{"id":"W4214752794","doi":"10.1007/s10143-022-01760-0","title":"Advances in computed tomography-based prognostic methods for intracerebral hemorrhage","year":2022,"lang":"en","type":"review","venue":"Neurosurgical Review","topic":"Intracerebral and Subarachnoid Hemorrhage Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Science and Technology Program of Gansu Province; National Natural Science Foundation of China","keywords":"Medicine; Intracerebral hemorrhage; Computed tomography; Hematoma; Radiology; Neurosurgery; Risk stratification; Intensive care medicine; Subarachnoid hemorrhage; Surgery; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002740722,0.0009289342,0.005785782,0.0006416713,0.0001796186,0.00005487687,0.0006774283,0.0003714929,0.002238332],"category_scores_gemma":[0.003211776,0.0006725949,0.002596593,0.002893231,0.0001858202,0.0001233696,0.000233347,0.002552901,0.00005961173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002542891,"about_ca_system_score_gemma":0.0009277051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002340807,"about_ca_topic_score_gemma":0.000001090973,"domain_scores_codex":[0.9926102,0.002110917,0.002022192,0.001376029,0.0007654664,0.001115157],"domain_scores_gemma":[0.9933496,0.00461353,0.0005168974,0.0009024257,0.000135347,0.0004821839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004216912,0.0003113899,0.000008803743,0.3130921,0.00001597897,0.0005346022,0.000001035408,5.929354e-7,1.517045e-7,0.0001058376,0.0001559517,0.6857314],"study_design_scores_gemma":[0.0008746195,0.0006758672,0.000002950339,0.04947131,0.001232169,0.000703501,9.466037e-7,0.00370168,9.75459e-7,0.00003919626,0.9427547,0.0005420909],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[7.783864e-7,0.9851101,0.002075962,0.0004935965,0.0004112635,0.01052849,0.0000835803,0.0001660982,0.001130129],"genre_scores_gemma":[7.37815e-7,0.95686,0.03586373,0.001323153,0.0002199743,0.004588623,0.0007825553,0.0001633866,0.0001978073],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9425988,"threshold_uncertainty_score":0.9997482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08276295233536601,"score_gpt":0.4534511908065655,"score_spread":0.3706882384711995,"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."}}