{"id":"W2113374668","doi":"10.1145/332040.332414","title":"Using naming time to evaluate quality predictors for model simplification","year":2000,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristics; Computer science; Quality (philosophy); Measure (data warehouse); Artificial intelligence; Machine learning; Cognition; Data mining; Natural language processing; Psychology","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":[0.000469969,0.0000647245,0.00008070729,0.00004970711,0.00009750506,0.0001280305,0.0003405313,0.00002411038,0.0002181087],"category_scores_gemma":[0.00005116689,0.00006003575,0.0000309784,0.0002322848,0.000007493472,0.0003645396,0.00004479512,0.00001711239,0.0002202557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003445435,"about_ca_system_score_gemma":0.00005190555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008455347,"about_ca_topic_score_gemma":0.000001099437,"domain_scores_codex":[0.999197,0.00003066637,0.0002080214,0.0002389331,0.0001870166,0.000138339],"domain_scores_gemma":[0.9994215,0.00003345142,0.00003547765,0.0003360211,0.00009345388,0.00008006506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001664558,0.000149241,0.0001107865,0.00003176792,0.00002947486,1.977355e-7,0.001029905,0.7318662,0.009855474,0.1292674,0.01158766,0.1160552],"study_design_scores_gemma":[0.0001083742,0.00001233483,0.00006479067,0.000004359733,0.000005059005,2.828913e-7,0.000003906662,0.9944894,0.0004182355,0.001265683,0.003539,0.00008862243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01269655,0.000001686677,0.9837745,0.0003194069,0.00001846225,0.0001643027,0.00001619418,0.0001285845,0.002880256],"genre_scores_gemma":[0.2485293,0.000003373184,0.7118269,0.003722278,0.00008199105,0.00002060754,0.00009995355,0.00002130677,0.03569438],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2719477,"threshold_uncertainty_score":0.2831015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1383067402434222,"score_gpt":0.4184403955553931,"score_spread":0.2801336553119709,"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."}}