{"id":"W1519555383","doi":"10.1007/978-3-642-16181-0_3","title":"Advances on Genome Duplication Distances","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Genome; Gene duplication; Tree (set theory); Phylogenetic tree; Computer science; Gene rearrangement; Node (physics); Combinatorics; Computational biology; Biology; Gene; Mathematics; Genetics; 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":[0.001433542,0.0008721427,0.001312159,0.002660203,0.0006031699,0.001603297,0.002000201,0.001092555,0.007755845],"category_scores_gemma":[0.007802241,0.0005484222,0.0006482398,0.004086678,0.001308095,0.005347332,0.002730767,0.002758681,0.002775776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002005105,"about_ca_system_score_gemma":0.0007556832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001098269,"about_ca_topic_score_gemma":0.0009963613,"domain_scores_codex":[0.9987312,0.0002753154,0.00005604051,0.0004214136,0.0004523506,0.0000636379],"domain_scores_gemma":[0.9973148,0.001624715,0.0001697025,0.000346935,0.0004399427,0.0001040292],"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":[0.00009517225,0.00003099152,0.001044038,0.0007527521,0.00006153602,0.00005809718,0.0001108317,0.02043381,0.004433838,0.5831951,0.01123747,0.3785463],"study_design_scores_gemma":[0.00002633289,0.00007039705,0.001689206,0.0002443361,0.00006496082,0.0004309097,0.0001177339,0.08267736,0.006030108,0.7241226,0.1844654,0.00006061398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03791762,0.1769367,0.6645897,0.007346009,0.003858586,0.00007215716,0.001179334,0.0009402964,0.1071596],"genre_scores_gemma":[0.4291802,0.1319802,0.3830453,0.001970218,0.006248927,0.000204019,0.002968396,0.0009228339,0.04347989],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007755845,"threshold_uncertainty_score":0.0259459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007667278432481175,"score_gpt":0.236859674641153,"score_spread":0.2291923962086719,"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."}}