{"id":"W2069104338","doi":"10.1371/journal.pone.0010316","title":"Mining Mammalian Transcript Data for Functional Long Non-Coding RNAs","year":2010,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Biology; Gene; Genetics; Transcriptome; Conserved sequence; Coding region; Computational biology; Exon; Functional genomics; Homology (biology); Comparative genomics; Genomics; Genome; Gene expression; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003025429,0.0001350765,0.0001388424,0.00005870918,0.0001293427,0.00004586591,0.0004321527,0.0002076121,0.0001372948],"category_scores_gemma":[0.0002007883,0.0001498774,0.00006420819,0.00008120198,0.00004859073,0.000008568853,0.0001697213,0.0002277815,0.0000140937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001211366,"about_ca_system_score_gemma":0.0001305708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001242975,"about_ca_topic_score_gemma":0.0002030224,"domain_scores_codex":[0.9986637,0.0000183154,0.0001643192,0.0005107772,0.0002959789,0.0003468775],"domain_scores_gemma":[0.9988607,0.00001584699,0.00004326104,0.0008210632,0.0001363606,0.0001227644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001397496,0.0001986321,0.00004042408,0.00006656098,0.0001933362,0.000003845649,0.00001472774,0.000005795092,0.9959409,0.00006157032,0.00173149,0.001603004],"study_design_scores_gemma":[0.0008363986,0.0001822997,0.0001830581,0.00003460403,0.00008151799,0.000008342045,0.00002283492,0.001937788,0.9876651,0.00002309696,0.008837465,0.0001874627],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5440566,0.0002753599,0.4510648,0.0008658869,0.0005060001,0.0009338356,0.0003176593,0.00003706805,0.001942807],"genre_scores_gemma":[0.9778502,0.00004630519,0.01663807,0.0002163391,0.0009241695,0.000107691,0.001770532,0.00006201775,0.002384684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4344268,"threshold_uncertainty_score":0.6111825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07432095130441903,"score_gpt":0.2825243816629512,"score_spread":0.2082034303585322,"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."}}