{"id":"W4408311134","doi":"10.4108/eettti.6833","title":"The Role of Machine Learning in Smart Education: Taxonomy, Challenges, and Use Cases","year":2024,"lang":"en","type":"article","venue":"EAI Endorsed Transactions on Tourism Technology and Intelligence","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Taxonomy (biology); Computer science; Artificial intelligence; Machine learning; Data science; Biology; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001735946,0.0001055331,0.0001160485,0.0004569203,0.0001719241,0.00006254864,0.0002238349,0.0001071336,0.000004422763],"category_scores_gemma":[0.00007314749,0.00008310511,0.00002861033,0.000472627,0.0001875054,0.000189671,0.00001573232,0.0006108477,0.000004708224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000130098,"about_ca_system_score_gemma":0.00006786326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007396219,"about_ca_topic_score_gemma":0.0001202702,"domain_scores_codex":[0.9992702,0.00005103056,0.0001895353,0.0002735832,0.00006793786,0.0001476852],"domain_scores_gemma":[0.9991665,0.0005095877,0.00003721115,0.0002262572,0.00002945106,0.00003102905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003721573,0.00005106328,0.0002284199,0.00001289712,0.00001406119,0.00001244217,0.0002115904,0.0001800573,0.00003137946,0.08821133,0.000003575332,0.9110395],"study_design_scores_gemma":[0.0002092414,0.001269016,0.001163028,0.0007330601,0.00006037625,0.0008482619,0.00490739,0.3851989,0.02432225,0.1212351,0.4594297,0.0006236719],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07731169,0.2360302,0.6228308,0.05935363,0.001005159,0.0006646122,0.00001197524,0.001228004,0.001563905],"genre_scores_gemma":[0.9782084,0.01750651,0.003475029,0.00001834459,0.00001243934,0.00003144382,4.735712e-7,0.000005986157,0.0007413612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9104158,"threshold_uncertainty_score":0.3388928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01805924478772813,"score_gpt":0.2506116991077529,"score_spread":0.2325524543200248,"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."}}