{"id":"W3118043980","doi":"10.18502/cjn.v19i2.4940","title":"Predictive value of inflammatory markers for functional outcomes in patients with ischemic stroke","year":2020,"lang":"en","type":"article","venue":"Current Journal of Neurology","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Stroke (engine); Modified Rankin Scale; Magnetic resonance imaging; Internal medicine; Tumor necrosis factor alpha; Pathophysiology; Ischemic stroke; Cardiology; Interleukin 6; Inflammation; Radiology; 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":[0.0006340025,0.000477557,0.0004119478,0.0006968444,0.0002784005,0.0005063127,0.0002758403,0.0004953071,0.001466588],"category_scores_gemma":[0.003745933,0.0001319173,0.0003214715,0.0005646056,0.0002601435,0.0002670122,0.0002835082,0.0007011276,0.0002394329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001668845,"about_ca_system_score_gemma":0.0002988321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000652656,"about_ca_topic_score_gemma":0.0009141624,"domain_scores_codex":[0.9996741,0.00007995233,0.00005073256,0.00004986854,0.0000847766,0.00006067094],"domain_scores_gemma":[0.9972229,0.0008418574,0.001023475,0.00008325483,0.0002788077,0.0005497812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002689075,0.00003556853,0.9981761,0.000008343543,0.00003691631,0.00006215317,0.00001083484,0.00008547839,0.0001074959,0.000007423046,0.00005248708,0.001148231],"study_design_scores_gemma":[0.00001582846,0.0002344634,0.9985196,0.000008833826,0.00005955442,0.0003544357,0.00003751503,0.000476218,0.00008897173,0.00005987669,0.0001399319,0.000004682165],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982217,0.0008800373,0.0001018098,0.00009739406,0.00001975307,0.00000872138,0.0001821594,0.000005971249,0.0004825438],"genre_scores_gemma":[0.999409,0.0001514958,0.00008104565,0.00001698297,0.00003493857,0.000006698751,0.0002171117,0.000001020768,0.00008176735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001466588,"threshold_uncertainty_score":0.004906297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02885067845679613,"score_gpt":0.2491049255083667,"score_spread":0.2202542470515705,"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."}}