{"id":"W2498286492","doi":"10.1111/cogs.12396","title":"Words Get in the Way: Linguistic Effects on Talker Discrimination","year":2016,"lang":"en","type":"article","venue":"Cognitive Science","topic":"Language, Discourse, Communication Strategies","field":"Arts and Humanities","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; York University","keywords":"Linguistics; Psychology; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009573975,0.0004047006,0.0002933163,0.0004029002,0.0003353927,0.001153351,0.0002657821,0.0007564606,0.004849338],"category_scores_gemma":[0.009876264,0.0004092094,0.0001976824,0.0001392422,0.0009387092,0.001241509,0.001314862,0.0009093557,0.0005876799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001621839,"about_ca_system_score_gemma":0.0001249008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002182575,"about_ca_topic_score_gemma":0.0002582478,"domain_scores_codex":[0.9991828,0.0003086684,0.00005854083,0.0002026312,0.0001840282,0.00006345179],"domain_scores_gemma":[0.993122,0.005483975,0.0005361015,0.0002743892,0.0002051594,0.0003783704],"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":[0.003135619,0.0002534694,0.006029892,0.0002133826,0.0000418666,0.0004416499,0.003132425,0.0001136829,0.9731847,0.0004531833,0.0000871237,0.01291293],"study_design_scores_gemma":[0.0006188294,0.006591361,0.4897719,0.0001334991,0.0005950784,0.002611708,0.006868433,0.002687521,0.4770681,0.01033477,0.00255067,0.0001681085],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949055,0.0001727494,0.0008431574,0.00009500698,0.00001608487,0.000009857117,0.0000253654,0.00003496812,0.003897289],"genre_scores_gemma":[0.9979919,0.00009479953,0.001126004,0.0001499095,0.00001097543,0.00001269741,0.00003206383,0.00003879757,0.0005428295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004849338,"threshold_uncertainty_score":0.01622266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04537350940143765,"score_gpt":0.3223217514170259,"score_spread":0.2769482420155883,"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."}}