{"id":"W2024290096","doi":"10.1109/tvcg.2009.167","title":"MizBee: A Multiscale Synteny Browser","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":160,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Synteny; Computer science; Visualization; Data visualization; Comparative genomics; Similarity (geometry); Data science; Abstraction; Genomics; Human–computer interaction; Genome; Information retrieval; Data mining; Artificial intelligence; Biology","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":[0.000150354,0.0002239663,0.0002014126,0.0004092319,0.0003273152,0.0003690899,0.000383122,0.000112626,0.00001968667],"category_scores_gemma":[0.000003002226,0.0002207607,0.00009956751,0.001023623,0.00006077027,0.0005973926,0.000004812655,0.0001533649,0.00002554907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000167081,"about_ca_system_score_gemma":0.00003020314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006335051,"about_ca_topic_score_gemma":0.000008607492,"domain_scores_codex":[0.9985159,0.00009524795,0.0003311015,0.0004785522,0.0003327545,0.0002464383],"domain_scores_gemma":[0.9990963,0.00005672477,0.00008738336,0.0004211659,0.0001534915,0.0001849741],"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":[0.000009919278,0.0004936518,0.00003129095,0.00001530674,0.00003204789,0.000007302775,0.00053538,0.0005332967,0.00003859667,0.9613879,0.001554689,0.03536063],"study_design_scores_gemma":[0.0005794609,0.0002644713,0.0005092889,0.00004108926,0.00001825436,0.00002337548,0.00001420478,0.9915004,0.001041377,0.001315709,0.004404199,0.0002881436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001279937,0.00003209519,0.9972563,0.0002777436,0.0004462242,0.0001526725,0.0000117775,0.0004164893,0.0001267449],"genre_scores_gemma":[0.98549,0.0003534018,0.004904704,0.008798949,0.00007010432,0.000007930581,0.00001863239,0.00001836745,0.0003379006],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9923516,"threshold_uncertainty_score":0.9002362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01787192504938046,"score_gpt":0.2814564830515746,"score_spread":0.2635845580021941,"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."}}