{"id":"W4413593307","doi":"10.64628/aam.n3xfrqx7w","title":"How to combat the unethical and costly use of deepfakes","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Business; Psychology","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":[0.01013094,0.0004229502,0.0004762772,0.00126704,0.002618528,0.00659276,0.001355788,0.00598813,0.01791761],"category_scores_gemma":[0.04511471,0.0002948686,0.0004881309,0.000729977,0.01097741,0.01038743,0.002674417,0.004984532,0.002427828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00215647,"about_ca_system_score_gemma":0.005280876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003641614,"about_ca_topic_score_gemma":0.003884678,"domain_scores_codex":[0.9935443,0.003624316,0.000207825,0.0005104577,0.001413095,0.0006998992],"domain_scores_gemma":[0.9734081,0.01540771,0.002345953,0.00383193,0.003803387,0.001202883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004608293,0.00008120591,0.001304203,0.0001973267,0.00006466179,0.00008616586,0.00119574,0.002976754,0.001271388,0.9275989,0.01394887,0.05122868],"study_design_scores_gemma":[0.00001617796,0.00001897228,0.0004854503,0.0001247364,0.00001128125,0.00008455337,0.0009136842,0.002800908,0.0006184684,0.9686201,0.02628868,0.00001712377],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.07404717,0.004346797,0.2093079,0.281823,0.001586632,0.0002226877,0.0001698289,0.0003650795,0.4281309],"genre_scores_gemma":[0.912827,0.00186862,0.04133179,0.01022282,0.0005068093,0.0001858966,0.0000450735,0.0001916036,0.03282047],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.01791761,"threshold_uncertainty_score":0.05994034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.188338349860663,"score_gpt":0.4123010728179139,"score_spread":0.223962722957251,"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."}}