{"id":"W4304128255","doi":"10.3390/meteorology1040027","title":"The Future of Climate Modelling: Weather Details, Macroweather Stochastics—Or Both?","year":2022,"lang":"en","type":"article","venue":"Meteorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Downscaling; Climate model; Stochastic modelling; Generalization; Climate change; Exploit; General Circulation Model; Scale (ratio); Computer science; Statistical mechanics; Econometrics; Meteorology; Statistical physics; Mathematics; Geography; Physics; Statistics; Geology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009132888,0.0001256016,0.0001888215,0.00002033007,0.0004541094,0.000009467109,0.0004322127,0.00006532641,0.008082481],"category_scores_gemma":[0.00001397144,0.00008255448,0.00008301359,0.0001510949,0.0002644299,0.00004493273,0.0005847231,0.0002217205,0.00006457938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007488218,"about_ca_system_score_gemma":0.00001302439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008892546,"about_ca_topic_score_gemma":0.0002046152,"domain_scores_codex":[0.9985721,0.0002354493,0.0002669939,0.0002891256,0.0002340085,0.0004023715],"domain_scores_gemma":[0.9991769,0.0002150157,0.0001111679,0.0004403307,0.00000581124,0.00005077448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001469393,0.0004910755,0.006223216,0.00002328943,0.00009049147,0.00002081334,0.002713213,0.9261031,0.007089715,0.03106669,0.001878171,0.02283085],"study_design_scores_gemma":[0.001144516,0.001058215,0.0007763081,0.000002467383,0.0001160036,0.00007802604,0.00160761,0.4070343,0.0002977273,0.03404262,0.5534084,0.0004338477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670814,0.0005499112,0.01540522,0.002733535,0.000870504,0.0005457493,0.0001167328,0.00006855985,0.01262836],"genre_scores_gemma":[0.9957029,0.0002933059,0.002074452,0.0005032883,0.0000603299,0.0001069152,0.000006053663,0.00002607028,0.001226695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5515302,"threshold_uncertainty_score":0.9928243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01736223877856482,"score_gpt":0.2355105457957744,"score_spread":0.2181483070172096,"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."}}