{"id":"W3089056874","doi":"10.55175/cdk.v47i9.919","title":"Sistem Skoring Alberta Stroke Program Early CT Score untuk Evaluasi Kasus Stroke Iskemik","year":2020,"lang":"id","type":"article","venue":"Cermin Dunia Kedokteran","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Thrombolysis; Stroke (engine); Guideline; Acute stroke; Internal medicine; Cardiology; Radiology; Tissue plasminogen activator; Myocardial infarction; Pathology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004607995,0.001035071,0.001414388,0.0002673477,0.0003360907,0.0006625821,0.001114548,0.0002669502,0.001037355],"category_scores_gemma":[0.000527935,0.001065177,0.0008110406,0.0009281132,0.0002720346,0.0004082194,0.0003046528,0.001573045,0.001192922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002458599,"about_ca_system_score_gemma":0.0001702125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006645803,"about_ca_topic_score_gemma":0.00009307166,"domain_scores_codex":[0.9943232,0.0002964567,0.001281011,0.001295215,0.001236349,0.001567755],"domain_scores_gemma":[0.996463,0.0003584526,0.0002605839,0.001087424,0.0001729306,0.001657588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002053461,0.001225142,0.1360077,0.007787537,0.005948277,0.003207864,0.02166305,0.005282816,0.02604095,0.0004390705,0.01364681,0.7785455],"study_design_scores_gemma":[0.006994566,0.001156947,0.01349347,0.003033407,0.004327891,0.0001522445,0.001440392,0.4774639,0.01124217,0.00004001823,0.4763948,0.004260199],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609045,0.003132849,0.000776624,0.00350903,0.001771322,0.001132763,0.0001328078,0.001154703,0.02748543],"genre_scores_gemma":[0.9614432,0.0002655155,0.001358006,0.0004747408,0.001674616,0.0001144444,0.000117027,0.0002591863,0.03429327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7742853,"threshold_uncertainty_score":0.9998758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02449717208125333,"score_gpt":0.2534356886121059,"score_spread":0.2289385165308525,"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."}}