{"id":"W1578639305","doi":"10.1002/0470018860.s00262","title":"Speech Error Models of Language Production","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Cognitive Science","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Production (economics); Speech production; Speech error; Natural language processing; Speech recognition; Language model; Language production; Artificial intelligence; Linguistics; Psychology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004044813,0.0002654582,0.0004107655,0.0006262879,0.00006317491,0.000009500485,0.0006891116,0.0001532479,0.001001506],"category_scores_gemma":[0.002592992,0.00022682,0.00009461989,0.0008511185,0.002454153,0.0002358721,0.0001710302,0.0002540836,0.00005367592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001621682,"about_ca_system_score_gemma":0.0003037484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000736851,"about_ca_topic_score_gemma":0.00005684304,"domain_scores_codex":[0.9976353,0.0001078499,0.0003538697,0.0008856355,0.0006428054,0.0003745176],"domain_scores_gemma":[0.9986175,0.0002014455,0.0005627741,0.0003897317,0.0001444774,0.00008402557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001136516,0.0008046287,0.00006734702,0.0003581891,0.00002511655,0.0005134003,0.01156674,0.0000237558,0.8325701,0.0006938344,0.0186212,0.134642],"study_design_scores_gemma":[0.0004893098,0.0002642885,0.00006496726,0.000889192,0.00007412894,0.0002346975,0.001177666,0.00005136038,0.9785375,0.0004303819,0.01715853,0.0006279785],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.08206242,0.0004563506,0.00005414811,0.00005596766,0.0008691928,0.0005497624,0.0001707075,0.0001038514,0.9156776],"genre_scores_gemma":[0.4018904,0.0007314138,0.0006736334,0.0001996827,0.0006513911,0.0000145546,0.000007521301,0.0001324321,0.595699],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3199786,"threshold_uncertainty_score":0.9999117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0254109161755619,"score_gpt":0.3111644995073878,"score_spread":0.2857535833318259,"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."}}