{"id":"W1635457575","doi":"10.5539/elt.v8n10p107","title":"Intentional Vocabulary Learning Using Digital Flashcards","year":2015,"lang":"en","type":"article","venue":"English Language Teaching","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vocabulary; Vocabulary learning; Psychology; Vocabulary development; Set (abstract data type); Digital learning; Language acquisition; Value (mathematics); Teaching method; Mathematics education; Linguistics; Computer science; Pedagogy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007726136,0.0003265858,0.0002553453,0.0003970055,0.0002932579,0.001725187,0.0005331556,0.0003755469,0.004787811],"category_scores_gemma":[0.003300817,0.00009438419,0.0002707759,0.0002807185,0.0008700349,0.002715787,0.001878697,0.0004653173,0.0005177601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003003717,"about_ca_system_score_gemma":0.0005320462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003342314,"about_ca_topic_score_gemma":0.000562545,"domain_scores_codex":[0.9996282,0.0001234305,0.00002817755,0.0000854217,0.00008676954,0.00004805786],"domain_scores_gemma":[0.9986268,0.0008487768,0.0001251252,0.0001953509,0.0000698462,0.0001340131],"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":[0.0008532148,0.003144283,0.03892146,0.001045336,0.0000554108,0.001371583,0.02319892,0.002458027,0.1238141,0.08448893,0.002677714,0.7179711],"study_design_scores_gemma":[0.0008567475,0.01692398,0.1689428,0.001631301,0.0003889465,0.003745125,0.05112073,0.02949638,0.2046185,0.2590729,0.2629002,0.0003023449],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9449052,0.0001621069,0.02166707,0.0001977008,0.00004099963,0.0001147453,0.00002877151,0.0002012844,0.03268215],"genre_scores_gemma":[0.9756647,0.0002179595,0.01835603,0.00008069727,0.000008107289,0.00008727536,0.00004038588,0.00001249956,0.005532349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004787811,"threshold_uncertainty_score":0.01601678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02505020812605614,"score_gpt":0.3240887475927147,"score_spread":0.2990385394666585,"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."}}