{"id":"W2286919200","doi":"","title":"Researching Self-Regulated Learning: Tracking the Missing Link with Interactive Softwar","year":2005,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria; Simon Fraser University","funders":"","keywords":"Link (geometry); Missing data; Computer science; Self-regulated learning; Tracking (education); Artificial intelligence; Psychology; Machine learning; Social psychology; Computer network; Pedagogy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002448631,0.0002807396,0.0003972788,0.001164974,0.0006472999,0.003272911,0.001139105,0.001013488,0.005142835],"category_scores_gemma":[0.03443457,0.0003787639,0.000231493,0.001014908,0.001770776,0.005128398,0.001993445,0.002032942,0.0006838311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007190364,"about_ca_system_score_gemma":0.0005274477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001199919,"about_ca_topic_score_gemma":0.001399654,"domain_scores_codex":[0.9986672,0.0004985755,0.00003838443,0.0003635148,0.0003152587,0.0001171558],"domain_scores_gemma":[0.9730188,0.01951065,0.002464124,0.002665174,0.001514075,0.0008272101],"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":[0.001292511,0.001856933,0.228244,0.00112177,0.0003756171,0.0002584521,0.01813856,0.0207912,0.0387903,0.1470298,0.004909817,0.537191],"study_design_scores_gemma":[0.0001090499,0.001203673,0.386594,0.0004262471,0.0002293039,0.000386145,0.009374553,0.2304315,0.03591473,0.3136056,0.02144849,0.0002766381],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9110579,0.001241013,0.0608842,0.001917582,0.0001003973,0.00006744319,0.0002475331,0.0002185343,0.02426544],"genre_scores_gemma":[0.9928079,0.0001638278,0.005494396,0.0001057632,0.00002315878,0.00003914297,0.00005110005,0.00005596208,0.001258747],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.005142835,"threshold_uncertainty_score":0.01720452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05403887290208938,"score_gpt":0.3148153385423511,"score_spread":0.2607764656402617,"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."}}