{"id":"W2746567044","doi":"10.13034/jsst.v10i1.181","title":"The Application of Machine Learning to Education","year":2017,"lang":"en","type":"article","venue":"Journal of Student Science and Technology","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ranking (information retrieval); Test (biology); Mathematics education; Quality (philosophy); Field (mathematics); Accountability; Computer science; Standardized test; Government (linguistics); Artificial intelligence; Machine learning; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001041831,0.00003290394,0.00007583087,0.0002249299,0.0006584134,0.000158927,0.001651599,0.00001981088,8.661096e-8],"category_scores_gemma":[0.0004535968,0.00002045334,0.00001199043,0.0003417008,0.0003044124,0.0002238198,0.0003505869,0.0001549576,0.000001333155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001791296,"about_ca_system_score_gemma":0.0001754059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000646424,"about_ca_topic_score_gemma":0.000004664294,"domain_scores_codex":[0.99936,0.000007409427,0.0001567835,0.00008882059,0.0002958906,0.00009107544],"domain_scores_gemma":[0.9987943,0.00002333931,0.0003976389,0.0002791626,0.0004690209,0.00003654218],"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":[0.000001631591,0.00006046813,0.1475052,0.000002398675,0.000005796795,6.436397e-7,0.0002474747,0.00005052104,0.009402722,0.09646426,0.0000497477,0.7462091],"study_design_scores_gemma":[0.0008760624,0.002652005,0.6800359,0.0001964166,0.00004918601,0.0003647955,0.003860436,0.0802688,0.01571999,0.08420191,0.1313825,0.0003919919],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9066284,0.0003495381,0.02818101,0.06410451,0.0002510739,0.00006361146,6.919826e-8,0.00001533588,0.0004065034],"genre_scores_gemma":[0.9947135,0.0001013343,0.0050496,0.00003446187,0.00002502775,8.385693e-7,1.028716e-8,9.622673e-7,0.00007422067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7458171,"threshold_uncertainty_score":0.506405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00834636361553105,"score_gpt":0.3405394049137784,"score_spread":0.3321930412982473,"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."}}