{"id":"W1617472016","doi":"","title":"Making Learning Design Standards Work with an Ontology of Educational Theories","year":2005,"lang":"en","type":"preprint","venue":"R-libre (Université Téluq)","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université TÉLUQ; Université du Québec à Montréal","funders":"","keywords":"Ontology; Computer science; OWL-S; Upper ontology; Process ontology; Relation (database); Java; Ontology-based data integration; Semantic Web; Ontology Inference Layer; Software engineering; Suggested Upper Merged Ontology; Ontology learning; World Wide Web; Knowledge management; Programming language; Semantic Web Stack; Database","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005778651,0.0002842052,0.0003875368,0.0001930964,0.0004059229,0.0002525234,0.001538022,0.0002278042,0.0004996355],"category_scores_gemma":[0.00007298521,0.0002980689,0.00008891357,0.0005318844,0.0001556656,0.0008833581,0.0008269973,0.0008638976,0.00002126353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003153641,"about_ca_system_score_gemma":0.002010951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006992056,"about_ca_topic_score_gemma":0.00005022261,"domain_scores_codex":[0.9978036,0.0004671797,0.0002193008,0.0006642437,0.0005018282,0.0003438718],"domain_scores_gemma":[0.9981093,0.0002760255,0.0004702853,0.0005974023,0.0004137739,0.0001331645],"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":[0.0004268702,0.0002970595,0.01156256,0.0001314343,0.0002638499,0.00002452938,0.03256335,0.09551005,0.00003130606,0.3619145,0.001010846,0.4962636],"study_design_scores_gemma":[0.004177613,0.003265969,0.6118524,0.003694465,0.0005544182,0.0003660463,0.04380167,0.04980978,0.0005324018,0.05101129,0.2254912,0.005442685],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3629754,0.0006793881,0.5589156,0.01240298,0.00143503,0.0007243254,0.00001460935,0.0004438591,0.06240888],"genre_scores_gemma":[0.9140904,0.00003980055,0.08136944,0.00008604088,0.0001756896,0.000006363421,0.00003233095,0.00002639762,0.004173544],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6002899,"threshold_uncertainty_score":0.9999471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02425529615486243,"score_gpt":0.2767135761708155,"score_spread":0.2524582800159531,"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."}}