{"id":"W2042044826","doi":"10.1109/vast.2009.5333020","title":"Capturing and supporting the analysis process","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Boeing","keywords":"Computer science; Visual analytics; Analytics; Scripting language; Process (computing); Visualization; Human–computer interaction; Cultural analytics; Timeline; Interactive visual analysis; Data visualization; Process mining; Undo; Data science; Reuse; Process modeling; Work in process; Programming language; World Wide Web; Artificial intelligence; Semantic analytics; Business process modeling; Web page","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":[0.0001526777,0.00003290493,0.00004936033,0.00005086961,0.00007593592,0.0001927818,0.000242876,0.000007832594,0.00001337545],"category_scores_gemma":[0.00002043646,0.00001932242,0.00001835443,0.0005709824,0.000008478516,0.0002051347,0.00003518638,0.00002276269,0.000003034688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001979485,"about_ca_system_score_gemma":0.000008061123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004907493,"about_ca_topic_score_gemma":0.000008308421,"domain_scores_codex":[0.9996246,0.000008643522,0.00008626455,0.0001105297,0.00008962132,0.0000803869],"domain_scores_gemma":[0.9997401,0.00001223049,0.00003377395,0.000161436,0.00002463303,0.00002784162],"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":[0.000001137343,0.00008546102,0.02431252,0.00001526595,0.0002054594,0.00001431,0.006981242,0.002180611,0.0001249769,0.7828986,0.001919841,0.1812606],"study_design_scores_gemma":[0.00005204657,0.000008832867,0.01717036,0.000001716386,0.00004460251,0.000002956853,0.0002248292,0.9769388,0.0004871565,0.004317831,0.0006725378,0.00007830342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02157569,0.00001856844,0.9698352,0.003636053,0.00001085981,0.00002634886,3.639175e-7,0.00007920639,0.004817734],"genre_scores_gemma":[0.9962732,0.000003303069,0.00182127,0.001480064,0.000008909484,2.410065e-7,0.000001661525,6.158608e-7,0.0004108045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9747582,"threshold_uncertainty_score":0.1858999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01550945355463141,"score_gpt":0.3221305469962769,"score_spread":0.3066210934416455,"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."}}