{"id":"W3130219831","doi":"10.1109/tvcg.2021.3060666","title":"The Effect of Exploration Mode and Frame of Reference in Immersive Analytics","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Global Affairs Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Computer science; Endocentric and exocentric; Human–computer interaction; Visualization; Affordance; Workload; Visual analytics; Data visualization; Analytics; Frame (networking); Data science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004339614,0.00101445,0.0004533555,0.0007936701,0.0005125373,0.001933216,0.0006735801,0.0006715104,0.002758339],"category_scores_gemma":[0.04476851,0.0006299558,0.0004022706,0.0004177118,0.0009158655,0.002465748,0.001780143,0.0003979476,0.0002629815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002922174,"about_ca_system_score_gemma":0.000326697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001331309,"about_ca_topic_score_gemma":0.001722316,"domain_scores_codex":[0.9957185,0.002571783,0.0003444762,0.0004170951,0.0006375065,0.0003105479],"domain_scores_gemma":[0.9406969,0.05218835,0.002510914,0.001861431,0.001649538,0.001092877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01470436,0.002423231,0.1526434,0.004444974,0.000545405,0.001492001,0.02811334,0.01833358,0.4361832,0.004572494,0.00164048,0.3349035],"study_design_scores_gemma":[0.001370408,0.02407731,0.7453039,0.001369954,0.001340551,0.003321223,0.0233236,0.06061378,0.1187888,0.006813337,0.01286987,0.0008073078],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9787884,0.0004973034,0.01765445,0.00008594611,0.00003281558,0.00007803609,0.00004625964,0.0001512774,0.002665606],"genre_scores_gemma":[0.9861038,0.0002082348,0.01311555,0.00002616879,0.00001694645,0.00006797185,0.00003971276,0.00006790556,0.0003536735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004339614,"threshold_uncertainty_score":0.02295035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02619661228509974,"score_gpt":0.3070430522470996,"score_spread":0.2808464399619999,"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."}}