{"id":"W4312143581","doi":"10.1016/j.childyouth.2022.106796","title":"Decomposing the gap in undernutrition among under-five children between EAG and non-EAG states of India","year":2022,"lang":"en","type":"article","venue":"Children and Youth Services Review","topic":"Child Nutrition and Water Access","field":"Nursing","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Underweight; Wasting; Malnutrition; Environmental health; Quarter (Canadian coin); Medicine; Socioeconomics; Demography; Geography; Economics; Overweight; Body mass index","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00151328,0.0004215895,0.0006204699,0.003980564,0.0003753777,0.001561917,0.0006802824,0.0003197558,0.0009618175],"category_scores_gemma":[0.002599051,0.0002127311,0.001025945,0.005345946,0.0004284126,0.0008797445,0.001189905,0.0008785035,0.00007256036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002183667,"about_ca_system_score_gemma":0.009861383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09338564,"about_ca_topic_score_gemma":0.2025094,"domain_scores_codex":[0.9993626,0.0001515265,0.0001217575,0.00004968423,0.0001249064,0.0001895909],"domain_scores_gemma":[0.9985675,0.0005653755,0.0003358559,0.00002417044,0.0003584321,0.0001486964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006498753,0.0002405606,0.5316528,0.03601674,0.003456285,0.001063434,0.007066598,0.001287737,0.0008866626,0.009305944,0.01255146,0.395822],"study_design_scores_gemma":[0.00004393499,0.0003747107,0.8889871,0.01828848,0.004300607,0.0009809592,0.02361393,0.0005946766,0.000489386,0.001054116,0.06121618,0.00005599012],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3452182,0.6363894,0.0003746363,0.008072813,0.0008929319,0.00007662804,0.002185449,0.00001807983,0.006771727],"genre_scores_gemma":[0.7463576,0.2503678,0.0005842649,0.0009227845,0.0002081135,0.00005747658,0.001072229,0.000005597147,0.0004241984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09338564,"threshold_uncertainty_score":0.1856841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01222993914903898,"score_gpt":0.2603170316862334,"score_spread":0.2480870925371945,"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."}}