{"id":"W2247773252","doi":"","title":"Usability Evaluation of Ontology Mapping for Learning Object Retrieval","year":2009,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Usability; Computer science; Information retrieval; Ontology; Object (grammar); Learning object; World Wide Web; Artificial intelligence; Human–computer interaction","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":[0.02069758,0.0009795743,0.001025453,0.002810227,0.001097294,0.002078313,0.001119952,0.001139342,0.002323593],"category_scores_gemma":[0.1037177,0.000437403,0.001291422,0.001552618,0.0007240653,0.002536104,0.002041501,0.0005632325,0.0005526493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102082,"about_ca_system_score_gemma":0.001367612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006739242,"about_ca_topic_score_gemma":0.006775024,"domain_scores_codex":[0.9762464,0.01663884,0.00271697,0.001053812,0.002914331,0.0004296678],"domain_scores_gemma":[0.8558437,0.1199527,0.001690957,0.006483224,0.01524652,0.0007829234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0220969,0.005477646,0.05952425,0.01081585,0.002496592,0.001053927,0.02181832,0.007925689,0.06957772,0.002355727,0.009699886,0.7871575],"study_design_scores_gemma":[0.007591395,0.03646769,0.343286,0.00378136,0.01177532,0.007328497,0.03425483,0.2629771,0.2076129,0.006682059,0.07709586,0.001146937],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9427791,0.002563593,0.04575109,0.0003808287,0.0001957203,0.00161921,0.0005890933,0.001522647,0.00459876],"genre_scores_gemma":[0.9374315,0.0006352188,0.05745995,0.0001820087,0.00004120878,0.0007909536,0.0011337,0.0003489884,0.001976378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02069758,"threshold_uncertainty_score":0.1094606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1218625598906572,"score_gpt":0.3475554324476328,"score_spread":0.2256928725569755,"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."}}