{"id":"W4404619186","doi":"10.1242/dmm.050913","title":"Beyond genomic studies of congenital heart defects through systematic modelling and phenotyping","year":2024,"lang":"en","type":"article","venue":"Disease Models & Mechanisms","topic":"Congenital heart defects research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Agencia Estatal de Investigación; European Commission; European Regional Development Fund; Medical Research Council; Instituto de Salud Carlos III; Canadian Institutes of Health Research; Ministerio de Ciencia, Innovación y Universidades; Centro Nacional de Investigaciones Cardiovasculares; Institut National de la Santé et de la Recherche Médicale; Agence Nationale de la Recherche; British Heart Foundation; Additional Ventures","keywords":"Genetic architecture; Biology; Computational biology; Model organism; Gene; Genetics; Bioinformatics; Phenotype","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":[0.005799914,0.001048385,0.001506915,0.001140061,0.0003829501,0.001927477,0.001443131,0.0008931251,0.001200938],"category_scores_gemma":[0.00685994,0.0004076195,0.001281418,0.001022729,0.002173591,0.001610022,0.002280468,0.001679846,0.0005645555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007330128,"about_ca_system_score_gemma":0.002450283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001351275,"about_ca_topic_score_gemma":0.001109793,"domain_scores_codex":[0.9967337,0.002017641,0.0001700313,0.0004862347,0.0005146919,0.00007771686],"domain_scores_gemma":[0.9951675,0.002175954,0.0005399221,0.001705274,0.0002502117,0.000161209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005252623,0.0004917428,0.05185809,0.002764399,0.0009979653,0.001480081,0.001750846,0.105559,0.1832215,0.280859,0.006603368,0.3638887],"study_design_scores_gemma":[0.0001887053,0.00247742,0.03350737,0.001567681,0.00139931,0.004529975,0.001633912,0.151916,0.09244701,0.4390392,0.2708542,0.0004393073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05515606,0.008109245,0.9253607,0.002756047,0.0002832905,0.0002623384,0.001047473,0.0009323502,0.006092305],"genre_scores_gemma":[0.3761245,0.02669105,0.5888477,0.001225851,0.0002900421,0.0008122443,0.002877882,0.0005592753,0.002571392],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005799914,"threshold_uncertainty_score":0.03067327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04248786173614046,"score_gpt":0.3074272522805017,"score_spread":0.2649393905443613,"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."}}