{"meta":{"query_hash":"6c268607d80e","filters":{"venue":"Asia-Pacific Journal of Atmospheric Sciences"},"cohort_total":8,"direct_labels_cover":0,"predictions_cover":8,"exported":8,"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/6c268607d80e","api":"https://metacan.xera.ac/api/v1/cohort?venue=Asia-Pacific+Journal+of+Atmospheric+Sciences"},"results":[{"id":"W1482996580","doi":"","title":"Sources of Errors in Precipitation Measurements by Polarimetric Radar","year":2007,"lang":"en","type":"article","venue":"Asia-Pacific Journal of Atmospheric Sciences","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Polarimetry; Drop (telecommunication); Precipitation; Radar; Scattering; Random error; Environmental science; Remote sensing; Mathematics; Meteorology; Physics; Geology; Statistics; Optics; Computer science","score_opus":0.028425065803558698,"score_gpt":0.2496115122215243,"score_spread":0.22118644641796562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1482996580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98519415,0.0046895216,0.0014875173,0.00017772742,0.00037910749,0.00008572384,0.000004234335,0.0000066447933,0.007975356],"genre_scores_gemma":[0.9817699,0.00009667091,0.017966338,0.000020550844,0.000049418355,9.733743e-8,0.0000031731913,0.0000025918646,0.000091258036],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99683607,0.00016919996,0.00089647446,0.00020319448,0.0015471589,0.00034793004],"domain_scores_gemma":[0.9983632,0.00026284647,0.0008874186,0.000097214295,0.0002464467,0.00014285759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006348021,0.00014377409,0.00032060244,0.00016245517,0.00014555384,0.000064825574,0.00051297137,0.00006066062,0.00040640123],"category_scores_gemma":[0.0003986106,0.00010912243,0.00013104729,0.0032186806,0.00026259315,0.0007777354,0.0000067946476,0.00015620771,0.000011737615],"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":[0.000046763358,0.00005267594,0.9626617,0.000006758068,0.00003486048,0.0000036944532,0.00060474966,0.0018543417,0.0017351124,0.0000050030812,0.0003092116,0.032685157],"study_design_scores_gemma":[0.000567461,0.00058946555,0.9797443,0.00006752276,0.00005342466,0.000017766124,0.011458435,0.0007886729,0.0054963585,0.0004168914,0.00060185743,0.00019783826],"about_ca_topic_score_codex":0.0008047768,"about_ca_topic_score_gemma":0.00052077975,"teacher_disagreement_score":0.03248732,"about_ca_system_score_codex":0.000022325154,"about_ca_system_score_gemma":0.00016184842,"threshold_uncertainty_score":0.44498837},"labels":[],"label_agreement":null},{"id":"W1979003302","doi":"10.1007/s13143-014-0035-4","title":"Statistical properties of effective drought index (EDI) for Seoul, Busan, Daegu, Mokpo in South Korea","year":2014,"lang":"en","type":"article","venue":"Asia-Pacific Journal of Atmospheric Sciences","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Alberta Water Research Institute","keywords":"Index (typography); Statistical analysis; Geography; Statistics; Computer science; Mathematics; World Wide Web","score_opus":0.00893786782898532,"score_gpt":0.22953857562288427,"score_spread":0.22060070779389895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979003302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9664051,0.0002009979,0.027270118,0.00031166716,0.00020502685,0.00022734188,0.0000034576476,0.00000750884,0.0053687925],"genre_scores_gemma":[0.9872015,0.000015641677,0.012481972,0.000046451336,0.00007068516,0.000012208219,5.275858e-7,0.000008588398,0.00016243423],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99769956,0.00024723093,0.0006396183,0.00033131908,0.0006309886,0.00045129398],"domain_scores_gemma":[0.998796,0.00034929285,0.0005025678,0.00016885444,0.00005117435,0.00013210716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025546525,0.00018459563,0.0004981541,0.000026906368,0.00020084273,0.000038728635,0.000555124,0.00010954557,0.00027952032],"category_scores_gemma":[0.0005386262,0.00012502044,0.00013675736,0.000931928,0.0016481203,0.00045002226,0.000090303016,0.00021937767,0.000021235472],"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":[0.00045229684,0.00037693852,0.91840595,0.000045636825,0.00010799151,0.000019686087,0.0068082465,0.03980272,0.0048731933,0.00081085745,0.00088411104,0.027412392],"study_design_scores_gemma":[0.0050665,0.0073341504,0.5854193,0.00037641672,0.00047450865,0.00026068473,0.0247771,0.32644802,0.017324911,0.02341707,0.0076916334,0.0014097206],"about_ca_topic_score_codex":0.0001515725,"about_ca_topic_score_gemma":0.000097784716,"teacher_disagreement_score":0.33298665,"about_ca_system_score_codex":0.000086041415,"about_ca_system_score_gemma":0.00006997911,"threshold_uncertainty_score":0.6072568},"labels":[],"label_agreement":null},{"id":"W2002097689","doi":"10.1007/s13143-012-0004-8","title":"Pollutant dispersion characteristics in Dhaka city, Bangladesh","year":2012,"lang":"en","type":"article","venue":"Asia-Pacific Journal of Atmospheric Sciences","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"U.S. Environmental Protection Agency","keywords":"Environmental science; Pollutant; Air quality index; Air pollution; Particulates; Pollution; Air pollutant concentrations; Atmospheric sciences; Environmental engineering; Air pollutants; Environmental protection; Meteorology; Geography; Chemistry","score_opus":0.025542808443949842,"score_gpt":0.2627603174241917,"score_spread":0.23721750898024185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002097689","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98954386,0.00026300005,0.00040033506,0.00047806004,0.0011598492,0.000056025805,0.0000014378975,0.00001136644,0.0080860555],"genre_scores_gemma":[0.98881674,0.00007583605,0.010500611,0.000029158786,0.0003375826,7.9779755e-7,2.2012617e-7,0.000008060505,0.00023101644],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99787164,0.000106053136,0.0005547414,0.000176644,0.00074758846,0.00054331747],"domain_scores_gemma":[0.9990598,0.000116811345,0.0004528693,0.0001263145,0.000014970205,0.00022925418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002397546,0.00014913596,0.00025547575,0.000014515576,0.00023251513,0.000070767535,0.00045485215,0.00006459552,0.00069455506],"category_scores_gemma":[0.00020159682,0.00011207987,0.00008900219,0.00084131083,0.0004974741,0.0008852325,0.0001300235,0.0002560211,0.00006694296],"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":[0.000015398975,0.00012233204,0.95459086,0.0000034613643,0.0000053260824,0.00001271122,0.0020441087,0.00014466852,0.0015222011,0.00003894646,0.0003885745,0.041111387],"study_design_scores_gemma":[0.00034317732,0.00041588096,0.9734765,0.00013597595,0.000024184645,0.000323815,0.014317154,0.0020716225,0.00088744605,0.00026025248,0.0073978174,0.00034613846],"about_ca_topic_score_codex":0.00007397195,"about_ca_topic_score_gemma":0.0000034087518,"teacher_disagreement_score":0.04076525,"about_ca_system_score_codex":0.00018337391,"about_ca_system_score_gemma":0.000035448487,"threshold_uncertainty_score":0.7604891},"labels":[],"label_agreement":null},{"id":"W2295310777","doi":"10.1007/s13143-016-0002-3","title":"Diurnal and seasonal variations of meteorology and aerosol concentrations in the foothills of the nepal himalayas (Nagarkot: 1,900 m asl)","year":2016,"lang":"en","type":"article","venue":"Asia-Pacific Journal of Atmospheric Sciences","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria; Environment and Climate Change Canada","funders":"University of Manchester; Natural Environment Research Council; Sight Research UK","keywords":"Aerosol; Morning; Atmospheric sciences; Katabatic wind; Monsoon; Diurnal temperature variation; Environmental science; Seasonality; Sea breeze; Climatology; Meteorology; Geography; Geology","score_opus":0.010275329173333694,"score_gpt":0.21124908987446736,"score_spread":0.20097376070113365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295310777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9920508,0.0012014154,0.00038126486,0.003303492,0.00022269158,0.00011014282,0.000022036564,0.0000022309976,0.0027058695],"genre_scores_gemma":[0.9955565,0.00028624135,0.0039660977,0.000058489553,0.000068654015,5.888304e-7,3.7547736e-7,0.0000016874176,0.00006137499],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998373,0.0002109939,0.000521309,0.00017193641,0.00047914177,0.00024366756],"domain_scores_gemma":[0.99823284,0.0008603792,0.00059240835,0.00013423532,0.00009571747,0.000084432846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011938945,0.00012418567,0.00025878006,0.0000037338434,0.00024390826,0.000046673147,0.0005015443,0.00006310834,0.0002707993],"category_scores_gemma":[0.0002718892,0.000055487402,0.000080454214,0.00054916827,0.0015625549,0.00035977483,0.000020158537,0.00015936609,6.0581203e-7],"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":[0.000051086347,0.00004562098,0.9789083,0.000010637118,0.000035101915,0.000005862403,0.0011537722,0.00044969475,0.00655559,0.000718341,0.00017774504,0.011888232],"study_design_scores_gemma":[0.00094278296,0.00063653087,0.9829749,0.00013243296,0.000070242924,0.0006171668,0.0060524484,0.0019535248,0.0031978702,0.002723328,0.0005268688,0.00017193898],"about_ca_topic_score_codex":0.000102772094,"about_ca_topic_score_gemma":0.00011201467,"teacher_disagreement_score":0.011716293,"about_ca_system_score_codex":0.0000056355507,"about_ca_system_score_gemma":0.00026976553,"threshold_uncertainty_score":0.57572985},"labels":[],"label_agreement":null},{"id":"W4321240477","doi":"10.1007/s13143-023-00317-5","title":"Extreme Weather and Climate Events: Dynamics, Predictability and Ensemble Simulations","year":2023,"lang":"en","type":"article","venue":"Asia-Pacific Journal of Atmospheric Sciences","topic":"Meteorological Phenomena and Simulations","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":"Predictability; Environmental science; Climatology; Extreme weather; Climate change; Meteorology; Geography; Statistics; Mathematics; Geology; Oceanography","score_opus":0.030344022094051588,"score_gpt":0.24530252182247184,"score_spread":0.21495849972842024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321240477","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935055,0.0007163148,0.00040297455,0.0007606447,0.0002481355,0.00010178431,0.000030372734,0.00002670214,0.004207578],"genre_scores_gemma":[0.9952611,0.00042140827,0.0040746615,0.000027321781,0.00005777193,2.3291354e-7,0.0000055236965,0.0000023057653,0.00014968477],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856883,0.00012281298,0.0003915748,0.00023304144,0.00036752445,0.0003162114],"domain_scores_gemma":[0.9988683,0.0005717012,0.00020322163,0.00010157625,0.000071232025,0.0001839943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012875346,0.00011772537,0.00021569215,0.000026170037,0.00046182898,0.00009073414,0.00018769923,0.00005121599,0.0005505787],"category_scores_gemma":[0.0002145908,0.00007917619,0.00004720312,0.0007483863,0.00040968249,0.0004741798,0.000024735406,0.000121672376,0.000020459775],"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":[0.000018484327,0.000014473591,0.95850986,0.000008030959,0.000011673378,0.0000070828523,0.0002636226,0.024858529,0.000024497689,0.00025061602,0.00004737561,0.015985778],"study_design_scores_gemma":[0.00017719418,0.00030616758,0.7095593,0.000011877105,0.000017299417,0.00003277781,0.0019606664,0.2779909,0.0000015606464,0.0096000815,0.00025176696,0.000090394984],"about_ca_topic_score_codex":0.000053518055,"about_ca_topic_score_gemma":0.00019824319,"teacher_disagreement_score":0.25313237,"about_ca_system_score_codex":0.0000070450646,"about_ca_system_score_gemma":0.000050127943,"threshold_uncertainty_score":0.6028451},"labels":[],"label_agreement":null},{"id":"W4382345429","doi":"10.1007/s13143-023-00328-2","title":"Estimating Probabilities of Extreme ENSO Events from Copernicus Seasonal Hindcasts","year":2023,"lang":"en","type":"article","venue":"Asia-Pacific Journal of Atmospheric Sciences","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":"Hindcast; Climatology; Environmental science; Statistics; El Niño Southern Oscillation; Extreme value theory; Variance (accounting); La Niña; Econometrics; Meteorology; Mathematics; Geography; Economics; Geology","score_opus":0.04051056949202308,"score_gpt":0.2601357460230832,"score_spread":0.21962517653106012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382345429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9934804,0.000108708155,0.0005606186,0.0005548359,0.00063152256,0.00013660522,0.000014958056,0.000027478422,0.0044848947],"genre_scores_gemma":[0.94239485,0.000036236095,0.05714666,0.000016860915,0.00008230225,0.0000033274096,0.0000015338112,0.000009541793,0.00030868352],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99722993,0.00014615232,0.0007132669,0.00034142745,0.0011573605,0.00041186096],"domain_scores_gemma":[0.9985586,0.0004370958,0.0005682906,0.00022131369,0.00005441537,0.00016030083],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002085684,0.00017673013,0.00035426437,0.0000130686685,0.00024258264,0.00005322055,0.0007041132,0.00006772975,0.002518336],"category_scores_gemma":[0.0004273695,0.00013369191,0.00015825151,0.0010030722,0.00082825543,0.0006889863,0.00022146002,0.00017702642,0.00012291904],"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":[0.00011078874,0.00043193984,0.6183945,0.000056987632,0.000080254205,0.000048101483,0.009294322,0.31372562,0.018005399,0.00023180374,0.0030824437,0.03653783],"study_design_scores_gemma":[0.001505546,0.0014463671,0.2577072,0.0005932259,0.000116482974,0.00020778163,0.024118153,0.65517974,0.002246796,0.053148434,0.00285502,0.00087524677],"about_ca_topic_score_codex":0.0002594407,"about_ca_topic_score_gemma":0.000021038677,"teacher_disagreement_score":0.3606873,"about_ca_system_score_codex":0.00013878863,"about_ca_system_score_gemma":0.0001312156,"threshold_uncertainty_score":0.9983935},"labels":[],"label_agreement":null},{"id":"W4389091243","doi":"10.1007/s13143-023-00344-2","title":"Parameterizations of Snow Cover, Snow Albedo and Snow Density in Land Surface Models: A Comparative Review","year":2023,"lang":"en","type":"review","venue":"Asia-Pacific Journal of Atmospheric Sciences","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":32,"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":"Ministry of Science and ICT, South Korea; National Research Foundation of Korea; Ministry of Education; National Research Foundation","keywords":"Snow; Biosphere; Albedo (alchemy); Atmosphere (unit); Environmental science; Meteorology; Land cover; Climate model; Atmospheric sciences; Climatology; Remote sensing; Land use; Climate change; Geography; Geology","score_opus":0.12688853659980998,"score_gpt":0.32169983258364787,"score_spread":0.1948112959838379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389091243","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026779235,0.9945643,0.00033029448,0.0001944252,0.0005159665,0.0005816586,0.00009236383,0.000013318648,0.0010297308],"genre_scores_gemma":[0.0015914701,0.991406,0.006661471,0.000036928624,0.000059564063,0.000002642333,0.000027777878,0.000009257478,0.00020484303],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964039,0.0003802975,0.0015682173,0.00046248708,0.00074670126,0.0004384494],"domain_scores_gemma":[0.99527436,0.0023176838,0.0017139924,0.0002555328,0.00025771908,0.00018071728],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017562375,0.00042216422,0.0024472363,0.000033395467,0.00030679026,0.000113041446,0.00066914584,0.00013890192,0.00022052533],"category_scores_gemma":[0.00054474006,0.00029012468,0.00034356068,0.00330831,0.00071251125,0.00054571964,0.00006641499,0.00040579162,0.00002601736],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004584052,0.00022491893,0.061003055,0.012490218,0.00082837685,0.00013546206,0.002346688,0.048311744,2.3890453e-7,0.00023755546,0.010458806,0.8639171],"study_design_scores_gemma":[0.0014293315,0.0025298984,0.03323935,0.19113733,0.0031135085,0.0012873468,0.01316654,0.05850937,0.00000199709,0.0029899154,0.68981206,0.0027833383],"about_ca_topic_score_codex":0.000884178,"about_ca_topic_score_gemma":0.0010655089,"teacher_disagreement_score":0.86113375,"about_ca_system_score_codex":0.000027074828,"about_ca_system_score_gemma":0.0006562075,"threshold_uncertainty_score":0.9999551},"labels":[],"label_agreement":null},{"id":"W4414661273","doi":"10.1007/s13143-025-00413-8","title":"Applicability of Reanalysis Data in Analyzing the Occurrence time of Extreme Temperature Events in China","year":2025,"lang":"en","type":"article","venue":"Asia-Pacific Journal of Atmospheric Sciences","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nipissing University","funders":"","keywords":"Extreme Cold; Variation (astronomy); Climate change; Extreme value theory; Frost (temperature); Spatial variability; Extreme weather; Spatial distribution","score_opus":0.021217410420419986,"score_gpt":0.2726154242155935,"score_spread":0.2513980137951735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414661273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961048,0.00030785194,0.00026264667,0.00072249584,0.00006865847,0.00015036824,0.000015367383,0.000002342286,0.0023655007],"genre_scores_gemma":[0.99701446,0.00014422402,0.0027794144,0.000010076294,0.00000635512,0.0000016401829,0.0000017934275,0.0000018170846,0.00004020601],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997639,0.0002602641,0.00091045594,0.0003720686,0.0005805313,0.00023768633],"domain_scores_gemma":[0.99840075,0.00031864402,0.0005255409,0.0006805135,0.00002922948,0.00004530755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058211465,0.00012776516,0.00042255045,0.00003047383,0.00008968887,0.000018323008,0.0017577598,0.000061089646,0.00030423774],"category_scores_gemma":[0.00046224688,0.00008118592,0.00009824393,0.0034648017,0.0008211068,0.00052121823,0.0004014267,0.0002638286,0.0000026147884],"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":[0.000041713072,0.0003220424,0.9580711,0.000023811468,0.000020925336,0.0000017234294,0.0009468044,0.027419826,0.007933693,0.00003907521,0.00016402903,0.0050152377],"study_design_scores_gemma":[0.00057687244,0.00017498169,0.9010652,0.00031987394,0.00009846323,0.000012465042,0.0053428286,0.085459106,0.0009857356,0.0055023064,0.00023324731,0.00022892299],"about_ca_topic_score_codex":0.0005220144,"about_ca_topic_score_gemma":0.00019551771,"teacher_disagreement_score":0.05803928,"about_ca_system_score_codex":0.0001078091,"about_ca_system_score_gemma":0.0001334616,"threshold_uncertainty_score":0.333119},"labels":[],"label_agreement":null}]}