{"id":"W4382360262","doi":"10.1371/journal.pone.0285599","title":"Multiple sclerosis: Exploring the limits and implications of genetic and environmental susceptibility","year":2023,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multiple sclerosis; Genetic predisposition; Genetics; Evolutionary biology; Environmental health; Biology; Computational biology; Medicine; Bioinformatics; Immunology; Gene","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":[0.007876416,0.0006057624,0.0006600177,0.001693846,0.0009524467,0.001524707,0.001395774,0.0006703981,0.0008542007],"category_scores_gemma":[0.04360135,0.0002849819,0.000654521,0.002012688,0.00287804,0.001590346,0.001999011,0.001113334,0.00005190146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006679493,"about_ca_system_score_gemma":0.009599533,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6406078,"about_ca_topic_score_gemma":0.5209272,"domain_scores_codex":[0.9966977,0.001851609,0.00008978806,0.000415298,0.000674561,0.0002710905],"domain_scores_gemma":[0.9860179,0.01178561,0.0007867253,0.0004685632,0.0006915976,0.0002495183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002842148,0.0001450707,0.6219079,0.0004532474,0.0009491345,0.0009117671,0.003097638,0.2400643,0.002556169,0.05586815,0.0007765131,0.07298577],"study_design_scores_gemma":[0.00005966007,0.0003512329,0.4022008,0.0002879533,0.0004725312,0.0008073816,0.004917227,0.5081367,0.001259528,0.07523837,0.006143665,0.0001249917],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9234361,0.004260245,0.0602134,0.002242447,0.000009757386,0.0001108943,0.0004142215,0.000109365,0.009203505],"genre_scores_gemma":[0.9873664,0.0007140102,0.01146336,0.00006830877,0.000005297482,0.0000241941,0.0000932404,0.000008578661,0.000256603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6406078,"threshold_uncertainty_score":0.7230175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2754687979903316,"score_gpt":0.2963998899460277,"score_spread":0.02093109195569615,"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."}}