{"id":"W3093711806","doi":"10.1177/1352458520964774","title":"Long-term prognostic counselling in people with multiple sclerosis using an online analytical processing tool","year":2020,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Worry; Multiple sclerosis; Cohort; Expanded Disability Status Scale; Coping (psychology); Anxiety; Likert scale; Personalized medicine; Physical therapy; Disease; Cohort study; Clinical psychology; Internal medicine; Psychology; Psychiatry; Bioinformatics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001021502,0.0007884005,0.001465032,0.0005826091,0.0008532642,0.0006132112,0.0005649836,0.0002713764,0.0001633391],"category_scores_gemma":[0.002093843,0.0006391219,0.0003183645,0.00188511,0.0004129051,0.001191799,0.0001694193,0.002039658,0.00002378098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005752242,"about_ca_system_score_gemma":0.0006754609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001506151,"about_ca_topic_score_gemma":0.001249133,"domain_scores_codex":[0.9932604,0.0003603258,0.001495935,0.001173123,0.002030715,0.001679532],"domain_scores_gemma":[0.9959436,0.0005451344,0.0005072947,0.0005237436,0.001035121,0.001445108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00190621,0.001818009,0.9039959,0.0004303585,0.0002182235,0.0001943073,0.002896609,0.006879693,0.05705476,6.827172e-7,0.00004860231,0.02455663],"study_design_scores_gemma":[0.007805427,0.0008320333,0.6471638,0.002408481,0.0002116355,0.0001722276,0.0007152365,0.3392306,0.0009316852,0.000001236413,0.0000211678,0.0005064796],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981446,0.000918588,0.01434995,0.001406103,0.0001050372,0.001494832,0.00007178589,0.0001945333,0.00001317831],"genre_scores_gemma":[0.9772417,0.001561092,0.01908067,0.0006828462,0.001089683,0.00005625824,0.00008384704,0.0001912363,0.00001269001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3323509,"threshold_uncertainty_score":0.999606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2385130736406358,"score_gpt":0.3350935979117455,"score_spread":0.09658052427110964,"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."}}