{"id":"W3022154641","doi":"10.17118/11143/18899","title":"Les impacts des changements climatiques sur la santé au Québec : l’exemple de l’Estrie","year":2019,"lang":"fr","type":"article","venue":"Le climatoscope","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007562411,0.0003320112,0.0002647331,0.0008159854,0.003610329,0.001896141,0.0006158359,0.0006312284,0.009242217],"category_scores_gemma":[0.001771111,0.0001334609,0.0003887146,0.001749072,0.001458454,0.000625479,0.001284307,0.001347711,0.0003491784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04039439,"about_ca_system_score_gemma":0.04810471,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9935788,"about_ca_topic_score_gemma":0.9967754,"domain_scores_codex":[0.9992796,0.0001593079,0.00002108444,0.00007035457,0.0002122906,0.0002574843],"domain_scores_gemma":[0.9983999,0.0001667575,0.0001342648,0.00004843492,0.0009285962,0.0003220364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003840172,0.0002342501,0.5219772,0.002026462,0.0005044767,0.001982194,0.01720607,0.007240226,0.00603936,0.05019182,0.1010117,0.2912022],"study_design_scores_gemma":[0.00002425898,0.0001187518,0.8108019,0.0008813923,0.0001481263,0.0002025075,0.01054469,0.001525625,0.0006688157,0.001682567,0.1733211,0.00008037941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6521328,0.02657367,0.005338657,0.07262249,0.001076132,0.0003106862,0.01524131,0.0002766139,0.2264276],"genre_scores_gemma":[0.9634511,0.008256122,0.001430195,0.003291248,0.0000833736,0.00006981155,0.00117921,0.00002887361,0.02221004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04039439,"threshold_uncertainty_score":0.2930833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04636247674414619,"score_gpt":0.3428744096373804,"score_spread":0.2965119328932342,"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."}}