{"id":"W2501038713","doi":"10.1075/sibil.47.08ch6","title":"Chapter 6. Modelling L2 vocabulary learning","year":2013,"lang":"en","type":"book-chapter","venue":"Studies in bilingualism","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Victoria","funders":"","keywords":"Vocabulary; Vocabulary learning; Linguistics; Computer science; Natural language processing; Artificial intelligence; Psychology; Mathematics education; Philosophy","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006198098,0.0006182485,0.000892965,0.0005141265,0.0002235267,0.00003829648,0.0002972088,0.0005947584,0.0681227],"category_scores_gemma":[0.0001177846,0.0005976375,0.0002619218,0.00005320003,0.0003418062,0.00007654329,0.0002373778,0.00182008,0.003454006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001166449,"about_ca_system_score_gemma":0.0000239473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001154464,"about_ca_topic_score_gemma":0.00001194843,"domain_scores_codex":[0.9972528,0.0001084076,0.0007989297,0.0009450224,0.0003197578,0.000575041],"domain_scores_gemma":[0.9982687,0.0004178258,0.0003871824,0.0006305076,0.0001991055,0.00009667949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001266593,0.00008221918,0.00004876502,0.000333571,0.002109596,0.004033008,0.2282624,0.004580678,0.00002206357,0.6927282,0.009334819,0.05833809],"study_design_scores_gemma":[0.001352395,0.000224116,0.00001903995,0.001196563,0.0001728038,0.0002071002,0.02846743,0.0007169239,0.000007860558,0.02355802,0.9423825,0.001695233],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004382636,0.1278063,0.0001064532,0.0001186583,0.002004598,0.0004042829,0.000005481394,0.0002355179,0.8649361],"genre_scores_gemma":[0.0466167,0.001990457,0.0004909697,0.003485909,0.001678097,0.00006974852,0.00007010989,0.0002385844,0.9453594],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9330477,"threshold_uncertainty_score":0.9996475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1094865146374832,"score_gpt":0.3708722918881823,"score_spread":0.261385777250699,"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."}}