{"id":"W3195903354","doi":"10.47611/jsrhs.v10i2.1612","title":"Impact of Model Architecture Against Adversarial Example's Effectivity","year":2021,"lang":"en","type":"article","venue":"Journal of Student Research","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Milton District Hospital","funders":"","keywords":"Adversarial system; Architecture; Computer science; Artificial intelligence; Cloning (programming); Machine learning; Adversarial machine learning; Programming language","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":[0.004349086,0.0001662091,0.0004762776,0.0004864905,0.0001950579,0.0001713784,0.001724159,0.0001014392,0.0000222535],"category_scores_gemma":[0.00103652,0.0001269717,0.0004149295,0.001017421,0.0001281231,0.0004779305,0.001402954,0.001818515,0.00000405175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003816813,"about_ca_system_score_gemma":0.001376061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000078918,"about_ca_topic_score_gemma":0.00001216557,"domain_scores_codex":[0.9949672,0.001231217,0.0005283203,0.0003143405,0.002448842,0.0005100569],"domain_scores_gemma":[0.9962525,0.001112501,0.0003551239,0.0006031356,0.001453306,0.0002234096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001582229,0.0005819586,0.03230233,0.00004253078,0.0003224812,0.0005253248,0.002873563,0.9078603,0.02145881,0.002062844,0.0004345832,0.03137703],"study_design_scores_gemma":[0.008023263,0.003476074,0.5221565,0.0005435663,0.0000694773,0.000565865,0.0005069718,0.444699,0.006591941,0.01227828,0.0003839453,0.0007051054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5810919,0.0001291868,0.4173943,0.0002588271,0.0002222539,0.00009836638,0.000001192047,0.000009750946,0.0007942633],"genre_scores_gemma":[0.9751021,0.0000537226,0.02438947,0.00001425619,0.0003431689,0.000001887088,6.596011e-7,0.00001403148,0.00008068154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4898541,"threshold_uncertainty_score":0.7900642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1211918281939953,"score_gpt":0.4543848082551557,"score_spread":0.3331929800611604,"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."}}