{"id":"W4417221370","doi":"10.3389/fninf.2025.1668395","title":"Assessing the eligibility of Brainomix e-ASPECTS for acute stroke imaging","year":2025,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Acute stroke; Radiological weapon; Stroke (engine); Medical imaging; Neuroimaging; MEDLINE","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":[0.000428338,0.0001453179,0.0003662309,0.0002382569,0.00006495038,0.00004877412,0.0002471525,0.00003876499,0.000002113974],"category_scores_gemma":[0.0003849486,0.0001111866,0.000128422,0.0002775214,0.0001294584,0.0002677648,0.000152618,0.0002154544,7.729492e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001306355,"about_ca_system_score_gemma":0.0001378912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000410967,"about_ca_topic_score_gemma":5.441643e-7,"domain_scores_codex":[0.9987491,0.00002003318,0.0006069047,0.0001435719,0.0002075982,0.0002728208],"domain_scores_gemma":[0.9989754,0.000164302,0.000200411,0.0005491414,0.0000753333,0.00003542942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002705983,0.0001948616,0.2498853,0.001633649,0.0006602404,0.00002635311,0.001520109,0.0002741429,0.00201722,0.001650422,0.677174,0.06469313],"study_design_scores_gemma":[0.01000236,0.0002315394,0.1459865,0.0008898404,0.00188828,0.00004282739,0.01560407,0.6838971,0.02747734,0.002993171,0.11043,0.000557002],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4261034,0.0003994358,0.4368249,0.006060984,0.002097572,0.002643635,0.00004714407,0.00009579438,0.1257271],"genre_scores_gemma":[0.8860622,0.0001019523,0.1087097,0.003688627,0.0000535733,0.00005050664,0.00002706208,0.00002305062,0.001283315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.683623,"threshold_uncertainty_score":0.4534059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01100339158528007,"score_gpt":0.3287100102660457,"score_spread":0.3177066186807656,"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."}}