{"id":"W4225336645","doi":"10.1109/access.2022.3160457","title":"Educational Data Mining: A Bibliometric Analysis of an Emerging Field","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Multidisciplinary approach; Data science; Field (mathematics); Extant taxon; Bibliometrics; Computer science; Educational data mining; Analytics; Library science; Social science; Sociology; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01139356,0.0009964368,0.001859937,0.1314821,0.002531935,0.009257818,0.001450826,0.001199715,0.005656458],"category_scores_gemma":[0.06884807,0.0004292615,0.001591487,0.1866438,0.001229969,0.007702867,0.003449888,0.00116683,0.002469504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002969561,"about_ca_system_score_gemma":0.006462538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005414113,"about_ca_topic_score_gemma":0.006453875,"domain_scores_codex":[0.9825074,0.003542649,0.002565332,0.001530391,0.009370354,0.0004837518],"domain_scores_gemma":[0.9413235,0.03418101,0.007175231,0.00332798,0.01296787,0.00102445],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001295162,0.0001646521,0.1231525,0.01289893,0.0007262059,0.000650493,0.003408782,0.002973063,0.001489508,0.03900852,0.08738293,0.7280149],"study_design_scores_gemma":[0.00005573648,0.0001956541,0.1954952,0.009087259,0.0009050639,0.00197338,0.01249883,0.02322066,0.004649427,0.05135803,0.7003167,0.0002439913],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.2875297,0.1942839,0.0999487,0.04565391,0.00307606,0.002494655,0.1719466,0.004321076,0.1907454],"genre_scores_gemma":[0.6183236,0.1499433,0.1212502,0.001757593,0.003208655,0.002142759,0.08958726,0.0008256426,0.01296097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9886065,"threshold_uncertainty_score":0.06025565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1044720757957683,"score_gpt":0.4291229528722822,"score_spread":0.3246508770765139,"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."}}