{"id":"W4409000114","doi":"10.21203/rs.3.rs-6247846/v1","title":"FullSynesth: Syntenic Reconciliation of a Set of Consistent Gene Trees","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Synteny; Set (abstract data type); Gene; Tree (set theory); Combinatorics; Biology; Genetics; Mathematics; Computational biology; Computer science; Genome; Programming language","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":[0.004038618,0.001305998,0.001618614,0.002947249,0.001299165,0.002423628,0.003182812,0.001717557,0.01293831],"category_scores_gemma":[0.01702789,0.001597445,0.002409643,0.00332197,0.001152316,0.003518655,0.004494928,0.002565906,0.003132309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000548227,"about_ca_system_score_gemma":0.001297201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006158973,"about_ca_topic_score_gemma":0.00152701,"domain_scores_codex":[0.997484,0.0008861691,0.0001719183,0.0006766769,0.0006064785,0.0001747686],"domain_scores_gemma":[0.9924368,0.003332755,0.0002868371,0.00323241,0.0005440005,0.0001670893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002619886,0.000359566,0.008584401,0.001502484,0.00107942,0.00115333,0.001691023,0.06928128,0.03117425,0.07768367,0.05631117,0.7485596],"study_design_scores_gemma":[0.0006957658,0.0003969024,0.004929096,0.0002798217,0.0005060076,0.001333388,0.0006407462,0.5560573,0.04159861,0.3487568,0.04466258,0.0001429307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07407662,0.0005384974,0.8893191,0.0006063631,0.0002092106,0.0002806717,0.009249933,0.02205495,0.003664757],"genre_scores_gemma":[0.2181522,0.0001833164,0.7517268,0.000197966,0.00009704049,0.0003266364,0.02208688,0.005335066,0.001894154],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01293831,"threshold_uncertainty_score":0.04328299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09989811910419988,"score_gpt":0.4004076278736275,"score_spread":0.3005095087694276,"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."}}