{"id":"W2958061626","doi":"10.3390/su11143924","title":"Mapping Obesogenic Food Environments in South Africa and Ghana: Correlations and Contradictions","year":2019,"lang":"en","type":"article","venue":"Sustainability","topic":"Obesity, Physical Activity, Diet","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"University of the Western Cape; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; International Development Research Centre","keywords":"Poverty; Environmental health; Food consumption; Obesity; Neighbourhood (mathematics); Consumption (sociology); Socioeconomics; Urbanization; Low income; Geography; Economic growth; Agricultural economics; Medicine; Economics; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001927249,0.0001256458,0.0002670802,0.00009496759,0.00007875181,0.00001388045,0.00003503662,0.00008065549,0.00003100522],"category_scores_gemma":[0.0002630641,0.00012293,0.00004657543,0.0001935359,0.000172432,0.0001283763,0.0000969453,0.0002514045,0.000009966564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004200283,"about_ca_system_score_gemma":0.00008598368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003332106,"about_ca_topic_score_gemma":0.00001846766,"domain_scores_codex":[0.9989779,0.00007281166,0.000177911,0.0003560332,0.0001439058,0.0002714256],"domain_scores_gemma":[0.9993421,0.0001468432,0.00004471899,0.0002857223,0.00004267993,0.0001378891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002010059,0.001129543,0.9933094,0.0001472736,0.00003079845,0.000003681016,0.002943153,0.000008369443,0.00008959293,0.001986365,0.00000662403,0.0003250823],"study_design_scores_gemma":[0.001182823,0.000271586,0.9830255,0.00001602093,0.00003645212,0.000003690088,0.00411925,0.000617393,0.00002471209,0.009957937,0.0006377587,0.0001069037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972814,0.0002090406,0.00008756033,0.0005909616,0.00004067952,0.0009805305,0.00001425998,0.00002769357,0.000767823],"genre_scores_gemma":[0.9992681,0.000004746926,0.00004190374,0.0000298415,0.00002710329,0.00003187612,0.000006028351,0.0000110752,0.0005792987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01028394,"threshold_uncertainty_score":0.5012938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01020002432004663,"score_gpt":0.2265316980155319,"score_spread":0.2163316736954853,"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."}}