{"id":"W2016107427","doi":"10.1159/000078755","title":"Use of CT Perfusion to Differentiate between Brain Tumour and Cerebral Infarction","year":2004,"lang":"en","type":"article","venue":"Cerebrovascular Diseases","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Robarts Clinical Trials","funders":"","keywords":"Medicine; Brain infarction; Perfusion scanning; Perfusion; Infarction; Cerebral infarction; Cerebral hypoperfusion; Stroke (engine); Penumbra; Cardiology; Radiology; Ischemia; Myocardial infarction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000791251,0.0007462651,0.0004476669,0.00261291,0.0002868057,0.0006264216,0.0006443165,0.001172291,0.001823825],"category_scores_gemma":[0.004490243,0.000353475,0.0003869573,0.0009294327,0.0008133007,0.001355631,0.0002819531,0.001075905,0.0004878276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002861619,"about_ca_system_score_gemma":0.0004220293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002023061,"about_ca_topic_score_gemma":0.001705468,"domain_scores_codex":[0.999827,0.00005771804,0.0000269524,0.00002689376,0.00003367011,0.00002788381],"domain_scores_gemma":[0.998867,0.0006723339,0.000101834,0.0000624914,0.0002163678,0.00007994463],"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":[0.01053997,0.0004927203,0.2495981,0.001773506,0.0007347272,0.0538657,0.0004123874,0.001894915,0.3614404,0.001493274,0.003509363,0.3142449],"study_design_scores_gemma":[0.0006318616,0.005816515,0.3767846,0.001084275,0.002543684,0.3097654,0.0008103296,0.02483478,0.2550271,0.004491366,0.01797277,0.0002372905],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8828057,0.05130598,0.02654107,0.002687841,0.0005245193,0.0003038286,0.0004936022,0.000222854,0.03511465],"genre_scores_gemma":[0.9631072,0.02147206,0.01286382,0.0004978499,0.0003003397,0.00007119503,0.000233734,0.00005635628,0.001397329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00261291,"threshold_uncertainty_score":0.006101251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02341806952038359,"score_gpt":0.2854646453220401,"score_spread":0.2620465758016565,"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."}}