{"id":"W4406615635","doi":"10.1093/eurheartj/ehae810","title":"Obesity in familial hypercholesterolaemia: when precision medicine should meet precision population health","year":2025,"lang":"en","type":"article","venue":"European Heart Journal","topic":"Lipoproteins and Cardiovascular Health","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centres Intégré Universitaires de Santé et de Services Sociaux; Institut universitaire de cardiologie et de pneumologie de Québec; Université Laval; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Precision medicine; Obesity; Population; Family medicine; Physical therapy; Environmental health; Internal medicine; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0904337,0.001311705,0.006628209,0.002761784,0.002826873,0.0108724,0.002376324,0.009294444,0.003021492],"category_scores_gemma":[0.1857069,0.001520975,0.002576929,0.002183144,0.008016016,0.01295944,0.005284136,0.01671236,0.000926158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00480333,"about_ca_system_score_gemma":0.01511769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01168603,"about_ca_topic_score_gemma":0.01275135,"domain_scores_codex":[0.9488091,0.02691721,0.008151366,0.003343069,0.01145926,0.001319946],"domain_scores_gemma":[0.7393254,0.1808769,0.02039664,0.01374124,0.03797326,0.007686506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.005600563,0.0006736101,0.0646131,0.008842219,0.00602863,0.0007564745,0.004528584,0.002334996,0.001594862,0.08898075,0.1995949,0.6164514],"study_design_scores_gemma":[0.003498376,0.002553814,0.1179116,0.04040661,0.008775535,0.002229769,0.005735072,0.00911346,0.002718185,0.4722728,0.3337867,0.0009980737],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.009228786,0.1691083,0.0125885,0.7820961,0.01776286,0.00008380764,0.0002857647,0.0002937712,0.008552101],"genre_scores_gemma":[0.3690472,0.08717903,0.06120731,0.3899378,0.08861449,0.0004968618,0.000514283,0.000285764,0.002717228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0904337,"threshold_uncertainty_score":0.4782649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05812027429944321,"score_gpt":0.3502252225123625,"score_spread":0.2921049482129193,"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."}}