{"id":"W4388023124","doi":"10.18280/ts.400548","title":"Experimental Investigations to Detection of Liver Cancer Using ResUNet","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cancer; Cancer detection; Computer science; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001167133,0.00007409229,0.00006402067,0.00006638305,0.00006098624,0.00000931063,0.00007761357,0.00004288548,0.00008148783],"category_scores_gemma":[0.00002047462,0.0000756087,0.00003450847,0.0001524532,0.00003291001,0.000003890349,0.00006132595,0.00003862129,0.00001365997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001974841,"about_ca_system_score_gemma":0.0000315942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001184347,"about_ca_topic_score_gemma":0.00003225008,"domain_scores_codex":[0.9994448,0.00002656336,0.0001736201,0.0001090062,0.0001246452,0.0001213824],"domain_scores_gemma":[0.9997473,0.000005750728,0.00006186614,0.00009688941,0.00003502465,0.0000531835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000238615,0.00001691817,0.0009294721,0.00001680534,0.00002086198,5.041369e-7,0.0004048059,0.01496596,0.9821519,0.00002425363,0.0006593318,0.0007853664],"study_design_scores_gemma":[0.0002327766,0.0002028762,0.005756291,0.00001779261,0.00001070045,0.000002550651,0.0001235862,0.03271912,0.955299,0.000004700794,0.005530966,0.00009969031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941541,0.00005649078,0.005305191,0.00005245774,0.00007724614,0.0001566218,0.00002010092,0.00001934923,0.0001584366],"genre_scores_gemma":[0.9975291,0.000007327635,0.001988474,0.0001671343,0.0001171516,0.00002578374,0.00004805478,0.00001044964,0.0001065082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02685291,"threshold_uncertainty_score":0.3083233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02975683163637803,"score_gpt":0.3037616246967139,"score_spread":0.2740047930603359,"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."}}