{"id":"W2937178077","doi":"10.1007/978-3-030-10837-3_5","title":"Gene Family Evolution—An Algorithmic Framework","year":2019,"lang":"en","type":"book-chapter","venue":"Computational biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Supertree; Tree (set theory); Gene family; Gene; Computational biology; Biology; Annotation; Tree of life (biology); Family tree; Phylogenetic tree; Computer science; Genome; Genetics; Mathematics; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009099826,0.0003371342,0.0003302614,0.00007965354,0.0001025377,0.00001387457,0.0002979045,0.0007090024,0.00005097173],"category_scores_gemma":[0.00001985721,0.0003446942,0.0001644826,0.00001695185,0.0001910772,5.49207e-7,0.000224128,0.0002035523,0.0002274732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003769008,"about_ca_system_score_gemma":0.0002926405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007306471,"about_ca_topic_score_gemma":0.000003574251,"domain_scores_codex":[0.998647,0.00003326351,0.000304107,0.000674792,0.00009846398,0.0002424237],"domain_scores_gemma":[0.9990835,0.00005237209,0.0001745971,0.0003863694,0.0002241559,0.0000790071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000157347,0.0000969787,0.001247676,0.00005109926,0.00138889,0.000009070466,0.00006673245,0.01349359,0.1111038,0.8533796,0.004799708,0.01420555],"study_design_scores_gemma":[0.0005747359,0.001131594,0.006017759,0.00003288906,0.00009066595,0.00004388205,0.00001314561,0.0006284866,0.0003704572,0.609581,0.3804781,0.00103734],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1658859,0.09491421,0.3370522,0.0008611533,0.010191,0.00296267,0.005227681,0.0001080976,0.3827971],"genre_scores_gemma":[0.7972217,0.001642036,0.06673206,0.0026491,0.004897836,0.00004859031,0.008722555,0.0002419367,0.1178442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6313357,"threshold_uncertainty_score":0.9999005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01604119235414066,"score_gpt":0.2533503940419569,"score_spread":0.2373092016878162,"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."}}