{"id":"W4285347669","doi":"10.1109/aipr52630.2021.9762068","title":"Adaptive Cycle-consistent Adversarial Network for Malaria Blood Cell Image Synthetization","year":2021,"lang":"en","type":"article","venue":"","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Discriminator; Computer science; Artificial intelligence; Pattern recognition (psychology); Convolutional neural network; Generator (circuit theory); Malaria; Feature (linguistics); Algorithm; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006394236,0.00009891461,0.0001006324,0.00001639191,0.00009387748,0.00005571464,0.00007218897,0.00006428894,0.00009515562],"category_scores_gemma":[0.00001320826,0.0001049358,0.00006389889,0.0001328011,0.00001632629,0.00008492234,0.00002630612,0.00006547075,0.00001283633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001931582,"about_ca_system_score_gemma":0.0000228566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003863558,"about_ca_topic_score_gemma":0.000003798669,"domain_scores_codex":[0.9994548,0.000007834875,0.0001450874,0.0001561158,0.00005615481,0.0001799891],"domain_scores_gemma":[0.9996198,0.00004228673,0.00002276459,0.0001692642,0.0001101078,0.00003570635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001176351,0.0009979322,0.0001098426,0.001051061,0.0005568364,0.00005007914,0.0006394624,0.1905721,0.3687686,0.2506864,0.1393379,0.04711211],"study_design_scores_gemma":[0.0007025411,0.00003585212,0.00004776267,0.00004700337,0.0002040912,0.00001479651,0.00008989736,0.5720117,0.4016523,0.01207655,0.01272059,0.0003968752],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005058252,0.0001840557,0.971598,0.0001916418,0.0001282967,0.0002453294,0.00002301616,0.0006030669,0.02652075],"genre_scores_gemma":[0.4189059,0.00003040303,0.5800045,0.00006771924,0.0002091431,0.00009651457,0.00005768809,0.00003597779,0.0005922677],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4184,"threshold_uncertainty_score":0.4279156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007840443748300329,"score_gpt":0.2085222886541487,"score_spread":0.2006818449058483,"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."}}