{"id":"W4286285099","doi":"10.32866/001c.35619","title":"Validity of Food Outlet Databases from Commercial and Community Science datasets in Vancouver and Montreal","year":2022,"lang":"en","type":"article","venue":"Findings","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Simon Fraser University","funders":"Canadian Institutes of Health Research","keywords":"Consistency (knowledge bases); Geography; Database; Measure (data warehouse); Internal consistency; Computer science; Business; Marketing; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002635112,0.00005346996,0.000136734,0.0001147981,0.00177802,0.00003214116,0.0002908038,0.00001585772,0.0002507337],"category_scores_gemma":[0.0005300161,0.00005929323,0.00001532579,0.0004122049,0.0008469769,0.0002387398,0.0003370541,0.0002514099,5.363303e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007946924,"about_ca_system_score_gemma":0.0001366971,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2755492,"about_ca_topic_score_gemma":0.6444104,"domain_scores_codex":[0.998639,0.0005880237,0.0001442019,0.0001640389,0.0003209648,0.0001437209],"domain_scores_gemma":[0.9990302,0.0006055069,0.00005808278,0.0002183092,0.00002477338,0.00006307474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004419352,0.0005592388,0.8937946,0.00002553845,0.00001747642,0.000002429429,0.09147841,0.0000338846,0.0003268339,0.001760497,0.005583912,0.006373011],"study_design_scores_gemma":[0.0004889701,0.0001177457,0.9537502,0.00001574605,0.00003751916,1.328601e-7,0.03371213,0.0002973549,0.000235534,0.002699406,0.008485517,0.0001597261],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967811,0.00002210459,0.00002750439,0.0001202183,0.00005685479,0.00008570855,0.002525575,0.000008078201,0.0003729046],"genre_scores_gemma":[0.999549,0.00001230173,0.0000503142,0.0000907706,0.00001780448,0.000007764008,0.0002573073,0.00000212335,0.00001260457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3688612,"threshold_uncertainty_score":0.9995216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0637459057259241,"score_gpt":0.3235068053539342,"score_spread":0.2597608996280101,"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."}}