{"id":"W7119075833","doi":"10.1109/hfia68651.2025.00007","title":"Evaluating an Immersive Analytics Application at an Enterprise Business Intelligence Customer Conference","year":2025,"lang":"","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Usability; Novelty; Formative assessment; Perspective (graphical); Context (archaeology); Analytics; Business intelligence; Pluralistic walkthrough","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001174413,0.0004953732,0.0004895063,0.0005755957,0.0006456798,0.001168224,0.002644951,0.0002161442,0.0007746255],"category_scores_gemma":[0.0002622587,0.0005114452,0.0001025947,0.004015762,0.0003224378,0.002380925,0.001391665,0.0002505554,0.0005642421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003352114,"about_ca_system_score_gemma":0.0008502426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002771237,"about_ca_topic_score_gemma":0.0003056752,"domain_scores_codex":[0.995418,0.0003972997,0.001122116,0.001602886,0.0008303453,0.0006293607],"domain_scores_gemma":[0.9941662,0.0001392561,0.000515304,0.002196711,0.002574892,0.000407649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000887335,0.001460748,0.003725343,0.0002584819,0.000171228,0.000009937564,0.003999055,0.02772279,0.006218556,0.4637184,0.001025531,0.4916012],"study_design_scores_gemma":[0.0002739111,0.0001453557,0.001114163,0.0001422164,0.0001623648,0.000004779202,0.001112456,0.9880104,0.004509671,0.001565317,0.002415326,0.0005440277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005589066,0.0000839752,0.98571,0.0007986064,0.0006038371,0.000542838,0.00003646945,0.0001143414,0.006520906],"genre_scores_gemma":[0.9720805,0.0003790951,0.0162546,0.002356192,0.0000943893,0.00002511903,0.0003259155,0.00002361735,0.008460534],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9694554,"threshold_uncertainty_score":0.9998686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08709432832887225,"score_gpt":0.4167100476550523,"score_spread":0.3296157193261801,"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."}}