{"id":"W4244278363","doi":"10.1002/9781119386230.app1","title":"Appendix 1: Growth Charts and Body Mass Index (BMI) Charts","year":2019,"lang":"en","type":"other","venue":"","topic":"Birth, Development, and Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Medicine; General hospital; Library science; Family medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002095504,0.001054319,0.0006129483,0.005122519,0.0005713179,0.001372526,0.001149075,0.0007156811,0.3257512],"category_scores_gemma":[0.02717114,0.0005061525,0.000442119,0.006912154,0.0002217851,0.001046736,0.000783254,0.001632789,0.1296882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001546368,"about_ca_system_score_gemma":0.003158312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03026853,"about_ca_topic_score_gemma":0.0203437,"domain_scores_codex":[0.998733,0.0002901171,0.0002886415,0.0001179095,0.0004808381,0.00008950943],"domain_scores_gemma":[0.9822855,0.006011901,0.00142966,0.0008424654,0.008750109,0.0006803595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001351615,0.00009800701,0.004045086,0.0002138134,0.000006415322,0.00005580204,0.00005315267,0.0003994596,0.00006217561,0.00163877,0.9526629,0.04062914],"study_design_scores_gemma":[0.0001762281,0.00007936129,0.03726591,0.0006588747,0.00001469249,0.0003201503,0.0002338674,0.0008994463,0.0003132149,0.004443911,0.9555306,0.00006372895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.002406345,0.0003913126,0.003893637,0.0009485976,0.0003850508,0.001020604,0.9355907,0.001917386,0.05344633],"genre_scores_gemma":[0.01467156,0.002420544,0.02794847,0.001036609,0.0003098162,0.005191754,0.864475,0.001512432,0.08243376],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3257512,"threshold_uncertainty_score":0.9617341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589324029489149,"score_gpt":0.2679426355533416,"score_spread":0.2520493952584502,"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."}}