{"id":"W6939852308","doi":"10.6084/m9.figshare.28657022.v1","title":"Additional file 1 of Whole exome sequencing enhances diagnosis of hereditary bronchiectasis","year":2025,"lang":"en","type":"article","venue":"Figshare","topic":"Cystic Fibrosis Research Advances","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Exome sequencing; DNA sequencing; Mutation; Whole genome sequencing; Disease; Exome","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001259302,0.001321118,0.001388063,0.00283267,0.001107851,0.002004918,0.001950993,0.002064241,0.8601272],"category_scores_gemma":[0.02212039,0.0007420576,0.001509146,0.002100691,0.0003075404,0.001314168,0.001310452,0.0009359327,0.1598653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008156951,"about_ca_system_score_gemma":0.00144588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005095161,"about_ca_topic_score_gemma":0.01065812,"domain_scores_codex":[0.9992293,0.0001127891,0.0001139892,0.0002771328,0.000152491,0.000114317],"domain_scores_gemma":[0.9799063,0.01586339,0.0008780187,0.001075678,0.001628873,0.0006478226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005831781,0.0001488893,0.00549128,0.00395292,0.0001641205,0.000461953,0.00008246634,0.0006577891,0.0007816015,0.001105091,0.9701301,0.01644072],"study_design_scores_gemma":[0.009650853,0.0005477282,0.08733682,0.006273396,0.00080377,0.004734087,0.0004440523,0.004148094,0.003876424,0.02687292,0.8549498,0.0003619375],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004866731,0.00006278306,0.0005152884,0.0001813034,0.00009445559,0.00007433763,0.9967133,0.0004557505,0.001416091],"genre_scores_gemma":[0.01352948,0.0003234089,0.01044874,0.001924407,0.0003832557,0.001278281,0.9579503,0.001836367,0.0123258],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8601272,"threshold_uncertainty_score":0.1995115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02692454479100608,"score_gpt":0.2994869466245594,"score_spread":0.2725624018335533,"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."}}