{"id":"W2134366530","doi":"10.1093/toxsci/kfv195","title":"Mining the Archives: A Cross-Platform Analysis of Gene Expression Profiles in Archival Formalin-Fixed Paraffin-Embedded Tissues","year":2015,"lang":"en","type":"review","venue":"Toxicological Sciences","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Health Canada","funders":"National Institute of Environmental Health Sciences; Health Canada; National Institutes of Health; Government of Canada; Vallee Foundation; WorldQuant Foundation; Weill Cornell Medical College; U.S. Environmental Protection Agency; Australian Government; Office of Research and Development","keywords":"Transcriptome; Biology; Gene; Gene expression; genomic DNA; Molecular biology; RNA; Computational biology; RNA extraction; DNA microarray; Nucleic acid; Genetics","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":[0.002419507,0.0007432926,0.0007906228,0.004185414,0.0007442778,0.001636193,0.0006454905,0.0005634801,0.001399634],"category_scores_gemma":[0.002246721,0.0003518246,0.0008084729,0.003362439,0.0004268192,0.000761241,0.001280035,0.0006740626,0.001494209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003670753,"about_ca_system_score_gemma":0.0009813892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001071244,"about_ca_topic_score_gemma":0.00266129,"domain_scores_codex":[0.9985667,0.000148746,0.0001357171,0.0005533457,0.0004492253,0.0001463086],"domain_scores_gemma":[0.9984651,0.0002548257,0.0003762449,0.0002985961,0.0004969969,0.0001082811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"systematic_review","study_design_scores_codex":[0.001129262,0.0002791376,0.0820929,0.001435654,0.0005703376,0.0006992239,0.001268803,0.001173543,0.7189459,0.0006254699,0.005423623,0.1863561],"study_design_scores_gemma":[0.00007168564,0.00100442,0.6601996,0.0002941638,0.001123077,0.003029083,0.002810189,0.01587266,0.2539307,0.003252178,0.05823714,0.0001751906],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.8191412,0.007558067,0.118821,0.0004879525,0.0003170012,0.00118069,0.04024887,0.005456963,0.006788147],"genre_scores_gemma":[0.5628548,0.005764399,0.3438911,0.0004821707,0.0002680731,0.002116689,0.07616325,0.001448017,0.007011624],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004185414,"threshold_uncertainty_score":0.01279569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0984573980529723,"score_gpt":0.4206839649398659,"score_spread":0.3222265668868936,"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."}}