{"id":"W2819693789","doi":"10.1007/s12665-018-7701-2","title":"Performance of multi-model ensembles for the simulation of temperature variability over Ontario, Canada","year":2018,"lang":"en","type":"article","venue":"Environmental Earth Sciences","topic":"Climate variability and models","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Natural Environment Research Council; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy","keywords":"Downscaling; Climate model; Mean radiant temperature; Climate change; Climatology; Environmental science; Ensemble average; Meteorology; Geography; Precipitation; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000738576,0.0001125302,0.000133666,0.00001178748,0.0003535085,0.000009899143,0.0002983805,0.00004771228,0.001555998],"category_scores_gemma":[0.00003574755,0.00007663018,0.00004857982,0.0001014546,0.001436881,0.0002320677,0.0001350803,0.00006567011,0.00000360741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001057681,"about_ca_system_score_gemma":0.0001058084,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.246737,"about_ca_topic_score_gemma":0.6502923,"domain_scores_codex":[0.9987646,0.00003165739,0.0002620781,0.0003049597,0.0004234847,0.0002131638],"domain_scores_gemma":[0.9993087,0.0002577566,0.0001276246,0.0002569871,0.000004728692,0.00004421476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003045644,0.00007779454,0.2559757,0.000008476933,0.00000442322,2.871215e-8,0.000725935,0.7064684,0.03632896,0.00001496696,0.00003215521,0.0003327224],"study_design_scores_gemma":[0.000160398,0.0001240255,0.2654465,0.000005513049,0.00001007997,3.153751e-7,0.00006187672,0.7238621,0.009736196,0.00004936584,0.0004657636,0.00007786768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984065,0.000008040539,0.0005202612,0.00004004872,0.0001014463,0.0003507102,0.0000666078,0.000004027735,0.000502325],"genre_scores_gemma":[0.9970619,0.000006613198,0.002471159,0.00008708727,0.00001413691,0.00000975662,0.000003924087,0.000004147056,0.0003412926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4035554,"threshold_uncertainty_score":0.9993567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01839862907638899,"score_gpt":0.2308110988790353,"score_spread":0.2124124698026463,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}