{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001419815,0.0001668867,0.0003907501,0.002267994,0.00009048825,0.0002793774,0.0006285652,0.00009819031,0.0001886152],"category_scores_gemma":[0.0002822941,0.0001313418,0.00020498,0.001682818,0.000502792,0.000387726,0.0003447237,0.0007206664,0.00001085965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002464211,"about_ca_system_score_gemma":0.000501972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001256351,"about_ca_topic_score_gemma":0.0001133619,"domain_scores_codex":[0.9945819,0.0001735212,0.000874459,0.0004078343,0.003560713,0.0004015309],"domain_scores_gemma":[0.9938557,0.0002264243,0.0004543269,0.00032146,0.004935893,0.0002062201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00187041,0.001548014,0.8873363,0.00006153168,0.0009099262,0.001065876,0.0006339643,0.00003792459,0.07158303,0.00004902314,0.003917293,0.03098672],"study_design_scores_gemma":[0.008988512,0.00250096,0.8851508,0.002155384,0.0002229287,0.0007107412,0.0006068135,0.02693593,0.06148779,0.00004770325,0.01093265,0.0002597833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942802,0.00009655699,0.0006129957,0.002045621,0.0006538249,0.0006910285,0.00003385222,0.00001252005,0.001573434],"genre_scores_gemma":[0.9846763,0.00002986026,0.007295665,0.00002335561,0.0001252247,0.00002680026,0.000101125,0.00002083796,0.007700859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03072694,"threshold_uncertainty_score":0.5355964,"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."}}