{"id":"W2034369306","doi":"10.1089/cmb.2011.0136","title":"Genome Halving and Double Distance with Losses","year":2011,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Genome; Gene duplication; Tree (set theory); Phylogenetic tree; Gene; Gene rearrangement; Biology; Combinatorics; Genome evolution; Node (physics); Segmental duplication; Genetics; Mathematics; Computational biology; Computer science; Gene family; Physics","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":[0.001036419,0.0007129459,0.001133373,0.0008815167,0.0006791005,0.001329512,0.002217951,0.001174506,0.003458322],"category_scores_gemma":[0.005160284,0.000457775,0.0008390813,0.001066621,0.001204115,0.002225482,0.002378397,0.001618497,0.0006454345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009040944,"about_ca_system_score_gemma":0.001258111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002119841,"about_ca_topic_score_gemma":0.002422266,"domain_scores_codex":[0.9990271,0.0001997672,0.00004725933,0.000326501,0.0002590757,0.0001403285],"domain_scores_gemma":[0.9974431,0.001418336,0.0002154857,0.0004767496,0.0002855873,0.000160717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008637295,0.0001665015,0.004483434,0.0003210435,0.00009618646,0.0004001786,0.0004166141,0.5755779,0.01243588,0.08321264,0.00555858,0.3164674],"study_design_scores_gemma":[0.00007095562,0.000129065,0.0005511666,0.00001672117,0.00001938302,0.000281094,0.0001229851,0.908035,0.009017623,0.07853736,0.003193202,0.00002535121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1180107,0.0004364701,0.8769071,0.0004861445,0.00005416008,0.00007728218,0.0002233521,0.00133906,0.002465741],"genre_scores_gemma":[0.4081466,0.0001632451,0.5866646,0.0001429414,0.0000370541,0.0001249816,0.0007879552,0.0003377022,0.003594957],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003458322,"threshold_uncertainty_score":0.01156926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01705976222796272,"score_gpt":0.2412856655203985,"score_spread":0.2242259032924357,"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."}}