{"id":"W2139903183","doi":"10.1007/978-94-011-4309-7_23","title":"Genome Scrambling Versus Functional Clustering","year":2000,"lang":"en","type":"book-chapter","venue":"Computational biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Genome; Scrambling; Biology; Phylogenetic tree; Computational biology; Surprise; Evolutionary biology; Comparative genomics; Genetics; Genomics; Gene; Computer science; Algorithm","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000655171,0.0002832229,0.0002417708,0.00008114551,0.0001352122,0.00001517714,0.0001584598,0.0003642142,0.00034106],"category_scores_gemma":[0.00001123405,0.0003019625,0.0001594889,0.00001387598,0.0001559546,3.961642e-7,0.0001867225,0.0001397977,0.0001523884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002982291,"about_ca_system_score_gemma":0.0001246516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002106621,"about_ca_topic_score_gemma":0.00001152614,"domain_scores_codex":[0.9989006,0.00001560779,0.0002721272,0.0005147383,0.00008496294,0.0002119802],"domain_scores_gemma":[0.9994747,0.00004693426,0.0001150415,0.0001889143,0.0001124964,0.00006188623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005813006,0.0001990051,0.0005493876,0.0001777095,0.007683945,0.00005009372,0.0002343328,0.4195455,0.2281406,0.217438,0.007564136,0.1126043],"study_design_scores_gemma":[0.001295781,0.0005803379,0.001878055,0.00001544771,0.00007303629,0.00003570517,0.000004274646,0.0004171825,0.00007100789,0.06670608,0.9282349,0.0006882133],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03874478,0.02657683,0.0171906,0.0004203517,0.004024337,0.0007107186,0.0009754155,0.0000436612,0.9113133],"genre_scores_gemma":[0.849154,0.003105659,0.006921796,0.001099991,0.005676542,0.00005009542,0.01178388,0.0002081258,0.1219999],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9206707,"threshold_uncertainty_score":0.9999433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03732079960184233,"score_gpt":0.2540957836611473,"score_spread":0.216774984059305,"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."}}