{"id":"W2277207449","doi":"","title":"Enhancing the Learning Experience with 3D Learning Objects","year":2011,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Computer science; Experiential learning; Active learning (machine learning); Artificial intelligence; Psychology; Mathematics education","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":[0.0009489022,0.0004609593,0.0004000607,0.0002219385,0.001163041,0.00041472,0.0008657466,0.0001494591,0.0002292456],"category_scores_gemma":[0.0001092158,0.0003863671,0.00004987772,0.001422292,0.0002573992,0.0007043866,0.0002623303,0.001975308,0.00009443654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005075566,"about_ca_system_score_gemma":0.0008228134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001483637,"about_ca_topic_score_gemma":0.001430928,"domain_scores_codex":[0.9956491,0.0008188348,0.0006694227,0.001152578,0.0009512664,0.0007587865],"domain_scores_gemma":[0.9972277,0.0002972527,0.001189793,0.0007329933,0.0002408044,0.0003114245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002419482,0.0007486258,0.2006345,0.0002283523,0.00006649517,0.00002226995,0.03968789,0.001314476,0.000981916,0.6556,0.0002073534,0.1002662],"study_design_scores_gemma":[0.002190632,0.00312165,0.8316218,0.002467225,0.00007772029,0.00009505483,0.03653672,0.01991686,0.002896934,0.01056943,0.08763104,0.002874907],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5388183,0.00151294,0.06875624,0.03339688,0.002900208,0.004398319,0.000007536349,0.00206491,0.3481447],"genre_scores_gemma":[0.9636076,0.0003486935,0.002606974,0.001010839,0.0001291597,0.0004416104,0.0000150279,0.00004867263,0.03179139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6450305,"threshold_uncertainty_score":0.9998588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08122980883074467,"score_gpt":0.2886210702464252,"score_spread":0.2073912614156805,"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."}}