{"meta":{"query_hash":"2627bd752737","filters":{"venue":"Meteorological Applications"},"cohort_total":46,"direct_labels_cover":0,"predictions_cover":46,"exported":46,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/2627bd752737","api":"https://metacan.xera.ac/api/v1/cohort?venue=Meteorological+Applications"},"results":[{"id":"W1497569944","doi":"10.1002/met.1404","title":"A new index for the verification of accuracy and timeliness of weather warnings","year":2013,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wave Control Systems (Canada); Environment and Climate Change Canada","funders":"","keywords":"Index (typography); Computer science; Warning system; Set (abstract data type); Meteorology; Data mining; Geography; Telecommunications","score_opus":0.011979844472527779,"score_gpt":0.24600376121317208,"score_spread":0.2340239167406443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1497569944","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4309143,0.00014422048,0.56384516,0.0032512746,0.0000058986675,0.0007987533,0.000004666664,0.000016018601,0.0010197068],"genre_scores_gemma":[0.9921789,0.000025334251,0.00682729,0.00013101078,0.000014312434,0.00045912585,0.0000046151968,0.0000027127066,0.00035668272],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995176,0.000022989696,0.00016968972,0.00014400316,0.00006570609,0.000080013466],"domain_scores_gemma":[0.99921566,0.0004195051,0.00011691137,0.00019945682,0.00001560615,0.00003284465],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00017043004,0.000052223786,0.00010956815,0.0000121254825,0.000076101845,0.000004261997,0.00017834728,0.0000643028,0.0018277329],"category_scores_gemma":[0.0000832057,0.000030411744,0.000043041964,0.00017949005,0.00021259219,0.0000555914,0.000055100005,0.000047303318,0.00006884773],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000091679045,0.0003398621,0.18826073,0.000021266114,0.00015578911,5.820134e-8,0.00095819734,0.0025186979,0.18053515,0.010487504,0.0050226487,0.6116084],"study_design_scores_gemma":[0.00053265324,0.00015110131,0.78533226,0.0000020439775,0.00020706693,0.0000021289675,0.00009192945,0.058819655,0.005912594,0.068473384,0.0803079,0.00016725625],"about_ca_topic_score_codex":0.00029441732,"about_ca_topic_score_gemma":0.000012385009,"teacher_disagreement_score":0.61144114,"about_ca_system_score_codex":0.000004950159,"about_ca_system_score_gemma":0.0000036402032,"threshold_uncertainty_score":0.9990847},"labels":[],"label_agreement":null},{"id":"W1766891869","doi":"10.1002/met.1392","title":"Progress and challenges in forecast verification","year":2013,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":119,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Computer science; Data assimilation; Forecast verification; Variety (cybernetics); Data science; Meteorology; Forecast skill; Artificial intelligence; Geography","score_opus":0.07775056215445175,"score_gpt":0.24251966186185778,"score_spread":0.16476909970740602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1766891869","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9537551,0.009360984,0.0010973884,0.008599305,0.000032326952,0.001618088,0.000021669619,0.0001350452,0.025380122],"genre_scores_gemma":[0.99403656,0.00082547107,0.004558882,0.00017129275,0.000039380375,0.00028456826,0.000052900214,0.0000019797076,0.000028976023],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9990087,0.0000872907,0.00022549325,0.00033596053,0.00010510517,0.00023741991],"domain_scores_gemma":[0.99935323,0.000249968,0.000049804883,0.00019060014,0.000032709275,0.00012369949],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00022351554,0.000105526815,0.00015212984,0.00006954162,0.00011710634,0.000043173633,0.00015346208,0.000097730765,0.0020924152],"category_scores_gemma":[0.000036131743,0.00007377316,0.000024288353,0.00022008785,0.00017730985,0.00014990119,0.000014604608,0.000116595074,0.00044556518],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008045522,0.00006614892,0.25836518,0.000012452126,0.000005088537,5.9838317e-7,0.000060604092,0.00025980157,0.000039817554,0.018717712,0.000020913514,0.72244364],"study_design_scores_gemma":[0.00013191832,0.00009183275,0.9093034,0.0000012397387,0.000003949046,0.0000024596145,0.000059315196,0.009937784,0.000004011348,0.06757348,0.012793006,0.000097553755],"about_ca_topic_score_codex":0.00008052669,"about_ca_topic_score_gemma":0.00011754527,"teacher_disagreement_score":0.72234607,"about_ca_system_score_codex":0.0000031294824,"about_ca_system_score_gemma":0.0000053891213,"threshold_uncertainty_score":0.9988198},"labels":[],"label_agreement":null},{"id":"W1825436892","doi":"10.1002/met.1342","title":"The Canadian Airport Nowcasting System (CAN‐Now)","year":2012,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Nowcasting; Meteorology; Environmental science; Visibility; Radar; Computer science; Geography; Telecommunications","score_opus":0.03615926800269575,"score_gpt":0.23097652587290823,"score_spread":0.19481725787021248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1825436892","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34301233,0.0034255763,0.008197216,0.008882685,0.00088866754,0.0026706427,0.0004108711,0.0007321631,0.63177985],"genre_scores_gemma":[0.99664646,0.000012466277,0.0018525477,0.000590019,0.00035182005,0.00008740042,0.00010860725,0.0000036057431,0.00034706166],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99828285,0.00014883345,0.00032308925,0.00024294046,0.0002327812,0.00076952047],"domain_scores_gemma":[0.99807745,0.00075756485,0.00009327942,0.0003569843,0.00006338636,0.0006513243],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010109978,0.0001509995,0.00016684002,0.00005257389,0.0023007733,0.00010501369,0.00041709145,0.00013410239,0.0009911114],"category_scores_gemma":[0.000109324996,0.000084948704,0.000081378595,0.0003927042,0.0002084389,0.00009130395,0.000018715758,0.00024506473,0.0016371367],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013254939,0.000037888167,0.79756874,0.000009846488,0.000038842318,0.0000029688003,0.000067454625,0.0023721212,0.000023738483,0.14355075,0.000930475,0.05538395],"study_design_scores_gemma":[0.000089264926,0.000051279996,0.7016146,0.000001531758,0.000028284434,0.000018023353,0.00010502892,0.0040843496,0.0000062038766,0.0045288503,0.2892882,0.00018438093],"about_ca_topic_score_codex":0.010420566,"about_ca_topic_score_gemma":0.13828869,"teacher_disagreement_score":0.65363413,"about_ca_system_score_codex":0.000032863347,"about_ca_system_score_gemma":0.00006291647,"threshold_uncertainty_score":0.9999221},"labels":[],"label_agreement":null},{"id":"W1948277581","doi":"10.1002/met.289","title":"Lidar studies of the polar troposphere","year":2011,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Lidar; Troposphere; Environmental science; Polar; Trace gas; Arctic; The arctic; Remote sensing; Meteorology; Tropospheric ozone; Geology; Geography","score_opus":0.03770336357213998,"score_gpt":0.2537079522432803,"score_spread":0.2160045886711403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1948277581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94080544,0.00036556346,0.008548278,0.00042469506,0.000033813827,0.00040589203,0.0000060076727,0.000043769734,0.049366552],"genre_scores_gemma":[0.9859189,0.000034122557,0.01291842,0.0002929598,0.000013619083,0.00015087616,3.7932722e-7,0.000004434473,0.0006662829],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99936885,0.000040369578,0.00015907652,0.00017243017,0.00012741615,0.00013186864],"domain_scores_gemma":[0.9995155,0.000036702495,0.000080419995,0.00032045165,0.000009126289,0.000037819576],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000102299346,0.000076185985,0.00011830646,2.741667e-7,0.00015246624,0.0000021269448,0.0003280014,0.000048559185,0.0032713313],"category_scores_gemma":[0.000025824924,0.000039980903,0.00007363038,0.0002256936,0.00059422455,0.00002728759,0.00025700466,0.00008028851,0.00023934481],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039485865,0.00091122865,0.85569793,0.000015466763,0.00012040962,0.000001496269,0.0018342051,0.000117924166,0.028538255,0.06908702,0.0045312066,0.03910534],"study_design_scores_gemma":[0.00014271302,0.00015570605,0.9007803,0.000002409098,0.000055574983,0.0000033283077,0.0005934217,0.00003568987,0.0059063155,0.04323259,0.048941724,0.00015020593],"about_ca_topic_score_codex":0.000085060274,"about_ca_topic_score_gemma":0.000024283438,"teacher_disagreement_score":0.04870027,"about_ca_system_score_codex":0.000023588978,"about_ca_system_score_gemma":0.0000030203996,"threshold_uncertainty_score":0.99763983},"labels":[],"label_agreement":null},{"id":"W1966394511","doi":"10.1017/s1350482706002106","title":"Mesoscale simulations of atmospheric flow and tracer transport in Phoenix, Arizona","year":2006,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; National Science Foundation","keywords":"Mesoscale meteorology; Phoenix; Environmental science; Population; Terrain; Atmospheric sciences; Meteorology; Planetary boundary layer; Flow (mathematics); Turbulence; Plume; Atmospheric circulation; Geology; Metropolitan area; Geography; Mechanics; Physics","score_opus":0.0072436670914269715,"score_gpt":0.20940813611423106,"score_spread":0.2021644690228041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966394511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9821016,0.00012633552,0.0101839695,0.00046768467,0.0000065849063,0.00029990432,0.000026939755,0.00002940034,0.0067575322],"genre_scores_gemma":[0.9855937,0.000014413481,0.013916228,0.000060883674,0.000018306093,0.0001261459,0.000013266921,0.000004628926,0.00025243507],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992661,0.000019567147,0.00022467352,0.00023117628,0.00010819891,0.00015028755],"domain_scores_gemma":[0.9997166,0.0000847945,0.000039001625,0.00012154498,0.0000046394343,0.000033413566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007998885,0.000089269015,0.00015707179,0.0000065456984,0.00008505395,0.000003286356,0.0000883422,0.00005748545,0.0006590584],"category_scores_gemma":[0.0000056042522,0.00006992717,0.00003770903,0.00030612052,0.00025328717,0.00005102757,0.000036241825,0.000072256764,0.000024667945],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023455439,0.00096354395,0.8570997,0.000012713257,0.0000126554505,0.0000026266869,0.00021375422,0.07267161,0.02971927,0.003731228,0.00035986662,0.035189595],"study_design_scores_gemma":[0.0002682142,0.000040243365,0.9620716,0.0000016105689,0.000016311204,0.0000010976344,0.000019327865,0.007440649,0.0004641866,0.006854673,0.022714073,0.00010799407],"about_ca_topic_score_codex":0.0001670458,"about_ca_topic_score_gemma":0.00037776312,"teacher_disagreement_score":0.10497194,"about_ca_system_score_codex":0.000018448014,"about_ca_system_score_gemma":0.0000022511572,"threshold_uncertainty_score":0.7216227},"labels":[],"label_agreement":null},{"id":"W1966587452","doi":"10.1017/s1350482700001572","title":"Orographic influences during winter precipitation events on the Avalon Peninsula, Newfoundland","year":2000,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Environment and Climate Change Canada; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland; University of Toronto","keywords":"Precipitation; Orographic lift; Peninsula; Geology; Precipitation types; Climatology; Front (military); Crest; Orography; Atmospheric sciences; Oceanography; Meteorology; Geography","score_opus":0.024120698374503577,"score_gpt":0.23924988036635694,"score_spread":0.21512918199185338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966587452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97472316,0.00012297292,0.00021972823,0.0016484103,0.000037727812,0.0006928435,0.00004151406,0.000112691494,0.022400964],"genre_scores_gemma":[0.99742717,0.00006397903,0.00043347385,0.0010011425,0.0001228604,0.00012454331,0.00009794211,0.0000036850763,0.00072519324],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99836516,0.00024869735,0.00032906022,0.00041437944,0.00030326657,0.00033943512],"domain_scores_gemma":[0.9985808,0.0008062069,0.00007965365,0.00035600676,0.00003993032,0.00013740048],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00035467284,0.00018299479,0.00017942314,0.00006707488,0.00073513744,0.00007300095,0.0004298041,0.00010769117,0.024777632],"category_scores_gemma":[0.0000710601,0.0000999308,0.00011298317,0.0004990059,0.0001883968,0.00013911442,0.000011644205,0.00025058602,0.002312195],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026361548,0.00020736016,0.91289955,0.000008800463,0.00006740761,0.0000028229756,0.0001749513,0.030219985,0.0002933415,0.0064049056,0.00010998223,0.049347255],"study_design_scores_gemma":[0.00020355293,0.00021835137,0.9486607,0.0000034184052,0.000020936715,0.0000031537822,0.000016902673,0.0016058796,0.000011038096,0.0398279,0.009285012,0.00014316404],"about_ca_topic_score_codex":0.00012066877,"about_ca_topic_score_gemma":0.00022163565,"teacher_disagreement_score":0.049204092,"about_ca_system_score_codex":0.0000069409793,"about_ca_system_score_gemma":0.0000095871565,"threshold_uncertainty_score":0.99846464},"labels":[],"label_agreement":null},{"id":"W1969074413","doi":"10.1002/met.145","title":"Copula‐based drought severity‐duration‐frequency analysis in Iran","year":2009,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":271,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Copula (linguistics); Univariate; Natural hazard; Joint probability distribution; Climatology; Statistics; Environmental science; Multivariate statistics; Physical geography; Econometrics; Mathematics; Geography; Meteorology; Geology","score_opus":0.015419024474763461,"score_gpt":0.25983123285429405,"score_spread":0.2444122083795306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969074413","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.762295,0.000084119136,0.19295083,0.008596473,0.000015056576,0.00063988206,0.000019119072,0.00029458475,0.035104908],"genre_scores_gemma":[0.98445183,0.000007924016,0.012360447,0.002665619,0.000021481874,0.00020823347,0.00009156168,0.000004915643,0.00018799967],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99837774,0.0001545228,0.00041552118,0.00052139,0.0002168672,0.00031398318],"domain_scores_gemma":[0.99921185,0.00009742202,0.00010211162,0.00046769207,0.0000075293856,0.00011341839],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00040617058,0.00015885661,0.00031606824,0.00014888009,0.00020300598,0.000020863126,0.00035938813,0.00018605182,0.0035282231],"category_scores_gemma":[0.00004508736,0.0001333244,0.00019644613,0.0029819456,0.00018583612,0.00013000795,0.00003748648,0.00020675964,0.0008848598],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040092884,0.0011271413,0.9415387,0.0000021444514,0.00012236444,0.000019825839,0.00010389939,0.030953765,0.0064093415,0.008318817,0.0005101531,0.010853758],"study_design_scores_gemma":[0.0002965278,0.000092638424,0.91938174,6.224874e-7,0.00034153232,0.0000017995158,0.000008435292,0.02797369,0.00030197843,0.045386445,0.005953744,0.0002608219],"about_ca_topic_score_codex":0.00017125274,"about_ca_topic_score_gemma":0.0009875655,"teacher_disagreement_score":0.2221568,"about_ca_system_score_codex":0.0001018697,"about_ca_system_score_gemma":0.0000058114506,"threshold_uncertainty_score":0.99989307},"labels":[],"label_agreement":null},{"id":"W1976481339","doi":"10.1017/s135048270500160x","title":"Summer regional rainfall over southern Ontario and its associations with outgoing longwave radiation and moisture convergence","year":2005,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Climate variability and models","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University","funders":"","keywords":"Outgoing longwave radiation; Environmental science; Precipitation; Climatology; Flooding (psychology); Moisture; Longwave; Atmospheric sciences; Meteorology; Geography; Radiation; Convection; Geology","score_opus":0.026513627214687415,"score_gpt":0.2394499157284355,"score_spread":0.21293628851374807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976481339","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99061024,0.00010123963,0.0033614978,0.0029110806,0.0000063986645,0.00047217362,0.00004345424,0.000044336088,0.002449553],"genre_scores_gemma":[0.99480605,0.000076674565,0.0029525454,0.0011072179,0.00003411535,0.00017949707,0.000046946116,0.0000065487357,0.00079042144],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99908787,0.00003988078,0.00016344286,0.00035914246,0.00016764078,0.00018202196],"domain_scores_gemma":[0.99951124,0.00014346388,0.00008244305,0.0001394002,0.000015440373,0.000108013446],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002344084,0.000115366536,0.00012540317,0.000015684138,0.0002472943,0.000030136152,0.000086494074,0.00010859942,0.0013345289],"category_scores_gemma":[0.000026349531,0.000088949,0.000021875721,0.00012119026,0.0001475347,0.00014618484,0.00008188191,0.00015218445,0.00010435361],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055016022,0.00036446267,0.9639992,0.000007813857,0.000056423607,0.0000010309672,0.0048377495,0.00395354,0.0043539503,0.012199463,0.00093543914,0.00923588],"study_design_scores_gemma":[0.00056325016,0.00007489003,0.8965289,0.0000025373624,0.00006481837,0.000008744533,0.00008702612,0.0063747684,0.00005707962,0.0048682373,0.091101296,0.00026847768],"about_ca_topic_score_codex":0.0017192113,"about_ca_topic_score_gemma":0.025463916,"teacher_disagreement_score":0.09016586,"about_ca_system_score_codex":0.00015549969,"about_ca_system_score_gemma":0.000014146308,"threshold_uncertainty_score":0.9995784},"labels":[],"label_agreement":null},{"id":"W1981153166","doi":"10.1017/s1350482703005048","title":"Using willingness‐to‐pay to assess the economic value of weather forecasts for multiple commercial sectors","year":2003,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Willingness to pay; Valuation (finance); Recreation; Business; Contingent valuation; Value (mathematics); Agricultural economics; National weather service; Landscaping; Actuarial science; Meteorology; Economics; Finance; Geography; Statistics; Mathematics","score_opus":0.2522286245251898,"score_gpt":0.29530565633714023,"score_spread":0.04307703181195044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981153166","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.620771,0.000039680246,0.37620008,0.00034983119,0.000100041,0.0010162555,0.0001733093,0.000011376479,0.0013384257],"genre_scores_gemma":[0.9675274,0.0000073027268,0.030822312,0.0005592273,0.00007801713,0.0008764462,0.00001591798,0.000019437937,0.00009393857],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9988783,0.000030570598,0.0005002329,0.00035273243,0.00002029464,0.0002178706],"domain_scores_gemma":[0.9991163,0.0002687082,0.00020623332,0.00031433243,0.00001088117,0.00008352241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073853665,0.00012562168,0.00029349598,0.00005820027,0.00018490393,0.000022395756,0.00024118098,0.00008772925,0.00027002097],"category_scores_gemma":[0.00009579948,0.00009964723,0.00012350036,0.00010663715,0.00006094657,0.000060529383,0.000046051282,0.00006995737,0.0002671428],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025484998,0.00013087828,0.3409731,0.000010249092,0.000055854107,3.4978136e-8,0.00018981766,0.06050782,0.00084482046,0.59468687,0.00025498754,0.0023200705],"study_design_scores_gemma":[0.0011608955,0.0003387223,0.5545544,0.0000066492794,0.000056088185,0.000003655717,0.00015521901,0.050722163,0.003986744,0.13127366,0.25709864,0.0006431554],"about_ca_topic_score_codex":0.00008818702,"about_ca_topic_score_gemma":0.00003590521,"teacher_disagreement_score":0.4634132,"about_ca_system_score_codex":0.00019142732,"about_ca_system_score_gemma":0.000014247226,"threshold_uncertainty_score":0.4063496},"labels":[],"label_agreement":null},{"id":"W1985575635","doi":"10.1002/met.170","title":"Index sensitivity analysis applied to the Canadian Forest Fire Weather Index and the McArthur Forest Fire Danger Index","year":2009,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":133,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Forest Service","funders":"","keywords":"Environmental science; Percentile; Index (typography); Relative humidity; Wind speed; Meteorology; Sensitivity (control systems); Climatology; Atmospheric sciences; Statistics; Geography; Mathematics; Geology; Computer science","score_opus":0.006713051327036684,"score_gpt":0.2076127990815716,"score_spread":0.20089974775453492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985575635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95091254,0.00007471084,0.019406768,0.016960165,0.00003059374,0.0031565952,0.000058626945,0.00010709386,0.009292883],"genre_scores_gemma":[0.99379617,0.0000051738875,0.00013709215,0.0045955605,0.00009233616,0.0011136965,0.000025007237,0.000014226789,0.00022075897],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978278,0.00026411773,0.00030139412,0.00065604766,0.00040260048,0.0005480214],"domain_scores_gemma":[0.9980821,0.0004955735,0.00011731472,0.0009209584,0.000020078292,0.00036396112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012041964,0.00027736544,0.00039475228,0.00006804033,0.0009411751,0.00014052457,0.0005098864,0.00023187538,0.00023568452],"category_scores_gemma":[0.00009271479,0.00015349676,0.00014927557,0.0014685533,0.00047333547,0.000075304204,0.0001900146,0.00037472704,0.00038168966],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001235779,0.00016017555,0.81543994,0.0000048071247,0.00021913351,0.000010305709,0.0005951627,0.043888908,0.00014425447,0.005074783,0.002506232,0.1318327],"study_design_scores_gemma":[0.00031002585,0.000044633434,0.8595856,0.0000013807716,0.00011926884,0.000008885744,0.000032804885,0.112005495,0.0000042090246,0.0021774992,0.025515785,0.00019441587],"about_ca_topic_score_codex":0.09773434,"about_ca_topic_score_gemma":0.71757513,"teacher_disagreement_score":0.6198408,"about_ca_system_score_codex":0.00020560891,"about_ca_system_score_gemma":0.000020040667,"threshold_uncertainty_score":0.90827394},"labels":[],"label_agreement":null},{"id":"W1998812257","doi":"10.1017/s1350482702004012","title":"Modelling a coastal ridging event over south‐eastern Australia","year":2002,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"Australian Research Council","keywords":"Mesoscale meteorology; Radiosonde; Climatology; Environmental science; Meteorology; East coast; Synoptic scale meteorology; Event (particle physics); Air mass (solar energy); Lag; Geography; Geology; Physical geography; Computer science","score_opus":0.08749542572773548,"score_gpt":0.2633252288815764,"score_spread":0.1758298031538409,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998812257","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70577055,0.00021593412,0.28128257,0.0003946083,0.00007373781,0.00053603284,0.00017524182,0.00018835839,0.011362948],"genre_scores_gemma":[0.9924028,0.0000142551435,0.005570419,0.00036693274,0.00014771745,0.000046016263,0.00010769568,0.0000044689214,0.0013396762],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99825627,0.000104681516,0.00039290264,0.0004790949,0.0002877832,0.00047928529],"domain_scores_gemma":[0.9990218,0.00024047667,0.00010640819,0.00032032267,0.000038285925,0.00027267056],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00024282032,0.00020502375,0.00024646666,0.000074011296,0.00037907492,0.000074902804,0.00032337438,0.00013811822,0.026253661],"category_scores_gemma":[0.000026335176,0.00015121825,0.00013889855,0.0003536635,0.00014308949,0.00013065338,0.000029502726,0.0002625451,0.0033714187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021903865,0.00013829929,0.15663683,0.0000089402765,0.000034742432,0.000006506099,0.00017799181,0.8256057,0.000055859753,0.004600795,0.00025668548,0.012455786],"study_design_scores_gemma":[0.0002686198,0.000121930025,0.05490505,0.0000023488435,0.000033069104,0.0000045955476,0.000029159142,0.91389304,0.0000049549612,0.014248819,0.016236845,0.00025156667],"about_ca_topic_score_codex":0.00019790682,"about_ca_topic_score_gemma":0.000067138564,"teacher_disagreement_score":0.28663227,"about_ca_system_score_codex":0.000005219071,"about_ca_system_score_gemma":0.0000041154067,"threshold_uncertainty_score":0.9974046},"labels":[],"label_agreement":null},{"id":"W2022201065","doi":"10.1002/met.198","title":"Public perception of and response to severe weather warnings in Nova Scotia, Canada","year":2010,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Nova scotia; Vulnerability (computing); Warning system; Nova (rocket); Social vulnerability; Geography; Perception; Social media; Political science; Psychology; Computer science; Aeronautics; Engineering; Computer security; Psychological intervention; Telecommunications","score_opus":0.025551712296049377,"score_gpt":0.28357006201280754,"score_spread":0.2580183497167582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022201065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9734803,0.000005990558,0.0003291966,0.011216567,0.000028860386,0.00035470258,0.0000032222517,0.000015972675,0.014565219],"genre_scores_gemma":[0.99714917,0.0000027823694,0.001047623,0.00035099566,0.000025196721,0.000049900646,0.0000014415741,0.0000024575327,0.0013704222],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992467,0.0001028516,0.00012322888,0.00018198414,0.0001757209,0.00016949828],"domain_scores_gemma":[0.9995504,0.0001440607,0.00003642097,0.00012681926,0.00004400125,0.00009828726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000662875,0.00005084158,0.00008438564,0.00006214447,0.00010622261,0.000026495067,0.00021885148,0.00005734249,0.0005130046],"category_scores_gemma":[0.00024802727,0.000041679545,0.000013221391,0.00039436645,0.00020346073,0.00006805129,0.00006498783,0.00010538092,0.000023057923],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026258748,0.00048612172,0.514009,0.000026314416,0.000020749509,0.000004352527,0.01918981,0.000040649622,0.10588243,0.14171408,0.004653463,0.21371046],"study_design_scores_gemma":[0.00015422681,0.000044939534,0.804994,0.0000028668455,0.0000056728263,5.5412613e-7,0.0037778607,0.00003675643,0.00001709849,0.0022880815,0.18855552,0.00012242366],"about_ca_topic_score_codex":0.1948393,"about_ca_topic_score_gemma":0.8542978,"teacher_disagreement_score":0.6594585,"about_ca_system_score_codex":0.000032510976,"about_ca_system_score_gemma":0.000099511126,"threshold_uncertainty_score":0.8105223},"labels":[],"label_agreement":null},{"id":"W2028001972","doi":"10.1002/met.14","title":"The influence of an upper‐level frontal zone on the Mack Lake Wildfire environment","year":2007,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"U.S. Forest Service; University of Wisconsin-Madison; U.S. Department of Agriculture","keywords":"Troposphere; Climatology; Ridge; Front (military); Geology; Jet stream; Environmental science; Cold front; Synoptic scale meteorology; Subsidence; Intrusion; Trough (economics); Air mass (solar energy); Atmospheric sciences; Jet (fluid); Structural basin; Oceanography; Boundary layer; Geomorphology","score_opus":0.011982708319546918,"score_gpt":0.22352784253808936,"score_spread":0.21154513421854243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028001972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99076974,0.00002655796,0.0042278385,0.0011576209,0.000021044847,0.0010083037,0.000036534853,0.000041553692,0.0027107997],"genre_scores_gemma":[0.9972711,0.000015166109,0.0013495742,0.0005487995,0.000037940274,0.00045322953,0.000010409796,0.000011197884,0.0003025498],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9983811,0.0001496284,0.00033411788,0.00036679962,0.000422528,0.00034584905],"domain_scores_gemma":[0.9980547,0.0008821066,0.00015063687,0.0007920873,0.0000042038255,0.00011630474],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013513155,0.000159828,0.00014851561,0.00001355762,0.00046402132,0.000021767366,0.0007785034,0.000100003126,0.00044224027],"category_scores_gemma":[0.00006791018,0.0000816395,0.00006988547,0.0001811979,0.0006389592,0.00007507907,0.0001872334,0.00022130457,0.0012532453],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050386717,0.0033351462,0.14687485,0.000020594332,0.00014939388,0.000019574305,0.00085461093,0.012762293,0.17476241,0.03796266,0.002994568,0.61976004],"study_design_scores_gemma":[0.00013574319,0.00028011212,0.8579331,0.0000028423947,0.000012719725,0.00000717045,0.00005624664,0.0008068285,0.001992936,0.0012581671,0.13738091,0.00013319032],"about_ca_topic_score_codex":0.00016037584,"about_ca_topic_score_gemma":0.00062750076,"teacher_disagreement_score":0.7110583,"about_ca_system_score_codex":0.00008693381,"about_ca_system_score_gemma":0.0000037308282,"threshold_uncertainty_score":0.9995244},"labels":[],"label_agreement":null},{"id":"W2047340247","doi":"10.1002/met.3","title":"Comparison of VAAC atmospheric dispersion models using the 1 November 2004 Grimsvötn eruption","year":2007,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Met Office","keywords":"Volcanic ash; Volcano; Environmental science; Meteorology; Dispersion (optics); Atmospheric sciences; Atmospheric dispersion modeling; Tephra; Vulcanian eruption; Numerical weather prediction; Climatology; Geology; Geography; Air pollution; Seismology","score_opus":0.04074113172469053,"score_gpt":0.31201628489699745,"score_spread":0.27127515317230694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047340247","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47857592,0.00012966878,0.51763916,0.00013254065,0.000018182745,0.00026971105,0.0000020058437,0.00002597298,0.0032068507],"genre_scores_gemma":[0.95475525,0.000010851879,0.044752117,0.00020872577,0.00003943962,0.000047184487,0.000005472627,0.000009234215,0.0001717272],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987673,0.000037918027,0.0003492041,0.00028625675,0.00028722204,0.00027211028],"domain_scores_gemma":[0.9992685,0.000112139576,0.00017346523,0.00034634935,0.00001559172,0.00008399784],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00038282626,0.00013080357,0.00018921412,6.063366e-7,0.00027970586,0.000011063693,0.00031984312,0.0001161019,0.0011670897],"category_scores_gemma":[0.000010110334,0.00008090477,0.0000912544,0.00046474798,0.00038039265,0.000091192516,0.00017257089,0.00015895214,0.00008037222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012520059,0.0016101893,0.24347098,0.000013853104,0.000046069938,0.0000013758574,0.0007612025,0.46167356,0.17561452,0.02174356,0.0014245287,0.09351496],"study_design_scores_gemma":[0.00064891926,0.00036738196,0.30094415,0.000009753463,0.00019314392,0.000013428941,0.0013047565,0.6359714,0.007144746,0.021740211,0.031004535,0.00065755524],"about_ca_topic_score_codex":0.00020472643,"about_ca_topic_score_gemma":0.000043794982,"teacher_disagreement_score":0.47617933,"about_ca_system_score_codex":0.000101320366,"about_ca_system_score_gemma":0.0000051763272,"threshold_uncertainty_score":0.99974597},"labels":[],"label_agreement":null},{"id":"W2065120723","doi":"10.1017/s1350482703003104","title":"Reply to Lance M. Leslie's and Milton S. Speer's comments on Modelling a coastal ridging event over south‐eastern Australia. C. J. C. Reason and P. L. Jackson (Meteorological Applications 2002, 9: 383–397)","year":2003,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Cape; Citation; Event (particle physics); History; Library science; Computer science; Archaeology; Physics","score_opus":0.04541120515916819,"score_gpt":0.2849077411851784,"score_spread":0.23949653602601023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065120723","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.775856,0.00008679547,0.21648715,0.0023440728,0.00002558854,0.0019273325,0.00015830794,0.00012617475,0.0029885657],"genre_scores_gemma":[0.9780176,0.00008266311,0.016578836,0.0032410664,0.000040645362,0.0013783718,0.000040099483,0.000021998745,0.0005986676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972411,0.00018847644,0.00047887242,0.0011435346,0.00036474885,0.00058326585],"domain_scores_gemma":[0.9984745,0.00027016614,0.00014558889,0.0006524391,0.000021461703,0.0004358635],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007801489,0.00034342313,0.00037802098,0.000057107594,0.00044440568,0.00008846938,0.0002928248,0.00020734331,0.0007754001],"category_scores_gemma":[0.00007435389,0.0002932286,0.0000827279,0.0003457149,0.00032539695,0.0001291567,0.0003063235,0.0003555811,0.00042001833],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013198027,0.007986462,0.36186406,0.00028220905,0.0003067423,0.000033500717,0.0024888543,0.37698972,0.028107028,0.14911073,0.015035096,0.056475777],"study_design_scores_gemma":[0.002170646,0.0011004165,0.06854872,0.00005865619,0.00021794921,0.0000632139,0.0002571734,0.06835406,0.0010926413,0.033779945,0.8227456,0.0016109811],"about_ca_topic_score_codex":0.00021758837,"about_ca_topic_score_gemma":0.00004501902,"teacher_disagreement_score":0.80771047,"about_ca_system_score_codex":0.000103792896,"about_ca_system_score_gemma":0.000007072154,"threshold_uncertainty_score":0.99995196},"labels":[],"label_agreement":null},{"id":"W2068583481","doi":"10.1002/met.213","title":"Climate change impact on the hydrological balance of the Itaipu Basin","year":2010,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Surface runoff; Environmental science; Hydropower; Climate change; Water balance; Structural basin; Hydrology (agriculture); Drainage basin; Precipitation; Climatology; Geography; Meteorology; Geology","score_opus":0.020581497325460482,"score_gpt":0.2538724829246267,"score_spread":0.23329098559916622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068583481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9551508,0.000010760202,0.00014070628,0.021806259,0.000052568997,0.00078330183,0.00001946984,0.000042668456,0.021993486],"genre_scores_gemma":[0.99553025,0.000029427347,0.0001780469,0.0032853708,0.000048407543,0.00085729087,0.0000018286973,0.0000044190197,0.00006494345],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99898905,0.00011725778,0.00016351907,0.0002731106,0.00016543259,0.00029162393],"domain_scores_gemma":[0.99904364,0.00029077908,0.00009328352,0.00052610406,0.0000053582476,0.000040808987],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005230065,0.00013243953,0.00015277005,0.000010971406,0.00042359447,0.000008034541,0.00063674536,0.000102434795,0.0019416534],"category_scores_gemma":[0.000065153865,0.00005144269,0.00012380346,0.00024664417,0.00091065734,0.00003876243,0.00048876496,0.00033411686,0.0005661579],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011536846,0.0007632625,0.8190809,0.0000065075465,0.00006243677,0.000002017019,0.00022409527,0.00041421878,0.016140563,0.14696226,0.0052265176,0.011001874],"study_design_scores_gemma":[0.00010529437,0.00013266611,0.9513387,0.0000012540376,0.000025595176,0.0000022032914,0.0000093264325,0.00047333163,0.00075709505,0.018269306,0.02879289,0.00009230647],"about_ca_topic_score_codex":0.000027128452,"about_ca_topic_score_gemma":0.000018771001,"teacher_disagreement_score":0.13225785,"about_ca_system_score_codex":0.000013642215,"about_ca_system_score_gemma":0.0000010621391,"threshold_uncertainty_score":0.9989707},"labels":[],"label_agreement":null},{"id":"W2069018481","doi":"10.1002/met.175","title":"A seasonal forecast scheme for spring dust storm predictions in Northern China","year":2010,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Environment and Climate Change Canada","funders":"National Natural Science Foundation of China","keywords":"Climatology; Storm; Dust storm; Environmental science; Empirical orthogonal functions; Precipitation; Meteorology; Forecast skill; Geography; Geology","score_opus":0.010574394016427175,"score_gpt":0.22959321793037465,"score_spread":0.21901882391394747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069018481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91387075,0.000010103114,0.08066679,0.00071303826,0.000040558287,0.00066497293,0.000019205689,0.00007292483,0.0039416254],"genre_scores_gemma":[0.95420533,0.0000023305447,0.043387417,0.00011436932,0.00009834198,0.0019471435,0.000011307415,0.000011117958,0.00022265724],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990569,0.000011207787,0.00018017807,0.000337415,0.00013507195,0.00027926738],"domain_scores_gemma":[0.99951273,0.00005999302,0.000055318156,0.0002463221,0.000008328583,0.0001173173],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00018880419,0.00011488009,0.00012059702,0.0000020763816,0.00023358146,0.000017675176,0.0002593385,0.00012307585,0.0010648486],"category_scores_gemma":[0.000041829528,0.000093275725,0.000071511444,0.0002486788,0.00019265177,0.00007081183,0.00012101666,0.00026845373,0.00017300314],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016510669,0.00028411223,0.95963657,0.0000027998801,0.000006404739,5.254238e-7,0.000051857744,0.0005624466,0.011453575,0.0052893995,0.00016152367,0.022534266],"study_design_scores_gemma":[0.00025717937,0.000062776024,0.90803003,9.489061e-7,0.0000088617735,0.0000034120937,0.000022353637,0.011815268,0.000079779646,0.0029279322,0.07666085,0.00013061902],"about_ca_topic_score_codex":0.00019153977,"about_ca_topic_score_gemma":0.0074283537,"teacher_disagreement_score":0.07649933,"about_ca_system_score_codex":0.00006134179,"about_ca_system_score_gemma":0.000009773624,"threshold_uncertainty_score":0.9998483},"labels":[],"label_agreement":null},{"id":"W2069361111","doi":"10.1002/met.214","title":"Evaluation of the Canadian fire weather index system in an eastern Mediterranean environment","year":2010,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":148,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mediterranean climate; Environmental science; Water content; Moisture; Climatology; Meteorology; Atmospheric sciences; Physical geography; Geography; Geology","score_opus":0.021953437766305112,"score_gpt":0.24325366831550418,"score_spread":0.22130023054919906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069361111","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922094,0.000012304968,0.0001717236,0.00030440823,0.00009441778,0.0014434622,0.000014548902,0.00002055911,0.0057292115],"genre_scores_gemma":[0.9986255,3.231198e-7,0.00018687916,0.000065368724,0.000042961237,0.0010301098,0.000006900003,0.000009511866,0.000032443226],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99818003,0.00034871083,0.00025808325,0.00031288803,0.00067823683,0.000222042],"domain_scores_gemma":[0.99903184,0.000053831714,0.00010769128,0.0006412905,0.000014668187,0.00015069277],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019791834,0.00011250162,0.00013528086,0.000029590854,0.00014572302,0.00001616784,0.00051149854,0.00016402235,0.0013768114],"category_scores_gemma":[0.00004379505,0.000074880096,0.00004235813,0.00020814943,0.00020630572,0.000078483055,0.00008606613,0.00024156744,0.00035638647],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000947502,0.00036601565,0.63307065,0.000018408064,0.000016721768,0.0000014932168,0.00053861714,0.0047831265,0.02925172,0.0010871887,0.00008209876,0.33077452],"study_design_scores_gemma":[0.0002588646,0.00004520248,0.69286644,0.000005379925,0.000032802658,0.0000054126613,0.000046369307,0.30028456,0.0002846235,0.000497295,0.0055561126,0.00011694343],"about_ca_topic_score_codex":0.042924248,"about_ca_topic_score_gemma":0.39353994,"teacher_disagreement_score":0.35061568,"about_ca_system_score_codex":0.0004153027,"about_ca_system_score_gemma":0.000032921434,"threshold_uncertainty_score":0.99953604},"labels":[],"label_agreement":null},{"id":"W2076788380","doi":"10.1017/s1350482700001523","title":"Dynamical influence of large valleys on the propagation of coastally trapped disturbances","year":2000,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Stratification (seeds); Geology; Climatology; Current (fluid); Atmospheric sciences; Environmental science; Meteorology; Physics; Oceanography","score_opus":0.015603145165181484,"score_gpt":0.23243209915652605,"score_spread":0.21682895399134455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076788380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.980985,0.000075502416,0.002494331,0.0008384111,0.000008017347,0.00060348737,0.00015598931,0.000035205783,0.014804073],"genre_scores_gemma":[0.99869853,0.00003485122,0.0006246801,0.00035708814,0.000021930846,0.000047395017,0.000090096844,0.0000020330115,0.00012341574],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9986197,0.00020331737,0.00042164198,0.0002554555,0.00028228475,0.00021761733],"domain_scores_gemma":[0.9984547,0.00096497074,0.00014009108,0.0003010116,0.00006653942,0.00007270498],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00046472673,0.00012232429,0.00023081053,0.00003387096,0.00019576678,0.000011395133,0.00038191883,0.00008762965,0.0056443056],"category_scores_gemma":[0.00010866623,0.00006503728,0.00009196793,0.0004058692,0.00034843176,0.00006385892,0.000010499633,0.00015841667,0.00012992193],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081094966,0.0016538971,0.16760854,0.00007730407,0.00014760542,0.00000247188,0.00041511157,0.36773717,0.006874371,0.3297199,0.0002328368,0.12471985],"study_design_scores_gemma":[0.0002687104,0.0005737697,0.93414205,0.000006337078,0.000028706168,9.878298e-7,0.000034864,0.017203536,0.00023553048,0.04229782,0.0050722654,0.0001354239],"about_ca_topic_score_codex":0.00006639758,"about_ca_topic_score_gemma":0.00008219874,"teacher_disagreement_score":0.7665335,"about_ca_system_score_codex":0.000002601806,"about_ca_system_score_gemma":0.000017144654,"threshold_uncertainty_score":0.99526465},"labels":[],"label_agreement":null},{"id":"W2088170334","doi":"10.1017/s1350482701003139","title":"Aspects of melting and the radar bright band","year":2001,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Snowflake; Radar; Snow; Geology; Reflectivity; Meteorology; Atmospheric sciences; Optics; Physics; Telecommunications; Computer science","score_opus":0.02279005600473188,"score_gpt":0.22457493119333571,"score_spread":0.20178487518860383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088170334","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8135272,0.003157451,0.020430312,0.0055696713,0.000029434366,0.00056219555,0.00002273844,0.00006221975,0.15663874],"genre_scores_gemma":[0.9983278,0.000164953,0.0011648401,0.00019415093,0.000037431433,0.000008867231,0.000017200413,6.8799557e-7,0.00008407396],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993971,0.00008677181,0.00015536169,0.0001277111,0.00013710109,0.00009594945],"domain_scores_gemma":[0.99939436,0.00035053823,0.00007012628,0.000111768284,0.000032354084,0.00004085635],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00050528924,0.00005256943,0.00012363902,0.000027656988,0.0001693499,0.00001936719,0.00012620418,0.00002710299,0.0010431553],"category_scores_gemma":[0.0000579293,0.000027327662,0.000044339635,0.00025047158,0.00020378384,0.00004385329,0.0000053931567,0.000056858706,0.000036316313],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017201761,0.000072913404,0.5838194,0.000015232646,0.00015124703,0.000002414443,0.00026904815,0.0004261046,0.0020380053,0.10073034,0.00021864648,0.31208465],"study_design_scores_gemma":[0.0007987684,0.000043451735,0.85966444,0.0000029828586,0.000111527406,0.0000081742755,0.00009837257,0.0031632471,0.00056746346,0.11108263,0.024340944,0.00011802181],"about_ca_topic_score_codex":0.00013265312,"about_ca_topic_score_gemma":0.00019548522,"teacher_disagreement_score":0.3119666,"about_ca_system_score_codex":7.687157e-7,"about_ca_system_score_gemma":0.000005635884,"threshold_uncertainty_score":0.99987},"labels":[],"label_agreement":null},{"id":"W2107069771","doi":"10.1002/met.1450","title":"Developments in aviation meteorology","year":2014,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Aviation; Flight planning; Civil aviation; International airport; Meteorology; Clear-air turbulence; Numerical weather prediction; Global Forecast System; Aeronautics; Computer science; Environmental science; Engineering; Transport engineering; Turbulence; Aerospace engineering; Geography","score_opus":0.022707931201940715,"score_gpt":0.2367615659606514,"score_spread":0.2140536347587107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107069771","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.709496,0.00019504623,0.09494267,0.0011586052,0.00014160716,0.0010213297,0.000031631083,0.00025240734,0.19276069],"genre_scores_gemma":[0.98493284,0.000013491604,0.013312766,0.0012864865,0.0000732546,0.000081039005,0.00017955055,0.0000029684504,0.00011762806],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983164,0.0002786138,0.00041041544,0.0004253351,0.00018378135,0.0003854661],"domain_scores_gemma":[0.99879515,0.0006854188,0.000088512286,0.00024872107,0.0000377273,0.00014446871],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00074710656,0.00015264364,0.00025580326,0.00014394904,0.00018073489,0.000028042277,0.00031073566,0.00016024316,0.0021191216],"category_scores_gemma":[0.00019065585,0.00011499132,0.00005345552,0.00055579725,0.00010999582,0.00010436535,0.000021090782,0.00020329836,0.0011727262],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003464575,0.000096433796,0.71458685,0.000005206413,0.0000113032775,0.0000013113774,0.000042784493,0.0069476515,0.00018804564,0.094280325,0.000042215364,0.18376319],"study_design_scores_gemma":[0.0002871648,0.00011129597,0.86221486,8.3219913e-7,0.0000071566174,0.0000020025902,0.000007308896,0.00655388,0.00001619227,0.08824357,0.042410757,0.00014501029],"about_ca_topic_score_codex":0.000096700795,"about_ca_topic_score_gemma":0.00043979418,"teacher_disagreement_score":0.2754368,"about_ca_system_score_codex":0.000009208371,"about_ca_system_score_gemma":0.000015158145,"threshold_uncertainty_score":0.999605},"labels":[],"label_agreement":null},{"id":"W2116157165","doi":"10.1002/met.1523","title":"Field trial of an automated ground‐based infrared cloud classification system","year":2015,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Campbell Scientific (Canada)","funders":"Met Office; Loughborough University; Technology Strategy Board","keywords":"Cloud computing; Remote sensing; Radar; Computer science; Meteorology; Environmental science; Lightning (connector); Field (mathematics); Detector; Infrared; Lightning detection; Real-time computing; Geology; Telecommunications; Thunderstorm; Geography; Operating system; Physics","score_opus":0.04387976260496429,"score_gpt":0.29262693654467775,"score_spread":0.24874717393971346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116157165","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7806482,0.00001161697,0.13006811,0.000987385,0.00014539703,0.0021190804,0.000023468801,0.0013267929,0.08466999],"genre_scores_gemma":[0.9764264,7.589885e-7,0.022787565,0.00018983151,0.00010118947,0.0002738091,0.0000888078,0.000011545316,0.00012007329],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99846363,0.000185383,0.000427162,0.00039583343,0.00032883504,0.00019917812],"domain_scores_gemma":[0.99860865,0.00017588702,0.00021203296,0.00073635625,0.00004732042,0.00021977266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052894145,0.00013616045,0.00021617576,0.00004215263,0.00014378216,0.000029430876,0.00036752105,0.0001842487,0.00008649748],"category_scores_gemma":[0.000096028976,0.00011339689,0.000072145216,0.000537289,0.00019057594,0.00009183095,0.000060766648,0.00013148981,0.00035575873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.040319413,0.016797587,0.005456705,0.00022711825,0.00026262895,0.000014896349,0.0018498015,0.024419365,0.20312616,0.2837426,0.07520925,0.34857446],"study_design_scores_gemma":[0.02658722,0.0052716606,0.02188539,0.000021525948,0.00023830586,0.000031223433,0.0013447203,0.742082,0.011378476,0.015379917,0.17473309,0.0010464949],"about_ca_topic_score_codex":0.00019350146,"about_ca_topic_score_gemma":0.000015342912,"teacher_disagreement_score":0.71766263,"about_ca_system_score_codex":0.0001339829,"about_ca_system_score_gemma":0.00003093087,"threshold_uncertainty_score":0.4624191},"labels":[],"label_agreement":null},{"id":"W2124476392","doi":"10.1002/met.52","title":"Forecast verification: current status and future directions","year":2008,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":301,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Computer science; Forecast verification; Event (particle physics); Process (computing); Functional verification; Data verification; Verification and validation of computer simulation models; Software verification; Data science; Operations research; Formal verification; Data mining; Software; Forecast skill; Software development; Geography; Meteorology","score_opus":0.03968620783540099,"score_gpt":0.2469762135315269,"score_spread":0.2072900056961259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124476392","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9298806,0.019784901,0.00920349,0.0027752498,0.00041804597,0.0013399342,0.00033173384,0.00048730324,0.035778705],"genre_scores_gemma":[0.9883618,0.0061620115,0.004222546,0.00024209602,0.0005120541,0.000100439494,0.00028868663,0.0000036027927,0.000106775355],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986864,0.00009476082,0.00027374207,0.00041973073,0.00017996045,0.00034545473],"domain_scores_gemma":[0.99902827,0.0002552787,0.00007588612,0.00027795133,0.00006324702,0.0002993962],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00014272796,0.00015826599,0.00019574095,0.00007402864,0.0008531893,0.000030458268,0.0001581263,0.00009941267,0.0029458092],"category_scores_gemma":[0.000034060948,0.00011385236,0.00006403891,0.00047462725,0.00030056608,0.00012767641,0.000018414335,0.00022404657,0.00032533493],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035256882,0.00015034508,0.29845166,0.000009566973,0.00002246989,0.0000020829655,0.00018785243,0.00031562656,0.000033566186,0.022020752,0.0003594431,0.67841136],"study_design_scores_gemma":[0.00010323372,0.00005947039,0.5033866,3.657284e-7,0.0000105809395,0.000009963881,0.000018485429,0.0007824739,0.0000021139645,0.0068779206,0.4886545,0.000094301475],"about_ca_topic_score_codex":0.000047848098,"about_ca_topic_score_gemma":0.000051825406,"teacher_disagreement_score":0.67831707,"about_ca_system_score_codex":0.0000063650036,"about_ca_system_score_gemma":0.000025339097,"threshold_uncertainty_score":0.99796563},"labels":[],"label_agreement":null},{"id":"W2157642650","doi":"10.1017/s1350482705001775","title":"The evolution and retreat features of the summer monsoon over India","year":2005,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Climate variability and models","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Monsoon; Climatology; Environmental science; Diabatic; Bay; BENGAL; Troposphere; Monsoon of South Asia; East Asian Monsoon; Atmospheric sciences; Geology; Oceanography","score_opus":0.01334304951929141,"score_gpt":0.2414880267497679,"score_spread":0.2281449772304765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157642650","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9778722,0.00015221635,0.00083646236,0.0031704104,0.0000117175605,0.00043071152,0.000011731715,0.00001898328,0.017495554],"genre_scores_gemma":[0.99849814,0.00004921088,0.0006709911,0.00024223933,0.000017211149,0.00013896257,0.0000018811966,0.0000025440472,0.0003787911],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99939823,0.000061677965,0.00012102372,0.00017257287,0.00012501056,0.000121507954],"domain_scores_gemma":[0.9994136,0.00019090752,0.000051361643,0.00030696334,0.0000040004707,0.000033183056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002126204,0.000061066276,0.00006436804,0.0000046640503,0.0002867474,0.0000113199385,0.00019874367,0.000069137575,0.0002663775],"category_scores_gemma":[0.000046136152,0.00002927654,0.000039376217,0.00016540915,0.00045837494,0.00004490159,0.00022047099,0.000104861676,0.000031679672],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000083154206,0.0006201087,0.6990524,0.000009406039,0.00003380715,1.5809951e-7,0.00053096336,0.003407447,0.051452506,0.15836461,0.009516881,0.07692858],"study_design_scores_gemma":[0.00007988902,0.000018128465,0.9281332,7.3884127e-7,0.000017174338,0.0000017051933,0.000018820832,0.0006097199,0.00031739436,0.02044247,0.050312113,0.000048671172],"about_ca_topic_score_codex":0.0001546489,"about_ca_topic_score_gemma":0.00026184737,"teacher_disagreement_score":0.2290808,"about_ca_system_score_codex":0.00006685855,"about_ca_system_score_gemma":0.0000025771028,"threshold_uncertainty_score":0.29166466},"labels":[],"label_agreement":null},{"id":"W2191731587","doi":"10.1002/met.1541","title":"Observed regional climatic changes over Ontario, Canada, in response to global warming","year":2015,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Climate variability and models","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University; University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Precipitation; Environmental science; Climatology; Mean radiant temperature; Global warming; Climate change; Physical geography; Geography; Meteorology; Ecology; Geology","score_opus":0.08962598979921199,"score_gpt":0.27738261351580684,"score_spread":0.18775662371659485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2191731587","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.987267,0.000009959409,0.0012294888,0.008335436,0.000025161165,0.0005403226,0.000029525945,0.000030261936,0.0025327983],"genre_scores_gemma":[0.9893787,0.00000123086,0.006150454,0.0034883558,0.0000155604,0.00061454886,0.000016946771,0.000004438062,0.0003297483],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986825,0.00013053657,0.00021101032,0.0003711809,0.00029669312,0.00030808398],"domain_scores_gemma":[0.9991687,0.00019089495,0.00004166815,0.00031286792,0.00001072273,0.00027516417],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00077435275,0.00011452475,0.00016086512,0.000015667056,0.00007513832,0.000014767908,0.00028230183,0.000076759025,0.0010128156],"category_scores_gemma":[0.00014123143,0.00009810113,0.000025308946,0.0003661662,0.00007689283,0.000050977284,0.00023881468,0.00010969973,0.00013546173],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001656503,0.001168127,0.9069945,0.000017482516,0.000023349423,0.000035188626,0.0021121157,0.03425541,0.009511025,0.007940478,0.030038003,0.006247771],"study_design_scores_gemma":[0.00036603186,0.00011138653,0.7758198,0.0000039314386,0.000009500315,0.0000056434046,0.000080863974,0.0011300622,0.000018819892,0.011198964,0.21105862,0.00019639073],"about_ca_topic_score_codex":0.74573374,"about_ca_topic_score_gemma":0.9885926,"teacher_disagreement_score":0.24285887,"about_ca_system_score_codex":0.0017972632,"about_ca_system_score_gemma":0.0001272261,"threshold_uncertainty_score":0.9999004},"labels":[],"label_agreement":null},{"id":"W2193034424","doi":"10.1002/met.1539","title":"Assessment of the benefits of the Chinese Public Weather Service","year":2015,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of Education and Child Care","funders":"National Key Research and Development Program of China; Nanjing University; China Meteorological Administration; National Natural Science Foundation of China","keywords":"China; Receipt; Service (business); Business; Gross domestic product; Product (mathematics); Public opinion; Agricultural economics; Geography; Marketing; Economic growth; Economics; Political science","score_opus":0.12574693504165219,"score_gpt":0.2538451467950771,"score_spread":0.1280982117534249,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2193034424","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96652496,0.00030201167,0.002378788,0.004149632,0.000068873735,0.0003913352,0.000088921275,0.0000081831695,0.026087282],"genre_scores_gemma":[0.99819964,0.000017165847,0.0009088861,0.00047367773,0.000026160467,0.00017233749,0.0000063733646,0.000005854545,0.00018989814],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99929285,0.00002721846,0.00037009706,0.00017155654,0.000042498526,0.00009577615],"domain_scores_gemma":[0.9990878,0.000043249198,0.00034240008,0.00046461629,0.000024530975,0.000037416936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048415991,0.00007130406,0.00017629983,0.00002211673,0.000064774336,0.000008001651,0.00043164965,0.000062468025,0.00022664705],"category_scores_gemma":[0.000045144912,0.00004203907,0.00008947976,0.00030104458,0.000092827984,0.000057279038,0.00017420009,0.00008072056,0.00007178561],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[6.3326434e-7,0.000101497666,0.7033264,0.0000032576015,0.000012493952,1.8309184e-9,0.000036621477,0.0009459951,0.00006138446,0.2951316,0.000043184227,0.00033695035],"study_design_scores_gemma":[0.00017046792,0.000016643107,0.9445414,0.0000010502642,0.0000053985245,4.3408247e-7,0.00002380048,0.0010406226,0.000042730535,0.049329575,0.0047812457,0.000046622194],"about_ca_topic_score_codex":0.000055221713,"about_ca_topic_score_gemma":0.000030408275,"teacher_disagreement_score":0.24580202,"about_ca_system_score_codex":0.000057405825,"about_ca_system_score_gemma":0.000014483431,"threshold_uncertainty_score":0.24816264},"labels":[],"label_agreement":null},{"id":"W2551310797","doi":"10.1002/met.1577","title":"Analysing heat exposure in two German cities by using meteorological data from both within and outside the urban area","year":2016,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung","keywords":"Altitude (triangle); Urban heat island; Distribution (mathematics); Quarter (Canadian coin); Meteorology; Geography; Environmental science; Population; Daytime; Climatology; Physical geography; Atmospheric sciences; Demography; Mathematics; Geology","score_opus":0.04941801650773666,"score_gpt":0.28800285676441373,"score_spread":0.23858484025667706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2551310797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9719922,0.00035024772,0.024892433,0.001461802,0.000018006214,0.00045566025,0.00022467997,0.0000599918,0.00054496457],"genre_scores_gemma":[0.994888,0.000033522618,0.004034398,0.00062647735,0.000055464076,0.00014399143,0.00011442853,0.000010666193,0.00009306466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981132,0.00025607427,0.00038004766,0.0007001746,0.000244283,0.00030619232],"domain_scores_gemma":[0.9984163,0.0005883018,0.00008571132,0.00079568283,0.00000674814,0.00010726377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006029719,0.00019004209,0.00024882218,0.00003151379,0.00025489865,0.000057525613,0.00059225864,0.00010138864,0.00066861743],"category_scores_gemma":[0.00008951738,0.0000976203,0.00003636689,0.00027447898,0.0006224484,0.00027338258,0.0005178507,0.00017958181,0.000057208865],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042986034,0.00015349656,0.69091,0.0000019789677,0.000041296553,0.000004843327,0.00041521163,0.0002596078,0.29771954,0.0007822087,0.0027785583,0.006890297],"study_design_scores_gemma":[0.0031157613,0.00034782977,0.8212591,0.000050038765,0.00051510293,0.000051763716,0.0006071841,0.046934906,0.008981859,0.08370826,0.032977596,0.00145061],"about_ca_topic_score_codex":0.0009913215,"about_ca_topic_score_gemma":0.000936063,"teacher_disagreement_score":0.28873768,"about_ca_system_score_codex":0.00009969275,"about_ca_system_score_gemma":0.000007864673,"threshold_uncertainty_score":0.73208916},"labels":[],"label_agreement":null},{"id":"W2567827994","doi":"10.1002/met.1606","title":"Observed changes in temperature extremes for the Beijing–Tianjin–Hebei region of China","year":2017,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Climate variability and models","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; National Key Research and Development Program of China; Higher Education Discipline Innovation Project","keywords":"Beijing; Environmental science; Climate change; Climatology; Context (archaeology); Global warming; China; Frost (temperature); Geography; Physical geography; Meteorology; Oceanography; Geology","score_opus":0.08258081660380946,"score_gpt":0.2842759754135588,"score_spread":0.20169515880974936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2567827994","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9721932,0.000097940356,0.0054087094,0.018995292,0.00004070275,0.0014950038,0.000040189192,0.000030411793,0.0016985827],"genre_scores_gemma":[0.99650866,0.00008146743,0.0018851999,0.00019423688,0.000037426522,0.0010693158,0.000010769179,0.0000052008895,0.00020770168],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924916,0.00003708972,0.00016203841,0.00027891918,0.00009743784,0.00017533249],"domain_scores_gemma":[0.9988799,0.00024789115,0.00012854856,0.0006989307,0.00000880453,0.000035939323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042738387,0.000090960326,0.00014937427,0.0000113048545,0.0004253883,0.00003230297,0.00059745123,0.000111226494,0.00018106672],"category_scores_gemma":[0.0001796961,0.00005507014,0.00006149214,0.00007832779,0.0003492729,0.00007091058,0.00020269038,0.00010966714,0.0000101581945],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043138713,0.0021170282,0.45079458,0.0001563954,0.00008228304,0.000004445608,0.0015910518,0.0058631995,0.32888672,0.0848777,0.0037782756,0.12141694],"study_design_scores_gemma":[0.0004465042,0.00011508497,0.92648715,0.000008570975,0.000037650112,0.0000026279238,0.00005536366,0.004119057,0.001857665,0.038929526,0.02777944,0.00016135236],"about_ca_topic_score_codex":0.00017514837,"about_ca_topic_score_gemma":0.0010036568,"teacher_disagreement_score":0.4756926,"about_ca_system_score_codex":0.000028233,"about_ca_system_score_gemma":0.0000035923772,"threshold_uncertainty_score":0.3271786},"labels":[],"label_agreement":null},{"id":"W2577990050","doi":"10.1002/met.1613","title":"Snowfall rate estimation using C‐band polarimetric radars","year":2017,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Impact; Barrie Urology Group; York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nowcasting; Snow; Radar; Remote sensing; Meteorology; Polarimetry; Environmental science; Precipitation; Weather radar; Algorithm; Computer science; Geology; Geography; Scattering; Physics","score_opus":0.07013505272315335,"score_gpt":0.2898276337778676,"score_spread":0.21969258105471423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2577990050","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6271986,0.0005371511,0.3509316,0.002002341,0.0001369889,0.0006312183,0.00009899697,0.00015079182,0.01831234],"genre_scores_gemma":[0.9786623,0.00002289667,0.020799406,0.00016058878,0.00007326716,0.000006873523,0.00010180627,0.0000020345944,0.00017081344],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99906635,0.00008559156,0.00020233437,0.00025935424,0.00019295412,0.00019341892],"domain_scores_gemma":[0.9991106,0.00013498933,0.00019764209,0.00038594578,0.00006529982,0.000105522166],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00061872526,0.00010328049,0.00015188826,0.00010954172,0.0010528592,0.00023075113,0.00040372557,0.0000706452,0.0011615467],"category_scores_gemma":[0.00025504013,0.00007019833,0.0000760711,0.00023856008,0.00011969226,0.00028035344,0.000013161175,0.000101770085,0.00039327555],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003036863,0.00007328415,0.72623086,0.000011540837,0.00008312476,0.0000025349889,0.000028070863,0.009972737,0.003961117,0.0012928294,0.00018246275,0.25813106],"study_design_scores_gemma":[0.00018966357,0.000031742104,0.92710066,0.0000022427716,0.00008092417,0.0000016183268,0.000008667395,0.0565482,0.00042490545,0.010795742,0.0046724216,0.00014322727],"about_ca_topic_score_codex":0.00083699817,"about_ca_topic_score_gemma":0.00024542786,"teacher_disagreement_score":0.35146374,"about_ca_system_score_codex":0.000006149071,"about_ca_system_score_gemma":0.000021397915,"threshold_uncertainty_score":0.9997515},"labels":[],"label_agreement":null},{"id":"W2738937980","doi":"10.1002/met.1661","title":"Forecasting soil temperature based on surface air temperature using a wavelet artificial neural network","year":2017,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Ste. Anne's Hospital","funders":"","keywords":"Artificial neural network; Environmental science; Wavelet transform; Frost (temperature); Meteorology; Air temperature; Surface air temperature; Wavelet; Computer science; Precipitation; Machine learning; Artificial intelligence; Geography","score_opus":0.049723444329044665,"score_gpt":0.2720255723570545,"score_spread":0.22230212802800983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2738937980","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914975,0.000012726851,0.000989502,0.003024975,0.0001496148,0.0006734627,0.000033442324,0.00022319859,0.003395548],"genre_scores_gemma":[0.9764722,8.8092827e-7,0.020246068,0.0025087562,0.00044854754,0.00010843215,0.000034495893,0.00003375888,0.0001468676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971822,0.00019464784,0.0004097262,0.00094208325,0.00045310528,0.00081825745],"domain_scores_gemma":[0.9979806,0.00029818574,0.00031258274,0.0011167657,0.00003037893,0.00026149602],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00073251716,0.00038504312,0.00038614433,0.000023342165,0.002966924,0.00025945206,0.00094822183,0.00044636798,0.0006476789],"category_scores_gemma":[0.00041345836,0.00028756913,0.00018025658,0.0003384364,0.0006948064,0.00016269785,0.00040287361,0.0008305055,0.00022261376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006786969,0.00017505346,0.0048648147,0.0000044288745,0.000007740149,0.000019423049,0.000012891661,0.96200824,0.028754344,0.000257098,0.00072471605,0.0031033838],"study_design_scores_gemma":[0.0003063254,0.0002858811,0.013793076,0.00002142827,0.000046939545,0.000027632248,0.00000440755,0.9741958,0.0020325189,0.004711726,0.0040573254,0.0005169404],"about_ca_topic_score_codex":0.00008019799,"about_ca_topic_score_gemma":0.000055672128,"teacher_disagreement_score":0.026721826,"about_ca_system_score_codex":0.00014123892,"about_ca_system_score_gemma":0.000019781355,"threshold_uncertainty_score":0.9999576},"labels":[],"label_agreement":null},{"id":"W2790688155","doi":"10.1002/met.1713","title":"Modelling weather risk preferences with multi‐criteria decision analysis for an aerospace vehicle launch","year":2018,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Instituto Tecnológico de Aeronáutica","keywords":"Computer science; Operations research; Decision support system; Consensus forecast; Decision analysis; Probabilistic logic; Econometrics; Economics; Engineering; Data mining","score_opus":0.16819125476795363,"score_gpt":0.4021588714709599,"score_spread":0.23396761670300628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790688155","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36382082,0.000058528367,0.63503414,0.00024529648,0.000013079094,0.00036103665,0.00008737194,0.000057557714,0.00032213723],"genre_scores_gemma":[0.7139253,0.000061746316,0.28504798,0.00008312994,0.00009180517,0.00039521925,0.000023300248,0.0000088346305,0.00036268425],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968227,0.00030988848,0.00063972815,0.0011042249,0.0007616235,0.00036180217],"domain_scores_gemma":[0.99554926,0.0018291688,0.00034014432,0.0012116571,0.0008352368,0.00023450391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025961052,0.0002203113,0.0005537292,0.00031487164,0.0008670894,0.00029924934,0.001068165,0.00017427106,0.0007454476],"category_scores_gemma":[0.0003915417,0.00012364019,0.0003126221,0.002988787,0.0003556677,0.0002886643,0.00009869571,0.00014910068,0.0002570693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012835934,0.0014716008,0.19149463,0.000003928542,0.0011642628,9.770575e-7,0.0014022527,0.33621326,0.0016099545,0.006583198,0.00080863375,0.4579637],"study_design_scores_gemma":[0.00039829774,0.00052380114,0.020105533,0.0000015850525,0.00058590056,5.552835e-7,0.00030935073,0.83068424,0.00018292246,0.131868,0.015109213,0.00023058939],"about_ca_topic_score_codex":0.00024295074,"about_ca_topic_score_gemma":0.0016764421,"teacher_disagreement_score":0.49447098,"about_ca_system_score_codex":0.000021555157,"about_ca_system_score_gemma":0.000026659121,"threshold_uncertainty_score":0.81621283},"labels":[],"label_agreement":null},{"id":"W2893128609","doi":"10.1002/met.1740","title":"Predicting major peach yield reductions in the Midwest and Southeast United States","year":2018,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Plant Physiology and Cultivation Studies","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Yield (engineering); Crop; Geopotential height; Growing degree-day; Nova scotia; Environmental science; Spring (device); Geography; Physical geography; Climatology; Meteorology; Agronomy; Forestry; Phenology; Archaeology; Geology; Precipitation; Biology","score_opus":0.03538716860065957,"score_gpt":0.2428891322044856,"score_spread":0.20750196360382603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893128609","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98946816,0.00008025754,0.000049130587,0.00858846,0.000015130469,0.0002737813,0.00008056498,0.000058737452,0.001385776],"genre_scores_gemma":[0.9981672,0.000049640938,0.000089927395,0.00089062884,0.00021202529,0.00033716427,0.0001774002,3.8500306e-7,0.00007562072],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99927276,0.00010440256,0.0001553047,0.00022453968,0.00007290798,0.00017006282],"domain_scores_gemma":[0.9991917,0.00062339916,0.00005013014,0.00005087037,0.00005265769,0.000031238564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002596147,0.0000857086,0.00009944886,0.000014016442,0.00065541937,0.000025291103,0.00017602037,0.00007212636,0.0001253765],"category_scores_gemma":[0.00008013794,0.000027079466,0.000024218036,0.0005300101,0.00034140825,0.000041256248,0.000054430904,0.00014770639,0.00003557727],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022762957,0.0013996657,0.18667136,0.000016649165,0.00013373332,0.0000048724246,0.003781641,0.000033102282,0.69065565,0.07485497,0.0067006927,0.03552006],"study_design_scores_gemma":[0.00008878461,0.00021606017,0.93141633,0.0000057257157,0.000020190213,0.000019143019,0.0055739293,0.00014005872,0.0003302505,0.010830125,0.051234033,0.00012538821],"about_ca_topic_score_codex":0.000117727526,"about_ca_topic_score_gemma":0.00046197744,"teacher_disagreement_score":0.74474496,"about_ca_system_score_codex":0.000003942028,"about_ca_system_score_gemma":0.0000015648546,"threshold_uncertainty_score":0.50410223},"labels":[],"label_agreement":null},{"id":"W2893947668","doi":"10.1002/met.1737","title":"Solid snowfall rate estimation using a C‐band radar","year":2018,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Impact; Barrie Urology Group; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada","keywords":"Snow; Radar; Environmental science; Snow removal; Meteorology; Remote sensing; Computer science; Geology; Geography","score_opus":0.053131480423299286,"score_gpt":0.30045723661330537,"score_spread":0.24732575619000607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893947668","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44885746,0.00015134981,0.5395609,0.0010064333,0.00008364238,0.00043986738,0.000047331185,0.00016364572,0.00968937],"genre_scores_gemma":[0.9693146,0.00000905148,0.029814996,0.00042305645,0.0001815319,0.000011586835,0.00011324792,0.0000020346674,0.0001299321],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990583,0.00010519861,0.00021650964,0.00025311808,0.00016845048,0.00019844402],"domain_scores_gemma":[0.99941987,0.00011389117,0.000090670204,0.00017837773,0.00010010431,0.00009709358],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00048881007,0.000098663695,0.00013734409,0.000072880066,0.0003684179,0.00006046829,0.00017985444,0.000061165,0.0030953013],"category_scores_gemma":[0.000070730835,0.00006565814,0.00005896332,0.0004230253,0.00015381225,0.00013865216,0.0000068355635,0.00007147134,0.00100099],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025663903,0.00039447402,0.2478684,0.00004990912,0.00040386012,0.0000067338065,0.0006056603,0.024963846,0.10834257,0.005613245,0.0027339316,0.6087607],"study_design_scores_gemma":[0.00073155627,0.0004015737,0.34010765,0.000012126888,0.00030818215,0.000010224893,0.00009097017,0.53605944,0.012226602,0.07130496,0.038098283,0.0006484549],"about_ca_topic_score_codex":0.00010623105,"about_ca_topic_score_gemma":0.00022140962,"teacher_disagreement_score":0.6081123,"about_ca_system_score_codex":0.000005246012,"about_ca_system_score_gemma":0.000020854197,"threshold_uncertainty_score":0.99977684},"labels":[],"label_agreement":null},{"id":"W2995940717","doi":"10.1002/met.1861","title":"Climate indices to characterize climatic changes across southern Canada","year":2019,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Climate variability and models","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; McMaster University Medical Centre; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Natural Resources Canada; Environment and Climate Change Canada; U.S. Department of Energy","keywords":"Precipitation; Coupled model intercomparison project; Environmental science; Climatology; Climate change; Frost (temperature); Bay; Maximum temperature; Climate model; Global warming; Representative Concentration Pathways; Atmospheric sciences; Geography; Meteorology; Geology; Oceanography","score_opus":0.02088791956827635,"score_gpt":0.24753547650733024,"score_spread":0.2266475569390539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995940717","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99184525,0.00000672119,0.00039750632,0.0030506286,0.00004557265,0.0009496034,0.00053071964,0.00007241988,0.0031015745],"genre_scores_gemma":[0.9938415,0.0000146249695,0.00134133,0.0036174422,0.000030843603,0.0007786057,0.000071226736,0.000011348512,0.00029306923],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985261,0.00005000104,0.00021860095,0.00045907756,0.0002453801,0.0005008601],"domain_scores_gemma":[0.9991256,0.00014844356,0.00008362306,0.00044968084,0.000008373312,0.0001842854],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00039963506,0.00014636907,0.00020974735,0.000009235028,0.00020049427,0.000036829628,0.00040176613,0.00008322626,0.0048378124],"category_scores_gemma":[0.000025082134,0.00011459066,0.000037025442,0.00025891248,0.000077732155,0.00005471883,0.00042285534,0.000121470424,0.0042466754],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018489783,0.0009977861,0.64592,0.0002086981,0.00006272055,0.000007696965,0.0043991073,0.0038906347,0.2618988,0.004944961,0.0014645244,0.076020196],"study_design_scores_gemma":[0.0006524106,0.0003610864,0.5129166,0.000019333698,0.00004994642,0.000011498749,0.0012778937,0.0029814963,0.0010174399,0.0033693402,0.4763381,0.0010048661],"about_ca_topic_score_codex":0.032893457,"about_ca_topic_score_gemma":0.20508477,"teacher_disagreement_score":0.47487354,"about_ca_system_score_codex":0.00013024666,"about_ca_system_score_gemma":0.000011130007,"threshold_uncertainty_score":0.9965286},"labels":[],"label_agreement":null},{"id":"W3044770889","doi":"10.1002/met.1929","title":"Monitoring the impacts of weather radar data quality control for quantitative application at the continental scale","year":2020,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Radar; Weather radar; Data quality; Environmental science; Computer science; Remote sensing; Data set; Meteorology; Metric (unit); Geography; Artificial intelligence; Engineering; Telecommunications","score_opus":0.10049406146944136,"score_gpt":0.3287690514529475,"score_spread":0.22827498998350615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044770889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5966114,0.0020650376,0.36548927,0.025761882,0.00008939931,0.0044138604,0.0033407458,0.00011190389,0.0021165267],"genre_scores_gemma":[0.99375635,0.000030535695,0.0045255623,0.00095444283,0.00016245859,0.00015687529,0.0003829633,0.0000040370687,0.000026758296],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983427,0.00027908912,0.00045910923,0.00042878336,0.00024115032,0.00024919186],"domain_scores_gemma":[0.99541,0.0034666942,0.00026553133,0.0006390014,0.00008776454,0.00013097425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010319941,0.00014353517,0.0002778016,0.000012718256,0.0005557148,0.00003141911,0.000922302,0.00007810079,0.00032327586],"category_scores_gemma":[0.00041322078,0.00006907859,0.00010435697,0.0002895042,0.00038985882,0.000099633595,0.00007754595,0.00014875631,0.00009847838],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020221653,0.00035867374,0.7908761,0.000093376184,0.0003844215,4.8062446e-7,0.0012407303,0.0101738395,0.050345015,0.03482572,0.0016891082,0.10799036],"study_design_scores_gemma":[0.001307932,0.0005180142,0.8771734,0.0000034402954,0.0001866891,0.0000015456353,0.0006174013,0.053365067,0.0008847699,0.015061421,0.05060346,0.00027686163],"about_ca_topic_score_codex":0.00020049686,"about_ca_topic_score_gemma":0.00019484857,"teacher_disagreement_score":0.397145,"about_ca_system_score_codex":0.000005699812,"about_ca_system_score_gemma":0.000017816812,"threshold_uncertainty_score":0.4274165},"labels":[],"label_agreement":null},{"id":"W3093008217","doi":"10.1002/met.1953","title":"Malaria and meningitis under climate change: initial assessment of climate information service in Nigeria","year":2020,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Malaria Research and Control","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Global Affairs Canada; Department for International Development, UK Government; International Development Research Centre; Government of Canada","keywords":"Malaria; Climate change; Early warning system; Meningitis; Warning system; Geography; Environmental science; Ecology; Medicine; Biology; Immunology; Pediatrics","score_opus":0.0449273534537175,"score_gpt":0.3422412484735754,"score_spread":0.2973138950198579,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093008217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6601087,0.0003185169,0.048862424,0.25229052,0.00004893289,0.007897349,0.00054199935,0.00028798103,0.029643618],"genre_scores_gemma":[0.9898606,0.00027192206,0.004055044,0.0044451137,0.00006807059,0.0011511974,0.00014144626,0.0000056530366,9.833957e-7],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99892664,0.00006848381,0.00035393942,0.00017492642,0.00020433482,0.00027165285],"domain_scores_gemma":[0.9993654,0.000094682066,0.000095425494,0.00014746896,0.000110831614,0.00018622981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003058392,0.00010117649,0.0002815993,0.00007318514,0.00005910249,0.000024525814,0.00008978568,0.000106239604,0.0002680174],"category_scores_gemma":[0.00005299534,0.00008199623,0.000035269106,0.0003717386,0.000051597806,0.00016761418,0.00013226813,0.00022236754,0.000029044242],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021168962,0.0007789926,0.09420186,0.0015554192,0.00017633887,0.00002795604,0.0013780736,0.00009577202,0.03131195,0.76817405,0.00008834639,0.10009432],"study_design_scores_gemma":[0.0034767832,0.0007600284,0.97349626,0.000028563696,0.00006757408,0.00001658554,0.0003757508,0.016134406,0.0002673591,0.0018154191,0.00339899,0.0001622893],"about_ca_topic_score_codex":0.00002313653,"about_ca_topic_score_gemma":0.000020909292,"teacher_disagreement_score":0.8792944,"about_ca_system_score_codex":0.000022170883,"about_ca_system_score_gemma":0.000034680244,"threshold_uncertainty_score":0.3343709},"labels":[],"label_agreement":null},{"id":"W3125471724","doi":"10.1002/met.1976","title":"A comparison of statistical and dynamical downscaling methods for short‐term weather forecasts in the <scp>US N</scp>ortheast","year":2021,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Climate variability and models","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian International Development Agency; National Center for Atmospheric Research","keywords":"Weather Research and Forecasting Model; Downscaling; Meteorology; Environmental science; Global Forecast System; Climatology; Probabilistic logic; Precipitation; Numerical weather prediction; Hydrometeorology; Computer science; Geography; Statistics; Mathematics","score_opus":0.05579028710138205,"score_gpt":0.37830588151369215,"score_spread":0.3225155944123101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125471724","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46976715,0.00005321928,0.5282657,0.00022071996,0.000009285933,0.0004928003,0.0000560946,0.000011343405,0.00112368],"genre_scores_gemma":[0.8339658,0.0000103474895,0.16522425,0.00013415105,0.00001061168,0.0005913074,0.000043771746,0.0000054352304,0.000014378214],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986619,0.00026589204,0.00034925106,0.00036594764,0.000121185934,0.00023582223],"domain_scores_gemma":[0.9970454,0.0025527873,0.000047522088,0.00027060654,0.000014123309,0.000069535716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009452719,0.00010750201,0.0002661797,0.000014920131,0.00010735366,0.000022410302,0.00019589339,0.00011018988,0.00012493323],"category_scores_gemma":[0.00028995503,0.0000719533,0.00006009625,0.00020907764,0.0003421031,0.00003451537,0.00015225189,0.00015788274,0.000005681297],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045534776,0.0031767362,0.53908277,0.00009972154,0.000047611793,0.0000036896806,0.0022291963,0.003266186,0.07991894,0.14833131,0.00018943257,0.22360885],"study_design_scores_gemma":[0.0005835533,0.00031859413,0.41777584,0.000010375138,0.00015153916,0.00003388937,0.0007560846,0.39222595,0.0018202278,0.16494185,0.021219758,0.00016234274],"about_ca_topic_score_codex":0.000020788295,"about_ca_topic_score_gemma":0.00011044985,"teacher_disagreement_score":0.38895977,"about_ca_system_score_codex":0.00002873393,"about_ca_system_score_gemma":0.0000070642745,"threshold_uncertainty_score":0.29341704},"labels":[],"label_agreement":null},{"id":"W4211252315","doi":"10.1002/met.2043","title":"Intercomparison of atmospheric forcing datasets and two<scp>PBL</scp>schemes for precipitation modelling over a coastal valley in northern British Columbia, Canada","year":2022,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Climate variability and models","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Northern British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Forcing (mathematics); Precipitation; Weather Research and Forecasting Model; Environmental science; Climatology; Mesoscale meteorology; Downscaling; Climate model; Meteorology; Atmospheric sciences; Climate change; Geography; Geology","score_opus":0.01699093751617984,"score_gpt":0.23276179908155264,"score_spread":0.2157708615653728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211252315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88096213,0.00004402089,0.11729711,0.000040129737,0.000013009202,0.00075383316,0.0007494496,0.000013345488,0.00012695449],"genre_scores_gemma":[0.9837203,0.000008454122,0.014470886,0.00009611041,0.0000063445505,0.0012564614,0.00039133464,0.000007952326,0.000042136206],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998896,0.00006182945,0.00030243996,0.00035842747,0.0001780718,0.00020323113],"domain_scores_gemma":[0.99924594,0.0004020748,0.00010925851,0.00017516017,0.000008309709,0.00005925608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033813049,0.00007294579,0.0001818667,0.0000043458253,0.00022356301,0.00003297997,0.00018845462,0.000032329815,0.00013360726],"category_scores_gemma":[0.000045522713,0.00010078386,0.000031570722,0.00019055083,0.00008408635,0.00008366501,0.00031634685,0.000121512465,6.74091e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016296235,0.0004040232,0.51580566,0.00003523433,0.00001574803,0.0000011552934,0.0002792635,0.4742428,0.0010174968,0.00030760144,0.000860335,0.0070143733],"study_design_scores_gemma":[0.00090746203,0.00017128591,0.059659183,0.0000068836057,0.00003806305,0.000007875451,0.0006656791,0.885145,0.00003469885,0.0149829965,0.03823864,0.00014224308],"about_ca_topic_score_codex":0.6581609,"about_ca_topic_score_gemma":0.9679143,"teacher_disagreement_score":0.4561465,"about_ca_system_score_codex":0.00014662433,"about_ca_system_score_gemma":0.000027757396,"threshold_uncertainty_score":0.41098464},"labels":[],"label_agreement":null},{"id":"W4282840247","doi":"10.1002/met.2078","title":"End‐user satisfaction with Hurricane Dorian information in Atlantic Canada","year":2022,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Ocean Frontier Institute; National Science Foundation","keywords":"Storm; Context (archaeology); Storm track; Winter storm; Climate change; Meteorology; Environmental science; History; Geography","score_opus":0.008972515051726542,"score_gpt":0.18764454236460443,"score_spread":0.17867202731287787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282840247","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98407644,0.000050006038,0.0032002723,0.0013060969,0.0000788188,0.00076699007,0.00019187431,0.00007255182,0.010256952],"genre_scores_gemma":[0.9968791,0.0000053310155,0.0010846622,0.0011598339,0.000031532476,0.00019325993,0.00058108347,0.0000019368747,0.00006323233],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986367,0.00015754908,0.00030882505,0.00022512754,0.0003824789,0.00028931175],"domain_scores_gemma":[0.99925745,0.00028334634,0.000107310974,0.00020390665,0.00002975942,0.000118202435],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00027282818,0.00012272816,0.00017417003,0.00009630137,0.0004596128,0.000031496755,0.00021076361,0.000038838018,0.012455511],"category_scores_gemma":[0.000028629103,0.000089245084,0.000025391078,0.0007145336,0.000058627782,0.00018984976,0.000025467116,0.00029236704,0.00009193735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000066,0.000027457558,0.838064,0.000003865907,0.0000090461535,0.0000047529093,0.000033760145,0.14213257,0.000010260521,0.004750533,0.0002988191,0.014598913],"study_design_scores_gemma":[0.00029317697,0.00018951263,0.88338476,5.112685e-7,0.000010079763,0.0000103891525,0.00013449918,0.0046560573,0.0000011227949,0.00249556,0.108682126,0.00014219554],"about_ca_topic_score_codex":0.4537951,"about_ca_topic_score_gemma":0.6536595,"teacher_disagreement_score":0.19986443,"about_ca_system_score_codex":0.000053941312,"about_ca_system_score_gemma":0.00013108442,"threshold_uncertainty_score":0.98844725},"labels":[],"label_agreement":null},{"id":"W4386886088","doi":"10.1002/met.2148","title":"Understanding your audience: The influence of social media user‐type on informational behaviors and hazard adjustments during <scp>Hurricane Dorian</scp>","year":2023,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Public Relations and Crisis Communication","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Storm; Preparedness; Landfall; Hazard; Internet privacy; Information sharing; Psychology; Business; Computer science; Political science; World Wide Web; Geography; Meteorology; Ecology","score_opus":0.09619188982705643,"score_gpt":0.3379433526387026,"score_spread":0.2417514628116462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386886088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.991532,0.000033391236,0.00023096615,0.002411935,0.0000370274,0.00040040212,0.000021726588,0.00010696891,0.0052255373],"genre_scores_gemma":[0.9988396,0.00037363303,0.00017593366,0.000086972985,0.000060794853,0.00028422163,0.000041037263,0.00000486611,0.00013292671],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9986635,0.00016420694,0.00030004038,0.00016748438,0.00045588025,0.000248927],"domain_scores_gemma":[0.99834484,0.0010043137,0.00020370838,0.00022814648,0.00013830289,0.00008071701],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00080841366,0.000092805145,0.00013244057,0.00012825368,0.0016396291,0.000070262206,0.0004592298,0.00012918003,0.00002757455],"category_scores_gemma":[0.000714983,0.000069165,0.000045388137,0.0013512354,0.00057494413,0.00024861578,0.0001437622,0.00020637244,0.000049632385],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008681484,0.00010225382,0.013571355,0.000007612238,0.000028389446,3.141024e-7,0.01554835,0.00079536205,0.0005879039,0.96716684,0.0008731428,0.0013098068],"study_design_scores_gemma":[0.00021142553,0.000043359476,0.9376075,0.0000055736587,0.000035216024,7.19036e-7,0.015116762,0.00009182635,0.000026125552,0.022219595,0.024578253,0.0000636026],"about_ca_topic_score_codex":0.00002784834,"about_ca_topic_score_gemma":0.00006251762,"teacher_disagreement_score":0.94494724,"about_ca_system_score_codex":0.00011991132,"about_ca_system_score_gemma":0.0000709139,"threshold_uncertainty_score":0.9996601},"labels":[],"label_agreement":null},{"id":"W4387850251","doi":"10.1002/met.2152","title":"Testing the suitability of Marginal Distribution Sampling as a gap‐filling method using some meteorological data from seven sites in West Africa","year":2023,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Global Affairs Canada; African Institute for Mathematical Sciences; United Nations Educational, Scientific and Cultural Organization; Organization for Women in Science for the Developing World; International Development Research Centre; Division of Mathematical Sciences; Government of Canada","keywords":"Environmental science; Homogeneity (statistics); Missing data; Statistics; Relative humidity; Meteorology; Shortwave; Sampling (signal processing); Climatology; Atmospheric sciences; Mathematics; Computer science; Geography","score_opus":0.1772992024502087,"score_gpt":0.3550591201380399,"score_spread":0.17775991768783123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387850251","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89378434,0.00011064486,0.10383853,0.00093888503,0.000013474314,0.0004112973,0.00038112,0.000103312705,0.0004184115],"genre_scores_gemma":[0.9494291,0.000012402484,0.049561873,0.000112309,0.000055852906,0.00016013766,0.0006484483,0.000008107389,0.000011796304],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997192,0.0006034989,0.00056383736,0.0008382731,0.0003091245,0.00049323356],"domain_scores_gemma":[0.99481416,0.0039298255,0.00021201318,0.0009303769,0.00002130684,0.000092340895],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003242386,0.00019421444,0.00039358085,0.000048150552,0.00040671413,0.00002723626,0.0010539118,0.00021794852,0.0010251657],"category_scores_gemma":[0.0015897276,0.00013176515,0.00009612002,0.0018412813,0.0004918857,0.00021180605,0.0011555046,0.00038938073,0.00033361316],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000135413,0.00065122097,0.6042093,0.000015044171,0.0001273645,0.000015420155,0.00039654007,0.098268814,0.27881822,0.0038540426,0.00013874244,0.013369855],"study_design_scores_gemma":[0.000240956,0.00008287352,0.52840364,0.0000054399043,0.00022520937,0.000008044172,0.00018192499,0.31676716,0.00067488593,0.150588,0.0025513466,0.0002704964],"about_ca_topic_score_codex":0.001105945,"about_ca_topic_score_gemma":0.00017755199,"teacher_disagreement_score":0.27814335,"about_ca_system_score_codex":0.000095235,"about_ca_system_score_gemma":0.000017806644,"threshold_uncertainty_score":0.999888},"labels":[],"label_agreement":null},{"id":"W4401151211","doi":"10.1002/met.2221","title":"Utilization of the Google Earth Engine for the evaluation of daily soil temperature derived from Global Land Data Assimilation System in two different depths over a semiarid region","year":2024,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Environmental science; Data assimilation; Climatology; Meteorology; Geology; Geography","score_opus":0.05917011806944184,"score_gpt":0.3157639452543982,"score_spread":0.2565938271849564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401151211","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9605515,0.0005914551,0.036366723,0.0005041756,0.000102071834,0.0011771028,0.00009505769,0.000030823216,0.0005811065],"genre_scores_gemma":[0.9991413,0.000017336359,0.00048815546,0.000042058775,0.000059744543,0.000053844138,0.0001836147,0.00000540714,0.000008570834],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99889624,0.00014815803,0.00024313491,0.0002970454,0.00031715332,0.00009827347],"domain_scores_gemma":[0.999073,0.00029003056,0.00009624207,0.00049499504,0.000026169782,0.000019554613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041973375,0.000094994255,0.0001299691,0.000012961148,0.00009324194,0.000022169459,0.00027263717,0.000083551466,0.000013259003],"category_scores_gemma":[0.000080113285,0.000047459514,0.00005078831,0.00035663066,0.000100019795,0.00006655543,0.00014412076,0.00009838972,0.0000022482775],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015671931,0.00036070548,0.26832977,0.00013515186,0.00017135928,0.0000010395146,0.00064920995,0.14223161,0.11041766,0.0024018302,0.00093854347,0.47420642],"study_design_scores_gemma":[0.00023685167,0.00001037802,0.61776125,0.000028035034,0.00012213236,0.0000012703529,0.00004232381,0.3783458,0.002179496,0.00085810747,0.00037200557,0.000042353327],"about_ca_topic_score_codex":0.00044431078,"about_ca_topic_score_gemma":0.0045765517,"teacher_disagreement_score":0.47416404,"about_ca_system_score_codex":0.00010107397,"about_ca_system_score_gemma":0.00001844631,"threshold_uncertainty_score":0.25538233},"labels":[],"label_agreement":null},{"id":"W4406133577","doi":"10.1002/met.70023","title":"Estimating latent heat flux of subtropical forests using machine learning algorithms","year":2025,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Latent heat; Subtropics; Flux (metallurgy); Computer science; Heat flux; Algorithm; Machine learning; Meteorology; Artificial intelligence; Environmental science; Geography; Heat transfer; Physics; Materials science","score_opus":0.015405402063824656,"score_gpt":0.2515420585237566,"score_spread":0.23613665645993195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406133577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61054194,0.000038114875,0.38751686,0.00013300584,0.000021341251,0.00020541773,0.000010615664,0.000045223536,0.0014874504],"genre_scores_gemma":[0.91063744,0.000003900512,0.08885361,0.00005351101,0.000011849063,0.0000694413,0.00004873265,0.0000046880077,0.00031682375],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999131,0.00005170502,0.00026288463,0.00023990042,0.00013393542,0.00018057696],"domain_scores_gemma":[0.99963427,0.00008668409,0.000051718358,0.00016738947,0.000009598103,0.00005036332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015138747,0.00009900314,0.00015977402,0.00003764037,0.00017891025,0.000013701225,0.00017922612,0.000086923756,0.0002578043],"category_scores_gemma":[0.000029981165,0.00007782611,0.00006117104,0.00034034814,0.00014430835,0.000045677203,0.00018859205,0.00018069074,0.000036459543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010872267,0.00015744082,0.4999987,0.000010942635,0.000022375123,0.0000018542715,0.00002423545,0.45904133,0.024226375,0.005095952,0.000013927236,0.011396005],"study_design_scores_gemma":[0.00012488732,0.000031664327,0.051681057,0.0000053398735,0.00003048142,0.0000055028845,0.000001825231,0.9407377,0.0005460319,0.0053760386,0.0013823622,0.00007708903],"about_ca_topic_score_codex":0.00021154237,"about_ca_topic_score_gemma":0.000051326697,"teacher_disagreement_score":0.4816964,"about_ca_system_score_codex":0.00006688002,"about_ca_system_score_gemma":0.0000060495713,"threshold_uncertainty_score":0.31736568},"labels":[],"label_agreement":null},{"id":"W4416388507","doi":"10.1002/met.70129","title":"On the Reliability of Surface Observations and the Pitfalls of Verification Against Own Analyses","year":2025,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Radiosonde; Data assimilation; Representativeness heuristic; Humidity; Numerical weather prediction; Reliability (semiconductor)","score_opus":0.06125127307162563,"score_gpt":0.2842994448043285,"score_spread":0.22304817173270286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416388507","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9755703,0.00033473145,0.0074214865,0.006031098,0.000020924293,0.00075958914,0.00012566491,0.000022206823,0.009713969],"genre_scores_gemma":[0.997624,0.00008373714,0.0012990264,0.0008176082,0.000008113916,0.000036919,0.00004976539,0.0000010267414,0.00007980029],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.998624,0.00038958286,0.00042785957,0.00023597087,0.00020049173,0.000122048776],"domain_scores_gemma":[0.9921167,0.0070004486,0.00017868943,0.00050605333,0.00016322172,0.000034878656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001249425,0.00009936577,0.00024294242,0.000035197732,0.0003119049,0.000017060698,0.00034976692,0.00007253496,0.00025944225],"category_scores_gemma":[0.0012982523,0.00004372915,0.000090420835,0.0006935483,0.0008628237,0.00004156725,0.000025118905,0.00014577332,0.000008154557],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019773534,0.00015660549,0.15260829,0.000026095064,0.00005515441,5.5588654e-8,0.00008645903,0.09996037,0.0016220311,0.74110866,0.00026675692,0.0039117835],"study_design_scores_gemma":[0.00025423992,0.000057597408,0.7693835,0.0000036471756,0.00005140529,6.662589e-8,0.000053489955,0.014958179,0.00020093135,0.21337819,0.0016066032,0.000052152252],"about_ca_topic_score_codex":0.00015730095,"about_ca_topic_score_gemma":0.000042644428,"teacher_disagreement_score":0.6167752,"about_ca_system_score_codex":0.0000039572724,"about_ca_system_score_gemma":0.000029985038,"threshold_uncertainty_score":0.31791097},"labels":[],"label_agreement":null},{"id":"W4417147657","doi":"10.1002/met.70133","title":"Neighborhood‐Based Verification of Precipitation Forecasts at the Local Scale: An Application Over Southern Quebec","year":2025,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université du Québec à Montréal","funders":"","keywords":"Precipitation; Forecast verification; Metric (unit); Numerical weather prediction; Quantitative precipitation forecast; Forecast skill; Grid; Intensity (physics); Scale (ratio)","score_opus":0.015387075151316982,"score_gpt":0.24782205408010455,"score_spread":0.23243497892878756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417147657","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4704168,0.00022959198,0.5191858,0.0013589371,0.00005023617,0.0013228233,0.00022677677,0.000110698966,0.00709832],"genre_scores_gemma":[0.99559474,0.0000058947817,0.0017062549,0.0008654648,0.00004990681,0.00027192527,0.0010222427,0.000004512662,0.00047908255],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9981312,0.0002945693,0.0005169409,0.0005056383,0.00028224976,0.00026938328],"domain_scores_gemma":[0.9980623,0.0007706755,0.00023152119,0.0006821455,0.00014045365,0.000112894086],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00056172424,0.00018779338,0.00024324184,0.000098251294,0.00048295475,0.00003945596,0.00048071565,0.00019074998,0.0017345651],"category_scores_gemma":[0.000060653467,0.000119090975,0.00011197115,0.0007749596,0.0004899535,0.00012698823,0.000028558588,0.00016953703,0.00020621023],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037257082,0.00042349493,0.25877044,0.00004057741,0.00005368685,2.2966746e-7,0.00024202447,0.121240355,0.0038064758,0.03232251,0.00033370985,0.58239394],"study_design_scores_gemma":[0.0004629072,0.00018428545,0.6980018,0.000003882207,0.0000881971,6.3298387e-7,0.00014415215,0.24987635,0.00042317517,0.03671219,0.013903799,0.00019865879],"about_ca_topic_score_codex":0.0016836519,"about_ca_topic_score_gemma":0.01131849,"teacher_disagreement_score":0.5821953,"about_ca_system_score_codex":0.000030468986,"about_ca_system_score_gemma":0.00006149829,"threshold_uncertainty_score":0.999178},"labels":[],"label_agreement":null},{"id":"W7114899136","doi":"10.1002/met.70136","title":"Addressing the Effects of Station Network Geographical Inhomogeneity on Spatially Aggregated Verification Scores","year":2025,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Weighting; Homogeneous; Exploit; Gaussian; A-weighting","score_opus":0.037427197874958414,"score_gpt":0.2747612899435067,"score_spread":0.23733409206854827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7114899136","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92297715,0.0011951791,0.065210946,0.0014872972,0.00020938314,0.0016779939,0.00006586077,0.0001402177,0.0070360033],"genre_scores_gemma":[0.9965985,0.00009188296,0.0018854003,0.00094986474,0.00008071473,0.00010813212,0.0002432345,0.0000024767778,0.000039785424],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982913,0.0004083563,0.00041338406,0.00036270096,0.00024664492,0.00027760206],"domain_scores_gemma":[0.9965947,0.0026189014,0.00019181006,0.00041509423,0.000102319565,0.000077171026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052128895,0.00015735644,0.0002417894,0.00009134995,0.00055149413,0.00004535313,0.00037889858,0.0001500309,0.0003002095],"category_scores_gemma":[0.00044513872,0.000093551156,0.0001041536,0.0010622791,0.00035554898,0.00005823305,0.00002383082,0.00024485128,0.000041730287],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042362345,0.00044199306,0.35650772,0.00012906252,0.00017777843,0.0000021447543,0.00008388459,0.15670936,0.0022759242,0.15185396,0.00074826996,0.33064628],"study_design_scores_gemma":[0.00028144394,0.00027578158,0.89792335,0.00002338513,0.000067655514,3.7507644e-7,0.0000065140234,0.0118128825,0.00043590946,0.08577758,0.0032813768,0.00011372297],"about_ca_topic_score_codex":0.00014590695,"about_ca_topic_score_gemma":0.00018589692,"teacher_disagreement_score":0.54141563,"about_ca_system_score_codex":0.000005914206,"about_ca_system_score_gemma":0.00003453067,"threshold_uncertainty_score":0.4241703},"labels":[],"label_agreement":null}]}