{"id":"W4210659622","doi":"10.31590/ejosat.1063356","title":"Computer Aided Deep Learning Based Assessment of Stroke From Brain Radiological CT Images","year":2022,"lang":"en","type":"article","venue":"European Journal of Science and Technology","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Preprocessor; Thresholding; Deep learning; Computer science; Image processing; Medicine; Segmentation; Stroke (engine); Computer vision; Pattern recognition (psychology); Radiology; Image (mathematics); Engineering","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":[0.002083756,0.00008110717,0.0002582398,0.0005396025,0.0001692926,0.00001277728,0.0004086709,0.000009562561,0.0001109697],"category_scores_gemma":[0.000273441,0.00006236867,0.00004314752,0.0004816862,0.001006578,0.00006310125,0.0004723872,0.0005765863,0.000001077753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007535464,"about_ca_system_score_gemma":0.00009867361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001156989,"about_ca_topic_score_gemma":3.282953e-8,"domain_scores_codex":[0.9986827,0.0001452936,0.0003310651,0.0001937269,0.0004697227,0.0001774667],"domain_scores_gemma":[0.999213,0.00009101074,0.0003300483,0.000152127,0.0001464578,0.00006740175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001130272,0.0002763882,0.1262876,0.0000223557,0.0001443624,0.00409498,0.0001838767,0.001092453,0.6583156,0.0003481171,0.008673015,0.2004482],"study_design_scores_gemma":[0.01387306,0.02224136,0.6715193,0.0002635676,0.0003872204,0.005392879,0.01019471,0.05308964,0.05412298,0.0001759661,0.1681111,0.000628164],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702018,0.0001998123,0.02010448,0.00659009,0.0001236128,0.00007664629,0.000002896227,0.00002752171,0.002673143],"genre_scores_gemma":[0.9689047,0.00001973294,0.03042104,0.0005270873,0.00005006182,7.385451e-7,0.000001162766,0.000006724755,0.00006877443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6041926,"threshold_uncertainty_score":0.3708777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0112689671110107,"score_gpt":0.2590803253891624,"score_spread":0.2478113582781517,"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."}}