{"id":"W2110615044","doi":"10.1145/2076354.2076390","title":"<i>\"Point it, split it, peel it, view it\"</i>","year":2011,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Immediacy; Visualization; Flexibility (engineering); Domain (mathematical analysis); Point (geometry); Process (computing); Reservoir engineering; Human–computer interaction; Drilling engineering; Representation (politics); Data visualization; Data science; Drilling; Artificial intelligence; Geology; Engineering; Petroleum","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":[0.0007895492,0.001804161,0.000602165,0.0006711917,0.001088846,0.0029473,0.001417703,0.002518127,0.0536672],"category_scores_gemma":[0.006237995,0.0002916858,0.0006793536,0.001116886,0.001436991,0.003631445,0.002429106,0.0013888,0.01888299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002728171,"about_ca_system_score_gemma":0.0003539462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001620915,"about_ca_topic_score_gemma":0.002475463,"domain_scores_codex":[0.9994025,0.0002309499,0.00004207551,0.00009993899,0.0001555026,0.00006904203],"domain_scores_gemma":[0.9978942,0.0009354334,0.0002058596,0.0004202267,0.0003582017,0.0001860784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001176442,0.0001972158,0.004613902,0.001755624,0.00008384793,0.001472568,0.01607768,0.001588846,0.04854987,0.03263766,0.5191245,0.3727217],"study_design_scores_gemma":[0.0001030107,0.0004223339,0.007358122,0.001019439,0.00008886778,0.002418202,0.007701632,0.01867126,0.02150318,0.01556764,0.9248476,0.0002986993],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04531409,0.001574866,0.6015206,0.01367981,0.002218162,0.001401534,0.005365626,0.04777654,0.2811488],"genre_scores_gemma":[0.2943175,0.002794351,0.5549219,0.0100405,0.001031592,0.002314202,0.00534978,0.005693878,0.1235363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0536672,"threshold_uncertainty_score":0.1795347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07709404704964605,"score_gpt":0.3110517060422177,"score_spread":0.2339576589925716,"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."}}