{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008724831,0.0006703032,0.0006718007,0.006811196,0.003260757,0.005192621,0.002989527,0.0008213695,0.002167329],"category_scores_gemma":[0.08255848,0.0004995717,0.00053373,0.01762781,0.001689903,0.001709202,0.003965644,0.0008207263,0.0007340757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01212836,"about_ca_system_score_gemma":0.01363062,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.926315,"about_ca_topic_score_gemma":0.9535174,"domain_scores_codex":[0.9872341,0.003272698,0.001145673,0.002494878,0.004675515,0.001177221],"domain_scores_gemma":[0.9504613,0.01381711,0.005374471,0.005927946,0.02288506,0.001534129],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002393266,0.00009711228,0.9301245,0.0005963771,0.0003803474,0.0002069839,0.005808816,0.002442068,0.0007183603,0.00363978,0.01877762,0.03696863],"study_design_scores_gemma":[0.00005282675,0.00003654965,0.9203175,0.0006986035,0.0001177708,0.0001443074,0.0131668,0.01074361,0.001291984,0.001256726,0.05207632,0.00009692329],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8692272,0.001499538,0.006311245,0.002002783,0.0001445569,0.0005592071,0.09604085,0.0004774411,0.0237372],"genre_scores_gemma":[0.8900284,0.0004100589,0.00744744,0.0003613092,0.00002963997,0.0004545119,0.0990218,0.0001943448,0.002052492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9912752,"threshold_uncertainty_score":0.1482378,"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."}}