{"id":"W4403174248","doi":"10.1002/ctd2.70009","title":"Developing messenger RNA biomarkers: A workflow to characterise and identify transcript target sequences unaffected by alternative splicing for reproducible gene transcript quantification by reverse transcriptase quantitative polymerase chain reaction","year":2024,"lang":"en","type":"article","venue":"Clinical and Translational Discovery","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Reverse transcriptase; RNA splicing; Biology; Messenger RNA; Gene; Alternative splicing; Mature messenger RNA; Computational biology; RNA; Post-transcriptional modification; Genetics","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":[0.004123399,0.00243521,0.001761291,0.003024762,0.0009447248,0.002319244,0.001352562,0.001803145,0.004621753],"category_scores_gemma":[0.003906866,0.001637735,0.001954442,0.001227579,0.001502339,0.0009728742,0.00114454,0.002721192,0.006983364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008582036,"about_ca_system_score_gemma":0.001916533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000461245,"about_ca_topic_score_gemma":0.0008763908,"domain_scores_codex":[0.9964926,0.0006165118,0.0003920974,0.001219288,0.001025215,0.0002542769],"domain_scores_gemma":[0.9972945,0.001158501,0.0004461003,0.0003790143,0.000577977,0.0001439222],"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":[0.0002442354,0.0000866456,0.0006150621,0.0003464439,0.00003800269,0.0001773361,0.0001137848,0.000746702,0.9820931,0.001394141,0.001127797,0.01301671],"study_design_scores_gemma":[0.00007664179,0.000333984,0.001120799,0.0000727387,0.00005662541,0.0003819699,0.00004709145,0.01029824,0.9685532,0.002111331,0.01684648,0.0001008981],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02295604,0.0006523512,0.9605688,0.0002102798,0.0002011349,0.001486751,0.003504751,0.008938272,0.00148154],"genre_scores_gemma":[0.0314192,0.00050354,0.956853,0.000360823,0.00004268746,0.003882631,0.003415353,0.0009649777,0.002557756],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004621753,"threshold_uncertainty_score":0.0218069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05534122912123656,"score_gpt":0.375574750912204,"score_spread":0.3202335217909674,"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."}}