{"id":"W2947243905","doi":"10.1186/s13023-019-1088-3","title":"The DM-scope registry: a rare disease innovative framework bridging the gap between research and medical care","year":2019,"lang":"en","type":"article","venue":"Orphanet Journal of Rare Diseases","topic":"Genetic Neurodegenerative Diseases","field":"Neuroscience","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Hydro-Québec","funders":"Centre Hospitalier Universitaire de Nantes; AFM-Téléthon","keywords":"Disease registry; Medicine; Clinical trial; Scope (computer science); Observational study; Biobank; Interoperability; Patient registry; Disease; Family medicine; Pediatrics; Pathology; Computer science; Bioinformatics","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":[0.1000352,0.0009163212,0.002004646,0.01380411,0.002055924,0.01194079,0.005487276,0.003121783,0.00596385],"category_scores_gemma":[0.1173904,0.0009760825,0.001801206,0.01317319,0.00322976,0.01157759,0.02178602,0.002964488,0.003206834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00439168,"about_ca_system_score_gemma":0.02926703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005223673,"about_ca_topic_score_gemma":0.004362125,"domain_scores_codex":[0.9216223,0.05005919,0.01153907,0.007613944,0.007329392,0.001836105],"domain_scores_gemma":[0.8375403,0.08182874,0.01692982,0.03199543,0.01663852,0.01506713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0008317868,0.0003501581,0.03689929,0.003586754,0.0007154972,0.001073219,0.005633053,0.007740605,0.002225801,0.470704,0.1338067,0.3364332],"study_design_scores_gemma":[0.0004761023,0.0004006498,0.01759097,0.004330148,0.0004179714,0.001813959,0.002754293,0.0132556,0.001376611,0.1213796,0.8358952,0.0003089282],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02666834,0.01251108,0.7832657,0.072127,0.002665998,0.005415236,0.03709696,0.01238955,0.04786023],"genre_scores_gemma":[0.1304941,0.008506301,0.7910438,0.006791918,0.004200798,0.00475508,0.04888643,0.001553497,0.003768073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1000352,"threshold_uncertainty_score":0.5290429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04994879039940633,"score_gpt":0.3473540445810242,"score_spread":0.2974052541816179,"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."}}