{"id":"W2775729303","doi":"","title":"Toward graph layout of large data visualization: algorithms, evaluations and application","year":2016,"lang":"en","type":"dissertation","venue":"e-scholar@UOIT (University of Ontario Institute of Technology)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Ontario Institute of Technology","keywords":"Graph Layout; Computer science; Graph drawing; Visualization; Graph; Data mining; Algorithm; Theoretical computer science; Information retrieval","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003009703,0.002163996,0.001047149,0.00360687,0.0009643505,0.003570263,0.002591455,0.002108906,0.008986588],"category_scores_gemma":[0.01490305,0.0009362538,0.001047192,0.004322227,0.0009835646,0.003196438,0.002031653,0.001869095,0.00216493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001759843,"about_ca_system_score_gemma":0.002221367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01129383,"about_ca_topic_score_gemma":0.01657261,"domain_scores_codex":[0.9981771,0.0007529351,0.00008622953,0.0003425265,0.0005586269,0.00008257746],"domain_scores_gemma":[0.9917818,0.004979891,0.0004415144,0.001025944,0.001441934,0.0003288644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001816691,0.0003436077,0.002871282,0.001234111,0.0001344852,0.0001393716,0.0005270424,0.4037349,0.008956082,0.02726598,0.02010612,0.5345054],"study_design_scores_gemma":[0.0000347701,0.00005441603,0.0003593406,0.00006874705,0.00001555947,0.00007990282,0.0001783733,0.9703549,0.004563187,0.01781284,0.006458721,0.00001933033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01232034,0.000775834,0.9767512,0.0005063972,0.00005431194,0.000246387,0.0003956019,0.006364551,0.002585323],"genre_scores_gemma":[0.04382255,0.0007409165,0.952205,0.00006557334,0.00002570109,0.0001409059,0.0009191347,0.0008590255,0.001221172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01129383,"threshold_uncertainty_score":0.03006315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03108420748563381,"score_gpt":0.3048812913136126,"score_spread":0.2737970838279788,"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."}}