{"id":"W2511376745","doi":"10.1186/s12942-016-0060-x","title":"Do marginalized neighbourhoods have less healthy retail food environments? An analysis using Bayesian spatial latent factor and hurdle models","year":2016,"lang":"en","type":"article","venue":"International Journal of Health Geographics","topic":"Obesity, Physical Activity, Diet","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; University of Waterloo","funders":"Canadian Cancer Society Research Institute; China Scholarship Council","keywords":"Health geography; Geography; Human geography; Spatial ecology; Environmental health; Scale (ratio); Cartography; Medicine; Public health; Economic geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0137524,0.0009781581,0.001756073,0.002778377,0.001836197,0.003278704,0.002752884,0.001515172,0.007310985],"category_scores_gemma":[0.04645898,0.0008524196,0.005768399,0.003569875,0.002805316,0.002374597,0.004198957,0.002327033,0.0005301057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002031245,"about_ca_system_score_gemma":0.002052275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05508827,"about_ca_topic_score_gemma":0.02338343,"domain_scores_codex":[0.9893054,0.00650725,0.0004898906,0.001954491,0.0008159885,0.0009270739],"domain_scores_gemma":[0.9492751,0.03580633,0.007069771,0.003816748,0.001929623,0.002102423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008745223,0.0002998061,0.9645607,0.0001338039,0.001467685,0.0003355913,0.003847069,0.007772137,0.0001551849,0.01018537,0.00103057,0.009337614],"study_design_scores_gemma":[0.0002252766,0.0007404088,0.6923352,0.000270706,0.001543427,0.000777059,0.01136475,0.2536913,0.0001902327,0.03529248,0.00340346,0.0001656615],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978031,0.0004109104,0.01910612,0.0005612005,0.00003045453,0.0001735885,0.0007537334,0.0000537568,0.0008791682],"genre_scores_gemma":[0.9948138,0.00009585477,0.004048326,0.00004228167,0.00001512503,0.000120751,0.0005927986,0.00001429474,0.0002565733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05508827,"threshold_uncertainty_score":0.1095353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06481534642903615,"score_gpt":0.3333636156003204,"score_spread":0.2685482691712843,"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."}}