{"id":"W2978449927","doi":"10.5539/enrr.v9n3p117","title":"Classification and Regression Tree to Predict the Precipitation Labels of North-West Region in Bangladesh","year":2019,"lang":"en","type":"article","venue":"Environment and Natural Resources Research","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cart; Precipitation; Regression; Agriculture; North west; Regression analysis; Geography; Environmental science; Statistics; Physical geography; Mathematics; Meteorology; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008253194,0.00009340107,0.0001105384,0.00008435199,0.0001262263,0.00002530268,0.0001926409,0.00006611629,0.0001062023],"category_scores_gemma":[0.0001601144,0.00005646904,0.00001598915,0.0002796996,0.0003691037,0.0001052929,0.0003411386,0.0003410575,0.00007797329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001015912,"about_ca_system_score_gemma":0.000002231542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001050045,"about_ca_topic_score_gemma":0.0001191421,"domain_scores_codex":[0.9983421,0.0002863253,0.0001780691,0.0003454696,0.0005949146,0.0002531172],"domain_scores_gemma":[0.9992928,0.0003488784,0.00005616244,0.0002203106,0.000004681452,0.00007719905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001401325,0.00003694521,0.9230987,0.00001094387,0.00000244004,0.000001830695,0.001437923,0.0007984896,0.01287818,0.00001214221,0.0002112001,0.06137104],"study_design_scores_gemma":[0.0002170701,0.000254172,0.9870654,0.00004248102,0.000002144504,0.000002240586,0.0000770731,0.006451512,0.0002871459,0.00007944283,0.005455222,0.00006605011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970799,0.0002163873,0.000002525283,0.001425246,0.00001982877,0.0004927371,0.000001338199,0.000007516618,0.0007544935],"genre_scores_gemma":[0.9982845,0.0001756029,0.0001257779,0.00003460789,0.00001753919,0.00001935807,0.000005958532,0.00000760145,0.001329054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06396672,"threshold_uncertainty_score":0.2302741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03918207360926219,"score_gpt":0.2897086108606373,"score_spread":0.2505265372513751,"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."}}