{"id":"W1605701032","doi":"10.1186/1471-2105-6-274","title":"A stepwise framework for the normalization of array CGH data","year":2005,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Centre for Applied Research in Cancer Control; University of British Columbia","funders":"National Institute of Dental and Craniofacial Research; Genome British Columbia; Genome Canada","keywords":"Normalization (sociology); DNA microarray; Comparative genomic hybridization; Biology; Copy-number variation; Computational biology; Microarray; Genetics; Computer science; Pattern recognition (psychology); Chromosome; Gene; Artificial intelligence; Gene expression; Genome","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002266429,0.00008942389,0.0000877229,0.00001966171,0.0001003294,0.00002723199,0.0004250017,0.00009567824,0.00002059608],"category_scores_gemma":[0.0001552707,0.00006422668,0.00005136427,0.00005938157,0.00005000254,0.0000175925,0.0001225584,0.00003828374,0.000008101227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006517719,"about_ca_system_score_gemma":0.00008888431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005092832,"about_ca_topic_score_gemma":0.00004108776,"domain_scores_codex":[0.9993459,0.00001136193,0.0003257892,0.00008852452,0.00008992305,0.0001385153],"domain_scores_gemma":[0.9989559,0.00005607122,0.0001752435,0.0006986608,0.00008729567,0.00002680454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001910941,0.001746055,0.05827277,0.005864872,0.002434619,4.971429e-7,0.02604523,0.1757591,0.04293939,0.3841998,0.1301258,0.170701],"study_design_scores_gemma":[0.0015893,0.0004021591,0.0027892,0.00007893683,0.0002344579,0.00002695249,0.005061631,0.3228342,0.06901006,0.001351651,0.5960175,0.0006039477],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009334175,0.0003336578,0.9887664,0.0001683605,0.0001143714,0.0002937859,0.0003263631,0.000008058353,0.0006548031],"genre_scores_gemma":[0.3933877,0.000178029,0.6043894,0.0003336239,0.0004254313,0.00002989101,0.0008839288,0.00001435416,0.0003575816],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4658917,"threshold_uncertainty_score":0.2619088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03866257181589215,"score_gpt":0.2817151930408506,"score_spread":0.2430526212249584,"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."}}