{"id":"W2003454829","doi":"10.1109/ccece.2013.6567826","title":"Multilevel label placement for execution trace events","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"TRACE (psycholinguistics); Computer science; Visualization; Graph; Data mining; Quality (philosophy); Theoretical computer science; Data visualization; Information retrieval; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008848767,0.00005474102,0.00005140924,0.00003449898,0.00005554076,0.00008074298,0.0002800658,0.00002063785,0.0001283169],"category_scores_gemma":[0.00002402723,0.00004560828,0.00001951876,0.00008029379,0.00000520718,0.0004447387,0.00006660334,0.0000166892,0.0002586855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001764397,"about_ca_system_score_gemma":0.00001615649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001603612,"about_ca_topic_score_gemma":0.000002526457,"domain_scores_codex":[0.9994746,0.00001010522,0.0001180578,0.0001549871,0.0001179256,0.0001242931],"domain_scores_gemma":[0.999613,0.0000257654,0.00003374735,0.0001922369,0.00008240093,0.00005286899],"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":[0.000003723459,0.0005620161,0.0003274935,0.00003840101,0.00003227016,3.66678e-7,0.0004824144,0.0002264198,0.002374106,0.570338,0.2960345,0.1295803],"study_design_scores_gemma":[0.0005199446,0.00003629166,0.0005448071,0.000005133033,0.000002203266,4.758569e-7,0.00003098762,0.9737712,0.001320298,0.001776975,0.02190669,0.00008505728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001220723,0.000005740798,0.9965544,0.0007945073,0.0001221945,0.0002395955,0.00000537798,0.00008237291,0.0009750286],"genre_scores_gemma":[0.434201,0.00001840951,0.5015458,0.003366264,0.00008169829,0.0001677575,0.00008267241,0.00001485802,0.0605215],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9735447,"threshold_uncertainty_score":0.3324966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04828618361476973,"score_gpt":0.3278611412640152,"score_spread":0.2795749576492454,"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."}}