{"id":"W4413440381","doi":"10.1111/cge.70048","title":"Molecular Landscape in Limb Anomalies: Diagnostic Yield and New Candidate Genes","year":2025,"lang":"en","type":"article","venue":"Clinical Genetics","topic":"Congenital limb and hand anomalies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"Gene; Candidate gene; Genetics; Yield (engineering); Biology; Phenotype; Computational biology; Medicine; Bioinformatics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001485062,0.0001554146,0.0002197768,0.0000559474,0.00003791432,0.00004142875,0.0001619244,0.0002186443,0.00001865779],"category_scores_gemma":[0.0004726085,0.0001492197,0.00009010144,0.0001072843,0.0001107069,0.000001915895,0.0002263093,0.0001108017,0.000006381586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002962468,"about_ca_system_score_gemma":0.0001412633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009577965,"about_ca_topic_score_gemma":0.0003565175,"domain_scores_codex":[0.9989262,0.00004260703,0.0004095109,0.0003329429,0.00006090406,0.000227868],"domain_scores_gemma":[0.999312,0.0001814712,0.00004862181,0.0002974455,0.00003288541,0.0001275703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001352104,0.0001343537,0.8285621,0.00004460476,0.00009581795,0.00003212437,0.00003150862,0.00007148649,0.02699465,0.0002279031,0.001373647,0.1422966],"study_design_scores_gemma":[0.003765869,0.002006623,0.5502876,0.0002028494,0.0002252361,0.00002027391,0.0003712577,0.0003725593,0.08392315,0.001576981,0.3561906,0.001056987],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9673694,0.02685734,0.0003875324,0.0003689778,0.0002416677,0.0001391668,0.00001266839,0.000009579815,0.004613705],"genre_scores_gemma":[0.9846753,0.01014547,0.0003418547,0.001064189,0.0002112971,0.000009950424,0.00003222459,0.00001364184,0.003506022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3548169,"threshold_uncertainty_score":0.6085005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02229557956425453,"score_gpt":0.3100442483331768,"score_spread":0.2877486687689222,"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."}}