{"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":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.0004508103,0.00005833298,0.0001447774,0.02945552,0.0001475573,0.0001595241,0.003592332,0.00001413172,0.0002379003],"category_scores_gemma":[0.0001414588,0.00006097633,0.00004952984,0.1479362,0.000009722477,0.0007767221,0.0009427724,0.0001164329,0.000001259753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001259509,"about_ca_system_score_gemma":0.0001219747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002004834,"about_ca_topic_score_gemma":0.00002178643,"domain_scores_codex":[0.9988706,0.00007262277,0.0001932373,0.0003245011,0.0004100178,0.0001290184],"domain_scores_gemma":[0.998462,0.0002627203,0.00014869,0.001006419,0.00006807368,0.00005207202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001327112,0.001193186,0.4228902,0.000040745,0.001240223,0.00002426305,0.001442943,0.162355,0.0002945874,0.002945241,0.03100733,0.3765531],"study_design_scores_gemma":[0.00006974367,0.00005305995,0.04742867,0.000002029862,0.0001236498,0.000002247432,0.00005800501,0.9497373,0.00008443149,0.0003210485,0.00202207,0.0000977918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9444125,0.0001189743,0.04899104,0.005396564,0.0004668987,0.00003126956,0.00003537266,0.00004453298,0.0005028451],"genre_scores_gemma":[0.9915003,0.000006740843,0.007741833,0.0003323525,0.00008199273,0.000003439937,0.00007090934,0.000003768174,0.0002586501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7873822,"threshold_uncertainty_score":0.9815448,"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."}}