{"id":"W2106669190","doi":"10.1109/tvcg.2006.177","title":"Smashing Peacocks Further: Drawing Quasi-Trees from Biconnected Components","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Computer science; Biconnected graph; Tree (set theory); Graph; Theoretical computer science; Node (physics); Block graph; Combinatorics; Mathematics; Line graph; Pathwidth","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005605358,0.0008760581,0.0005618655,0.001313192,0.0008111421,0.001935227,0.001069016,0.001182051,0.01153324],"category_scores_gemma":[0.003485981,0.0007986123,0.0008673936,0.001570425,0.0009436097,0.003545538,0.001317185,0.001561856,0.00234095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006211894,"about_ca_system_score_gemma":0.0006882797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005602192,"about_ca_topic_score_gemma":0.009793032,"domain_scores_codex":[0.9995797,0.00009482937,0.00002051023,0.0001148959,0.0001509974,0.00003907122],"domain_scores_gemma":[0.9989349,0.0003711224,0.00005335624,0.0003350443,0.0002281033,0.00007740119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002408693,0.00007762338,0.001643032,0.0003934454,0.0001086652,0.000758754,0.002203322,0.1123038,0.07628251,0.138533,0.02718255,0.6402724],"study_design_scores_gemma":[0.00005631988,0.0001371166,0.001256096,0.0001324147,0.00005452134,0.0009879995,0.0003907303,0.6556535,0.03283256,0.1775798,0.1307993,0.0001197066],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01765845,0.0003221712,0.9699061,0.000575494,0.0001295876,0.00005906533,0.0001292581,0.003503516,0.007716362],"genre_scores_gemma":[0.1625717,0.0007179155,0.8222616,0.000438841,0.0000610383,0.00007744198,0.0003674739,0.002021985,0.01148204],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01153324,"threshold_uncertainty_score":0.0385825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01948905818129087,"score_gpt":0.261039845021401,"score_spread":0.2415507868401102,"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."}}