{"id":"W4401835368","doi":"10.18280/ria.380405","title":"Data Augmentation by Wavelet Transform for Breast Cancer Based on Deep Learning","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Breast cancer; Wavelet transform; Wavelet; Artificial intelligence; Deep learning; Computer science; Pattern recognition (psychology); Cancer; 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":[0.000409586,0.0003848218,0.000352485,0.0004995177,0.0001247698,0.0003614317,0.0006846475,0.0003876413,0.001215886],"category_scores_gemma":[0.001052462,0.000199456,0.0004850611,0.0005733201,0.0002441334,0.0005931773,0.0005853223,0.0007527525,0.0004576707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004429561,"about_ca_system_score_gemma":0.0006069197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002575416,"about_ca_topic_score_gemma":0.00373599,"domain_scores_codex":[0.9998906,0.00001890716,0.000005873712,0.0000225792,0.00004315573,0.00001898982],"domain_scores_gemma":[0.9998156,0.00006692219,0.00002225146,0.0000339127,0.00005001197,0.00001116739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001732341,0.0001664293,0.002727874,0.0001245775,0.00007769698,0.0001596556,0.00008625317,0.3324727,0.04219537,0.008769576,0.003936872,0.6091097],"study_design_scores_gemma":[0.00000298927,0.00002719987,0.000352009,0.000005705271,0.000007414915,0.00003496336,0.000005186338,0.9914674,0.005523364,0.001590186,0.0009801439,0.000003464202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08595901,0.0007830852,0.9088477,0.0003527713,0.00007384341,0.00004559163,0.0002095682,0.001455693,0.00227274],"genre_scores_gemma":[0.7056561,0.0009026144,0.2870425,0.0002217936,0.00006154594,0.0001235165,0.00100644,0.0001647033,0.004820755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002575416,"threshold_uncertainty_score":0.005120814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04900731269338691,"score_gpt":0.3178882298732041,"score_spread":0.2688809171798172,"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."}}