{"id":"W4402511863","doi":"10.1097/io9.0000000000000120","title":"Re-evaluating the timing of mechanical thrombectomy in low ASPECTS stroke: insights from real-world data","year":2024,"lang":"en","type":"article","venue":"International Journal of Surgery Open","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Stroke (engine); Physical medicine and rehabilitation; Cardiology; Mechanical engineering","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":[0.001844327,0.0001226926,0.0004581519,0.0004299072,0.00001988919,0.0001435941,0.001313648,0.00003235042,0.0004344421],"category_scores_gemma":[0.0007512263,0.00008198275,0.0001279068,0.0002764422,0.00005534768,0.0005474596,0.00107412,0.0004156175,0.00001318272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002277242,"about_ca_system_score_gemma":0.0004255916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001243544,"about_ca_topic_score_gemma":0.0004569901,"domain_scores_codex":[0.9975081,0.0001149102,0.0009236293,0.0002445374,0.001079196,0.0001296453],"domain_scores_gemma":[0.9970656,0.00175475,0.0004559823,0.0004135267,0.0002500069,0.00006015391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00743907,0.001859451,0.1582942,0.0004248146,0.01673801,0.01436048,0.004498801,0.0006191246,0.1173369,0.008597906,0.4494648,0.2203665],"study_design_scores_gemma":[0.009822831,0.0009875931,0.5527012,0.04215486,0.002478168,0.0008889659,0.008136785,0.202639,0.1022007,0.009792998,0.0668174,0.001379496],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971757,0.00045935,0.000396482,0.009887955,0.001755914,0.0002727046,0.00005999958,0.00001131277,0.01539928],"genre_scores_gemma":[0.9961544,0.0002228479,0.002171188,0.0003277241,0.000641325,0.000003597347,0.0000641109,0.00002075659,0.0003940658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3944071,"threshold_uncertainty_score":0.4756837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1929963515407571,"score_gpt":0.4282096789249361,"score_spread":0.235213327384179,"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."}}