{"id":"W4409270823","doi":"10.1002/neo2.70018","title":"When to Call a Code: Using Transcranial Doppler to Anticipate Cardiac Arrest a Case Report","year":2025,"lang":"en","type":"article","venue":"Clinical neuroimaging.","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McMaster University","funders":"","keywords":"Transcranial Doppler; Code (set theory); Medicine; Computer science; Internal medicine; Cardiology; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009421221,0.0002358893,0.0007492405,0.0002092055,0.000139557,0.00006436679,0.0001071757,0.0001195815,0.00001783255],"category_scores_gemma":[0.001770234,0.0002151032,0.0005213229,0.000492678,0.0001292354,0.00006710023,0.0001072824,0.0004726531,0.00007176705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005454593,"about_ca_system_score_gemma":0.0002997098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003189443,"about_ca_topic_score_gemma":0.00004926733,"domain_scores_codex":[0.9972748,0.0002036537,0.0009849827,0.0007947901,0.0003081189,0.0004336404],"domain_scores_gemma":[0.9979731,0.0004214952,0.00008808394,0.000706971,0.0002341172,0.0005762712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002727095,0.0008583405,0.5528746,0.0003982475,0.0005552584,0.2412893,0.001775127,0.0005870281,0.01984035,0.0001105618,0.1552912,0.02369292],"study_design_scores_gemma":[0.006153376,0.000562367,0.6126431,0.001079978,0.002619819,0.005758543,0.0002283833,0.006294041,0.0004184351,0.0002214706,0.3629419,0.001078609],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9627932,0.00006105461,0.004449649,0.01889988,0.01057125,0.001112158,0.00004193975,0.0001454903,0.001925344],"genre_scores_gemma":[0.9845476,0.00001240089,0.003982814,0.009244687,0.001374699,0.00002867534,0.00001889735,0.00004730034,0.0007429766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2355307,"threshold_uncertainty_score":0.8771652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07267539404927394,"score_gpt":0.4212601829244995,"score_spread":0.3485847888752256,"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."}}