{"id":"W4312200521","doi":"10.1515/lingvan-2022-0017","title":"The Red Hen Anonymizer and the Red Hen Protocol for de-identifying audiovisual recordings","year":2022,"lang":"en","type":"article","venue":"Linguistics Vanguard","topic":"Hearing Impairment and Communication","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Fundación Séneca; Google; Alexander von Humboldt-Stiftung","keywords":"JSON; Computer science; Software; Protocol (science); Identification (biology); Face (sociological concept); Multimedia; Human–computer interaction; Speech recognition; World Wide Web; Programming language; Linguistics","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":[0.03626467,0.001025665,0.0009568845,0.003777514,0.002930224,0.004091033,0.002221333,0.002478948,0.1470459],"category_scores_gemma":[0.07201785,0.001454204,0.0006805212,0.002229728,0.002914648,0.005624579,0.00638518,0.00450379,0.0699674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001598789,"about_ca_system_score_gemma":0.005599926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001373503,"about_ca_topic_score_gemma":0.001791032,"domain_scores_codex":[0.9683779,0.01649209,0.004859952,0.002312932,0.006569215,0.00138784],"domain_scores_gemma":[0.9185116,0.02525934,0.003995008,0.03584022,0.0149955,0.001398449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002068595,0.0002727294,0.001508769,0.001080312,0.00005652736,0.001385968,0.005955906,0.001550263,0.01954908,0.13411,0.6670112,0.1654506],"study_design_scores_gemma":[0.0001509077,0.0001286727,0.001910154,0.0006810707,0.0000254298,0.0005626461,0.001032494,0.003767979,0.02145889,0.02754174,0.9425935,0.0001464661],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01073794,0.0003570587,0.7666093,0.006454321,0.002933656,0.02033312,0.03338702,0.03223015,0.1269575],"genre_scores_gemma":[0.1021547,0.001182365,0.5088083,0.006679698,0.001647906,0.07537706,0.05200663,0.01701937,0.235124],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1470459,"threshold_uncertainty_score":0.4919176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06178125760216429,"score_gpt":0.4070607818337643,"score_spread":0.3452795242316,"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."}}