{"id":"W2155737242","doi":"10.1161/01.str.0000078840.96473.20","title":"Reliability of Assessing Percentage of Diffusion-Perfusion Mismatch","year":2003,"lang":"en","type":"article","venue":"Stroke","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Foothills Medical Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation pour la Recherche Médicale; Multiple Sclerosis Society; Canadian Stroke Network; Multiple Sclerosis Society of Canada; Heart and Stroke Foundation of Canada","keywords":"Medicine; Inter-rater reliability; Reliability (semiconductor); Intra-rater reliability; Thrombolysis; Nuclear medicine; Stroke (engine); Magnetic resonance imaging; Neurovascular bundle; Infarction; Radiology; Surgery; Internal medicine; Confidence interval; Myocardial infarction; Psychology; Rating scale","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000315019,0.0001222404,0.0003448596,0.00007955371,0.00003106938,0.000004291557,0.00008575035,0.00007129862,0.0005838187],"category_scores_gemma":[0.0002632903,0.0001005767,0.0001322889,0.00009730855,0.0001016146,0.0000577869,0.00007360819,0.0001345414,0.000007147109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006627951,"about_ca_system_score_gemma":0.00005516564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004991669,"about_ca_topic_score_gemma":7.616936e-7,"domain_scores_codex":[0.9987632,0.00004943142,0.0003891469,0.0002258053,0.0003889815,0.0001834342],"domain_scores_gemma":[0.9991001,0.00006668999,0.000156727,0.0005018799,0.00009998103,0.00007457512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004966337,0.0003300816,0.1865041,0.0003023462,0.0000249946,0.000008199999,0.0002611693,0.000003346991,0.8069994,0.0001260855,0.003194282,0.002196325],"study_design_scores_gemma":[0.003492202,0.0003530511,0.3228348,0.0004575861,0.0003320796,0.00002819889,0.004423534,0.0003186227,0.6299621,0.00005548341,0.03749468,0.0002477009],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9102222,0.00007692735,0.0008157156,0.0001183105,0.000144119,0.0002638576,0.00001188709,0.00002292992,0.08832407],"genre_scores_gemma":[0.9881477,0.00003836992,0.008477784,0.00007490849,0.00002704697,0.000004267812,0.000009617724,0.00001520692,0.003205149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1770373,"threshold_uncertainty_score":0.6392406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01250588264756866,"score_gpt":0.2773180366692299,"score_spread":0.2648121540216613,"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."}}