{"id":"W3196787998","doi":"10.1186/s41043-021-00262-x","title":"Call for emergency action to limit global temperature increases, restore biodiversity, and protect health","year":2021,"lang":"en","type":"editorial","venue":"Journal of Health Population and Nutrition","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Medical Association","funders":"","keywords":"Global health; Harm; Summit; Global warming; Natural disaster; Political science; Action (physics); China; Development economics; Economic growth; Climate change; Health care; Geography; Economics; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.001096228,0.0001833672,0.0004912055,0.0001128154,0.00051452,0.00004883433,0.00006580551,0.0003558089,0.00004496942],"category_scores_gemma":[0.0003791147,0.0001757569,0.00007171589,0.0002159261,0.0000166417,0.0002518002,0.00005936547,0.0003773776,0.000002212425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001297467,"about_ca_system_score_gemma":0.0001687644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004523646,"about_ca_topic_score_gemma":0.004288147,"domain_scores_codex":[0.9978989,0.0002373149,0.0007494022,0.0002686347,0.0005244083,0.0003213194],"domain_scores_gemma":[0.9981728,0.00006256358,0.0009975005,0.00009337826,0.0001206588,0.0005530614],"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":[0.0003301823,0.0001292971,0.005802509,0.001567093,0.000005958831,0.000002316177,0.0001532335,0.000002490305,0.00001438362,0.000001449498,0.983627,0.008364149],"study_design_scores_gemma":[0.001988501,0.00341844,0.1162358,0.001661039,0.00003850425,0.00005386389,0.0003033762,0.00001335732,0.000002744133,0.0003854112,0.8756336,0.000265354],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"editorial","genre_scores_codex":[0.4886287,0.020732,0.0001986424,0.09900049,0.3825915,0.005575672,0.003204426,0.00005435832,0.00001416804],"genre_scores_gemma":[0.04597056,0.2071411,0.0075573,0.008602808,0.7229234,0.0001549852,0.007359525,0.00008940986,0.0002009317],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.4426582,"threshold_uncertainty_score":0.7167159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06452393707198037,"score_gpt":0.382224146107874,"score_spread":0.3177002090358937,"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."}}