{"id":"W4408281356","doi":"10.1109/tvcg.2025.3549578","title":"Evaluating 3D Visual Comparison Techniques for Change Detection in Virtual Reality","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Virtual reality; Computer science; Visualization; Change detection; Computer graphics (images); Data visualization; Augmented reality; Human–computer interaction; Computer vision; 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":[0.003564973,0.001219174,0.0007375941,0.003172305,0.0003536299,0.002261363,0.001401846,0.00120152,0.002841684],"category_scores_gemma":[0.0254983,0.0004970111,0.001051896,0.001260836,0.0006895534,0.002121096,0.002036626,0.0006968065,0.0005307017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005187058,"about_ca_system_score_gemma":0.0004138259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001222421,"about_ca_topic_score_gemma":0.001260901,"domain_scores_codex":[0.9960918,0.0015905,0.0002524089,0.0005781993,0.001273396,0.000213648],"domain_scores_gemma":[0.9830636,0.01146441,0.001718424,0.001477611,0.001846741,0.000429208],"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":[0.004992193,0.001086408,0.01065871,0.003116779,0.0006069926,0.0002883064,0.002318101,0.04329753,0.1643202,0.003345337,0.002438182,0.7635313],"study_design_scores_gemma":[0.0009443855,0.01374131,0.09425451,0.000625195,0.0009956034,0.003901378,0.003616385,0.6586788,0.199138,0.007773999,0.01555868,0.0007718523],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4473667,0.00244983,0.5408804,0.000214158,0.0002559065,0.0008963255,0.0006528852,0.003141414,0.004142374],"genre_scores_gemma":[0.599623,0.0008281407,0.3975598,0.00008452377,0.00005489251,0.0003185598,0.0005078633,0.0003524606,0.000670849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003564973,"threshold_uncertainty_score":0.0188536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07416754435340438,"score_gpt":0.4213460985933723,"score_spread":0.3471785542399679,"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."}}