{"id":"W1995934506","doi":"10.1016/j.eswa.2008.05.011","title":"Information extraction from syllabi for academic e-Advising","year":2008,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Syllabus; Information extraction; Extraction (chemistry); Academic advising; Information retrieval; Mathematics education; Higher education; Psychology; Chromatography; Chemistry; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009537335,0.001078469,0.0008005354,0.01569161,0.001169973,0.002042089,0.001026591,0.001119179,0.01463886],"category_scores_gemma":[0.009331645,0.0004035244,0.0009586909,0.01204516,0.0002405789,0.001558347,0.001270056,0.001089438,0.009758851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001411532,"about_ca_system_score_gemma":0.004800928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01818447,"about_ca_topic_score_gemma":0.02492866,"domain_scores_codex":[0.998664,0.0002810133,0.0002351759,0.0002249766,0.0004003278,0.0001944748],"domain_scores_gemma":[0.993454,0.002838053,0.0004876367,0.0004128667,0.002257016,0.0005504491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005898933,0.0006138042,0.02679936,0.001733325,0.00007766278,0.0004084825,0.0004384812,0.001955596,0.02167301,0.00299608,0.07896143,0.8637528],"study_design_scores_gemma":[0.0003108093,0.0009361041,0.196943,0.001820497,0.001012149,0.001348539,0.00437001,0.1675736,0.1432198,0.01756831,0.4645271,0.0003701174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3486077,0.008320469,0.2678829,0.004044579,0.00160749,0.004612483,0.2683142,0.02390221,0.07270791],"genre_scores_gemma":[0.4279144,0.002576245,0.3702288,0.000345198,0.0005502542,0.002186468,0.1795245,0.0005786931,0.01609543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01818447,"threshold_uncertainty_score":0.04897189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02437700956399376,"score_gpt":0.2810708853278222,"score_spread":0.2566938757638285,"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."}}