{"id":"W2753664105","doi":"10.1145/3103010.3103013","title":"MACE","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Subtractive color; Set (abstract data type); Context (archaeology); Visualization; Readability; Clutter; Theoretical computer science; Generative grammar; Human–computer interaction; Artificial intelligence; Programming language","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":[0.00004044607,0.00001666047,0.00001906371,0.000008810384,0.0001265462,0.0003972942,0.0007597028,0.000006013449,0.0000604755],"category_scores_gemma":[0.00002537666,0.00001321523,0.000007826534,0.00001386856,0.00001037063,0.0003489559,0.0001919108,0.000009608258,0.00030676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001557569,"about_ca_system_score_gemma":0.00000675613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007872746,"about_ca_topic_score_gemma":0.000004049293,"domain_scores_codex":[0.9998161,0.00000242554,0.00002699294,0.00006306639,0.00004938916,0.00004203546],"domain_scores_gemma":[0.9994075,0.000002816565,0.00001975259,0.0005337424,0.00001312669,0.0000230759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[3.272704e-8,0.000004448893,0.0006199953,4.509757e-7,8.087496e-7,0.000001322292,0.00001122245,6.25269e-7,0.00001912333,0.9696016,0.01722245,0.01251795],"study_design_scores_gemma":[0.000175206,0.00001126089,0.01133955,0.000003627511,0.000001220905,0.000003115446,0.000006724297,0.424205,0.002184173,0.01002139,0.5519288,0.0001199606],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001073411,0.000001720796,0.8389727,0.001801478,0.00008386687,0.000006796376,2.522939e-7,0.00004755198,0.1589783],"genre_scores_gemma":[0.8931677,0.0000107591,0.05279173,0.002077485,0.0000431856,5.174891e-7,0.00000145011,0.000002239306,0.05190496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9595802,"threshold_uncertainty_score":0.3942881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04504198478706526,"score_gpt":0.352585663478483,"score_spread":0.3075436786914177,"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."}}