{"id":"W2946027146","doi":"10.1055/s-0037-1682160","title":"Evaluation of Conventional Automated and Volume Weighted Automated Aspects vs. CT Perfusion Core Volume to predict the Final Infarct Volume after Successful Endovascular Therapy","year":2019,"lang":"de","type":"article","venue":"RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Volume (thermodynamics); Medicine; Perfusion; Stroke volume; Perfusion scanning; Stroke (engine); Core (optical fiber); Radiology; Acute stroke; Computer science; Internal medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001419939,0.0004939013,0.0004452339,0.0008172309,0.0001205207,0.0005811944,0.0004175517,0.0004994569,0.0005360978],"category_scores_gemma":[0.004135453,0.0001901167,0.0003649465,0.0004058199,0.0003389386,0.00058128,0.0002753988,0.0003218149,0.0001528244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002541021,"about_ca_system_score_gemma":0.0002556742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008930295,"about_ca_topic_score_gemma":0.001190111,"domain_scores_codex":[0.9993956,0.0002308272,0.00004618468,0.0001327696,0.0001424795,0.00005202026],"domain_scores_gemma":[0.9979341,0.0009916729,0.0003029882,0.0001422737,0.0003848356,0.000244161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02518708,0.0006215822,0.8987231,0.0001147508,0.00102287,0.0002411886,0.0001585409,0.004279636,0.01070897,0.0002311434,0.0004998525,0.05821127],"study_design_scores_gemma":[0.0006621095,0.009959434,0.9289135,0.00002574741,0.0006033637,0.001074525,0.000117666,0.05151127,0.006040561,0.0004584368,0.0005780984,0.00005519945],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969158,0.0005843535,0.001556485,0.00002703856,0.00002325044,0.00004476884,0.0001497129,0.00002897797,0.0006695372],"genre_scores_gemma":[0.9985291,0.00007972659,0.0009990281,0.00002110219,0.00001981443,0.00003108664,0.000176461,0.000005595065,0.0001381795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001419939,"threshold_uncertainty_score":0.00750941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01643803471694671,"score_gpt":0.2635738177359973,"score_spread":0.2471357830190506,"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."}}