{"id":"W1898875485","doi":"10.1017/s0272263115000236","title":"DOES STUDYING VOCABULARY IN SMALLER SETS INCREASE LEARNING?","year":2015,"lang":"en","type":"article","venue":"Studies in Second Language Acquisition","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Vocabulary learning; Learning effect; Vocabulary; Psychology; Artificial intelligence; Computer science; Natural language processing; Cognitive psychology; Linguistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002092963,0.0003580191,0.0006593029,0.0006063036,0.0002525204,0.001057066,0.0006509347,0.000851988,0.005433199],"category_scores_gemma":[0.0274473,0.0002558371,0.0004981729,0.0003481906,0.001020739,0.002359534,0.001236171,0.0007569852,0.0006448471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002623413,"about_ca_system_score_gemma":0.0004376167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004589829,"about_ca_topic_score_gemma":0.0007831029,"domain_scores_codex":[0.9986877,0.0005523101,0.00006586206,0.0002713919,0.0003468527,0.00007595187],"domain_scores_gemma":[0.9676802,0.02512413,0.002960391,0.001667241,0.000686241,0.00188175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.007549411,0.01233065,0.2016924,0.002362168,0.0009030762,0.0008402842,0.004052774,0.0009019307,0.08242863,0.0046744,0.003489527,0.6787748],"study_design_scores_gemma":[0.001189976,0.0156642,0.9148521,0.0004624292,0.0006693337,0.0009021423,0.001819042,0.00150076,0.02371088,0.02791618,0.01121029,0.0001028231],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911759,0.001160362,0.0007021725,0.001689521,0.00009693802,0.00003322835,0.0000529851,0.00006106223,0.005027908],"genre_scores_gemma":[0.993463,0.001377168,0.002500252,0.0006562773,0.0001707702,0.00006860004,0.0001082572,0.00003944508,0.00161619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005433199,"threshold_uncertainty_score":0.0181759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04794064054124444,"score_gpt":0.3683131560368892,"score_spread":0.3203725154956448,"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."}}