{"id":"W4401751452","doi":"10.1109/isbi56570.2024.10635756","title":"Unveiling the Temporal Patterns of a 4D CTP Stroke Lesion Outcome Prediction Model Through Attention Analysis","year":2024,"lang":"en","type":"article","venue":"","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canada Research Chairs; Calgary Foundation","keywords":"Computer science; Outcome (game theory); Stroke (engine); Artificial intelligence; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007491362,0.0005909317,0.0004284957,0.0006622517,0.0002003628,0.0007442744,0.0006419133,0.000731784,0.001242962],"category_scores_gemma":[0.002677018,0.0002405665,0.0007248258,0.0003263966,0.0003447268,0.0005538561,0.000714937,0.001153104,0.0001741907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006966126,"about_ca_system_score_gemma":0.0007938498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01028233,"about_ca_topic_score_gemma":0.008556357,"domain_scores_codex":[0.999833,0.00004194076,0.000008233264,0.00005464709,0.00002671086,0.0000355249],"domain_scores_gemma":[0.9993373,0.0004432717,0.00007674249,0.00003211293,0.00007735442,0.00003334634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003642255,0.0001279232,0.01656906,0.00008173496,0.0001279618,0.0004377451,0.0001643747,0.8533334,0.01267799,0.005597558,0.001809913,0.1087082],"study_design_scores_gemma":[0.000001757918,0.00001117225,0.0008589228,0.000002662884,0.000007746556,0.00001996795,0.000005446901,0.9973491,0.0004349829,0.001224212,0.00008089312,0.000003017972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4580986,0.0006799719,0.5361716,0.001525474,0.00007949222,0.00006566699,0.0004792902,0.0006576178,0.002242281],"genre_scores_gemma":[0.9815715,0.0001511914,0.01697134,0.0001074147,0.00002790013,0.00003292188,0.000185451,0.00002675609,0.0009255276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01028233,"threshold_uncertainty_score":0.02044499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04911493177375383,"score_gpt":0.3259988491296014,"score_spread":0.2768839173558476,"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."}}