{"id":"W2075578011","doi":"10.1007/s00382-014-2408-x","title":"Fast-track attribution assessments based on pre-computed estimates of changes in the odds of warm extremes","year":2014,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"Pacific Institute for Climate Solutions; University of Victoria","funders":"European Commission; Met Office; Department for Environment, Food and Rural Affairs, UK Government","keywords":"Odds; Climatology; Environmental science; Attribution; Climate change; Climate model; Range (aeronautics); Event (particle physics); Statistics; Geology; Logistic regression; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006150616,0.0008954727,0.0005456359,0.002570635,0.000645044,0.002254362,0.00107593,0.0008878781,0.005837901],"category_scores_gemma":[0.02191981,0.000322793,0.0008481931,0.001837573,0.0002946682,0.003001859,0.00173044,0.001253404,0.001000511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007257077,"about_ca_system_score_gemma":0.0009804107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00487679,"about_ca_topic_score_gemma":0.01004911,"domain_scores_codex":[0.9986808,0.0003314638,0.0001015953,0.0004078494,0.0003393453,0.0001390928],"domain_scores_gemma":[0.9830335,0.008457204,0.002510751,0.001907338,0.00338145,0.000709825],"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":[0.001437653,0.0002645396,0.3165853,0.0002165687,0.0006377735,0.0001733631,0.0002946599,0.5087639,0.002634761,0.008799265,0.008777766,0.1514144],"study_design_scores_gemma":[0.0001011391,0.0002128612,0.1212421,0.00007648934,0.0001383294,0.0001050558,0.0002749057,0.8498886,0.003730055,0.01968142,0.00444829,0.0001008369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.687696,0.0005343208,0.2828389,0.0005987968,0.000691633,0.0001983775,0.009208119,0.002779263,0.01545449],"genre_scores_gemma":[0.9631715,0.0001204526,0.03067938,0.00006315234,0.0001577411,0.00005504138,0.003791658,0.0001218394,0.001839209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006150616,"threshold_uncertainty_score":0.03252798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02021539971392214,"score_gpt":0.2808872037088484,"score_spread":0.2606718039949262,"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."}}