{"id":"W2012838005","doi":"10.3329/bjms.v12i2.14943","title":"Gender Differentials In Nutritional Status of Elderly People In Selected Rural Areas of Bangladesh","year":2013,"lang":"en","type":"article","venue":"Bangladesh Journal of Medical Science","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Economics","funders":"","keywords":"Spouse; Medicine; Demography; Anthropometry; Gerontology; Body mass index; Cross-sectional study; Rural area; Population; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001160516,0.0001389999,0.0004910557,0.0007790386,0.00004825934,0.00005814248,0.0007605355,0.0001390819,0.001372363],"category_scores_gemma":[0.001150214,0.0001100362,0.0001023603,0.001822236,0.0004976868,0.0006360877,0.00007905746,0.0004800039,0.00000369531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001710163,"about_ca_system_score_gemma":0.0003843895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006252389,"about_ca_topic_score_gemma":0.0002103751,"domain_scores_codex":[0.9956238,0.0001835636,0.001116341,0.0001809794,0.002329858,0.0005654604],"domain_scores_gemma":[0.9981283,0.0002681366,0.0004344966,0.0001285241,0.0005810145,0.0004595144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003349766,0.001897079,0.9505616,0.0002008217,0.00001584552,0.00003331942,0.002083237,0.00001543771,0.03447636,0.0003023826,0.001548877,0.008530024],"study_design_scores_gemma":[0.003640111,0.0002894905,0.9741989,0.0007009113,0.00001101084,0.0001258825,0.0003687875,0.0004117712,0.01827698,0.001774143,0.00008061978,0.0001213744],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958151,0.0004270215,0.00009405071,0.002942341,0.0003987003,0.0002085556,0.00001039326,0.000006566185,0.00009727202],"genre_scores_gemma":[0.9992256,0.0001377385,0.0003401198,0.0001357012,0.0001386003,0.000004831922,0.000006109524,0.000008435028,0.000002895424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02363728,"threshold_uncertainty_score":0.9995405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01822475680115468,"score_gpt":0.2903023772229664,"score_spread":0.2720776204218117,"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."}}