{"id":"W2464694747","doi":"10.1007/978-3-319-43681-4_9","title":"The Gene Family-Free Median of Three","year":2016,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Genome; Breakpoint; Adjacency list; Computational biology; Gene family; Gene; Similarity (geometry); Comparative genomics; Genetics; Graph; Gene prediction; Sequence (biology); Extant taxon; Biology; Genomics; Combinatorics; Computer science; Mathematics; Artificial intelligence; Evolutionary biology","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":[0.001043109,0.0006143604,0.001196279,0.001134833,0.001051062,0.001441255,0.002059075,0.001532755,0.007224719],"category_scores_gemma":[0.003533775,0.0006119253,0.002007852,0.001474891,0.001158001,0.003517098,0.001704838,0.001689485,0.0005884593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001802295,"about_ca_system_score_gemma":0.001157717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002942992,"about_ca_topic_score_gemma":0.003271651,"domain_scores_codex":[0.9993242,0.0001579,0.00002798615,0.0002879553,0.0001215669,0.00008045707],"domain_scores_gemma":[0.99863,0.0008094496,0.0001715148,0.0001885859,0.00008960081,0.0001107736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002121833,0.0001133857,0.002127056,0.0001711099,0.00005857609,0.0001521906,0.0002023335,0.8176565,0.005229057,0.09855509,0.003242638,0.07227978],"study_design_scores_gemma":[0.00002300132,0.0000802394,0.0004381927,0.00001925303,0.00001747653,0.0001059545,0.00008531507,0.8605092,0.002551133,0.1325413,0.003604291,0.00002463543],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09138888,0.0002240342,0.9038665,0.0002975938,0.00002537804,0.00004916575,0.0006218107,0.0004965948,0.00303],"genre_scores_gemma":[0.3830327,0.0002392827,0.6107511,0.0001468001,0.00003436186,0.0001782665,0.001656195,0.0003264091,0.003634857],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007224719,"threshold_uncertainty_score":0.02416909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01332698947201799,"score_gpt":0.2427944954860763,"score_spread":0.2294675060140584,"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."}}