{"id":"W2909479250","doi":"","title":"HUBUNGAN KADAR TROMBOSIT DENGAN ALBERTA STROKE PROGRAM EARLY CT SCORE (ASPECTS) PADA STROKE ISKEMIK AKUT: CORRELATION BETWEEN PLATELET COUNT AND ALBERTA STROKE PROGRAM EARLY CT SCORE (ASPECTS) IN ACUTE ISCHEMIC STROKE","year":2018,"lang":"en","type":"article","venue":"","topic":"Public Health and Nutrition","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Stroke (engine); Cardiology; Internal medicine; Ischemic stroke; Ischemia","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":[0.0008268605,0.0002510237,0.0003870274,0.001042826,0.0003860953,0.001105748,0.000247438,0.0003638462,0.00514115],"category_scores_gemma":[0.003556485,0.0001834225,0.0004607001,0.001286524,0.0002248662,0.0004449316,0.0004274166,0.0008878295,0.0005533039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006232683,"about_ca_system_score_gemma":0.001050535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02119315,"about_ca_topic_score_gemma":0.03162574,"domain_scores_codex":[0.9994434,0.0001256306,0.00007411453,0.00007774642,0.0001937776,0.00008539156],"domain_scores_gemma":[0.9986584,0.0004071109,0.0003942574,0.00004749794,0.000330379,0.0001622767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001005222,0.0001250122,0.9564058,0.0001480614,0.0002263826,0.0004295491,0.0002466561,0.0002253878,0.0005346396,0.0002133733,0.002844496,0.03759553],"study_design_scores_gemma":[0.00002945501,0.0001345801,0.995998,0.00008069021,0.000152351,0.0006983885,0.000274328,0.0004716691,0.0004005416,0.000259958,0.001486302,0.00001370101],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795171,0.006243473,0.000819242,0.001676044,0.0001144905,0.0001093232,0.002067454,0.0000370048,0.009415898],"genre_scores_gemma":[0.9931219,0.001926838,0.0008095357,0.0001695956,0.00007117082,0.00005173834,0.001205062,0.000008230956,0.002635971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02119315,"threshold_uncertainty_score":0.04213959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01783156700510178,"score_gpt":0.2869833458362734,"score_spread":0.2691517788311716,"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."}}