{"id":"W3083929420","doi":"10.1111/ene.14510","title":"Nomogram predicting early neurological improvement in ischaemic stroke patients treated with endovascular thrombectomy","year":2020,"lang":"en","type":"article","venue":"European Journal of Neurology","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Nomogram; Medicine; Modified Rankin Scale; Receiver operating characteristic; Cohort; Logistic regression; Stroke (engine); Area under the curve; Internal medicine; Prospective cohort study; Surgery; Radiology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003561322,0.000255715,0.0005518359,0.0001894958,0.00003212985,0.00001783506,0.0003007937,0.00004639716,0.00005102015],"category_scores_gemma":[0.0002044652,0.0001841418,0.0001663305,0.0002486349,0.0001038782,0.0001012888,0.0001939386,0.001028753,0.00002274226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002000084,"about_ca_system_score_gemma":0.00002903596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005670106,"about_ca_topic_score_gemma":8.178583e-7,"domain_scores_codex":[0.9976147,0.0004164496,0.0007476794,0.0003826182,0.0004343503,0.0004041568],"domain_scores_gemma":[0.998823,0.00006391633,0.0004624531,0.0002290775,0.0001393394,0.0002821836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0028605,0.0003147171,0.9722992,0.00002762818,0.0002396915,0.009994061,0.0002912978,0.00009594055,0.00722097,0.000001478603,0.0007815094,0.005873063],"study_design_scores_gemma":[0.01137176,0.03753429,0.9408094,0.00003216789,0.0002584132,0.0005100523,0.00002597491,0.0003648595,0.0006135923,3.945802e-7,0.0083301,0.0001489621],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931049,0.00005043416,0.0002645533,0.003135222,0.0001087638,0.0004273391,0.000004446999,0.0000470657,0.002857264],"genre_scores_gemma":[0.9930621,0.00003026544,0.0004234453,0.006117518,0.000279878,0.000002684393,0.000005171945,0.00005680167,0.00002214933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03721957,"threshold_uncertainty_score":0.7509085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01322298069100325,"score_gpt":0.2100180722361792,"score_spread":0.196795091545176,"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."}}