{"id":"W4310668181","doi":"10.1111/ene.15658","title":"Clinical outcomes of delayed mechanical thrombectomy: Descriptive analysis and development of a screening tool","year":2022,"lang":"en","type":"article","venue":"European Journal of Neurology","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Descriptive statistics; Intensive care medicine; Medical physics; Statistics","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":[0.003266142,0.0002372626,0.0004369496,0.002120126,0.0002287511,0.0006435157,0.0004474944,0.0002748207,0.0006915234],"category_scores_gemma":[0.008838311,0.000143154,0.0005670162,0.001672214,0.0003818265,0.0007497451,0.000634899,0.0003839058,0.0001136579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000529399,"about_ca_system_score_gemma":0.0005585193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001390508,"about_ca_topic_score_gemma":0.001187925,"domain_scores_codex":[0.9986999,0.0004529654,0.0003120739,0.0001583649,0.0002681168,0.0001085534],"domain_scores_gemma":[0.9917057,0.003340084,0.003302205,0.0003933078,0.0009092294,0.0003494319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002332576,0.00003549933,0.9980772,0.000008542147,0.00002793047,0.00002811296,0.00004362005,0.0001029738,0.00006256309,0.00002543498,0.00005443789,0.001300346],"study_design_scores_gemma":[0.00002407163,0.0004047231,0.9968151,0.000009130941,0.00003778777,0.000273407,0.0002553122,0.001769528,0.0001483496,0.0001020748,0.0001510443,0.000009426532],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984227,0.00006850804,0.0004980171,0.00002980678,0.000002759295,0.00004849939,0.0006637722,0.000005083912,0.0002609042],"genre_scores_gemma":[0.9988657,0.00002394832,0.0002955051,0.00000773907,0.00000459735,0.00005206105,0.0007196642,0.000001911352,0.00002880065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003266142,"threshold_uncertainty_score":0.01727319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05575553555907835,"score_gpt":0.3070328503051925,"score_spread":0.2512773147461141,"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."}}