{"id":"W1986902347","doi":"10.1002/prot.22723","title":"The evolutionary landscape of the chromatin modification machinery reveals lineage specific gains, expansions, and losses","year":2010,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Lineage (genetic); Biology; Modularity (biology); Context (archaeology); Evolutionary biology; Function (biology); Set (abstract data type); Computational biology; Repertoire; Chromatin; Gene; Genetics; Computer science","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":[0.0002678674,0.0001307512,0.0001689202,0.0008506022,0.0002660501,0.0005580968,0.0001701464,0.0002876156,0.0007136515],"category_scores_gemma":[0.0004433562,0.0001567102,0.0001196221,0.0006613507,0.0003632694,0.000491919,0.0003751268,0.0003802264,0.0002270408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002984164,"about_ca_system_score_gemma":0.0001437245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006073542,"about_ca_topic_score_gemma":0.001167427,"domain_scores_codex":[0.9998732,0.00001749327,0.000006010197,0.00005913744,0.00002549135,0.00001877585],"domain_scores_gemma":[0.9997256,0.00007360899,0.0001090639,0.00003623384,0.00002785536,0.00002751126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003098074,0.00002882853,0.08485997,0.00008433827,0.00006196124,0.000233697,0.0004178119,0.001739239,0.8712558,0.002680085,0.0001819337,0.03814638],"study_design_scores_gemma":[0.00001141783,0.0002749887,0.8707458,0.00003327133,0.0001030459,0.001566155,0.0005511685,0.01462462,0.0980748,0.005251546,0.008724226,0.00003886535],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946312,0.0008447537,0.002812898,0.00007766936,0.000001642395,0.000003903783,0.0001648251,0.00004691279,0.001416222],"genre_scores_gemma":[0.9961189,0.0006161436,0.002324605,0.00004992984,0.000003324673,0.000005061265,0.0002744626,0.00001652943,0.0005910608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008506022,"threshold_uncertainty_score":0.002387404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005624776859677908,"score_gpt":0.2051930675175853,"score_spread":0.1995682906579074,"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."}}