{"id":"W4205581146","doi":"10.36106/ijsr/5904235","title":"CORRELATION OF DIFFUSION WEIGHTED MR DETERMINED INFARCT VOLUME WITH ALBERTA STROKE PROGRAM EARLY COMPUTED TOMOGRAPHY SCORE IN ACUTE STROKE PROGNOSIS","year":2021,"lang":"en","type":"article","venue":"INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Stroke (engine); Stroke volume; Correlation; Contouring; Internal medicine; Computed tomography; Radiology; Cardiology; Magnetic resonance imaging; Nuclear medicine; Acute stroke; Heart failure; Ejection fraction","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":[0.0008127778,0.0002873032,0.0002335655,0.0009055651,0.0001159409,0.0003605725,0.0002646223,0.0003681026,0.001305893],"category_scores_gemma":[0.003164029,0.0001200966,0.0001627111,0.0004001945,0.0002125403,0.0002841945,0.0003059043,0.0003347426,0.0001914724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001367089,"about_ca_system_score_gemma":0.0002264843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001490485,"about_ca_topic_score_gemma":0.002085447,"domain_scores_codex":[0.9996806,0.00009790667,0.00004294867,0.00004939978,0.00009221343,0.00003694647],"domain_scores_gemma":[0.9985425,0.0004587481,0.0005069328,0.00005505048,0.0002201981,0.00021648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001848299,0.00002457943,0.9971557,0.000007293992,0.0000430214,0.00005467928,0.00001196241,0.0001932562,0.0002210641,0.00001264535,0.0000642345,0.002026664],"study_design_scores_gemma":[0.000007582278,0.0001240797,0.9983218,0.000004841208,0.00001951107,0.0002633377,0.0000224522,0.001009855,0.0001058966,0.00004305976,0.00007447834,0.000003087256],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982838,0.0004239696,0.0003524117,0.00005372286,0.000007536284,0.00001661833,0.0001942045,0.0000136631,0.0006540841],"genre_scores_gemma":[0.9991965,0.0001049541,0.000261849,0.000009101859,0.00001154406,0.000009336562,0.0002838164,0.000001511812,0.0001213847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001490485,"threshold_uncertainty_score":0.004368603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02714468684761926,"score_gpt":0.3305398377776673,"score_spread":0.303395150930048,"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."}}