{"id":"W2970203934","doi":"10.1001/jamapediatrics.2019.2740","title":"Leveraging Omics Profiling to Advance the Treatment of Pediatric Obesity","year":2019,"lang":"en","type":"article","venue":"JAMA Pediatrics","topic":"Obesity, Physical Activity, Diet","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Omics; Profiling (computer programming); Obesity; Bioinformatics; Computational biology; Data science; Pathology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001966239,0.0002287704,0.0004569688,0.0001477875,0.0000741359,0.0000253503,0.0001868565,0.0001025138,0.00001871732],"category_scores_gemma":[0.000171244,0.0001615884,0.0001929287,0.0007736917,0.00002358411,0.0001432673,0.00009619763,0.0002276526,0.0002151832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002533921,"about_ca_system_score_gemma":0.0001436499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004678641,"about_ca_topic_score_gemma":0.000002518083,"domain_scores_codex":[0.9984109,0.00005009463,0.0003068677,0.0003837075,0.0004791732,0.0003692375],"domain_scores_gemma":[0.9983722,0.0004524588,0.0001751059,0.0006243621,0.0001975715,0.0001783256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007316583,0.003969585,0.9921591,0.0002296438,0.00002236749,0.000009140318,0.0005217221,0.000190294,0.0004362975,0.0003120412,0.0002432123,0.001833482],"study_design_scores_gemma":[0.002345931,0.001738724,0.9799986,0.00001033748,0.0005519055,0.000007585022,0.0002979185,0.0007095364,0.01051006,0.0004929976,0.003010608,0.0003257241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960991,0.0004382514,0.00008803332,0.0006966945,0.0004481937,0.001132532,0.00002758897,0.00006601538,0.001003559],"genre_scores_gemma":[0.994065,0.0008762593,0.001937223,0.0002743391,0.002287471,0.00002476736,0.00001619924,0.00003536335,0.0004833338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01216038,"threshold_uncertainty_score":0.6589382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01609157698509762,"score_gpt":0.2689824032238572,"score_spread":0.2528908262387596,"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."}}