{"id":"W2115261945","doi":"10.1109/cbms.2009.5255446","title":"Identifier and database from the same sequence repository provide the greatest number of correct pairings between RNA and protein data","year":2009,"lang":"en","type":"article","venue":"","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Identifier; Computer science; Gene; Database; Unique identifier; Computational biology; Matching (statistics); Protein sequencing; Data mining; Information retrieval; Bioinformatics; Biology; Genetics; Peptide sequence; Medicine; Computer network","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":[0.009571348,0.001106919,0.002134195,0.005312986,0.001055543,0.002748491,0.001127197,0.00141014,0.004180018],"category_scores_gemma":[0.03173837,0.0006831875,0.001090292,0.00821586,0.00060368,0.005359631,0.002583018,0.001555551,0.006140702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005963208,"about_ca_system_score_gemma":0.001492776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005954144,"about_ca_topic_score_gemma":0.001045054,"domain_scores_codex":[0.9889966,0.002749038,0.00233647,0.002427045,0.002873382,0.0006173687],"domain_scores_gemma":[0.9772757,0.007907738,0.002773304,0.008109104,0.003473078,0.0004611199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003891365,0.001026552,0.1968643,0.004711193,0.0009968005,0.002684403,0.001997675,0.008686971,0.1831511,0.01266311,0.02777802,0.5555486],"study_design_scores_gemma":[0.0005366281,0.001390921,0.1786798,0.001489971,0.001753213,0.01102937,0.002817222,0.0536174,0.3225608,0.02972346,0.3959668,0.0004344994],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6204745,0.005396629,0.252194,0.001753844,0.0005604929,0.0007816742,0.09128965,0.01075429,0.01679498],"genre_scores_gemma":[0.4082786,0.001946043,0.3826445,0.000632965,0.0001213326,0.000638889,0.2003532,0.00204198,0.003342591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009571348,"threshold_uncertainty_score":0.05061871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02519649545061065,"score_gpt":0.2629145560667474,"score_spread":0.2377180606161368,"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."}}