{"meta":{"query_hash":"ab210b350f5f","filters":{"venue":"Journal of Advances in Modeling Earth Systems"},"cohort_total":153,"direct_labels_cover":0,"predictions_cover":153,"exported":153,"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/ab210b350f5f","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Advances+in+Modeling+Earth+Systems"},"results":[{"id":"W1530808387","doi":"10.1029/2012ms000157","title":"Impact of melt ponds on Arctic sea ice in past and future climates as simulated by MPI‐ESM","year":2012,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":35,"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":"Deutsches Klimarechenzentrum","keywords":"Sea ice; Arctic sea ice decline; Arctic ice pack; Arctic geoengineering; Climatology; Arctic; Cryosphere; Oceanography; Antarctic sea ice; Melt pond; Ice-albedo feedback; Sea ice concentration; Environmental science; Geology; Archipelago; Sea ice thickness","score_opus":0.008377892798121837,"score_gpt":0.2623259620044632,"score_spread":0.25394806920634133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1530808387","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938968,0.00012332128,0.0007793056,0.00021980035,0.000034718913,0.000011564238,0.0014172281,0.00017341436,0.0033438515],"genre_scores_gemma":[0.99823606,0.00009372301,0.00043425904,0.000033107633,0.00000961676,0.000020887417,0.0007788599,0.000030360507,0.000363186],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997465,0.00008898969,0.000015921092,0.000040616284,0.000036463804,0.00007146691],"domain_scores_gemma":[0.99917406,0.00040043716,0.00009281732,0.00009494495,0.000091624745,0.00014611476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083320966,0.0008902764,0.0007713829,0.0005503186,0.00079233147,0.0012682291,0.0007869866,0.0012100477,0.0019574808],"category_scores_gemma":[0.002467362,0.0004631719,0.0011454746,0.0010989797,0.0007887415,0.0008177271,0.0007240566,0.0008880867,0.0002285825],"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":[0.0001417082,0.000057805748,0.014525512,0.000035910896,0.00008922401,0.00013297788,0.000036416346,0.9819016,0.0007480634,0.0004547954,0.0005032213,0.0013727588],"study_design_scores_gemma":[0.00016228223,0.00017988945,0.025214927,0.000023218374,0.000095919444,0.000057123758,0.000105678555,0.9712189,0.001248348,0.00066657056,0.0009775786,0.000049581253],"about_ca_topic_score_codex":0.033354167,"about_ca_topic_score_gemma":0.01764843,"teacher_disagreement_score":0.033354167,"about_ca_system_score_codex":0.0011940316,"about_ca_system_score_gemma":0.000918713,"threshold_uncertainty_score":0.06632006},"labels":[],"label_agreement":null},{"id":"W1573853306","doi":"10.1029/2011ms000065","title":"Sigma-point particle filter for parameter estimation in a multiplicative noise environment","year":2011,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":4,"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 Northern British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; International Max Planck Research School for Advanced Methods in Process and Systems Engineering; State Key Laboratory of Satellite Ocean Environment Dynamics","keywords":"Ensemble Kalman filter; Multiplicative function; Kalman filter; Square root; Data assimilation; Multiplicative noise; Particle filter; Sigma; Mathematics; Invariant extended Kalman filter; Noise (video); Gaussian; Algorithm; Filter (signal processing); Extended Kalman filter; Control theory (sociology); Applied mathematics; Computer science; Statistics; Physics; Mathematical analysis; Meteorology; Artificial intelligence; Geometry; Telecommunications","score_opus":0.05916851543020722,"score_gpt":0.26133790155722303,"score_spread":0.2021693861270158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1573853306","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016526392,0.00034100073,0.9970898,0.000063107706,0.000056566732,0.000008821293,0.000031128755,0.0001917808,0.00056527584],"genre_scores_gemma":[0.35455847,0.00257186,0.6320146,0.0001806706,0.00028420112,0.00024083084,0.0005273288,0.00015409145,0.009467965],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965847,0.00010250053,0.000014187042,0.00006130739,0.00014584835,0.000017636972],"domain_scores_gemma":[0.9995431,0.00025714622,0.000032952405,0.00004235157,0.000114660244,0.000009884118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007337427,0.00057761837,0.0007142309,0.00042227874,0.00033203937,0.0005702431,0.000779294,0.0010428086,0.0016109409],"category_scores_gemma":[0.0027562995,0.00033014675,0.00046998676,0.00088814547,0.00038925488,0.0008206708,0.00052743295,0.0011626353,0.00070460606],"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":[0.000106667445,0.000030177767,0.0010659763,0.00013989756,0.000088769746,0.00009601594,0.00007643707,0.8039253,0.0036751484,0.041951433,0.0038930671,0.1449511],"study_design_scores_gemma":[0.000005415921,0.000011866905,0.00014209973,0.0000054965158,0.0000069631124,0.000011416286,0.0000026043156,0.9930754,0.0004610765,0.004794323,0.0014775766,0.000005747344],"about_ca_topic_score_codex":0.0077196555,"about_ca_topic_score_gemma":0.004977086,"teacher_disagreement_score":0.0077196555,"about_ca_system_score_codex":0.00045719408,"about_ca_system_score_gemma":0.0009625192,"threshold_uncertainty_score":0.015349448},"labels":[],"label_agreement":null},{"id":"W1765543570","doi":"10.1002/2015ms000440","title":"WRF‐simulated sensitivity to land surface schemes in short and medium ranges for a high‐temperature event in <scp>E</scp>ast <scp>C</scp>hina: A comparative study","year":2015,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":30,"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":"China Meteorological Administration; National Natural Science Foundation of China; University of Bristol","keywords":"Weather Research and Forecasting Model; Initialization; Environmental science; Range (aeronautics); Sensible heat; Climatology; Sensitivity (control systems); Atmospheric sciences; Flux (metallurgy); Atmospheric model; Meteorology; Atmosphere (unit); Materials science; Geology; Physics; Computer science","score_opus":0.049403768844296994,"score_gpt":0.3037778155493847,"score_spread":0.25437404670508773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1765543570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980921,0.00002267677,0.0010223142,0.00003909009,0.000011185953,0.000010333118,0.00020220202,0.00006899058,0.0005309705],"genre_scores_gemma":[0.99920815,0.000008255251,0.00050307537,0.000006638261,0.0000019022799,0.00000670391,0.00017476623,0.000008126025,0.00008234528],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997466,0.00007765758,0.000022828479,0.000064420754,0.000034037566,0.00005435247],"domain_scores_gemma":[0.99888664,0.00054849056,0.00009860089,0.0001343126,0.00020951669,0.00012243282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009199787,0.00058796676,0.00050266215,0.00040194922,0.0003598622,0.000688404,0.0006729926,0.0009913836,0.0009881124],"category_scores_gemma":[0.0020759166,0.00037293427,0.0009761247,0.0004184409,0.000375191,0.0007331637,0.0003317002,0.0006768471,0.00012096551],"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":[0.00019014857,0.0001370332,0.030320546,0.000018735585,0.00008286308,0.00009484041,0.000033877976,0.9633487,0.0030027998,0.00019795357,0.0001565994,0.002415912],"study_design_scores_gemma":[0.000048027818,0.00007925105,0.01147615,0.0000030815802,0.000026154592,0.000008728949,0.000024298843,0.98599446,0.0021422447,0.00007573006,0.00010671027,0.000015193594],"about_ca_topic_score_codex":0.03313841,"about_ca_topic_score_gemma":0.014868064,"teacher_disagreement_score":0.03313841,"about_ca_system_score_codex":0.0012325277,"about_ca_system_score_gemma":0.0006473483,"threshold_uncertainty_score":0.06589103},"labels":[],"label_agreement":null},{"id":"W1865208554","doi":"10.1002/2015ms000473","title":"Dry deposition of polycyclic aromatic compounds to various land covers in the Athabasca oil sands region","year":2015,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University; Environment and Climate Change Canada","funders":"","keywords":"Oil sands; Deposition (geology); Environmental chemistry; Alkylation; Dry weight; Environmental science; Hydrocarbon; Range (aeronautics); Chemistry; Geology; Organic chemistry; Botany; Materials science","score_opus":0.019011606450312062,"score_gpt":0.257739950161262,"score_spread":0.23872834371094995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1865208554","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99577844,0.0000775919,0.0019210015,0.000014659504,0.0000016430404,0.000024216873,0.0013720302,0.00008279646,0.0007276059],"genre_scores_gemma":[0.997393,0.000042890333,0.0017414343,0.0000040797936,9.2693045e-7,0.000018608915,0.0006211049,0.0000048178704,0.00017311497],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988973,0.000013990896,0.000008711005,0.00003172136,0.000038370443,0.000017405893],"domain_scores_gemma":[0.9998982,0.000015724027,0.000039703806,0.000007555659,0.0000261761,0.000012645627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018937077,0.00054193876,0.00019255218,0.0015755495,0.0004405126,0.0004887196,0.00038025374,0.00017980259,0.00033335315],"category_scores_gemma":[0.00023586489,0.00014320633,0.000510865,0.0009186211,0.00015408853,0.00023777761,0.00028800723,0.00009999237,0.00008174414],"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":[0.00023573486,0.00014966111,0.79015917,0.0001396792,0.00051545113,0.00045612556,0.00025982672,0.13740167,0.04345005,0.00041650352,0.00036111314,0.026455015],"study_design_scores_gemma":[0.000023845125,0.00004630846,0.8050472,0.000018153809,0.000086797074,0.00009952595,0.00035777973,0.18525167,0.007909026,0.00017283815,0.0009528532,0.000034005367],"about_ca_topic_score_codex":0.27926636,"about_ca_topic_score_gemma":0.2822424,"teacher_disagreement_score":0.72073364,"about_ca_system_score_codex":0.0018021042,"about_ca_system_score_gemma":0.0009167936,"threshold_uncertainty_score":0.5552817},"labels":[],"label_agreement":null},{"id":"W1878399745","doi":"10.1002/2013ms000255","title":"A practical scheme of the sigma‐point Kalman filter for high‐dimensional systems","year":2013,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Northern British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Data assimilation; Kalman filter; Computer science; Ensemble Kalman filter; Algorithm; State-space representation; Meteorology; Extended Kalman filter; Artificial intelligence","score_opus":0.042539236535554414,"score_gpt":0.27737978568796745,"score_spread":0.23484054915241304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1878399745","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023719172,0.000036783753,0.9969727,0.000036364647,0.000022481385,0.000010154301,0.000011535072,0.000074848525,0.00046316636],"genre_scores_gemma":[0.44258842,0.00032499694,0.55171853,0.000083719155,0.00007188617,0.00020779145,0.00018969482,0.000058783688,0.0047563277],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993395,0.00020392412,0.00005231389,0.00013694225,0.00022677399,0.000040519993],"domain_scores_gemma":[0.99929976,0.00020245652,0.000055524633,0.00011485097,0.000298748,0.000028583869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010871859,0.0005860438,0.0005282092,0.00034277787,0.0006572163,0.00071769697,0.0008152794,0.00086005207,0.0027857346],"category_scores_gemma":[0.0022978846,0.00030067482,0.0006893346,0.00051917444,0.0007046148,0.0012750002,0.00095054926,0.001305996,0.0006073832],"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":[0.000075809425,0.000028633609,0.0011021117,0.00008190209,0.000045071443,0.000063542255,0.0001267128,0.8261276,0.0055813296,0.060550306,0.001408728,0.10480826],"study_design_scores_gemma":[0.0000050102026,0.0000121153,0.00007238617,0.0000031741206,0.000002624849,0.000007436714,0.0000043915884,0.9957041,0.0005339445,0.00308163,0.00056792155,0.0000052553314],"about_ca_topic_score_codex":0.010650179,"about_ca_topic_score_gemma":0.006208778,"teacher_disagreement_score":0.010650179,"about_ca_system_score_codex":0.00080228195,"about_ca_system_score_gemma":0.0016609653,"threshold_uncertainty_score":0.021176398},"labels":[],"label_agreement":null},{"id":"W2008696075","doi":"10.1002/2014ms000367","title":"An approach estimating bidirectional air‐surface exchange for gaseous elemental mercury at AMNet sites","year":2014,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":31,"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; University of Prince Edward Island","funders":"","keywords":"Environmental science; Atmospheric sciences; Mercury (programming language); Deposition (geology); Canopy; Elemental mercury; Environmental chemistry; Meteorology; Chemistry; Geology; Geography","score_opus":0.02733842375809537,"score_gpt":0.2982728790585646,"score_spread":0.2709344553004692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008696075","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9454049,0.00048031216,0.047162157,0.00008362676,0.000018625002,0.0001409154,0.0023905102,0.00034717176,0.003971756],"genre_scores_gemma":[0.9702827,0.00028373243,0.026996912,0.000014067846,0.000007588831,0.00010754069,0.0016625584,0.000039046023,0.00060583634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977034,0.000058844453,0.0000126202185,0.00007897369,0.000052881103,0.000026282007],"domain_scores_gemma":[0.9997671,0.00007068238,0.000051923245,0.0000256673,0.00007005371,0.000014485755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006422728,0.00066268165,0.00047421918,0.0014369006,0.00040145885,0.00083293975,0.0008322996,0.00069106254,0.0007286696],"category_scores_gemma":[0.0011344353,0.00037287115,0.00094729406,0.0015650928,0.00012912489,0.0008276421,0.0008178494,0.00035608743,0.00017399318],"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":[0.00034710838,0.0002703101,0.36250547,0.00054265145,0.0006756157,0.0004914754,0.00037780064,0.51005334,0.019299094,0.00275146,0.0008535726,0.10183207],"study_design_scores_gemma":[0.000047633726,0.00008675511,0.09721486,0.000045496527,0.00021193827,0.00007074617,0.00029926322,0.8920873,0.006309403,0.0014534493,0.0021142128,0.00005899435],"about_ca_topic_score_codex":0.09292211,"about_ca_topic_score_gemma":0.08568772,"teacher_disagreement_score":0.09292211,"about_ca_system_score_codex":0.0013689297,"about_ca_system_score_gemma":0.0014375473,"threshold_uncertainty_score":0.18476248},"labels":[],"label_agreement":null},{"id":"W2021361126","doi":"10.1002/2014ms000316","title":"Some aspects of the problem of secondary eyewall formation in idealized three‐dimensional nonlinear simulations","year":2014,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Tropical and Extratropical Cyclones Research","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":false,"ca_institutions":"Environment and Climate Change Canada; McGill University","funders":"","keywords":"Eye; Rainband; Boundary layer; Mechanics; Vortex; Spiral (railway); Vorticity; Meteorology; Nonlinear system; Geology; Convection; Tropical cyclone; Physics; Engineering; Mechanical engineering","score_opus":0.017506402269295007,"score_gpt":0.25829999391813846,"score_spread":0.24079359164884345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021361126","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8903443,0.00026684062,0.09441737,0.0008489726,0.00009397103,0.00013697945,0.00020534892,0.00021694443,0.013469238],"genre_scores_gemma":[0.9923653,0.00007577828,0.0065928227,0.000042624713,0.000018440254,0.00007143349,0.00004820579,0.00002669631,0.00075871026],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997142,0.00013600467,0.000012372581,0.000025213001,0.00004754752,0.000064605694],"domain_scores_gemma":[0.99869114,0.0007200631,0.00019822625,0.0001382117,0.00012774329,0.00012466944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009438872,0.0004270943,0.00077223644,0.00033919862,0.0008345418,0.001070177,0.00079607766,0.0012682328,0.0015129945],"category_scores_gemma":[0.003689651,0.00043140133,0.0006507256,0.00017920525,0.0014033574,0.0007204699,0.000884662,0.0007031929,0.00009284442],"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":[0.00010210418,0.000047970596,0.0016346348,0.00002980915,0.000017015936,0.00015537791,0.000053926462,0.98757637,0.002342843,0.0072115595,0.0001547475,0.00067356066],"study_design_scores_gemma":[0.000018625375,0.000017060322,0.00020988125,0.000004271125,0.0000022902864,0.000007893342,0.0000120095265,0.9982229,0.0002987524,0.0011329224,0.00006910069,0.0000042581264],"about_ca_topic_score_codex":0.007559666,"about_ca_topic_score_gemma":0.0026760777,"teacher_disagreement_score":0.007559666,"about_ca_system_score_codex":0.00063982134,"about_ca_system_score_gemma":0.00085880817,"threshold_uncertainty_score":0.015031338},"labels":[],"label_agreement":null},{"id":"W2042482931","doi":"10.1002/2014ms000346","title":"The Specified Chemistry Whole Atmosphere Community Climate Model (SC‐WACCM)","year":2014,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":112,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"NOAA Research; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy; Office of Science; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Atmosphere (unit); Climatology; Environmental science; Climate model; Ozone layer; Atmospheric sciences; Montreal Protocol; Stratosphere; Climate change; Meteorology; Oceanography; Geography; Geology","score_opus":0.017263541390953308,"score_gpt":0.2366000627830658,"score_spread":0.2193365213921125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042482931","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4397495,0.0011355892,0.06822717,0.0036881585,0.0011951143,0.0007578711,0.40618595,0.019588092,0.059472512],"genre_scores_gemma":[0.75035834,0.0004088316,0.051089283,0.0006199805,0.00018473505,0.0008932174,0.18705696,0.0025184937,0.00687007],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955076,0.000111920766,0.00002130493,0.000099386736,0.00014223586,0.00007429219],"domain_scores_gemma":[0.998796,0.0001643438,0.00010614912,0.00024270936,0.00049161,0.00019915207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011436499,0.0011232707,0.00086781976,0.00063092884,0.0007836698,0.0014909904,0.00385636,0.0016851737,0.006144195],"category_scores_gemma":[0.0023501888,0.00054043997,0.0012372066,0.0019053664,0.000517394,0.0015630069,0.0009855776,0.0019096868,0.0021399485],"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":[0.0004269495,0.00019789228,0.01411869,0.00024427532,0.00043871131,0.00011801721,0.00006879092,0.9004577,0.002882295,0.0070894114,0.06256063,0.011396683],"study_design_scores_gemma":[0.00066493405,0.000052576615,0.0067946734,0.000027354617,0.00008536892,0.000019466821,0.000027937722,0.963716,0.0016730835,0.0021477027,0.024708249,0.00008264035],"about_ca_topic_score_codex":0.122752406,"about_ca_topic_score_gemma":0.083331496,"teacher_disagreement_score":0.122752406,"about_ca_system_score_codex":0.0016543178,"about_ca_system_score_gemma":0.004951175,"threshold_uncertainty_score":0.24407578},"labels":[],"label_agreement":null},{"id":"W2077568143","doi":"10.3894/james.2010.2.4","title":"Comparison of Firebrand Propagation Prediction by a Plume Model and a Coupled–Fire/Atmosphere Large–Eddy Simulator","year":2010,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Plume; Atmosphere (unit); Combustion; Large eddy simulation; Meteorology; Environmental science; Deposition (geology); Simulation; Atmospheric sciences; Mechanics; Geology; Computer science; Physics; Turbulence; Chemistry","score_opus":0.006838594561886821,"score_gpt":0.2565619014640204,"score_spread":0.2497233069021336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077568143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97519034,0.00010652752,0.019547367,0.0001283953,0.000046980163,0.000053442785,0.00015699472,0.00043035575,0.004339706],"genre_scores_gemma":[0.9923862,0.00006413182,0.00659851,0.000024576375,0.0000074203363,0.000023706767,0.00016703711,0.000045041885,0.00068335584],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986184,0.000042068594,0.000010296305,0.000022836422,0.000039084927,0.000023911809],"domain_scores_gemma":[0.9992524,0.00040283575,0.000049566963,0.00007251842,0.00014108172,0.000081633465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000670057,0.0006870705,0.0005727027,0.00032821138,0.00034908284,0.00081506616,0.0009052529,0.0010038132,0.00074535183],"category_scores_gemma":[0.0014796301,0.00029680395,0.0006039387,0.00027746797,0.00041235075,0.0007264107,0.00045147497,0.0006571659,0.00013400652],"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":[0.0002597085,0.00020209575,0.0055444334,0.000030974305,0.00004460508,0.000056599725,0.000069682144,0.9825514,0.005600966,0.0007374692,0.00018537109,0.0047167316],"study_design_scores_gemma":[0.000017479715,0.000031561794,0.0004738298,0.000001171621,0.000004443154,0.0000027068452,0.0000074067507,0.9988337,0.0005484518,0.000036650712,0.000038541824,0.0000039531465],"about_ca_topic_score_codex":0.038147755,"about_ca_topic_score_gemma":0.016361594,"teacher_disagreement_score":0.038147755,"about_ca_system_score_codex":0.00076301733,"about_ca_system_score_gemma":0.0010755664,"threshold_uncertainty_score":0.07585138},"labels":[],"label_agreement":null},{"id":"W2143576520","doi":"10.1002/2014ms000373","title":"A modified ensemble Kalman particle filter for non‐Gaussian systems with nonlinear measurement functions","year":2014,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":42,"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":"National Natural Science Foundation of China","keywords":"Ensemble Kalman filter; Particle filter; Data assimilation; Kalman filter; Nonlinear system; Algorithm; Resampling; Extended Kalman filter; Computer science; Gaussian; Covariance; Invariant extended Kalman filter; Computation; Applied mathematics; Mathematics; Artificial intelligence; Physics; Statistics; Meteorology","score_opus":0.0503414054190761,"score_gpt":0.24949315926161256,"score_spread":0.19915175384253647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143576520","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067836614,0.00011802393,0.99221534,0.00006246553,0.000062494255,0.000014136738,0.000033474407,0.0001740364,0.00053632964],"genre_scores_gemma":[0.515064,0.00048549034,0.47864288,0.00011155106,0.00015386092,0.00015660508,0.00034170094,0.00008075382,0.004963145],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947625,0.00014126387,0.000030444819,0.00012575442,0.00018865269,0.000037645816],"domain_scores_gemma":[0.9991543,0.00038120963,0.000083799605,0.00008451695,0.0002691184,0.000027044432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010575675,0.0006109521,0.0010234821,0.0003936553,0.00039871084,0.0005814473,0.0009947271,0.0009408708,0.0012157566],"category_scores_gemma":[0.0031775623,0.0003317875,0.00069141533,0.000542515,0.00041106791,0.0010340525,0.00075478206,0.0010971539,0.00028636496],"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":[0.00008636526,0.000028794393,0.0012645554,0.000059613427,0.00006733098,0.000075792756,0.000053602045,0.8967919,0.0030368075,0.010943476,0.0011905768,0.086401224],"study_design_scores_gemma":[0.000004289296,0.0000068992977,0.0001330682,0.0000016709791,0.000004040542,0.0000058171922,0.0000013518317,0.99859387,0.00022703613,0.000632604,0.0003855808,0.0000037793243],"about_ca_topic_score_codex":0.017400986,"about_ca_topic_score_gemma":0.011458752,"teacher_disagreement_score":0.017400986,"about_ca_system_score_codex":0.0005886096,"about_ca_system_score_gemma":0.0013217989,"threshold_uncertainty_score":0.034599364},"labels":[],"label_agreement":null},{"id":"W2145733138","doi":"10.1002/2014ms000392","title":"Bulk or modal parameterizations for below‐cloud scavenging of fine, coarse, and giant particles by both rain and snow","year":2014,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric chemistry and aerosols","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":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Scavenging; Aerosol; Log-normal distribution; Range (aeronautics); Snow; Precipitation; Power law; Environmental science; Atmospheric sciences; Meteorology; Physics; Mathematics; Materials science; Statistics; Chemistry","score_opus":0.0141829701302636,"score_gpt":0.23430910447152392,"score_spread":0.22012613434126033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145733138","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41748676,0.0005321697,0.5681041,0.00014820733,0.00009402716,0.0002852505,0.0016701351,0.0010903369,0.0105890855],"genre_scores_gemma":[0.96843284,0.00016877592,0.027875757,0.00008293877,0.000035535268,0.00016050923,0.0011714142,0.00012157852,0.0019505332],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998233,0.000024241355,0.000013033083,0.000047102036,0.00006447086,0.000027999698],"domain_scores_gemma":[0.9996213,0.000120883116,0.00006137678,0.000048957314,0.0001273073,0.000020279891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007347637,0.0007273316,0.00030410144,0.00093876745,0.00024796044,0.00058120827,0.001505165,0.0005037599,0.0017468601],"category_scores_gemma":[0.0015559196,0.0003079485,0.0010801984,0.00037600615,0.00024340987,0.0013940226,0.00062730705,0.0007246911,0.00038001747],"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":[0.00013711593,0.00018862597,0.035918765,0.00016679235,0.00018834465,0.0001462279,0.00013501718,0.8395515,0.04460001,0.012548302,0.0030020594,0.06341721],"study_design_scores_gemma":[0.000013950138,0.000025552008,0.0072955196,0.000011595042,0.000022947965,0.00003548056,0.000022774637,0.9860452,0.0023715654,0.0030943553,0.0010382674,0.000022669841],"about_ca_topic_score_codex":0.009912589,"about_ca_topic_score_gemma":0.008266084,"teacher_disagreement_score":0.009912589,"about_ca_system_score_codex":0.00079891755,"about_ca_system_score_gemma":0.0006527002,"threshold_uncertainty_score":0.019709766},"labels":[],"label_agreement":null},{"id":"W2152916584","doi":"10.1002/2013ms000282","title":"Intercomparison of large‐eddy simulations of Arctic mixed‐phase clouds: Importance of ice size distribution assumptions","year":2014,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":188,"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":"Biological and Environmental Research; Oak Ridge Institute for Science and Education; Pacific Northwest National Laboratory; National Energy Research Scientific Computing Center; Battelle; Office of Science; National Aeronautics and Space Administration; U.S. Department of Energy; Oak Ridge Associated Universities; National Science Foundation","keywords":"Bin; Ice crystals; Liquid water path; Environmental science; Parametrization (atmospheric modeling); Atmospheric sciences; Aerosol; Meteorology; Statistical physics; Climatology; Physics; Geology; Radiative transfer; Mathematics","score_opus":0.012754297361136552,"score_gpt":0.2940653663755299,"score_spread":0.28131106901439334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152916584","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99676263,0.000056750498,0.0019834836,0.000059429105,0.000021149157,0.000024486842,0.00015364865,0.00007500774,0.000863405],"genre_scores_gemma":[0.9981229,0.000024477758,0.001441482,0.000016754853,0.0000055463347,0.000024104887,0.00019729328,0.0000141547835,0.00015330307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999678,0.00014057629,0.00002439802,0.00005266887,0.000040145245,0.00006416818],"domain_scores_gemma":[0.99837995,0.0009825433,0.00013750848,0.0001234764,0.0001973057,0.00017923543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016178248,0.0009043187,0.000901771,0.00044960613,0.0007447082,0.0012679574,0.0010336736,0.0014055428,0.0005162371],"category_scores_gemma":[0.002258854,0.00046799448,0.0011081151,0.0004117786,0.00050794246,0.0006948589,0.0004855796,0.00077722745,0.00008723523],"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":[0.00035963402,0.00020973347,0.011161373,0.0000280944,0.000115146504,0.000059895294,0.00004273145,0.9835113,0.0021885587,0.0002836192,0.00012325951,0.0019166174],"study_design_scores_gemma":[0.00005487148,0.00016132748,0.0033255492,0.0000045853853,0.00002233802,0.0000060270877,0.000029462153,0.99510974,0.0011345752,0.00006237001,0.000078238176,0.000010828272],"about_ca_topic_score_codex":0.03404262,"about_ca_topic_score_gemma":0.016672792,"teacher_disagreement_score":0.03404262,"about_ca_system_score_codex":0.0011534458,"about_ca_system_score_gemma":0.0010872394,"threshold_uncertainty_score":0.06768894},"labels":[],"label_agreement":null},{"id":"W2154489866","doi":"10.1002/2013ms000246","title":"CGILS: Results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models","year":2013,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":175,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Pacific Institute for Climate Solutions; University of British Columbia","funders":"Seoul National University; Biological and Environmental Research; Natural Sciences and Engineering Research Council of Canada; European Commission; Department for Environment, Food and Rural Affairs, UK Government; National Aeronautics and Space Administration; Commonwealth Scientific and Industrial Research Organisation; Met Office; U.S. Department of Energy; Stony Brook University; National Science Foundation","keywords":"Subsidence; Marine stratocumulus; Cloud feedback; Environmental science; Convection; Climate model; Positive feedback; Atmospheric sciences; Climatology; Cloud computing; Drizzle; Precipitation; Meteorology; Geology; Climate change; Climate sensitivity; Geography; Oceanography; Computer science; Structural basin","score_opus":0.0465192829414436,"score_gpt":0.29799932463288165,"score_spread":0.25148004169143806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154489866","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9514625,0.0002596661,0.00885751,0.00045062482,0.00008079678,0.00018950061,0.026288373,0.0064514377,0.005959692],"genre_scores_gemma":[0.95469207,0.00012775541,0.013102968,0.00015404,0.00005518129,0.0002395284,0.030103276,0.00065954326,0.00086557155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995834,0.00010679872,0.00002877268,0.00008970894,0.00010213952,0.00008921717],"domain_scores_gemma":[0.99821186,0.0005924766,0.00013504912,0.0003886295,0.00039973177,0.0002722747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016605875,0.0017897502,0.0009771367,0.00065636187,0.00042138406,0.00088792504,0.0022926114,0.00089538353,0.0021647895],"category_scores_gemma":[0.0020410605,0.00044017722,0.0012258599,0.0007116765,0.0004994846,0.0011990161,0.00081076694,0.0010748166,0.00027679978],"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":[0.0009537059,0.00089969794,0.044294287,0.00026041782,0.00040588627,0.00015801887,0.00014421783,0.9158473,0.0116861025,0.0014374404,0.009182219,0.014730729],"study_design_scores_gemma":[0.0006229646,0.0002866166,0.022266688,0.000017347053,0.00010020271,0.00003244991,0.000047214926,0.9650253,0.008793733,0.00046800406,0.0022773412,0.000062186075],"about_ca_topic_score_codex":0.046324875,"about_ca_topic_score_gemma":0.02792322,"teacher_disagreement_score":0.046324875,"about_ca_system_score_codex":0.0010844681,"about_ca_system_score_gemma":0.0011065581,"threshold_uncertainty_score":0.092110455},"labels":[],"label_agreement":null},{"id":"W2169372365","doi":"10.1002/jame.20039","title":"On the formulation of snow thermal conductivity in large‐scale sea ice models","year":2013,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Environment Research Council; European Commission; Sight Research UK","keywords":"Snow; Sea ice; Sea ice thickness; Northern Hemisphere; Thermal conductivity; Cryosphere; Climatology; Arctic; Sea ice growth processes; Sea ice concentration; Geology; Environmental science; Atmospheric sciences; Meteorology; Geomorphology; Oceanography; Geography; Thermodynamics; Physics","score_opus":0.01901308171897615,"score_gpt":0.23299056151309017,"score_spread":0.21397747979411402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169372365","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2052823,0.0016313994,0.7750464,0.0011245261,0.00020621494,0.00020513241,0.00041896364,0.00066798035,0.015417039],"genre_scores_gemma":[0.9062821,0.0012031668,0.08700174,0.00018574872,0.00018758015,0.00040444385,0.00029864738,0.0004278428,0.0040087565],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996698,0.00020201874,0.000017656663,0.0000296036,0.000050419218,0.000030592935],"domain_scores_gemma":[0.9985328,0.0010736804,0.00011646517,0.00008373501,0.00014306237,0.000050314247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001382752,0.0008763015,0.00083546474,0.0004344234,0.000714159,0.001588027,0.0010681811,0.0013396192,0.0013768157],"category_scores_gemma":[0.004962264,0.0006124685,0.0010325512,0.000630977,0.0012646285,0.0013824755,0.0012745364,0.0012652683,0.00025466966],"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":[0.000013948817,0.000012350955,0.00023055718,0.000019405947,0.000008602037,0.000026797272,0.000015432746,0.99465454,0.00038287177,0.0030347195,0.0000775603,0.0015232514],"study_design_scores_gemma":[0.000004871963,0.000007368044,0.000052364907,0.000004044307,0.0000018625867,0.0000023949344,0.000004808251,0.9986993,0.00009834107,0.001007041,0.00011509787,0.0000023967918],"about_ca_topic_score_codex":0.012161855,"about_ca_topic_score_gemma":0.009647042,"teacher_disagreement_score":0.012161855,"about_ca_system_score_codex":0.0013145744,"about_ca_system_score_gemma":0.0013634844,"threshold_uncertainty_score":0.02418214},"labels":[],"label_agreement":null},{"id":"W2257315136","doi":"10.1002/2015ms000463","title":"Complex functionality with minimal computation: Promise and pitfalls of reduced‐tracer ocean biogeochemistry models","year":2015,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Compute Canada; National Aeronautics and Space Administration; U.S. Department of Energy; National Science Foundation","keywords":"Biogeochemistry; Biogeochemical cycle; TRACER; Environmental science; Carbon cycle; Forcing (mathematics); Ecosystem; Atmospheric sciences; Oceanography; Chemistry; Ecology; Environmental chemistry; Geology; Biology","score_opus":0.042538414170113885,"score_gpt":0.2473593021078977,"score_spread":0.2048208879377838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2257315136","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34565157,0.0010112929,0.62974864,0.0034181774,0.00023316001,0.00019570482,0.0006971528,0.0034465753,0.015597772],"genre_scores_gemma":[0.9112152,0.0003834442,0.0850651,0.00022468825,0.00006652156,0.00017390138,0.00032203223,0.0003401069,0.0022090788],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961203,0.00021304461,0.000018283272,0.00003733674,0.0000808034,0.000038557693],"domain_scores_gemma":[0.99642414,0.0023032904,0.00021045186,0.000604479,0.00032464595,0.00013299234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001455557,0.0010403675,0.0011716015,0.0004582572,0.00047782334,0.0015915199,0.0026525045,0.0013359599,0.0024698973],"category_scores_gemma":[0.0065077,0.0008118698,0.0009513253,0.00042663224,0.0015920419,0.0026966545,0.001639457,0.0014718896,0.0004364781],"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":[0.000058683025,0.000044981647,0.0008708681,0.000025107862,0.000028617502,0.000023724064,0.000029811292,0.985754,0.00044943855,0.008829935,0.00032013992,0.0035646285],"study_design_scores_gemma":[0.0000135942555,0.000009706866,0.000038402675,0.0000026929504,0.0000027077065,0.00000164873,0.0000031001523,0.99638724,0.00006387448,0.00330811,0.00016563627,0.0000032817757],"about_ca_topic_score_codex":0.03007227,"about_ca_topic_score_gemma":0.013325631,"teacher_disagreement_score":0.03007227,"about_ca_system_score_codex":0.0011005444,"about_ca_system_score_gemma":0.0013604447,"threshold_uncertainty_score":0.059794486},"labels":[],"label_agreement":null},{"id":"W2275660238","doi":"10.1002/2015ms000564","title":"Impacts of parameterized orographic drag on the <scp>N</scp>orthern <scp>H</scp>emisphere winter circulation","year":2015,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":79,"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":"Orographic lift; Orography; Stratosphere; Atmospheric sciences; Climatology; Environmental science; Troposphere; Numerical weather prediction; Drag; Meteorology; Atmospheric circulation; Northern Hemisphere; Geology; Precipitation; Physics; Mechanics","score_opus":0.034028676985402934,"score_gpt":0.2666836490941994,"score_spread":0.23265497210879646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2275660238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981901,0.000024929437,0.0005509588,0.000048972288,0.000010151886,0.000006618993,0.00018413053,0.000032016018,0.0009520236],"genre_scores_gemma":[0.9994646,0.000018129324,0.00027259326,0.000014047504,0.0000020823654,0.0000046548853,0.00011366251,0.000011010051,0.000099267425],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997985,0.00007533182,0.000012386258,0.000032732496,0.000026277308,0.000054875618],"domain_scores_gemma":[0.99941015,0.00032023693,0.000069530404,0.00007604147,0.000057326735,0.00006675409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035911935,0.00051406183,0.0002709993,0.00017013679,0.00028210803,0.00069090584,0.00045576732,0.0004631147,0.00092545984],"category_scores_gemma":[0.0014942532,0.00020955855,0.00036265282,0.00022932341,0.00037768562,0.00044864952,0.00050926884,0.0005042112,0.00006748224],"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":[0.0004238365,0.00021610115,0.04796552,0.000040221115,0.00011678994,0.00012400512,0.000038621107,0.92962056,0.015888628,0.0006621385,0.0003309911,0.0045725196],"study_design_scores_gemma":[0.00015324318,0.00046107994,0.0383788,0.000013704277,0.000069193426,0.000025017813,0.00008202493,0.95190084,0.008025977,0.00021717153,0.000645762,0.000027094675],"about_ca_topic_score_codex":0.023507195,"about_ca_topic_score_gemma":0.013651159,"teacher_disagreement_score":0.023507195,"about_ca_system_score_codex":0.00081419165,"about_ca_system_score_gemma":0.0005808909,"threshold_uncertainty_score":0.04674077},"labels":[],"label_agreement":null},{"id":"W2290813649","doi":"10.1002/2015ms000601","title":"A parametrization of 3‐D subgrid‐scale clouds for conventional GCMs: Assessment using A‐Train satellite data and solar radiative transfer characteristics","year":2016,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":11,"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":"Pennsylvania State University; U.S. Department of Energy","keywords":"Parametrization (atmospheric modeling); Radiative transfer; Cloud fraction; Solar zenith angle; Environmental science; Satellite; Atmospheric radiative transfer codes; GCM transcription factors; Downwelling; Cloud computing; Zenith; Meteorology; Atmospheric sciences; Upwelling; Physics; Remote sensing; Geology; Computer science; Cloud cover; General Circulation Model; Climate change; Optics","score_opus":0.030412114789429373,"score_gpt":0.2994760656281038,"score_spread":0.2690639508386744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2290813649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9710098,0.00003067455,0.026246795,0.00007655773,0.000010679542,0.00004088074,0.0006996098,0.00021285961,0.0016721275],"genre_scores_gemma":[0.9943264,0.000014380376,0.005120584,0.000010280064,0.0000033883116,0.000024222736,0.00037272426,0.000021378999,0.00010651846],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988925,0.000035426514,0.0000088982915,0.000028035349,0.000020157375,0.000018205528],"domain_scores_gemma":[0.9996537,0.000123408,0.00004626172,0.000071426475,0.00007267552,0.000032548753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033519126,0.00032014778,0.00017874874,0.00029857867,0.00028393857,0.0006234138,0.00059719244,0.00046559682,0.0004980913],"category_scores_gemma":[0.0012042898,0.00025313176,0.0005878777,0.000404047,0.00025266543,0.000508694,0.00035150495,0.00043126117,0.00009861685],"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":[0.00008133321,0.000049094873,0.022447096,0.000008651589,0.000023513176,0.0000259681,0.000022660042,0.9701283,0.0023320608,0.0009443392,0.00016172233,0.0037752825],"study_design_scores_gemma":[0.000012939372,0.000008354892,0.0059954715,0.0000017895654,0.0000032855055,0.0000043734253,0.0000061865812,0.9929222,0.0007043235,0.0001793986,0.00015678539,0.00000478603],"about_ca_topic_score_codex":0.04213029,"about_ca_topic_score_gemma":0.020706454,"teacher_disagreement_score":0.04213029,"about_ca_system_score_codex":0.0009808938,"about_ca_system_score_gemma":0.0004965994,"threshold_uncertainty_score":0.083770156},"labels":[],"label_agreement":null},{"id":"W2469467445","doi":"10.1002/2015ms000576","title":"Climate, soil organic layer, and nitrogen jointly drive forest development after fire in the North American boreal zone","year":2016,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue; Université du Québec à Montréal; Natural Sciences and Engineering Research Council of Canada","funders":"National Science Foundation","keywords":"Taiga; Boreal; Environmental science; Fire regime; Nitrogen; Atmospheric sciences; Climatology; Earth science; Ecosystem; Physical geography; Geology; Forestry; Ecology; Geography; Chemistry","score_opus":0.006204332319065049,"score_gpt":0.2115798413687962,"score_spread":0.20537550904973115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2469467445","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991794,0.00005166247,0.0002165288,0.000041504245,0.0000039807246,0.0000026449684,0.00015919658,0.000015707928,0.0003295052],"genre_scores_gemma":[0.99957436,0.000027582877,0.0001522954,0.000011148455,0.0000014144746,0.0000024637393,0.00008916549,0.000002419296,0.00013919783],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993205,0.000016229915,0.000004132394,0.000021267253,0.0000071875306,0.000019098781],"domain_scores_gemma":[0.99978405,0.000061256775,0.000044117725,0.000012422775,0.00003454838,0.0000635734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032125396,0.00029724688,0.00017074493,0.0002140271,0.00034240965,0.0006137166,0.00040784615,0.00030307568,0.00097437564],"category_scores_gemma":[0.00042715576,0.00018558922,0.00035488233,0.00018020575,0.00023676366,0.00027628246,0.0002977909,0.00020896098,0.000056780686],"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":[0.00033135962,0.000269413,0.83469826,0.00005392316,0.00018676935,0.00023475863,0.000122017635,0.14307539,0.013213116,0.00053846336,0.00090515846,0.006371395],"study_design_scores_gemma":[0.00006978996,0.0000877399,0.6867968,0.000009262059,0.00006230912,0.000069861075,0.00023235449,0.3107744,0.00081925944,0.0004564403,0.0005934322,0.00002837936],"about_ca_topic_score_codex":0.20818351,"about_ca_topic_score_gemma":0.24476212,"teacher_disagreement_score":0.20818351,"about_ca_system_score_codex":0.0013848369,"about_ca_system_score_gemma":0.00066068704,"threshold_uncertainty_score":0.41394353},"labels":[],"label_agreement":null},{"id":"W2499545913","doi":"10.1002/2015ms000540","title":"Modeling the diurnal variability of respiratory fluxes in the Canadian Terrestrial Ecosystem Model (CTEM)","year":2016,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Environment Canada","keywords":"Biosphere; Environmental science; Atmospheric sciences; Diurnal cycle; Ecosystem; Flux (metallurgy); Carbon cycle; Terrestrial ecosystem; Atmosphere (unit); Primary production; Biosphere model; Diurnal temperature variation; Eddy covariance; Vegetation (pathology); Ecosystem respiration; Respiration; Carbon dioxide; Soil respiration; Soil water; Soil science; Ecology; Chemistry; Geology; Meteorology; Physics; Biology","score_opus":0.01756494080890847,"score_gpt":0.23377501499373937,"score_spread":0.2162100741848309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2499545913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96318156,0.0003072806,0.02036347,0.0005749672,0.000062920466,0.00005638649,0.0046527954,0.0005380875,0.010262634],"genre_scores_gemma":[0.99232,0.000121264624,0.0049529974,0.000046597088,0.000005807699,0.000023910665,0.0010794302,0.000038881153,0.0014110872],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986184,0.000021361351,0.000005415055,0.000035343375,0.000033618977,0.000042476815],"domain_scores_gemma":[0.99969447,0.00006884762,0.000024690635,0.000017399705,0.00015423511,0.00004040717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034939797,0.0006759182,0.00033022417,0.00034768588,0.00083978317,0.00079391524,0.0015703988,0.00064294465,0.0014243658],"category_scores_gemma":[0.0010880429,0.00028416145,0.00042405023,0.0006705045,0.0003452593,0.000537175,0.00038599185,0.0005362199,0.00011927331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006480164,0.000026210788,0.008264054,0.000023542478,0.00003488816,0.000031499625,0.000028797846,0.98426163,0.0015017946,0.001235967,0.0010288558,0.0034979011],"study_design_scores_gemma":[0.000015099279,0.000007110702,0.0050899507,0.0000024714946,0.000012572082,0.0000046790738,0.000012784441,0.99377006,0.00031596402,0.00016670566,0.0005904113,0.000012111548],"about_ca_topic_score_codex":0.9298116,"about_ca_topic_score_gemma":0.9115919,"teacher_disagreement_score":0.0701884,"about_ca_system_score_codex":0.0074652596,"about_ca_system_score_gemma":0.006100221,"threshold_uncertainty_score":0.14120346},"labels":[],"label_agreement":null},{"id":"W2519107385","doi":"10.1002/2016ms000751","title":"Validation of a weather forecast model at radiance level against satellite observations allowing quantification of temperature, humidity, and cloud‐related biases","year":2016,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric aerosols and clouds","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":true,"ca_institutions":"Environment and Climate Change Canada; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Radiance; Environmental science; Water vapor; Infrared window; Overcast; Radiative transfer; Sky; Remote sensing; Troposphere; Brightness temperature; Atmospheric sciences; Atmospheric Infrared Sounder; Meteorology; Infrared; Brightness; Geology; Physics; Optics","score_opus":0.06323299177560394,"score_gpt":0.2677229895916908,"score_spread":0.20448999781608684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2519107385","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97553396,0.000054681375,0.018618505,0.00005852463,0.000046382393,0.000065495115,0.0022285641,0.0013366686,0.002057137],"genre_scores_gemma":[0.9926267,0.000020533607,0.0053953016,0.000010201864,0.0000051436728,0.000031547093,0.0015601643,0.00003772209,0.00031277674],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976414,0.000047897476,0.00001829209,0.000069583024,0.000057950143,0.000042180298],"domain_scores_gemma":[0.999456,0.0001286255,0.000045818066,0.00009188681,0.00023490137,0.000042666587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090339774,0.00060384604,0.00032641366,0.00033252692,0.00033958172,0.00054329383,0.0006858246,0.0005016262,0.0007784646],"category_scores_gemma":[0.0013295511,0.00019697248,0.0005560997,0.00033851262,0.00024192032,0.00042655153,0.0003290548,0.00047332526,0.00034655677],"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":[0.0001850857,0.0001096632,0.021713594,0.000027617229,0.000059595102,0.0000435793,0.000026521036,0.9592602,0.0074164337,0.00024311198,0.00054935185,0.010365187],"study_design_scores_gemma":[0.000032047872,0.000036748643,0.010219168,0.0000030857298,0.000011036102,0.0000038121088,0.000008206858,0.9863049,0.0031169436,0.000059419108,0.00019526691,0.0000094359875],"about_ca_topic_score_codex":0.16772896,"about_ca_topic_score_gemma":0.06250885,"teacher_disagreement_score":0.16772896,"about_ca_system_score_codex":0.0010467457,"about_ca_system_score_gemma":0.0014380045,"threshold_uncertainty_score":0.33350533},"labels":[],"label_agreement":null},{"id":"W2551999027","doi":"10.1002/2016ms000700","title":"Assessment of the simulation of <scp>I</scp>ndian <scp>O</scp>cean <scp>D</scp>ipole in the <scp>C</scp>ESM—Impacts of atmospheric physics and model resolution","year":2016,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":27,"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":"State Key Laboratory of Satellite Ocean Environment Dynamics; National Natural Science Foundation of China; National Center for Atmospheric Research","keywords":"Thermocline; Climatology; Atmospheric physics; Teleconnection; Indian Ocean Dipole; Atmospheric model; Atmospheric sciences; El Niño Southern Oscillation; Zonal and meridional; Physics; Environmental science; Meteorology; Atmosphere (unit); Geology","score_opus":0.020971968802587646,"score_gpt":0.2782454256825069,"score_spread":0.2572734568799192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2551999027","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963111,0.00003575957,0.0014945897,0.000086030916,0.000019042509,0.00002321352,0.00015633609,0.00012679379,0.0017472359],"genre_scores_gemma":[0.99811184,0.000012787725,0.0015900633,0.000018730761,0.0000031766176,0.000015316848,0.000115472234,0.000013644656,0.000118962074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996971,0.0001237757,0.000022029393,0.00004951209,0.00005312136,0.00005442748],"domain_scores_gemma":[0.99835086,0.0009775416,0.00011262212,0.00018342107,0.000212174,0.00016338221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015682359,0.00064036454,0.00045084194,0.00028964676,0.00047834127,0.0007401074,0.0010085208,0.0009939441,0.0010369602],"category_scores_gemma":[0.0033332394,0.00035272853,0.0005495554,0.00036142016,0.0005764216,0.0006606093,0.0006311072,0.0007876596,0.00010770804],"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":[0.0005275933,0.00036089701,0.022732839,0.000060025606,0.000108573404,0.0001310326,0.000071844326,0.96101415,0.008626452,0.00072539586,0.00034533493,0.0052958825],"study_design_scores_gemma":[0.00014350747,0.00019074923,0.0047371653,0.0000045413826,0.000026469183,0.0000060241514,0.00004090208,0.99119043,0.0033648184,0.000091544396,0.00019268489,0.000011143299],"about_ca_topic_score_codex":0.030887248,"about_ca_topic_score_gemma":0.0151511,"teacher_disagreement_score":0.030887248,"about_ca_system_score_codex":0.0009997679,"about_ca_system_score_gemma":0.0007820495,"threshold_uncertainty_score":0.061414897},"labels":[],"label_agreement":null},{"id":"W2565231333","doi":"10.1002/2016ms000697","title":"Understanding the <scp>W</scp>est <scp>A</scp>frican <scp>M</scp>onsoon from the analysis of diabatic heating distributions as simulated by climate models","year":2016,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"European Commission","keywords":"Diabatic; Climatology; Rainband; Environmental science; Climate model; Convection; Radiative transfer; Atmospheric sciences; Flow (mathematics); Condensation; Meteorology; Climate change; Geology; Mechanics; Physics; Thermodynamics","score_opus":0.04161938494422582,"score_gpt":0.26914067029812383,"score_spread":0.227521285353898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2565231333","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9926117,0.0002821615,0.0032249114,0.00039906986,0.000008019541,0.000007313375,0.00045591747,0.000030875588,0.0029799526],"genre_scores_gemma":[0.9980894,0.00022012884,0.0011826075,0.000024819868,0.000007787308,0.0000068419067,0.00020508464,0.000014035936,0.00024941846],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999597,0.000012260426,0.0000019139961,0.000007671559,0.000008096996,0.000010331682],"domain_scores_gemma":[0.9998456,0.00007730393,0.000020275544,0.000020297695,0.000018897228,0.000017533957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002572109,0.00017843353,0.00012859666,0.00030970952,0.00018865817,0.0006895724,0.0001924604,0.00022578762,0.0010021109],"category_scores_gemma":[0.00061726064,0.00011379735,0.00027430477,0.00030370854,0.00019145211,0.0005536542,0.00023449975,0.00025514868,0.00011294968],"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":[0.0002903016,0.00013513095,0.5808664,0.00033134222,0.0003623697,0.0006830096,0.0006959084,0.2586368,0.05789347,0.004527559,0.0032451819,0.09233249],"study_design_scores_gemma":[0.000016753513,0.000055346503,0.64694595,0.00007641576,0.00008046059,0.00011557168,0.0008708771,0.3378986,0.0069361734,0.0033652228,0.003616679,0.00002193208],"about_ca_topic_score_codex":0.02173662,"about_ca_topic_score_gemma":0.03434977,"teacher_disagreement_score":0.02173662,"about_ca_system_score_codex":0.0003919054,"about_ca_system_score_gemma":0.00053248176,"threshold_uncertainty_score":0.043220222},"labels":[],"label_agreement":null},{"id":"W2565438658","doi":"10.1002/2016ms000785","title":"Variations in tropical cyclone frequency response to solar and CO<sub>2</sub> forcing in aquaplanet simulations","year":2016,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Tropical and Extratropical Cyclones Research","field":"Earth and Planetary Sciences","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":"McGill University","funders":"Compute Canada","keywords":"Radiative forcing; Forcing (mathematics); Cloud forcing; Atmospheric sciences; Environmental science; Radiative transfer; Tropical cyclone; Climatology; Solar constant; Intertropical Convergence Zone; Shortwave; Physics; Meteorology; Geology; Solar irradiance","score_opus":0.01758280488603006,"score_gpt":0.2694020534804938,"score_spread":0.25181924859446375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2565438658","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99614954,0.000014660534,0.00037857157,0.00009601881,0.000008095127,0.00000875443,0.0005065426,0.00006354117,0.0027742807],"genre_scores_gemma":[0.99882644,0.0000145732565,0.00039222307,0.000025678168,0.0000015396633,0.000013411578,0.00032814813,0.00001463063,0.00038326625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998677,0.000048726673,0.0000070724723,0.000023997825,0.000020387912,0.000032194144],"domain_scores_gemma":[0.9995016,0.00026815676,0.000056493103,0.000033996464,0.00006971538,0.00007011811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030886912,0.0003991069,0.00034372,0.00026529632,0.00039804267,0.00058096374,0.0008143193,0.0006524212,0.0029502332],"category_scores_gemma":[0.0013550074,0.00031163977,0.00037573776,0.00039025734,0.00044296778,0.00034734068,0.00040543443,0.00065701874,0.00016166568],"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":[0.0002526995,0.00010051001,0.017916897,0.000021022102,0.000054915294,0.00012264137,0.00003995584,0.97743565,0.0017191597,0.00062479347,0.00065920036,0.001052619],"study_design_scores_gemma":[0.00014156029,0.00013541142,0.008762778,0.0000067454807,0.000023301945,0.000019023353,0.00009930787,0.9886169,0.0014174042,0.0003127993,0.00044618978,0.0000186436],"about_ca_topic_score_codex":0.067718804,"about_ca_topic_score_gemma":0.036292523,"teacher_disagreement_score":0.067718804,"about_ca_system_score_codex":0.0011448856,"about_ca_system_score_gemma":0.0007728383,"threshold_uncertainty_score":0.13464928},"labels":[],"label_agreement":null},{"id":"W2604641069","doi":"10.1002/2016ms000871","title":"Tangent linear superparameterization of convection in a 10 layer global atmosphere with calibrated climatology","year":2017,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":6,"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":"Pacific Northwest National Laboratory; Office of Naval Research; Office of Science; Institute of Social and Economic Research, Memorial University of Newfoundland; National Oceanic and Atmospheric Administration; Battelle; U.S. Department of Energy","keywords":"Troposphere; Convection; Moisture; Advection; Atmosphere (unit); Water vapor; Atmospheric convection; Kelvin wave; Environmental science; Mechanics; Atmospheric sciences; Meteorology; Physics; Climatology; Geology; Thermodynamics","score_opus":0.02525908010618959,"score_gpt":0.288074730232724,"score_spread":0.2628156501265344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604641069","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94099426,0.00006119546,0.052581567,0.00018571988,0.00001590877,0.000028796188,0.0004933318,0.00033546786,0.0053037866],"genre_scores_gemma":[0.9971462,0.000014969482,0.0021413653,0.000014469774,0.0000040106456,0.000011031985,0.00014063754,0.000015499925,0.00051174447],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988675,0.000039385286,0.0000055470186,0.00003244166,0.000015572614,0.000020141912],"domain_scores_gemma":[0.99983263,0.00005521115,0.000034902423,0.000030737603,0.000028314267,0.000018133265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025075368,0.00031381537,0.0002034716,0.00018767428,0.00017550745,0.0006185961,0.0005732635,0.00033767283,0.0013477281],"category_scores_gemma":[0.00077895256,0.00019131598,0.00036022722,0.00023392742,0.0004162329,0.0006882098,0.00045602,0.00045430593,0.00010589346],"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":[0.000034406003,0.000019379142,0.0043745395,0.000007475958,0.000017682136,0.000029446925,0.000024560035,0.98771405,0.0021353029,0.003419275,0.00015359673,0.002070363],"study_design_scores_gemma":[0.0000047902113,0.000005791282,0.0010958103,6.838466e-7,0.000002291564,0.000002395022,0.000004278597,0.9980866,0.00016912556,0.0005360995,0.00008922122,0.0000028603956],"about_ca_topic_score_codex":0.015412805,"about_ca_topic_score_gemma":0.008203751,"teacher_disagreement_score":0.015412805,"about_ca_system_score_codex":0.00086273724,"about_ca_system_score_gemma":0.00047119797,"threshold_uncertainty_score":0.030646205},"labels":[],"label_agreement":null},{"id":"W2606780533","doi":"10.1002/2016ms000830","title":"Fully nonlinear statistical and machine‐learning approaches for hydrological frequency estimation at ungauged sites","year":2017,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Pacific Institute for Climate Solutions; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonlinear system; Quantile; Computer science; Artificial neural network; Linear model; Machine learning; Artificial intelligence; Mathematics; Statistics","score_opus":0.06639370173454329,"score_gpt":0.2908321233278244,"score_spread":0.2244384215932811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606780533","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.329662,0.00032664769,0.66705704,0.0002698838,0.00002918049,0.000051285988,0.00024486898,0.0003357211,0.0020233411],"genre_scores_gemma":[0.94807595,0.00012613644,0.050560076,0.000020650026,0.000020119334,0.000039935032,0.0001989039,0.000041713523,0.00091657933],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938524,0.00038095535,0.000023524688,0.00009395806,0.00007394931,0.000042321873],"domain_scores_gemma":[0.99822706,0.001191888,0.00021142742,0.00011522143,0.00021310154,0.000041216383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017665809,0.0005716891,0.0005044823,0.0010993017,0.00023018848,0.0006835405,0.0007093209,0.00045396853,0.001038456],"category_scores_gemma":[0.0036157968,0.00027307807,0.0008875927,0.0011144637,0.000411164,0.00071068696,0.0007587192,0.0007081385,0.00021636533],"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":[0.00004145203,0.000030914067,0.00647104,0.000037516562,0.000051976633,0.0000632971,0.000052672833,0.96127546,0.0008643697,0.0019602731,0.00017686494,0.028974062],"study_design_scores_gemma":[5.7523215e-7,0.0000031315076,0.0009689827,0.0000015677881,0.0000017005558,0.0000037356772,0.0000061512005,0.9984068,0.000073349205,0.00048625312,0.00004499047,0.0000028521567],"about_ca_topic_score_codex":0.01351325,"about_ca_topic_score_gemma":0.012413551,"teacher_disagreement_score":0.01351325,"about_ca_system_score_codex":0.0005011609,"about_ca_system_score_gemma":0.00075933,"threshold_uncertainty_score":0.026869178},"labels":[],"label_agreement":null},{"id":"W2610310793","doi":"10.1002/2016ms000822","title":"The “<scp>G</scp>rey <scp>Z</scp>one” cold air outbreak global model intercomparison: A cross evaluation using large‐eddy simulations","year":2016,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":40,"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":"Natural Environment Research Council; Sight Research UK","keywords":"Convection; Environmental science; Boundary layer; Atmospheric sciences; Meteorology; Planetary boundary layer; Precipitation; Large eddy simulation; Turbulence; Cloud physics; Climatology; Geology; Mechanics; Cloud computing; Physics; Computer science","score_opus":0.06717390127628936,"score_gpt":0.3311251545377289,"score_spread":0.26395125326143953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610310793","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.990211,0.00011262917,0.002914794,0.00030576566,0.00008593245,0.00015444329,0.0023396784,0.0006863305,0.003189532],"genre_scores_gemma":[0.98074466,0.000085108506,0.009734863,0.00012687226,0.000038422182,0.00025830677,0.007461115,0.00030353214,0.0012471313],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991153,0.00051055045,0.000039104198,0.00013372162,0.00011454114,0.00008674777],"domain_scores_gemma":[0.9975624,0.0011406406,0.00017021847,0.00038688778,0.0004627922,0.00027706177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005039522,0.0012874078,0.0008722716,0.000566856,0.00064256944,0.0011551687,0.00202117,0.0015831777,0.0012973413],"category_scores_gemma":[0.003112837,0.00049919233,0.0013454702,0.0006926394,0.00066364766,0.0012973783,0.0009121956,0.0011316981,0.00033964726],"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":[0.0033261327,0.0027063028,0.04478224,0.00021977331,0.0012356926,0.00038558798,0.0003136411,0.8979913,0.01500827,0.0019442252,0.009339274,0.022747578],"study_design_scores_gemma":[0.002714291,0.0017247703,0.04103975,0.00003747572,0.00029877067,0.000032709853,0.00019374414,0.9379334,0.012607791,0.0006010752,0.0027119066,0.000104358565],"about_ca_topic_score_codex":0.05101089,"about_ca_topic_score_gemma":0.032140665,"teacher_disagreement_score":0.05101089,"about_ca_system_score_codex":0.0010191377,"about_ca_system_score_gemma":0.0012464408,"threshold_uncertainty_score":0.10142797},"labels":[],"label_agreement":null},{"id":"W2681669025","doi":"10.1002/2017ms001014","title":"Implementation and calibration of a stochastic multicloud convective parameterization in the NCEP <scp>C</scp>limate <scp>F</scp>orecast <scp>S</scp>ystem (CFSv2)","year":2017,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":31,"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 Victoria","funders":"","keywords":"Climate Forecast System; Convection; Environmental science; Madden–Julian oscillation; Climatology; Meteorology; Robustness (evolution); Precipitation; Atmospheric sciences; Geology; Physics; Chemistry","score_opus":0.02965959063441011,"score_gpt":0.2974736260605726,"score_spread":0.2678140354261625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2681669025","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9782882,0.00005543618,0.01550178,0.0002467102,0.00006314411,0.00014441265,0.0015639805,0.0011673771,0.0029690203],"genre_scores_gemma":[0.9904441,0.000016948246,0.008473159,0.00003733053,0.000007408746,0.00008392091,0.0006909255,0.000072640105,0.00017343703],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996189,0.00012477016,0.000038831586,0.00008526886,0.00008399182,0.000048235343],"domain_scores_gemma":[0.99914515,0.0002806078,0.00009699009,0.00020765506,0.00021854199,0.00005105489],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016532857,0.00057442416,0.00035714917,0.00030232532,0.00047296038,0.0007161102,0.001562638,0.0008112152,0.0008656791],"category_scores_gemma":[0.00298719,0.000374539,0.00046372143,0.00043030517,0.00038268097,0.00078474445,0.0004963578,0.0007562123,0.00016626439],"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":[0.00017417267,0.00025031998,0.017447425,0.000043444947,0.00007401745,0.00005889491,0.000065856286,0.9640744,0.0066770394,0.00085057504,0.0007912396,0.009492566],"study_design_scores_gemma":[0.000099739176,0.000084148116,0.0066862684,0.000006916203,0.000016731314,0.000008346941,0.000020567548,0.9869441,0.0053466684,0.00012616538,0.00063920824,0.00002112845],"about_ca_topic_score_codex":0.04066178,"about_ca_topic_score_gemma":0.021063106,"teacher_disagreement_score":0.04066178,"about_ca_system_score_codex":0.0009570459,"about_ca_system_score_gemma":0.0012019342,"threshold_uncertainty_score":0.080850184},"labels":[],"label_agreement":null},{"id":"W2746033087","doi":"10.1002/2017ms001048","title":"Coastal Tropical Convection in a Stochastic Modeling Framework","year":2017,"lang":"en","type":"preprint","venue":"Journal of Advances in Modeling Earth Systems","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":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Parametrization (atmospheric modeling); Convection; Climatology; Meteorology; Atmospheric convection; Environmental science; Deep convection; Convection cell; Geology; Atmospheric sciences; Geography; Natural convection; Combined forced and natural convection; Physics; Radiative transfer","score_opus":0.03589636402136922,"score_gpt":0.30653800472078313,"score_spread":0.27064164069941393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2746033087","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19311404,0.0006055463,0.7965289,0.00069086865,0.00008253398,0.000065102475,0.00043306287,0.00028485345,0.008195076],"genre_scores_gemma":[0.9728905,0.00034599705,0.023687584,0.00006372465,0.0000898875,0.00009229448,0.00017212483,0.000038930404,0.0026190109],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965274,0.0001699513,0.00001921569,0.00006200263,0.000055378747,0.000040707906],"domain_scores_gemma":[0.9991229,0.00045236727,0.00018206512,0.000045963912,0.00011555945,0.00008110154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000994637,0.0005976517,0.0005809538,0.0004863801,0.00038145535,0.0010040451,0.0009167587,0.00055045733,0.0010371944],"category_scores_gemma":[0.0018152931,0.0002713654,0.0006496738,0.00041673318,0.00062739046,0.0006368944,0.00094723084,0.0005382654,0.0000894681],"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":[0.000010970774,0.000011788425,0.00073647,0.000010917909,0.000017754875,0.000040297364,0.000020261916,0.9581168,0.0005227783,0.03934799,0.000117647774,0.0010462863],"study_design_scores_gemma":[0.000002141057,0.0000033071294,0.000056022287,0.0000010591724,0.0000020665113,0.0000024367412,0.0000020571008,0.9966522,0.000027113998,0.0031262476,0.00012390446,0.0000015564476],"about_ca_topic_score_codex":0.012899677,"about_ca_topic_score_gemma":0.0064126626,"teacher_disagreement_score":0.012899677,"about_ca_system_score_codex":0.0010207628,"about_ca_system_score_gemma":0.0010407661,"threshold_uncertainty_score":0.02564919},"labels":[],"label_agreement":null},{"id":"W2750078372","doi":"10.1002/2017ms000934","title":"Process‐based<scp>TRIPLEX‐GHG</scp>model for simulating<scp>N</scp><sub>2</sub><scp>O</scp>emissions from global forests and grasslands:<scp>M</scp>odel development and evaluation","year":2017,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Environmental science; Atmospheric sciences; Nitrous oxide; Nitrification; Grassland; Greenhouse gas; Primary production; Snowmelt; Temperate forest; Temperate climate; Ecosystem; Snow; Ecology; Nitrogen; Chemistry; Meteorology; Biology; Geography","score_opus":0.02834288878259389,"score_gpt":0.29586334688263694,"score_spread":0.26752045810004305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2750078372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9402785,0.000109663066,0.04346353,0.00023059997,0.000052078063,0.000111805515,0.0027268159,0.00097361085,0.012053355],"genre_scores_gemma":[0.99076897,0.000040399624,0.0061475215,0.000023558578,0.000005254579,0.00009283759,0.0010115048,0.000030411533,0.0018795993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989295,0.000026518206,0.000005378973,0.000022254691,0.000030276857,0.000022610155],"domain_scores_gemma":[0.9998363,0.00005949951,0.00001937742,0.000017098297,0.000046095058,0.000021521671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042734414,0.00056319527,0.00048199992,0.00032515303,0.00035284457,0.0007426819,0.0008556434,0.0008271506,0.0016116657],"category_scores_gemma":[0.00044876026,0.00031169326,0.00061971374,0.0003208276,0.00047970426,0.00046437923,0.0004495978,0.00062617176,0.00022390128],"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":[0.000023874336,0.000017148352,0.0009752208,0.0000073992396,0.000009191622,0.000020148296,0.000004533243,0.9972053,0.0005863225,0.0002370885,0.00012041652,0.0007933235],"study_design_scores_gemma":[0.000011137066,0.000008884844,0.00039759604,7.400277e-7,0.0000024523686,0.0000016101104,0.0000031003917,0.9991296,0.0002597156,0.000075727214,0.000107572196,0.0000019160143],"about_ca_topic_score_codex":0.059826463,"about_ca_topic_score_gemma":0.02848217,"teacher_disagreement_score":0.059826463,"about_ca_system_score_codex":0.0010859537,"about_ca_system_score_gemma":0.0012050982,"threshold_uncertainty_score":0.11895645},"labels":[],"label_agreement":null},{"id":"W2751248724","doi":"10.1002/2017ms001025","title":"Analysis of near‐surface biases in <scp>ERA</scp>‐<scp>I</scp>nterim over the <scp>C</scp>anadian <scp>P</scp>rairies","year":2017,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":21,"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":"University of Vermont; National Science Foundation","keywords":"Environmental science; Diurnal cycle; Atmospheric sciences; Diurnal temperature variation; Snow; Daytime; Climatology; Forcing (mathematics); Meteorology; Physics; Geology","score_opus":0.031682081173140954,"score_gpt":0.2870154254119867,"score_spread":0.25533334423884574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751248724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99422485,0.000111831025,0.00069265935,0.00004125703,0.000015141122,0.000006336692,0.0038557723,0.00009076636,0.0009613666],"genre_scores_gemma":[0.9939032,0.00005271214,0.0011944503,0.000035743982,0.000009173041,0.000008046465,0.004246675,0.000020488686,0.0005295685],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998468,0.000032101863,0.0000090824215,0.000042358217,0.00003827425,0.000031334694],"domain_scores_gemma":[0.9996172,0.00007153239,0.0000687755,0.00007294144,0.00014307795,0.000026424139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005940803,0.00022765205,0.00021766787,0.0005375573,0.00020338198,0.00043513396,0.00028723173,0.0002559554,0.000827594],"category_scores_gemma":[0.00079820264,0.00017083743,0.00028808744,0.0008716941,0.00011773225,0.00027441306,0.00021204584,0.00019257532,0.00027850718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002478476,0.00005641195,0.93067586,0.00007316126,0.0005753487,0.00010743338,0.00012736814,0.023540227,0.016484339,0.00025156178,0.0027278678,0.02513251],"study_design_scores_gemma":[0.000011469279,0.000012640932,0.9796234,0.000012615594,0.000050987383,0.000028767377,0.000058728336,0.016333703,0.002159392,0.000058564074,0.0016338953,0.000015896994],"about_ca_topic_score_codex":0.0817611,"about_ca_topic_score_gemma":0.19213107,"teacher_disagreement_score":0.9182389,"about_ca_system_score_codex":0.0005742367,"about_ca_system_score_gemma":0.00043897107,"threshold_uncertainty_score":0.16257036},"labels":[],"label_agreement":null},{"id":"W2757442791","doi":"10.1002/2017ms000920","title":"Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model <scp>TRIPLEX‐GHG</scp>","year":2017,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada","keywords":"Soil carbon; Environmental science; Biogeochemical cycle; Carbon cycle; Soil organic matter; Carbon fibers; Environmental chemistry; Ecosystem; Tundra; Biomass (ecology); Soil science; Soil water; Chemistry; Ecology; Biology; Materials science","score_opus":0.021633123378390125,"score_gpt":0.2619035570859226,"score_spread":0.24027043370753248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2757442791","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91257674,0.00032853475,0.07698922,0.0005246249,0.00010880173,0.00006424496,0.0014989702,0.0007914072,0.0071174265],"genre_scores_gemma":[0.98846054,0.00011946679,0.009966948,0.00004212864,0.000020842443,0.000052923508,0.00050710625,0.000043497585,0.0007865875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998704,0.00004113909,0.000005733014,0.00003523864,0.000026891645,0.000020501893],"domain_scores_gemma":[0.9997603,0.00011020722,0.000031423977,0.000023963143,0.000044400404,0.000029552853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050919,0.00081399817,0.0005338386,0.00037797898,0.00036050152,0.00084591133,0.0007235893,0.001020143,0.0012498129],"category_scores_gemma":[0.0005403177,0.00032242728,0.0010222923,0.0005433961,0.0004566714,0.00068269315,0.00073875935,0.000831194,0.00015840781],"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":[0.000016460826,0.000018943892,0.0017155587,0.000010907131,0.000029547686,0.00003285925,0.0000060770926,0.99541414,0.0010380006,0.0005882031,0.00009834512,0.0010309125],"study_design_scores_gemma":[0.000005778677,0.000007161866,0.00039173625,6.6800607e-7,0.000004913541,0.000002759224,0.0000021633346,0.9991658,0.00014841367,0.00018278798,0.00008556225,0.0000022929785],"about_ca_topic_score_codex":0.034224946,"about_ca_topic_score_gemma":0.014267576,"teacher_disagreement_score":0.034224946,"about_ca_system_score_codex":0.00086166715,"about_ca_system_score_gemma":0.0008209735,"threshold_uncertainty_score":0.06805152},"labels":[],"label_agreement":null},{"id":"W2771552535","doi":"10.1002/2017ms001065","title":"An Optimally Stable and Accurate Second‐Order SSP Runge‐Kutta IMEX Scheme for Atmospheric Applications","year":2017,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Environment and Climate Change Canada; University of Ottawa","funders":"Environment Canada; University of Ottawa","keywords":"Scheme (mathematics); Runge–Kutta methods; Stability (learning theory); Property (philosophy); Monotonic function; Computer science; Applied mathematics; Order (exchange); Compressibility; Class (philosophy); Mathematics; Mathematical optimization; Numerical analysis; Mathematical analysis; Physics; Artificial intelligence","score_opus":0.01012795386183146,"score_gpt":0.27361638095569196,"score_spread":0.2634884270938605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771552535","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.067865826,0.00018122196,0.9258757,0.00008648828,0.000067962,0.00006484974,0.0000660837,0.0004086144,0.005383271],"genre_scores_gemma":[0.64074683,0.00014074189,0.35188723,0.00004297456,0.00003971867,0.0001738388,0.00016314267,0.00011137243,0.0066942326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998746,0.00003497239,0.000007879012,0.000014761572,0.00005330792,0.000014458272],"domain_scores_gemma":[0.99987185,0.00003311922,0.00001887672,0.000024003672,0.000041087274,0.000011014864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028192357,0.00037104817,0.0004407869,0.00014834937,0.00022856225,0.00038914118,0.00078897795,0.00044813447,0.0016334591],"category_scores_gemma":[0.00047947842,0.00017121446,0.00028117598,0.00016868958,0.00027762834,0.0003775886,0.00072739157,0.00059110974,0.00032207338],"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":[0.00019916725,0.00009900453,0.0019108573,0.00018460848,0.00003110494,0.00015090371,0.00018476206,0.83548,0.05855469,0.031445052,0.0015681399,0.070191756],"study_design_scores_gemma":[0.000009000092,0.000029336084,0.0001165786,0.0000034982766,0.0000020070242,0.000011256985,0.0000049983782,0.9954224,0.002962821,0.00036151425,0.0010731677,0.0000033579547],"about_ca_topic_score_codex":0.0017353385,"about_ca_topic_score_gemma":0.001301889,"teacher_disagreement_score":0.0017353385,"about_ca_system_score_codex":0.00022170453,"about_ca_system_score_gemma":0.00053658086,"threshold_uncertainty_score":0.005464494},"labels":[],"label_agreement":null},{"id":"W2800601928","doi":"10.1002/2017ms001052","title":"Full Coupling Between the Atmosphere, Surface, and Subsurface for Integrated Hydrologic Simulation","year":2017,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":35,"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 Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Weather Research and Forecasting Model; Evapotranspiration; Environmental science; Water cycle; Mesoscale meteorology; Precipitation; Sensible heat; Latent heat; Atmosphere (unit); Climate model; Meteorology; Atmospheric sciences; Geology; Climatology; Climate change; Geography","score_opus":0.05241495025519727,"score_gpt":0.29836419196674024,"score_spread":0.24594924171154298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800601928","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6961707,0.00021679435,0.28615797,0.00043570413,0.0001159892,0.0001118219,0.0008571431,0.0015538185,0.014380016],"genre_scores_gemma":[0.97553647,0.000054572636,0.023054654,0.00004583073,0.000014524742,0.00007611669,0.00021434358,0.00007022639,0.0009332561],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998641,0.00004003491,0.000007868672,0.000023640294,0.0000413279,0.000023032007],"domain_scores_gemma":[0.9997154,0.00011635561,0.000022244563,0.00005367844,0.000054346106,0.000037964597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037857005,0.00049231725,0.00041520712,0.0002744225,0.00039919597,0.00061515253,0.00077944924,0.0006618494,0.0017061699],"category_scores_gemma":[0.0011235024,0.00032219372,0.00056794274,0.00031202298,0.00046020083,0.00077412033,0.0010833761,0.0008268385,0.00018502488],"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":[0.000024629631,0.000038654103,0.001916004,0.000011770108,0.00002110068,0.000030363834,0.000021763326,0.990581,0.0018490141,0.0021813698,0.00021658755,0.003107884],"study_design_scores_gemma":[0.000007708589,0.000006818095,0.00020069111,9.75229e-7,0.000001915419,0.0000014954974,0.0000027537797,0.9991172,0.0001454074,0.00038070665,0.00013266505,0.0000017042084],"about_ca_topic_score_codex":0.036468044,"about_ca_topic_score_gemma":0.022319296,"teacher_disagreement_score":0.036468044,"about_ca_system_score_codex":0.0007016901,"about_ca_system_score_gemma":0.001459339,"threshold_uncertainty_score":0.072511494},"labels":[],"label_agreement":null},{"id":"W2800694964","doi":"10.1029/2017ms001044","title":"Robust Inverse Modeling of Growing Season Net Ecosystem Exchange in a Mountainous Peatland: Influence of Distributional Assumptions on Estimated Parameters and Total Carbon Fluxes","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Deutscher Akademischer Austauschdienst; Universität Hohenheim","keywords":"Environmental science; Eddy covariance; Peat; Atmospheric sciences; Covariance; Statistics; Mathematics; Ecosystem; Geography; Ecology; Physics","score_opus":0.023220424063626788,"score_gpt":0.2510013682060331,"score_spread":0.2277809441424063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800694964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86578864,0.000047389065,0.13360539,0.000055935714,0.0000047209646,0.000012787087,0.000049539,0.00006496235,0.00037059977],"genre_scores_gemma":[0.9947699,0.0000188089,0.005010634,0.0000059973695,0.0000024306019,0.000010584255,0.000032474076,0.000007907865,0.00014137193],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969625,0.00015174648,0.000016059288,0.000060540562,0.000040611725,0.00003475843],"domain_scores_gemma":[0.9966229,0.0026780413,0.0003836349,0.00009731591,0.00017068646,0.00004732741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023298773,0.00035611936,0.0004175396,0.0003005487,0.00024788763,0.00065990386,0.0005751572,0.0005604335,0.0002479316],"category_scores_gemma":[0.0063512023,0.00029430963,0.00058909255,0.00016347655,0.00081274606,0.0004178643,0.00047137093,0.000481125,0.000026783608],"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":[0.000028161701,0.000012951287,0.0027861362,0.0000082136285,0.000017393988,0.000043910437,0.000019287592,0.9935389,0.0009140765,0.0011798867,0.000011392047,0.0014396559],"study_design_scores_gemma":[0.000002003277,0.0000084386165,0.00095843273,0.000001643588,0.0000032353535,0.000008106118,0.0000039072256,0.9983796,0.00022223119,0.00039877667,0.000010244337,0.0000033466133],"about_ca_topic_score_codex":0.016661117,"about_ca_topic_score_gemma":0.0072383676,"teacher_disagreement_score":0.016661117,"about_ca_system_score_codex":0.00053972576,"about_ca_system_score_gemma":0.0007329181,"threshold_uncertainty_score":0.03312826},"labels":[],"label_agreement":null},{"id":"W2801203986","doi":"10.1029/2017ms001219","title":"Impacts of Aerosol Dry Deposition on Black Carbon Spatial Distributions and Radiative Effects in the Community Atmosphere Model CAM5","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":55,"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; National Aeronautics and Space Administration; Pacific Northwest National Laboratory; National Science Foundation","keywords":"Atmospheric sciences; Aerosol; Environmental science; Troposphere; Atmospheric model; Radiative transfer; Arctic; Atmosphere (unit); Radiative forcing; Climatology; Deposition (geology); Meteorology; Physics; Geology","score_opus":0.012003262940374236,"score_gpt":0.24404280606797948,"score_spread":0.23203954312760525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801203986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922156,0.0002028616,0.0011001315,0.0002646657,0.00006488331,0.000040098224,0.0020621861,0.0003609928,0.0036884265],"genre_scores_gemma":[0.99665606,0.00005723673,0.0013251652,0.00008773709,0.000013396711,0.00003150367,0.0014946332,0.000049254457,0.00028485057],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965465,0.00010454671,0.000021638843,0.00008209675,0.000054266107,0.000082848106],"domain_scores_gemma":[0.999057,0.00032644044,0.0000867739,0.000086669854,0.00023913525,0.00020392501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010538232,0.0014761573,0.00075852545,0.00058944727,0.00094774953,0.0011470589,0.0025556777,0.0019944839,0.0019578012],"category_scores_gemma":[0.001632384,0.0004986122,0.001207479,0.0006938487,0.00055538147,0.00090928725,0.0007281815,0.0011183433,0.00027409615],"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":[0.00072263525,0.00044652802,0.041410834,0.00014601121,0.00023702353,0.00023552444,0.00008129592,0.9419169,0.0066441908,0.0011678179,0.0022113554,0.004779932],"study_design_scores_gemma":[0.00027831734,0.00015972364,0.010016616,0.000012320501,0.000054854398,0.000015419422,0.00004300827,0.98713833,0.0014811133,0.00015483487,0.00061017554,0.000035196386],"about_ca_topic_score_codex":0.16564423,"about_ca_topic_score_gemma":0.06586909,"teacher_disagreement_score":0.16564423,"about_ca_system_score_codex":0.0022141142,"about_ca_system_score_gemma":0.0019983258,"threshold_uncertainty_score":0.32936013},"labels":[],"label_agreement":null},{"id":"W2805425493","doi":"10.1029/2017ms001240","title":"An Economical Model for Simulating Turbulence Enhancement of Droplet Collisions and Coalescence","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Particle Dynamics in Fluid Flows","field":"Engineering","cited_by":12,"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":"National Science Foundation of Sri Lanka; McGill University; National Science Foundation","keywords":"Turbulence; Coalescence (physics); Mechanics; Physics; Microscale chemistry; Collision; Eddy; Inertia; Direct numerical simulation; Stokes number; Advection; Kolmogorov microscales; Large eddy simulation; Statistical physics; K-epsilon turbulence model; Classical mechanics; Thermodynamics; K-omega turbulence model; Reynolds number; Mathematics; Computer science","score_opus":0.020582059776580505,"score_gpt":0.2928197587428924,"score_spread":0.2722376989663119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805425493","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6045164,0.00016753328,0.38256833,0.00025009268,0.00008925366,0.00024185736,0.00058776187,0.00091211754,0.010666634],"genre_scores_gemma":[0.9498388,0.00006670933,0.047761388,0.000047793284,0.000017754826,0.00024211321,0.00020450898,0.0000955619,0.0017254335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998066,0.000046206223,0.000010377198,0.000023057275,0.00007852646,0.00003529235],"domain_scores_gemma":[0.99926573,0.00035213315,0.00010172217,0.000072220544,0.00013426007,0.0000739239],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057938776,0.00044909277,0.00039337002,0.0005894495,0.00058910745,0.0007095963,0.0010794413,0.0007018817,0.0011872369],"category_scores_gemma":[0.0014901125,0.00031887114,0.0004550688,0.00041746316,0.0006167123,0.0005134443,0.0008779592,0.0005155951,0.00013208027],"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":[0.000044072014,0.000027975806,0.0016540954,0.000013311509,0.000012904283,0.000067092675,0.000022011342,0.9873346,0.003571996,0.0050002327,0.00021482642,0.0020368584],"study_design_scores_gemma":[0.000005195483,0.000007444024,0.00008397408,6.197952e-7,0.0000012202821,0.0000029799776,0.000001780964,0.9990982,0.00048741535,0.00017563536,0.00013366311,0.0000018289732],"about_ca_topic_score_codex":0.009987275,"about_ca_topic_score_gemma":0.0054179993,"teacher_disagreement_score":0.009987275,"about_ca_system_score_codex":0.0011482986,"about_ca_system_score_gemma":0.0014034356,"threshold_uncertainty_score":0.019858241},"labels":[],"label_agreement":null},{"id":"W2810027500","doi":"10.1029/2017ms001231","title":"Evaluation and Intercomparison of Five North American Dry Deposition Algorithms at a Mixed Forest Site","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":92,"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":"U.S. Environmental Protection Agency","keywords":"Diel vertical migration; Environmental science; Temperate climate; Atmospheric sciences; Deposition (geology); Flux (metallurgy); Climatology; Temperate forest; Meteorology; Geology; Ecology; Geography; Chemistry; Oceanography","score_opus":0.01770057552918805,"score_gpt":0.26748254904555374,"score_spread":0.2497819735163657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810027500","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9911542,0.00012476729,0.0061747623,0.00005044661,0.000019458843,0.000078324825,0.0002623947,0.0006035027,0.0015319885],"genre_scores_gemma":[0.98315537,0.00007753336,0.015234872,0.000039460418,0.0000057518064,0.00008804915,0.00075715175,0.00008037843,0.00056151144],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995865,0.00010944094,0.00003075132,0.00013533382,0.00008412241,0.000053879634],"domain_scores_gemma":[0.99914443,0.00029067788,0.000066565415,0.00006582285,0.00034952702,0.00008288933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022663127,0.0012281049,0.0007867943,0.0006954246,0.0009041822,0.00121533,0.0012248952,0.000727255,0.00047147876],"category_scores_gemma":[0.001831613,0.0005311506,0.0007403077,0.0006324668,0.0002657948,0.0007146996,0.0004789561,0.0003871848,0.00013106504],"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":[0.0010821095,0.0006785499,0.10682344,0.00010599462,0.0005843414,0.00010094679,0.00030771317,0.8015146,0.0056819064,0.0003880396,0.001343725,0.08138856],"study_design_scores_gemma":[0.00019175172,0.00022008589,0.027501427,0.000013391439,0.00013082754,0.0000179228,0.00012075363,0.9679446,0.0029991555,0.00012471015,0.0007051307,0.000030277068],"about_ca_topic_score_codex":0.1712051,"about_ca_topic_score_gemma":0.14312115,"teacher_disagreement_score":0.1712051,"about_ca_system_score_codex":0.0023701028,"about_ca_system_score_gemma":0.0017391624,"threshold_uncertainty_score":0.34041715},"labels":[],"label_agreement":null},{"id":"W2888244295","doi":"10.1029/2018ms001327","title":"The Relative Influence of Atmospheric and Oceanic Model Resolution on the Circulation of the North Atlantic Ocean in a Coupled Climate Model","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":84,"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; European Commission","keywords":"Atmosphere (unit); Climatology; Climate model; Ocean current; Environmental science; Atmospheric model; Ocean dynamics; Oceanic basin; General Circulation Model; Geology; Oceanography; Atmospheric sciences; Climate change; Structural basin; Meteorology; Geography","score_opus":0.015351865272436786,"score_gpt":0.2401845903203503,"score_spread":0.22483272504791352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888244295","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99678624,0.00016703742,0.0014683377,0.00012848039,0.00001999505,0.000009754061,0.00022348837,0.000057590936,0.0011390295],"genre_scores_gemma":[0.998591,0.00006637461,0.0010683798,0.000029909592,0.00000620415,0.000010617152,0.00013033273,0.000011579751,0.00008556573],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995735,0.00020924209,0.000040294926,0.00006375769,0.000056068413,0.000057113553],"domain_scores_gemma":[0.9974936,0.0018088034,0.00017342145,0.00020000321,0.000195105,0.00012905126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013778617,0.00051096344,0.00049601775,0.00033455915,0.000455985,0.0010703171,0.00061434484,0.0006932439,0.0007857572],"category_scores_gemma":[0.005023747,0.00038018034,0.00072103355,0.00045782473,0.0005775493,0.0006232217,0.0006578279,0.00075119035,0.00006864625],"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":[0.00059164607,0.0001602893,0.034627654,0.0000671655,0.00031730114,0.000114272756,0.000049807888,0.9497119,0.009918172,0.0007566637,0.00033537,0.0033496458],"study_design_scores_gemma":[0.00020441701,0.00033690134,0.02245707,0.000030505764,0.00023426516,0.00002312557,0.00007848366,0.97088325,0.004976452,0.00039451892,0.00034162047,0.000039399718],"about_ca_topic_score_codex":0.01938143,"about_ca_topic_score_gemma":0.011071648,"teacher_disagreement_score":0.01938143,"about_ca_system_score_codex":0.0005187938,"about_ca_system_score_gemma":0.0005031694,"threshold_uncertainty_score":0.038537264},"labels":[],"label_agreement":null},{"id":"W2889528509","doi":"10.1029/2017ms001270","title":"Modeling Sediment Yield in Land Surface and Earth System Models: Model Comparison, Development, and Evaluation","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Pacific Northwest National Laboratory; Battelle; U.S. Geological Survey; Agricultural Research Service; Environment and Climate Change Canada; Office of Science; U.S. Department of Agriculture; U.S. Department of Energy","keywords":"Surface runoff; Snowmelt; Erosion; Environmental science; Hydrology (agriculture); Stream power; Sediment; Predictability; Context (archaeology); Biogeochemistry; Earth system science; Geology; Geomorphology; Oceanography; Ecology","score_opus":0.08947189582776935,"score_gpt":0.2899951467562291,"score_spread":0.20052325092845977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889528509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97034365,0.00037585356,0.023151323,0.00025069522,0.00005533856,0.00018438237,0.0012432857,0.0006982616,0.003697286],"genre_scores_gemma":[0.98756546,0.0001815053,0.010907016,0.000027469318,0.000014839757,0.0000875815,0.0006168655,0.000063707244,0.0005356577],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961394,0.00015960138,0.000035777186,0.00006270749,0.00008586364,0.000042129584],"domain_scores_gemma":[0.99862003,0.00070328556,0.00010067554,0.00012522012,0.00038007673,0.00007059091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018451763,0.0009861299,0.0007426423,0.0007552156,0.00033803357,0.0010091667,0.0014970211,0.0007334883,0.00086270354],"category_scores_gemma":[0.0032521824,0.00042855166,0.0008151539,0.0009825662,0.00042802296,0.0010545166,0.0006671813,0.0007681776,0.00014921874],"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":[0.00004355514,0.00006960796,0.003434561,0.000017294862,0.000034750235,0.000017573015,0.000009468203,0.99200624,0.00024807215,0.00034273154,0.00017373046,0.0036025487],"study_design_scores_gemma":[0.000015007503,0.000028334085,0.00075506925,0.0000019970294,0.000009209544,0.000001681454,0.000006580328,0.99871635,0.00028075316,0.00009087034,0.00008986538,0.00000435579],"about_ca_topic_score_codex":0.10134547,"about_ca_topic_score_gemma":0.051737484,"teacher_disagreement_score":0.10134547,"about_ca_system_score_codex":0.002165493,"about_ca_system_score_gemma":0.0012607769,"threshold_uncertainty_score":0.20151114},"labels":[],"label_agreement":null},{"id":"W2893584644","doi":"10.1029/2018ms001444","title":"Explicitly Accounting for the Role of Remote Oceans in Regional Climate Modeling of South America","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":8,"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":"Université du Québec à Montréal; National Center for Atmospheric Research; National Science Foundation","keywords":"Downscaling; Teleconnection; Climate model; Climatology; Environmental science; Scale (ratio); General Circulation Model; Climate change; Domain (mathematical analysis); Atmospheric model; Meteorology; Computer science; Geography; Geology; El Niño Southern Oscillation; Oceanography","score_opus":0.027341238917135486,"score_gpt":0.2744594884058315,"score_spread":0.247118249488696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893584644","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97743714,0.00013314735,0.018161636,0.00041605378,0.000019430638,0.000027788015,0.00018514013,0.00012347713,0.0034960795],"genre_scores_gemma":[0.9951534,0.00004747481,0.0043558464,0.000037931455,0.0000061454757,0.00001672082,0.00005533202,0.000019250903,0.0003078902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998281,0.000086452994,0.000008719686,0.000038143593,0.000018165274,0.000020481813],"domain_scores_gemma":[0.99955314,0.0001881411,0.00006785823,0.00007366812,0.00006847222,0.000048715527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006597702,0.00034827107,0.00030712492,0.00026787558,0.00046302774,0.00081079017,0.00077703455,0.0006100921,0.0008804045],"category_scores_gemma":[0.0017343634,0.00025121553,0.000508018,0.0003850607,0.00046525587,0.00082416437,0.0011825992,0.0007129194,0.00005606748],"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":[0.00003902152,0.000033771663,0.030018672,0.000021206873,0.000059625454,0.000084316795,0.00011907164,0.9586967,0.0032535603,0.0033145668,0.0002619755,0.0040974347],"study_design_scores_gemma":[0.000019167468,0.00001443519,0.0054185656,0.000008111003,0.000019639834,0.000008580024,0.000044985016,0.99215275,0.0007134106,0.0009423557,0.00064807566,0.000009813022],"about_ca_topic_score_codex":0.10670602,"about_ca_topic_score_gemma":0.08403127,"teacher_disagreement_score":0.10670602,"about_ca_system_score_codex":0.0012475324,"about_ca_system_score_gemma":0.0018880051,"threshold_uncertainty_score":0.21216983},"labels":[],"label_agreement":null},{"id":"W2899727215","doi":"10.1029/2018ms001389","title":"Evaluation of Simulated Snow and Snowmelt Timing in the Community Land Model Using Satellite‐Based Products and Streamflow Observations","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Goddard Space Flight Center; National Aeronautics and Space Administration","keywords":"Snowmelt; Snow; Streamflow; Environmental science; Terrain; Climatology; Satellite; Surface runoff; Meteorology; Atmospheric sciences; Hydrology (agriculture); Geology; Drainage basin; Geography; Physics","score_opus":0.19710285819458007,"score_gpt":0.33194304894971455,"score_spread":0.13484019075513448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899727215","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99774843,0.000027127544,0.0009653691,0.00004889384,0.000010067073,0.0000264029,0.00036031211,0.00017356969,0.0006398149],"genre_scores_gemma":[0.99635625,0.00001778155,0.0025195864,0.000015840144,0.0000045160596,0.000032174346,0.0007844735,0.000035224028,0.00023409758],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995421,0.00019115173,0.000023656357,0.000093209586,0.0000770037,0.00007291203],"domain_scores_gemma":[0.99845815,0.00061087415,0.00015406641,0.00011803639,0.00043906015,0.00021980586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019287502,0.0011270402,0.0006758818,0.00055409316,0.000512962,0.0008070666,0.0016423763,0.0011851009,0.00096041826],"category_scores_gemma":[0.003267075,0.00053658494,0.0006543944,0.00057828793,0.00042119954,0.0010710887,0.0006948864,0.0006331731,0.00018451923],"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":[0.000460133,0.00025358037,0.04435351,0.00003336455,0.00011623868,0.00009396793,0.000055969507,0.9476982,0.0022390676,0.00020322388,0.0003013801,0.004191439],"study_design_scores_gemma":[0.0001242009,0.00012798689,0.0053885086,0.0000043771656,0.000018446386,0.00000766355,0.000026132953,0.9932579,0.00081255456,0.000066162254,0.00015298303,0.000013160025],"about_ca_topic_score_codex":0.09399775,"about_ca_topic_score_gemma":0.053597867,"teacher_disagreement_score":0.09399775,"about_ca_system_score_codex":0.0021834415,"about_ca_system_score_gemma":0.002142461,"threshold_uncertainty_score":0.18690121},"labels":[],"label_agreement":null},{"id":"W2904469151","doi":"10.1029/2018ms001512","title":"Three‐Moment Representation of Rain in a Bulk Microphysics Model","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":58,"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":"Biological and Environmental Research; Office of Science; Battelle","keywords":"Drizzle; Bin; Environmental science; Drop (telecommunication); Breakup; Evaporation; Meteorology; Atmospheric sciences; Moment (physics); Physics; Mathematics; Precipitation; Mechanics; Computer science","score_opus":0.04165827410301346,"score_gpt":0.2818117475298936,"score_spread":0.24015347342688012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904469151","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24289629,0.00016580058,0.7371151,0.0002479305,0.00010849342,0.000158253,0.002730804,0.0024222245,0.014155151],"genre_scores_gemma":[0.9467944,0.000120621036,0.0476221,0.00007364919,0.00005128667,0.00020684028,0.0011294782,0.00036186154,0.003639837],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998894,0.000022470691,0.000006535591,0.000020897582,0.00004008983,0.000020613266],"domain_scores_gemma":[0.9997373,0.00009203951,0.00002861237,0.00005100176,0.00006560627,0.00002553321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027364053,0.000476127,0.0004853628,0.00035935635,0.00030871428,0.00066268357,0.0013940452,0.0005825587,0.0022104175],"category_scores_gemma":[0.00071136723,0.00028692576,0.0007329971,0.0003902875,0.00024860716,0.0008426913,0.0004660446,0.00077193254,0.00040630653],"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":[0.000040891115,0.000032525528,0.0017424345,0.000017609002,0.000018349201,0.000042554595,0.000021864988,0.9817806,0.0040235897,0.0064363806,0.00072769355,0.0051154885],"study_design_scores_gemma":[0.0000056345857,0.000006555911,0.00024105044,9.5158384e-7,0.000002280568,0.000005436104,0.0000020554269,0.9983354,0.00031770143,0.00068593636,0.0003941124,0.0000029826876],"about_ca_topic_score_codex":0.012799283,"about_ca_topic_score_gemma":0.00562872,"teacher_disagreement_score":0.012799283,"about_ca_system_score_codex":0.0006233268,"about_ca_system_score_gemma":0.0009033801,"threshold_uncertainty_score":0.025449574},"labels":[],"label_agreement":null},{"id":"W2905150721","doi":"10.1029/2018ms001445","title":"Major Issues in Simulating Some Arctic Snowpack Properties Using Current Detailed Snow Physics Models: Consequences for the Thermal Regime and Water Budget of Permafrost","year":2018,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":167,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université Laval; Makivik Corporation","funders":"Fondation BNP Paribas; Natural Sciences and Engineering Research Council of Canada; Institut Polaire Français Paul Emile Victor; Center for Neuroscience and Regenerative Medicine; BNP Paribas Cardif; Agence Nationale de la Recherche; Parks Canada","keywords":"Snowpack; Permafrost; Snow; Arctic; Environmental science; Stratification (seeds); Atmospheric sciences; Latent heat; Climatology; Geology; Meteorology; Geomorphology; Physics","score_opus":0.09469476834865981,"score_gpt":0.304176169009514,"score_spread":0.2094814006608542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905150721","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9883627,0.00013645751,0.008324764,0.0002279285,0.000026170848,0.0000733853,0.0005176605,0.00022493364,0.0021059946],"genre_scores_gemma":[0.9937191,0.000095356445,0.005512998,0.00004267757,0.000008958546,0.00004421619,0.00025706788,0.000027386206,0.00029214102],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997372,0.00010663327,0.00001821747,0.000037691254,0.000046657853,0.000053677053],"domain_scores_gemma":[0.9993911,0.00027833998,0.000060132243,0.00008199359,0.00012225831,0.00006618611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077352935,0.00061244454,0.0005707532,0.00028120118,0.0006178198,0.001143365,0.0010669159,0.0010379604,0.0006474325],"category_scores_gemma":[0.0016003844,0.0004370564,0.00086636236,0.0004114453,0.00046565075,0.0005298566,0.00045549063,0.0006486801,0.00009581993],"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":[0.00007041835,0.00007937351,0.008730921,0.000029236218,0.000039264647,0.00004815078,0.00003569292,0.98630685,0.0025482648,0.00030594313,0.00008020849,0.0017255542],"study_design_scores_gemma":[0.000046144138,0.00006369191,0.0035060516,0.000010018179,0.00002306394,0.000009580387,0.0000463433,0.9942595,0.0015970517,0.00018008004,0.00024748233,0.000011001097],"about_ca_topic_score_codex":0.056817517,"about_ca_topic_score_gemma":0.036629304,"teacher_disagreement_score":0.056817517,"about_ca_system_score_codex":0.0010480478,"about_ca_system_score_gemma":0.0012619458,"threshold_uncertainty_score":0.11297363},"labels":[],"label_agreement":null},{"id":"W2908148979","doi":"10.1029/2018ms001363","title":"Modeling Global Riverine DOC Flux Dynamics From 1951 to 2015","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Environmental science; Dissolved organic carbon; Carbon cycle; Ecosystem; Flux (metallurgy); Terrestrial ecosystem; Global change; Water cycle; Hydrology (agriculture); Primary production; Atmospheric sciences; Climate change; Ecology; Oceanography; Geology; Chemistry; Biology","score_opus":0.008240813638980377,"score_gpt":0.23238241659628597,"score_spread":0.2241416029573056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2908148979","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99438006,0.00011335465,0.0028399252,0.00007003038,0.000012356123,0.000009526824,0.001670029,0.00017324109,0.0007314951],"genre_scores_gemma":[0.9971533,0.00006589396,0.0014691621,0.000014216227,0.0000048565876,0.000011222498,0.0010685655,0.000013185933,0.0001995323],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999143,0.000016577496,0.0000073159986,0.00003796006,0.000008517428,0.000015378128],"domain_scores_gemma":[0.99985206,0.000042769232,0.000026949197,0.000023818468,0.000036029116,0.000018429126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036199254,0.00042768734,0.000277926,0.00048808366,0.00027577297,0.0005106228,0.00037049147,0.0004843592,0.00054042327],"category_scores_gemma":[0.0004946836,0.00024491604,0.00079471525,0.0006678543,0.0002929254,0.000545391,0.00032207184,0.00031181274,0.000100577716],"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":[0.00005239044,0.000033367705,0.07909938,0.00004611111,0.00013756799,0.000097327465,0.000046912177,0.9121655,0.0017790332,0.0005019817,0.00045175018,0.005588708],"study_design_scores_gemma":[0.000021388547,0.000032909767,0.050600838,0.000008755921,0.000064011045,0.000019523475,0.000044699056,0.94659156,0.0012649741,0.00033027408,0.0009970499,0.000024007439],"about_ca_topic_score_codex":0.051581465,"about_ca_topic_score_gemma":0.03178322,"teacher_disagreement_score":0.051581465,"about_ca_system_score_codex":0.0011040075,"about_ca_system_score_gemma":0.00064334244,"threshold_uncertainty_score":0.10256249},"labels":[],"label_agreement":null},{"id":"W2921025948","doi":"10.1029/2018ms001603","title":"The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":896,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Workers Compensation Board of Alberta; University of British Columbia","funders":"Biological and Environmental Research; Office of Science; National Research Foundation; U.S. Department of Energy","keywords":"Climatology; Climate model; Coupled model intercomparison project; Environmental science; Radiative forcing; Forcing (mathematics); Earth system science; Predictability; Meteorology; Atmospheric sciences; Aerosol; Geology; Climate change; Geography; Physics","score_opus":0.02957760213283273,"score_gpt":0.2961470223610742,"score_spread":0.2665694202282415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921025948","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87657356,0.0010071538,0.031405218,0.00097505737,0.00020939451,0.000911257,0.056922927,0.011054485,0.0209409],"genre_scores_gemma":[0.8969312,0.0004456724,0.04452296,0.0002568289,0.00004603463,0.0007006973,0.053300675,0.0017449431,0.0020509479],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990778,0.00036672552,0.00008453354,0.00012794054,0.00025590876,0.000086963184],"domain_scores_gemma":[0.9976978,0.0008874861,0.0001467031,0.00038101926,0.0007543348,0.0001327748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036909534,0.0015460287,0.0010034193,0.0007787406,0.00059692643,0.0011338822,0.0029756788,0.0011448397,0.0032128447],"category_scores_gemma":[0.0059113153,0.0007250258,0.0009046739,0.0013568869,0.0004929625,0.0013575766,0.00093478226,0.0010364555,0.000874174],"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":[0.0005776719,0.00028700355,0.013457804,0.00024647897,0.00022250539,0.00012308708,0.00007767908,0.9552187,0.0021043967,0.00163843,0.007979772,0.018066457],"study_design_scores_gemma":[0.00028030024,0.00019477906,0.00597466,0.000028588825,0.00005034237,0.00001847399,0.0000585417,0.98773557,0.0022513869,0.00046200174,0.002891111,0.000054154563],"about_ca_topic_score_codex":0.10397721,"about_ca_topic_score_gemma":0.056631185,"teacher_disagreement_score":0.10397721,"about_ca_system_score_codex":0.0014643387,"about_ca_system_score_gemma":0.0017140605,"threshold_uncertainty_score":0.20674396},"labels":[],"label_agreement":null},{"id":"W2921073006","doi":"10.1029/2018ms001352","title":"Explicit Representation of Grazing Activity in a Diagnostic Terrestrial Model: A Data‐Process Combined Scheme","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Rangeland Management and Livestock Ecology","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":"National Key Research and Development Program of China; National Oceanic and Atmospheric Administration; East China Normal University; Priority Academic Program Development of Jiangsu Higher Education Institutions; University of Toronto; Nanjing University; Nanjing Forestry University; University of Oklahoma","keywords":"Grazing; Environmental science; Livestock; Ecosystem; Terrestrial ecosystem; Pasture; Biomass (ecology); Steppe; Temperate climate; Ecology; Biology","score_opus":0.03140396102382097,"score_gpt":0.30665107572612915,"score_spread":0.27524711470230817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921073006","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46915635,0.00024201492,0.52054155,0.00049359276,0.00009030204,0.00016117757,0.0007944106,0.0007659999,0.0077545918],"genre_scores_gemma":[0.9829778,0.00003823171,0.015763042,0.000029794088,0.0000145017675,0.000069771384,0.00016856704,0.00001993172,0.00091831],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998004,0.00007350407,0.000016099451,0.000037971375,0.000039065835,0.000033012257],"domain_scores_gemma":[0.99941206,0.00027512715,0.00007123054,0.00006042738,0.00012908963,0.000052021962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006478806,0.00056123256,0.0005640093,0.00038946202,0.00042244766,0.00070891296,0.0011749694,0.0011523097,0.0018549009],"category_scores_gemma":[0.0013676846,0.00037430288,0.00068679295,0.00038419297,0.00048414618,0.00069271465,0.0007404675,0.0007404019,0.00015003241],"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":[0.000024908642,0.000021267102,0.0011159362,0.000008211203,0.000010929529,0.000026974178,0.0000094829975,0.99585766,0.00043795607,0.0008625948,0.000053512067,0.0015705753],"study_design_scores_gemma":[0.0000026978382,0.0000038188145,0.000050815317,4.401152e-7,0.000001276357,0.0000011326753,9.183143e-7,0.99979335,0.00003803965,0.000079756304,0.00002680825,8.596181e-7],"about_ca_topic_score_codex":0.024726218,"about_ca_topic_score_gemma":0.009653978,"teacher_disagreement_score":0.024726218,"about_ca_system_score_codex":0.00078643067,"about_ca_system_score_gemma":0.00078720105,"threshold_uncertainty_score":0.049164593},"labels":[],"label_agreement":null},{"id":"W2923666357","doi":"10.1029/2018ms001532","title":"A New TKE‐Based Parameterization of Atmospheric Turbulence in the Canadian Global and Regional Climate Models","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Pacific Institute for Climate Solutions; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Turbulence; Turbulence kinetic energy; Environmental science; Marine stratocumulus; Meteorology; Turbulence modeling; Climate model; Planetary boundary layer; Convection; Large eddy simulation; Boundary layer; Atmospheric sciences; Mechanics; Physics; Geology; Climate change; Aerosol","score_opus":0.027878542254914117,"score_gpt":0.24471238127296632,"score_spread":0.2168338390180522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2923666357","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80345803,0.00059552415,0.15506603,0.000802625,0.00015123177,0.00025379943,0.00652346,0.0016558311,0.031493537],"genre_scores_gemma":[0.9773761,0.00015526642,0.018049205,0.00003733765,0.00001646713,0.000079609374,0.0015470779,0.00012144793,0.0026174316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998154,0.000029092313,0.000013027375,0.0000392099,0.00006521551,0.00003814078],"domain_scores_gemma":[0.9997533,0.000035778725,0.000015536714,0.000029420255,0.00014564421,0.000020336374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044488243,0.0006244676,0.0003793603,0.00053300883,0.000890757,0.0012969441,0.0012504441,0.0005062657,0.0011961624],"category_scores_gemma":[0.0011360245,0.0002862596,0.0005773035,0.0006469332,0.00045346032,0.00079969526,0.0004926801,0.0007796565,0.00017567755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002066132,0.000021003309,0.0034464975,0.000013304682,0.000022677095,0.0000143333145,0.000019730707,0.98555195,0.0011235133,0.002954437,0.00046464507,0.0063471673],"study_design_scores_gemma":[0.00000894138,0.0000032402502,0.0018409031,0.0000030809422,0.0000052576897,0.0000031047332,0.000007957863,0.9965044,0.00033546877,0.00031026438,0.00096676475,0.000010584395],"about_ca_topic_score_codex":0.814796,"about_ca_topic_score_gemma":0.73968554,"teacher_disagreement_score":0.18520403,"about_ca_system_score_codex":0.006039954,"about_ca_system_score_gemma":0.005448678,"threshold_uncertainty_score":0.3725894},"labels":[],"label_agreement":null},{"id":"W2937245495","doi":"10.1029/2018ms001373","title":"An Evaluation of the Ocean and Sea Ice Climate of E3SM Using MPAS and Interannual CORE‐II Forcing","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":168,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Geology; Forcing (mathematics); Climatology; Zonal and meridional; Sea surface temperature; Sea ice; Latitude; Environmental science; Atmospheric sciences; Geodesy","score_opus":0.02567896440564944,"score_gpt":0.28265597015259647,"score_spread":0.25697700574694704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937245495","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99548894,0.000051442657,0.00074404635,0.0001545553,0.000016539818,0.000013956989,0.001034629,0.00017585109,0.00232012],"genre_scores_gemma":[0.99847096,0.00001290902,0.00075737474,0.000026956126,0.000005498753,0.000010318247,0.0005831704,0.000023711395,0.00010900981],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996183,0.00018901195,0.000022551685,0.0000665808,0.000049819177,0.00005370303],"domain_scores_gemma":[0.99845815,0.00078753656,0.000116947274,0.00018893793,0.0002783107,0.00017012678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020139865,0.00068238843,0.00044047818,0.00043977523,0.00038086652,0.00056459557,0.00086319115,0.0008482472,0.001314421],"category_scores_gemma":[0.0033123,0.0003632206,0.0008688999,0.0007640051,0.00044210994,0.00074984075,0.0006650558,0.00061111775,0.00018732047],"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":[0.0013750388,0.00037113889,0.10528845,0.00008411715,0.00021195991,0.00016421737,0.000049520568,0.8768541,0.0041302755,0.0011160265,0.0018661182,0.008489071],"study_design_scores_gemma":[0.00025064702,0.00030827525,0.045494407,0.000012199465,0.000041325286,0.000016648348,0.00004180033,0.9514707,0.0016362114,0.00030638394,0.00039901584,0.000022345275],"about_ca_topic_score_codex":0.04442538,"about_ca_topic_score_gemma":0.023711173,"teacher_disagreement_score":0.04442538,"about_ca_system_score_codex":0.0010408281,"about_ca_system_score_gemma":0.00069772115,"threshold_uncertainty_score":0.08833355},"labels":[],"label_agreement":null},{"id":"W2944323741","doi":"10.1029/2018ms001574","title":"PEAT‐CLSM: A Specific Treatment of Peatland Hydrology in the NASA Catchment Land Surface Model","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":101,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Carleton University; University of Calgary; University of Alberta; Université du Québec à Montréal","funders":"Fonds Wetenschappelijk Onderzoek; Alexander von Humboldt-Stiftung","keywords":"Peat; Evapotranspiration; Environmental science; Water table; Hydrology (agriculture); Groundwater; Eddy covariance; Surface runoff; Bog; Soil science; Geology; Ecosystem; Ecology","score_opus":0.015466913306543942,"score_gpt":0.24908370537958807,"score_spread":0.23361679207304414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944323741","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5087772,0.000833297,0.36970362,0.0009286614,0.0006262501,0.00040322382,0.03920516,0.028953288,0.050569296],"genre_scores_gemma":[0.858267,0.00038302212,0.10863151,0.0002677521,0.000109149216,0.00048235978,0.021382766,0.0022167652,0.008259699],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999337,0.000018184908,0.0000044064177,0.000013724202,0.0000176489,0.000012268072],"domain_scores_gemma":[0.9998828,0.000024651146,0.000011025451,0.000026609923,0.000035841964,0.000019079327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034259574,0.00045446775,0.00036074925,0.00024115691,0.00020005199,0.00049135264,0.0009251442,0.00041014398,0.0025815708],"category_scores_gemma":[0.00057642494,0.00019552307,0.00056535087,0.0004220918,0.00016973446,0.0005662663,0.000495634,0.0004518244,0.00054367277],"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":[0.00009476782,0.00007574603,0.013439289,0.00010420634,0.00012695228,0.0001429072,0.00009033448,0.93210554,0.0050363867,0.007923379,0.018239658,0.022620847],"study_design_scores_gemma":[0.000046856134,0.000028106082,0.003364883,0.000010567518,0.000023982653,0.00003058869,0.00002112981,0.97443646,0.0012224898,0.0022999668,0.018499011,0.00001592346],"about_ca_topic_score_codex":0.015163542,"about_ca_topic_score_gemma":0.018012566,"teacher_disagreement_score":0.015163542,"about_ca_system_score_codex":0.00032922113,"about_ca_system_score_gemma":0.0007797034,"threshold_uncertainty_score":0.030150533},"labels":[],"label_agreement":null},{"id":"W2944339133","doi":"10.1029/2018ms001537","title":"Using Radar Data to Calibrate a Stochastic Parametrization of Organized Convection","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Environment and Climate Change Canada; University of Victoria; Memorial University of Newfoundland","funders":"Office of the Director; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy","keywords":"Parametrization (atmospheric modeling); Radar; Meteorology; Environmental science; Convection; Madden–Julian oscillation; Bayesian probability; Precipitation; Computer science; Scale (ratio); Stochastic modelling; Climatology; Mathematics; Geology; Geography; Artificial intelligence; Statistics; Radiative transfer; Physics","score_opus":0.06742033363376114,"score_gpt":0.31102084176035566,"score_spread":0.2436005081265945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944339133","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9399438,0.00004900708,0.0584819,0.000033341486,0.00001598153,0.000033524084,0.00032631174,0.00021960685,0.0008965541],"genre_scores_gemma":[0.9927498,0.000013036032,0.006936613,0.0000068544286,0.00000374116,0.0000137707375,0.00021274184,0.0000073651686,0.00005599837],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975675,0.00009162451,0.000016064761,0.00007436819,0.000031771546,0.000029362502],"domain_scores_gemma":[0.9993222,0.00027638098,0.00009487539,0.0001574591,0.00011796245,0.00003128697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001020179,0.0003989753,0.00018477134,0.0006485256,0.00017568258,0.0005757597,0.00046759497,0.00038765292,0.00039740113],"category_scores_gemma":[0.002430715,0.00026427011,0.00030901964,0.00047691964,0.00022251287,0.00045159832,0.00031836447,0.00044992744,0.0001486799],"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":[0.00009180781,0.00014598425,0.06908486,0.000023047036,0.000076248296,0.00003312351,0.000049254206,0.8938081,0.011523673,0.00083636143,0.00019808448,0.024129514],"study_design_scores_gemma":[0.00001571309,0.000031882024,0.019627,0.0000045672487,0.000009254285,0.000009519844,0.000013111587,0.97690195,0.0028604085,0.0003251526,0.00019152873,0.0000098320825],"about_ca_topic_score_codex":0.005743435,"about_ca_topic_score_gemma":0.005350524,"teacher_disagreement_score":0.005743435,"about_ca_system_score_codex":0.00045444455,"about_ca_system_score_gemma":0.00032133606,"threshold_uncertainty_score":0.0114200115},"labels":[],"label_agreement":null},{"id":"W2948718903","doi":"10.1029/2019ms001661","title":"Uncertainty in the Representation of Orography in Weather and Climate Models and Implications for Parameterized Drag","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":46,"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":"Science and Technology Facilities Council; Met Office; Natural Environment Research Council; Sight Research UK","keywords":"Orography; Orographic lift; Numerical weather prediction; Meteorology; Environmental science; Climatology; Drag; Parameterized complexity; Computer science; Geology; Precipitation; Geography; Physics; Mechanics; Algorithm","score_opus":0.033314567232380514,"score_gpt":0.30861147674311123,"score_spread":0.2752969095107307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948718903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76492196,0.0007272875,0.22436981,0.001528757,0.00014433902,0.00012247686,0.0014102198,0.00043682283,0.0063382746],"genre_scores_gemma":[0.9912684,0.00018636794,0.007923543,0.00007945824,0.000024897898,0.000028087323,0.00023172419,0.00007321571,0.00018419651],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982338,0.0009930199,0.00015874633,0.00022695123,0.00028513256,0.000102357],"domain_scores_gemma":[0.99176425,0.0050538112,0.00082509266,0.0016946925,0.000557824,0.00010435302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004062128,0.00055358297,0.00060261425,0.00060271646,0.0004398027,0.0018679454,0.0012859164,0.00074446126,0.000603764],"category_scores_gemma":[0.021607338,0.00044562964,0.0008200989,0.0008557612,0.0009401208,0.0024139509,0.0013646927,0.0014903112,0.00008634842],"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":[0.000036738948,0.000023493401,0.01154637,0.000028753715,0.00009953488,0.00004064983,0.000045415676,0.9782406,0.0013331871,0.0041603358,0.00016423334,0.0042806193],"study_design_scores_gemma":[0.00001170149,0.00002739635,0.0070558954,0.000037697515,0.00002018892,0.000018363207,0.00004476622,0.9857954,0.0012492366,0.0052336995,0.00046945814,0.00003627741],"about_ca_topic_score_codex":0.017112365,"about_ca_topic_score_gemma":0.008566848,"teacher_disagreement_score":0.017112365,"about_ca_system_score_codex":0.0009935853,"about_ca_system_score_gemma":0.0008423352,"threshold_uncertainty_score":0.03402555},"labels":[],"label_agreement":null},{"id":"W2949593089","doi":"10.1029/2018ms001544","title":"Connecting Direct Effects of CO<sub>2</sub> Radiative Forcing to Ocean Heat Uptake and Circulation","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","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":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Longwave; Downwelling; Environmental science; Radiative forcing; Atmospheric sciences; Climatology; Shortwave; Ocean general circulation model; Forcing (mathematics); Ocean heat content; Mixed layer; Sea surface temperature; Shortwave radiation; Radiative transfer; Climate change; Upwelling; General Circulation Model; Oceanography; Geology; Radiation; Physics","score_opus":0.01016037060486196,"score_gpt":0.24485478270354835,"score_spread":0.23469441209868638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949593089","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9962993,0.00008076514,0.0011478422,0.00013094844,0.000026633414,0.000012715855,0.00026530048,0.00004631198,0.0019902366],"genre_scores_gemma":[0.9992729,0.000043191227,0.00026083092,0.000019251374,0.0000067391916,0.0000062305216,0.000081030135,0.000009887159,0.00029989376],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998859,0.00003561264,0.0000052274427,0.00002603154,0.000018362189,0.000028859638],"domain_scores_gemma":[0.99969447,0.00017395499,0.00002642588,0.000021997888,0.000044566143,0.000038559076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018417771,0.00037058705,0.00018248714,0.00023428634,0.00017249063,0.00048296293,0.00023581408,0.00045613458,0.0026710161],"category_scores_gemma":[0.0011406373,0.000304812,0.00045568022,0.0002473048,0.00032473818,0.0003076052,0.0005227946,0.00037525845,0.00016263945],"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":[0.000543979,0.0002240114,0.14760497,0.00015050979,0.00042459654,0.0004314985,0.00008882246,0.7588135,0.07861482,0.0018530091,0.0011370521,0.010113277],"study_design_scores_gemma":[0.0001066713,0.00033714072,0.2734968,0.0000136315875,0.00012526255,0.00007056012,0.000101047255,0.70287186,0.019898675,0.0018123931,0.0011203631,0.000045632085],"about_ca_topic_score_codex":0.013825583,"about_ca_topic_score_gemma":0.010067103,"teacher_disagreement_score":0.013825583,"about_ca_system_score_codex":0.0005881565,"about_ca_system_score_gemma":0.00033888913,"threshold_uncertainty_score":0.027490258},"labels":[],"label_agreement":null},{"id":"W2960957508","doi":"10.1029/2019ms001627","title":"Toward a Stochastic Relaxation for the Quasi‐Equilibrium Theory of Cumulus Parameterization: Multicloud Instability, Multiple Equilibria, and Chaotic Dynamics","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":8,"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 Victoria","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Chaotic; Statistical physics; Relaxation (psychology); Forcing (mathematics); Instability; Limit (mathematics); Physics; Representation (politics); Applied mathematics; Mechanics; Computer science; Mathematics; Mathematical analysis; Atmospheric sciences","score_opus":0.029134259502710067,"score_gpt":0.26118719238460114,"score_spread":0.23205293288189108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2960957508","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16817965,0.0008865428,0.8156572,0.0027159504,0.00021548024,0.000071339426,0.000077994744,0.00013788143,0.012058005],"genre_scores_gemma":[0.9623346,0.00035073562,0.03403774,0.00025050508,0.00020692157,0.00010783309,0.000037283324,0.00006213896,0.0026121405],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996105,0.00017139365,0.000017012402,0.00004633217,0.00010623801,0.000048505255],"domain_scores_gemma":[0.9990614,0.0003568504,0.0002678031,0.000084018415,0.00013822722,0.00009156717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015334015,0.0006099909,0.0006125193,0.00053616165,0.0006323472,0.0011596998,0.001165309,0.0010272147,0.0011700562],"category_scores_gemma":[0.0038724947,0.0003887528,0.0008924442,0.00022072566,0.001888148,0.0016800674,0.0023317623,0.0018093133,0.000113952534],"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":[0.000031467906,0.000048504608,0.0014526537,0.00005240074,0.00004794843,0.000127204,0.00019257852,0.4871961,0.004195051,0.50285965,0.00070948765,0.0030868873],"study_design_scores_gemma":[0.0000026989755,0.0000052797327,0.00008778852,0.0000027632907,0.0000015113696,0.0000043176215,0.000005430804,0.98310906,0.00007191734,0.016546875,0.0001584065,0.0000038631997],"about_ca_topic_score_codex":0.00474971,"about_ca_topic_score_gemma":0.002320263,"teacher_disagreement_score":0.00474971,"about_ca_system_score_codex":0.0013052088,"about_ca_system_score_gemma":0.0010438055,"threshold_uncertainty_score":0.009469986},"labels":[],"label_agreement":null},{"id":"W2967464641","doi":"10.1029/2019ms001730","title":"Sensitivity of Simulated Deep Convection to a Stochastic Ice Microphysics Framework","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":28,"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":"Context (archaeology); Environmental science; Radiative transfer; Ice crystals; Atmospheric sciences; Cirrus; Meteorology; Statistical physics; Physics; Geology","score_opus":0.015371176615593242,"score_gpt":0.25057295151806436,"score_spread":0.23520177490247113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967464641","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99626017,0.000027132248,0.002784172,0.000054627988,0.000009847231,0.000015176228,0.00015239514,0.000072962765,0.0006235429],"genre_scores_gemma":[0.9995146,0.0000058880564,0.00035767796,0.000013526194,0.0000013647456,0.0000051714833,0.000066131695,0.0000040241916,0.00003167987],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996239,0.00015967635,0.000022376164,0.0000722394,0.000049876122,0.000071845454],"domain_scores_gemma":[0.998004,0.001282027,0.00020519778,0.00020506358,0.00017979837,0.00012385653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00124312,0.0004734739,0.0003036324,0.0003392633,0.00037700665,0.0006488072,0.0005464514,0.00065768755,0.00041386805],"category_scores_gemma":[0.0035293584,0.00030448756,0.00044923023,0.00026846747,0.00044063883,0.00046105814,0.0005835198,0.00065124774,0.00004517322],"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":[0.00008089692,0.000060070717,0.008640299,0.0000087205,0.000041465184,0.000021921644,0.000012503352,0.98746675,0.0022272584,0.00037439296,0.00007127828,0.0009943984],"study_design_scores_gemma":[0.000024629688,0.00009068922,0.0030601877,0.000003406508,0.00001065163,0.0000062463814,0.000010476455,0.99513197,0.0013847537,0.00020226922,0.000066288165,0.000008468209],"about_ca_topic_score_codex":0.01624236,"about_ca_topic_score_gemma":0.0057294453,"teacher_disagreement_score":0.01624236,"about_ca_system_score_codex":0.0010383639,"about_ca_system_score_gemma":0.00052926806,"threshold_uncertainty_score":0.032295644},"labels":[],"label_agreement":null},{"id":"W2971039919","doi":"10.1029/2019ms001728","title":"New Bidirectional Ammonia Flux Model in an Air Quality Model Coupled With an Agricultural Model","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":87,"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":"CMAQ; Environmental science; Flux (metallurgy); Ammonia; Deposition (geology); Atmospheric sciences; Fertilizer; Air quality index; Nitrate; Hydrology (agriculture); Meteorology; Chemistry; Geology","score_opus":0.022059120733671077,"score_gpt":0.2626887437034115,"score_spread":0.24062962296974041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971039919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7797627,0.00030140192,0.19158237,0.0008812464,0.0002843464,0.0001906059,0.0029310728,0.0015380492,0.022528159],"genre_scores_gemma":[0.98026246,0.00011354575,0.013672448,0.000081464466,0.000052777497,0.00015319024,0.00084913993,0.0000789266,0.004735991],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997973,0.00006112494,0.0000110533865,0.000061909486,0.00003607737,0.00003255408],"domain_scores_gemma":[0.9996768,0.000117210904,0.000034430377,0.00002235286,0.00010288477,0.000046339577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047628063,0.00088537036,0.000835251,0.00038223836,0.0006559376,0.0010129204,0.0012642882,0.0016223135,0.0020733539],"category_scores_gemma":[0.00076010294,0.00051089964,0.0010019552,0.00046081824,0.00044748478,0.0008345497,0.00076235307,0.00077320467,0.0002359553],"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":[0.000028767226,0.00002357565,0.001253382,0.0000072921353,0.000019197127,0.000024321564,0.000006749103,0.99647033,0.0004520063,0.0004621584,0.0001565358,0.0010956036],"study_design_scores_gemma":[0.000008567889,0.000006050091,0.00015253891,5.776526e-7,0.0000033454755,9.696656e-7,0.0000018017669,0.9996081,0.000039993753,0.000095034855,0.00008089067,0.0000021782198],"about_ca_topic_score_codex":0.08403792,"about_ca_topic_score_gemma":0.03493444,"teacher_disagreement_score":0.08403792,"about_ca_system_score_codex":0.0011549112,"about_ca_system_score_gemma":0.0014272857,"threshold_uncertainty_score":0.16709757},"labels":[],"label_agreement":null},{"id":"W2971199049","doi":"10.1029/2019ms001726","title":"The GFDL Global Ocean and Sea Ice Model OM4.0: Model Description and Simulation Features","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":490,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Pacific Institute for Climate Solutions; University of Victoria; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Sea ice; Climate model; Environmental science; General Circulation Model; Climate simulation; Climatology; Geology; Meteorology; Oceanography; Climate change; Geography","score_opus":0.011714779104215874,"score_gpt":0.24011198240798085,"score_spread":0.22839720330376498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971199049","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3321271,0.0005574661,0.035860553,0.0016833113,0.00037929285,0.00083799503,0.5708269,0.008125389,0.04960205],"genre_scores_gemma":[0.5622608,0.00053360465,0.043644052,0.0007238312,0.000118355274,0.0018088559,0.38180166,0.00252686,0.006581947],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996207,0.000091780734,0.00003614169,0.00006669216,0.0001092629,0.00007548734],"domain_scores_gemma":[0.99930716,0.00014117776,0.00007243572,0.00015943954,0.0002418361,0.00007798346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089152507,0.0012461352,0.0006994215,0.0008221153,0.0005799082,0.0013235487,0.0032123025,0.0010279214,0.006963532],"category_scores_gemma":[0.0021532378,0.000523586,0.0010606601,0.0023685892,0.00041810996,0.0011796487,0.00074771687,0.0014121345,0.002852194],"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":[0.0004197714,0.00032201232,0.025465643,0.00022113796,0.00023885076,0.00018765121,0.00006827713,0.8762671,0.0034004224,0.007176424,0.071318716,0.014914041],"study_design_scores_gemma":[0.0010891403,0.00011180164,0.019855728,0.00009978927,0.00014293703,0.000091405134,0.00015979589,0.8963756,0.0074265976,0.0066580605,0.06783645,0.00015268463],"about_ca_topic_score_codex":0.05446207,"about_ca_topic_score_gemma":0.024769986,"teacher_disagreement_score":0.05446207,"about_ca_system_score_codex":0.0016339491,"about_ca_system_score_gemma":0.0018759388,"threshold_uncertainty_score":0.108290136},"labels":[],"label_agreement":null},{"id":"W2971467437","doi":"10.1029/2019ms001729","title":"Version 4 of the SMAP Level‐4 Soil Moisture Algorithm and Data Product","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":279,"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 Space Agency; Environment and Climate Change Canada","keywords":"Environmental science; Water content; Ensemble Kalman filter; Radiometer; Data assimilation; Moisture; Standard deviation; Soil science; Satellite; Atmospheric sciences; Meteorology; Remote sensing; Kalman filter; Mathematics; Geology; Extended Kalman filter; Statistics","score_opus":0.01885836765910421,"score_gpt":0.25075836449110583,"score_spread":0.23189999683200163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971467437","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08159807,0.0003019164,0.4492037,0.00050271704,0.00027113163,0.0010417462,0.2550408,0.17930812,0.03273178],"genre_scores_gemma":[0.19758613,0.00017763638,0.39047417,0.0003700199,0.00009804495,0.0018546149,0.38403922,0.011583574,0.013816554],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995409,0.0000707693,0.000052824114,0.000085037114,0.00019936221,0.000051156378],"domain_scores_gemma":[0.99916947,0.000125113,0.00011277963,0.00020304535,0.00035167774,0.000037904407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009521877,0.00068836065,0.0003999069,0.0012229839,0.00020187865,0.00097474153,0.0012710836,0.0005007648,0.020348126],"category_scores_gemma":[0.0031574338,0.0005977523,0.0004332939,0.001420092,0.0001434098,0.0011777725,0.0008144734,0.00074402365,0.015834546],"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":[0.0009939441,0.00024676186,0.03621061,0.0004711808,0.00023560041,0.00018785082,0.00016580132,0.09376116,0.01591679,0.007916014,0.40980047,0.43409392],"study_design_scores_gemma":[0.0007474874,0.000116377014,0.0397707,0.00009843286,0.00006243136,0.00010249306,0.000060296825,0.5652956,0.024727104,0.010622317,0.35825846,0.00013829487],"about_ca_topic_score_codex":0.00571203,"about_ca_topic_score_gemma":0.0044500716,"teacher_disagreement_score":0.020348126,"about_ca_system_score_codex":0.00040871566,"about_ca_system_score_gemma":0.0006708148,"threshold_uncertainty_score":0.068071306},"labels":[],"label_agreement":null},{"id":"W2971984598","doi":"10.1029/2019ms001781","title":"Modernization of Atmospheric Physics Parameterization in Canadian NWP","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":114,"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":"Numerical weather prediction; Suite; Meteorology; Atmospheric physics; Computer science; Scale (ratio); Environmental science; Physics; Geography; Atmosphere (unit)","score_opus":0.0167195848312366,"score_gpt":0.23010681741053288,"score_spread":0.2133872325792963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971984598","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49038488,0.0027801779,0.27739304,0.006003515,0.0007326986,0.0010311159,0.05240615,0.011277947,0.15799046],"genre_scores_gemma":[0.80750656,0.0014042498,0.16491751,0.00026794279,0.00006301065,0.0002266944,0.015572614,0.0007952962,0.009246071],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983467,0.00014355281,0.000072981755,0.00021456934,0.0010594233,0.00016279035],"domain_scores_gemma":[0.9968354,0.00014761704,0.00012768869,0.00036679616,0.0023705992,0.0001518206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017153225,0.0007115859,0.0003416782,0.0021039536,0.0021835496,0.0023852785,0.002246655,0.00037832832,0.0024024886],"category_scores_gemma":[0.0040626065,0.00037954753,0.00072844326,0.0040089926,0.00078916777,0.0012930632,0.0013079036,0.0012197456,0.00041637776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018688942,0.00017497831,0.11945639,0.00033491294,0.00023310314,0.0002093684,0.0010002478,0.47991896,0.011453722,0.051792357,0.04362902,0.29161003],"study_design_scores_gemma":[0.000052558822,0.000046778667,0.17904747,0.00015736227,0.00009901382,0.00008920916,0.0005116501,0.5659664,0.008699774,0.0070033497,0.23805264,0.00027385156],"about_ca_topic_score_codex":0.97986835,"about_ca_topic_score_gemma":0.97390723,"teacher_disagreement_score":0.97986835,"about_ca_system_score_codex":0.025254231,"about_ca_system_score_gemma":0.036300883,"threshold_uncertainty_score":0.18323314},"labels":[],"label_agreement":null},{"id":"W2973149622","doi":"10.1029/2019ms001762","title":"The Role of Interactive SST in the Cloud‐Resolving Simulations of Aggregated Convection","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":25,"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":"","keywords":"Convection; Advection; Perturbation (astronomy); Atmospheric sciences; Moisture; Amplitude; Temperature gradient; Environmental science; Boundary layer; Sea surface temperature; Climatology; Mechanics; Geology; Physics; Meteorology; Thermodynamics; Optics","score_opus":0.00906449041374823,"score_gpt":0.2560814666589302,"score_spread":0.24701697624518199,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973149622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978644,0.00004204626,0.0012421518,0.000055163768,0.000010953517,0.000005637752,0.000054979737,0.00003921752,0.0006855098],"genre_scores_gemma":[0.9995546,0.000012853168,0.0003198708,0.000008237442,0.000003048874,0.000002809451,0.00003041354,0.000007228949,0.000060913895],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998944,0.00003424631,0.0000068624954,0.000017144748,0.000015559579,0.0000316816],"domain_scores_gemma":[0.99963593,0.00012456623,0.00006282931,0.000036954894,0.00004376199,0.000096048796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031804654,0.00037611637,0.00033803744,0.00023870984,0.00043617928,0.0006018451,0.00046758534,0.0005348633,0.00061991427],"category_scores_gemma":[0.0011068659,0.00022635104,0.0004337429,0.00024512465,0.00043298735,0.00058990926,0.0004904624,0.00047772843,0.000049215043],"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":[0.00018259883,0.00014907433,0.025812358,0.000025841744,0.000094399955,0.00020589726,0.00010249618,0.95588917,0.013823539,0.0015451001,0.00018830226,0.0019812714],"study_design_scores_gemma":[0.00002736779,0.00004017238,0.0033003644,0.0000023662665,0.000009549579,0.0000074135387,0.000019553823,0.99554473,0.000817471,0.00016443396,0.00006165827,0.000004910276],"about_ca_topic_score_codex":0.017598782,"about_ca_topic_score_gemma":0.008646409,"teacher_disagreement_score":0.017598782,"about_ca_system_score_codex":0.00045376475,"about_ca_system_score_gemma":0.000576184,"threshold_uncertainty_score":0.034992695},"labels":[],"label_agreement":null},{"id":"W2980324102","doi":"10.1029/2018ms001586","title":"Parameterization and Surface Data Improvements and New Capabilities for the Community Land Model Urban (CLMU)","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":110,"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 Victoria","funders":"National Aeronautics and Space Administration; National Science Foundation","keywords":"Environmental science; Meteorology; Grid; Radiative transfer; Flux (metallurgy); Tower; Computer science; Climate model; Climate change; Civil engineering; Geography; Geology","score_opus":0.05131185352334507,"score_gpt":0.2767926127367632,"score_spread":0.22548075921341812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980324102","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41088232,0.00096240063,0.41612425,0.002726444,0.00086347136,0.000966524,0.07631306,0.039901815,0.051259708],"genre_scores_gemma":[0.78133225,0.0003309484,0.16178699,0.000314815,0.00011233298,0.0007482523,0.045619164,0.0048042135,0.0049510845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991222,0.00031912894,0.000058881058,0.00012610901,0.0002816365,0.00009205572],"domain_scores_gemma":[0.998464,0.00035401972,0.00010579534,0.0004609263,0.0005112158,0.000104111736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002217951,0.0010009931,0.0006982027,0.00064743933,0.0004970064,0.0012588402,0.0026799084,0.0006225772,0.0056881392],"category_scores_gemma":[0.004042105,0.00051651837,0.0010181774,0.0013754946,0.00038577555,0.0019310851,0.0016523493,0.00166297,0.0015475323],"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":[0.00032479723,0.00016257055,0.010331909,0.00011510423,0.00010481899,0.00006617998,0.000087682754,0.918325,0.0037720213,0.0064503127,0.023230793,0.037028864],"study_design_scores_gemma":[0.00017647652,0.000049147904,0.0029345388,0.00003411136,0.00003675283,0.000021222702,0.000045656878,0.9502282,0.004440044,0.0023480093,0.0396164,0.0000695786],"about_ca_topic_score_codex":0.034532912,"about_ca_topic_score_gemma":0.032524373,"teacher_disagreement_score":0.034532912,"about_ca_system_score_codex":0.0010669084,"about_ca_system_score_gemma":0.0014084318,"threshold_uncertainty_score":0.068663776},"labels":[],"label_agreement":null},{"id":"W2982785288","doi":"10.1029/2019ms001833","title":"Representing Intrahillslope Lateral Subsurface Flow in the Community Land Model","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canmore Museum and Geoscience Centre","funders":"National Science Foundation","keywords":"Evapotranspiration; Surface runoff; Hydrology (agriculture); Environmental science; Subsurface flow; Catchment hydrology; Drainage basin; Arid; Geology; Hydrological modelling; Streamflow; Groundwater; Climatology; Geography; Ecology","score_opus":0.016625893590708506,"score_gpt":0.25074656314468113,"score_spread":0.23412066955397262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982785288","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90637004,0.000103233375,0.08375403,0.00020930561,0.00002250346,0.000052656247,0.0007920112,0.00045409042,0.008242131],"genre_scores_gemma":[0.99090636,0.00002546625,0.0076222527,0.0000152247585,0.0000030101544,0.000029903418,0.00020880441,0.000027365182,0.001161622],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990714,0.000028416227,0.000003375191,0.00002139837,0.0000145180875,0.00002511742],"domain_scores_gemma":[0.9997546,0.00008531241,0.000029461062,0.000018978111,0.0000621463,0.00004958223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000265542,0.0003505477,0.0003064224,0.00036851937,0.0003974686,0.0006877073,0.0011055545,0.0006986953,0.002099482],"category_scores_gemma":[0.0008824781,0.0001631035,0.0003269818,0.00049491733,0.00046040444,0.0007972885,0.0006307007,0.00036637363,0.0001467606],"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":[0.000027801394,0.00002102207,0.0016403146,0.0000039937586,0.000006272605,0.0000202359,0.000011858783,0.9946489,0.00038925005,0.0017055597,0.00011272803,0.0014121305],"study_design_scores_gemma":[0.0000071188683,0.000006043307,0.00015108327,6.931524e-7,0.0000010742874,0.0000019391819,0.0000055251576,0.99922645,0.00005220098,0.00046206993,0.00008424726,0.0000016113818],"about_ca_topic_score_codex":0.07071785,"about_ca_topic_score_gemma":0.05612225,"teacher_disagreement_score":0.07071785,"about_ca_system_score_codex":0.0014592174,"about_ca_system_score_gemma":0.0013032841,"threshold_uncertainty_score":0.14061242},"labels":[],"label_agreement":null},{"id":"W2988138585","doi":"10.1029/2019ms001870","title":"The DOE E3SM Coupled Model Version 1: Description and Results at High Resolution","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":294,"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":"Command and General Staff College","keywords":"Initialization; Climatology; Environmental science; Resolution (logic); Mesoscale meteorology; Climate model; Sensitivity (control systems); Atmospheric sciences; Climate change; Geology; Computer science; Oceanography","score_opus":0.017099967581802083,"score_gpt":0.23381197990917174,"score_spread":0.21671201232736967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988138585","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8044995,0.00087068544,0.03209544,0.00072000886,0.00021768331,0.00080891384,0.11519124,0.00966919,0.03592734],"genre_scores_gemma":[0.8906861,0.000378332,0.043944567,0.00020161663,0.00004918225,0.0010759889,0.05832161,0.0019563367,0.0033862914],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995529,0.0001365173,0.00004084667,0.0000745647,0.0001280375,0.00006700614],"domain_scores_gemma":[0.9992847,0.0002488646,0.00004068861,0.00014980264,0.00022259072,0.0000533304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011461518,0.001400519,0.00093655183,0.0006329556,0.0005715657,0.00096349366,0.0018348154,0.00096339907,0.0055137333],"category_scores_gemma":[0.0021625522,0.00054752885,0.0009256904,0.0013139979,0.0003273645,0.0006787766,0.0006776116,0.0011408689,0.0013801844],"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":[0.0003667937,0.00025081047,0.014517824,0.00027585783,0.00021796298,0.00023634535,0.00007435546,0.9527795,0.0053501637,0.0024917105,0.009435989,0.014002591],"study_design_scores_gemma":[0.0003398656,0.00012179922,0.010465729,0.000027669206,0.000055170814,0.000033098462,0.000057879923,0.9764301,0.0053805946,0.0008386119,0.006163252,0.00008624437],"about_ca_topic_score_codex":0.0738167,"about_ca_topic_score_gemma":0.037671257,"teacher_disagreement_score":0.0738167,"about_ca_system_score_codex":0.0008334896,"about_ca_system_score_gemma":0.0011673605,"threshold_uncertainty_score":0.14677411},"labels":[],"label_agreement":null},{"id":"W2992279818","doi":"10.1029/2018ms001541","title":"Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: Part 2. Carbon Cycling","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":35,"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":"Australian Research Council; Division of Polar Programs; Natural Sciences and Engineering Research Council of Canada; Office of Science; Lunds Universitet; Eidgenössische Technische Hochschule Zürich; U.S. Department of Energy; European Commission; Oak Ridge National Laboratory; Biological and Environmental Research; Canadian Foundation for Climate and Atmospheric Sciences; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Australian Government; Natural Resources Canada; National Aeronautics and Space Administration; Office of Polar Programs; BIOCAP Canada; National Science Foundation","keywords":"Leaf area index; Environmental science; Grassland; Primary production; Phenology; Growing season; Precipitation; Moderate-resolution imaging spectroradiometer; Carbon cycle; Atmospheric sciences; Biosphere model; Ecosystem respiration; Vegetation (pathology); Ecosystem; Biosphere; Agronomy; Ecology; Geography; Biology; Meteorology; Satellite","score_opus":0.016548255402733955,"score_gpt":0.2497795664993551,"score_spread":0.23323131109662115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2992279818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9772282,0.00010678822,0.020642495,0.00006508935,0.00001275351,0.00002470287,0.0006759862,0.00033987235,0.00090407656],"genre_scores_gemma":[0.9935355,0.000027802416,0.0058779283,0.0000108990525,0.0000050432745,0.000014835707,0.00033357847,0.000012862164,0.00018139469],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99994504,0.000012749065,0.000003580332,0.000020820367,0.0000068498307,0.00001105463],"domain_scores_gemma":[0.9998011,0.00007352053,0.00004459951,0.00002103313,0.0000328648,0.000026916077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003326772,0.00043804874,0.00020620276,0.0006231605,0.00019211206,0.0006017384,0.00034499756,0.00037908685,0.0010376103],"category_scores_gemma":[0.00065975136,0.00019078734,0.00041134452,0.00041793782,0.00017144447,0.00036741229,0.00027531796,0.00017734036,0.00012232625],"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":[0.00016919995,0.000097763055,0.14481811,0.000058357116,0.000099024095,0.00007979302,0.00006881725,0.8192775,0.0076598306,0.00047571148,0.0004643078,0.02673162],"study_design_scores_gemma":[0.000012748516,0.000019727217,0.023518134,0.0000044874027,0.000010192054,0.000016526985,0.000017625951,0.9754742,0.0004155494,0.00033296447,0.00017083356,0.0000069917555],"about_ca_topic_score_codex":0.022236414,"about_ca_topic_score_gemma":0.016594619,"teacher_disagreement_score":0.022236414,"about_ca_system_score_codex":0.0005929385,"about_ca_system_score_gemma":0.0005402718,"threshold_uncertainty_score":0.04421395},"labels":[],"label_agreement":null},{"id":"W2996332817","doi":"10.1029/2019ms001862","title":"Error Analysis for an Algorithm That Reduces Radiative Transfer Calculations in High‐Resolution Atmospheric Models","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric aerosols and clouds","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":"Environment and Climate Change Canada","funders":"","keywords":"Radiative transfer; Longwave; Radiative flux; Series (stratigraphy); Algorithm; Atmospheric radiative transfer codes; Irradiance; Solar irradiance; Mathematics; Meteorology; Environmental science; Physics; Geology; Optics","score_opus":0.0242031249520348,"score_gpt":0.2693653199216262,"score_spread":0.2451621949695914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2996332817","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09939302,0.00012994648,0.8979551,0.0001559221,0.000053193544,0.000058733847,0.000072635434,0.0011290765,0.0010522645],"genre_scores_gemma":[0.49622333,0.00006239777,0.5017276,0.00008127362,0.000034021567,0.00017046659,0.0003535277,0.0002952539,0.0010521078],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842346,0.00065310654,0.00009842104,0.00017692859,0.00055901054,0.00008904431],"domain_scores_gemma":[0.9907274,0.0058291806,0.0004040207,0.0011170357,0.0018083655,0.0001139496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049112514,0.00055155,0.00049557514,0.00052829605,0.00046654313,0.00080842245,0.0012899418,0.000884188,0.0011644247],"category_scores_gemma":[0.016413921,0.0003090591,0.0005234842,0.0005157654,0.0005979377,0.00091988844,0.001037435,0.0011316733,0.0003211832],"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":[0.00020430806,0.000090108624,0.0029755495,0.000043894168,0.000061179184,0.000031329564,0.00006403299,0.9318257,0.005323157,0.008383691,0.00064133946,0.050355703],"study_design_scores_gemma":[0.0000044621424,0.000008452361,0.00012439313,0.0000013711236,0.0000014988613,0.0000022142021,0.0000017813207,0.99881244,0.00064054545,0.00031789538,0.00008370073,0.0000013479638],"about_ca_topic_score_codex":0.0082965875,"about_ca_topic_score_gemma":0.0060468432,"teacher_disagreement_score":0.0082965875,"about_ca_system_score_codex":0.00081932754,"about_ca_system_score_gemma":0.0016192233,"threshold_uncertainty_score":0.025973558},"labels":[],"label_agreement":null},{"id":"W2998721850","doi":"10.1029/2019ms002027","title":"Ocean‐Only FAFMIP: Understanding Regional Patterns of Ocean Heat Content and Dynamic Sea Level Change","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Pacific Institute for Climate Solutions","funders":"Consiliului National al Cercetarii Stiintifice din Invatamantul Superior; Natural Environment Research Council; Sight Research UK","keywords":"Climatology; Ocean heat content; Ocean general circulation model; Thermohaline circulation; Ocean current; Environmental science; Sea surface temperature; Stratification (seeds); Isopycnal; Atmospheric sciences; Atmosphere (unit); Geology; Climate change; Oceanography; General Circulation Model; Meteorology; Geography","score_opus":0.2045798833539623,"score_gpt":0.28970978789788754,"score_spread":0.08512990454392524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998721850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99610484,0.000060293965,0.0017592632,0.00010898499,0.000007151402,0.0000079255715,0.0013325375,0.0001158125,0.000503229],"genre_scores_gemma":[0.99649066,0.000029531471,0.002368575,0.000027920345,0.000007497508,0.000014427753,0.0009871876,0.000020152429,0.000054035056],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985385,0.000041670723,0.0000075804114,0.000050549454,0.00001977294,0.000026509862],"domain_scores_gemma":[0.999539,0.00015403931,0.000089662535,0.00009974858,0.000057598172,0.000060087143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009013347,0.0005403432,0.0003660865,0.00041389925,0.00025423444,0.0005344083,0.00057518075,0.0005728509,0.0005588913],"category_scores_gemma":[0.0017063844,0.00019410781,0.000578283,0.0006785541,0.0003399328,0.0009132361,0.00054991746,0.00047187804,0.00009658483],"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":[0.00077344873,0.00025725138,0.56111044,0.00017660506,0.00076262216,0.00014442857,0.00016579266,0.37070042,0.030584972,0.001071889,0.0019398557,0.032312304],"study_design_scores_gemma":[0.00008510354,0.00012252736,0.5212765,0.000012433498,0.00016634693,0.00003147093,0.00011388307,0.4702104,0.006090533,0.00096784637,0.00088185375,0.00004113627],"about_ca_topic_score_codex":0.03542369,"about_ca_topic_score_gemma":0.019668598,"teacher_disagreement_score":0.03542369,"about_ca_system_score_codex":0.0006245497,"about_ca_system_score_gemma":0.0005402363,"threshold_uncertainty_score":0.07043499},"labels":[],"label_agreement":null},{"id":"W2998885490","doi":"10.1029/2019ms001916","title":"The Community Earth System Model Version 2 (CESM2)","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":3190,"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 Toronto","funders":"National Science Foundation","keywords":"Earth system science; Computer science; Earth (classical element); Environmental science; Astrobiology; Earth science; Geology; Oceanography; Mathematics; Physics","score_opus":0.03586399044874617,"score_gpt":0.25887318495033496,"score_spread":0.2230091945015888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998885490","genre_codex":"dataset","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038972013,0.0022115964,0.08059571,0.0030475983,0.0007717945,0.00090095034,0.79027927,0.024841312,0.05837989],"genre_scores_gemma":[0.25583446,0.0017511242,0.09678008,0.0010779282,0.00035540247,0.0030419894,0.6173047,0.008774583,0.01507968],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994517,0.00019622261,0.000031394,0.00009946165,0.00015501716,0.000066293476],"domain_scores_gemma":[0.9989035,0.00021028191,0.00008593955,0.00016981711,0.0004958457,0.00013452025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014840573,0.0014667775,0.0012031175,0.0013495653,0.0006610794,0.0018673571,0.0032398845,0.0014386915,0.018628154],"category_scores_gemma":[0.0032572607,0.0007415003,0.0012704047,0.004551259,0.00033001427,0.0019972648,0.0011065792,0.0019304501,0.008430721],"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":[0.00039025026,0.00013452943,0.009709727,0.000634158,0.000548548,0.0001415539,0.00009523784,0.5448591,0.0013574932,0.013733755,0.3968441,0.031551573],"study_design_scores_gemma":[0.0009827857,0.00007311,0.0063435594,0.00018273464,0.00019660644,0.00006247445,0.00006833944,0.7023081,0.0012429074,0.011670345,0.2766896,0.00017946586],"about_ca_topic_score_codex":0.09039916,"about_ca_topic_score_gemma":0.0491393,"teacher_disagreement_score":0.09039916,"about_ca_system_score_codex":0.0013760213,"about_ca_system_score_gemma":0.003201847,"threshold_uncertainty_score":0.17974591},"labels":[],"label_agreement":null},{"id":"W3003709258","doi":"10.1029/2020ms002203","title":"WeatherBench: A Benchmark Data Set for Data‐Driven Weather Forecasting","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":445,"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 Toronto","funders":"Seventh Framework Programme; Deutsche Forschungsgemeinschaft","keywords":"Benchmark (surveying); Set (abstract data type); Data set; Weather forecasting; Baseline (sea); Numerical weather prediction; Deep learning; Code (set theory); Simple (philosophy)","score_opus":0.23843654253493943,"score_gpt":0.32054738351129725,"score_spread":0.08211084097635782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003709258","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1431094,0.0014977877,0.01960514,0.0018821687,0.0010074109,0.00050873857,0.79292697,0.028973343,0.010489043],"genre_scores_gemma":[0.110930935,0.00033345874,0.019239133,0.00018982284,0.00009319074,0.000343661,0.86648387,0.0009929255,0.001393015],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984999,0.00032843556,0.00024699816,0.00033241799,0.00046054498,0.00013172178],"domain_scores_gemma":[0.99578357,0.0013968779,0.00029032267,0.0010166294,0.0011809729,0.0003316348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024544355,0.0017964971,0.00077065773,0.0026656003,0.0005386028,0.0013471332,0.0025087532,0.0013503438,0.006012019],"category_scores_gemma":[0.00988953,0.00037631937,0.0009772484,0.0038537467,0.0004155439,0.0019818519,0.0010511617,0.0014707401,0.0041475217],"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":[0.0011298544,0.0009084802,0.025517846,0.0014202504,0.00054603134,0.00037449194,0.00012039097,0.26351663,0.0039414456,0.003641937,0.6232617,0.075620964],"study_design_scores_gemma":[0.0010466177,0.00043854179,0.03701307,0.00025023642,0.00013515963,0.00028079323,0.00031956926,0.74978715,0.0145427445,0.009134785,0.18683113,0.00022014065],"about_ca_topic_score_codex":0.027556704,"about_ca_topic_score_gemma":0.020206729,"teacher_disagreement_score":0.027556704,"about_ca_system_score_codex":0.00086318544,"about_ca_system_score_gemma":0.0011679878,"threshold_uncertainty_score":0.054792643},"labels":[],"label_agreement":null},{"id":"W3007927169","doi":"10.1029/2019ms001896","title":"Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":203,"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 Victoria","funders":"National Centre for Earth Observation; Natural Environment Research Council; Sight Research UK; National Science Foundation","keywords":"Adversarial system; Generative grammar; Computer science; Artificial intelligence; Applied mathematics; Mathematics","score_opus":0.035458339062541484,"score_gpt":0.27752426321167567,"score_spread":0.2420659241491342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007927169","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4463359,0.00054411025,0.53812146,0.0021021268,0.00008520664,0.00011615221,0.00041788345,0.00073877815,0.011538429],"genre_scores_gemma":[0.98263687,0.000074008385,0.016016973,0.00011108143,0.000015158889,0.00004393412,0.00014065139,0.00004771333,0.0009137427],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961674,0.00022483352,0.000011056766,0.000050520073,0.0000609661,0.00003581514],"domain_scores_gemma":[0.99784505,0.0016897928,0.00013899969,0.00011622679,0.00014412058,0.00006567954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018732894,0.000700031,0.0006486347,0.0003521664,0.00036498078,0.0005770417,0.00081899273,0.00079981104,0.0013553713],"category_scores_gemma":[0.0049098344,0.0003367975,0.0004618939,0.00032563912,0.0010393823,0.0010229883,0.0008999736,0.0016392159,0.00013000467],"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":[0.0000076530905,0.000003704437,0.00016704055,0.0000029425487,0.0000035636772,0.000005289127,0.00000355859,0.9977569,0.00006485082,0.0013690284,0.000077880824,0.00053758506],"study_design_scores_gemma":[0.0000013094134,0.0000022811198,0.000032496173,9.1555574e-7,5.717617e-7,0.0000010776387,8.998703e-7,0.99881786,0.000045177352,0.0010697783,0.000026494417,0.0000011463159],"about_ca_topic_score_codex":0.010773239,"about_ca_topic_score_gemma":0.0066585597,"teacher_disagreement_score":0.010773239,"about_ca_system_score_codex":0.0011628828,"about_ca_system_score_gemma":0.00061566517,"threshold_uncertainty_score":0.021421075},"labels":[],"label_agreement":null},{"id":"W3010108219","doi":"10.1029/2019ms001709","title":"Application of a High‐Resolution Distributed Hydrological Model on a U.S.‐Canada Transboundary Basin: Simulation of the Multiyear Mean AnnualHydrograph and 2011 Flood of theRichelieu River Basin","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ouranos; Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs; Université Laval; Ministère des Ressources naturelles et des Forêts; École de Technologie Supérieure","funders":"Agence Nationale de la Recherche","keywords":"Flood myth; Hydrology (agriculture); Structural basin; Hydrograph; Drainage basin; Streamflow; Flood forecasting; Environmental science; Hydrological modelling; Digital elevation model; Forcing (mathematics); Geology; Climatology; Remote sensing; Geomorphology; Geography","score_opus":0.010614792115840911,"score_gpt":0.21327900959452206,"score_spread":0.20266421747868116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010108219","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99519205,0.00004053333,0.0017225762,0.00019796849,0.000019604993,0.000032524007,0.0006883937,0.00018883136,0.0019175994],"genre_scores_gemma":[0.9964647,0.000027981887,0.0022097772,0.000026880703,0.0000037471032,0.000020744816,0.00057485426,0.000016330627,0.0006548187],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998565,0.000031622083,0.0000064929454,0.000036469795,0.000027905486,0.00004113338],"domain_scores_gemma":[0.99946576,0.00015381107,0.0000333992,0.000040582505,0.00019609854,0.00011033994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005138656,0.0007116307,0.000495124,0.0004983715,0.0011981946,0.00096326787,0.0013818423,0.0014805018,0.0018218872],"category_scores_gemma":[0.0010425056,0.00046867348,0.00076988037,0.0006856991,0.00078335515,0.00042172783,0.00055562926,0.0010451942,0.00014250603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055647775,0.0001043181,0.006129352,0.00001070177,0.000029515439,0.000061125225,0.00002612393,0.9909445,0.0005463837,0.00019941619,0.0003647532,0.0015280047],"study_design_scores_gemma":[0.000023684785,0.000012303617,0.0029683674,0.0000016854275,0.0000063028165,0.000002881174,0.000030363613,0.9966298,0.00018274042,0.000023618224,0.00011122756,0.000007019809],"about_ca_topic_score_codex":0.868871,"about_ca_topic_score_gemma":0.80544126,"teacher_disagreement_score":0.13112903,"about_ca_system_score_codex":0.0058409576,"about_ca_system_score_gemma":0.005617215,"threshold_uncertainty_score":0.26380253},"labels":[],"label_agreement":null},{"id":"W3020869288","doi":"10.1029/2020ms002159","title":"Joint Modeling of Crop and Irrigation in the central United States Using the Noah‐MP Land Surface Model","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"","keywords":"Irrigation; Environmental science; Crop yield; Crop; Sowing; Yield (engineering); Crop simulation model; Agricultural engineering; Agronomy; Engineering; Physics","score_opus":0.09794253434911741,"score_gpt":0.276699869453283,"score_spread":0.17875733510416558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3020869288","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98879343,0.000121040575,0.004551961,0.0003187453,0.000027981841,0.000025886675,0.0013317651,0.00017015464,0.0046590306],"genre_scores_gemma":[0.99732697,0.00004060882,0.0014616116,0.000030723502,0.000003848638,0.000022039314,0.0005180855,0.000010514193,0.00058561447],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998636,0.000037911755,0.000006715669,0.00004256509,0.00002344258,0.00002577096],"domain_scores_gemma":[0.99971896,0.00009863299,0.000036581638,0.000029831648,0.00008764439,0.000028421178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036623047,0.0004933425,0.00040667813,0.0003039403,0.00054867717,0.0008099855,0.00075363537,0.00075537857,0.000865064],"category_scores_gemma":[0.000723769,0.000363382,0.00060249853,0.00069512683,0.00039455944,0.0005120082,0.00045996642,0.0005535912,0.00012741718],"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":[0.00003787965,0.000032911194,0.007105183,0.000007792049,0.000034549368,0.00004372642,0.000016270515,0.9901805,0.00037246902,0.00038471672,0.00045387703,0.001330042],"study_design_scores_gemma":[0.000016079784,0.000012149273,0.0031789856,0.0000016267395,0.000009366375,0.0000030844785,0.000020452679,0.9962202,0.00014340956,0.00014872284,0.0002410056,0.0000048820134],"about_ca_topic_score_codex":0.24269795,"about_ca_topic_score_gemma":0.13192166,"teacher_disagreement_score":0.24269795,"about_ca_system_score_codex":0.0015265566,"about_ca_system_score_gemma":0.0016763894,"threshold_uncertainty_score":0.4825706},"labels":[],"label_agreement":null},{"id":"W3023073569","doi":"10.1029/2019ms001689","title":"Confronting the Challenge of Modeling Cloud and Precipitation Microphysics","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":612,"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":"Horizon 2020; European Research Council; National Aeronautics and Space Administration; U.S. Department of Energy; National Science Foundation","keywords":"Cloud computing; Cloud physics; Meteorology; Precipitation; Climate model; Computer science; Microscale chemistry; Environmental science; Population; Climate change; Geography; Mathematics; Geology","score_opus":0.038190953101888976,"score_gpt":0.2420342268497959,"score_spread":0.20384327374790692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023073569","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012592707,0.0009895235,0.98234576,0.0016819942,0.000083761406,0.000022265074,0.00013697382,0.00015399927,0.0019929945],"genre_scores_gemma":[0.4950487,0.0049721166,0.49509737,0.00049739657,0.0009055527,0.00026744037,0.00037750727,0.00023816511,0.0025957143],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994854,0.00018394184,0.000028333548,0.00011018648,0.00015099059,0.00004111521],"domain_scores_gemma":[0.99850047,0.0009513379,0.00017610825,0.0001822344,0.00012260114,0.0000672586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014471628,0.00058543,0.0008623473,0.000614957,0.00079743215,0.0016220734,0.0018306229,0.001498625,0.00048230463],"category_scores_gemma":[0.0028851072,0.00054622337,0.0010722358,0.0007664838,0.001683465,0.0030175636,0.0020203807,0.00280615,0.00026357133],"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":[0.00001332898,0.000038568316,0.0029041667,0.00009449829,0.000055649925,0.000062738465,0.00015193899,0.7557132,0.0020194184,0.20449288,0.0012835879,0.033170093],"study_design_scores_gemma":[0.0000032304804,0.000019028823,0.00042405145,0.000012690371,0.000010050233,0.000026654057,0.000030965457,0.9100883,0.00029602658,0.0854705,0.0036038372,0.000014634679],"about_ca_topic_score_codex":0.009401068,"about_ca_topic_score_gemma":0.0064177774,"teacher_disagreement_score":0.009401068,"about_ca_system_score_codex":0.0008519032,"about_ca_system_score_gemma":0.002068921,"threshold_uncertainty_score":0.018692732},"labels":[],"label_agreement":null},{"id":"W3036569948","doi":"10.1029/2020ms002172","title":"Bulk, Spectral and Deep Water Approximations for Stokes Drift: Implications for Coupled Ocean Circulation and Surface Wave Models","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary 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":"Bedford Institute of Oceanography; Fisheries and Oceans Canada; Dalhousie University","funders":"","keywords":"Stokes drift; Wind wave; Stokes wave; Wave model; Surface wave; Physics; Monochromatic color; Ocean current; Computational physics; Breaking wave; Geophysics; Wave propagation; Meteorology; Geology; Optics; Oceanography","score_opus":0.02847993878843953,"score_gpt":0.24393888278213025,"score_spread":0.21545894399369073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036569948","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31610942,0.00038953908,0.6774103,0.0005276589,0.00008237782,0.00008424012,0.00017180214,0.00032145114,0.004903286],"genre_scores_gemma":[0.9326476,0.00031123043,0.063357785,0.00009452534,0.00004120596,0.000099266734,0.00010529045,0.00017770655,0.0031654506],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997004,0.00012100827,0.000019393014,0.000030293555,0.00009372364,0.000035168363],"domain_scores_gemma":[0.9978835,0.0012857171,0.00018305461,0.00024015765,0.00031486677,0.00009270601],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018697849,0.00055768096,0.0004211136,0.00049841753,0.00037877922,0.000753853,0.0011115316,0.0006864102,0.0009212308],"category_scores_gemma":[0.005618432,0.00039181404,0.0007300643,0.0003680259,0.0006501938,0.0015866425,0.00088766287,0.0008965625,0.00025781608],"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":[0.000050700444,0.000038097438,0.0022056375,0.000020378053,0.000015883768,0.00006580695,0.000060303253,0.9734482,0.0022565369,0.015818035,0.0001828316,0.005837637],"study_design_scores_gemma":[0.0000023901223,0.0000064665082,0.00014912894,0.0000027853964,0.0000014274087,0.000004760212,0.00000748603,0.99827373,0.00013198906,0.0013445818,0.00007174349,0.000003565088],"about_ca_topic_score_codex":0.019142265,"about_ca_topic_score_gemma":0.010284194,"teacher_disagreement_score":0.019142265,"about_ca_system_score_codex":0.00087091944,"about_ca_system_score_gemma":0.0009229682,"threshold_uncertainty_score":0.03806168},"labels":[],"label_agreement":null},{"id":"W3045952052","doi":"10.1029/2019ms001984","title":"An Efficient Ice Sheet/Earth System Model Spin‐up Procedure for CESM2‐CISM2: Description, Evaluation, and Broader Applicability","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Virtual Materials Group (Canada)","funders":"H2020 European Research Council; University of Arizona; National Science Foundation","keywords":"Earth system science; Ice sheet; Earth (classical element); Earth science; Geology; Geophysics; Computer science; Astrobiology; Geomorphology; Physics; Oceanography","score_opus":0.052571066669340555,"score_gpt":0.2899835350648599,"score_spread":0.23741246839551935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3045952052","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12230285,0.00013580058,0.85492265,0.0002774287,0.00010680897,0.00052104075,0.0014349564,0.009412712,0.010885702],"genre_scores_gemma":[0.45788923,0.0001032542,0.53539085,0.000077898294,0.00003502239,0.0006702594,0.0017732125,0.0022246325,0.0018355626],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997212,0.0000995176,0.000020533327,0.000031126132,0.00009334702,0.000034256384],"domain_scores_gemma":[0.9987594,0.0005219517,0.00008548733,0.0002139866,0.00035649695,0.00006273221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013200607,0.0009500997,0.00054249977,0.00047725317,0.0007234097,0.0007372522,0.0013250855,0.00070200715,0.0057559223],"category_scores_gemma":[0.004628244,0.0005635612,0.00066832645,0.00037719592,0.0003766921,0.00069114094,0.0009848821,0.0015516002,0.0010919783],"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":[0.00020730574,0.00017951701,0.0058088154,0.00021834814,0.00013181617,0.00037583715,0.0002698084,0.89250773,0.012042769,0.01572864,0.004480972,0.06804844],"study_design_scores_gemma":[0.000030522413,0.000015202383,0.00036489044,0.0000071282107,0.000006162814,0.000012081828,0.000019491375,0.99561775,0.0021398254,0.0006822429,0.001094125,0.000010615657],"about_ca_topic_score_codex":0.014351053,"about_ca_topic_score_gemma":0.016531711,"teacher_disagreement_score":0.014351053,"about_ca_system_score_codex":0.0005920491,"about_ca_system_score_gemma":0.0017369005,"threshold_uncertainty_score":0.028535008},"labels":[],"label_agreement":null},{"id":"W3049229383","doi":"10.1029/2019ms002031","title":"Accelerated Greenland Ice Sheet Mass Loss Under High Greenhouse Gas Forcing as Simulated by the Coupled CESM2.1‐CISM2.1","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"EMD Inc. (Canada)","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Council for Eurasian and East European Research","keywords":"Greenland ice sheet; Ice sheet; Climatology; Greenhouse gas; Environmental science; Glacier mass balance; Atmospheric sciences; Albedo (alchemy); Forcing (mathematics); Future sea level; Ice-albedo feedback; Climate model; Ablation zone; Sea ice; Climate change; Cryosphere; Geology; Ice stream; Glacier; Geomorphology; Oceanography","score_opus":0.03330951829467412,"score_gpt":0.2506242611543845,"score_spread":0.2173147428597104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3049229383","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99553114,0.000044619042,0.0004938692,0.00020537918,0.000022597562,0.000014233372,0.0016713332,0.00015174491,0.0018650726],"genre_scores_gemma":[0.99757713,0.000029093533,0.0005545152,0.00006387598,0.0000065683475,0.000021904183,0.0013953367,0.00003476628,0.0003169005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984515,0.000047782138,0.0000066202633,0.000033151235,0.000016419941,0.00005079518],"domain_scores_gemma":[0.9997588,0.000058381505,0.00003121708,0.000033120115,0.000051310457,0.000067171204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059039297,0.0010883777,0.00071495917,0.00035718596,0.0005652116,0.00082483696,0.0009734459,0.0011940133,0.0015998656],"category_scores_gemma":[0.0007343811,0.00035370322,0.0011368754,0.00063323346,0.0005899421,0.0004975219,0.00054835354,0.0007488039,0.00019812713],"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":[0.00031308443,0.00012405879,0.026930887,0.00004852507,0.00019341696,0.00019525173,0.00004735278,0.9642343,0.0045008296,0.0007049662,0.0013587011,0.0013486883],"study_design_scores_gemma":[0.00029955577,0.00012245197,0.04297545,0.000012717486,0.00009877435,0.00003183469,0.00009258016,0.95294976,0.0020994071,0.00045083277,0.0008079665,0.00005859099],"about_ca_topic_score_codex":0.11395016,"about_ca_topic_score_gemma":0.061347242,"teacher_disagreement_score":0.11395016,"about_ca_system_score_codex":0.0019827802,"about_ca_system_score_gemma":0.0012430098,"threshold_uncertainty_score":0.22657382},"labels":[],"label_agreement":null},{"id":"W3084961635","doi":"10.1029/2020ms002143","title":"An Overview of Antarctic Sea Ice in the Community Earth System Model Version 2, Part I: Analysis of the Seasonal Cycle in the Context of Sea Ice Thermodynamics and Coupled Atmosphere‐Ocean‐Ice Processes","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":46,"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 Victoria","funders":"","keywords":"Sea ice; Antarctic sea ice; Arctic ice pack; Climatology; Environmental science; Geology; Lead (geology); Atmospheric sciences; Oceanography","score_opus":0.029957769089354734,"score_gpt":0.25912248753947825,"score_spread":0.2291647184501235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084961635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78295326,0.025002955,0.079495266,0.003139305,0.00059376453,0.00036574373,0.05954739,0.003682613,0.045219753],"genre_scores_gemma":[0.92823005,0.0069321333,0.03669266,0.00031303716,0.0003017917,0.00032803073,0.022674955,0.0010364671,0.0034910417],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998337,0.00006379953,0.000012132016,0.000026573773,0.00004449964,0.0000192252],"domain_scores_gemma":[0.99969995,0.00007617088,0.000034365796,0.000047392514,0.00011668874,0.000025506773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007456594,0.0009868518,0.00051299745,0.0008529482,0.00034124055,0.00091825705,0.0009246992,0.000527881,0.0018349234],"category_scores_gemma":[0.0014147492,0.00033844117,0.0008187095,0.0018314255,0.00019842378,0.0008251294,0.0005406822,0.0005615526,0.0004066634],"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":[0.0001907436,0.00009344445,0.04632878,0.00043174086,0.00034447623,0.00016220543,0.000070327005,0.8852107,0.0029705523,0.005328942,0.013663263,0.045204826],"study_design_scores_gemma":[0.000072758325,0.0000560842,0.027277298,0.00009711047,0.000075898715,0.000039862683,0.000054278793,0.95294434,0.0011827955,0.0026699167,0.015483625,0.000045983907],"about_ca_topic_score_codex":0.05536878,"about_ca_topic_score_gemma":0.03188088,"teacher_disagreement_score":0.05536878,"about_ca_system_score_codex":0.0007452289,"about_ca_system_score_gemma":0.0011431995,"threshold_uncertainty_score":0.110093},"labels":[],"label_agreement":null},{"id":"W3086257204","doi":"10.1029/2020ms002123","title":"Coupling of Phosphorus Processes With Carbon and Nitrogen Cycles in the Dynamic Land Ecosystem Model: Model Structure, Parameterization, and Evaluation in Tropical Forests","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":40,"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 Guelph","funders":"National Key Research and Development Program of China; China Scholarship Council; National Science Foundation","keywords":"Primary production; Environmental science; Eddy covariance; Biogeochemical cycle; Terrestrial ecosystem; Chronosequence; Atmospheric sciences; Biosphere; Ecosystem; Carbon cycle; Biosphere model; Biogeochemistry; Ecology; Soil water; Soil science; Biology; Geology","score_opus":0.011568398327365694,"score_gpt":0.2346008020350376,"score_spread":0.2230324037076719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3086257204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98918086,0.00012712032,0.008838089,0.0000844263,0.000008754703,0.000047948837,0.00022061556,0.00014757468,0.0013446828],"genre_scores_gemma":[0.99630773,0.00004859497,0.0033178483,0.00001806069,0.0000035758271,0.00003684514,0.00009919057,0.000017064542,0.00015120069],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997944,0.00010324966,0.000014539881,0.000035798388,0.000021424215,0.000030544623],"domain_scores_gemma":[0.9989104,0.0007022011,0.00009236674,0.00006500181,0.00015557208,0.00007439315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013671851,0.00080972386,0.00060059194,0.00044707695,0.00045420573,0.0006925087,0.0013487,0.0007239559,0.00068446645],"category_scores_gemma":[0.0026742904,0.00044581702,0.0004710372,0.00036730792,0.0005605443,0.00072211656,0.00075111235,0.00062553945,0.000070216156],"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":[0.000055247056,0.000039273928,0.004937116,0.000013580188,0.000023566028,0.00002595957,0.0000135754235,0.9930702,0.00036873404,0.00016059843,0.00003761483,0.0012545533],"study_design_scores_gemma":[0.000017503286,0.00001952966,0.0006955384,0.0000018664082,0.0000072542143,0.0000033749068,0.0000064617366,0.998987,0.00017933929,0.000056661993,0.000022413042,0.0000029994721],"about_ca_topic_score_codex":0.062434427,"about_ca_topic_score_gemma":0.02440052,"teacher_disagreement_score":0.062434427,"about_ca_system_score_codex":0.0012469023,"about_ca_system_score_gemma":0.00096098665,"threshold_uncertainty_score":0.12414205},"labels":[],"label_agreement":null},{"id":"W3087938632","doi":"10.1029/2020ms002160","title":"COnstraining ORographic Drag Effects (COORDE): A Model Comparison of Resolved and Parametrized Orographic Drag","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":35,"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":"DOC Office of the Secretary","keywords":"Orographic lift; Drag; Wave drag; Parametrization (atmospheric modeling); Orography; Environmental science; Climatology; Meteorology; Gravity wave; Atmospheric sciences; Geology; Drag coefficient; Physics; Mechanics; Precipitation; Wave propagation","score_opus":0.016834135473413017,"score_gpt":0.275060596025974,"score_spread":0.258226460552561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087938632","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94983494,0.00031065007,0.025615701,0.0007048325,0.00013641418,0.00019748794,0.008020979,0.0017454921,0.01343354],"genre_scores_gemma":[0.9839422,0.000091789254,0.010846043,0.00007593496,0.000022015602,0.00015186447,0.0038427706,0.00021890957,0.00080844754],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944097,0.00022332984,0.000033066106,0.00014081717,0.00010298515,0.000058753754],"domain_scores_gemma":[0.99774265,0.0010871631,0.00019200835,0.00049355644,0.00034192254,0.00014271733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025733318,0.0008408485,0.0009224077,0.00063380704,0.00060460536,0.002014571,0.0018880079,0.0009243006,0.0018070223],"category_scores_gemma":[0.003987571,0.0005659363,0.0010642695,0.0009602852,0.0005910168,0.0015210949,0.001157841,0.0013173893,0.00029114014],"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":[0.0002958194,0.0001513918,0.013942863,0.000055605295,0.00013494966,0.000033639266,0.000034551904,0.9753025,0.0011316251,0.0021318698,0.0016067761,0.0051784357],"study_design_scores_gemma":[0.00034556095,0.00018139793,0.006823028,0.000016017786,0.000039173898,0.000011717253,0.0000474542,0.9889552,0.0015316133,0.0005989435,0.0014009534,0.000048885442],"about_ca_topic_score_codex":0.05499997,"about_ca_topic_score_gemma":0.032585934,"teacher_disagreement_score":0.05499997,"about_ca_system_score_codex":0.0011447143,"about_ca_system_score_gemma":0.0018096906,"threshold_uncertainty_score":0.10935968},"labels":[],"label_agreement":null},{"id":"W3092632667","doi":"10.1029/2020ms002221","title":"A Global Flood Risk Modeling Framework Built With Climate Models and Machine Learning","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Mitacs; Marine Environmental Observation Prediction and Response Network","keywords":"Flood myth; Climate change; Climate model; Socioeconomic status; Natural hazard; Population; Scale (ratio); Environmental resource management; Climatology; Environmental science; Geography; Computer science; Meteorology; Cartography; Geology","score_opus":0.01409643553556023,"score_gpt":0.26098926732227046,"score_spread":0.24689283178671023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092632667","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042785026,0.0002279258,0.94569856,0.00095998374,0.00008583428,0.00007261598,0.0014907685,0.0023043184,0.006374987],"genre_scores_gemma":[0.6819299,0.0004721826,0.30953333,0.00027784007,0.00017549361,0.00038725653,0.0022964384,0.000518362,0.004409185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975294,0.00009592986,0.000016424192,0.00006247516,0.000046877718,0.00002542674],"domain_scores_gemma":[0.99953234,0.0002034574,0.00005800338,0.000046991925,0.000110158864,0.00004904118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011331517,0.000962855,0.0006492321,0.0009914596,0.00055685954,0.0011612826,0.001629529,0.0011243916,0.002934017],"category_scores_gemma":[0.0018898615,0.00052791875,0.0013873593,0.00081008126,0.0005286222,0.0012431885,0.0016719422,0.0011059885,0.00043158088],"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":[0.000004157044,0.000008120442,0.00047479142,0.0000045582537,0.000016303822,0.000018352619,0.0000076572915,0.99347514,0.00006671026,0.0034743757,0.00031880275,0.0021309545],"study_design_scores_gemma":[0.0000025172274,0.0000023746784,0.00005744437,0.0000016849269,0.0000027193666,0.000002984371,0.0000025333102,0.9966646,0.000021476508,0.0028677394,0.00037164395,0.0000022265144],"about_ca_topic_score_codex":0.024576688,"about_ca_topic_score_gemma":0.018273104,"teacher_disagreement_score":0.024576688,"about_ca_system_score_codex":0.001080957,"about_ca_system_score_gemma":0.0017141299,"threshold_uncertainty_score":0.048867285},"labels":[],"label_agreement":null},{"id":"W3095694818","doi":"10.1029/2019ms001902","title":"Disentangling the Coupled Atmosphere‐Ocean‐Ice Interactions Driving Arctic Sea Ice Response to CO<sub>2</sub> Increases","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","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":false,"ca_institutions":"University of Victoria","funders":"U.S. Department of Energy","keywords":"Sea ice; Arctic ice pack; Arctic sea ice decline; Sea ice thickness; Drift ice; Atmosphere (unit); Climatology; Antarctic sea ice; Cryosphere; Arctic; Geology; Oceanography; Lead (geology); Thermohaline circulation; Environmental science; Sea ice growth processes; Arctic geoengineering; Meteorology; Geography; Geomorphology","score_opus":0.013295480334224312,"score_gpt":0.2449405817722498,"score_spread":0.2316451014380255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3095694818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991893,0.000039348914,0.00041240873,0.000016016063,0.000006176663,0.0000070812143,0.000106212094,0.000012627604,0.000210814],"genre_scores_gemma":[0.9993519,0.00004532838,0.00027220277,0.000019268344,0.0000030071883,0.000013268501,0.00013809623,0.0000075227217,0.00014936108],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999387,0.000010570953,0.000004738821,0.000017322998,0.000009314919,0.000019354396],"domain_scores_gemma":[0.99985397,0.00006047486,0.000019680518,0.00002065177,0.000014088524,0.000031126405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024161537,0.0004416824,0.0005448374,0.00013667266,0.0002849311,0.0005045766,0.00018450005,0.00021020895,0.0009508718],"category_scores_gemma":[0.00027409173,0.00035473792,0.00036912097,0.00009614073,0.0002758161,0.00036689985,0.00046403587,0.00034195214,0.00010160783],"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":[0.0015327365,0.00026277744,0.03198948,0.00014268945,0.00028534367,0.00011074506,0.00011917125,0.025275229,0.93408644,0.0003074187,0.00014478798,0.0057430854],"study_design_scores_gemma":[0.00012568808,0.0012387685,0.57933617,0.000015834526,0.00030315854,0.000081040875,0.00041077766,0.21333316,0.2030569,0.0007752739,0.0012400466,0.00008317518],"about_ca_topic_score_codex":0.010877227,"about_ca_topic_score_gemma":0.016733417,"teacher_disagreement_score":0.010877227,"about_ca_system_score_codex":0.00040540894,"about_ca_system_score_gemma":0.00050376204,"threshold_uncertainty_score":0.021627843},"labels":[],"label_agreement":null},{"id":"W3104050426","doi":"10.1029/2019ms001992","title":"A General‐Coordinate, Nonlocal Neutral Diffusion Operator","year":2020,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Oceanographic and Atmospheric Processes","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":false,"ca_institutions":"University of Victoria","funders":"National Oceanic and Atmospheric Administration","keywords":"Isopycnal; Stencil; Maxima and minima; Advection; Discretization; Diffusion; Diffusion equation; Grid; Operator (biology); Flux (metallurgy); Nonlinear system; Mathematical analysis; Physics; Mathematics; Geometry; Geology","score_opus":0.013591976781254253,"score_gpt":0.22156250835423152,"score_spread":0.20797053157297726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3104050426","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019408427,0.0000869058,0.9744804,0.00019294211,0.00009793994,0.00003948868,0.000073332645,0.0001743386,0.0054461984],"genre_scores_gemma":[0.44373012,0.00026514754,0.53965646,0.00018626766,0.000101678714,0.00015562578,0.00016250722,0.0001856953,0.015556521],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979526,0.000052205847,0.000009468392,0.000042602507,0.00007993609,0.000020537746],"domain_scores_gemma":[0.9997441,0.00007467006,0.000030658124,0.000040078845,0.00007707658,0.000033382385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005037625,0.00041004407,0.00041544606,0.0002900895,0.00042340925,0.00069788215,0.000973184,0.00081129593,0.0029682992],"category_scores_gemma":[0.0011333849,0.00020641008,0.0005340956,0.00031807413,0.0010431614,0.0011222471,0.0013353302,0.0007648614,0.0004118699],"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":[0.000083775674,0.000051145154,0.00073367805,0.00012308767,0.000026421038,0.00027130198,0.00016588502,0.393955,0.032911632,0.5259084,0.002712954,0.043056693],"study_design_scores_gemma":[0.000012092734,0.000020245976,0.000063828025,0.0000030658903,0.0000029473922,0.000043780587,0.000010104657,0.9770389,0.0013996696,0.018891178,0.0025036854,0.0000104409255],"about_ca_topic_score_codex":0.0030845117,"about_ca_topic_score_gemma":0.00183468,"teacher_disagreement_score":0.0030845117,"about_ca_system_score_codex":0.00065495685,"about_ca_system_score_gemma":0.0010272196,"threshold_uncertainty_score":0.009930015},"labels":[],"label_agreement":null},{"id":"W3128192127","doi":"10.1029/2021ms002492","title":"Rotating Shallow Water Flow Under Location Uncertainty With a Structure‐Preserving Discretization","year":2021,"lang":"en","type":"preprint","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Mitacs; Agence Nationale de la Recherche; Natural Environment Research Council; Sight Research UK","keywords":"Discretization; Inviscid flow; Flow (mathematics); Temporal discretization; Noise (video); Applied mathematics; Mathematics; Realization (probability); Finite volume method; Scale (ratio); Representation (politics); Stochastic modelling; Mathematical optimization; Statistical physics; Computer science; Mathematical analysis; Geometry; Physics; Classical mechanics; Mechanics; Statistics","score_opus":0.02335037607320054,"score_gpt":0.24871924507895635,"score_spread":0.2253688690057558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128192127","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07080227,0.00024391872,0.9207265,0.00044227898,0.00009678399,0.00003080719,0.00023033869,0.00017297467,0.00725418],"genre_scores_gemma":[0.9077266,0.00038038756,0.08410586,0.00014367147,0.00011555264,0.00007635531,0.000285578,0.00009784769,0.007068089],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978834,0.00006458344,0.000011867497,0.000039073264,0.00006872701,0.000027267],"domain_scores_gemma":[0.99970263,0.00006993866,0.00009105173,0.000045171986,0.0000593898,0.00003183033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049001427,0.00053686684,0.00051011785,0.00036581472,0.00025081608,0.00084275997,0.00086206215,0.0007050964,0.0011467072],"category_scores_gemma":[0.0011207802,0.0003239861,0.0007643248,0.00036322165,0.0010399632,0.00080346665,0.0010309784,0.00095036003,0.00020409415],"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":[0.000037465285,0.000018121504,0.00055585674,0.000027516024,0.000017513934,0.00008101697,0.00004986387,0.71194196,0.0055567943,0.273563,0.00063956145,0.007511348],"study_design_scores_gemma":[0.000004232518,0.000007715038,0.000054597243,0.0000011403614,0.0000015168084,0.000005223583,0.0000022490274,0.9926664,0.00017296449,0.006861417,0.00021952826,0.0000030562946],"about_ca_topic_score_codex":0.008763753,"about_ca_topic_score_gemma":0.003089229,"teacher_disagreement_score":0.008763753,"about_ca_system_score_codex":0.0009828644,"about_ca_system_score_gemma":0.0007801418,"threshold_uncertainty_score":0.017425478},"labels":[],"label_agreement":null},{"id":"W3129555178","doi":"10.1029/2020ms002366","title":"Multicentennial Variability Driven by Salinity Exchanges Between the Atlantic and the Arctic Ocean in a Coupled Climate Model","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":61,"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":"Sorbonne Université; Centre National d’Etudes Spatiales; Grand Équipement National De Calcul Intensif; Agence Nationale de la Recherche; Centre National de la Recherche Scientifique; European Commission","keywords":"Oceanography; Arctic dipole anomaly; Arctic; Arctic geoengineering; Climatology; Arctic sea ice decline; Geology; Sea ice; Arctic ice pack; Thermohaline circulation; Salinity; North Atlantic Deep Water; Climate model; Ocean current; Environmental science; Climate change; Sea ice thickness; Antarctic sea ice","score_opus":0.013804373368731805,"score_gpt":0.238385558029572,"score_spread":0.2245811846608402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129555178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98716134,0.00016630099,0.0044142203,0.00033573306,0.000108320055,0.000026912974,0.001958802,0.00024734598,0.0055810604],"genre_scores_gemma":[0.9960211,0.000073820185,0.0013992933,0.000044246994,0.000021456586,0.000034674467,0.0009684255,0.000033662876,0.001403271],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998708,0.00003492693,0.000007603738,0.000038092585,0.000018136257,0.000030445191],"domain_scores_gemma":[0.99976414,0.00007084129,0.000034358003,0.00002174764,0.000055532113,0.00005336693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003538452,0.00077698455,0.0006681685,0.00042226425,0.000670826,0.0013032543,0.00094682665,0.0014336278,0.001674613],"category_scores_gemma":[0.0008064747,0.00049330655,0.0010911776,0.00053021027,0.00053681055,0.0006641054,0.0008404127,0.0008507643,0.00022131679],"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":[0.00010954085,0.000048156737,0.005899916,0.000014789975,0.0000943187,0.00008610448,0.000018200379,0.99081296,0.00094932603,0.0006417476,0.00044263087,0.00088232313],"study_design_scores_gemma":[0.000046531313,0.000028752645,0.0031011824,0.0000034522445,0.000027214746,0.0000073371593,0.000013839365,0.99608684,0.00016286952,0.00022975686,0.00027908222,0.000013139763],"about_ca_topic_score_codex":0.09252067,"about_ca_topic_score_gemma":0.047737073,"teacher_disagreement_score":0.09252067,"about_ca_system_score_codex":0.0012338331,"about_ca_system_score_gemma":0.001271198,"threshold_uncertainty_score":0.18396425},"labels":[],"label_agreement":null},{"id":"W3130732567","doi":"10.1029/2020ms002367","title":"Scale‐Aware Space‐Time Stochastic Parameterization of Subgrid‐Scale Velocity Enhancement of Sea Surface Fluxes","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","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":"University of Victoria","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Mesoscale meteorology; Scale (ratio); Stochastic modelling; Wind speed; Statistical physics; Meteorology; Mathematics; Physics; Statistics","score_opus":0.013627874164379985,"score_gpt":0.24857933174615632,"score_spread":0.23495145758177632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130732567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5009845,0.000098729724,0.49637708,0.0002532399,0.000024209161,0.000022233335,0.0001657368,0.00030789388,0.0017664335],"genre_scores_gemma":[0.9941355,0.000029548679,0.005503851,0.000014370556,0.000008588886,0.0000145413105,0.00004745711,0.000026253932,0.00021999556],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997589,0.00009423938,0.000011083351,0.000052119878,0.00004712394,0.000036533867],"domain_scores_gemma":[0.9987919,0.0006236569,0.00024149804,0.00017949691,0.000118819,0.00004475998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079543726,0.0004015396,0.00034100443,0.00034819872,0.0002173746,0.0005487028,0.000669702,0.00045916362,0.00041654153],"category_scores_gemma":[0.0028352665,0.00031863988,0.0005350439,0.00031183116,0.00062374165,0.0010306814,0.00042438792,0.0007242444,0.000051648767],"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":[0.0000059404183,0.000007412031,0.0007027255,0.0000024402434,0.0000064969045,0.000007490681,0.0000065569334,0.9943347,0.0009194293,0.0033628873,0.000028003142,0.00061592495],"study_design_scores_gemma":[5.84292e-7,0.0000013383496,0.0001665605,2.470957e-7,6.446482e-7,9.0650417e-7,6.447546e-7,0.9991015,0.00012302781,0.00058786926,0.000015604148,0.000001113284],"about_ca_topic_score_codex":0.007130882,"about_ca_topic_score_gemma":0.005014515,"teacher_disagreement_score":0.007130882,"about_ca_system_score_codex":0.0009268779,"about_ca_system_score_gemma":0.0006423487,"threshold_uncertainty_score":0.014178753},"labels":[],"label_agreement":null},{"id":"W3161991429","doi":"10.1029/2020ms002451","title":"A Process‐Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Environmental science; Carbon sequestration; Ecosystem; Primary production; Biosphere; Evapotranspiration; Carbon cycle; Productivity; Ecosystem services; Terrestrial ecosystem; Soil carbon; Ecosystem model; Environmental resource management; Soil water; Soil science; Ecology; Carbon dioxide","score_opus":0.03937744686643549,"score_gpt":0.3197000318840132,"score_spread":0.2803225850175777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161991429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55499554,0.00049060216,0.43040624,0.0007313197,0.00014188018,0.00017062975,0.001342023,0.0007028071,0.011018941],"genre_scores_gemma":[0.9865437,0.00011475011,0.011101183,0.00003309925,0.00001839321,0.00013786333,0.00029189506,0.000022407825,0.0017367108],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996464,0.00009389267,0.000025224806,0.00010300514,0.000079618825,0.0000518224],"domain_scores_gemma":[0.99942917,0.00025574912,0.00007744687,0.000029133565,0.00016471985,0.00004372607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010172597,0.0009932404,0.00072450604,0.000967502,0.0005824899,0.0011562802,0.0015949339,0.0014022546,0.0016546588],"category_scores_gemma":[0.0013587828,0.00057407195,0.001246771,0.0009224495,0.000605312,0.0011632656,0.00075663003,0.00089782424,0.00018089575],"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":[0.000011369394,0.00001635941,0.0010511682,0.0000073622123,0.0000132943105,0.000019125067,0.000008543199,0.9964785,0.00029065745,0.00086567446,0.000072548944,0.0011654807],"study_design_scores_gemma":[0.0000027011133,0.0000030048584,0.0001058842,6.4665124e-7,0.0000024350034,0.0000011841144,0.0000014114373,0.99964297,0.000032821987,0.00017367087,0.00003151978,0.0000017412676],"about_ca_topic_score_codex":0.054377966,"about_ca_topic_score_gemma":0.021753026,"teacher_disagreement_score":0.054377966,"about_ca_system_score_codex":0.001732289,"about_ca_system_score_gemma":0.0017635747,"threshold_uncertainty_score":0.108122945},"labels":[],"label_agreement":null},{"id":"W3163819433","doi":"10.1029/2020ms002434","title":"A Vector‐Based River Routing Model for Earth System Models: Parallelization and Global Applications","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":80,"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 Saskatchewan","funders":"National Aeronautics and Space Administration; National Center for Atmospheric Research; National Science Foundation","keywords":"Tributary; Computer science; Routing (electronic design automation); Streamflow; Flow routing; Scale (ratio); Hydrology (agriculture); Computation; Drainage basin; Environmental science; Algorithm; Geology; Geography","score_opus":0.02136616474558545,"score_gpt":0.2587854210184392,"score_spread":0.23741925627285376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163819433","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2438437,0.00036614764,0.7317132,0.0010467526,0.000119228025,0.00016764435,0.001397492,0.0025551075,0.018790718],"genre_scores_gemma":[0.8336243,0.0003035005,0.15813483,0.0001083944,0.00004574723,0.00025130308,0.0009924611,0.0003569437,0.006182557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985826,0.000057682653,0.0000066736616,0.000031499698,0.000029571564,0.000016269752],"domain_scores_gemma":[0.99971265,0.00012432536,0.000032924163,0.000035431578,0.000069995476,0.000024682728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038935326,0.0004972547,0.0005380441,0.00030342175,0.000333146,0.00076190935,0.0007382808,0.00061591144,0.0027858114],"category_scores_gemma":[0.0008464431,0.0003028518,0.0004678774,0.0007225465,0.00040624652,0.00076529954,0.0005397844,0.00060021505,0.00031964394],"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":[0.000008905079,0.000011973932,0.0003796742,0.000006053585,0.000005928623,0.000010052854,0.0000068184945,0.99315554,0.00034146654,0.002335335,0.00039249143,0.0033457836],"study_design_scores_gemma":[0.0000034809893,0.0000024339006,0.000040641447,4.0272212e-7,8.237836e-7,9.921179e-7,0.0000015502567,0.9992865,0.00005255659,0.0004188081,0.00019102977,9.2746524e-7],"about_ca_topic_score_codex":0.015600203,"about_ca_topic_score_gemma":0.013536364,"teacher_disagreement_score":0.015600203,"about_ca_system_score_codex":0.0007167803,"about_ca_system_score_gemma":0.0007789952,"threshold_uncertainty_score":0.031018794},"labels":[],"label_agreement":null},{"id":"W3171340588","doi":"10.1029/2020ms002356","title":"Description and Demonstration of the Coupled Community Earth System Model v2 – Community Ice Sheet Model v2 (CESM2‐CISM2)","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"EMD Inc. (Canada)","funders":"H2020 European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Office of Legacy Management; National Center for Atmospheric Research; National Science Foundation","keywords":"Earth system science; Ice sheet; Geology; Earth (classical element); Meteorology; Oceanography; Geography; Physics","score_opus":0.053567972104460876,"score_gpt":0.2488347429488691,"score_spread":0.19526677084440822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171340588","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7413861,0.00040492738,0.14271058,0.0015732088,0.00046170328,0.0010761502,0.027715066,0.018315459,0.06635675],"genre_scores_gemma":[0.9623378,0.00008084105,0.02787123,0.00012343869,0.000031646126,0.00040752487,0.005866839,0.0005192925,0.0027612657],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974936,0.00010517205,0.000017596003,0.000037896254,0.00005688533,0.000033033943],"domain_scores_gemma":[0.99943215,0.0001870655,0.00003674475,0.00009859323,0.00016620076,0.00007926662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010188989,0.0010697647,0.00043093672,0.00042235947,0.00067521224,0.0010537539,0.00181549,0.0010794002,0.004697933],"category_scores_gemma":[0.0016110705,0.00044224248,0.00063813897,0.00046570066,0.00042408824,0.0006728409,0.00093251653,0.0008747523,0.00067577267],"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":[0.00015607246,0.00007949143,0.004753219,0.000053475316,0.00005110472,0.00018846268,0.00005222336,0.9802525,0.001387383,0.0033090413,0.005250634,0.0044665392],"study_design_scores_gemma":[0.00006779365,0.00002111208,0.0005860333,0.0000045073757,0.000006307981,0.000008752204,0.0000098826495,0.99711645,0.0004046357,0.00045147174,0.0013136448,0.00000948957],"about_ca_topic_score_codex":0.06496882,"about_ca_topic_score_gemma":0.038770128,"teacher_disagreement_score":0.06496882,"about_ca_system_score_codex":0.00091663335,"about_ca_system_score_gemma":0.0012416454,"threshold_uncertainty_score":0.12918133},"labels":[],"label_agreement":null},{"id":"W3175133288","doi":"10.1029/2020ms002394","title":"Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":76,"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 Saskatchewan","funders":"National Institute of Food and Agriculture; Center for Hierarchical Manufacturing, National Science Foundation; Beijing Normal University; National Centers for Environmental Information; National Oceanic and Atmospheric Administration; State Key Laboratory of Earth Surface Processes and Resource Ecology; U.S. Department of Agriculture; National Science Foundation","keywords":"Leaf area index; Data assimilation; Environmental science; Ensemble Kalman filter; Atmospheric sciences; Water content; Phenology; Canopy; Vegetation (pathology); Meteorology; Agronomy; Mathematics; Kalman filter; Ecology; Geology","score_opus":0.01199867482991916,"score_gpt":0.22449666899376491,"score_spread":0.21249799416384577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175133288","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.906305,0.00028618038,0.08813819,0.0002880522,0.00006359428,0.000038901067,0.00032307283,0.0009621365,0.003594842],"genre_scores_gemma":[0.9888797,0.000032074317,0.0105017265,0.00002182357,0.000005857797,0.000013454924,0.00014507819,0.000015392905,0.0003849489],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998971,0.000029113675,0.000007364531,0.000025075762,0.000024566516,0.000016689552],"domain_scores_gemma":[0.99984586,0.000056515368,0.000014637618,0.000023624987,0.000047910984,0.00001140355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004693985,0.00046410284,0.00026245342,0.00015188711,0.00020573908,0.00052155775,0.00040121132,0.00039115833,0.0004903121],"category_scores_gemma":[0.00086242944,0.00017409721,0.00034892862,0.00012545889,0.00015118804,0.00048401166,0.00044743228,0.00034480222,0.0001523472],"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":[0.00007703217,0.00006656268,0.007830364,0.000019816127,0.00006164008,0.000020897412,0.000024256477,0.96628124,0.0053204997,0.0002170211,0.0004556675,0.0196251],"study_design_scores_gemma":[0.000007328506,0.000008715026,0.0009868889,0.0000010171291,0.000005003162,0.00000107211,0.0000027940773,0.9981785,0.0006778374,0.000028598504,0.00010007288,0.0000022005927],"about_ca_topic_score_codex":0.03342071,"about_ca_topic_score_gemma":0.024288675,"teacher_disagreement_score":0.03342071,"about_ca_system_score_codex":0.00032688485,"about_ca_system_score_gemma":0.00067402446,"threshold_uncertainty_score":0.066452384},"labels":[],"label_agreement":null},{"id":"W3178844591","doi":"10.1029/2020ms002447","title":"Evaluating Precipitation Errors Using the Environmentally Conditioned Intensity‐Frequency Decomposition Method","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Precipitation; Forcing (mathematics); Compensation (psychology); Intensity (physics); Convection; Parameterized complexity; Computer science; Environmental science; Meteorology; Algorithm; Atmospheric sciences; Geology; Physics; Optics","score_opus":0.0817696835426389,"score_gpt":0.3708364008333777,"score_spread":0.2890667172907388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3178844591","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29462987,0.00012801992,0.70245945,0.00016702167,0.00005330601,0.000084837804,0.0004115341,0.0005385904,0.001527342],"genre_scores_gemma":[0.87288034,0.000055644938,0.12623061,0.000034711735,0.00002556948,0.00005526944,0.00033416972,0.000075647455,0.00030803395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919945,0.00033570014,0.00007762723,0.000091006244,0.0002364109,0.000059698206],"domain_scores_gemma":[0.9951303,0.0028079886,0.0006509443,0.0004578563,0.0007743118,0.00017867301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026652163,0.00066045753,0.00048292335,0.0013345261,0.00024481193,0.0007381057,0.00057375606,0.0007625325,0.00071049394],"category_scores_gemma":[0.011582794,0.00020823262,0.00044391782,0.00062337227,0.00053678575,0.0010432255,0.000983961,0.00079985,0.00009646545],"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":[0.0000938279,0.00007502603,0.0114651425,0.0000315705,0.000080465856,0.000025188207,0.00002847963,0.9603668,0.0036359488,0.0050886115,0.00023864492,0.018870316],"study_design_scores_gemma":[0.0000047456792,0.000014212422,0.0011100671,0.000003241687,0.0000026587534,0.00000384411,0.000003918994,0.9964406,0.0011565085,0.0011871787,0.000067615765,0.00000540701],"about_ca_topic_score_codex":0.008384044,"about_ca_topic_score_gemma":0.0047952854,"teacher_disagreement_score":0.008384044,"about_ca_system_score_codex":0.00063780247,"about_ca_system_score_gemma":0.0009725264,"threshold_uncertainty_score":0.016670525},"labels":[],"label_agreement":null},{"id":"W3196172941","doi":"10.1029/2021ms002570","title":"A Data Set for Intercomparing the Transient Behavior of Dynamical Model‐Based Subseasonal to Decadal Climate Predictions","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":7,"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":"Hindcast; Climatology; Set (abstract data type); Forecast skill; Data set; Range (aeronautics); Climate model; Coupled model intercomparison project; Transient (computer programming); Computer science; Environmental science; Meteorology; Climate change; Geology","score_opus":0.07536255300938054,"score_gpt":0.34080979057348654,"score_spread":0.265447237564106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196172941","genre_codex":"empirical","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8865692,0.00009382816,0.010121553,0.00010874348,0.00009056324,0.00009953505,0.099117205,0.00076242886,0.003036803],"genre_scores_gemma":[0.8675805,0.00005217472,0.008886272,0.000021780234,0.000027491025,0.00021368473,0.12269418,0.00006080682,0.00046314546],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973506,0.000054804572,0.000042619446,0.00007464269,0.000066416505,0.000026437461],"domain_scores_gemma":[0.99841034,0.00039133313,0.00023791326,0.0004965409,0.0003683336,0.00009546623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062633713,0.00029168636,0.00022996408,0.0012337093,0.0003193415,0.0004461378,0.0004240351,0.0004086901,0.00086762215],"category_scores_gemma":[0.0016556256,0.00012380283,0.0002648154,0.0011875768,0.00015130687,0.00036577514,0.00052663643,0.0004683256,0.00026989056],"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":[0.0013399197,0.0015651749,0.5087458,0.00039395163,0.00065921433,0.0006636102,0.00069159496,0.25432917,0.03033127,0.0060417126,0.041641425,0.15359715],"study_design_scores_gemma":[0.00017274238,0.00042293055,0.7128976,0.000060612147,0.000104605824,0.00022135129,0.00053019816,0.22333644,0.020871274,0.001830365,0.039453004,0.0000989126],"about_ca_topic_score_codex":0.009107851,"about_ca_topic_score_gemma":0.00929134,"teacher_disagreement_score":0.009107851,"about_ca_system_score_codex":0.00027762356,"about_ca_system_score_gemma":0.00041163596,"threshold_uncertainty_score":0.01810968},"labels":[],"label_agreement":null},{"id":"W3207047737","doi":"10.1029/2021ms002523","title":"Simulating Linear Kinematic Features in Viscous‐Plastic Sea Ice Models on Quadrilateral and Triangular Grids With Different Variable Staggering","year":2021,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"GDG Environnement; Environment and Climate Change Canada","funders":"","keywords":"Discretization; Quadrilateral; Grid; Polygon mesh; Mesh generation; Geology; Geometry; Applied mathematics; Computer science; Mathematics; Mathematical analysis; Finite element method; Physics","score_opus":0.011225626037546652,"score_gpt":0.2301051097759459,"score_spread":0.21887948373839924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207047737","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95696265,0.000094707444,0.03703082,0.000119080214,0.000046020596,0.000050863167,0.00017394996,0.00017940343,0.0053425776],"genre_scores_gemma":[0.9858742,0.00003742969,0.013404287,0.00001723937,0.0000029197918,0.00002559108,0.00010379987,0.000020153175,0.0005144122],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998165,0.00006181675,0.000015412093,0.000021966422,0.000042478536,0.00004191531],"domain_scores_gemma":[0.998992,0.0005783296,0.00012213261,0.00010098869,0.00012040285,0.00008606133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042647528,0.00037922454,0.00037316774,0.00042221497,0.0002820978,0.00068530027,0.0006646509,0.0007012325,0.0011570157],"category_scores_gemma":[0.0017966622,0.00020968147,0.00043924103,0.0005635706,0.0007103251,0.0004196865,0.0005237924,0.00043974293,0.000110569425],"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":[0.000067973626,0.0000555689,0.0021360256,0.000021604477,0.000010072727,0.00006368382,0.0000367777,0.9928911,0.0016833763,0.0010040033,0.00008456318,0.0019453102],"study_design_scores_gemma":[0.000008451157,0.000026171314,0.0002791868,0.000002790997,0.0000017528772,0.0000051743227,0.000020281257,0.99888724,0.0004976805,0.00020069927,0.000067829256,0.0000026572845],"about_ca_topic_score_codex":0.014231948,"about_ca_topic_score_gemma":0.008338455,"teacher_disagreement_score":0.014231948,"about_ca_system_score_codex":0.0006695648,"about_ca_system_score_gemma":0.0006167687,"threshold_uncertainty_score":0.0282982},"labels":[],"label_agreement":null},{"id":"W4205809052","doi":"10.1029/2021ms002715","title":"Influence of Nonseasonal River Discharge on Sea Surface Salinity and Height","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":25,"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 Saskatchewan","funders":"Earth Sciences Division","keywords":"Discharge; Environmental science; Climatology; Salinity; SSS*; Sea surface temperature; Forcing (mathematics); Oceanography; Geology; Geography","score_opus":0.009680240769655648,"score_gpt":0.22097598066541607,"score_spread":0.21129573989576042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205809052","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989888,0.000025279352,0.0002941426,0.000024757423,0.000008720911,0.0000033472954,0.0002709097,0.00002728123,0.0003567846],"genre_scores_gemma":[0.9994374,0.00001724553,0.000112168134,0.000008802251,0.0000018650711,0.0000028373001,0.00031969306,0.000008339463,0.00009162739],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998324,0.000038813887,0.000017479315,0.000045927474,0.000034072124,0.000031170563],"domain_scores_gemma":[0.9995098,0.00023090617,0.000052965734,0.00006835188,0.00007570294,0.00006228806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033490412,0.00030684483,0.0002384544,0.00017873374,0.00018142832,0.0004547006,0.00023451452,0.00029601384,0.0008159555],"category_scores_gemma":[0.0009743752,0.00016461544,0.0004821964,0.00020180533,0.00029061156,0.00036587226,0.0003939508,0.0003364222,0.00012339445],"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":[0.00074067,0.00032313194,0.71513826,0.00009074986,0.00042019054,0.00037172792,0.00008935433,0.1770414,0.086903855,0.0004341457,0.0008587458,0.01758778],"study_design_scores_gemma":[0.00010298098,0.00033020167,0.70807785,0.0000097717275,0.000113671595,0.000051205614,0.00012863088,0.26623276,0.023744555,0.00026117166,0.0009036053,0.00004362007],"about_ca_topic_score_codex":0.019196825,"about_ca_topic_score_gemma":0.013572468,"teacher_disagreement_score":0.019196825,"about_ca_system_score_codex":0.00041721395,"about_ca_system_score_gemma":0.00038583786,"threshold_uncertainty_score":0.03817022},"labels":[],"label_agreement":null},{"id":"W4206989791","doi":"10.1029/2021ms002468","title":"The DOE E3SM v1.2 Cryosphere Configuration: Description and Simulated Antarctic Ice‐Shelf Basal Melting","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":75,"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":"U.S. Department of Energy","keywords":"Ice shelf; Cryosphere; Iceberg; Geology; Antarctic ice sheet; Ice sheet; Arctic ice pack; Lead (geology); Sea ice; Forcing (mathematics); Climatology; Oceanography; Geomorphology","score_opus":0.022696538442510017,"score_gpt":0.23662389112043655,"score_spread":0.21392735267792654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206989791","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9073041,0.00025423625,0.0066540064,0.00066887034,0.000113506365,0.0001647374,0.054282855,0.0021681085,0.028389717],"genre_scores_gemma":[0.97424126,0.00016015315,0.007656407,0.00022238903,0.000032413358,0.00022443463,0.015327351,0.00040608362,0.001729486],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983096,0.000064384905,0.000011564194,0.00003145861,0.000026249132,0.000035341072],"domain_scores_gemma":[0.99967337,0.00008309709,0.000022503922,0.000084348394,0.00009706838,0.000039568222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051263184,0.0008176971,0.0004538467,0.0004421732,0.0006099923,0.00066661433,0.001597247,0.0009690127,0.003023491],"category_scores_gemma":[0.0009390085,0.00043640408,0.0007878363,0.0009758045,0.00038053136,0.00057349633,0.00042634967,0.0007353882,0.00064210076],"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":[0.00018680231,0.00013701816,0.020336654,0.00007244048,0.00009881752,0.00015025714,0.0000575522,0.9629104,0.0027761199,0.002004518,0.0074979477,0.0037714257],"study_design_scores_gemma":[0.00063403376,0.00012065612,0.02014548,0.000027026976,0.000059844057,0.000045311335,0.00009412592,0.9656414,0.0042978334,0.0013976234,0.0074737053,0.00006302968],"about_ca_topic_score_codex":0.114223294,"about_ca_topic_score_gemma":0.08304924,"teacher_disagreement_score":0.114223294,"about_ca_system_score_codex":0.0011606673,"about_ca_system_score_gemma":0.0010476611,"threshold_uncertainty_score":0.22711688},"labels":[],"label_agreement":null},{"id":"W4210906755","doi":"10.1029/2021ms002861","title":"A One‐Dimensional Lake Model in ECCC's Land Surface Prediction System","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Environment and Climate Change Canada","keywords":"Evapotranspiration; Environmental science; Current (fluid); Initialization; Climatology; Context (archaeology); Land cover; Latitude; Atmospheric sciences; Hydrology (agriculture); Geology; Land use; Oceanography; Ecology","score_opus":0.013825590742111331,"score_gpt":0.21209654583980395,"score_spread":0.1982709550976926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210906755","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95063007,0.000280296,0.014841388,0.0008762956,0.00009536154,0.00013998763,0.006790795,0.0020884748,0.024257349],"genre_scores_gemma":[0.98448807,0.00007954595,0.008070037,0.000079101526,0.000013227905,0.00006725518,0.0029650403,0.00007782283,0.0041599446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998667,0.000025415522,0.000005187642,0.000031585187,0.00003482717,0.000036267164],"domain_scores_gemma":[0.99970657,0.000065214124,0.000014848344,0.00001623554,0.0001398702,0.000057203477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002719484,0.00074913335,0.0005820026,0.00027671718,0.0008852569,0.0009868264,0.0015040911,0.00085089885,0.0035533297],"category_scores_gemma":[0.00073666475,0.0003786879,0.0005585731,0.0005438039,0.00048579305,0.000585223,0.00058725884,0.0009161199,0.00037298686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019439391,0.00007835057,0.005067928,0.000027770684,0.000041530166,0.000046646885,0.000025839592,0.98614454,0.0007532344,0.0007530741,0.0023831876,0.0044835433],"study_design_scores_gemma":[0.00003137381,0.000011852073,0.0008532989,0.0000012965695,0.0000075572966,0.000001224908,0.000007983664,0.99858713,0.00012715498,0.000058469843,0.0003067097,0.000005951163],"about_ca_topic_score_codex":0.84184563,"about_ca_topic_score_gemma":0.754935,"teacher_disagreement_score":0.15815437,"about_ca_system_score_codex":0.0043735844,"about_ca_system_score_gemma":0.004912787,"threshold_uncertainty_score":0.3181715},"labels":[],"label_agreement":null},{"id":"W4213213849","doi":"10.1029/2021ms002844","title":"Parameterizing the Impact of Unresolved Temperature Variability on the Large‐Scale Density Field: 2. Modeling","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":3,"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":"Global Ocean Monitoring and Observing Program; Climate Program Office; U.S. Department of Commerce; U.S. Department of Energy; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Hindcast; Ocean current; Climatology; Scale (ratio); Environmental science; Geology; Meteorology; Physics","score_opus":0.01299539765092991,"score_gpt":0.24495318431666807,"score_spread":0.23195778666573816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213213849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9362665,0.00010807276,0.05983416,0.00029726882,0.00003286234,0.000052479623,0.00035352993,0.00023589373,0.0028192785],"genre_scores_gemma":[0.9938589,0.000029478118,0.0057602143,0.000024704912,0.000006834258,0.0000256222,0.0000722645,0.000020179836,0.00020173035],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997831,0.00007642331,0.0000134990905,0.000048580667,0.000043417094,0.00003506912],"domain_scores_gemma":[0.9991505,0.00044916617,0.00016205086,0.0001368956,0.00008198417,0.000019419536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006522506,0.0005148084,0.00021437716,0.00025124618,0.0003532469,0.0007060072,0.00083725865,0.00077143,0.0006492745],"category_scores_gemma":[0.0032405867,0.00031326772,0.0005236519,0.0003388158,0.0005234912,0.00077560416,0.0004689459,0.00076658855,0.00007582026],"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":[0.000012144914,0.000033056207,0.002980692,0.00000924825,0.000009403613,0.00001077923,0.000008678404,0.9933349,0.0011066749,0.0007934478,0.000065112676,0.0016357162],"study_design_scores_gemma":[0.000010111229,0.000011766774,0.0013459235,0.0000019091883,0.0000034556072,0.000003436926,0.0000034650184,0.9975231,0.00076880667,0.00023989196,0.00008331421,0.0000047026247],"about_ca_topic_score_codex":0.02928426,"about_ca_topic_score_gemma":0.015133678,"teacher_disagreement_score":0.02928426,"about_ca_system_score_codex":0.00074352464,"about_ca_system_score_gemma":0.0008792455,"threshold_uncertainty_score":0.05822766},"labels":[],"label_agreement":null},{"id":"W4220983646","doi":"10.1029/2021ms002679","title":"Less Surface Sea Ice Melt in the CESM2 Improves Arctic Sea Ice Simulation With Minimal Non‐Polar Climate Impacts","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":40,"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 Victoria","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canadian Meteorological and Oceanographic Society; National Science Foundation","keywords":"Sea ice; Ice-albedo feedback; Arctic ice pack; Climatology; Environmental science; Arctic sea ice decline; Cryosphere; Arctic geoengineering; Arctic; Climate model; Sea ice thickness; Sea ice concentration; Climate change; Global warming; Atmospheric sciences; Geology; Oceanography","score_opus":0.014361888991188686,"score_gpt":0.2458671178392776,"score_spread":0.2315052288480889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220983646","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9836393,0.00023810843,0.006407392,0.00047304254,0.00016858352,0.00005272829,0.0019745957,0.0007180152,0.0063281134],"genre_scores_gemma":[0.9911573,0.00008583985,0.0056306724,0.00014628054,0.000046733472,0.000048587062,0.001995193,0.00016108947,0.0007283602],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997646,0.000096442105,0.000014004389,0.00004226387,0.00003592934,0.00004669256],"domain_scores_gemma":[0.999559,0.00014584996,0.00004021192,0.000077372766,0.000104012135,0.00007359727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000846784,0.0011475404,0.00084474945,0.00030858305,0.000483263,0.0011079621,0.0011396147,0.0011707313,0.0017203433],"category_scores_gemma":[0.001755175,0.00038068663,0.0010881356,0.0004071555,0.00045102378,0.00082585466,0.0007669909,0.0009849286,0.00029272048],"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":[0.00032035678,0.00022288942,0.010758259,0.00006836067,0.00016815079,0.0000903084,0.00003736857,0.9787482,0.0036877606,0.0007240329,0.0017146057,0.0034597132],"study_design_scores_gemma":[0.00016228599,0.00009543641,0.0031657922,0.000009106931,0.000038857776,0.000008270205,0.00002703714,0.9944642,0.0010322093,0.00016360484,0.00081461517,0.000018476823],"about_ca_topic_score_codex":0.030636389,"about_ca_topic_score_gemma":0.024107393,"teacher_disagreement_score":0.030636389,"about_ca_system_score_codex":0.00054679427,"about_ca_system_score_gemma":0.0013930206,"threshold_uncertainty_score":0.060916126},"labels":[],"label_agreement":null},{"id":"W4225527198","doi":"10.1029/2021ms002946","title":"Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink?","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric and Environmental Gas Dynamics","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":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Biosphere; Environmental science; Terrestrial ecosystem; Benchmark (surveying); Carbon cycle; Residual; Boreal; Carbon sink; Global change; Biosphere model; Sink (geography); Climatology; Atmospheric sciences; Computer science; Ecosystem; Ecology; Climate change; Geography; Geology","score_opus":0.02295212139279979,"score_gpt":0.25543008905970066,"score_spread":0.23247796766690088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225527198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96363604,0.00072629977,0.026108589,0.0018194374,0.000121983554,0.00004975154,0.0018140404,0.00077563827,0.0049482533],"genre_scores_gemma":[0.9953135,0.0000824737,0.0032912632,0.00009231746,0.000020094521,0.000014867843,0.00089700485,0.000100931,0.00018753186],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982723,0.0009642773,0.00009615994,0.000257884,0.0002550035,0.00015438172],"domain_scores_gemma":[0.99316496,0.0034041142,0.0010249199,0.0008521948,0.0011416194,0.0004120479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005770477,0.0011413015,0.0010091182,0.0016036844,0.00055111723,0.0026696662,0.0011257951,0.001400083,0.0015558375],"category_scores_gemma":[0.025922239,0.00035444414,0.0008916135,0.0015814286,0.00060560106,0.0025080591,0.0010279714,0.00086253876,0.00049772963],"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":[0.00015102263,0.00007338535,0.06445841,0.0000498641,0.00028731665,0.00006872412,0.000044792963,0.92289174,0.0005543476,0.0021396272,0.0016866884,0.0075940182],"study_design_scores_gemma":[0.000024762365,0.000031271888,0.009856611,0.000019708174,0.000020716525,0.000014356733,0.00007146666,0.98440766,0.00033562258,0.0048348205,0.00036467932,0.000018340523],"about_ca_topic_score_codex":0.01855694,"about_ca_topic_score_gemma":0.013733767,"teacher_disagreement_score":0.01855694,"about_ca_system_score_codex":0.0012019761,"about_ca_system_score_gemma":0.0010597424,"threshold_uncertainty_score":0.036897898},"labels":[],"label_agreement":null},{"id":"W4226129163","doi":"10.1029/2021ms002852","title":"NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0: Stratospheric Composition","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":50,"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 Toronto","funders":"National Aeronautics and Space Administration","keywords":"Stratosphere; Troposphere; Polar vortex; Atmospheric sciences; Environmental science; Polar; Atmospheric chemistry; Meteorology; Climatology; Ozone layer; Forcing (mathematics); Total Ozone Mapping Spectrometer; Ozone; Physics; Geology","score_opus":0.015593863103853548,"score_gpt":0.22545900746498312,"score_spread":0.20986514436112957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226129163","genre_codex":"dataset","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03881646,0.00059865887,0.094964385,0.0016310548,0.0008214406,0.0004934478,0.7285676,0.07977082,0.05433619],"genre_scores_gemma":[0.2897635,0.0010424322,0.09689704,0.00065916445,0.00037812605,0.0010917627,0.58369935,0.009803293,0.016665388],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997751,0.000048580743,0.00001844339,0.000045347013,0.00007894906,0.000033596865],"domain_scores_gemma":[0.99965537,0.000046116696,0.000043637232,0.000074081625,0.00014643856,0.000034405777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000811122,0.0012374411,0.00067884877,0.0009935976,0.00044145258,0.0012081394,0.0013851699,0.0011910592,0.023883404],"category_scores_gemma":[0.0011606683,0.00062923157,0.0011007069,0.0016884201,0.0002010103,0.001234702,0.0006268668,0.0011789342,0.0102080135],"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":[0.0003023209,0.00012537086,0.01222604,0.0003592569,0.00022726369,0.00013295923,0.00016517483,0.4368838,0.0048537836,0.011399929,0.48912466,0.04419945],"study_design_scores_gemma":[0.0006065674,0.00006289605,0.010659026,0.00011141932,0.000095397656,0.000041361644,0.00008674963,0.7350518,0.0042995196,0.009258488,0.23960394,0.00012282125],"about_ca_topic_score_codex":0.05448377,"about_ca_topic_score_gemma":0.028596379,"teacher_disagreement_score":0.05448377,"about_ca_system_score_codex":0.00080334535,"about_ca_system_score_gemma":0.0015749976,"threshold_uncertainty_score":0.10833329},"labels":[],"label_agreement":null},{"id":"W4234619948","doi":"10.1002/(issn)1942-2466","title":"Journal of Advances in Modeling Earth Systems","year":2018,"lang":"en","type":"paratext","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":181,"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":"Office of Naval Research; Natural Environment Research Council; National Oceanic and Atmospheric Administration; NOAA Research; Stony Brook University; Ocean Frontier Institute; Climate Program Office; Dalhousie University; U.S. Department of Energy; European Commission; Biological and Environmental Research; Colorado State University; Oregon State University; U.S. Department of Commerce; Princeton University; Canada First Research Excellence Fund; National Aeronautics and Space Administration; National Science Foundation","keywords":"Permafrost; Plateau (mathematics); Earth system science; Environmental science; Soil science; Permeability (electromagnetism); Earth science; Water content; Geology; Atmospheric sciences; Chemistry; Geotechnical engineering; Mathematics","score_opus":0.04528126857569427,"score_gpt":0.29368487452199804,"score_spread":0.24840360594630378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234619948","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004198143,0.208904,0.056482922,0.071129374,0.12523192,0.00019884027,0.008279948,0.0026304773,0.52294445],"genre_scores_gemma":[0.06934069,0.31273887,0.04507049,0.007947242,0.050939444,0.00024952338,0.012443955,0.0038816107,0.49738812],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99811894,0.00032977632,0.00021859918,0.00019608041,0.0010642356,0.000072384435],"domain_scores_gemma":[0.99068356,0.0038662958,0.0004697616,0.0016059054,0.0024769793,0.0008974476],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002832057,0.0008885548,0.0009354598,0.0021561699,0.0008600561,0.005702102,0.001083164,0.0012522062,0.08788673],"category_scores_gemma":[0.014459196,0.00034921546,0.0005763906,0.003743919,0.001126495,0.004081577,0.0021629415,0.0033737493,0.027093483],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034370893,0.00007918793,0.0007525902,0.00082110235,0.00005689481,0.00006791381,0.0001113067,0.002317949,0.0003718605,0.072838455,0.7250386,0.1975098],"study_design_scores_gemma":[0.000004671943,0.00001031768,0.0003645786,0.00022572635,0.000011882216,0.00005225648,0.000039736973,0.0012396411,0.00012789849,0.018716197,0.9792002,0.0000071254653],"about_ca_topic_score_codex":0.0025701846,"about_ca_topic_score_gemma":0.0025701185,"teacher_disagreement_score":0.91211325,"about_ca_system_score_codex":0.001135523,"about_ca_system_score_gemma":0.0043429015,"threshold_uncertainty_score":0.2940104},"labels":[],"label_agreement":null},{"id":"W4281732312","doi":"10.1029/2021ms002836","title":"Toward Efficient Calibration of Higher‐Resolution Earth System Models","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":10,"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 Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Microsoft","keywords":"Computer science; Calibration; Resolution (logic); Convolutional neural network; Process (computing); Baseline (sea); Algorithm; Earth system science; Machine learning; Artificial intelligence; Mathematics; Statistics; Geology","score_opus":0.031236609410208588,"score_gpt":0.2515298965500946,"score_spread":0.22029328713988602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281732312","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20178935,0.00014330805,0.7900801,0.0006180446,0.000096986674,0.0000772682,0.0005077665,0.0029925515,0.0036946365],"genre_scores_gemma":[0.8340864,0.00006516159,0.16423914,0.00011877571,0.000023512082,0.000102126185,0.0005733605,0.00020247808,0.0005891192],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999416,0.00024565833,0.000031068594,0.000115315655,0.00014802333,0.0000439804],"domain_scores_gemma":[0.99801683,0.0006815024,0.00018224413,0.0005512972,0.00049560214,0.0000724427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027678076,0.0006543538,0.0005322838,0.00053645583,0.00029094977,0.0009066879,0.0013491522,0.0011167825,0.0015602917],"category_scores_gemma":[0.009127052,0.0006630408,0.00055962877,0.0005111169,0.0005257597,0.0018575664,0.0012642557,0.0022036529,0.00043339902],"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":[0.000015880398,0.000022561642,0.0012804307,0.000008616057,0.000026548185,0.000012868446,0.000015328043,0.9891639,0.0014835255,0.0019959356,0.0002571165,0.0057173385],"study_design_scores_gemma":[0.000002567721,0.0000022029358,0.00020712892,0.0000019275885,0.0000013073814,0.0000013894445,0.0000019250058,0.99833256,0.00061688427,0.00068741274,0.00014236997,0.000002320026],"about_ca_topic_score_codex":0.008815132,"about_ca_topic_score_gemma":0.006141621,"teacher_disagreement_score":0.008815132,"about_ca_system_score_codex":0.0011573711,"about_ca_system_score_gemma":0.0012316328,"threshold_uncertainty_score":0.01752764},"labels":[],"label_agreement":null},{"id":"W4282583373","doi":"10.1029/2022ms003008","title":"Matrix Approach to Land Carbon Cycle Modeling","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","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":"Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Carbon cycle; Carbon sink; Environmental science; Carbon sequestration; Ecosystem model; Carbon fibers; Climate change; Biome; Ecosystem; Atmospheric sciences; Computer science; Ecology; Carbon dioxide; Algorithm; Physics","score_opus":0.00963501888212513,"score_gpt":0.22840840612049818,"score_spread":0.21877338723837306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282583373","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0084262425,0.00048816594,0.97676146,0.0008268813,0.00016089287,0.0000632116,0.0007000702,0.0004524694,0.012120678],"genre_scores_gemma":[0.5659099,0.0019443136,0.4131454,0.0002970581,0.0003341115,0.0005112859,0.0011991496,0.0003728389,0.016285842],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960786,0.0001631316,0.00002289763,0.00006805131,0.00010761876,0.000030449233],"domain_scores_gemma":[0.999137,0.00043901353,0.00007926279,0.000065519365,0.00022466434,0.00005465271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006681484,0.00068003056,0.0006623378,0.0007434591,0.00066473614,0.00165008,0.0014869488,0.0009448828,0.0063798516],"category_scores_gemma":[0.0021351948,0.00040323316,0.0009240769,0.0014044858,0.0006041166,0.0014509114,0.0012653611,0.0016442084,0.00089005847],"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":[0.000010289877,0.000015414236,0.00032020485,0.000039990256,0.000027461716,0.000049011902,0.00003612605,0.89613974,0.0003686256,0.09160186,0.0016693973,0.009721828],"study_design_scores_gemma":[0.0000025192558,0.0000043468976,0.000032884855,0.0000044028166,0.0000028847594,0.0000050955923,0.000007789616,0.9681018,0.00006288585,0.02908091,0.002690926,0.0000035644214],"about_ca_topic_score_codex":0.02554924,"about_ca_topic_score_gemma":0.020021364,"teacher_disagreement_score":0.02554924,"about_ca_system_score_codex":0.0013578959,"about_ca_system_score_gemma":0.001371238,"threshold_uncertainty_score":0.05080104},"labels":[],"label_agreement":null},{"id":"W4283579720","doi":"10.1029/2021ms002855","title":"Identification and Regionalization of Streamflow Routing Parameters Using Machine Learning for the HLM Hydrological Model in Iowa","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":10,"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; University of Manitoba","funders":"Mid-America Transportation Center, University of Nebraska-Lincoln","keywords":"Routing (electronic design automation); Streamflow; Computer science; Benchmark (surveying); Interpolation (computer graphics); Flood control; Random forest; Flood forecasting; Hydrology (agriculture); Environmental science; Meteorology; Flood myth; Machine learning; Artificial intelligence; Geology; Geography; Cartography; Drainage basin","score_opus":0.032007880883637,"score_gpt":0.26820179751673723,"score_spread":0.23619391663310024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283579720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9830031,0.000019532377,0.015811823,0.00009515441,0.000005076158,0.000017797329,0.00024577448,0.00011153339,0.000690335],"genre_scores_gemma":[0.99419373,0.000007842006,0.0054658675,0.000007983637,0.0000019734202,0.00001555502,0.00018209136,0.000008192856,0.00011673756],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983525,0.00006416066,0.00000807761,0.000052179763,0.000015530524,0.000024797644],"domain_scores_gemma":[0.9992207,0.00044359028,0.0000923572,0.00007849466,0.00013021186,0.00003463854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076487154,0.00032723063,0.00030509228,0.00034734712,0.00027732912,0.0004894945,0.0005993522,0.00057675684,0.0005510542],"category_scores_gemma":[0.0026202244,0.0002735954,0.00044679915,0.00029392602,0.00031899186,0.00050047564,0.00039361892,0.0005135826,0.00006906793],"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":[0.0000354056,0.000034718538,0.019215066,0.000005747397,0.000020294356,0.000030229101,0.000021501815,0.97609794,0.000901571,0.0003115156,0.000119529344,0.0032065061],"study_design_scores_gemma":[0.000009095094,0.000008063504,0.0023712637,0.0000014754976,0.000004292553,0.0000027499595,0.000013212288,0.99717003,0.00026550904,0.00010894951,0.000041627172,0.0000038103967],"about_ca_topic_score_codex":0.078379214,"about_ca_topic_score_gemma":0.074774906,"teacher_disagreement_score":0.078379214,"about_ca_system_score_codex":0.0011123907,"about_ca_system_score_gemma":0.0009257341,"threshold_uncertainty_score":0.155846},"labels":[],"label_agreement":null},{"id":"W4285591523","doi":"10.1029/2021ms002893","title":"Constraining Clouds and Convective Parameterizations in a Climate Model Using Paleoclimate Data","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"National Science Foundation","keywords":"Climate sensitivity; Paleoclimatology; Climatology; Climate model; Last Glacial Maximum; Forcing (mathematics); Environmental science; Precipitation; Atmospheric sciences; Meteorology; Holocene; Geology; Climate change; Geography","score_opus":0.0840648819260655,"score_gpt":0.3233345291983867,"score_spread":0.2392696472723212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285591523","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99103844,0.0000687403,0.0072434414,0.00015519302,0.000022895118,0.000023773035,0.0004004107,0.00014758305,0.00089950796],"genre_scores_gemma":[0.9954607,0.000025005296,0.004101643,0.00003311697,0.0000059636673,0.000018939036,0.00025162427,0.000017749175,0.00008537367],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972504,0.0001117469,0.000018730143,0.000081744394,0.000029906289,0.000032849548],"domain_scores_gemma":[0.999089,0.00045405483,0.00010013791,0.00017620028,0.00011559818,0.0000648929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012071203,0.0006737011,0.00040823125,0.00030610268,0.0005366719,0.0009790629,0.00079934025,0.0008454867,0.0005611711],"category_scores_gemma":[0.0032538131,0.0005309514,0.00060749665,0.0004167306,0.00045887902,0.0011726749,0.0005861388,0.00090746366,0.000084498315],"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":[0.00012126404,0.000104014645,0.018480787,0.000012687539,0.00008814611,0.000024305713,0.000025273606,0.97603023,0.0019020305,0.00035467505,0.00012298714,0.002733599],"study_design_scores_gemma":[0.000056373134,0.000030458337,0.003026708,0.000002813897,0.000018818095,0.000004214426,0.000012338054,0.99517655,0.0012335161,0.00025863474,0.00016891203,0.0000106628395],"about_ca_topic_score_codex":0.038691983,"about_ca_topic_score_gemma":0.021446781,"teacher_disagreement_score":0.038691983,"about_ca_system_score_codex":0.00082227006,"about_ca_system_score_gemma":0.0010761751,"threshold_uncertainty_score":0.07693356},"labels":[],"label_agreement":null},{"id":"W4293201966","doi":"10.1029/2022ms003117","title":"Reconciling and Improving Formulations for Thermodynamics and Conservation Principles in Earth System Models (ESMs)","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; Deutsche Forschungsgemeinschaft; Compute Canada; Office of Science; Norges Forskningsråd; ASCRS Research Foundation; National Science Foundation","keywords":"Spurious relationship; Dissipation; Earth system science; Statistical physics; Computer science; Physics; Thermodynamics; Applied mathematics; Mathematics; Geology","score_opus":0.03587513845074721,"score_gpt":0.2531955397273275,"score_spread":0.21732040127658028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293201966","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08745096,0.0012908634,0.9023725,0.002430848,0.0002523627,0.000120704244,0.0002555321,0.00051254313,0.0053138137],"genre_scores_gemma":[0.71948534,0.0009980365,0.27583963,0.00050400425,0.00029403227,0.00029791216,0.00034047925,0.0005037959,0.0017367214],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99703634,0.0017923552,0.0001883805,0.0001721108,0.00068177824,0.00012909007],"domain_scores_gemma":[0.9963905,0.0016461472,0.00049448037,0.0009077945,0.00044862393,0.000112442045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006107439,0.0008687066,0.0013161352,0.0007604423,0.00060007867,0.0020716498,0.0019536985,0.0011088996,0.0010735512],"category_scores_gemma":[0.018015858,0.00064796366,0.0009777336,0.0007693377,0.0014010152,0.003781137,0.0036880858,0.001851594,0.00023444275],"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":[0.000036897494,0.00008152091,0.0018926681,0.0001078184,0.000103005215,0.00007775799,0.00013438181,0.7707368,0.0016642762,0.2000311,0.0010548157,0.024078995],"study_design_scores_gemma":[0.000013044653,0.00002955095,0.0003466095,0.000021973181,0.000013640688,0.000011070874,0.000030068139,0.93147886,0.0005446268,0.0657844,0.0017116511,0.000014407932],"about_ca_topic_score_codex":0.00439296,"about_ca_topic_score_gemma":0.004661889,"teacher_disagreement_score":0.006107439,"about_ca_system_score_codex":0.0013372971,"about_ca_system_score_gemma":0.0022579846,"threshold_uncertainty_score":0.03229958},"labels":[],"label_agreement":null},{"id":"W4302362705","doi":"10.1029/2022ms003259","title":"An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Natural Environment Research Council; Sight Research UK","keywords":"Data assimilation; Exploit; Context (archaeology); Environmental science; Earth observation; Earth system science; Satellite; Land use; Computer science; Vegetation (pathology); Remote sensing; Environmental resource management; Climate change; Variety (cybernetics); Meteorology; Geography; Geology; Ecology","score_opus":0.11594751536670944,"score_gpt":0.3000243146342332,"score_spread":0.18407679926752374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302362705","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013759241,0.050193116,0.08345087,0.8144241,0.011160689,0.00034591582,0.002030917,0.0011465142,0.023488646],"genre_scores_gemma":[0.3104864,0.0776696,0.46829334,0.10874333,0.010298992,0.0015550758,0.0067310254,0.0005895555,0.01563262],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99421823,0.003000395,0.00034767637,0.000387107,0.0012531817,0.0007934058],"domain_scores_gemma":[0.9697613,0.013747523,0.0012721712,0.0016003157,0.008307544,0.0053110407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020882986,0.0008851734,0.0013061746,0.0013756178,0.0021175826,0.007892533,0.002700258,0.009437573,0.011913866],"category_scores_gemma":[0.02255356,0.0005652576,0.0008013814,0.00166795,0.0024700994,0.012364717,0.007248524,0.009210484,0.0028238974],"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":[0.00050030375,0.00069217116,0.005750001,0.0031369599,0.00013048993,0.0004645823,0.0015847997,0.01915025,0.007720597,0.28659326,0.32494703,0.34932965],"study_design_scores_gemma":[0.00010865494,0.00046338182,0.003487823,0.002885232,0.00007864924,0.00019828668,0.0066986163,0.048393484,0.002937375,0.2629396,0.671617,0.00019194648],"about_ca_topic_score_codex":0.0071951095,"about_ca_topic_score_gemma":0.006272785,"teacher_disagreement_score":0.020882986,"about_ca_system_score_codex":0.002363432,"about_ca_system_score_gemma":0.01955515,"threshold_uncertainty_score":0.11044109},"labels":[],"label_agreement":null},{"id":"W4309293790","doi":"10.1029/2022ms003106","title":"On Oceanic Initial State Errors in the Ensemble Data Assimilation for a Coupled General Circulation Model","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","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":"University of Northern British Columbia","funders":"National Natural Science Foundation of China","keywords":"Data assimilation; Assimilation (phonology); Computer science; General Circulation Model; Environmental science; Climatology; Meteorology; Geology; Climate change","score_opus":0.09778098915146852,"score_gpt":0.3199005081083256,"score_spread":0.22211951895685708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309293790","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8065165,0.0005582725,0.18929543,0.00037841042,0.00012576151,0.000040942326,0.000328444,0.00022674538,0.0025294658],"genre_scores_gemma":[0.98795146,0.00012664296,0.011415527,0.000027979699,0.000011942422,0.000014418725,0.00021632784,0.000026728681,0.00020900632],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955434,0.00018874317,0.000032519667,0.00006901058,0.000112445065,0.000042896096],"domain_scores_gemma":[0.9982668,0.0008472094,0.00016331066,0.00013773702,0.0005455429,0.00003940823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022824828,0.00046519356,0.0004329246,0.00035972925,0.0005120621,0.0006973861,0.0003280265,0.0004457437,0.0003056256],"category_scores_gemma":[0.0075363377,0.00025663694,0.0003779309,0.00042210412,0.00031200514,0.0009655562,0.000619224,0.0007795235,0.000058813333],"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":[0.00013525387,0.000041358737,0.017585967,0.000050624756,0.00010158828,0.00006816959,0.000088785775,0.94842815,0.005614097,0.0021494643,0.00045545906,0.025281087],"study_design_scores_gemma":[0.000006141898,0.000013932731,0.0036245082,0.000007994091,0.00001627223,0.000003478041,0.000012216998,0.99414164,0.0016700616,0.0003445978,0.00015091685,0.00000823892],"about_ca_topic_score_codex":0.043584913,"about_ca_topic_score_gemma":0.024996568,"teacher_disagreement_score":0.043584913,"about_ca_system_score_codex":0.00058400637,"about_ca_system_score_gemma":0.0011603881,"threshold_uncertainty_score":0.08666241},"labels":[],"label_agreement":null},{"id":"W4309722193","doi":"10.1029/2022ms003180","title":"Simple Hybrid Sea Ice Nudging Method for Improving Control Over Partitioning of Sea Ice Concentration and Thickness","year":2022,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","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":false,"ca_institutions":"University of Toronto","funders":"Government of Ontario; U.S. Department of Energy","keywords":"Sea ice; Environmental science; Sea ice concentration; Sea ice thickness; Climatology; Polar; Climate model; Atmosphere (unit); Flux (metallurgy); Sea ice growth processes; Lead (geology); Troposphere; Arctic ice pack; Atmospheric sciences; Geology; Meteorology; Climate change; Oceanography; Chemistry; Geomorphology","score_opus":0.011165925652043997,"score_gpt":0.25876690128055724,"score_spread":0.24760097562851324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309722193","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.070574775,0.00014661626,0.92711514,0.000048476577,0.000045999193,0.000040457526,0.00011128309,0.0010004614,0.00091678667],"genre_scores_gemma":[0.3589499,0.00007548981,0.6389842,0.000051712468,0.00001887526,0.00009077647,0.00029275127,0.00026726554,0.001269079],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997489,0.0000715926,0.000022195321,0.00007559457,0.00005915028,0.000022590259],"domain_scores_gemma":[0.9987469,0.0005839959,0.00012371525,0.00026398702,0.00021585378,0.00006561732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009691853,0.00068246253,0.0005173158,0.00059483305,0.00031476517,0.0005677912,0.00092601293,0.00049629627,0.0011113124],"category_scores_gemma":[0.0029117034,0.00032298197,0.0003111983,0.00030329477,0.000408627,0.000762158,0.000698486,0.00053931534,0.0002654471],"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":[0.0006509891,0.00017554995,0.00878493,0.00018999678,0.00011714429,0.0001734058,0.00024537306,0.50776756,0.10356706,0.008878018,0.0020398486,0.36741012],"study_design_scores_gemma":[0.00002025742,0.000030279158,0.0006386694,0.0000063359826,0.000007878358,0.000021527461,0.000007497505,0.9855254,0.011821533,0.00085229566,0.0010525355,0.00001570059],"about_ca_topic_score_codex":0.0029696147,"about_ca_topic_score_gemma":0.0044308025,"teacher_disagreement_score":0.0029696147,"about_ca_system_score_codex":0.00045453294,"about_ca_system_score_gemma":0.00052871794,"threshold_uncertainty_score":0.0059046745},"labels":[],"label_agreement":null},{"id":"W4323662617","doi":"10.1029/2022ms003013","title":"Challenges in Hydrologic‐Land Surface Modeling of Permafrost Signatures—A Canadian Perspective","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","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":"Global Institute for Water Security; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada; University of Saskatchewan","keywords":"Permafrost; Forcing (mathematics); Environmental science; Surface runoff; Climatology; Radiative forcing; Identifiability; Climate model; Climate change; Computer science; Meteorology; Geology; Geography","score_opus":0.08101649676901311,"score_gpt":0.28675445640530567,"score_spread":0.20573795963629254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323662617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75656176,0.0051243003,0.144597,0.015659727,0.00017070268,0.00039660334,0.0094522955,0.0012387628,0.06679883],"genre_scores_gemma":[0.9715195,0.0014418748,0.023258355,0.00016582997,0.000018245326,0.000043983586,0.0006923619,0.00007023397,0.0027896161],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995579,0.00008205139,0.000018735142,0.00007688486,0.00017690392,0.00008749182],"domain_scores_gemma":[0.99933416,0.00014984063,0.000039177536,0.00004168928,0.00037957597,0.000055499546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009851927,0.00066566997,0.00050190766,0.0009986265,0.0016735283,0.0020025908,0.0019803264,0.00074531237,0.0012931937],"category_scores_gemma":[0.00229864,0.00031208873,0.00065266376,0.0019705577,0.0010956028,0.00089617644,0.0007921359,0.00077507336,0.00010790221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046728215,0.000039566905,0.014849085,0.000066832894,0.00006205893,0.00007770575,0.000097627,0.9458167,0.002113292,0.0137448795,0.0017273447,0.021358185],"study_design_scores_gemma":[0.000014810983,0.000012288225,0.009592516,0.000018438563,0.000023305458,0.000011337351,0.0001753454,0.9816234,0.00068259914,0.0029553045,0.0048559937,0.000034709734],"about_ca_topic_score_codex":0.9887317,"about_ca_topic_score_gemma":0.98286945,"teacher_disagreement_score":0.019944139,"about_ca_system_score_codex":0.019944139,"about_ca_system_score_gemma":0.030837344,"threshold_uncertainty_score":0.14470553},"labels":[],"label_agreement":null},{"id":"W4360613429","doi":"10.1029/2022ms003563","title":"Global Surface Ocean Acidification Indicators From 1750 to 2100","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Ocean Acidification Effects and Responses","field":"Earth and Planetary Sciences","cited_by":101,"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 Victoria","funders":"Global Ocean Monitoring and Observing Program; Natural Environment Research Council; Norges Forskningsråd; Sight Research UK","keywords":"Environmental science; Earth system science; Ocean acidification; Coupled model intercomparison project; Metadata; Data assimilation; Climatology; NetCDF; Global change; Climate change; Climate model; Meteorology; Oceanography; Geology; Geography; Computer science","score_opus":0.015728499781778336,"score_gpt":0.2676879178327238,"score_spread":0.25195941805094546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360613429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.861639,0.0024003068,0.00387355,0.00074255426,0.0003098686,0.000049684546,0.109686196,0.0005459078,0.020752916],"genre_scores_gemma":[0.9124647,0.0011415307,0.0045171026,0.00014477427,0.00005879258,0.000042509848,0.0806115,0.000024902012,0.0009941469],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998141,0.000017379198,0.000018886181,0.000044962842,0.000073913696,0.000030842155],"domain_scores_gemma":[0.9996836,0.000017855076,0.000082863546,0.00002000244,0.00016051864,0.000035158748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042935007,0.00046113026,0.00013415086,0.0018471201,0.00014991571,0.0006188461,0.00017422973,0.00015467293,0.00061840593],"category_scores_gemma":[0.00083806284,0.00009115341,0.0003972792,0.0024844678,0.0001537731,0.0005345746,0.0007716755,0.00027692146,0.00018368928],"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":[0.00022862668,0.000058511043,0.87069046,0.00035451417,0.0005774164,0.00021114609,0.00023854354,0.02918951,0.0029072887,0.002460938,0.021172088,0.071910955],"study_design_scores_gemma":[0.000014249084,0.000100277735,0.9367787,0.000098686265,0.00012485372,0.00014984503,0.0002610467,0.0068620257,0.002137948,0.0008867008,0.052550144,0.000035461962],"about_ca_topic_score_codex":0.043573316,"about_ca_topic_score_gemma":0.03684164,"teacher_disagreement_score":0.043573316,"about_ca_system_score_codex":0.0011080407,"about_ca_system_score_gemma":0.0008348743,"threshold_uncertainty_score":0.086639404},"labels":[],"label_agreement":null},{"id":"W4364375617","doi":"10.1029/2023ms003741","title":"Aims and Scope of <i>JAMES</i>","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Scientific Computing and Data Management","field":"Decision 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":false,"ca_institutions":"Western University","funders":"","keywords":"Scope (computer science); Earth system science; Publication; Atmosphere (unit); Computer science; Astrobiology; Earth science; Cryosphere; Engineering ethics; Political science; Meteorology; Geology; Engineering; Geography; Oceanography; Law; Physics","score_opus":0.1175104141919884,"score_gpt":0.4006383651332537,"score_spread":0.2831279509412653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4364375617","genre_codex":"commentary","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014754675,0.014633917,0.002481979,0.49975348,0.45112303,0.0003737788,0.0004967065,0.00028013138,0.02938158],"genre_scores_gemma":[0.02848476,0.017868547,0.0058461563,0.3012336,0.56017256,0.00094357884,0.0005013343,0.00085933134,0.08409015],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9856309,0.002663911,0.0011073889,0.002153149,0.006831088,0.0016135502],"domain_scores_gemma":[0.90073365,0.022487527,0.0058817905,0.0033757992,0.042957168,0.024564063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.037019875,0.0012019137,0.0012400475,0.0034805422,0.0034974555,0.02008909,0.003109388,0.011275936,0.009476202],"category_scores_gemma":[0.070203915,0.00046881184,0.0009016542,0.0015094782,0.0055693174,0.005832463,0.007822751,0.010039318,0.007587557],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000091864466,0.000036114063,0.00021146839,0.00040280717,0.000012222922,0.0001186746,0.00036007888,0.00012402666,0.0006355679,0.020737274,0.96123064,0.016039327],"study_design_scores_gemma":[0.000017574683,0.000049552695,0.00054178154,0.00093856885,0.000011889801,0.000106263695,0.0002931442,0.00014904414,0.00059952284,0.0054955212,0.99175996,0.000037079255],"about_ca_topic_score_codex":0.0021896544,"about_ca_topic_score_gemma":0.0018101896,"teacher_disagreement_score":0.037019875,"about_ca_system_score_codex":0.0051084845,"about_ca_system_score_gemma":0.01377865,"threshold_uncertainty_score":0.19578218},"labels":[],"label_agreement":null},{"id":"W4365450664","doi":"10.1029/2022ms003480","title":"Evaluating the Performance of the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) Tailored to the Pan‐Canadian Domain","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal; Carleton University; Environment and Climate Change Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biogeochemical cycle; Tundra; Environmental science; Boreal; Carbon cycle; Land cover; Terrestrial ecosystem; Taiga; Permafrost; Vegetation (pathology); Global change; Peat; Climatology; Climate change; Plant functional type; Benchmark (surveying); Climate model; Physical geography; Ecosystem; Land use; Ecology; Geography; Forestry; Geology","score_opus":0.0990068252800463,"score_gpt":0.3197943272598065,"score_spread":0.22078750197976021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365450664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9784102,0.00018350438,0.0054265857,0.00031206722,0.00006651109,0.00010643708,0.0070136925,0.0015064315,0.006974642],"genre_scores_gemma":[0.98712885,0.000058303445,0.0065554767,0.00008569561,0.000009084368,0.000021981667,0.0053669997,0.00007026141,0.00070333184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993723,0.00010233799,0.000034245215,0.00016175961,0.00019622443,0.00013324777],"domain_scores_gemma":[0.99793917,0.0003061277,0.00010495429,0.00023521822,0.0011973651,0.00021719343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016374999,0.0010810029,0.00045118376,0.0007271909,0.0008407143,0.0010177454,0.0016471792,0.0006067144,0.0014788643],"category_scores_gemma":[0.003631055,0.00024647595,0.0006812091,0.0014495731,0.00067359774,0.00078053144,0.00078807364,0.00055095233,0.00022330029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037702452,0.00012071873,0.06718207,0.00008436653,0.00019179982,0.00006209749,0.00007150787,0.90014887,0.0023484102,0.0011145015,0.004263615,0.02403505],"study_design_scores_gemma":[0.00010976886,0.00008793601,0.03653142,0.000014399598,0.000048932932,0.000014678186,0.00010555643,0.95794725,0.0023231632,0.0003350516,0.0024324898,0.000049293212],"about_ca_topic_score_codex":0.95227224,"about_ca_topic_score_gemma":0.9201613,"teacher_disagreement_score":0.047727764,"about_ca_system_score_codex":0.009418842,"about_ca_system_score_gemma":0.00925658,"threshold_uncertainty_score":0.09601766},"labels":[],"label_agreement":null},{"id":"W4366588782","doi":"10.1029/2022ms003328","title":"Combining Triple‐Moment Ice With Prognostic Liquid Fraction in the P3 Microphysics Scheme: Impacts on a Simulated Squall Line","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":30,"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":"Squall line; Sublimation (psychology); Ice crystals; Ice cloud; Materials science; Mechanics; Atmospheric sciences; Environmental science; Geology; Meteorology; Mesoscale meteorology; Physics; Radiative transfer; Optics","score_opus":0.037393269890042886,"score_gpt":0.2844827095826667,"score_spread":0.2470894396926238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366588782","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9859708,0.00006933505,0.009528567,0.00017781524,0.000064323984,0.000043021482,0.0003922169,0.0006219824,0.00313191],"genre_scores_gemma":[0.9954691,0.000017026241,0.003893027,0.000029029976,0.000006540213,0.000019247831,0.00020965347,0.000051695493,0.00030478055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998264,0.000058442776,0.000009560231,0.000025425212,0.00003745031,0.00004280706],"domain_scores_gemma":[0.9993524,0.00023471266,0.00006508883,0.000074416275,0.0001280349,0.00014533571],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005686588,0.0008112913,0.0006252129,0.0003196802,0.0004587032,0.00074215134,0.0011617729,0.0010376445,0.001542396],"category_scores_gemma":[0.0013715958,0.00024317582,0.0006284452,0.00033704084,0.0005297016,0.00047925542,0.00070021045,0.0007005706,0.00016640173],"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":[0.00036584603,0.00019139843,0.010630625,0.000039503702,0.00006868189,0.00019914648,0.00005132197,0.97461504,0.008059198,0.00073443464,0.0004226422,0.004622104],"study_design_scores_gemma":[0.000048719376,0.00009235531,0.0011590443,0.0000031966474,0.000009098346,0.000008245327,0.000013032704,0.99693215,0.0014844124,0.00009654821,0.00014416515,0.000008987811],"about_ca_topic_score_codex":0.027855378,"about_ca_topic_score_gemma":0.011142984,"teacher_disagreement_score":0.027855378,"about_ca_system_score_codex":0.00065166404,"about_ca_system_score_gemma":0.00075493247,"threshold_uncertainty_score":0.055386484},"labels":[],"label_agreement":null},{"id":"W4372271505","doi":"10.1029/2022ms003419","title":"Optimized Alternate Mapping Correlated K‐Distribution Method for Atmospheric Longwave Radiative Transfer","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric and Environmental Gas Dynamics","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":"Environment and Climate Change Canada","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Longwave; Radiative transfer; Infrared window; Atmospheric radiative transfer codes; Computational physics; Transmittance; Environmental science; Radiative flux; Absorption (acoustics); Stratopause; Parametrization (atmospheric modeling); Atmospheric model; Atmospheric sciences; Infrared; Physics; Meteorology; Optics; Mesosphere; Stratosphere","score_opus":0.013963016939916818,"score_gpt":0.2604260092787585,"score_spread":0.24646299233884167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4372271505","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023496212,0.0001237156,0.97336924,0.000080428836,0.000035427674,0.000052675237,0.00008790361,0.00067442365,0.0020799255],"genre_scores_gemma":[0.42814687,0.00013089705,0.5673514,0.00010935325,0.000029006802,0.00035355808,0.0003489676,0.0004866134,0.0030432404],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997793,0.00009180737,0.000010165973,0.000028349692,0.00006198292,0.000028426768],"domain_scores_gemma":[0.9994578,0.00025363406,0.000044501576,0.000056381374,0.00015110167,0.000036586312],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052074704,0.00071028684,0.0007014805,0.00038224945,0.0004760691,0.000499337,0.0014323661,0.00075687986,0.0030292745],"category_scores_gemma":[0.0012759137,0.00031524542,0.00056862575,0.00054702914,0.0004470972,0.0008032167,0.0008030893,0.00097335083,0.00071436464],"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":[0.00010244561,0.000095470954,0.0011577392,0.00006933873,0.000040534196,0.00008914246,0.000054338758,0.93249786,0.0049160337,0.011742306,0.0015092265,0.047725488],"study_design_scores_gemma":[0.0000050472377,0.0000028306442,0.000024677161,8.2196823e-7,6.760642e-7,0.0000024869842,0.0000018311325,0.9991842,0.00018025372,0.00045375025,0.00014159197,0.0000017405879],"about_ca_topic_score_codex":0.008801482,"about_ca_topic_score_gemma":0.007257646,"teacher_disagreement_score":0.008801482,"about_ca_system_score_codex":0.00067237817,"about_ca_system_score_gemma":0.0017831858,"threshold_uncertainty_score":0.01750052},"labels":[],"label_agreement":null},{"id":"W4376113939","doi":"10.1029/2023ms003785","title":"Thank You to Our 2022 Peer Reviewers","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Geological Modeling and Analysis","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":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Work (physics); Data science; Peer review; Earth system science; Library science; Political science; Engineering; Geology; Oceanography","score_opus":0.036871483976134364,"score_gpt":0.2888654818134494,"score_spread":0.251993997837315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376113939","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":"evaluation","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":"evaluation","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007920021,0.009368648,0.00576548,0.22672202,0.7266459,0.0008185749,0.0022970862,0.0035599857,0.024030212],"genre_scores_gemma":[0.012053671,0.0107721565,0.014231103,0.13192736,0.37956554,0.0019271496,0.004013594,0.005579924,0.43992957],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9708527,0.0066898256,0.002638799,0.003779413,0.014688152,0.0013512274],"domain_scores_gemma":[0.48249578,0.01167985,0.01022616,0.009103637,0.46079713,0.025697464],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.021333432,0.0021290842,0.002824593,0.0054466887,0.005393065,0.01855114,0.0030445086,0.0063179047,0.15417314],"category_scores_gemma":[0.19924173,0.0011808674,0.0016595955,0.003175403,0.0017071366,0.0080283675,0.004563054,0.007208529,0.24628845],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012628315,0.0000041772,0.000118906544,0.00005133961,0.0000045106594,0.00003508551,0.000035864898,0.000011820549,0.000061287225,0.00014483675,0.99024665,0.009272907],"study_design_scores_gemma":[0.0000140663215,0.000011193942,0.0003098356,0.00012408095,0.000009720068,0.00013650153,0.00022899354,0.000080566104,0.000085683525,0.000533917,0.9984326,0.0000328226],"about_ca_topic_score_codex":0.004358364,"about_ca_topic_score_gemma":0.008754773,"teacher_disagreement_score":0.97866654,"about_ca_system_score_codex":0.0030158642,"about_ca_system_score_gemma":0.010149427,"threshold_uncertainty_score":0.51576054},"labels":[],"label_agreement":null},{"id":"W4377023492","doi":"10.1029/2022ms003397","title":"Uncertainty and Emergent Constraints on Enhanced Ecosystem Carbon Stock by Land Greening","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":23,"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":"Biome; Environmental science; Ecosystem; Carbon stock; Stock (firearms); Leaf area index; Greening; Primary production; Ecosystem services; Terrestrial ecosystem; Greenhouse gas; Atmospheric sciences; Climate change; Ecology; Geography","score_opus":0.011062398382073135,"score_gpt":0.24058560828233116,"score_spread":0.22952320990025804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377023492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9957736,0.00003896412,0.0033779761,0.00006054619,0.0000018902062,0.000002061933,0.00018048502,0.000021683776,0.0005428506],"genre_scores_gemma":[0.9997004,0.000009665554,0.00021914148,0.000005431843,7.14151e-7,8.617091e-7,0.000043186803,0.0000031209586,0.00001751104],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977154,0.00007764641,0.000015039887,0.000064824795,0.000031838226,0.00003921214],"domain_scores_gemma":[0.9979226,0.0013596351,0.0002923863,0.00026056962,0.00010119432,0.00006355169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010022909,0.0003106437,0.00033191752,0.0003348438,0.00017544403,0.0008316546,0.00033894306,0.00028631446,0.00065774797],"category_scores_gemma":[0.0037868426,0.0002216031,0.0003929692,0.0003349255,0.00057426677,0.0008450102,0.00064104423,0.00037791632,0.00003044527],"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":[0.00012132591,0.00004363627,0.19299412,0.000051421786,0.00029189378,0.0002952295,0.00010257886,0.786501,0.009264713,0.0050377594,0.000227008,0.0050692856],"study_design_scores_gemma":[0.000014912839,0.000041405438,0.13097234,0.000014750841,0.000058572066,0.00006515257,0.00010461205,0.85471255,0.002938036,0.010783871,0.00026506672,0.000028687986],"about_ca_topic_score_codex":0.008545987,"about_ca_topic_score_gemma":0.0067236386,"teacher_disagreement_score":0.008545987,"about_ca_system_score_codex":0.00066984026,"about_ca_system_score_gemma":0.00029943502,"threshold_uncertainty_score":0.01699251},"labels":[],"label_agreement":null},{"id":"W4378575664","doi":"10.1029/2023ms003751","title":"Representing Eddy Diffusion in the Surface Boundary Layer of Ocean Models With General Vertical Coordinates","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Oceanographic and Atmospheric Processes","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":"Hewlett-Packard (Canada)","funders":"National Science Foundation","keywords":"Mesoscale meteorology; Geology; Advection; Boundary current; Ocean general circulation model; Ocean current; Stratification (seeds); Eddy; Boundary layer; Geophysics; Mechanics; Meteorology; Turbulence; Climatology; Physics; Oceanography","score_opus":0.01995836263145851,"score_gpt":0.24617017652098985,"score_spread":0.22621181388953135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378575664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7339839,0.0004716632,0.26097152,0.0002164416,0.00010099758,0.000058958354,0.00037627466,0.00094093836,0.0028792887],"genre_scores_gemma":[0.95122135,0.0001402149,0.047273107,0.00004257306,0.000018938039,0.00004770358,0.0002492878,0.00008620162,0.000920596],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988854,0.000051158797,0.000008410863,0.000018161973,0.000018455794,0.000015179947],"domain_scores_gemma":[0.9996501,0.00014286806,0.00007671558,0.000041497075,0.000059166327,0.000029612673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005679495,0.00097611593,0.0004418746,0.00041908442,0.0003134915,0.0008913819,0.0006981731,0.000756506,0.0005503215],"category_scores_gemma":[0.0012686386,0.00040432476,0.000605922,0.00034753743,0.0005014887,0.0005917281,0.00072703714,0.00052487495,0.000111640846],"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":[0.0000458901,0.000014903266,0.0016307869,0.0000118189255,0.000018736002,0.000033900935,0.00002023063,0.9931444,0.0018515312,0.0013446695,0.00007418782,0.0018089011],"study_design_scores_gemma":[0.000007714521,0.000008256008,0.00014473194,0.0000013776636,0.0000023190246,0.0000015591543,0.000002898101,0.9992884,0.00020412967,0.0002667331,0.000069674796,0.0000022456404],"about_ca_topic_score_codex":0.032862544,"about_ca_topic_score_gemma":0.016383665,"teacher_disagreement_score":0.032862544,"about_ca_system_score_codex":0.0008730191,"about_ca_system_score_gemma":0.0006331134,"threshold_uncertainty_score":0.065342546},"labels":[],"label_agreement":null},{"id":"W4379233214","doi":"10.1029/2022ms003150","title":"Do State‐Of‐The‐Art Atmospheric CO<sub>2</sub> Inverse Models Capture Drought Impacts on the European Land Carbon Uptake?","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":23,"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 Toronto","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Environmental science; Carbon cycle; Atmospheric sciences; Climatology; Carbon fibers; Vegetation (pathology); Satellite; Carbon flux; Scale (ratio); Geography; Geology; Ecosystem; Ecology; Mathematics","score_opus":0.011318961420432632,"score_gpt":0.21244431114459225,"score_spread":0.20112534972415963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379233214","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95246404,0.0020309766,0.03578397,0.000906559,0.00018175587,0.000041922463,0.0027735692,0.0016482316,0.004168973],"genre_scores_gemma":[0.9891973,0.0002432117,0.008959872,0.00012942376,0.000048227917,0.000014796193,0.0011201261,0.000068623725,0.00021840399],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956995,0.00015688261,0.000040758532,0.000110641755,0.000056269837,0.00006554257],"domain_scores_gemma":[0.9988148,0.0003969009,0.00020360335,0.00023855435,0.00028187575,0.00006428593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025990175,0.00095230376,0.0007350456,0.0008080601,0.0002338195,0.0016471792,0.0011430853,0.0012162287,0.0008052514],"category_scores_gemma":[0.004028929,0.0005560372,0.00086036767,0.0006568375,0.00045494476,0.0017621759,0.0006107943,0.0005677612,0.00030470188],"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":[0.0006622041,0.00025549266,0.16940217,0.00030998635,0.0018203661,0.00011663465,0.000112644026,0.73532164,0.017076047,0.0013439535,0.003909362,0.0696695],"study_design_scores_gemma":[0.000050279847,0.00003340826,0.029199056,0.000034787197,0.00012769536,0.000015850947,0.000045166988,0.96571344,0.0029685614,0.0007705842,0.0009960635,0.000045059904],"about_ca_topic_score_codex":0.01845195,"about_ca_topic_score_gemma":0.02393944,"teacher_disagreement_score":0.01845195,"about_ca_system_score_codex":0.0004408285,"about_ca_system_score_gemma":0.00080666493,"threshold_uncertainty_score":0.036689103},"labels":[],"label_agreement":null},{"id":"W4383558108","doi":"10.1029/2022ms003224","title":"Assessing the Complementary Role of Surface Flux Equilibrium (SFE) Theory and Maximum Entropy Production (MEP) Principle in the Estimation of Actual Evapotranspiration","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":8,"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 British Columbia","funders":"Canadian Space Agency; European Commission","keywords":"Evapotranspiration; Principle of maximum entropy; Empirical modelling; Environmental science; Mathematics; Thermodynamics; Computer science; Statistics; Physics; Simulation","score_opus":0.017118728153639302,"score_gpt":0.2852687236670817,"score_spread":0.26814999551344243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383558108","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6277865,0.0003853327,0.36757657,0.00034521997,0.00003252102,0.000023771205,0.00015486943,0.00013088685,0.0035643957],"genre_scores_gemma":[0.9948585,0.000044023804,0.0049243565,0.000010392576,0.000008548088,0.000008006296,0.00003810993,0.000007987276,0.00010004108],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975926,0.000104784034,0.000013118438,0.000045568468,0.00005300351,0.000024237122],"domain_scores_gemma":[0.998409,0.0011819481,0.00014938302,0.000079109086,0.0001299414,0.00005067575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010275132,0.0003540382,0.0002653793,0.0005088581,0.0002056265,0.0006555148,0.00056774006,0.0005971108,0.00052750704],"category_scores_gemma":[0.0044855666,0.00017772599,0.00038052117,0.00034075908,0.0005377339,0.0015590243,0.0007136287,0.00038870552,0.000074402815],"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":[0.00006460212,0.00004115496,0.02186514,0.00006058832,0.00006482492,0.000074914125,0.000056666802,0.94293636,0.0045925053,0.011565476,0.0002402807,0.018437488],"study_design_scores_gemma":[0.0000023074638,0.000011059266,0.0032768915,0.0000039809674,0.000004110295,0.000010281723,0.000008726376,0.9937995,0.0004924775,0.002320693,0.00006355773,0.0000064202914],"about_ca_topic_score_codex":0.0027803977,"about_ca_topic_score_gemma":0.001330097,"teacher_disagreement_score":0.0027803977,"about_ca_system_score_codex":0.0003415634,"about_ca_system_score_gemma":0.0003377356,"threshold_uncertainty_score":0.0055283904},"labels":[],"label_agreement":null},{"id":"W4383957077","doi":"10.1029/2022ms003287","title":"Novel Geometric Parameters for Assessing Flow Over Realistic Versus Idealized Urban Arrays","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":30,"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 Guelph","funders":"Australian Research Council; National Cancer Institute; Australian Government; Climate Extremes; National Computational Infrastructure","keywords":"Flow (mathematics); Environmental science; Computer science; Geology; Geometry; Mathematics","score_opus":0.048640337012254266,"score_gpt":0.31061445795262477,"score_spread":0.2619741209403705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383957077","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9292856,0.00003666165,0.0685761,0.00002780631,0.000007488622,0.000028637127,0.0003934979,0.0003051572,0.001338963],"genre_scores_gemma":[0.9929623,0.000014654797,0.006788095,0.000003341781,0.0000020458936,0.000014588479,0.00015801738,0.000012319106,0.000044788332],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998722,0.000035483627,0.0000098542,0.000030042394,0.000028323222,0.000024039142],"domain_scores_gemma":[0.99948955,0.00021810003,0.00010256349,0.000094974304,0.00006023322,0.000034460714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032783425,0.000357235,0.00024143368,0.0007987037,0.0002513394,0.00058742735,0.00033552217,0.00027420095,0.0006857884],"category_scores_gemma":[0.001426571,0.00015739484,0.00020149577,0.0005961966,0.00047635124,0.00075943174,0.00037216392,0.0002680511,0.000068909656],"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":[0.000049800357,0.00006439006,0.025392324,0.000025006091,0.0000204113,0.000056102534,0.00006539794,0.9562998,0.007861645,0.0031026124,0.00019241039,0.006870189],"study_design_scores_gemma":[0.000006548213,0.0000341699,0.009571176,0.000003740454,0.000004802591,0.000019600486,0.0000614083,0.98629713,0.0027549705,0.0010216968,0.00021083403,0.000013902523],"about_ca_topic_score_codex":0.0031932069,"about_ca_topic_score_gemma":0.002599763,"teacher_disagreement_score":0.0031932069,"about_ca_system_score_codex":0.00034654984,"about_ca_system_score_gemma":0.00032390273,"threshold_uncertainty_score":0.006349206},"labels":[],"label_agreement":null},{"id":"W4384701489","doi":"10.1029/2023ms003674","title":"A Functionalized Monte Carlo 3D Radiative Transfer Model: Radiative Effects of Clouds Over Reflecting Surfaces","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","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":"Environment and Climate Change Canada","funders":"","keywords":"Radiative transfer; Albedo (alchemy); Monte Carlo method; Computational physics; Atmospheric radiative transfer codes; Zenith; Physics; Atmosphere (unit); Solar zenith angle; Surface (topology); Optics; Atmospheric sciences; Meteorology; Geometry; Mathematics","score_opus":0.016212592358491876,"score_gpt":0.280393983956093,"score_spread":0.2641813915976011,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384701489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50217205,0.00065435603,0.4686795,0.0012300638,0.00018102213,0.00018246313,0.0009308083,0.0006837492,0.025286086],"genre_scores_gemma":[0.9710113,0.00019784988,0.022892829,0.00015516876,0.0000469975,0.00014410779,0.00021116437,0.00006824818,0.005272498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998319,0.000061155275,0.0000060599236,0.000034009707,0.00003660322,0.000030277148],"domain_scores_gemma":[0.99952126,0.00027343413,0.00005674779,0.000029158376,0.00007592267,0.000043553882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004336532,0.00046674238,0.0006327466,0.00042404438,0.00073199923,0.0010691269,0.0012431003,0.0019341515,0.0017280837],"category_scores_gemma":[0.001247887,0.00047274874,0.00072338595,0.0005279666,0.0009082141,0.00069060404,0.000711045,0.0007588993,0.00023266952],"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":[0.0000094471225,0.000010807633,0.00028523474,0.000004092885,0.000005883354,0.000018575001,0.000006494281,0.9972716,0.00039556102,0.0015272687,0.00005661877,0.0004084461],"study_design_scores_gemma":[0.0000029524163,0.0000023401842,0.00004895633,7.296371e-7,0.0000012843161,0.000002181435,0.0000011087812,0.99960405,0.000051242077,0.00022694892,0.000056421308,0.0000019371025],"about_ca_topic_score_codex":0.028946232,"about_ca_topic_score_gemma":0.010804582,"teacher_disagreement_score":0.028946232,"about_ca_system_score_codex":0.0012691034,"about_ca_system_score_gemma":0.0011406754,"threshold_uncertainty_score":0.057555497},"labels":[],"label_agreement":null},{"id":"W4386388182","doi":"10.1029/2023ms003613","title":"Teardrop and Parabolic Lens Yield Curves for Viscous‐Plastic Sea Ice Models: New Constitutive Equations and Failure Angles","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Environment and Climate Change Canada; Deutsche Forschungsgemeinschaft","keywords":"Yield (engineering); Constitutive equation; Solver; Mechanics; Nonlinear system; Materials science; Yield surface; Geometry; Mathematical analysis; Mathematics; Physics; Composite material; Thermodynamics; Finite element method","score_opus":0.04088044632003512,"score_gpt":0.2612131526192637,"score_spread":0.22033270629922858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386388182","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36847842,0.0011387108,0.61034596,0.0007200866,0.000105431354,0.00018655487,0.0005566441,0.0004239734,0.018044282],"genre_scores_gemma":[0.9643863,0.00065454724,0.0291316,0.000071203285,0.00003683748,0.00013464081,0.0002695814,0.00022060136,0.005094764],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997693,0.00005682692,0.000022170938,0.00002681768,0.00009076622,0.000034130135],"domain_scores_gemma":[0.99919826,0.00027984,0.0001671216,0.00008478814,0.00020679357,0.00006328025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087014434,0.0010214725,0.00048151956,0.0008471184,0.0003192036,0.0013068514,0.000814568,0.0008550313,0.0016681366],"category_scores_gemma":[0.003228029,0.00038354564,0.00077011815,0.0006341034,0.0009493415,0.0012755351,0.0012331805,0.0010686814,0.00032095393],"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":[0.00007108309,0.00008800237,0.0058884877,0.00010216635,0.00002489874,0.0001924768,0.00023493073,0.90901417,0.015855042,0.040273044,0.0013069058,0.02694883],"study_design_scores_gemma":[0.000004465317,0.0000121755065,0.000281442,0.000008065898,0.0000026259959,0.000019910127,0.000022521746,0.99596244,0.0016714459,0.0015810028,0.0004264171,0.000007623351],"about_ca_topic_score_codex":0.0074956673,"about_ca_topic_score_gemma":0.003627139,"teacher_disagreement_score":0.0074956673,"about_ca_system_score_codex":0.00088108174,"about_ca_system_score_gemma":0.0008624907,"threshold_uncertainty_score":0.014904082},"labels":[],"label_agreement":null},{"id":"W4388783620","doi":"10.1029/2022ms003391","title":"A Shallow‐Deep Unified Stochastic Mass Flux Cumulus Parameterization in the Single Column Community Climate Model","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":4,"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 Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; New York University Abu Dhabi","keywords":"Context (archaeology); Convection; Climate model; Environmental science; Mass flux; Diurnal cycle; Lapse rate; Meteorology; Atmospheric sciences; Climatology; Statistical physics; Geology; Climate change; Physics; Mechanics","score_opus":0.052659235910613784,"score_gpt":0.2872935885401088,"score_spread":0.234634352629495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388783620","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81847894,0.00032460588,0.17058948,0.00080130843,0.000108713386,0.00009500054,0.0010233118,0.0005570445,0.00802167],"genre_scores_gemma":[0.98913574,0.00005550368,0.009904311,0.000050448936,0.0000226251,0.00004778123,0.00022519009,0.00003329736,0.000525065],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998553,0.000060952447,0.000008056353,0.000025232002,0.000027028713,0.000023393522],"domain_scores_gemma":[0.9996598,0.00011512103,0.00005979256,0.000044346005,0.000070943555,0.000050080052],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004761715,0.0004953978,0.00047591556,0.0002636834,0.00037621643,0.00081367005,0.0012351372,0.0007691632,0.00064809865],"category_scores_gemma":[0.0012382069,0.00021381372,0.00045677696,0.00034695794,0.00039791688,0.0006946417,0.0007421782,0.00090697187,0.00009217777],"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":[0.000023692395,0.00002203399,0.0013479426,0.0000072304533,0.000013548776,0.000016366152,0.0000090986305,0.9925085,0.0009143947,0.0034373095,0.00020493417,0.0014949751],"study_design_scores_gemma":[0.0000049723435,0.0000042121333,0.00015606683,5.347568e-7,0.0000016688384,9.239011e-7,0.0000011777678,0.999514,0.000064821135,0.00020105267,0.0000487218,0.0000019718275],"about_ca_topic_score_codex":0.03845604,"about_ca_topic_score_gemma":0.018471025,"teacher_disagreement_score":0.03845604,"about_ca_system_score_codex":0.0008314656,"about_ca_system_score_gemma":0.0010741911,"threshold_uncertainty_score":0.076464415},"labels":[],"label_agreement":null},{"id":"W4389943238","doi":"10.1029/2022ms003385","title":"Linking Biogeochemical and Hydrodynamic Processes to Model Methane Fluxes in Shallow, Tropical Floodplain Lakes","year":2023,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Division of Environmental Biology; National Aeronautics and Space Administration; National Science Foundation","keywords":"Biogeochemical cycle; Methane; Environmental science; Biogeochemistry; Anaerobic oxidation of methane; Methanogenesis; Floodplain; Atmospheric sciences; Wetland; Hydrology (agriculture); Environmental chemistry; Geology; Chemistry; Ecology","score_opus":0.009772548310034304,"score_gpt":0.24006819763363044,"score_spread":0.23029564932359614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389943238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99839526,0.000010921605,0.0010686198,0.000026485457,0.000003016511,0.000013098492,0.00008817126,0.0000628184,0.00033174187],"genre_scores_gemma":[0.9987116,0.000008920989,0.0010413344,0.0000061166234,0.0000019484182,0.000018881214,0.00006316834,0.000007526238,0.00014057317],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999052,0.00003050649,0.000007520874,0.00001970765,0.000011354178,0.000025680298],"domain_scores_gemma":[0.99944454,0.00034720957,0.00006288418,0.000025634976,0.00006346242,0.000056134046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042773498,0.00063790486,0.00030865896,0.00041876035,0.00046368164,0.00061117864,0.0006364914,0.00081162737,0.0008563668],"category_scores_gemma":[0.0012005046,0.00036526518,0.0005369459,0.00034280567,0.0003882998,0.00042928517,0.00044328562,0.00048867136,0.00006119082],"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":[0.000057285593,0.00008323137,0.017397638,0.000009082119,0.000031568692,0.00004432673,0.000023842207,0.97960246,0.0014438328,0.00010815117,0.000052489915,0.0011462442],"study_design_scores_gemma":[0.00002668644,0.00004206747,0.0036927098,0.0000013262305,0.0000089878795,0.0000032999474,0.00001375571,0.99555343,0.00057151576,0.000052853065,0.000029107454,0.000004254287],"about_ca_topic_score_codex":0.074362926,"about_ca_topic_score_gemma":0.031381942,"teacher_disagreement_score":0.074362926,"about_ca_system_score_codex":0.001450894,"about_ca_system_score_gemma":0.0009638884,"threshold_uncertainty_score":0.14786017},"labels":[],"label_agreement":null},{"id":"W4390955046","doi":"10.1029/2023ms003749","title":"The Impact of Climate Forcing Biases and the Nitrogen Cycle on Land Carbon Balance Projections","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric and Environmental Gas Dynamics","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":true,"ca_institutions":"Dalhousie University; Queen's University; Environment and Climate Change Canada","funders":"","keywords":"Environmental science; Carbon cycle; Carbon sink; Sink (geography); Climate change; Ecosystem; Greenhouse gas; Global change; Atmospheric sciences; Forcing (mathematics); Nutrient; Nitrogen; Nitrogen cycle; Carbon fibers; Precipitation; Ecology; Meteorology; Chemistry; Computer science","score_opus":0.007954204555628997,"score_gpt":0.258627638674611,"score_spread":0.250673434118982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390955046","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9872004,0.0005706852,0.0025236523,0.0010944346,0.00009686157,0.000022652763,0.0018814831,0.00016344714,0.0064465017],"genre_scores_gemma":[0.998139,0.00015031915,0.0007486923,0.000087581015,0.000009527391,0.0000078416015,0.0005890398,0.00003769554,0.00023028096],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991762,0.00031726353,0.000040032177,0.00012022894,0.00016268835,0.0001835468],"domain_scores_gemma":[0.9978892,0.0009324471,0.00021647164,0.00022699407,0.00056868384,0.0001661491],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002880881,0.0008695476,0.00047918534,0.0005359159,0.00080827344,0.0016215915,0.0008700453,0.0008916295,0.0014277983],"category_scores_gemma":[0.0070935464,0.00032289547,0.0008062226,0.00085993984,0.0008106009,0.0014165126,0.00086316396,0.00084344647,0.0001428723],"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":[0.00021065497,0.000065559965,0.08194343,0.00007100096,0.00029318736,0.000076273085,0.000054178996,0.9052378,0.0014805769,0.0030540074,0.0015245207,0.0059888787],"study_design_scores_gemma":[0.00015637728,0.00008814243,0.0651152,0.00008099095,0.00019892397,0.000022395687,0.00020115485,0.92366153,0.0030955395,0.0038532387,0.003424108,0.00010231763],"about_ca_topic_score_codex":0.49260512,"about_ca_topic_score_gemma":0.422597,"teacher_disagreement_score":0.49260512,"about_ca_system_score_codex":0.004334485,"about_ca_system_score_gemma":0.0052035544,"threshold_uncertainty_score":0.9794757},"labels":[],"label_agreement":null},{"id":"W4391480574","doi":"10.1029/2023ms003700","title":"The Green's Function Model Intercomparison Project (GFMIP) Protocol","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":33,"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":"HORIZON EUROPE European Research Council; Nuclear Safety and Security Commission; European Commission; Sight Research UK; National Aeronautics and Space Administration; Natural Environment Research Council; U.S. Department of Energy; National Science Foundation","keywords":"Radiative transfer; Environmental science; Atmosphere (unit); Coupled model intercomparison project; Atmospheric circulation; Climate model; Atmospheric model; Atmospheric sciences; Meteorology; Atmospheric temperature; General Circulation Model; Climatology; Climate change; Geology; Physics","score_opus":0.033811254008756425,"score_gpt":0.32422301745142573,"score_spread":0.2904117634426693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391480574","genre_codex":"dataset","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008337878,0.0002398117,0.13758439,0.0077067735,0.0027546738,0.08605271,0.622908,0.010322297,0.12409347],"genre_scores_gemma":[0.033954173,0.00079038006,0.17724274,0.0036393735,0.00075076503,0.28032014,0.44734251,0.004027082,0.051932834],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9935169,0.0035999662,0.00061345455,0.00050765,0.0012702917,0.0004916527],"domain_scores_gemma":[0.9801485,0.0055758455,0.00093748985,0.0059851278,0.006113519,0.0012393881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027212426,0.0014749526,0.00085781614,0.0017941925,0.001970721,0.0025151214,0.0049698204,0.0030733254,0.17926076],"category_scores_gemma":[0.044875506,0.0010508427,0.0010262751,0.0021855587,0.000977145,0.002376823,0.0032386666,0.0030654953,0.0402382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015432357,0.00040596016,0.0018790734,0.00084592827,0.000087270644,0.0005001939,0.0003588748,0.0153242415,0.0035618106,0.054902922,0.869611,0.05097948],"study_design_scores_gemma":[0.0020247437,0.00038185788,0.0038372148,0.0007723815,0.00005817505,0.0001212655,0.00026031455,0.012853612,0.0046935068,0.040568426,0.9342958,0.00013284033],"about_ca_topic_score_codex":0.013436507,"about_ca_topic_score_gemma":0.008666051,"teacher_disagreement_score":0.17926076,"about_ca_system_score_codex":0.0031461362,"about_ca_system_score_gemma":0.009773764,"threshold_uncertainty_score":0.599687},"labels":[],"label_agreement":null},{"id":"W4392237216","doi":"10.1029/2023ms003691","title":"Response of the Current Climate to Land‐Ocean Contrasts in Parameterized Cumulus Entrainment","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","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":false,"ca_institutions":"McGill University","funders":"U.S. Department of Energy","keywords":"Entrainment (biomusicology); Environmental science; Convection; Climatology; Precipitation; Atmospheric sciences; Climate model; Ocean current; Diabatic; Subsidence; Geology; Climate change; Oceanography; Meteorology; Geography","score_opus":0.019004935707072415,"score_gpt":0.29363824717780784,"score_spread":0.27463331147073544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392237216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986395,0.000027767283,0.00023046344,0.000058759964,0.000010875099,0.0000048191273,0.00016493886,0.000025960217,0.00083697255],"genre_scores_gemma":[0.9996612,0.000011969528,0.00008905757,0.00001375934,0.000002591932,0.0000040871496,0.00014285302,0.0000067299516,0.00006765671],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990714,0.00002121871,0.00000636222,0.000024079332,0.000011715224,0.000029511168],"domain_scores_gemma":[0.9996797,0.00013668663,0.000048312948,0.000032609034,0.00004159589,0.00006116398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032123894,0.0004080855,0.00025221606,0.0002160351,0.00030113984,0.0007165116,0.00041791948,0.00056169904,0.0010263044],"category_scores_gemma":[0.0014586125,0.00019225867,0.0004401642,0.00020164877,0.00031732357,0.0003697639,0.00040695968,0.00052909605,0.000100642384],"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":[0.0005004685,0.0003134484,0.11636371,0.00006664403,0.00031482617,0.00024708186,0.00007427301,0.84188944,0.033200625,0.0010744883,0.0011033441,0.0048517524],"study_design_scores_gemma":[0.00012317578,0.00025578513,0.11580081,0.000010765618,0.000093771465,0.00004945812,0.00012476485,0.8755163,0.006699292,0.000331053,0.0009598517,0.000034925804],"about_ca_topic_score_codex":0.016624004,"about_ca_topic_score_gemma":0.0075533725,"teacher_disagreement_score":0.016624004,"about_ca_system_score_codex":0.00067455234,"about_ca_system_score_gemma":0.0003763183,"threshold_uncertainty_score":0.03305447},"labels":[],"label_agreement":null},{"id":"W4392552461","doi":"10.1029/2023ms003799","title":"UQAM‐TCW: A Global Hybrid Tropical Cyclone Wind Model Based Upon Statistical and Coupled Climate Models","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Tropical and Extratropical Cyclones Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ouranos; Université du Québec à Montréal","funders":"Fonds de recherche du Québec; Natural Sciences and Engineering Research Council of Canada; Mitacs; Marine Environmental Observation Prediction and Response Network","keywords":"Tropical cyclone; Climatology; Environmental science; Climate model; Meteorology; General Circulation Model; Tropical cyclone forecast model; Atmospheric sciences; Climate change; Geography; Geology; Oceanography","score_opus":0.020553549180386217,"score_gpt":0.282811612640524,"score_spread":0.2622580634601378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392552461","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7925812,0.00042207097,0.16693191,0.0012685457,0.00023646375,0.00016340813,0.0046234527,0.0013212129,0.032451782],"genre_scores_gemma":[0.9843612,0.00013026655,0.011898123,0.00007473469,0.000033247332,0.00010073297,0.00086481305,0.00007196122,0.0024649096],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988985,0.000043884957,0.0000049702066,0.00002617763,0.000017918044,0.000017239652],"domain_scores_gemma":[0.99972755,0.000121916004,0.000036425987,0.000029134317,0.000042484317,0.000042446733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030444286,0.00054899626,0.00043677594,0.00029293823,0.0003325919,0.0009308645,0.0007749264,0.0008687927,0.001521665],"category_scores_gemma":[0.0008113976,0.0002994173,0.00052554003,0.0004653399,0.00051256386,0.00058981904,0.00072268693,0.0007677093,0.00015172499],"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":[0.000010288762,0.00000792793,0.00062209775,0.0000036689069,0.000010223736,0.000016812408,0.000003998354,0.99711895,0.00013139845,0.0010853288,0.00021939886,0.00076992164],"study_design_scores_gemma":[0.00000924686,0.000006288455,0.00016962427,0.000001008518,0.0000020877294,0.0000017479088,0.0000020328332,0.99921846,0.000028773313,0.00040769443,0.00015069368,0.0000023348996],"about_ca_topic_score_codex":0.043607667,"about_ca_topic_score_gemma":0.022633187,"teacher_disagreement_score":0.043607667,"about_ca_system_score_codex":0.0006422548,"about_ca_system_score_gemma":0.0009971196,"threshold_uncertainty_score":0.08670765},"labels":[],"label_agreement":null},{"id":"W4398157119","doi":"10.1029/2024ms004424","title":"Thank You to Our 2023 Peer Reviewers","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Scientific Computing and Data Management","field":"Decision 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":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Environmental science","score_opus":0.15049704514316267,"score_gpt":0.44676237195890084,"score_spread":0.29626532681573814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398157119","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007590018,0.0089936815,0.0073895496,0.25505322,0.68619144,0.0011266122,0.00347997,0.0048989374,0.032107577],"genre_scores_gemma":[0.007809077,0.008851391,0.016686847,0.13474491,0.30818394,0.0024660067,0.004704013,0.006292033,0.5102617],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9731694,0.0061018467,0.0028523614,0.0033452278,0.0133104725,0.0012206824],"domain_scores_gemma":[0.4768549,0.014012542,0.011466086,0.011124302,0.46163374,0.024908448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020056356,0.0022446667,0.0031854012,0.005392467,0.0047370163,0.016676303,0.0028865465,0.0058938446,0.2108159],"category_scores_gemma":[0.21256076,0.0012547582,0.0017406027,0.0037537443,0.0015725783,0.0074701686,0.004364377,0.0073859277,0.35847908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011853809,0.0000037004247,0.00006785413,0.00004748733,0.0000032564824,0.00002834965,0.000024608744,0.000010142737,0.00006021216,0.00011714296,0.99115115,0.008474288],"study_design_scores_gemma":[0.000013702918,0.000011904542,0.00024510786,0.00010999788,0.0000091006705,0.000118737065,0.0001767179,0.00006981617,0.00008189073,0.00048655557,0.9986487,0.000027818427],"about_ca_topic_score_codex":0.0036417176,"about_ca_topic_score_gemma":0.007993169,"teacher_disagreement_score":0.2108159,"about_ca_system_score_codex":0.0025647676,"about_ca_system_score_gemma":0.009370663,"threshold_uncertainty_score":0.7052494},"labels":[],"label_agreement":null},{"id":"W4400615252","doi":"10.1029/2023ms003902","title":"Machine Learning‐Based Clustering of Oceanic Lagrangian Particles: Identification of the Main Pathways of the Labrador Current","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Oceanographic and Atmospheric Processes","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":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Cluster analysis; Current (fluid); Identification (biology); Geology; Geospatial analysis; Computer science; Geophysics; Artificial intelligence; Oceanography; Remote sensing; Biology","score_opus":0.014791204556461258,"score_gpt":0.22975007866647768,"score_spread":0.2149588741100164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400615252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81688446,0.00018644215,0.17945804,0.00016871715,0.000031821204,0.00009385564,0.0006587008,0.0007468127,0.0017710542],"genre_scores_gemma":[0.95895123,0.00003998509,0.039550994,0.000013118967,0.000008391592,0.00002175221,0.0008376652,0.000038344086,0.00053865096],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983263,0.000032091182,0.000011758831,0.00006120106,0.000028974362,0.000033322267],"domain_scores_gemma":[0.9994566,0.0001120203,0.00012972344,0.000059616894,0.00019331262,0.000048718255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004108409,0.00044106538,0.0003199342,0.0017079756,0.0004176242,0.00070294907,0.00065669254,0.00040981153,0.0006013686],"category_scores_gemma":[0.0012901488,0.0001642008,0.0006232588,0.00081993325,0.00032321856,0.0004156606,0.00039756257,0.00031216163,0.0003123358],"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":[0.000364257,0.00021318792,0.14015242,0.00013443273,0.0002361423,0.00028068628,0.00048778777,0.6933944,0.016900072,0.0036207724,0.0043576355,0.13985817],"study_design_scores_gemma":[0.00000627182,0.000008892513,0.01513609,0.0000070596984,0.000008039739,0.000011582912,0.000057219917,0.98251235,0.0013568976,0.00057758414,0.0003067373,0.000011383517],"about_ca_topic_score_codex":0.03457683,"about_ca_topic_score_gemma":0.020453429,"teacher_disagreement_score":0.03457683,"about_ca_system_score_codex":0.0007091363,"about_ca_system_score_gemma":0.0009105218,"threshold_uncertainty_score":0.06875116},"labels":[],"label_agreement":null},{"id":"W4400901900","doi":"10.1029/2023ms004014","title":"Solar Radiation Triggers the Bimodal Leaf Phenology of Central African Evergreen Broadleaved Forests","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Island University","funders":"China Scholarship Council; Belgian Federal Science Policy Office; National Natural Science Foundation of China; International Development Research Centre","keywords":"Phenology; Evergreen; Seasonality; Environmental science; Canopy; Leaf area index; Evergreen forest; Atmospheric sciences; Climatology; Ecology; Biology","score_opus":0.008426265216275344,"score_gpt":0.231738282524346,"score_spread":0.22331201730807065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400901900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999527,0.000017637849,0.00024604154,0.0000067043675,8.2270356e-7,0.0000016985214,0.0000685053,0.000012369109,0.000119256685],"genre_scores_gemma":[0.99980503,0.0000072656126,0.0001078348,0.000001849893,3.9150416e-7,0.0000011219184,0.000050721497,0.0000016555787,0.000024182498],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999928,0.000017753764,0.0000037766579,0.00002388652,0.000009521175,0.000017057095],"domain_scores_gemma":[0.9998803,0.000042634256,0.00002531835,0.000014959611,0.000018747529,0.000018127388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019380878,0.00016802081,0.00019925208,0.00022527066,0.00015948084,0.00035816373,0.00019977293,0.00015906275,0.0005960799],"category_scores_gemma":[0.00039614367,0.00013315018,0.00018205214,0.00024898053,0.00013253772,0.0002559781,0.00029348474,0.00014896115,0.000055071836],"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":[0.00036511643,0.0001310079,0.8116412,0.00007712442,0.00013924508,0.0002304098,0.00023919926,0.09790041,0.07455126,0.00045494668,0.0003273613,0.013942848],"study_design_scores_gemma":[0.000020191092,0.000033120887,0.83921224,0.000007487073,0.000021301043,0.000056239067,0.0001611254,0.15611465,0.003893728,0.000172283,0.00029745587,0.000010064164],"about_ca_topic_score_codex":0.0113875335,"about_ca_topic_score_gemma":0.009985639,"teacher_disagreement_score":0.0113875335,"about_ca_system_score_codex":0.0004066093,"about_ca_system_score_gemma":0.00020072302,"threshold_uncertainty_score":0.022642493},"labels":[],"label_agreement":null},{"id":"W4403439653","doi":"10.1029/2023ms004094","title":"Toward Fine Horizontal Resolution Global Simulations of Aerosol Sectional Microphysics: Advances Enabled by GCHP‐TOMAS","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric chemistry and aerosols","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":false,"ca_institutions":"Dalhousie University","funders":"National Aeronautics and Space Administration; National Science Foundation","keywords":"Environmental science; Aerosol; Atmospheric sciences; Meteorology; Horizontal resolution; Remote sensing; Climatology; Geography; Geology","score_opus":0.013269200998430269,"score_gpt":0.24656957771919902,"score_spread":0.23330037672076875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403439653","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8874059,0.0003749719,0.08923406,0.0009800392,0.00027292967,0.00015713142,0.002234872,0.0062662633,0.013073753],"genre_scores_gemma":[0.9300136,0.00014739788,0.06710726,0.00010446315,0.00004599696,0.0001155021,0.0014469059,0.00026331778,0.0007555233],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998658,0.000040703188,0.0000049543187,0.000020531128,0.000043404747,0.00002454996],"domain_scores_gemma":[0.9997061,0.00006684406,0.000028653281,0.00007321095,0.00006632053,0.000058833157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041734063,0.0006527898,0.00041769526,0.00026832035,0.0003121774,0.0007010905,0.0010299275,0.00059435784,0.0017059166],"category_scores_gemma":[0.0008609216,0.00030082563,0.0005327508,0.00052263116,0.00049207796,0.00071021373,0.0009015743,0.0011830566,0.00023641335],"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":[0.00015444624,0.00014059916,0.008225394,0.000056620436,0.00010379409,0.00009430168,0.000055725875,0.958093,0.015998013,0.0053510494,0.0025887298,0.0091384025],"study_design_scores_gemma":[0.000030922485,0.000013313924,0.0011464134,0.0000028775619,0.0000066113485,0.00000385402,0.000007746201,0.99567467,0.0013981404,0.00067804335,0.0010326314,0.0000048830734],"about_ca_topic_score_codex":0.023105096,"about_ca_topic_score_gemma":0.012069797,"teacher_disagreement_score":0.023105096,"about_ca_system_score_codex":0.00073509425,"about_ca_system_score_gemma":0.00087574765,"threshold_uncertainty_score":0.045941174},"labels":[],"label_agreement":null},{"id":"W4403847049","doi":"10.1029/2024ms004275","title":"A Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site‐Level Validation, and Global Applicability","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","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":"Université du Québec à Montréal; Ministry of Environment","funders":"National Aeronautics and Space Administration; U.S. Department of Energy; Office of Science; National Science Foundation","keywords":"Environmental science; Biogeochemical cycle; Methane; Biogeochemistry; Floodplain; Hydrology (agriculture); Atmospheric sciences; Oceanography; Geology; Ecology","score_opus":0.02141586165147979,"score_gpt":0.28029334214276064,"score_spread":0.25887748049128084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403847049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94886285,0.00013596212,0.039321937,0.00038546414,0.00003639144,0.00012029641,0.0030039165,0.0015167939,0.006616301],"genre_scores_gemma":[0.97751325,0.00006087069,0.018974831,0.000054477507,0.0000090049325,0.00018007426,0.0018041325,0.00018365149,0.0012198585],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997905,0.00007290511,0.000013699407,0.00005380415,0.000032466487,0.000036638932],"domain_scores_gemma":[0.9992787,0.0003855872,0.000058164183,0.00007053919,0.00016569765,0.00004131477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008921534,0.0009372405,0.0006696679,0.00056716945,0.00058847555,0.0007740076,0.0012446009,0.001291682,0.0029206004],"category_scores_gemma":[0.0018410245,0.00062378054,0.0010495151,0.000706345,0.00052761566,0.00095367804,0.0008976905,0.0010116565,0.00031664362],"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":[0.000024404224,0.000028049286,0.002140827,0.000009771493,0.000018657342,0.000016990733,0.0000075494127,0.9958402,0.00045028562,0.000254649,0.00014607346,0.0010626782],"study_design_scores_gemma":[0.000020232495,0.000007152267,0.0003591229,0.0000011215781,0.000004255652,0.0000010662056,0.0000030386116,0.99928063,0.00015740976,0.00008379837,0.0000794144,0.0000028642137],"about_ca_topic_score_codex":0.06946559,"about_ca_topic_score_gemma":0.037405733,"teacher_disagreement_score":0.06946559,"about_ca_system_score_codex":0.0017834676,"about_ca_system_score_gemma":0.0019782672,"threshold_uncertainty_score":0.1381225},"labels":[],"label_agreement":null},{"id":"W4404833591","doi":"10.1029/2024ms004256","title":"Accurate and Efficient Numerical Simulation of Land Models Using SUMMA With SUNDIALS","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":3,"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 Calgary; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Nonlinear system; Suite; Algorithm; Applied mathematics; Mathematics","score_opus":0.039337487101076436,"score_gpt":0.306364658515356,"score_spread":0.26702717141427956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404833591","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41964167,0.0002905439,0.52857816,0.00081588235,0.000301006,0.00015935102,0.0029993332,0.0072356937,0.039978318],"genre_scores_gemma":[0.7627689,0.0001535648,0.22988813,0.00010857995,0.000057291,0.0002291463,0.002070437,0.00052947405,0.004194436],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975127,0.00006738236,0.000018606293,0.000027864522,0.000106849766,0.000027990902],"domain_scores_gemma":[0.99931526,0.00028993734,0.00007452103,0.00012536933,0.0001358129,0.00005908224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005004172,0.00048775063,0.0006816335,0.00035073288,0.00065785204,0.0007953103,0.0014232316,0.00072958606,0.004401076],"category_scores_gemma":[0.0017596664,0.0003748231,0.0007996945,0.00043336125,0.0005857269,0.0008053907,0.0014256394,0.0009709677,0.0007006177],"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":[0.00004939588,0.00008228482,0.0033260633,0.00007907906,0.000046114306,0.00010569823,0.000079486745,0.9657089,0.0038600895,0.01120073,0.0022777603,0.013184464],"study_design_scores_gemma":[0.000011273708,0.000012543347,0.0002298099,0.000003923083,0.0000035255746,0.000009675985,0.000010711503,0.99672914,0.0006755757,0.0010565292,0.0012523589,0.0000049152645],"about_ca_topic_score_codex":0.009029106,"about_ca_topic_score_gemma":0.015364518,"teacher_disagreement_score":0.009029106,"about_ca_system_score_codex":0.0005150845,"about_ca_system_score_gemma":0.0010903146,"threshold_uncertainty_score":0.017953157},"labels":[],"label_agreement":null},{"id":"W4405339866","doi":"10.1029/2024ms004563","title":"Climatological Adaptive Bias Correction of Climate Models","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Climate model; Climatology; Environmental science; Atmospheric sciences; Meteorology; Computer science; Climate change; Geology; Oceanography; Physics","score_opus":0.05244089525070626,"score_gpt":0.2893887747739856,"score_spread":0.23694787952327934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405339866","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24790674,0.00031979324,0.74741733,0.000206567,0.00007365092,0.00004667806,0.00024233482,0.0009909599,0.0027959375],"genre_scores_gemma":[0.9048343,0.000092376686,0.09406992,0.00004411054,0.000027077927,0.000036115558,0.00019625908,0.00016245918,0.0005374556],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956423,0.00019879993,0.000021582935,0.00007863578,0.00009658844,0.00004009897],"domain_scores_gemma":[0.9980057,0.00081589725,0.00036390574,0.00047384395,0.000307944,0.000032758544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013719434,0.00036775833,0.0001947383,0.00042789424,0.0001491344,0.00040456827,0.0005662744,0.0002449985,0.00053988316],"category_scores_gemma":[0.008645632,0.00017826757,0.00033103648,0.00045552236,0.00028316083,0.0003380276,0.00055210595,0.0007439006,0.00010386134],"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":[0.00014765224,0.000040943327,0.017047897,0.000075459146,0.00015939045,0.000059073544,0.00008802284,0.86713916,0.013273048,0.009703285,0.0009006274,0.091365434],"study_design_scores_gemma":[0.000010045041,0.000019657542,0.002845023,0.0000094490415,0.00001214647,0.00001632668,0.000009144308,0.9895399,0.004116525,0.0024800336,0.0009338623,0.000007868765],"about_ca_topic_score_codex":0.0056796507,"about_ca_topic_score_gemma":0.005869658,"teacher_disagreement_score":0.0056796507,"about_ca_system_score_codex":0.00040001958,"about_ca_system_score_gemma":0.0006217317,"threshold_uncertainty_score":0.011293173},"labels":[],"label_agreement":null},{"id":"W4405388631","doi":"10.1029/2024ms004580","title":"Physical Drivers and Biogeochemical Effects of the Projected Decline of the Shelfbreak Jet in the Northwest North Atlantic Ocean","year":2024,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biogeochemical cycle; Oceanography; Environmental science; Climatology; Geology; Jet (fluid); Physics","score_opus":0.003688725738136618,"score_gpt":0.206516666029125,"score_spread":0.20282794029098838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405388631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983523,0.00007287707,0.00019417082,0.00027288133,0.000011620045,0.000006900859,0.00048013098,0.000020326981,0.0005887037],"genre_scores_gemma":[0.999383,0.000047384037,0.000097403645,0.0000273441,0.000006591172,0.0000032326836,0.00028131373,0.0000034895825,0.00015017585],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999119,0.000017403587,0.000009592439,0.000021761478,0.00001851525,0.000020861176],"domain_scores_gemma":[0.9996093,0.00005905748,0.00013145179,0.000017684984,0.00008860371,0.0000938872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048179552,0.00030095875,0.00021752159,0.00040815573,0.00041481366,0.0011238428,0.0003393885,0.0005821413,0.0025491393],"category_scores_gemma":[0.0008670978,0.00027042473,0.00059385697,0.00035288173,0.0003233477,0.0004110409,0.00050896197,0.0005059531,0.00016549758],"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":[0.0001844039,0.000086058826,0.96459496,0.000041510964,0.00013216866,0.0002704499,0.000060829498,0.023320822,0.00783473,0.0003549133,0.00046247768,0.0026565993],"study_design_scores_gemma":[0.0000257551,0.00005631599,0.9649553,0.000010398046,0.00004167294,0.000029891258,0.00018814168,0.033491913,0.00047929754,0.00020178306,0.0005079806,0.000011511497],"about_ca_topic_score_codex":0.09037358,"about_ca_topic_score_gemma":0.09303433,"teacher_disagreement_score":0.09037358,"about_ca_system_score_codex":0.0015932537,"about_ca_system_score_gemma":0.0008233948,"threshold_uncertainty_score":0.17969507},"labels":[],"label_agreement":null},{"id":"W4407168403","doi":"10.1029/2024ms004714","title":"Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Biological and Environmental Research; Office of Science; U.S. Department of Energy","keywords":"Environmental science; Soil respiration; Soil carbon; Water content; Ecosystem; Biomass (ecology); Soil science; Agronomy; Soil organic matter; Soil water; Atmospheric sciences; Ecology","score_opus":0.004624480065531636,"score_gpt":0.21381476461189372,"score_spread":0.20919028454636207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407168403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99875975,0.000019626776,0.000631719,0.000017329392,0.0000029383546,0.000011281753,0.00016448241,0.000026693662,0.0003661956],"genre_scores_gemma":[0.9995036,0.0000142507815,0.00032288156,0.00000835774,8.035908e-7,0.00001438561,0.000072358256,0.000003935647,0.00005939089],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999232,0.000018696805,0.000005660726,0.000024259323,0.000009240049,0.000018865758],"domain_scores_gemma":[0.99987674,0.000050877992,0.00002867187,0.00002119117,0.0000094656525,0.000012991908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023258569,0.00027717714,0.00015225093,0.00009166752,0.00021590928,0.000250042,0.00033712632,0.00021309267,0.00091399864],"category_scores_gemma":[0.00019081827,0.0001784269,0.00030360318,0.000084120926,0.00029292062,0.00024433996,0.00019673674,0.0004006613,0.00003841205],"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":[0.0024142948,0.0014779276,0.12250332,0.00022973791,0.00035387612,0.00022429986,0.00019557084,0.24468592,0.6145653,0.0010689324,0.0007863696,0.011494526],"study_design_scores_gemma":[0.00038098582,0.0025784173,0.33155155,0.00002185589,0.0002300729,0.0000785463,0.00022903456,0.4395653,0.22223671,0.0012944669,0.001755951,0.00007715051],"about_ca_topic_score_codex":0.0090177655,"about_ca_topic_score_gemma":0.008744334,"teacher_disagreement_score":0.0090177655,"about_ca_system_score_codex":0.0008241943,"about_ca_system_score_gemma":0.00023957857,"threshold_uncertainty_score":0.017930567},"labels":[],"label_agreement":null},{"id":"W4408221340","doi":"10.1029/2024ms004404","title":"Impacts of Predicted Liquid Fraction and Multiple Ice‐Phase Categories on the Simulation of Hail in the Predicted Particle Properties (P3) Microphysics Scheme","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric aerosols and clouds","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":"Environment and Climate Change Canada","funders":"","keywords":"Particle (ecology); Phase (matter); Environmental science; Meteorology; Fraction (chemistry); Atmospheric sciences; Mechanics; Materials science; Geology; Physics; Chemistry; Chromatography","score_opus":0.016484105343254195,"score_gpt":0.26386838567350374,"score_spread":0.24738428033024953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408221340","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9891242,0.00007701505,0.0055714636,0.00021012651,0.00004452943,0.00006863344,0.0003589267,0.00017057508,0.0043744915],"genre_scores_gemma":[0.9955974,0.000027447237,0.0038253656,0.0000569922,0.000006153702,0.000035693218,0.0001669345,0.000023315724,0.00026062503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997694,0.00008239538,0.00001225718,0.000029091612,0.000041741412,0.0000651155],"domain_scores_gemma":[0.9987166,0.0007547616,0.00012874822,0.00010653548,0.00015982136,0.00013368917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008968867,0.0005172056,0.0005013379,0.0002748105,0.0005222763,0.0007573875,0.0011500705,0.0010627052,0.0013728837],"category_scores_gemma":[0.0025701334,0.00025477944,0.000697662,0.00028951452,0.00079165265,0.0005478491,0.0007259453,0.0011383183,0.00012601893],"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":[0.00018715677,0.000111228386,0.0071648527,0.000030512349,0.000027386302,0.00009651035,0.000035044486,0.9865443,0.002498138,0.0010647906,0.00023212539,0.0020079776],"study_design_scores_gemma":[0.000040736897,0.000094017574,0.0010216852,0.0000049404052,0.0000069626244,0.000007957234,0.000018077422,0.9974667,0.0010897783,0.000106654,0.00013526285,0.0000071928484],"about_ca_topic_score_codex":0.02402602,"about_ca_topic_score_gemma":0.00997551,"teacher_disagreement_score":0.02402602,"about_ca_system_score_codex":0.0007970037,"about_ca_system_score_gemma":0.0012994318,"threshold_uncertainty_score":0.047772348},"labels":[],"label_agreement":null},{"id":"W4408307428","doi":"10.1029/2024ms004276","title":"Sensitivity to Sea Ice Thickness Parameters in a Coupled Ice‐Ocean Data Assimilation System","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","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":false,"ca_institutions":"University of Manitoba","funders":"European Research Council; Horizon 2020 Framework Programme; Natural Environment Research Council; Met Office; European Space Agency; Norges Forskningsråd; Sight Research UK","keywords":"Data assimilation; Sea ice; Sensitivity (control systems); Climatology; Environmental science; Sea ice thickness; Assimilation (phonology); Geology; Sea ice concentration; Oceanography; Atmospheric sciences; Meteorology; Remote sensing; Cryosphere; Geography","score_opus":0.024732928688617997,"score_gpt":0.2711457379503684,"score_spread":0.2464128092617504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408307428","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970893,0.00005446861,0.0017297341,0.00009368724,0.000023331831,0.000017319953,0.00030684166,0.00009230867,0.0005929749],"genre_scores_gemma":[0.99863714,0.000019517329,0.00082506594,0.00003176343,0.0000028051033,0.000011625689,0.00036436645,0.00000966681,0.00009794168],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957734,0.00014587739,0.00004013638,0.000111350215,0.000064093656,0.00006116461],"domain_scores_gemma":[0.998345,0.001063392,0.00010529007,0.0001549792,0.00025061934,0.000080623286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001914726,0.00075641804,0.0005829536,0.00026804474,0.0006127458,0.001150432,0.00060781924,0.0010561016,0.0004972246],"category_scores_gemma":[0.004167253,0.0005899534,0.0010550579,0.00033410973,0.00046670812,0.0008487748,0.0006341726,0.0007837841,0.00009389682],"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":[0.00033099044,0.00012903119,0.034573007,0.000037215457,0.00027264294,0.00006219491,0.000058990678,0.95527154,0.005638596,0.00023079733,0.00021867108,0.003176322],"study_design_scores_gemma":[0.000055910954,0.00012553432,0.015462367,0.00000939923,0.00007273945,0.00001131178,0.00003346134,0.9805047,0.0033740173,0.00018215523,0.00014225906,0.000026095879],"about_ca_topic_score_codex":0.07856159,"about_ca_topic_score_gemma":0.03293375,"teacher_disagreement_score":0.07856159,"about_ca_system_score_codex":0.0012341293,"about_ca_system_score_gemma":0.0009077953,"threshold_uncertainty_score":0.15620863},"labels":[],"label_agreement":null},{"id":"W4408308408","doi":"10.1029/2024ms004383","title":"Water Mass Transformation Budgets in Finite‐Volume Generalized Vertical Coordinate Ocean Models","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":6,"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":"Transformation (genetics); Coordinate system; Finite volume method; Volume (thermodynamics); Water mass; Mechanics; Geology; Geodesy; Geometry; Mathematics; Physics; Oceanography; Thermodynamics","score_opus":0.010528451120060124,"score_gpt":0.22538830173598753,"score_spread":0.2148598506159274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408308408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82806826,0.00017776535,0.15360418,0.000608072,0.000059715556,0.00007889396,0.0010981786,0.0018688417,0.014436083],"genre_scores_gemma":[0.98413384,0.00006031893,0.014247045,0.000047703463,0.0000090274425,0.000048603386,0.00035084662,0.0001633438,0.00093933474],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981207,0.00006673,0.000012445927,0.000025058831,0.00005645474,0.000027256598],"domain_scores_gemma":[0.9994599,0.00023814612,0.00008401755,0.00006580786,0.00012258957,0.000029491332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006116859,0.00046511838,0.00033007312,0.0005292784,0.00031434596,0.00085345993,0.0011535513,0.00066375645,0.0011548855],"category_scores_gemma":[0.0034721373,0.00027037578,0.00043975297,0.00044817544,0.0007048055,0.00097040535,0.0009241866,0.0004817765,0.0001258706],"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":[0.000022182752,0.000015002588,0.0036023986,0.000017224025,0.0000112315765,0.000038307233,0.000036671947,0.98518455,0.0018108963,0.00653635,0.00021402708,0.0025112464],"study_design_scores_gemma":[0.0000073348815,0.0000070108904,0.000382946,0.0000035937683,0.0000025589718,0.0000027602985,0.000009302007,0.9976768,0.0005572846,0.0011320482,0.00021482859,0.0000035037626],"about_ca_topic_score_codex":0.02586122,"about_ca_topic_score_gemma":0.01047081,"teacher_disagreement_score":0.02586122,"about_ca_system_score_codex":0.001110193,"about_ca_system_score_gemma":0.00083291443,"threshold_uncertainty_score":0.051421404},"labels":[],"label_agreement":null},{"id":"W4408341660","doi":"10.1029/2023ms004192","title":"Reducing Long‐Standing Surface Ozone Overestimation in Earth System Modeling by High‐Resolution Simulation and Dry Deposition Improvement","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Environment and Climate Change Canada","funders":"National Natural Science Foundation of China","keywords":"Deposition (geology); Ozone; Environmental science; High resolution; Atmospheric sciences; Earth surface; Meteorology; Remote sensing; Geology; Earth science; Geomorphology; Physics","score_opus":0.006940186662023127,"score_gpt":0.23744474814637667,"score_spread":0.23050456148435355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408341660","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9441074,0.00090353936,0.044759892,0.0010555813,0.00024220021,0.000114315444,0.002530354,0.0017239576,0.0045626187],"genre_scores_gemma":[0.98245066,0.00016630198,0.015629422,0.00013803232,0.000042376738,0.00006187887,0.0010557871,0.000117113224,0.0003383052],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964345,0.0001586541,0.000033138633,0.0000763679,0.00004726035,0.000041115516],"domain_scores_gemma":[0.9991141,0.00032572736,0.00010639073,0.00016918055,0.00019651171,0.000088155684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014757224,0.00078227196,0.0007965265,0.00036031034,0.0004152916,0.0008302634,0.0013208054,0.0007941679,0.0014630152],"category_scores_gemma":[0.0027369952,0.0003788222,0.0011393505,0.00054982625,0.00033445455,0.0008551361,0.0009925191,0.0011025066,0.00019375075],"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":[0.00010666527,0.0001826418,0.021398513,0.00011387979,0.00021958629,0.00007127782,0.000055563494,0.9643844,0.0042195423,0.0009056368,0.001091841,0.007250434],"study_design_scores_gemma":[0.00011037487,0.000036418012,0.004259143,0.000009309067,0.0000428864,0.000006833586,0.000016037251,0.993493,0.001093768,0.00031509006,0.00060179137,0.000015355554],"about_ca_topic_score_codex":0.027328106,"about_ca_topic_score_gemma":0.015495863,"teacher_disagreement_score":0.027328106,"about_ca_system_score_codex":0.0006274652,"about_ca_system_score_gemma":0.0010338732,"threshold_uncertainty_score":0.054338098},"labels":[],"label_agreement":null},{"id":"W4408389320","doi":"10.1029/2024ms004379","title":"Benchmark Framework for Global River Models","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"New Energy and Industrial Technology Development Organization; Google","keywords":"Benchmark (surveying); Computer science; Climatology; Environmental science; Geology; Geodesy","score_opus":0.013788017339373937,"score_gpt":0.2828322716202503,"score_spread":0.26904425428087636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408389320","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006758009,0.00043810607,0.97469103,0.00033181466,0.0001335236,0.000277287,0.0019727997,0.0028645778,0.012532915],"genre_scores_gemma":[0.2915667,0.00084729673,0.6906225,0.00025787385,0.00020224668,0.0017707708,0.0090473695,0.0013842923,0.0043009543],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99406296,0.0031685887,0.00043921886,0.0004755311,0.0015602179,0.0002935552],"domain_scores_gemma":[0.99005145,0.0036166667,0.0006581629,0.0015156873,0.0037942573,0.00036379963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012622434,0.0016022536,0.0013886192,0.0036268202,0.0009760365,0.0041292557,0.0037137999,0.0012897347,0.008678274],"category_scores_gemma":[0.02829464,0.00057862647,0.001485571,0.003329392,0.0009543639,0.0034555132,0.0035712097,0.0022598323,0.0014724411],"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":[0.000080061516,0.00008176026,0.0017354367,0.00017407823,0.000093034054,0.00009147288,0.00006160556,0.7257167,0.0004969704,0.22304752,0.0069190366,0.041502398],"study_design_scores_gemma":[0.000014748643,0.000032164084,0.00014818762,0.000044669636,0.000011041862,0.0000123896025,0.000022234963,0.94173425,0.00032983202,0.051397868,0.0062432745,0.000009306945],"about_ca_topic_score_codex":0.012812766,"about_ca_topic_score_gemma":0.008469055,"teacher_disagreement_score":0.012812766,"about_ca_system_score_codex":0.0026722613,"about_ca_system_score_gemma":0.0035945058,"threshold_uncertainty_score":0.06675458},"labels":[],"label_agreement":null},{"id":"W4408547139","doi":"10.1029/2025ms005079","title":"Thank You to Our 2024 Peer Reviewers","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Scientific Computing and Data Management","field":"Decision 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":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science","score_opus":0.10863423343021489,"score_gpt":0.44306037882303906,"score_spread":0.33442614539282417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408547139","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":"evaluation","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":"evaluation","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009741817,0.009586678,0.007034486,0.25230813,0.69755256,0.0010969865,0.0028660002,0.0042777504,0.024303244],"genre_scores_gemma":[0.01374407,0.011417948,0.019040046,0.13636868,0.368016,0.0026143594,0.004655009,0.006154761,0.4379891],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9668315,0.008225405,0.003309134,0.0041247066,0.016060298,0.0014490036],"domain_scores_gemma":[0.41984627,0.012875902,0.010973584,0.010453108,0.5215426,0.024308434],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.024667073,0.0021625236,0.0030679477,0.0055093523,0.004919739,0.017289244,0.003151451,0.006492454,0.15725905],"category_scores_gemma":[0.22590773,0.0012558127,0.0018422673,0.003301931,0.0017229855,0.0076133483,0.004399338,0.0072059156,0.24918939],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015546888,0.0000046950554,0.00013664407,0.000060684728,0.000005461953,0.000038298538,0.00003665033,0.000013444217,0.00007070765,0.00012846051,0.9891403,0.010349041],"study_design_scores_gemma":[0.00001946369,0.000013717186,0.0003747212,0.00015373695,0.000013435397,0.0001632235,0.00024909744,0.00010209532,0.00011235307,0.0006240284,0.99813473,0.000039461833],"about_ca_topic_score_codex":0.004210171,"about_ca_topic_score_gemma":0.008602748,"teacher_disagreement_score":0.9753329,"about_ca_system_score_codex":0.0028936712,"about_ca_system_score_gemma":0.011080794,"threshold_uncertainty_score":0.52608395},"labels":[],"label_agreement":null},{"id":"W4408642999","doi":"10.1029/2024ms004666","title":"Evaluating Near‐Surface Wind Speeds Simulated by the CRCM6‐GEM5 Model Using AmeriFlux Data Over North America","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","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":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Meteorology; Environmental science; Wind speed; Climatology; Atmospheric sciences; Computer science; Geology; Geography","score_opus":0.10488644341978452,"score_gpt":0.3627651263345798,"score_spread":0.25787868291479527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408642999","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966338,0.00006551779,0.0005382532,0.00006536232,0.000011994183,0.000014836201,0.0012118157,0.00019710173,0.0012613283],"genre_scores_gemma":[0.99650973,0.000028134984,0.001441519,0.000016984719,0.0000027483013,0.000010478901,0.001686822,0.00001686949,0.00028675303],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965405,0.00008012109,0.000018928957,0.00008000282,0.0000812265,0.00008561777],"domain_scores_gemma":[0.99928504,0.00018948306,0.000049103164,0.00006110632,0.00031083386,0.00010450466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011896573,0.00082642655,0.0005288031,0.00049924257,0.00084405794,0.0006669997,0.0014039176,0.0008512553,0.0011129874],"category_scores_gemma":[0.0018660786,0.0003265528,0.0007219032,0.0009363596,0.00048912014,0.00049180415,0.00038597916,0.00054897665,0.00016326734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036948913,0.00015556127,0.071169995,0.0000639336,0.00011763553,0.000101582,0.00011094891,0.9173181,0.0025962926,0.00034697916,0.000987096,0.0066623874],"study_design_scores_gemma":[0.00013489428,0.00012117426,0.06621106,0.000013083239,0.00004774982,0.000021937441,0.000198851,0.9300977,0.0019983007,0.00008803417,0.0010227166,0.00004448146],"about_ca_topic_score_codex":0.8701368,"about_ca_topic_score_gemma":0.81057537,"teacher_disagreement_score":0.8701368,"about_ca_system_score_codex":0.0046089157,"about_ca_system_score_gemma":0.0037616806,"threshold_uncertainty_score":0.26125592},"labels":[],"label_agreement":null},{"id":"W4409178341","doi":"10.1029/2024ms004644","title":"A Complete Three‐Moment Representation of Ice in the Predicted Particle Properties (P3) Microphysics Scheme","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Environment and Climate Change Canada","funders":"National Science Foundation","keywords":"Scheme (mathematics); Moment (physics); Representation (politics); Particle (ecology); Statistical physics; Atmospheric sciences; Meteorology; Physics; Environmental science; Geology; Classical mechanics; Mathematics; Mathematical analysis; Oceanography","score_opus":0.025353555444138986,"score_gpt":0.261464442402237,"score_spread":0.236110886958098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409178341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17647852,0.00016487173,0.8050487,0.00022705848,0.0001042338,0.0001678115,0.001081903,0.0012861517,0.015440807],"genre_scores_gemma":[0.8905131,0.00012559394,0.10527423,0.00007678473,0.000052958658,0.0001980426,0.0006048189,0.0002264137,0.0029278754],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991846,0.000014465182,0.0000061210485,0.0000130549,0.000032064203,0.000015855865],"domain_scores_gemma":[0.9997942,0.000042802658,0.000030404995,0.000059531907,0.000054232445,0.000018916213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002890448,0.00040981217,0.00032646753,0.00030962715,0.0003630148,0.000593595,0.0010277017,0.0005166619,0.002197848],"category_scores_gemma":[0.0004939448,0.0002653135,0.00072552206,0.00023437504,0.0002437982,0.00072052074,0.00045973607,0.0006649262,0.00043104333],"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":[0.00006522143,0.000056816116,0.0033765691,0.000043281994,0.000024953084,0.00012816707,0.000053431046,0.9261724,0.013695675,0.028163139,0.0011917553,0.02702866],"study_design_scores_gemma":[0.000005788731,0.000014484136,0.00034183427,0.0000021785845,0.0000028652332,0.000016308653,0.000002902917,0.9958692,0.0009427727,0.001716095,0.0010800343,0.0000054215475],"about_ca_topic_score_codex":0.004797215,"about_ca_topic_score_gemma":0.002296704,"teacher_disagreement_score":0.004797215,"about_ca_system_score_codex":0.00052482216,"about_ca_system_score_gemma":0.00091002183,"threshold_uncertainty_score":0.009538591},"labels":[],"label_agreement":null},{"id":"W4409769353","doi":"10.1029/2024ms004441","title":"Modeling Thermal and Biogeochemical Dynamics in Two Ponds Within Alaska's Yukon–Kuskokwim Delta: Impacts of Climatic Variability on Greenhouse Gas Fluxes","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate change and permafrost","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":"Gordon and Betty Moore Foundation; National Science Foundation","keywords":"Biogeochemical cycle; Environmental science; Delta; Greenhouse gas; Atmospheric sciences; Climatology; Hydrology (agriculture); Earth science; Oceanography; Environmental chemistry; Geology; Chemistry","score_opus":0.018913071086666972,"score_gpt":0.2785762291939196,"score_spread":0.25966315810725266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409769353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992567,0.000008506106,0.00043805837,0.0000109332805,0.0000018118421,0.000005079596,0.00005159069,0.000013916188,0.00021339334],"genre_scores_gemma":[0.999355,0.000010084553,0.00045240356,0.0000030903743,6.964621e-7,0.000008790427,0.000058140395,0.0000018029399,0.00010978634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99992895,0.000012638891,0.0000065042996,0.000024079305,0.0000075288463,0.000020277506],"domain_scores_gemma":[0.9998004,0.00008143743,0.000028004319,0.000018937793,0.000032521628,0.00003875502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023443202,0.00034734132,0.00034177367,0.00030418986,0.00073651696,0.0007857756,0.00057160575,0.00082953234,0.0007751476],"category_scores_gemma":[0.00039796034,0.0003398335,0.0006623404,0.00040484642,0.0006212821,0.0005484928,0.0005364492,0.00034500775,0.00005336314],"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":[0.00013129048,0.00015358813,0.0798632,0.000028950672,0.00006157805,0.00022354722,0.000099302124,0.9101985,0.006684069,0.00025144522,0.000092118746,0.00221243],"study_design_scores_gemma":[0.000027611675,0.000067067296,0.032960773,0.000004354916,0.00002710123,0.0000133153335,0.00023311388,0.9656394,0.000786201,0.0001363187,0.000091695394,0.000013021914],"about_ca_topic_score_codex":0.092799895,"about_ca_topic_score_gemma":0.07459505,"teacher_disagreement_score":0.092799895,"about_ca_system_score_codex":0.0015845719,"about_ca_system_score_gemma":0.0012044453,"threshold_uncertainty_score":0.18451947},"labels":[],"label_agreement":null},{"id":"W4409957745","doi":"10.1029/2024ms004697","title":"Addressing Challenges in Simulating Inter–Annual Variability of Gross Primary Production","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","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":"McMaster University; McGill University; University of British Columbia","funders":"Fonds Wetenschappelijk Onderzoek; Svenska Forskningsrådet Formas; Swedish National Space Agency","keywords":"Primary (astronomy); Production (economics); Primary production; Environmental science; Computer science; Climatology; Geology; Economics; Physics; Ecosystem; Macroeconomics","score_opus":0.031350181834053886,"score_gpt":0.28467909015344905,"score_spread":0.25332890831939514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409957745","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9739832,0.00007626995,0.023773989,0.00016520265,0.000015569569,0.000016491575,0.0002807267,0.00015701559,0.0015314167],"genre_scores_gemma":[0.9957146,0.000020415375,0.003944842,0.000022258535,0.0000038064757,0.00001046461,0.00013569341,0.00002120172,0.0001267874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996699,0.00016438583,0.000019675956,0.00007166659,0.00003939034,0.000034962268],"domain_scores_gemma":[0.99873465,0.00079023995,0.00011891978,0.00017513966,0.00013092483,0.00005009506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016375412,0.00037310546,0.00038378887,0.00026088493,0.00026170356,0.00072447467,0.00082020246,0.0007209706,0.00046664607],"category_scores_gemma":[0.0032307259,0.00037125783,0.00057671755,0.00033005988,0.0003884468,0.0009216566,0.00039129858,0.00076925376,0.00010246729],"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":[0.000018060395,0.000023933851,0.0063576233,0.000009548278,0.000027317445,0.000008908781,0.00001309421,0.9910615,0.0005455752,0.00027792988,0.000077862926,0.0015787751],"study_design_scores_gemma":[0.000007631884,0.000014060148,0.0024977804,0.0000023102375,0.0000060082025,0.000004050728,0.000012522898,0.9964071,0.00052247907,0.00040615944,0.00011538357,0.0000044910657],"about_ca_topic_score_codex":0.030272787,"about_ca_topic_score_gemma":0.01766623,"teacher_disagreement_score":0.030272787,"about_ca_system_score_codex":0.0009208118,"about_ca_system_score_gemma":0.0009947867,"threshold_uncertainty_score":0.06019312},"labels":[],"label_agreement":null},{"id":"W4411236305","doi":"10.1029/2024ms004849","title":"Inclusion of Biomass Burning Plume Injection Height in GEOS‐Chem‐TOMAS: Global‐Scale Implications for Atmospheric Aerosols and Radiative Forcing","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":1,"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","funders":"Nuclear Safety and Security Commission; National Science Foundation; Government of Canada; Ocean Frontier Institute; Canada First Research Excellence Fund; National Aeronautics and Space Administration","keywords":"Radiative forcing; Biomass burning; Plume; Radiative transfer; Atmospheric sciences; Forcing (mathematics); Environmental science; Scale (ratio); Inclusion (mineral); Climatology; Meteorology; Aerosol; Geology; Physics; Mineralogy; Optics","score_opus":0.008737545940527041,"score_gpt":0.26048094494766916,"score_spread":0.2517433990071421,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411236305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98866886,0.00020407635,0.003341478,0.0009698111,0.00019375366,0.00004850225,0.0014463709,0.0004749354,0.0046522147],"genre_scores_gemma":[0.99751043,0.00006213501,0.0015640551,0.000110522196,0.000019397758,0.000016810205,0.00036359858,0.00005937939,0.0002935572],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980503,0.00006700055,0.000013323371,0.000035224137,0.00003346315,0.000045884273],"domain_scores_gemma":[0.9995197,0.0001672323,0.000053225413,0.00006108297,0.00009803413,0.000100668854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066055765,0.0010727559,0.0005192462,0.0002653388,0.00063615304,0.0011411828,0.0011233933,0.0015537669,0.0017302107],"category_scores_gemma":[0.0012865363,0.00045270214,0.001072028,0.00052275375,0.0006447432,0.0009264673,0.0007465969,0.001379264,0.00017455315],"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":[0.00033707332,0.00028216923,0.027646791,0.00005796225,0.0002353474,0.00014883843,0.000036154426,0.95419633,0.011625958,0.0013565639,0.0010318934,0.0030449291],"study_design_scores_gemma":[0.000176007,0.000075487216,0.009769224,0.000008710082,0.000056927016,0.000011018633,0.00003750476,0.9859955,0.0029885143,0.00036020612,0.00049628265,0.000024524972],"about_ca_topic_score_codex":0.060730234,"about_ca_topic_score_gemma":0.029380709,"teacher_disagreement_score":0.060730234,"about_ca_system_score_codex":0.0012633511,"about_ca_system_score_gemma":0.0014470945,"threshold_uncertainty_score":0.12075347},"labels":[],"label_agreement":null},{"id":"W4411749825","doi":"10.1029/2024ms004742","title":"A Model‐Independent Strategy for the Targeted Observation Analysis and Its Application in ENSO Prediction","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"El Niño Southern Oscillation; Climatology; Environmental science; Computer science; Meteorology; Geology; Geography","score_opus":0.02362390853547186,"score_gpt":0.26273745743660026,"score_spread":0.2391135489011284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411749825","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05173041,0.00007514694,0.94684786,0.00006306078,0.000020873524,0.00003565915,0.000049838774,0.00023963366,0.00093752233],"genre_scores_gemma":[0.8517608,0.00007182579,0.1470924,0.000056378958,0.00003015194,0.00013640984,0.00019320525,0.000040293457,0.00061858824],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992151,0.0002537176,0.000036180434,0.00022981646,0.00020014214,0.00006498383],"domain_scores_gemma":[0.9992054,0.00024280514,0.000100786645,0.0001386685,0.00026767314,0.000044700944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009252531,0.0006290942,0.00052458263,0.0004319571,0.00051469036,0.0004407657,0.0006678298,0.00041104874,0.00075582037],"category_scores_gemma":[0.0027679421,0.0003588088,0.0007302768,0.0003507215,0.00033067248,0.0009792658,0.0010046402,0.0006498115,0.00014683789],"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":[0.00021073736,0.00022109237,0.008252681,0.000055204873,0.00012609712,0.0000993269,0.00016008495,0.8022602,0.022397906,0.010926157,0.00095682766,0.15433358],"study_design_scores_gemma":[0.000005418022,0.00002754812,0.0004744149,0.00000177971,0.000010661634,0.000005716893,0.0000066409903,0.9969447,0.0014629916,0.0008774262,0.0001774602,0.0000052647206],"about_ca_topic_score_codex":0.008422172,"about_ca_topic_score_gemma":0.007040416,"teacher_disagreement_score":0.008422172,"about_ca_system_score_codex":0.00038743994,"about_ca_system_score_gemma":0.0010222874,"threshold_uncertainty_score":0.016746283},"labels":[],"label_agreement":null},{"id":"W4413303252","doi":"10.1029/2024ms004577","title":"Parameter Optimization for Global Soil Carbon Simulations: Not a Simple Problem","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Soil and Unsaturated Flow","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Environment and Climate Change Canada; University of Victoria; Université de Montréal; Ouranos","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Simple (philosophy); Computer science; Environmental science; Mathematical optimization; Mathematics","score_opus":0.013255615434573677,"score_gpt":0.2649570699606789,"score_spread":0.25170145452610526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413303252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50568503,0.00095956697,0.47639555,0.002327906,0.00009380141,0.00023010385,0.0011552157,0.001899477,0.01125341],"genre_scores_gemma":[0.88708085,0.0001954717,0.11066388,0.00028192438,0.000020734016,0.00020072836,0.0004674417,0.00035824522,0.0007308644],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942267,0.00035392397,0.000024414618,0.00006357103,0.000080399106,0.00005501693],"domain_scores_gemma":[0.996167,0.0030874866,0.0001659834,0.00022415655,0.0002787187,0.00007654596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003596706,0.0010823745,0.0009597555,0.00068672193,0.00050693133,0.0010355089,0.0009888348,0.0011341695,0.0022557138],"category_scores_gemma":[0.009473786,0.0006002528,0.00091277505,0.0006096654,0.00067332626,0.0011888982,0.0009892993,0.0014755271,0.00024259918],"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":[0.000021427742,0.000020459016,0.0010867667,0.00003037914,0.00003688384,0.000014604942,0.000018777546,0.9930188,0.00046950582,0.0011996536,0.00024038626,0.0038422907],"study_design_scores_gemma":[0.000014588721,0.000014335504,0.00022536649,0.0000132899095,0.00000958506,0.0000047110775,0.00001924395,0.9969688,0.000584726,0.0016679771,0.00047080911,0.000006500028],"about_ca_topic_score_codex":0.012247526,"about_ca_topic_score_gemma":0.01140404,"teacher_disagreement_score":0.012247526,"about_ca_system_score_codex":0.0009426258,"about_ca_system_score_gemma":0.0010390729,"threshold_uncertainty_score":0.02435249},"labels":[],"label_agreement":null},{"id":"W4415651676","doi":"10.1029/2024ms004733","title":"Parameter Estimation in Land Surface Models: Challenges and Opportunities With Data Assimilation and Machine Learning","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Inversa Systems (Canada); Western University","funders":"H2020 Marie Skłodowska-Curie Actions; Lawrence Berkeley National Laboratory; Lawrence Livermore National Laboratory; Horizon 2020 Framework Programme; Academy of Finland; U.S. Department of Energy; European Commission; National Aeronautics and Space Administration; National Centre for Earth Observation; Pacific Northwest National Laboratory; UK Research and Innovation; HORIZON EUROPE Framework Programme; National Center for Atmospheric Research; National Science Foundation","keywords":"Leverage (statistics); Data assimilation; Earth system science; Climate change; Estimation theory; Climate model; Ecosystem model; Earth observation","score_opus":0.0659667731173006,"score_gpt":0.26110158988835125,"score_spread":0.19513481677105066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415651676","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032620385,0.0076764994,0.94679195,0.008995512,0.00028843113,0.00004483537,0.0003363359,0.0007836113,0.002462375],"genre_scores_gemma":[0.5598965,0.008007765,0.4282979,0.00089569925,0.0008385613,0.00018250347,0.0006170628,0.00024272874,0.0010212851],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984143,0.0008750877,0.0001107357,0.00023861178,0.0003103291,0.00005098792],"domain_scores_gemma":[0.98747754,0.009096045,0.00057109917,0.0015731063,0.0011321208,0.00015020989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069074812,0.0007463383,0.0010117876,0.00079177856,0.0004579179,0.0023940783,0.0011308251,0.0014583769,0.0007808998],"category_scores_gemma":[0.022289116,0.0006506271,0.0008126724,0.0013619518,0.001659779,0.0036730673,0.002287257,0.0032814636,0.000336855],"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":[0.000051301577,0.00007554973,0.008343443,0.00031310163,0.00029288168,0.000053935164,0.00020534039,0.7875209,0.0023470432,0.03755352,0.0030570955,0.16018586],"study_design_scores_gemma":[0.000005050457,0.000010675311,0.0005779989,0.00004847331,0.00000926839,0.000008400792,0.00004155524,0.95952195,0.00052291027,0.036631633,0.0026045395,0.00001767265],"about_ca_topic_score_codex":0.009591965,"about_ca_topic_score_gemma":0.006572532,"teacher_disagreement_score":0.009591965,"about_ca_system_score_codex":0.0008757363,"about_ca_system_score_gemma":0.0014101268,"threshold_uncertainty_score":0.036530674},"labels":[],"label_agreement":null},{"id":"W4415768585","doi":"10.1029/2025ms004961","title":"How Spatial Resolutions Impact the Large‐Scale River Hydrodynamic Model Simulations: Analysis Focuses on Model Physics","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Flood Risk Assessment and Management","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 Waterloo","funders":"New Energy and Industrial Technology Development Organization; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Floodplain; Downscaling; Flood myth; Range (aeronautics); Benchmark (surveying); Discharge; Hydrology (agriculture); Hydrological modelling; Bifurcation","score_opus":0.011206670553284429,"score_gpt":0.2914581208076562,"score_spread":0.28025145025437176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415768585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98628926,0.0002246532,0.009179588,0.00040718217,0.000045683522,0.000029917674,0.00058015983,0.00025840936,0.0029850758],"genre_scores_gemma":[0.99626154,0.00007108167,0.0031127797,0.000056796936,0.000008865838,0.000014866939,0.00029498918,0.000051145744,0.00012773159],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991549,0.00034563648,0.000100952195,0.0001604922,0.00014221614,0.0000957274],"domain_scores_gemma":[0.99515706,0.0031816044,0.00032080951,0.0006309184,0.0005510749,0.00015857899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021892763,0.00046558084,0.0003479158,0.00045968674,0.00036690704,0.00122561,0.0008506265,0.0005680034,0.0011601322],"category_scores_gemma":[0.011590537,0.00036089888,0.0005979078,0.00081273785,0.00046467147,0.0014106742,0.0007058935,0.0006423839,0.00017394772],"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":[0.00014841442,0.00015971635,0.10546207,0.00007855223,0.00017347977,0.000117664844,0.000116189134,0.8753856,0.005077373,0.0018769001,0.0009029302,0.01050123],"study_design_scores_gemma":[0.000054532087,0.000040851563,0.020665366,0.0000296084,0.00006019377,0.00002862736,0.00017365119,0.9716921,0.005286874,0.0010585577,0.000882912,0.000026857266],"about_ca_topic_score_codex":0.020131107,"about_ca_topic_score_gemma":0.012616731,"teacher_disagreement_score":0.020131107,"about_ca_system_score_codex":0.0006399436,"about_ca_system_score_gemma":0.0006641412,"threshold_uncertainty_score":0.040027857},"labels":[],"label_agreement":null},{"id":"W4416039221","doi":"10.1029/2024ms004905","title":"MERCURY: A Fast and Versatile Multi‐Resolution Based Global Emulator of Compound Climate Hazards","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Fonds de recherche du Québec; Agence Nationale de la Recherche; European Cooperation in Science and Technology","keywords":"Emulation; Climate model; Probabilistic logic; Downscaling; Compounding; Quantile; Relative humidity","score_opus":0.014489984684098081,"score_gpt":0.2835019801882739,"score_spread":0.2690119955041758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416039221","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11709909,0.00009579427,0.85228264,0.00017389149,0.00007528141,0.00007235504,0.001171889,0.024003873,0.005025265],"genre_scores_gemma":[0.6979892,0.00009788806,0.29350507,0.00015363736,0.000031307023,0.00017286174,0.0021748475,0.0031906893,0.002684504],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988794,0.0000301313,0.000005458371,0.000021379725,0.000042014766,0.000013049497],"domain_scores_gemma":[0.9997845,0.00008149285,0.000020227451,0.000051445397,0.00004082669,0.00002145674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005081529,0.00058810855,0.00030665006,0.00038839717,0.00016950173,0.00043010645,0.001076573,0.0005433226,0.0048190923],"category_scores_gemma":[0.0013278099,0.0002298549,0.00040623604,0.00036611911,0.00018980807,0.0005426536,0.00080904365,0.00060843106,0.000874724],"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":[0.0003006023,0.00007951286,0.0051404336,0.00008084592,0.00013048522,0.00019640436,0.00016772877,0.8803943,0.017911924,0.0070371577,0.009936455,0.078624144],"study_design_scores_gemma":[0.000015725442,0.00001727723,0.00041978748,0.0000035580717,0.0000051560824,0.000018072431,0.000008471849,0.9913276,0.00461868,0.0009663568,0.0025914055,0.00000804916],"about_ca_topic_score_codex":0.0021771768,"about_ca_topic_score_gemma":0.0018953453,"teacher_disagreement_score":0.0048190923,"about_ca_system_score_codex":0.00033083046,"about_ca_system_score_gemma":0.00036655582,"threshold_uncertainty_score":0.016121507},"labels":[],"label_agreement":null},{"id":"W4416280700","doi":"10.1029/2025ms005177","title":"Atmospheric Feedbacks Reverse the Sensitivity of Modeled Photosynthesis to Stomatal Function","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Science Foundation Graduate Research Fellowship Program; U.S. Department of Energy; Biological and Environmental Research; National Science Foundation","keywords":"Photosynthesis; Carbon dioxide in Earth's atmosphere; Atmosphere (unit); Carbon dioxide; Water vapor; Terrestrial plant; Carbon cycle; Atmospheric model; Sensitivity (control systems)","score_opus":0.005060810439404053,"score_gpt":0.21295698062211188,"score_spread":0.20789617018270784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416280700","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99710685,0.000024292092,0.0015679593,0.00007731637,0.000009944907,0.0000040514205,0.00021672397,0.000041245938,0.0009516282],"genre_scores_gemma":[0.9996141,0.0000103319335,0.00019253056,0.000015279249,8.828454e-7,0.0000025583183,0.00006468318,0.000006837241,0.00009284987],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998989,0.000024730778,0.000007213634,0.000036526377,0.000011037255,0.000021462962],"domain_scores_gemma":[0.999749,0.00012628925,0.00002998763,0.000036589157,0.000033660675,0.000024420258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001907535,0.000233231,0.0002407108,0.0001038756,0.0002838352,0.0005049709,0.00051034644,0.00035535052,0.0012981807],"category_scores_gemma":[0.00094702333,0.00017130836,0.00046070624,0.00017453585,0.00036567054,0.00045619346,0.0003121816,0.00053848175,0.0000736468],"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":[0.00016537223,0.00009075125,0.037048984,0.000072870556,0.00013488744,0.000059082027,0.00006240878,0.9180596,0.03922081,0.001781491,0.0004564572,0.0028473765],"study_design_scores_gemma":[0.000055919256,0.00008180747,0.02704599,0.000006200068,0.00006269095,0.00001999228,0.00006466661,0.9638809,0.0072948704,0.00087495294,0.000591141,0.000020826545],"about_ca_topic_score_codex":0.03587008,"about_ca_topic_score_gemma":0.021852799,"teacher_disagreement_score":0.03587008,"about_ca_system_score_codex":0.0007602485,"about_ca_system_score_gemma":0.0004860703,"threshold_uncertainty_score":0.07132256},"labels":[],"label_agreement":null},{"id":"W4416827581","doi":"10.1029/2024ms004645","title":"The Climatic Impacts of a Satellite‐Based Parameterization of the Wegener‐Bergeron‐Findeisen Process for Large‐Scale Models","year":2025,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":0,"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","keywords":"Cloud computing; Cloud fraction; Cloud cover; Cloud top; Ice cloud; Satellite; Liquid water content; Scaling; Cloud height","score_opus":0.01337308156163268,"score_gpt":0.2805747887029294,"score_spread":0.2672017071412967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416827581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96058077,0.00029555586,0.03403955,0.0003958507,0.000106167296,0.0000734999,0.00073900144,0.001053075,0.0027165054],"genre_scores_gemma":[0.99167514,0.000052554817,0.0075235944,0.00004015129,0.000015118144,0.000033712025,0.00039036974,0.00012027933,0.00014901946],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958354,0.00020284917,0.000028849783,0.00007562886,0.00007223759,0.00003695994],"domain_scores_gemma":[0.99780554,0.0013024855,0.00019241714,0.00034832174,0.0002573083,0.00009395584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001687104,0.0008197637,0.00042357272,0.0002193249,0.00038059536,0.00075865415,0.00093890826,0.00069153955,0.0006434341],"category_scores_gemma":[0.0041301437,0.00036441718,0.0007460002,0.00040137468,0.00049275666,0.0010126353,0.000615203,0.0010968684,0.00012284197],"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":[0.00019051529,0.00011068786,0.015108669,0.000027095133,0.000091024,0.000029692414,0.000017890558,0.97358626,0.0053474545,0.00073933456,0.00033549021,0.0044158194],"study_design_scores_gemma":[0.000048916118,0.00004942207,0.004785026,0.0000064384953,0.000022367085,0.000005746606,0.000009582761,0.991727,0.0027269186,0.00025810793,0.0003435761,0.000016883207],"about_ca_topic_score_codex":0.02430041,"about_ca_topic_score_gemma":0.013082182,"teacher_disagreement_score":0.02430041,"about_ca_system_score_codex":0.0009156199,"about_ca_system_score_gemma":0.0006995682,"threshold_uncertainty_score":0.04831791},"labels":[],"label_agreement":null}]}