{"id":"W1869957243","doi":"10.1186/1471-2105-6-183","title":"Inconsistencies over time in 5% of NetAffx probe-to-gene annotations","year":2005,"lang":"en","type":"letter","venue":"BMC Bioinformatics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Genomics","funders":"Ministry of Education, India","keywords":"DNA microarray; Microarray; Microarray databases; Annotation; Microarray analysis techniques; Computational biology; Biology; Gene; Gene Annotation; Genetics; Set (abstract data type); Genome; Bioinformatics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02796354,0.0004105829,0.0006525857,0.002361813,0.001689636,0.002087419,0.002262888,0.003177111,0.004596315],"category_scores_gemma":[0.08080688,0.0004253348,0.0006369256,0.004139596,0.001558845,0.002224942,0.001401972,0.004025639,0.003962682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003537827,"about_ca_system_score_gemma":0.001633809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002881788,"about_ca_topic_score_gemma":0.004640005,"domain_scores_codex":[0.9773078,0.006462074,0.00331764,0.00330395,0.008762326,0.0008462431],"domain_scores_gemma":[0.8921483,0.06899514,0.006803056,0.009164126,0.02189852,0.0009909259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001006247,0.0001062707,0.02887899,0.001463649,0.0001538631,0.004542571,0.003787351,0.001255692,0.01481159,0.0199544,0.402454,0.5215854],"study_design_scores_gemma":[0.00002879418,0.0001076983,0.01765021,0.000622151,0.0001086543,0.01085523,0.001007768,0.002676422,0.01356857,0.01676216,0.9365296,0.0000827429],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1233374,0.02822691,0.1341795,0.610298,0.04122038,0.0002854888,0.01064345,0.006708781,0.04510009],"genre_scores_gemma":[0.3958881,0.01153562,0.1299705,0.4058723,0.01413709,0.0006738409,0.01351656,0.003381974,0.02502397],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02796354,"threshold_uncertainty_score":0.1478871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01633046268354742,"score_gpt":0.2503158012860126,"score_spread":0.2339853386024652,"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."}}