{"id":"W4387267528","doi":"10.36227/techrxiv.24190293.v1","title":"Defence against Image Distortions using Artificial Immune Systems","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Immunotherapy and Immune Responses","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Artificial intelligence; Pixel; Pattern recognition (psychology); Robustness (evolution); Artificial immune system; Noise (video); Image (mathematics); Object detection; Computer vision","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001712725,0.0008650878,0.0008286249,0.0007000864,0.0003428099,0.000979013,0.001413082,0.001476415,0.001312681],"category_scores_gemma":[0.004302941,0.0004255117,0.0008589272,0.0004383806,0.0009320337,0.001327059,0.001282367,0.001497323,0.0005055226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007552653,"about_ca_system_score_gemma":0.0005672673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001412886,"about_ca_topic_score_gemma":0.001053311,"domain_scores_codex":[0.9992188,0.0002269047,0.00003753307,0.0001728858,0.0002402065,0.0001035547],"domain_scores_gemma":[0.9979771,0.0008016637,0.0003328398,0.0004053265,0.0004089586,0.00007410593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002203416,0.0001343508,0.005052427,0.0001464303,0.0001733846,0.0001517882,0.0001528807,0.7700812,0.05065445,0.007396124,0.001719126,0.1641175],"study_design_scores_gemma":[0.00001146534,0.00008604129,0.0004372071,0.000007846631,0.00001560138,0.00005593125,0.00001551458,0.984476,0.01042754,0.003527022,0.0009310955,0.000008721169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2136572,0.0009317838,0.7780934,0.0009067525,0.0001864314,0.00008656176,0.00006353998,0.002087861,0.003986383],"genre_scores_gemma":[0.8524872,0.0002632936,0.1432958,0.0005018601,0.00009930284,0.00007349318,0.0001365796,0.0001060041,0.003036422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001712725,"threshold_uncertainty_score":0.009057879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05788378574303048,"score_gpt":0.2951113672388188,"score_spread":0.2372275814957883,"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."}}