{"id":"W4389952510","doi":"10.5539/ies.v17n1p1","title":"A Study on the Construction of College English Context Vocabulary Teaching Based on Hands-Off Data-Driven Learning in China","year":2023,"lang":"en","type":"article","venue":"International Education Studies","topic":"Foreign Language Teaching Methods","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Southwest University","keywords":"Vocabulary; Context (archaeology); Mathematics education; Computer science; Teaching method; College English; Control (management); English vocabulary; Psychology; Artificial intelligence; Linguistics","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":[0.002122999,0.0004156854,0.0004010251,0.001029398,0.002091211,0.000803981,0.0006576123,0.0003875563,0.001344244],"category_scores_gemma":[0.002242937,0.0003394087,0.0004651534,0.0007351874,0.0008924255,0.0008563102,0.001115575,0.0005753765,0.000144139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003024605,"about_ca_system_score_gemma":0.004082731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01970261,"about_ca_topic_score_gemma":0.03267546,"domain_scores_codex":[0.9987685,0.0003736649,0.00007725335,0.0002147398,0.0002449232,0.0003208467],"domain_scores_gemma":[0.9985681,0.0003110792,0.0001452027,0.0001077812,0.0002107698,0.0006569877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005277102,0.01462499,0.4882688,0.0005709855,0.00008444954,0.00204818,0.2782069,0.0008295617,0.02388668,0.001717733,0.0006198311,0.1886141],"study_design_scores_gemma":[0.0001445418,0.008198573,0.8396389,0.000110856,0.0001144784,0.0004149384,0.1335199,0.002070816,0.007934188,0.0004075573,0.00735336,0.00009196615],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993858,0.00001682401,0.0001252286,0.00002520383,0.000001572685,0.0000511481,0.000004619936,0.000001622308,0.0003879574],"genre_scores_gemma":[0.9977817,0.00008558252,0.0007025353,0.00002733405,0.000003262268,0.000060499,0.000021063,0.000002163197,0.001316063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01970261,"threshold_uncertainty_score":0.03917587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.109432455707579,"score_gpt":0.4492415981037344,"score_spread":0.3398091423961554,"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."}}