{"id":"W3199780611","doi":"","title":"IMPLICATIONS OF NUTRITIONAL INSECURITY IN PAKISTAN","year":2019,"lang":"en","type":"article","venue":"Advanced Food and Nutritional Sciences","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Food security; Malnutrition; Economic growth; Safeguarding; Millennium Development Goals; Development economics; Population; Developing country; Food insecurity; International community; Business; Environmental health; Political science; Geography; Medicine; Economics; Agriculture","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005669222,0.0001722011,0.0001660857,0.0008406902,0.002208332,0.001570002,0.0002663915,0.0006142412,0.007318429],"category_scores_gemma":[0.002146192,0.0001295553,0.0002605404,0.00116242,0.0009207465,0.0009266964,0.001364775,0.001172746,0.0003174225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001989036,"about_ca_system_score_gemma":0.003669312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05313826,"about_ca_topic_score_gemma":0.0576176,"domain_scores_codex":[0.9995146,0.0001479418,0.00002957936,0.00003979533,0.00006690677,0.0002012043],"domain_scores_gemma":[0.9987919,0.0001734787,0.0003382499,0.00002074838,0.0002269112,0.0004487819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004162744,0.0003139793,0.8590376,0.0005796106,0.0001208051,0.008793646,0.007277646,0.0002973232,0.0004367187,0.007992461,0.02512008,0.08961389],"study_design_scores_gemma":[0.00004111286,0.0002049324,0.9018934,0.001188373,0.00007865793,0.004467843,0.0529031,0.0004078638,0.0001873779,0.008316273,0.03025637,0.00005465431],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.868711,0.01146447,0.0002164725,0.08227027,0.0005502073,0.00004853287,0.002038678,0.00001508236,0.03468523],"genre_scores_gemma":[0.9922234,0.0049953,0.00006094109,0.001855374,0.00008291308,0.000006880245,0.0001597353,0.000001720319,0.0006136218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05313826,"threshold_uncertainty_score":0.1056579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1070452890237383,"score_gpt":0.4691750911561102,"score_spread":0.3621298021323718,"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."}}