{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001148562,0.0007538034,0.0005663271,0.00214486,0.0006398835,0.001582319,0.001204492,0.0009211996,0.01581098],"category_scores_gemma":[0.004011657,0.0006956367,0.0006852284,0.001908825,0.0003220666,0.002760832,0.002759283,0.001096725,0.002778761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004812326,"about_ca_system_score_gemma":0.001183354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006991393,"about_ca_topic_score_gemma":0.01793697,"domain_scores_codex":[0.999602,0.00009901103,0.00004637192,0.00008184151,0.0001337257,0.00003712918],"domain_scores_gemma":[0.998569,0.0008099739,0.00007903096,0.0002121953,0.0001910316,0.00013869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001790979,0.0002852489,0.01753073,0.002745472,0.0004238703,0.002290171,0.009151844,0.01146732,0.1328822,0.09599357,0.3029612,0.4224774],"study_design_scores_gemma":[0.0003232982,0.0001641186,0.01517372,0.0005806191,0.0001632587,0.002567549,0.002317631,0.1637764,0.03881973,0.09567246,0.6801369,0.0003044123],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.0297242,0.001351034,0.7577059,0.0008786837,0.0001228669,0.0002595925,0.03027868,0.1673375,0.01234156],"genre_scores_gemma":[0.161602,0.001210851,0.7855768,0.0004690458,0.00003784423,0.0008060969,0.03009168,0.01075266,0.009453045],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01581098,"threshold_uncertainty_score":0.05289292,"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."}}