{"id":"W2021955412","doi":"10.1002/cfg.443","title":"Exploring the foundation of genomics: a Northern blot reference set for the comparative analysis of transcript profiling technologies","year":2004,"lang":"en","type":"article","venue":"Comparative and Functional Genomics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Profiling (computer programming); Data science; Computational biology; Genomics; Foundation (evidence); Northern blot; Gene expression profiling; Computer science; Biology; Genetics; Geography; Gene; Genome; Gene expression; Archaeology","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":[0.01362941,0.002463221,0.002612069,0.01281772,0.002893197,0.004246968,0.004156096,0.002063574,0.008511967],"category_scores_gemma":[0.01472759,0.001200248,0.001568894,0.01642342,0.001424392,0.002656945,0.002968416,0.003969974,0.0133983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002195254,"about_ca_system_score_gemma":0.005259342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00295308,"about_ca_topic_score_gemma":0.004296435,"domain_scores_codex":[0.9905919,0.002600823,0.001395386,0.001575593,0.003389055,0.0004471641],"domain_scores_gemma":[0.9859862,0.003675703,0.001501209,0.004849227,0.003523099,0.0004645735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008930106,0.0005512665,0.009128796,0.006191724,0.000387789,0.001166729,0.00141889,0.008560757,0.3508911,0.08589466,0.1080976,0.4268177],"study_design_scores_gemma":[0.00007859652,0.000414178,0.01722644,0.001610051,0.0003285193,0.001699142,0.0003354857,0.005776851,0.05294167,0.01914332,0.9002573,0.0001883862],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01545134,0.01050547,0.8582745,0.001032073,0.001153632,0.001315978,0.0749508,0.008765451,0.02855078],"genre_scores_gemma":[0.01443928,0.005551238,0.7643458,0.0004156771,0.0002057347,0.003859426,0.2040446,0.003069342,0.004068847],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01362941,"threshold_uncertainty_score":0.07208008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.24032741322932,"score_gpt":0.3207691843382519,"score_spread":0.08044177110893189,"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."}}