{"id":"W4403668014","doi":"10.1016/j.envint.2024.109096","title":"Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study","year":2024,"lang":"en","type":"article","venue":"Environment International","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"China Scholarship Council; Australian Research Council; Faculty of Medicine, Nursing and Health Sciences, Monash University; Monash University; National Health and Medical Research Council; Centre for Air Pollution, Energy and Health Research; VicHealth","keywords":"Productivity; Economics; Environmental health; Demographic economics; Environmental science; Medicine; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002562324,0.0005397507,0.0006506686,0.001270987,0.0008371283,0.0009749797,0.0007350371,0.000599517,0.001943818],"category_scores_gemma":[0.003769208,0.0006058975,0.00211297,0.00176757,0.0004895022,0.0008361875,0.001473403,0.001154032,0.0002359272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006136622,"about_ca_system_score_gemma":0.0006886891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01030344,"about_ca_topic_score_gemma":0.01324798,"domain_scores_codex":[0.9985656,0.0007087088,0.0001497985,0.0002105515,0.0001000784,0.0002652948],"domain_scores_gemma":[0.9965586,0.0007412746,0.001480563,0.00031376,0.0004094502,0.0004962452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001180338,0.00004683987,0.9967467,0.0001109777,0.0004353408,0.0002730102,0.0004667678,0.0001694422,0.00006637579,0.00006043716,0.0002688719,0.00123725],"study_design_scores_gemma":[0.000008528028,0.0001564364,0.9965719,0.00009815639,0.0002486529,0.0003728413,0.001639773,0.000446414,0.00003062898,0.00006768255,0.0003455878,0.00001335828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971322,0.001148167,0.0003757091,0.0001744798,0.00002075135,0.00002970747,0.0007720074,0.000003539852,0.0003433558],"genre_scores_gemma":[0.9986756,0.0005887597,0.0001751129,0.00005102205,0.00001605697,0.00003414818,0.0003687388,0.000002799853,0.00008778217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01030344,"threshold_uncertainty_score":0.02048695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01911830059906257,"score_gpt":0.3033751965687778,"score_spread":0.2842568959697152,"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."}}