{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009924639,0.0001445314,0.0002289537,0.00005230506,0.00005615457,0.00001457739,0.0003141066,0.00008935002,0.0001146977],"category_scores_gemma":[0.00005798239,0.0001102036,0.00005243999,0.0002412,0.0001801847,0.00008365648,0.0001088576,0.0001143176,0.000009952015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001367157,"about_ca_system_score_gemma":0.000006929111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001512145,"about_ca_topic_score_gemma":0.0006399741,"domain_scores_codex":[0.9987258,0.0001348914,0.0003051801,0.000252422,0.0003126224,0.0002690721],"domain_scores_gemma":[0.9990025,0.0003657082,0.0001853004,0.0003986217,0.00001594943,0.0000319908],"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":[0.0001392819,0.00121018,0.3973918,0.0002887713,0.000009758132,0.000001333334,0.0006291913,0.5773609,0.006826267,0.005251677,0.00003255674,0.01085832],"study_design_scores_gemma":[0.00029235,0.0002105046,0.1862979,0.00005823423,0.00001475737,4.535381e-7,0.00004729163,0.8116523,0.0006666006,0.0006483427,0.00002499328,0.00008625971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9620758,0.000002641122,0.0352441,0.0002599212,0.00007681811,0.0002969215,0.0001302713,0.0000233054,0.001890231],"genre_scores_gemma":[0.9971675,0.0000215368,0.002494551,0.000109489,0.000007649505,0.00001706845,0.0001669786,0.00001031871,0.000004963145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2342914,"threshold_uncertainty_score":0.4493974,"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."}}