{"id":"W4415079674","doi":"10.1016/j.gim.2025.101597","title":"Screening rare genetic diagnoses for amenability to bespoke antisense oligonucleotide therapy development: A retrospective cohort study","year":2025,"lang":"en","type":"article","venue":"Genetics in Medicine","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Ontario; University of Toronto; Hospital for Sick Children; SickKids Foundation","funders":"Sickkids Research Institute; Deutsche Forschungsgemeinschaft; Canadian Institutes of Health Research; Sick Kids Foundation; European Commission; Hospital for Sick Children; Alexander von Humboldt-Stiftung; Gemeinnützige Hertie-Stiftung; McLaughlin Centre, University of Toronto","keywords":"Medical diagnosis; Bespoke; Retrospective cohort study; Genetic diagnosis; Genetic testing; DNA sequencing; Cohort study; Identification (biology)","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":[0.0004981146,0.0004611296,0.0004924785,0.000948605,0.001050533,0.0008220714,0.0004908873,0.0005571701,0.002670668],"category_scores_gemma":[0.002024364,0.000729993,0.0007534835,0.001025258,0.0004728326,0.0005819977,0.0007296195,0.0007992442,0.0004604878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004291696,"about_ca_system_score_gemma":0.0006893182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007907845,"about_ca_topic_score_gemma":0.005973369,"domain_scores_codex":[0.9992523,0.000109229,0.00006573178,0.0003322043,0.0001120162,0.0001285254],"domain_scores_gemma":[0.9988386,0.0001842003,0.0003490078,0.0002409579,0.000151171,0.0002359928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001471948,0.00006602862,0.9968114,0.000005709253,0.00007492669,0.0009312091,0.0001235167,0.00002678849,0.0006264991,0.00005251444,0.0001555355,0.0009786366],"study_design_scores_gemma":[0.00003460895,0.0003864558,0.9886705,0.00001581883,0.0001605026,0.00854632,0.0007498095,0.0002707659,0.0002802305,0.0001225222,0.0007427636,0.00001970043],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988706,0.0001436816,0.0002207889,0.00002887945,0.000005611408,0.00001438995,0.0004032114,0.000005286695,0.0003076473],"genre_scores_gemma":[0.9989582,0.0001332727,0.0001495617,0.00003812946,0.000005894552,0.00001171025,0.0004601298,0.000006340139,0.0002367215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007907845,"threshold_uncertainty_score":0.01572365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01492543613206897,"score_gpt":0.3108437666923702,"score_spread":0.2959183305603012,"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."}}