{"id":"W3173782945","doi":"10.1111/cogs.12986","title":"The Other Accent Effect in Talker Recognition: Now You See It, Now You Don't","year":2021,"lang":"en","type":"article","venue":"Cognitive Science","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mandarin Chinese; Stress (linguistics); Psychology; Set (abstract data type); Linguistics; Acoustics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003763828,0.0004611052,0.0003718401,0.0004470512,0.0005932972,0.001339625,0.0004352368,0.0007072904,0.005026498],"category_scores_gemma":[0.01673442,0.0003360193,0.0005273334,0.0002376174,0.001517721,0.001662247,0.001513232,0.001096872,0.0005474756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003853148,"about_ca_system_score_gemma":0.0007350105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01301894,"about_ca_topic_score_gemma":0.01620692,"domain_scores_codex":[0.9981628,0.0003162087,0.000122512,0.0005426882,0.0006932184,0.0001624733],"domain_scores_gemma":[0.9895329,0.006665983,0.001121368,0.0009811849,0.001141381,0.000557177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00612803,0.0005098431,0.3143538,0.001182248,0.0006101374,0.001537632,0.02737928,0.001081468,0.5181786,0.005122482,0.001327844,0.1225886],"study_design_scores_gemma":[0.00005474384,0.0007010546,0.9730921,0.00007701976,0.0001812735,0.0009674909,0.001533914,0.0008369882,0.01967151,0.001269672,0.001549612,0.00006458877],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9721681,0.0007301377,0.007463253,0.0002896871,0.0001265199,0.00009612321,0.0001166104,0.00005774435,0.01895172],"genre_scores_gemma":[0.9959534,0.000150387,0.001721599,0.000254181,0.0000312698,0.00002651486,0.00009172457,0.00003297216,0.001737894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01301894,"threshold_uncertainty_score":0.0258863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03772468212168609,"score_gpt":0.3481541100150367,"score_spread":0.3104294278933506,"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."}}