{"id":"W4389495548","doi":"10.4000/statsoc.501","title":"Pandémie, statistiques et fédéralisme : la COVID au Canada","year":2022,"lang":"fr","type":"article","venue":"Statistique et société","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Humanities; Political science; Coronavirus disease 2019 (COVID-19); Geography; Art; Medicine","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":[0.00354941,0.0002107333,0.0004359282,0.002673095,0.005162985,0.005244028,0.0008284366,0.0008489443,0.006195218],"category_scores_gemma":[0.01242905,0.0002379761,0.0003606795,0.007282577,0.004404109,0.00114528,0.001585046,0.001760174,0.0001659983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08603346,"about_ca_system_score_gemma":0.1541894,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9935136,"about_ca_topic_score_gemma":0.9963135,"domain_scores_codex":[0.9966803,0.0005744239,0.0001529597,0.0003121338,0.001562201,0.0007181074],"domain_scores_gemma":[0.9872114,0.004177748,0.001134617,0.000461034,0.006077263,0.0009379763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003738843,0.00007345205,0.2370434,0.002025661,0.0004240319,0.0009098157,0.0257192,0.002586846,0.001110375,0.3357897,0.126471,0.2674725],"study_design_scores_gemma":[0.00003387794,0.00005959605,0.4653798,0.002231493,0.0002635655,0.0002088296,0.01230199,0.001423553,0.0009165483,0.0154887,0.5015042,0.0001879359],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3022084,0.1229529,0.005612331,0.3049847,0.002464628,0.0001993543,0.01324006,0.0002054541,0.2481322],"genre_scores_gemma":[0.9094894,0.04182671,0.003039652,0.01234617,0.0004162615,0.00007553591,0.002251116,0.00006254006,0.03049269],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08603346,"threshold_uncertainty_score":0.6242194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04419865354446661,"score_gpt":0.3778979706875277,"score_spread":0.3336993171430611,"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."}}