{"id":"W2951946877","doi":"10.1371/journal.pone.0128026","title":"UniqTag: Content-Derived Unique and Stable Identifiers for Gene Annotation","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia; BC Cancer Agency","funders":"","keywords":"Ensembl; Identifier; Unique identifier; Computer science; Annotation; Gene Annotation; Genome; Genome project; Gene nomenclature; Sequence (biology); Computational biology; Reference genome; Gene; Genetics; Genomics; Biology; Programming language; Artificial intelligence","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":[0.008491018,0.002624649,0.002711501,0.005686702,0.003258204,0.005137815,0.005146648,0.002205133,0.04051528],"category_scores_gemma":[0.03790667,0.002962265,0.002514942,0.007328333,0.00139901,0.00548217,0.006528725,0.005001133,0.05587836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001764334,"about_ca_system_score_gemma":0.003494878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003583032,"about_ca_topic_score_gemma":0.005082117,"domain_scores_codex":[0.9931834,0.001542938,0.0008272215,0.002299424,0.001688481,0.0004584879],"domain_scores_gemma":[0.9868574,0.004431073,0.002023461,0.004082345,0.001976516,0.0006292303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002098976,0.0001389136,0.01053892,0.003486575,0.0005606737,0.0005605943,0.00174765,0.004152352,0.05108212,0.02056956,0.7618636,0.1432001],"study_design_scores_gemma":[0.000541453,0.0003202427,0.01103183,0.00082516,0.0003709305,0.001637187,0.0004048761,0.03539979,0.07297087,0.05149528,0.8244061,0.0005961427],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009279657,0.001227008,0.5348196,0.0005581079,0.001583099,0.0003902772,0.1228995,0.3221185,0.007124296],"genre_scores_gemma":[0.02834212,0.000573976,0.6119919,0.0006675908,0.0003571996,0.001470772,0.2159601,0.1334097,0.007226701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04051528,"threshold_uncertainty_score":0.1355371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1119345139140407,"score_gpt":0.244137362106936,"score_spread":0.1322028481928953,"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."}}