{"id":"W4386307317","doi":"10.18280/ts.400438","title":"Hybrid CNN model employing patch-based exemplar for accessory spleen detection in abdominal CT images","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer science; Spleen; Computer vision; Pattern recognition (psychology); Medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.000200146,0.0004617101,0.0003454926,0.0003216738,0.0001106843,0.0003254684,0.00080187,0.0005281918,0.001033897],"category_scores_gemma":[0.0003829834,0.0001898443,0.0004455625,0.0002181742,0.0001798554,0.0003565275,0.0002861054,0.0003327223,0.00035132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004545559,"about_ca_system_score_gemma":0.0003537049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00810477,"about_ca_topic_score_gemma":0.007882981,"domain_scores_codex":[0.9999219,0.000007529892,0.000003178596,0.00003045433,0.00001850587,0.00001838039],"domain_scores_gemma":[0.9999121,0.00002027828,0.00001136753,0.00001045271,0.00003873578,0.000007045555],"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":[0.0002706654,0.0001223591,0.004627372,0.00009745985,0.0001550383,0.0004086403,0.00005503195,0.721438,0.04304825,0.002063584,0.002406986,0.2253066],"study_design_scores_gemma":[0.000001525957,0.0000232337,0.0004768891,0.000002560459,0.00001071932,0.00004035598,0.000002229492,0.9971851,0.001901273,0.0001374299,0.0002160331,0.000002667841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3035673,0.0013137,0.6865774,0.0003086837,0.0001788785,0.0000993072,0.0003253631,0.001551125,0.006078294],"genre_scores_gemma":[0.9240819,0.000510496,0.06875379,0.000129424,0.00004551295,0.00007406951,0.0003777949,0.00004489138,0.005982074],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00810477,"threshold_uncertainty_score":0.01611519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1886215115171552,"score_gpt":0.4135447077379359,"score_spread":0.2249231962207808,"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."}}