{"id":"W2137839234","doi":"10.1146/annurev-genom-082908-145957","title":"Applications of New Sequencing Technologies for Transcriptome Analysis","year":2009,"lang":"en","type":"review","venue":"Annual Review of Genomics and Human Genetics","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":587,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Transcriptome; Computational biology; DNA microarray; DNA sequencing; Biology; Gene expression profiling; Profiling (computer programming); Data science; Genetics; Gene; Computer science; Gene expression","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002301691,0.000291442,0.001344265,0.0001735993,0.00006652643,0.000006777987,0.0004642585,0.0003786923,0.000002981663],"category_scores_gemma":[0.00001661973,0.0002620147,0.00076408,0.0003072952,0.0001523591,0.000001258572,0.0001020366,0.0001009874,2.995231e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000175487,"about_ca_system_score_gemma":0.0002253051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000685231,"about_ca_topic_score_gemma":0.000008750248,"domain_scores_codex":[0.9984215,0.00003141428,0.0008569307,0.0004483305,0.00006720449,0.0001746219],"domain_scores_gemma":[0.9983958,0.00001331675,0.000638491,0.0007247112,0.0001754186,0.00005226296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001346439,0.00002855789,0.000001559478,0.01987905,0.0005948909,9.056311e-8,0.00001293889,7.155897e-7,0.001944753,0.002153426,0.0008331419,0.9745495],"study_design_scores_gemma":[0.00005904401,0.0002478603,0.000001216534,0.002201674,0.003575934,0.000004813895,0.00001820342,7.553602e-7,0.0008169421,0.0006063086,0.9922324,0.0002347852],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002796494,0.9728428,0.02466997,0.00002866073,0.000006145639,0.001647418,0.0006574049,0.00001336139,0.0001062574],"genre_scores_gemma":[0.00007514837,0.9870038,0.01105822,0.00007212596,0.00005448094,0.0002725219,0.001283982,0.00002886769,0.0001508473],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9913993,"threshold_uncertainty_score":0.9999832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02479816668819531,"score_gpt":0.3505783560507356,"score_spread":0.3257801893625403,"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."}}