{"id":"W4401024554","doi":"10.24963/ijcai.2024/59","title":"Unlocking the Potential of Lightweight Quantized Models for Deepfake Detection","year":2024,"lang":"en","type":"article","venue":"","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"Office of Science; Defense Advanced Research Projects Agency; Advanced Scientific Computing Research; Florida High Tech Corridor Council; U.S. Department of Energy","keywords":"Magnitude (astronomy); Computer science; Quality (philosophy); Artificial intelligence; Physics","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":[0.0007341337,0.0006744463,0.0008600344,0.0006275196,0.0003529182,0.001364001,0.001537856,0.0007740547,0.003005974],"category_scores_gemma":[0.004104576,0.0003900948,0.0004392327,0.0005019,0.0009252928,0.003653764,0.001591729,0.001793296,0.000779431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008634211,"about_ca_system_score_gemma":0.0009791669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003223302,"about_ca_topic_score_gemma":0.004689777,"domain_scores_codex":[0.9994172,0.0001075502,0.00003125109,0.0001073276,0.0002768045,0.00005993612],"domain_scores_gemma":[0.9987154,0.0004660699,0.0001158757,0.0004842466,0.0001728188,0.00004556293],"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":[0.0004852016,0.0001151965,0.001360292,0.0001938278,0.0000732839,0.0001695104,0.0002074867,0.4540466,0.04382722,0.07739904,0.005251356,0.4168711],"study_design_scores_gemma":[0.000009742998,0.00003777987,0.0001167135,0.0000125667,0.00000607826,0.00004407493,0.00002289005,0.9703392,0.005961842,0.0220866,0.0013515,0.00001095604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02114809,0.0004168864,0.9752704,0.0003685505,0.00005283442,0.00003532222,0.0001149903,0.001577353,0.00101558],"genre_scores_gemma":[0.7317345,0.0004290248,0.2644347,0.0002975814,0.00005511907,0.00007083195,0.0002803665,0.0001908684,0.002507048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003223302,"threshold_uncertainty_score":0.01005602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02338048407729137,"score_gpt":0.2450306135087838,"score_spread":0.2216501294314924,"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."}}