{"id":"W2055257835","doi":"10.1371/journal.pone.0013409","title":"Genome-Wide Comparative Gene Family Classification","year":2010,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Gene family; Genome; Gene; Biology; Genetics; Computational biology; Gene prediction; Gene cluster; Cluster analysis; Computer science; Artificial intelligence","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":[0.001802657,0.0004858924,0.0006642469,0.002911205,0.0008006384,0.0005651488,0.0007195608,0.000500525,0.002922188],"category_scores_gemma":[0.002970509,0.0001837455,0.0008359568,0.002607191,0.0003706538,0.0004330591,0.0005211483,0.0004884225,0.0008454017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007938997,"about_ca_system_score_gemma":0.0005472776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003752532,"about_ca_topic_score_gemma":0.004535854,"domain_scores_codex":[0.9986261,0.0003027799,0.00006246632,0.0006094946,0.0002932581,0.0001059456],"domain_scores_gemma":[0.9988834,0.0003902653,0.0001542511,0.0002300631,0.0002859271,0.0000561807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00158165,0.0003213885,0.05769983,0.0007861529,0.0005796662,0.0003657666,0.0006296041,0.01496438,0.4943755,0.005462802,0.01539073,0.4078425],"study_design_scores_gemma":[0.0001687839,0.000446043,0.425585,0.00008442388,0.0003330871,0.00208353,0.0004045778,0.2808486,0.2147875,0.008337852,0.06672942,0.0001911531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6923879,0.002168995,0.2601031,0.0002459831,0.00006823166,0.0003891215,0.0286031,0.006574641,0.009458995],"genre_scores_gemma":[0.6097757,0.0005059584,0.3458895,0.0001604282,0.00002457071,0.0007831345,0.03962092,0.0006832006,0.002556646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003752532,"threshold_uncertainty_score":0.009775639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06597166402580623,"score_gpt":0.2482510512695884,"score_spread":0.1822793872437821,"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."}}