{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018135,0.00008467845,0.0001441107,0.00013987,0.0001098432,0.00005824941,0.000116933,0.00005942038,6.277263e-7],"category_scores_gemma":[0.000007315909,0.00006791836,0.0000309434,0.00075448,0.00008510866,0.0002399549,0.000005481499,0.00009222484,2.40307e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008554363,"about_ca_system_score_gemma":0.00003328697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000346033,"about_ca_topic_score_gemma":0.00007723154,"domain_scores_codex":[0.9991909,0.0001399876,0.0002456289,0.0001807739,0.0001567252,0.00008597317],"domain_scores_gemma":[0.9992077,0.0002828908,0.00009419167,0.0002383599,0.000133819,0.00004308771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003571794,0.0001451477,0.0002786227,0.00008034003,0.00004618434,0.000001019784,0.001903056,0.004821691,0.0008366912,0.9583947,0.00002125977,0.03343558],"study_design_scores_gemma":[0.0003670328,0.0003713084,0.001008658,0.00004704416,0.00001409939,0.000003510781,0.00006994989,0.9629534,0.03290452,0.00209909,0.00008432706,0.00007706688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06840184,0.00006046512,0.9312385,0.00009966701,0.00005580365,0.0001070967,0.00000620587,0.000009902487,0.00002052616],"genre_scores_gemma":[0.9983491,0.001181893,0.0003694111,0.00007199964,0.000004051201,0.000009351942,0.000003587133,0.00000374918,0.000006883414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9581317,"threshold_uncertainty_score":0.2769631,"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."}}