{"id":"W4280598218","doi":"10.18280/ria.360212","title":"Semantics Convolutional Neural Network for Medical Images Analysis","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"AI in cancer detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Computer science; Semantics (computer science); Artificial intelligence; Feature (linguistics); Pattern recognition (psychology); Image (mathematics); False positive paradox; Layer (electronics); Data mining; Deep learning; Semantic feature; Artificial neural network; Noise (video)","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":[0.0005097045,0.000664713,0.0004168031,0.001197623,0.0001959221,0.0006470078,0.0005951932,0.0006398802,0.002138828],"category_scores_gemma":[0.001311673,0.0002162944,0.0005888183,0.001042916,0.000283011,0.0007811662,0.0004802203,0.0006922078,0.0006970081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009914213,"about_ca_system_score_gemma":0.001142674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009429205,"about_ca_topic_score_gemma":0.00960766,"domain_scores_codex":[0.9997372,0.00004650752,0.0000167458,0.00006601193,0.0001001469,0.00003330838],"domain_scores_gemma":[0.9997347,0.00007869511,0.00004038549,0.00003903541,0.00009382737,0.00001341418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004050483,0.0001686479,0.005885129,0.0002901811,0.0002405346,0.000273163,0.00005617134,0.2532178,0.01543615,0.01587605,0.01563927,0.6925119],"study_design_scores_gemma":[0.000006814579,0.00002775348,0.001466137,0.00001838602,0.00002694645,0.00008796147,0.00001082882,0.9809586,0.004741066,0.009005886,0.003638349,0.00001123484],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04167932,0.004540775,0.9409859,0.001243847,0.0002141223,0.0001270654,0.001657315,0.003666224,0.005885473],"genre_scores_gemma":[0.7158061,0.003685525,0.2665043,0.0004928895,0.0001943848,0.000220558,0.003847739,0.0002049599,0.009043542],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009429205,"threshold_uncertainty_score":0.01874864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03053992316767669,"score_gpt":0.2858623798987183,"score_spread":0.2553224567310416,"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."}}