{"id":"W7095157809","doi":"","title":"SHORT REPORT Multiple sclerosis in stepsiblings: recurrence risk and ascertainment","year":2016,"lang":"en","type":"article","venue":"","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multiple sclerosis; Epidemiology; Population; Disease; Genetic predisposition; Genetic epidemiology; Incidence (geometry); Risk assessment","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007128331,0.0001162736,0.0001767323,0.001051317,0.0003879796,0.0003376419,0.0004229778,0.0002070063,0.003168603],"category_scores_gemma":[0.005654399,0.0001058585,0.0002088861,0.0009871338,0.0001717622,0.0001768751,0.0003946179,0.0002552202,0.0006205619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005740925,"about_ca_system_score_gemma":0.0007451469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1011464,"about_ca_topic_score_gemma":0.08349673,"domain_scores_codex":[0.9995888,0.00008909419,0.00005465543,0.00008496337,0.0001202162,0.00006225378],"domain_scores_gemma":[0.9975004,0.0005481003,0.0007640937,0.0003047909,0.0006040001,0.0002787074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001379125,0.00001683831,0.9893662,0.00002681062,0.00003375413,0.0002449849,0.0001684588,0.0000585169,0.0002955814,0.00005682274,0.001247824,0.008346387],"study_design_scores_gemma":[0.000009849707,0.00008140855,0.9964669,0.00001227829,0.00004757307,0.0008000358,0.0001941736,0.0002480803,0.0003710835,0.00006580648,0.001697652,0.000005161903],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913817,0.0004993608,0.0006838132,0.0001786011,0.00003947251,0.00008408388,0.005186144,0.00002696298,0.001919903],"genre_scores_gemma":[0.9925814,0.0003108513,0.0007991096,0.00006880296,0.00003532555,0.00005627408,0.003939581,0.00001229655,0.002196393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1011464,"threshold_uncertainty_score":0.2011153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09465703876654159,"score_gpt":0.33006626580831,"score_spread":0.2354092270417684,"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."}}