{"id":"W3097019881","doi":"10.33262/concienciadigital.v3i3.1.1380","title":"Automatización del diagnóstico de índice de masa corporal (IMC) y sus factores de riesgo para la salud. Evaluación antropométrica en universitarios","year":2020,"lang":"es","type":"article","venue":"ConcienciaDigital","topic":"Health and Lifestyle Studies","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Medicine; Gynecology; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.006011663,0.0006825119,0.0006582123,0.002502673,0.0004386895,0.001294803,0.0004963098,0.0005092106,0.001402631],"category_scores_gemma":[0.01028592,0.0004223971,0.0007001524,0.002475591,0.000420106,0.0005795999,0.0008104874,0.0004117649,0.0004240246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007982334,"about_ca_system_score_gemma":0.0009760751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01837817,"about_ca_topic_score_gemma":0.02104375,"domain_scores_codex":[0.9969651,0.001437166,0.0003678433,0.0004603426,0.0005805893,0.0001890356],"domain_scores_gemma":[0.9947544,0.001480991,0.001913085,0.0002832043,0.001376746,0.000191522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002260029,0.00005687618,0.9707499,0.0002291754,0.0001215181,0.00004589469,0.0005911996,0.0001755825,0.001671516,0.00005892816,0.0001686591,0.0259048],"study_design_scores_gemma":[0.000004823577,0.0001810898,0.9976655,0.00004586825,0.00004394554,0.0001050725,0.0004430936,0.000570031,0.000459592,0.00005123565,0.0004218296,0.000007934106],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879918,0.003558317,0.00459613,0.0002095935,0.0000222263,0.0002508738,0.001132742,0.00008035685,0.002158063],"genre_scores_gemma":[0.9908248,0.0007288884,0.00653328,0.00004492807,0.00001244105,0.000241934,0.0005278084,0.00000932337,0.00107665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01837817,"threshold_uncertainty_score":0.03654242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05846934650785832,"score_gpt":0.3965034157051838,"score_spread":0.3380340691973255,"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."}}