{"id":"W4256555295","doi":"10.4018/978-1-4666-8751-6.ch066","title":"Incidental Learning in 3D Virtual Environments","year":2015,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Visual and Cognitive Learning Processes","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Salience (neuroscience); Salient; Style (visual arts); Virtual learning environment; Computer science; Psychology; Multimedia; Human–computer interaction; Cognitive psychology; Artificial intelligence","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":[0.0005529128,0.0003125151,0.0002610703,0.0005787422,0.0002789632,0.002260678,0.0004737664,0.0003425571,0.002077173],"category_scores_gemma":[0.005771503,0.0001737143,0.0003323006,0.0003279927,0.001018179,0.001954725,0.001598158,0.0005187386,0.0003101788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002018546,"about_ca_system_score_gemma":0.0002575547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005077505,"about_ca_topic_score_gemma":0.0008832302,"domain_scores_codex":[0.9994684,0.000210397,0.00003415548,0.00007359053,0.000158163,0.0000553137],"domain_scores_gemma":[0.9955842,0.00327599,0.0004989022,0.0003216943,0.0001409938,0.0001782076],"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":[0.0005568414,0.0008996234,0.1047552,0.001478838,0.00009612757,0.002588228,0.02339516,0.008278172,0.03551149,0.02447351,0.002042237,0.7959247],"study_design_scores_gemma":[0.0001296021,0.003776992,0.5462177,0.00160413,0.0002403658,0.01349036,0.02725892,0.03453175,0.05439901,0.2363609,0.08173849,0.000251826],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9406292,0.001722727,0.03555788,0.0001838465,0.00003117958,0.00005608541,0.00004008855,0.0001531464,0.02162582],"genre_scores_gemma":[0.9864364,0.0013212,0.008994574,0.00005010776,0.00001964937,0.00002850631,0.00005413406,0.00001590087,0.003079497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002260678,"threshold_uncertainty_score":0.006948829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03659300487498539,"score_gpt":0.3166150647465001,"score_spread":0.2800220598715147,"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."}}