{"id":"W4390262248","doi":"10.1016/j.jns.2023.121004","title":"SMA: From genotype to phenotype","year":2023,"lang":"en","type":"article","venue":"Journal of the Neurological Sciences","topic":"Neurogenetic and Muscular Disorders Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Phenotype; Genotype; SMA*; Genetics; Biology; Gene; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0006147862,0.001382076,0.001035162,0.001918341,0.0003990913,0.001091703,0.000631066,0.001414028,0.005002996],"category_scores_gemma":[0.00343953,0.0003724777,0.0003811725,0.0008528453,0.0008122331,0.0008879598,0.001153211,0.0008276405,0.001931921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002089785,"about_ca_system_score_gemma":0.0002355078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003731468,"about_ca_topic_score_gemma":0.0002927525,"domain_scores_codex":[0.9989892,0.0003913942,0.0001078092,0.0002300094,0.0002028005,0.00007886526],"domain_scores_gemma":[0.9980257,0.001150344,0.0003645445,0.000106002,0.0002066488,0.0001468378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002086757,0.0004395224,0.4973989,0.0006944416,0.0006250013,0.1096533,0.002145394,0.003288759,0.08997318,0.01424039,0.01826522,0.2611893],"study_design_scores_gemma":[0.0001612859,0.001024795,0.5878026,0.001669338,0.001182213,0.3371173,0.001642245,0.005313066,0.01208891,0.02931794,0.02243039,0.0002498734],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.8990918,0.02360645,0.01884422,0.008361082,0.0007302422,0.00008932731,0.00287714,0.0009590988,0.04544065],"genre_scores_gemma":[0.9835007,0.006007731,0.003097353,0.001117267,0.0008256102,0.00004131562,0.0007849148,0.000288608,0.004336479],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005002996,"threshold_uncertainty_score":0.01673675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0655386433579268,"score_gpt":0.3411593354457865,"score_spread":0.2756206920878597,"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."}}