{"id":"W3147553300","doi":"","title":"KORELASI KADAR FIBRINOGEN DENGAN NILAI ALBERTA STROKE PROGRAM EARLY CT SCORE (ASPECTS) PADA STROKE ISKEMIK","year":2015,"lang":"id","type":"article","venue":"Neurona (Majalah Kedokteran Neuro Sains Perhimpunan Dokter Spesialis Saraf Indonesia)","topic":"Public Health and Nutrition","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Cardiology; Stroke (engine); Internal medicine; Ischemic stroke; Fibrinogen; Middle cerebral artery; 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":[0.001027147,0.0008382637,0.0008368519,0.001059786,0.0003307324,0.001710223,0.0003823551,0.0003416009,0.006329132],"category_scores_gemma":[0.002214331,0.0002099503,0.0007220395,0.0007321977,0.0002600111,0.0005322694,0.0006134816,0.0008278377,0.001209791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005520094,"about_ca_system_score_gemma":0.0009397088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0113533,"about_ca_topic_score_gemma":0.009113112,"domain_scores_codex":[0.9995387,0.00009566276,0.000063884,0.00008323706,0.000145768,0.00007281617],"domain_scores_gemma":[0.9992787,0.0001795146,0.0001681525,0.00002731513,0.0002705602,0.00007568097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002202274,0.0004013255,0.6816952,0.0008234555,0.001266635,0.002222096,0.001135748,0.00239832,0.004482842,0.001508591,0.00856224,0.2933013],"study_design_scores_gemma":[0.0001639153,0.001193619,0.9543605,0.000672955,0.001704054,0.004911985,0.001757595,0.009804768,0.00360428,0.004999535,0.0166809,0.0001457585],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9368196,0.0151784,0.008431179,0.002357255,0.000385235,0.0002110547,0.002789671,0.0003337639,0.03349377],"genre_scores_gemma":[0.9768355,0.005938303,0.00787311,0.0002049399,0.0001227316,0.0001293687,0.001611656,0.00004437677,0.007240079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0113533,"threshold_uncertainty_score":0.02257448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03476959803991725,"score_gpt":0.2833253191480621,"score_spread":0.2485557211081449,"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."}}