{"id":"W2914690475","doi":"10.1161/str.50.suppl_1.tp172","title":"Abstract TP172: Global Insight into Long-term Stroke Outcomes Using the Post Stroke Checklist","year":2019,"lang":"en","type":"article","venue":"Stroke","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Stroke (engine); Checklist; Referral; Rehabilitation; Population; Mood; Gerontology; Physical therapy; Family medicine; Psychiatry; Environmental health","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":[0.004730977,0.0006374415,0.0009403855,0.003388413,0.0008108357,0.001156743,0.00114343,0.0005291782,0.006940656],"category_scores_gemma":[0.01436632,0.0002574081,0.001619441,0.002230509,0.0003281372,0.001798349,0.001924117,0.001474107,0.001248459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001666801,"about_ca_system_score_gemma":0.003411252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01063737,"about_ca_topic_score_gemma":0.01568801,"domain_scores_codex":[0.9975211,0.0006859278,0.0006696403,0.0001219794,0.0007129872,0.0002883319],"domain_scores_gemma":[0.9899934,0.001956621,0.00338629,0.0003227846,0.003353758,0.0009871969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007565814,0.0008262498,0.7900816,0.001900255,0.0005485669,0.0003175892,0.002999817,0.001021967,0.0003642765,0.0004130422,0.06531332,0.1354567],"study_design_scores_gemma":[0.0001307681,0.0007530318,0.9862997,0.0004847031,0.00008665491,0.0002686484,0.001892321,0.0005988593,0.0001695883,0.0003621329,0.008894386,0.00005927384],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8945268,0.001873017,0.002718685,0.003033767,0.0003323406,0.008798487,0.06245771,0.0004405072,0.02581859],"genre_scores_gemma":[0.9207948,0.002221821,0.009686828,0.0007294085,0.0001659608,0.01512827,0.04396224,0.0000886613,0.007222019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01063737,"threshold_uncertainty_score":0.02502012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588015782558446,"score_gpt":0.3075894088020897,"score_spread":0.2917092509765053,"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."}}