{"id":"W4408040757","doi":"10.18280/ts.420136","title":"Conditional Generative Adversarial Network Based on Self-Attention Mechanism and VAE Algorithm and Its Applications","year":2025,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Generative grammar; Mechanism (biology); Adversarial system; Computer science; Generative adversarial network; Algorithm; Artificial intelligence; Theoretical computer science; Deep learning; Philosophy","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":[0.00007177013,0.0001343672,0.0001071038,0.00005862895,0.000218078,0.00002916201,0.00004663382,0.00005013586,0.00005342658],"category_scores_gemma":[0.000001207336,0.0001421209,0.00002606783,0.0001401903,0.00001835757,0.0000759705,0.00001428313,0.00009163673,0.000005232656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004554717,"about_ca_system_score_gemma":0.0000164668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001027843,"about_ca_topic_score_gemma":0.000001267102,"domain_scores_codex":[0.9993578,0.00001418905,0.0001611569,0.0002067881,0.000108313,0.0001517353],"domain_scores_gemma":[0.9997401,0.00006993592,0.00002565891,0.00006831356,0.00003857932,0.00005740286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001790776,0.0002395448,0.00003215814,0.00009086349,0.0002307577,0.000002541083,0.00008309021,0.3477557,0.006518416,0.5903591,0.002049293,0.05262063],"study_design_scores_gemma":[0.0008526085,0.00003872606,0.0008036877,0.00001934016,0.00004705504,0.00000104254,0.00002086272,0.9716197,0.0008826376,0.01900748,0.006559407,0.0001475002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001494683,0.0001262966,0.9966804,0.0001867036,0.00007259918,0.0005631603,0.0001394522,0.0001692438,0.0005674591],"genre_scores_gemma":[0.858884,0.0001255481,0.1376868,0.0005629428,0.0007025175,0.001407234,0.0004809466,0.00003045681,0.0001195927],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8589936,"threshold_uncertainty_score":0.579552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004531558595454663,"score_gpt":0.2098552685757596,"score_spread":0.205323709980305,"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."}}