{"id":"W2622768147","doi":"10.1075/bpa.6.04sai","title":"The bilingual mental lexicon","year":2017,"lang":"en","type":"book-chapter","venue":"Bilingual processing and acquisition","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Mental lexicon; Lexicon; Aphasia; Neuroscience of multilingualism; Linguistics; Psychology; Functional magnetic resonance imaging; Computer science; Cognitive psychology; Natural language processing; Neuroscience","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0004440268,0.0004690515,0.0003644579,0.0001038474,0.002627562,0.000629565,0.000488102,0.0004120008,0.00005746122],"category_scores_gemma":[0.0003668223,0.0003223011,0.0001420948,0.00001779556,0.001202601,0.0002013443,0.0002277876,0.0006068682,0.00006351266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003879512,"about_ca_system_score_gemma":0.0004194759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006708971,"about_ca_topic_score_gemma":0.00002203763,"domain_scores_codex":[0.9977687,0.00006072304,0.0004334077,0.0009643743,0.0003457024,0.0004271125],"domain_scores_gemma":[0.9983947,0.0002987304,0.0005801974,0.0005260254,0.00008762738,0.0001127492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004444805,0.00009795354,0.000009258373,0.0003696499,0.00004215742,0.001853279,0.00336483,0.000003978064,0.1722131,0.01934666,0.001224247,0.8010304],"study_design_scores_gemma":[0.002655873,0.001278133,0.00001709168,0.0027163,0.0003931301,0.007065993,0.000648274,0.0006932442,0.1904416,0.1567649,0.6339502,0.00337534],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1888315,0.03101192,0.00004635457,0.003925135,0.004552129,0.001815976,0.0003346331,0.001051974,0.7684304],"genre_scores_gemma":[0.4828352,0.002316106,0.00009969624,0.002200921,0.00250916,0.00000947321,0.00008569885,0.0001505665,0.5097932],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.797655,"threshold_uncertainty_score":0.9999229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0379920705684853,"score_gpt":0.3015204717060083,"score_spread":0.263528401137523,"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."}}