{"id":"W1489507727","doi":"10.1007/978-3-540-75975-1_20","title":"The Use of Ontologies and Rules to Assist in Academic Advising","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Ontology; Interoperability; Computer science; Grading (engineering); Upper ontology; Knowledge management; World Wide Web; Engineering management; Engineering ethics; Software engineering; Data science; Mathematics education; Semantic Web; Engineering; Psychology; Epistemology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001238151,0.0003236902,0.0004562324,0.0007139597,0.0001903012,0.0003895416,0.002521363,0.0003150393,7.767221e-7],"category_scores_gemma":[0.0006493604,0.0002238561,0.00005715158,0.0004532772,0.001138035,0.0004723062,0.001657225,0.0007387717,0.000003941771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001282286,"about_ca_system_score_gemma":0.0002235208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001194948,"about_ca_topic_score_gemma":0.001058715,"domain_scores_codex":[0.9973112,0.00003803896,0.0005647214,0.000892507,0.0006097431,0.0005837762],"domain_scores_gemma":[0.9960582,0.002623145,0.0002315947,0.0008735295,0.000123961,0.00008955139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008909405,0.000005909701,0.001791518,0.00001825501,0.000004257764,0.00004017294,0.0007612181,0.003208677,0.00005754235,0.02886781,0.00001319938,0.9652225],"study_design_scores_gemma":[0.0007736412,0.0006498859,0.1323294,0.003245778,0.00002270968,0.0002833727,0.000007560678,0.3291303,0.004205227,0.5126952,0.01445973,0.002197179],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004801493,0.001705297,0.9903249,0.00154228,0.0008241737,0.0002715211,0.000001609109,0.00006749392,0.0004612969],"genre_scores_gemma":[0.2607911,0.0004419805,0.7366769,0.001736475,0.0001606312,0.00000593809,7.453817e-7,0.00002126273,0.0001649493],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9630253,"threshold_uncertainty_score":0.9128588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0861654985409858,"score_gpt":0.312024682948653,"score_spread":0.2258591844076672,"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."}}