{"id":"W4402308573","doi":"10.26633/rpsp.2024.83","title":"Pan American climate resilient health systems: a training course for health professionals","year":2024,"lang":"en","type":"article","venue":"Revista Panamericana de Salud Pública","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Course (navigation); Health professionals; Training (meteorology); Medical education; Psychology; Medicine; Health care; Political science; Engineering; Geography; Meteorology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002569485,0.0003572956,0.0009093531,0.0001382581,0.000586875,0.0002199148,0.0003365839,0.00005723569,0.0002834854],"category_scores_gemma":[0.0001384264,0.0003105385,0.000175937,0.001171879,0.0003114986,0.0001607556,0.0001373671,0.0003189498,0.0002085806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001812497,"about_ca_system_score_gemma":0.0009205328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004780291,"about_ca_topic_score_gemma":0.0004462895,"domain_scores_codex":[0.9953279,0.0004476619,0.0009015018,0.0008157113,0.000551959,0.001955286],"domain_scores_gemma":[0.9973006,0.0003958225,0.0005381161,0.0005474014,0.00002151453,0.001196517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001113657,0.0002971652,0.006456919,0.003634153,0.00006949953,0.00003134872,0.01060364,0.0001348216,0.0001435383,0.003444836,0.6140811,0.3609916],"study_design_scores_gemma":[0.0003372888,0.00143179,0.02505932,0.002167401,0.00003964376,0.00007020566,0.008637629,0.008496963,0.000002323036,0.00006233389,0.9531366,0.0005584805],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2633759,0.0654683,0.01117853,0.6279868,0.002216296,0.01615643,0.005554742,0.002704,0.005359029],"genre_scores_gemma":[0.96046,0.005988744,0.002977103,0.02840972,0.0005217352,0.0007195532,0.0002371689,0.0001581204,0.0005278514],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6970841,"threshold_uncertainty_score":0.9999347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06840137635789408,"score_gpt":0.4155194365748813,"score_spread":0.3471180602169872,"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."}}