{"id":"W7034516062","doi":"","title":"The Units of Gating and Access to Lexical Representations During Spoken Word Recognition","year":2023,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Populism, Right-Wing Movements","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; McGill University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Gating; Word (group theory); Categorical variable; Word recognition; Lexical diversity; Point (geometry); Word lists by frequency","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":[0.001200286,0.0003256289,0.0004793185,0.0008037703,0.0003073666,0.001910602,0.0005687908,0.000445786,0.001702427],"category_scores_gemma":[0.01149555,0.0005793248,0.0003449532,0.000571707,0.001179598,0.002956124,0.001385104,0.0006920832,0.0004292144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003445139,"about_ca_system_score_gemma":0.0003837466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001467112,"about_ca_topic_score_gemma":0.0009904461,"domain_scores_codex":[0.9989685,0.0003535798,0.0000608563,0.0003288436,0.0001838441,0.0001043374],"domain_scores_gemma":[0.9937384,0.004534396,0.0006228701,0.000550558,0.000313938,0.000239875],"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":[0.0009031824,0.0001417457,0.05764521,0.0002962093,0.0001117778,0.0003464405,0.006378504,0.006145628,0.6970414,0.01072952,0.0003253254,0.2199352],"study_design_scores_gemma":[0.00009555813,0.001643124,0.6205138,0.0001361833,0.00019554,0.001187744,0.003293553,0.1755908,0.1492775,0.04400609,0.003753023,0.0003071415],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9341313,0.0002415384,0.06131519,0.00008819623,0.00002376571,0.0000636569,0.0001510927,0.0001698589,0.003815524],"genre_scores_gemma":[0.9894575,0.0001001164,0.009621122,0.00002093829,0.00001248166,0.000056823,0.0001196575,0.0000646435,0.0005467072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001910602,"threshold_uncertainty_score":0.006347835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0613760196272843,"score_gpt":0.3128437867098707,"score_spread":0.2514677670825864,"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."}}