{"id":"W2105091000","doi":"10.1093/bioinformatics/btn295","title":"Poisson adjacency distributions in genome comparison: multichromosomal, circular, signed and unsigned cases","year":2008,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Poisson distribution; Phylogenetic tree; Mathematics; Statistics; Limiting; Adjacency list; Similarity (geometry); Chromosome; Probability distribution; Genome; Adjacency matrix; Poisson regression; Biology; Combinatorics; Genetics; Computer science; Artificial intelligence; Population","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01143867,0.0003500317,0.0006502143,0.003810635,0.0006713838,0.001960898,0.002482126,0.001260578,0.002873658],"category_scores_gemma":[0.07450792,0.0004080147,0.0008975279,0.002551926,0.00237088,0.002973638,0.002003468,0.001208536,0.000549564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001099346,"about_ca_system_score_gemma":0.0005323627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001110939,"about_ca_topic_score_gemma":0.0009618317,"domain_scores_codex":[0.9959618,0.00191988,0.0002182699,0.0006114737,0.001075272,0.0002132692],"domain_scores_gemma":[0.9341108,0.0577361,0.003131461,0.002695099,0.001658137,0.0006683498],"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":[0.0003712033,0.0001518347,0.04625838,0.0002484845,0.0001133673,0.001843442,0.001749175,0.300548,0.003676651,0.5388729,0.003081681,0.1030849],"study_design_scores_gemma":[0.00002051869,0.00003710809,0.005386295,0.000044332,0.00001888249,0.001535944,0.0002904901,0.7141091,0.00178783,0.275171,0.001541655,0.00005692363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1811511,0.0006052313,0.8141348,0.0003740978,0.00003135564,0.0001298217,0.0002551732,0.0004850794,0.002833361],"genre_scores_gemma":[0.8765454,0.0004623439,0.1197246,0.0001219751,0.000109557,0.0003122548,0.0008242025,0.0001737068,0.001725954],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01143867,"threshold_uncertainty_score":0.06049418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02415182833651396,"score_gpt":0.2510118703173962,"score_spread":0.2268600419808822,"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."}}