{"id":"W2345653044","doi":"","title":"Personalization in learning by knowledge engineering with didactic knowledge","year":2010,"lang":"en","type":"article","venue":"Common Library Network (Der Gemeinsame Bibliotheksverbund)","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Athabasca University","keywords":"Storyboard; Personalization; Profiling (computer programming); Pluralistic walkthrough; Computer science; Curriculum; Process (computing); Data science; Human–computer interaction; Multimedia; World Wide Web; Usability; Psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005538389,0.0005422423,0.000419291,0.001712677,0.0005955501,0.004317309,0.001078069,0.001012408,0.002558157],"category_scores_gemma":[0.02381381,0.0005305348,0.0006493652,0.001471871,0.002123205,0.007329756,0.002558575,0.001011485,0.000436605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002071336,"about_ca_system_score_gemma":0.001280844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001445076,"about_ca_topic_score_gemma":0.002211814,"domain_scores_codex":[0.9953934,0.002249395,0.0002299877,0.001013379,0.0009184096,0.0001954458],"domain_scores_gemma":[0.9842056,0.008328543,0.00137442,0.004812175,0.0008705739,0.0004087534],"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":[0.0003135025,0.001273607,0.07333247,0.0005738849,0.0002638355,0.000394541,0.01089683,0.1172877,0.006380082,0.1990729,0.00150658,0.588704],"study_design_scores_gemma":[0.00008134239,0.0007231365,0.03098055,0.0003165287,0.0001955565,0.0006623444,0.003559243,0.4233181,0.01652251,0.4729815,0.0505363,0.0001228483],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.244908,0.0006279892,0.7252507,0.00127961,0.00005018402,0.0005580808,0.0001715882,0.000752099,0.02640165],"genre_scores_gemma":[0.7615558,0.0002813415,0.2347247,0.00009671025,0.0000248603,0.0002164329,0.0001572636,0.00006292719,0.002879933],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005538389,"threshold_uncertainty_score":0.02929014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004477658780137962,"score_gpt":0.2210985832927713,"score_spread":0.2166209245126333,"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."}}