{"id":"W4378448087","doi":"10.1016/j.technovation.2023.102784","title":"Mapping the deepfake landscape for innovation: A multidisciplinary systematic review and future research agenda","year":2023,"lang":"en","type":"article","venue":"Technovation","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Multidisciplinary approach; Scholarship; Value (mathematics); Systematic review; Engineering ethics; Sociology; Computer science; Social science; Political science; MEDLINE; Engineering","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":[0.008293482,0.00005862616,0.0001545129,0.0002464334,0.001028186,0.00006682082,0.0001732722,0.00008532816,0.000005432104],"category_scores_gemma":[0.004108676,0.00004263162,0.00002235008,0.005172758,0.0001335015,0.0001090309,0.00006006367,0.0001346567,0.00001497625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003998502,"about_ca_system_score_gemma":0.0000710079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001452027,"about_ca_topic_score_gemma":0.00003750905,"domain_scores_codex":[0.9989499,0.00005138145,0.0002656593,0.0001423921,0.0003705738,0.0002200203],"domain_scores_gemma":[0.998692,0.000567742,0.0001064179,0.0001470923,0.0004705696,0.00001614336],"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":[0.000008493941,0.00002706656,0.000508929,0.0772441,0.00003862509,0.000002174578,0.02463447,1.863565e-7,0.0001143446,0.8368076,0.04072939,0.01988462],"study_design_scores_gemma":[0.000909459,0.0001767853,0.005688094,0.04966813,0.0001899668,0.000004212814,0.3253794,0.0007268435,0.00003934044,0.5254554,0.09091699,0.000845451],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.674601,0.02058562,0.0006614269,0.2187396,0.001644916,0.02067057,0.00005572937,0.003063676,0.05997748],"genre_scores_gemma":[0.9843358,0.005685047,0.0003895923,0.0007641407,0.001290107,0.002060561,0.0001127418,0.00003327899,0.005328663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3113523,"threshold_uncertainty_score":0.790808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1382719889321439,"score_gpt":0.4106158094608312,"score_spread":0.2723438205286873,"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."}}