{"id":"W6928927651","doi":"10.4224/21275411","title":"Learning and performance support systems: personal learning record: user studies white paper","year":2015,"lang":"en","type":"report","venue":"NPARC","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Context (archaeology); Learning analytics; Experiential learning; Learning Management; Work (physics); Active learning (machine learning); Learning design; Point (geometry); Online learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.009335501,0.0005027413,0.0009695949,0.0003378589,0.001420909,0.0003239041,0.0003412294,0.0004245812,0.0005382424],"category_scores_gemma":[0.001041969,0.0004824055,0.0002064112,0.0004319914,0.0006908326,0.0005008001,0.0002973337,0.001316609,0.00009757448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008190248,"about_ca_system_score_gemma":0.001183755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001142148,"about_ca_topic_score_gemma":0.001368182,"domain_scores_codex":[0.9933305,0.0007412524,0.0007204171,0.0008458252,0.003468236,0.0008937968],"domain_scores_gemma":[0.9967076,0.0001356712,0.0007353877,0.0002514845,0.001912949,0.0002569247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002793667,0.00003731799,0.8205778,0.001296198,0.0006230522,0.00006368067,0.02680001,0.0000384055,0.000002902035,0.0002222778,0.1244089,0.02590153],"study_design_scores_gemma":[0.0002075653,0.0002079884,0.0163014,0.0004343509,0.0002094877,0.00001219123,0.03950724,0.00005997155,1.645539e-7,0.00004281195,0.9424509,0.00056588],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.131173,0.004919255,0.000005684616,0.0003020985,0.004317228,0.0008652092,0.00001234107,0.0003432223,0.858062],"genre_scores_gemma":[0.6718192,0.06683455,0.0001813068,0.00005712255,0.001942249,0.000170902,0.00004222414,0.00009280693,0.2588597],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.818042,"threshold_uncertainty_score":0.9998791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05639547408472852,"score_gpt":0.3425176832298052,"score_spread":0.2861222091450767,"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."}}