{"id":"W2733310550","doi":"10.18747/phsg-coll3/id/482","title":"Using structural domain and learner models to link multiple data sources for learning analytics","year":2017,"lang":"en","type":"article","venue":"Das Repository der Padagogischen Hoschule St. Gallen (Padagogischen Hoschule St. Gallen)","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Domain (mathematical analysis); Analytics; Data analysis; Learning analytics; Data science; Link (geometry); Artificial intelligence; Data mining; Mathematics; Computer network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.002872764,0.001598871,0.00177043,0.0006024329,0.006003315,0.004443287,0.006873772,0.0007896845,0.0000258447],"category_scores_gemma":[0.001094302,0.001534947,0.0005115956,0.0003467088,0.000492504,0.005333401,0.00577922,0.001897202,0.00003536285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003047476,"about_ca_system_score_gemma":0.0006369093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001700688,"about_ca_topic_score_gemma":0.0004052714,"domain_scores_codex":[0.9891031,0.0008237369,0.001937723,0.003948471,0.001822916,0.002364056],"domain_scores_gemma":[0.9894759,0.0007610531,0.001831298,0.005858406,0.0009328586,0.001140482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002661005,0.001312538,0.1341481,0.003477638,0.01050791,0.001866726,0.0666672,0.4278074,0.1553717,0.1244161,0.01329741,0.05846631],"study_design_scores_gemma":[0.003166329,0.0009964332,0.004154627,0.0008883961,0.0004696494,0.0003155128,0.005283361,0.6982611,0.00697309,0.001623185,0.2739892,0.003879118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2075673,0.003415063,0.7778984,0.001666307,0.002462594,0.002425186,0.0002103166,0.0008408037,0.003513998],"genre_scores_gemma":[0.790998,0.0001488993,0.1902228,0.0002518279,0.002504557,0.0001678607,0.0001878163,0.0003240494,0.01519409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5876756,"threshold_uncertainty_score":0.9996759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1739148371122018,"score_gpt":0.3569857176907604,"score_spread":0.1830708805785586,"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."}}