{"id":"W1524121516","doi":"10.1007/bf03405486","title":"The Geography of Overweight in Quebec: A Multilevel Perspective","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Public Health","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Institut National de Santé Publique du Québec","funders":"","keywords":"Overweight; Multilevel model; Obesity; Geography; Perspective (graphical); Odds; Demography; Scale (ratio); Spatial ecology; Multilevel modelling; Logistic regression; Gerontology; Medicine; Cartography; Sociology; Statistics; Computer science; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.000814688,0.0004140299,0.0009235224,0.005425137,0.004346971,0.004054144,0.001551191,0.001158887,0.006069997],"category_scores_gemma":[0.003094125,0.0004309634,0.001432723,0.01316969,0.00182695,0.001731819,0.003204592,0.001441297,0.0002403446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03088871,"about_ca_system_score_gemma":0.023073,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.990289,"about_ca_topic_score_gemma":0.9938648,"domain_scores_codex":[0.9986532,0.0003362277,0.00006519165,0.0001757427,0.0001862874,0.0005832999],"domain_scores_gemma":[0.9976336,0.0004101605,0.0004633322,0.0001466665,0.0007010226,0.0006451992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006222068,0.00009891963,0.9731326,0.0001330051,0.0005540748,0.0003154666,0.0023793,0.002359337,0.0002038623,0.006551093,0.00282023,0.01138992],"study_design_scores_gemma":[0.000005122263,0.00002305015,0.9893165,0.0002266136,0.0001380687,0.00005177671,0.004811515,0.001492564,0.00002818231,0.001068822,0.00280978,0.00002805791],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9588984,0.00715657,0.001367075,0.007690245,0.00007742146,0.0001278572,0.01005368,0.00004930969,0.01457952],"genre_scores_gemma":[0.9956865,0.001751141,0.000447607,0.0002014119,0.00003110813,0.00004245924,0.000840342,0.000009264364,0.0009901809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03088871,"threshold_uncertainty_score":0.2241144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03828531422599703,"score_gpt":0.3277180315754919,"score_spread":0.2894327173494949,"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."}}