{"id":"W1898493273","doi":"10.1109/vl.1997.626556","title":"Making distortions comprehensible","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Comprehension; Focus (optics); Perception; Perspective (graphical); Confusion; Phenomenon; Human–computer interaction; Representation (politics); Space (punctuation); Distortion (music); Visualization; Cognitive science; Artificial intelligence; Psychology","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":[0.001999532,0.001071167,0.0004597672,0.0009066007,0.0005174958,0.004524478,0.001160168,0.001198691,0.01188632],"category_scores_gemma":[0.02927338,0.0004231026,0.0006239331,0.0006112037,0.002309222,0.0114281,0.003149316,0.001831785,0.002421377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006789468,"about_ca_system_score_gemma":0.0005924471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00121254,"about_ca_topic_score_gemma":0.0009433267,"domain_scores_codex":[0.9979107,0.0008167697,0.0001206259,0.0003876793,0.0005886142,0.0001756663],"domain_scores_gemma":[0.9860475,0.007851722,0.001124,0.002889771,0.001809756,0.0002773065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008428617,0.0001025544,0.005409236,0.001860149,0.0001146758,0.002650565,0.04551468,0.00910819,0.1024191,0.2793658,0.02755496,0.5250573],"study_design_scores_gemma":[0.0001410159,0.0005915364,0.006608547,0.0009269556,0.0002160668,0.00379316,0.02358132,0.02999059,0.07154413,0.3546925,0.50761,0.0003041483],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1903682,0.003808969,0.6725085,0.00864209,0.001351429,0.0002910887,0.0007420679,0.004129356,0.1181583],"genre_scores_gemma":[0.8221187,0.00312746,0.149454,0.00175409,0.0004826567,0.0002180396,0.0008575827,0.001597732,0.02038979],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01188632,"threshold_uncertainty_score":0.03976375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1188613196934996,"score_gpt":0.3327301123636501,"score_spread":0.2138687926701504,"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."}}