{"id":"W2294770079","doi":"","title":"Testing the Model: Exploring Real-Life Use of E-Learning Standards, Digital Learning Objects, and Learning Object Repositories in Canada’s Education Community","year":2003,"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":"Innovation, Science and Economic Development Canada","funders":"","keywords":"Object (grammar); Learning object; Computer science; Digital learning; Experiential learning; Educational technology; Multimedia; World Wide Web; Artificial intelligence; Sociology; Pedagogy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003863138,0.0005444104,0.0004976004,0.00115924,0.002809381,0.003784834,0.003059636,0.002078253,0.003158304],"category_scores_gemma":[0.02499275,0.0004183518,0.0006606162,0.002869144,0.002836338,0.003597411,0.001782784,0.001703203,0.0006491294],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0208384,"about_ca_system_score_gemma":0.01642592,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9388734,"about_ca_topic_score_gemma":0.9475807,"domain_scores_codex":[0.998089,0.0007845989,0.00008723087,0.0003314634,0.00040534,0.0003022672],"domain_scores_gemma":[0.9769046,0.01540775,0.001355454,0.001369762,0.003969549,0.0009929846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003447906,0.006975618,0.7287846,0.0006519373,0.0003762512,0.001164341,0.08177331,0.04463357,0.003155715,0.02248054,0.01076513,0.09579117],"study_design_scores_gemma":[0.001098163,0.001277295,0.4678482,0.0002992183,0.0004647794,0.0003967069,0.1412248,0.3538281,0.004253372,0.009835206,0.0191326,0.0003414857],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952073,0.00004284016,0.001067784,0.0005022841,0.000005035939,0.0001256242,0.0006029648,0.0000476095,0.002398649],"genre_scores_gemma":[0.9926463,0.00005527606,0.00466996,0.0001284479,0.000002626602,0.0001340739,0.001053397,0.00002780743,0.001282039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9791616,"threshold_uncertainty_score":0.1511939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1270263193129373,"score_gpt":0.2900205657174944,"score_spread":0.1629942464045571,"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."}}