{"id":"W4412565521","doi":"10.1088/2515-7620/adf2f9","title":"Machine-learning unravels spatial shifting in homogeneous rainfall subregions in Central Africa under global warming","year":2025,"lang":"en","type":"article","venue":"Environmental Research Communications","topic":"Climate variability and models","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Alexander von Humboldt-Stiftung","keywords":"Homogeneous; Global warming; Climatology; Environmental science; Geography; Climate change; Geology; Mathematics; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001139591,0.0004868743,0.0003838242,0.0008689173,0.0002841531,0.0008011719,0.0005496874,0.0005435878,0.0005700518],"category_scores_gemma":[0.001640937,0.0002015404,0.0006231916,0.0009295975,0.0004278386,0.0005815995,0.0004425048,0.0003829048,0.0001016348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006387204,"about_ca_system_score_gemma":0.0005856094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03343767,"about_ca_topic_score_gemma":0.02669207,"domain_scores_codex":[0.9998005,0.00006404443,0.00001118312,0.00007280364,0.00001493347,0.0000365456],"domain_scores_gemma":[0.9994519,0.0002415037,0.00009821547,0.00008407539,0.00008780802,0.0000364493],"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":[0.0002905679,0.0001337331,0.1318184,0.0001172026,0.0002407239,0.0001789592,0.0001959241,0.8274468,0.007735457,0.0005706622,0.0007297224,0.03054187],"study_design_scores_gemma":[0.00001654172,0.00003168881,0.06354447,0.00001731741,0.00003446137,0.00001806077,0.0001322216,0.9338604,0.001504694,0.0004285823,0.0003981099,0.00001354845],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950092,0.0001975252,0.00366599,0.0001070127,0.00001484978,0.00001200483,0.000420767,0.0001388223,0.0004338674],"genre_scores_gemma":[0.9974502,0.00003237743,0.002089436,0.00001089932,0.000008191629,0.000005517924,0.0003433067,0.00000762768,0.00005240181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03343767,"threshold_uncertainty_score":0.06648606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0644267526686284,"score_gpt":0.3393432932507438,"score_spread":0.2749165405821154,"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."}}