{"id":"W2142618358","doi":"10.19173/irrodl.v15i2.1704","title":"Mass customization of education by an institution of HE: What can we learn from industry?","year":2014,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Configurator; Mass customization; Quality (philosophy); Personalization; Product (mathematics); Curriculum; Open learning; Computer science; Institution; Point (geometry); Knowledge management; Open education; Open educational resources; Engineering management; Business; Teaching method; Engineering; Marketing; World Wide Web; Mathematics education; Cooperative learning; Pedagogy; Sociology; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003733995,0.00008010445,0.000218166,0.0001455919,0.0001129509,0.0002599334,0.001392095,0.00006811898,0.0001021651],"category_scores_gemma":[0.00171272,0.00006466341,0.000026567,0.0006357189,0.0001398189,0.001134611,0.0003900083,0.0006158228,0.000003919005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008731496,"about_ca_system_score_gemma":0.000440024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001587926,"about_ca_topic_score_gemma":0.00002888503,"domain_scores_codex":[0.9976211,0.0009955147,0.000430703,0.0002351221,0.0005791016,0.0001384435],"domain_scores_gemma":[0.9983289,0.0003907994,0.0003415137,0.0002648465,0.0006004251,0.00007357459],"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":[0.0001094543,0.0007635629,0.06606545,0.001412542,0.00008222106,7.145972e-7,0.00278887,0.004016729,0.003550611,0.1222131,0.006548921,0.7924479],"study_design_scores_gemma":[0.004325529,0.001297617,0.05528764,0.0726936,0.00007596717,0.00002333288,0.09068137,0.1971114,0.01468664,0.02420929,0.5385395,0.001068101],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7413656,0.0328776,0.06620328,0.1122821,0.001818141,0.003310896,0.0001128476,0.00007333256,0.04195626],"genre_scores_gemma":[0.9802741,0.0182229,0.0007211499,0.0001157945,0.00003642751,0.00002642324,0.0003107542,0.000004920688,0.0002874585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7913797,"threshold_uncertainty_score":0.2675478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05802920274910821,"score_gpt":0.4091253264711059,"score_spread":0.3510961237219977,"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."}}