{"id":"W4361023872","doi":"10.16995/dscn.8651","title":"Synthetic Media and Deepfakes: Tactical Media in the Pluriverse","year":2023,"lang":"en","type":"article","venue":"Digital Studies / Le champ numérique","topic":"Geographies of human-animal interactions","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Foregrounding; Witness; Narrative; Sociology; History; Disadvantaged; Representation (politics); Media studies; Political science; Literature; Art; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00251023,0.0005676468,0.0001910992,0.001352777,0.005142247,0.01007599,0.0006194733,0.001354865,0.005307702],"category_scores_gemma":[0.005156467,0.0002070132,0.0002436727,0.0007406045,0.02298364,0.008325359,0.006652932,0.002227794,0.0003781601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001912904,"about_ca_system_score_gemma":0.0007475402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001352679,"about_ca_topic_score_gemma":0.003209264,"domain_scores_codex":[0.9982916,0.001184783,0.0000314082,0.0001461593,0.0002147804,0.0001312313],"domain_scores_gemma":[0.9962116,0.002709787,0.0001998071,0.0005894176,0.0001402937,0.0001491721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005950961,0.00001577864,0.001047116,0.0001080589,0.000006523425,0.0005714055,0.1655588,0.0002880828,0.001304299,0.8098766,0.001861151,0.01930267],"study_design_scores_gemma":[0.00003265221,0.0001105338,0.002575773,0.000719852,0.00001965485,0.001477516,0.1993818,0.001112437,0.005098947,0.1942942,0.5951231,0.00005364416],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2696434,0.002584891,0.02586536,0.007436108,0.0005502725,0.00007844423,0.0001117413,0.0001275616,0.6936023],"genre_scores_gemma":[0.9784112,0.0003662247,0.002787102,0.0002773798,0.00008735177,0.00003761965,0.00002964459,0.00005718969,0.01794623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01007599,"threshold_uncertainty_score":0.01775604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04902804024127805,"score_gpt":0.3251566930571063,"score_spread":0.2761286528158283,"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."}}