{"id":"W2787193025","doi":"10.1111/mcn.12557","title":"Nutritional status, food insecurity, and biodiversity among the<scp>K</scp>hasi in<scp>M</scp>eghalaya,<scp>N</scp>orth‐East<scp>I</scp>ndia","year":2017,"lang":"en","type":"article","venue":"Maternal and Child Nutrition","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Medicine; Wasting; Underweight; Malnutrition; Environmental health; Anthropometry; Socioeconomic status; Food security; Population; Public health; Agriculture; Obesity; Geography; Overweight","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":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005838076,0.001006426,0.0009790681,0.0007574947,0.002637436,0.002264303,0.001062811,0.0006657102,0.00001691194],"category_scores_gemma":[0.0007945055,0.000956019,0.00039683,0.0004095129,0.001006181,0.002077611,0.0007539468,0.00129605,0.00009923939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001924861,"about_ca_system_score_gemma":0.00003703257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009250723,"about_ca_topic_score_gemma":0.00067177,"domain_scores_codex":[0.9943987,0.0003823025,0.001015687,0.001453881,0.001136287,0.001613176],"domain_scores_gemma":[0.996255,0.0009597008,0.0008072885,0.000880317,0.0003221855,0.0007754773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008127614,0.001945973,0.9567756,0.001292382,0.0001936155,0.0001717306,0.003728201,0.000004125096,0.0005457868,0.00060697,0.03425874,0.0003956123],"study_design_scores_gemma":[0.009870412,0.0005225292,0.8953905,0.00145215,0.000200703,0.0004058624,0.001902686,0.00009018465,0.01445487,0.01093003,0.06461044,0.0001696638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844115,0.004486092,0.00002254633,0.001736528,0.001339285,0.001608899,0.002345555,0.0002927547,0.003756861],"genre_scores_gemma":[0.9921126,0.003828232,0.0001268404,0.001099572,0.001555604,0.0001356805,0.0007822142,0.00009358779,0.0002656083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06138512,"threshold_uncertainty_score":0.999289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01254179195778948,"score_gpt":0.221547844068022,"score_spread":0.2090060521102325,"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."}}