0.0001160172,0.00002893019,0.0001569246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001042644,0.00001681405,0.05491636,0.000002203267,0.00006699467,0.00005253882,0.0004776489,0.9168626,0.02674424,0.000005797079,0.000188842,0.0005616648],"study_design_scores_gemma":[0.001331575,0.0001647442,0.006869324,0.00001518365,0.00008615568,0.0002899182,0.000006577799,0.982843,0.001033237,0.005576859,0.001618246,0.0001651133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9701752,0.0001400984,0.02853527,0.0002683362,0.0002651255,0.00005694363,0.000006915928,0.000006534493,0.0005455382],"genre_scores_gemma":[0.9899359,0.00002861121,0.009746066,0.0001707165,0.00003482381,4.822488e-8,0.00001100177,0.000009581466,0.00006319566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06598043,"threshold_uncertainty_score":0.9938853,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2340538778","doi":"10.1175/jhm-d-15-0171.1","title":"The Plumbing of Land Surface Models: Is Poor Performance a Result of Methodology or Data Quality?","year":2016,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":102,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Natural Resources Canada; Horizon 2020 Framework Programme; Natural Sciences and Engineering Research Council of Canada; ETH Zürich Foundation; U.S. Department of Energy; European Commission; Environment and Climate Change Canada; Met Office; Eidgenössische Technische Hochschule Zürich; Uniscientia Foundation; Bundesministerium für Bildung und Forschung; Oak Ridge National Laboratory; Biological and Environmental Research; Canadian Foundation for Climate and Atmospheric Sciences; Department for Environment, Food and Rural Affairs, UK Government; Microsoft Research; Université Laval; National Science Foundation","keywords":"Sensible heat; Latent heat; Shortwave radiation; Environmental science; Shortwave; Predictability; Meteorology; Flux (metallurgy); Range (aeronautics); Empirical modelling; Scale (ratio); Atmospheric sciences; Climatology; Computer science; Statistics; Mathematics; Radiation; Geography; Radiative transfer; Simulation","retraction":null,"screen_n_in":null,"score":{"opus":0.1232022863933649,"gpt":0.3154676603618579,"spread":0.192265373968493,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00324303,0.00008062566,0.0003267854,0.00004539017,0.00005204673,0.000004496357,0.000724534,0.00008819795,0.0001226087],"category_scores_gemma":[0.0002593248,0.00003851411,0.00005446076,0.0001437123,0.000309518,0.0003100373,0.0002922751,0.0001328221,0.000005561294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003245685,"about_ca_system_score_gemma":0.00003007045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001404809,"about_ca_topic_score_gemma":0.0001613706,"domain_scores_codex":[0.9983239,0.0004053744,0.0006985099,0.0001380003,0.0002459848,0.0001882871],"domain_scores_gemma":[0.9977806,0.0009872656,0.0007603461,0.0003976094,0.00002873031,0.00004549929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006312177,0.0004546413,0.3321832,0.0001059754,0.001006498,0.000080408,0.003045795,0.1098825,0.473691,0.001056768,0.004277279,0.06790368],"study_design_scores_gemma":[0.01118975,0.006953405,0.1298017,0.0003498348,0.0007123445,0.004321729,0.0003964847,0.7383816,0.03474667,0.04232962,0.02971722,0.001099584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945959,0.0001329154,0.003509896,0.001143069,0.0001309116,0.00004543836,0.00009108429,0.000002363644,0.0003483873],"genre_scores_gemma":[0.9915459,0.000835275,0.007066118,0.00006146097,0.00001473017,3.384384e-7,0.000001951311,0.000006326606,0.0004678545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6284992,"threshold_uncertainty_score":0.157056,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2163929020","doi":"10.1175/2007jhm870.1","title":"Radiative Transfer Modeling of a Coniferous Canopy Characterized by Airborne Remote Sensing","year":2008,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":102,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"Natural Environment Research Council; National Oceanic and Atmospheric Administration","keywords":"Environmental science; Radiative transfer; Remote sensing; Radiometer; Canopy; Atmospheric radiative transfer codes; Tree canopy; Spatial ecology; Meteorology; Atmospheric sciences; Geology; Geography; Optics; Physics; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.0110808016842885,"gpt":0.2040006610843575,"spread":0.1929198594000691,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003858216,0.0001968021,0.0006304846,0.00009792851,0.00008795543,0.000006146683,0.000210991,0.0001806329,0.0001415766],"category_scores_gemma":[0.00005313316,0.000149432,0.0001846941,0.000280551,0.000297445,0.0001879547,0.00003784182,0.0004260488,0.00001863864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000160907,"about_ca_system_score_gemma":0.00003586375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002203105,"about_ca_topic_score_gemma":0.00002015092,"domain_scores_codex":[0.99812,0.0002320712,0.0007186417,0.0002079635,0.0003927965,0.0003285566],"domain_scores_gemma":[0.9992065,0.00008838192,0.0003352325,0.0001622802,0.00005904153,0.0001485592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003465617,0.00007156142,0.0003611795,0.000009553565,0.0001381316,0.0004214744,0.00152716,0.02030145,0.964037,0.000001487625,0.0007420443,0.01204238],"study_design_scores_gemma":[0.01198588,0.005475522,0.01640615,0.0002204758,0.0005723751,0.05166686,0.0003574861,0.7046902,0.1898783,0.001453971,0.01561065,0.001682128],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9692672,0.0001877022,0.0291478,0.0004372688,0.0002362425,0.0001296421,0.000006187992,0.00001133535,0.0005766311],"genre_scores_gemma":[0.9892763,0.0002567582,0.009957059,0.0002844391,0.00008660245,3.888962e-8,0.000002911225,0.0000192788,0.0001166483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7741587,"threshold_uncertainty_score":0.6093659,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2045993143","doi":"10.1175/jhm-d-13-078.1","title":"Effects of Irrigation in India on the Atmospheric Water Budget","year":2014,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":96,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Environmental science; Irrigation; Precipitation; Moisture; Water content; Evaporation; Drainage basin; Hydrology (agriculture); Climatology; Meteorology; Geology; Geography; Agronomy","retraction":null,"screen_n_in":null,"score":{"opus":0.004585640887557961,"gpt":0.1987541777483756,"spread":0.1941685368608176,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001179899,0.00006520871,0.0001875431,0.00001891146,0.0000242948,0.00000373809,0.0001839792,0.00006716589,0.0005140959],"category_scores_gemma":[0.0001698103,0.00003409112,0.00005612478,0.0001043003,0.0001229055,0.00007848834,0.00005433681,0.0001735988,0.00005701339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005179857,"about_ca_system_score_gemma":0.000003557158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003641921,"about_ca_topic_score_gemma":0.000008147682,"domain_scores_codex":[0.9990304,0.0002795198,0.0002970552,0.00008335584,0.0001580296,0.0001516344],"domain_scores_gemma":[0.9992567,0.0004306216,0.0001585178,0.0001153958,0.000006152326,0.00003262293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000439996,0.0009118053,0.1019586,0.00006861299,0.00006459704,0.00004066368,0.003373008,0.05338661,0.8309902,0.003908467,0.0006656458,0.004191778],"study_design_scores_gemma":[0.001740687,0.002984654,0.8158809,0.00004543195,0.00005242358,0.00008696395,0.0000287685,0.01545698,0.08118232,0.0798573,0.002506282,0.000177279],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969403,0.000006572611,0.0001335791,0.0007847528,0.0001620266,0.0000857862,2.158994e-7,0.000001854383,0.001884925],"genre_scores_gemma":[0.9991727,0.000007777156,0.0002955084,0.0004755321,0.00002028591,0.000002517319,3.010773e-7,0.000004572977,0.00002081135],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7498078,"threshold_uncertainty_score":0.5628991,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2130253622","doi":"10.1175/jhm-d-11-0126.1","title":"Rationale for Monitoring Discharge on the Ground","year":2012,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":95,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada","funders":"Centrum fÖr Personcentrerad Vård; Woods Hole Oceanographic Institution","keywords":"Environmental science; Water cycle; Component (thermodynamics); Climate change; Resource (disambiguation); Environmental resource management; Remote sensing; Computer science; Geology; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.02732908634701236,"gpt":0.2722017437129422,"spread":0.2448726573659298,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007227195,0.00006108118,0.00009484909,0.00003579685,0.00009853449,0.00001197203,0.0001679413,0.0000244151,0.0007729594],"category_scores_gemma":[0.00004186359,0.00003513854,0.00007069053,0.00006025377,0.00004283023,0.0002262464,0.00003805809,0.00009477345,0.0000774282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004528991,"about_ca_system_score_gemma":0.000003043431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008213963,"about_ca_topic_score_gemma":0.000003374167,"domain_scores_codex":[0.9993579,0.00004769195,0.0001716655,0.00005331823,0.000178818,0.0001906049],"domain_scores_gemma":[0.9995257,0.0001757472,0.0001583435,0.00008467231,0.00000585354,0.00004967345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004376627,0.001193787,0.8230129,0.00002384501,0.0004905788,0.00001145655,0.002119602,0.005345692,0.03500723,0.03721824,0.07174338,0.02339565],"study_design_scores_gemma":[0.001188313,0.001425959,0.7885921,0.00001177688,0.0001254682,0.00006239704,0.0004261561,0.0006037409,0.004343849,0.009445645,0.193565,0.0002095953],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921346,0.00008662362,0.001352583,0.002747284,0.001011645,0.0001670556,8.27949e-7,0.000003051409,0.002496293],"genre_scores_gemma":[0.9969741,0.00003008641,0.001859215,0.0002471023,0.0003971943,0.000009464779,5.161244e-7,0.000004895553,0.0004775025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1218216,"threshold_uncertainty_score":0.8463364,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2055091998","doi":"10.1175/2008jhm874.1","title":"Comparing Simulated and Measured Sensible and Latent Heat Fluxes over Snow under a Pine Canopy to Improve an Energy Balance Snowmelt Model","year":2008,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":94,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Snowmelt; Eddy covariance; Latent heat; Environmental science; Sensible heat; Snow; Energy balance; Atmospheric sciences; Climatology; Meteorology; Geology; Ecosystem; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.03394056213506334,"gpt":0.2294335006569326,"spread":0.1954929385218693,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001902672,0.0001384678,0.0004005894,0.00008299081,0.0002016486,0.0000212986,0.00008724582,0.00006653692,0.00006534558],"category_scores_gemma":[0.00004168157,0.0001078515,0.00003868617,0.0001845678,0.00009368374,0.0001857587,0.00002490823,0.0001293034,0.000001217135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009723092,"about_ca_system_score_gemma":0.00004909006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002562843,"about_ca_topic_score_gemma":0.004128349,"domain_scores_codex":[0.9989868,0.00005549673,0.000323813,0.0001884457,0.0001790597,0.0002664071],"domain_scores_gemma":[0.9993512,0.0001031673,0.0001054158,0.0001069553,0.0001051626,0.0002280966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001772805,0.00002931189,0.488364,0.000004711032,0.00009959087,0.00004930211,0.0002949394,0.5065525,0.003366153,0.0000264569,0.0003079439,0.0007278604],"study_design_scores_gemma":[0.0006016697,0.0005887566,0.5100668,0.000006600074,0.00002521489,0.0002410408,0.00003078093,0.4876443,0.00006501653,0.0002960906,0.0003371684,0.00009654641],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962541,0.001702635,0.001064201,0.0006301436,0.0002111422,0.00005295294,0.00001075495,0.000009939007,0.00006408869],"genre_scores_gemma":[0.9965225,0.0006237738,0.001678363,0.0009930435,0.00007893715,2.256843e-7,0.000005583476,0.000004937235,0.00009257407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02170283,"threshold_uncertainty_score":0.4398059,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2581519219","doi":"10.1175/jhm-d-16-0246.1","title":"Comparison of Methods to Estimate Snow Water Equivalent at the Mountain Range Scale: A Case Study of the California Sierra Nevada","year":2017,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":90,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"National Aeronautics and Space Administration","keywords":"Snow; Water equivalent; Environmental science; Precipitation; Range (aeronautics); Weather Research and Forecasting Model; Climatology; Physical geography; Meteorology; Geology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.0695261611205155,"gpt":0.3877179764956609,"spread":0.3181918153751454,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001626527,0.0001235721,0.0005219062,0.00003997047,0.0006679993,0.00002540596,0.0006196581,0.00004799641,0.0006542284],"category_scores_gemma":[0.0002852266,0.0000533093,0.0001388827,0.0001080388,0.0002345132,0.00007462822,0.0001773995,0.0002050055,0.000008506802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001377347,"about_ca_system_score_gemma":0.00002536936,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005756726,"about_ca_topic_score_gemma":0.02814985,"domain_scores_codex":[0.9982901,0.0004048744,0.0006689821,0.0001238015,0.0002588589,0.0002533911],"domain_scores_gemma":[0.9981772,0.0004403737,0.000703127,0.0004658562,0.0001324473,0.00008100433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001607575,0.0001219696,0.9680129,0.00001095993,0.0001554848,0.00007287497,0.004668348,0.01783432,0.0004671067,0.000001033663,0.0007630772,0.007731112],"study_design_scores_gemma":[0.0009528233,0.001980606,0.9774853,0.00001721904,0.0002862185,0.001055807,0.005549453,0.006249137,0.0008509047,0.00009923013,0.005366423,0.000106873],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996034,0.000480613,0.0002491384,0.002184878,0.0006654781,0.0002590866,0.00003210078,0.000002015959,0.00009267931],"genre_scores_gemma":[0.9978229,0.00001321098,0.001885351,0.0001163887,0.00005902501,0.000001485959,9.743078e-7,0.000003635143,0.0000969603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02239312,"threshold_uncertainty_score":0.9895839,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2046411634","doi":"10.1175/2007jhm819.1","title":"A Land Data Assimilation System for Soil Moisture and Temperature: An Information Content Study","year":2007,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":88,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Data assimilation; Environmental science; Water content; Geostationary Operational Environmental Satellite; Satellite; Meteorology; Initialization; Remote sensing; Land cover; Numerical weather prediction; Land use; Computer science; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.02952350406799504,"gpt":0.264762506200555,"spread":0.2352390021325599,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001612911,0.00009326477,0.0002123555,0.00009527138,0.0001040939,0.00003939475,0.0001758439,0.0001051357,0.000003015435],"category_scores_gemma":[0.00009277789,0.00006469909,0.00002638996,0.00009875886,0.00005102605,0.0007688224,0.00007877419,0.0001645691,0.000002549144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006936061,"about_ca_system_score_gemma":0.00001019224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002119339,"about_ca_topic_score_gemma":0.002381223,"domain_scores_codex":[0.9990286,0.00006684592,0.0004198513,0.0001194245,0.0002088124,0.00015642],"domain_scores_gemma":[0.9992386,0.00008257657,0.0003416002,0.0002059805,0.00003847384,0.00009283025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00145017,0.0004218706,0.8553116,0.000068329,0.0002631623,0.0001523383,0.004990066,0.001583198,0.03627086,0.00002375081,0.002276169,0.09718847],"study_design_scores_gemma":[0.001578366,0.001348836,0.9905563,0.00001157096,0.00009910513,0.0008670934,0.001752319,0.00155728,0.0002853333,0.00003720189,0.001811044,0.00009555667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974782,0.00006846898,0.001102821,0.0002217725,0.0004457836,0.0002273865,0.000003700338,0.000009468804,0.0004424024],"genre_scores_gemma":[0.9983715,0.000005183088,0.00125394,0.0001817115,0.0001525817,2.435904e-7,0.00001692489,0.000005732083,0.00001212877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1352447,"threshold_uncertainty_score":0.2638352,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2588546114","doi":"10.1175/jhm-d-16-0155.1","title":"A Global Dynamic Long-Term Inundation Extent Dataset at High Spatial Resolution Derived through Downscaling of Satellite Observations","year":2017,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":88,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Centre National d’Etudes Spatiales; National Aeronautics and Space Administration","keywords":"Downscaling; Satellite; Environmental science; Remote sensing; Synthetic aperture radar; Smoothing; Image resolution; Term (time); Meteorology; Precipitation; Computer science; Geology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.02454447501329192,"gpt":0.2976320497842419,"spread":0.27308757477095,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004188473,0.0001303898,0.0002734956,0.00004851044,0.0002740914,0.00003902752,0.0005008634,0.00008136671,0.00053424],"category_scores_gemma":[0.00006635464,0.0001130242,0.00008754587,0.00008252058,0.0002606582,0.0006811214,0.00039297,0.0001034186,0.00003200708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003212602,"about_ca_system_score_gemma":0.00001673792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001654677,"about_ca_topic_score_gemma":0.00709088,"domain_scores_codex":[0.9985641,0.0001034436,0.0005532193,0.0002010267,0.0003492222,0.000228953],"domain_scores_gemma":[0.9982914,0.00003039487,0.001158041,0.0004331112,0.00002453716,0.00006249762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004151317,0.0003298648,0.9317864,0.00003572115,0.0002241735,0.0001071527,0.0001372762,0.01124452,0.02977707,0.0002377079,0.0009468985,0.02475811],"study_design_scores_gemma":[0.0008722333,0.0003788511,0.9933138,0.00001956788,0.0001310915,0.00004980735,0.000007629943,0.002235169,0.0003508597,0.001486277,0.001052279,0.0001024179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839748,0.0001199916,0.01393611,0.0009575422,0.0005527319,0.0001569354,0.0001116286,0.000005539104,0.0001847744],"genre_scores_gemma":[0.9914411,0.0006328509,0.007464032,0.00008913922,0.0000469641,0.000002237957,0.0002852845,0.000005909672,0.00003250058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06152744,"threshold_uncertainty_score":0.5849553,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2958396891","doi":"10.1175/jhm-d-19-0042.1","title":"Evaluation and Bias Correction of S2S Precipitation for Hydrological Extremes","year":2019,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":87,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Environment and Climate Change Canada; Wuhan University; Norges Forskningsråd; State Key Laboratory of Water Resources and Hydropower Engineering Science; National Natural Science Foundation of China","keywords":"Precipitation; Quantitative precipitation forecast; Environmental science; Climatology; Streamflow; Range (aeronautics); Meteorology; Scale (ratio); Reliability (semiconductor); Drainage basin; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.03209120867077563,"gpt":0.2743519389888198,"spread":0.2422607303180441,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002210753,0.0000782866,0.0002435923,0.0001101677,0.00004537786,0.0000036769,0.00008564724,0.00008515732,0.0005274685],"category_scores_gemma":[0.0003557499,0.00005917775,0.00006256076,0.00008773509,0.0001422865,0.000178886,0.00005966583,0.00008539962,0.0000181206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004263422,"about_ca_system_score_gemma":0.000006302859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001040285,"about_ca_topic_score_gemma":0.00001433132,"domain_scores_codex":[0.9989629,0.000202832,0.0003342006,0.0001353442,0.0002328684,0.0001318767],"domain_scores_gemma":[0.9992026,0.0002517014,0.0003944337,0.00007380614,0.00004964603,0.00002778121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001534385,0.0004114769,0.771414,0.00005742602,0.0005869386,0.000006093427,0.00204548,0.0680063,0.0617534,0.0002626033,0.006623239,0.08729864],"study_design_scores_gemma":[0.005594332,0.01184816,0.780069,0.00003030989,0.0009414376,0.0001775557,0.0003265684,0.1394549,0.004879714,0.0432664,0.01308703,0.0003245887],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995689,0.0001388629,0.0008333423,0.0005510563,0.00074613,0.0002951856,6.914819e-7,0.000004250703,0.001741443],"genre_scores_gemma":[0.9990086,0.00006437023,0.0005966519,0.0001095996,0.00002853125,0.000009192531,0.000001552096,0.000004371814,0.0001771454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08697405,"threshold_uncertainty_score":0.5775411,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2080805949","doi":"10.1175/2010jhm1191.1","title":"Intra- to Multidecadal Variations of Snowpack and Streamflow Records in the Andes of Chile and Argentina between 30° and 37°S","year":2010,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":81,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Snowpack; Streamflow; Climatology; Environmental science; Pacific decadal oscillation; Snow; El Niño Southern Oscillation; Drainage basin; Geology; Geography; Meteorology","retraction":null,"screen_n_in":null,"score":{"opus":0.01236270840691047,"gpt":0.2513654479447437,"spread":0.2390027395378333,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001115225,0.00007060726,0.0002511357,0.00007972836,0.00003595162,0.000007827386,0.0001013791,0.00007630573,0.0002235869],"category_scores_gemma":[0.0002624125,0.00004925755,0.00002432429,0.0001241604,0.0002371436,0.0001137456,0.00009244208,0.0002065017,7.011952e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007911462,"about_ca_system_score_gemma":0.000008793158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002431382,"about_ca_topic_score_gemma":0.0004098395,"domain_scores_codex":[0.9991795,0.0001017591,0.0003689225,0.0001138021,0.0001143053,0.0001217255],"domain_scores_gemma":[0.9992221,0.0003901181,0.0001978751,0.0001099142,0.00001266966,0.0000673186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005288404,0.0001649821,0.9081506,0.00002259191,0.00003051458,0.000004612206,0.002670031,0.0001859222,0.08224888,0.0002204388,0.00008618195,0.006162367],"study_design_scores_gemma":[0.0005702088,0.0006024919,0.9914184,0.000009088984,0.00004395247,0.00009344698,0.00008430863,0.0008102795,0.001124748,0.00482641,0.0003568055,0.00005987913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983273,0.00002082118,0.0001472676,0.001117065,0.00006061027,0.0001035192,0.00002054257,0.000001030029,0.0002018815],"genre_scores_gemma":[0.9965501,0.00008773421,0.003260129,0.00006697873,0.00002537481,0.000001303183,7.368203e-7,0.000003361007,0.000004266799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08326779,"threshold_uncertainty_score":0.2448119,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2169101462","doi":"10.1175/2008jhm977.1","title":"An Investigation of the Thermal and Energy Balance Regimes of Great Slave and Great Bear Lakes","year":2008,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":80,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada; University of Toronto; McMaster University","funders":"National Oceanic and Atmospheric Administration","keywords":"Outflow; Environmental science; Shelf ice; Hydrology (agriculture); Water balance; Period (music); Structural basin; Watershed; Geology; Climatology; Oceanography; Cryosphere","retraction":null,"screen_n_in":null,"score":{"opus":0.008744222602112783,"gpt":0.1881706187876845,"spread":0.1794263961855717,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000216003,0.00007309712,0.000227188,0.00007157304,0.00007730859,0.000003713594,0.000126831,0.00006264843,0.00007087392],"category_scores_gemma":[0.00003101299,0.000043825,0.00003869655,0.00009102483,0.0006007468,0.000173514,0.00001016344,0.0001020873,2.296769e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001574609,"about_ca_system_score_gemma":0.00004473818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002911062,"about_ca_topic_score_gemma":0.0001086521,"domain_scores_codex":[0.9992808,0.0001359241,0.0002601067,0.00007842806,0.000136855,0.0001078709],"domain_scores_gemma":[0.9993107,0.0001337864,0.0003424399,0.00009445646,0.0000511221,0.00006747113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006211931,0.000004941682,0.9947993,0.000009857456,0.00002948012,0.00001432506,0.0007292858,0.0002669792,0.001480235,0.0000780182,0.00001923887,0.002506215],"study_design_scores_gemma":[0.0002504349,0.0007428169,0.9913509,0.00001681016,0.00003671052,0.001351157,0.00009044234,0.004047928,0.000548196,0.001411173,0.0001030802,0.0000503804],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987353,0.0004875744,0.00002642621,0.000389547,0.0001010117,0.00001734843,0.000008832498,0.000001667752,0.0002323049],"genre_scores_gemma":[0.9985622,0.0005311191,0.000614549,0.0001634483,0.0000479614,5.800012e-8,0.00000253277,0.000002036843,0.00007615521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003780949,"threshold_uncertainty_score":0.2213477,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2163209546","doi":"10.1175/jhm-d-14-0060.1","title":"Regional Frequency Analysis at Ungauged Sites with the Generalized Additive Model","year":2014,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":79,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Generalized additive model; Canonical correlation; Generalized linear model; Quantile; Nonlinear system; Variable (mathematics); Linear model; Regression; Additive model; Econometrics; Regression analysis; Mathematics; Statistics; Model selection; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.009848209271460436,"gpt":0.2203608607496387,"spread":0.2105126514781783,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001015738,0.00018221,0.000543705,0.0002298113,0.0002727793,0.00001206643,0.0004701812,0.0001369713,0.002746679],"category_scores_gemma":[0.0000705686,0.0001009928,0.0003684608,0.0007051773,0.0006204416,0.0001844487,0.0001048208,0.0003231702,0.0001286735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001144585,"about_ca_system_score_gemma":0.00001871753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007612335,"about_ca_topic_score_gemma":0.001324262,"domain_scores_codex":[0.9981192,0.0004937811,0.0004032645,0.0002530026,0.0004068798,0.0003239056],"domain_scores_gemma":[0.9986343,0.0002970314,0.0005805261,0.0003154351,0.00003887248,0.0001338833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008009702,0.0002194352,0.2263057,0.000002436598,0.004844629,0.0001223773,0.001079876,0.7091131,0.02875644,0.001554144,0.02665058,0.0005502999],"study_design_scores_gemma":[0.004586686,0.003158528,0.1653759,0.000007545204,0.01233347,0.001524033,0.00009005031,0.7419672,0.002281365,0.04280466,0.02487024,0.001000258],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834883,0.00009567087,0.009337599,0.004592179,0.00002841006,0.00004800676,0.00000501135,0.00001259928,0.002392226],"genre_scores_gemma":[0.9927237,0.00003895648,0.003916938,0.00235648,0.00007585119,0.000005260338,0.00001148091,0.00001418819,0.0008571438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06092978,"threshold_uncertainty_score":0.998165,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4360611214","doi":"10.1175/jhm-d-22-0194.1","title":"Future Increases in North American Extreme Precipitation in CMIP6 Downscaled with LOCA","year":2023,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Strategic Environmental Research and Development Program; California Energy Commission","keywords":"Precipitation; Environmental science; Climatology; Anomaly (physics); Meteorology; Geography; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.01381869934475873,"gpt":0.2308495442138557,"spread":0.217030844869097,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006488457,0.0001031068,0.0003023048,0.0003000741,0.00002463046,0.000007994262,0.0001798553,0.00004657214,0.000239686],"category_scores_gemma":[0.00008710344,0.00007855422,0.00004180975,0.001496741,0.0001911552,0.0002257129,0.00006340875,0.000250022,0.00004707711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001476614,"about_ca_system_score_gemma":0.00002157114,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008063308,"about_ca_topic_score_gemma":0.02715302,"domain_scores_codex":[0.9987398,0.0001976855,0.0003971176,0.0001717139,0.0002243827,0.0002693413],"domain_scores_gemma":[0.9993637,0.0001738577,0.0002413899,0.0001294441,0.00001109191,0.00008049841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003477562,0.00017812,0.9548671,0.000006018817,0.00001001343,0.0001740566,0.0005986586,0.03919907,0.00124297,0.000009183132,0.0001534691,0.003213604],"study_design_scores_gemma":[0.0007838306,0.0008040544,0.9935222,0.000008470085,0.00001118529,0.0001036496,0.0002457392,0.003524673,0.00002065863,0.0004068659,0.000477106,0.00009156432],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985987,0.00001740603,0.00003838579,0.0009387669,0.00007784153,0.0001036826,0.000002910665,0.0000106336,0.0002116875],"genre_scores_gemma":[0.9989957,0.0001200588,0.0006405666,0.0001557122,0.00004537448,0.00000670979,0.000005076991,0.000008595137,0.00002216632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03865512,"threshold_uncertainty_score":0.9905989,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2109957029","doi":"10.1175/jhm-d-11-0151.1","title":"Predicting the Net Basin Supply to the Great Lakes with a Hydrometeorological Model","year":2012,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":76,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Impact; Environment and Climate Change Canada","funders":"","keywords":"Hydrometeorology; Precipitation; Environmental science; Forcing (mathematics); Surface runoff; Snowmelt; Evaporation; Snow; Streamflow; Drainage basin; Hydrology (agriculture); Climatology; Flux (metallurgy); Structural basin; Meteorology; Atmospheric sciences; Geology; Geomorphology","retraction":null,"screen_n_in":null,"score":{"opus":0.01353635682699592,"gpt":0.2207170333685376,"spread":0.2071806765415417,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00212015,0.0002159868,0.0003618259,0.00009384764,0.0004323515,0.00002230119,0.0007192769,0.00009939275,0.0006670441],"category_scores_gemma":[0.0001447321,0.00009109699,0.0001128372,0.0003431939,0.0005460834,0.0003187097,0.0004332939,0.000476573,0.0001536022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006001677,"about_ca_system_score_gemma":0.000008496224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004665872,"about_ca_topic_score_gemma":0.0001149528,"domain_scores_codex":[0.9980105,0.000320233,0.0004018741,0.0001951828,0.0003876289,0.0006845898],"domain_scores_gemma":[0.9989537,0.0002837587,0.0002716195,0.000309189,0.00001606168,0.0001656857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005343368,0.0001810953,0.8430344,0.00000424731,0.0003422967,0.00005801715,0.003715253,0.122365,0.0007779525,0.0001967192,0.02748729,0.001303351],"study_design_scores_gemma":[0.002720089,0.007538697,0.7742124,0.00003475711,0.001195737,0.00418383,0.0009583202,0.02727206,0.0006397635,0.004861025,0.1755443,0.0008390335],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9688433,0.0001726358,0.001367271,0.0253526,0.0002793206,0.0002447093,0.000003287587,0.00001799817,0.003718865],"genre_scores_gemma":[0.9921546,0.00004551454,0.001145487,0.005779723,0.0002027728,0.00002449474,7.513967e-7,0.0000143724,0.0006322751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.148057,"threshold_uncertainty_score":0.7303665,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2153237487","doi":"10.1175/jhm-d-13-0178.1","title":"Physically Based Mountain Hydrological Modeling Using Reanalysis Data in Patagonia","year":2014,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":75,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"Directorate for Mathematical and Physical Sciences; Inter-American Institute for Global Change Research; Natural Sciences and Engineering Research Council of Canada; Universidad de Chile; Canada Research Chairs","keywords":"Environmental science; Snowmelt; Evapotranspiration; Snow; Canopy interception; Interception; Precipitation; Climatology; Hydrological modelling; Forcing (mathematics); Wind speed; Water balance; Hydrology (agriculture); Meteorology; Geology; Soil water; Throughfall","retraction":null,"screen_n_in":null,"score":{"opus":0.03440757461842717,"gpt":0.2705386521671805,"spread":0.2361310775487534,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002547468,0.0001770982,0.0005522151,0.0002422587,0.0001053313,0.00001345694,0.0008700701,0.0001238347,0.0002639923],"category_scores_gemma":[0.0002609517,0.0001371708,0.0000989612,0.0003516476,0.0002351766,0.0003445051,0.0006293801,0.0003727835,0.00004674791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009689506,"about_ca_system_score_gemma":0.00001056312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002244355,"about_ca_topic_score_gemma":0.0001481792,"domain_scores_codex":[0.9978281,0.000462069,0.0006190243,0.0003706662,0.0003132069,0.0004068805],"domain_scores_gemma":[0.998889,0.0001653955,0.0003087603,0.0005395022,0.00001293454,0.00008439383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000162633,0.0002147488,0.1044283,0.000005656197,0.0001015227,0.0001067251,0.00007046819,0.8891258,0.0042113,0.00005075956,0.0001471234,0.001375022],"study_design_scores_gemma":[0.0007600154,0.000350589,0.005155088,0.000006539145,0.0001439716,0.00003331686,0.00001434492,0.9886879,0.00004092824,0.003706902,0.0009608861,0.000139557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9567981,0.00004125556,0.04079745,0.001557489,0.0001030268,0.00006159653,0.000002227775,0.00001000309,0.0006288156],"genre_scores_gemma":[0.9925896,0.0000231386,0.006214196,0.001062316,0.0000778831,0.000001362311,0.000007176117,0.00001099821,0.00001332653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09956209,"threshold_uncertainty_score":0.5593665,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2013713940","doi":"10.1175/2010jhm1297.1","title":"Regional Extreme Monthly Precipitation Simulated by NARCCAP RCMs","year":2010,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":74,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal; Ouranos","funders":"Lawrence Livermore National Laboratory; National Oceanic and Atmospheric Administration; University of Washington; U.S. Department of Energy; Department for Environment, Food and Rural Affairs, UK Government; Office of Research and Development; National Science Foundation","keywords":"Precipitation; Replicate; Climatology; Environmental science; Anomaly (physics); Storm; General Circulation Model; Climate model; Hydrometeorology; Structural basin; Climate change; Winter storm; Meteorology; Geology; Geography; Oceanography","retraction":null,"screen_n_in":null,"score":{"opus":0.01912307478157736,"gpt":0.2419087841979483,"spread":0.2227857094163709,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008235206,0.0001125171,0.0002230779,0.0000761066,0.00007202733,0.00001442825,0.0002725137,0.0001720753,0.003640507],"category_scores_gemma":[0.0001789522,0.00009447087,0.0001029876,0.0001505685,0.0002258223,0.0003173065,0.00006442209,0.0004355246,0.0001032351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005563382,"about_ca_system_score_gemma":0.00001634461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001022113,"about_ca_topic_score_gemma":0.00008905854,"domain_scores_codex":[0.9987277,0.0001035321,0.0004506915,0.000174182,0.0002933226,0.0002505346],"domain_scores_gemma":[0.9991241,0.0001998814,0.0003232536,0.0001810002,0.00003077305,0.0001410531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002519393,0.0004213326,0.01713683,0.000005500987,0.00004952155,0.00002761274,0.00070813,0.03101472,0.9281599,0.0001691299,0.02044068,0.001614726],"study_design_scores_gemma":[0.008091935,0.005711901,0.1471087,0.00003958098,0.0003312026,0.001838867,0.0001900655,0.2230731,0.01011132,0.1142427,0.4878833,0.00137734],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954057,0.00003779886,0.0002316591,0.001862013,0.0004841877,0.00008136975,0.000006583472,0.00001178393,0.001878947],"genre_scores_gemma":[0.997523,0.00001704627,0.001714714,0.0003933145,0.00006968601,0.000001184705,0.000007568225,0.00001076002,0.0002627439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9180486,"threshold_uncertainty_score":0.9972703,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2566754188","doi":"10.1175/jhm-d-16-0088.1","title":"The Use of Reanalyses and Gridded Observations as Weather Input Data for a Hydrological Model: Comparison of Performances of Simulated River Flows Based on the Density of Weather Stations","year":2016,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":73,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Environmental science; Precipitation; Climatology; Forcing (mathematics); Weather station; Meteorology; Weather Research and Forecasting Model; Watershed; Automatic weather station; Streamflow; Drainage basin; Geology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.1326022594808869,"gpt":0.3111578965434086,"spread":0.1785556370625218,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008982485,0.0001023224,0.0004039863,0.00008268048,0.0001348069,0.000002973741,0.0003930369,0.0000681673,0.00006118337],"category_scores_gemma":[0.0005183569,0.00004509856,0.00008315217,0.0001384552,0.001014099,0.0001892607,0.0001998356,0.00009179502,9.529223e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001287814,"about_ca_system_score_gemma":0.00001375795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006810389,"about_ca_topic_score_gemma":0.0001017873,"domain_scores_codex":[0.9986986,0.0002070014,0.0006024642,0.000138366,0.0002102619,0.0001433086],"domain_scores_gemma":[0.9970305,0.001755575,0.0007561065,0.0003664113,0.00006572282,0.0000256903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001427703,0.0004373387,0.4426652,0.00001982695,0.0006000139,0.000001445463,0.0009122672,0.5299659,0.02152415,0.0004920359,0.001278432,0.0006756766],"study_design_scores_gemma":[0.001199759,0.001868764,0.09683483,0.00002932627,0.0004242132,0.000003028694,0.00009007657,0.8905939,0.003183232,0.004784535,0.0009028623,0.00008546408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924802,0.00003505644,0.004508958,0.002660506,0.00003404513,0.0001890663,0.00004958266,0.000002380276,0.00004024356],"genre_scores_gemma":[0.9976634,0.000109899,0.002022041,0.0001410864,0.000005840876,0.000002658436,0.000003060128,0.000005141321,0.00004688201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.360628,"threshold_uncertainty_score":0.373649,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2160977151","doi":"10.1175/jhm430.1","title":"Transport of Atmospheric Moisture during Three Extreme Rainfall Events over the Mackenzie River Basin","year":2005,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":73,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"HYSPLIT; Structural basin; Climatology; Cyclogenesis; Moisture; Geology; Environmental science; Lagrangian; Cyclone (programming language); Meteorology; Geography; Aerosol; Geomorphology","retraction":null,"screen_n_in":null,"score":{"opus":0.01346357413420354,"gpt":0.2183978600154673,"spread":0.2049342858812638,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007419739,0.0001449372,0.000340168,0.0000194622,0.00007852956,0.000003404424,0.0004420859,0.0001208571,0.004203131],"category_scores_gemma":[0.00003627258,0.00009629144,0.0002286326,0.0001922837,0.0002903813,0.000250843,0.00008223102,0.0003061408,0.00002670989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001290376,"about_ca_system_score_gemma":0.00001751415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002546683,"about_ca_topic_score_gemma":0.0006121042,"domain_scores_codex":[0.998511,0.00009494471,0.0005819807,0.0001677831,0.0003643092,0.0002799754],"domain_scores_gemma":[0.9991356,0.00009000346,0.0004014176,0.0002678173,0.00001718056,0.00008800426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004707914,0.0005148064,0.9039218,0.00002823855,0.0001739444,0.00006245391,0.001829269,0.05983163,0.03013879,0.00008471213,0.0005270201,0.00241658],"study_design_scores_gemma":[0.001064124,0.0002100309,0.9876928,0.00001199542,0.00008606787,0.0002344933,0.00001549672,0.002015595,0.000363574,0.002775111,0.005418292,0.0001123879],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973087,0.0001219458,0.0004217597,0.00115701,0.0001603953,0.0001168558,0.00000893839,0.000006165324,0.0006981965],"genre_scores_gemma":[0.9969157,0.00008267882,0.0024387,0.0003233688,0.00008485034,0.000001871308,0.000001105291,0.00001280281,0.0001389087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08377107,"threshold_uncertainty_score":0.9967071,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2110733311","doi":"10.1175/jhm-d-11-0135.1","title":"Problems Closing the Energy Balance over a Homogeneous Snow Cover during Midwinter","year":2011,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":71,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"Canada Research Chairs; Aberystwyth University; Canadian Foundation for Climate and Atmospheric Sciences","keywords":"Snowpack; Energy balance; Sensible heat; Snow; Environmental science; Latent heat; Atmospheric sciences; Snowmelt; Longwave; Shortwave; Shortwave radiation; Earth's energy budget; Energy flux; Meteorology; Climatology; Radiative transfer; Radiation; Physics; Geology; Thermodynamics","retraction":null,"screen_n_in":null,"score":{"opus":0.01949523178755281,"gpt":0.1943791251261064,"spread":0.1748838933385536,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002298821,0.0001081489,0.0002239177,0.00004603796,0.0001920086,0.00001982029,0.0002741979,0.00005432019,0.003700122],"category_scores_gemma":[0.00005354364,0.00006418223,0.0001229191,0.0001832351,0.0001156077,0.0001416343,0.00002268879,0.0001692014,0.00002603323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006882694,"about_ca_system_score_gemma":0.00002477215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006563966,"about_ca_topic_score_gemma":0.0007297215,"domain_scores_codex":[0.9990363,0.00007607455,0.000349184,0.0001121673,0.0001620337,0.0002642679],"domain_scores_gemma":[0.9993032,0.0001454176,0.0002915046,0.0001365027,0.00006037633,0.00006306241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003120492,0.00008328041,0.9787519,0.00001711181,0.0004322508,0.0003271306,0.002213922,0.006014714,0.0009778504,0.0001358347,0.004042109,0.006691846],"study_design_scores_gemma":[0.0004714302,0.0005039783,0.9662828,0.00002172656,0.00005512096,0.001024685,0.00009089462,0.001843706,0.0002394199,0.001174292,0.02816861,0.0001233706],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935487,0.00308779,0.0003105719,0.0003090139,0.0008321776,0.00004002063,0.000007188701,0.000007133694,0.001857415],"genre_scores_gemma":[0.9977697,0.0005003721,0.0004875232,0.0006255097,0.0002255362,5.733893e-7,0.000001479296,0.000004066347,0.0003853022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0241265,"threshold_uncertainty_score":0.9972106,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3095201267","doi":"10.1175/jhm-d-20-0100.1","title":"Large-Scale Analysis of Global Gridded Precipitation and Temperature Datasets for Climate Change Impact Studies","year":2020,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":69,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Precipitation; Environmental science; Satellite; Climatology; Scale (ratio); Climate change; Computer science; Climate Forecast System; Gauge (firearms); Quantitative precipitation estimation; Meteorology; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.04765562577156633,"gpt":0.3153899252982879,"spread":0.2677342995267215,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007913833,0.0001032353,0.0005386773,0.0002509992,0.000079058,0.0000199291,0.0001269193,0.00006363041,0.0001710538],"category_scores_gemma":[0.0002520817,0.00007210246,0.0002256013,0.0008036941,0.00004424395,0.0003159728,0.00001003998,0.00007870195,0.000002409787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008018761,"about_ca_system_score_gemma":0.00002822353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009093427,"about_ca_topic_score_gemma":0.003758493,"domain_scores_codex":[0.9989221,0.0001287614,0.000412327,0.0001362615,0.000197275,0.000203236],"domain_scores_gemma":[0.9990313,0.0001399418,0.0004077316,0.00006731676,0.0001948396,0.0001588852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003625391,0.00002175664,0.9897976,0.00005756223,0.002853176,0.000005247155,0.001764254,0.002266816,0.0005945686,0.00001183629,0.0008896137,0.001375013],"study_design_scores_gemma":[0.0006948112,0.001100795,0.9787021,0.00001071851,0.002143617,0.000007204087,0.0007482668,0.01600293,0.00003643515,0.0002667205,0.0001964687,0.00008997004],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916081,0.003916644,0.00007639548,0.001418889,0.0001163097,0.00009794882,0.002745444,0.000003694206,0.00001650424],"genre_scores_gemma":[0.997497,0.0006862603,0.0009246818,0.0003853403,0.0001094282,7.620183e-7,0.000394567,0.000001502087,5.208398e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01373611,"threshold_uncertainty_score":0.2940253,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2120533299","doi":"10.1175/2008jhm883.1","title":"NASA Cold Land Processes Experiment (CLPX 2002/03): Airborne Remote Sensing","year":2008,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":68,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"U.S. Army Corps of Engineers; National Oceanic and Atmospheric Administration; Japan Science and Technology Corporation; National Aeronautics and Space Administration; California Institute of Technology; Jet Propulsion Laboratory","keywords":"Remote sensing; Environmental science; Lidar; Scatterometer; Satellite; Multispectral image; Synthetic aperture radar; Radar; Hyperspectral imaging; Polarimetry; Special sensor microwave/imager; Radiometer; Meteorology; Microwave; Geology; Computer science; Wind speed; Geography; Brightness temperature; Physics; Optics","retraction":null,"screen_n_in":null,"score":{"opus":0.0202843448955346,"gpt":0.2390984170780634,"spread":0.2188140721825288,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001995307,0.0001098362,0.0002590108,0.0001365074,0.0001268988,0.00001673222,0.0001322097,0.00003846864,0.0001591542],"category_scores_gemma":[0.00001651606,0.00008870108,0.00005912222,0.0002112203,0.0000768754,0.0003445166,0.00001847931,0.0001670336,0.0001275534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001594999,"about_ca_system_score_gemma":0.0001445056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007442689,"about_ca_topic_score_gemma":0.00000915408,"domain_scores_codex":[0.9990729,0.00005104304,0.000331943,0.0001223968,0.0001939788,0.0002277313],"domain_scores_gemma":[0.9993272,0.00005392012,0.0002982442,0.0001024158,0.0001203794,0.00009783039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001769567,0.001473868,0.1560673,0.0001390395,0.001715499,0.00353816,0.01346222,0.02771517,0.5906773,0.0007111436,0.1427651,0.05996558],"study_design_scores_gemma":[0.0132914,0.01119508,0.04414386,0.0003774077,0.0004724883,0.00980009,0.002435585,0.03619845,0.4149548,0.0141418,0.4502596,0.002729463],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939268,0.0003463536,0.003735814,0.0005783289,0.0003146281,0.00005606769,0.000004542709,0.00000759031,0.001029827],"genre_scores_gemma":[0.9963467,0.00004563602,0.002810118,0.0001742312,0.0003523356,1.663114e-7,0.00001070874,0.000006745507,0.0002533474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3074945,"threshold_uncertainty_score":0.3617125,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2136184828","doi":"10.1175/jhm-d-12-0170.1","title":"The Importance of Spring and Autumn Atmospheric Conditions for the Evaporation Regime of Lake Superior","year":2013,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":67,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Evaporation; Environmental science; Latent heat; Spring (device); Climatology; Atmospheric sciences; Potential evaporation; Lead (geology); Water cycle; Hydrology (agriculture); Geology; Meteorology; Geography; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.007731268665842427,"gpt":0.2136349681425272,"spread":0.2059036994766848,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004932781,0.00005455803,0.0001648391,0.00001217879,0.0001484892,0.00001208678,0.0001450223,0.00003659381,0.000284423],"category_scores_gemma":[0.0001357172,0.00002799783,0.00006220789,0.00007994268,0.0002802625,0.0001546212,0.000007579246,0.00009699781,0.00000182781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001850958,"about_ca_system_score_gemma":0.00004785756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001690441,"about_ca_topic_score_gemma":0.001046739,"domain_scores_codex":[0.9993253,0.00004318955,0.0003550036,0.00005314653,0.0001035148,0.0001198749],"domain_scores_gemma":[0.9985593,0.0007557153,0.0004428587,0.00009279775,0.0001152573,0.00003408482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000080073,0.00001452465,0.9887273,0.00002568754,0.0001268347,0.000002730611,0.000284239,0.001270304,0.0007738016,0.000825312,0.0002525752,0.00761662],"study_design_scores_gemma":[0.0003122602,0.0006231653,0.9509885,0.00001003623,0.00007164008,0.0001625956,0.0004622274,0.03914786,0.00003749857,0.00630736,0.001830625,0.00004628583],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961036,0.000537731,0.0007086447,0.002223441,0.0002067867,0.0001305354,0.00001160244,0.000001490173,0.00007613206],"genre_scores_gemma":[0.9980438,0.0003182419,0.001426712,0.0001000765,0.00004741511,0.000001069509,0.000002685925,0.000001925614,0.0000580097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03787756,"threshold_uncertainty_score":0.3114232,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}