{"id":"W1974274010","doi":"10.1093/database/bas025","title":"HAltORF: a database of predicted out-of-frame alternative open reading frames in human","year":2012,"lang":"en","type":"article","venue":"Database","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"Canadian Institutes of Health Research","keywords":"Open reading frame; Human proteome project; Human genome; Ribosome profiling; Biology; Frame (networking); Computational biology; Transcriptome; Computer science; Genome; Translation (biology); Genetics; Gene; Gene expression; Messenger RNA; Proteomics; Peptide sequence","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":[0.0009454816,0.002142575,0.002237289,0.005771772,0.0008320775,0.001705945,0.001993261,0.002600481,0.0179499],"category_scores_gemma":[0.003406683,0.000701429,0.001177736,0.00405228,0.0003559055,0.001539085,0.001412059,0.00103374,0.01869631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000981905,"about_ca_system_score_gemma":0.001999413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002589067,"about_ca_topic_score_gemma":0.003461832,"domain_scores_codex":[0.999493,0.0000693617,0.0001105299,0.0001482829,0.0001041053,0.00007457965],"domain_scores_gemma":[0.998881,0.0004126375,0.00028567,0.0001212037,0.0001208861,0.0001786178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005594535,0.0003056144,0.01501163,0.01707177,0.000713901,0.005453691,0.0007081421,0.004352397,0.06634769,0.005765475,0.6628155,0.2158597],"study_design_scores_gemma":[0.001240025,0.000486737,0.03763765,0.001670858,0.0005781288,0.006971246,0.0003924002,0.00716207,0.02965993,0.005881461,0.9079517,0.0003678126],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02323914,0.01253066,0.01126479,0.0003440185,0.0001726809,0.0002207498,0.9304945,0.01702438,0.004709047],"genre_scores_gemma":[0.01697737,0.00275457,0.02007526,0.0002423634,0.00005245257,0.0002950642,0.9578255,0.0006614748,0.00111592],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0179499,"threshold_uncertainty_score":0.0600484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04269381016478672,"score_gpt":0.3292702306601261,"score_spread":0.2865764204953393,"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."}}