{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001993829,0.001247581,0.0007302938,0.00176862,0.0005371433,0.003020978,0.00193852,0.001477999,0.1709632],"category_scores_gemma":[0.01073912,0.0005766395,0.00110723,0.0007318601,0.0004849843,0.00391448,0.003789545,0.001363088,0.03227413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004767117,"about_ca_system_score_gemma":0.000522487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007687232,"about_ca_topic_score_gemma":0.001711538,"domain_scores_codex":[0.9990543,0.0002919765,0.00007990687,0.0001600105,0.0003563462,0.00005754993],"domain_scores_gemma":[0.9950275,0.002792415,0.0001587446,0.001162998,0.0006358758,0.0002224951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001666805,0.0003391542,0.001942225,0.001751762,0.0001706892,0.0005890951,0.001895161,0.003728004,0.0202499,0.06527064,0.4070899,0.4953067],"study_design_scores_gemma":[0.0002561756,0.0001740911,0.001476871,0.0003103508,0.0000532373,0.0006397258,0.0001857328,0.02726127,0.01024765,0.03163501,0.9276494,0.0001105537],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.008011584,0.0008003188,0.7216845,0.001080218,0.0005916838,0.0006388156,0.0103263,0.187584,0.06928256],"genre_scores_gemma":[0.1026185,0.0008547762,0.7487913,0.00201367,0.0002888144,0.002382695,0.01440849,0.02740039,0.1012414],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8290368,"threshold_uncertainty_score":0,"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."}}