{"id":"W2509659139","doi":"10.1186/s12864-016-2946-1","title":"A strategy to identify housekeeping genes suitable for analysis in breast cancer diseases","year":2016,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Universidade Federal do Rio de Janeiro; Fundação Oswaldo Cruz; Alberta Cancer Foundation; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Allard Foundation; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Housekeeping gene; Biology; Gene; Housekeeping; Computational biology; Genome; Breast cancer; DNA microarray; Genetics; Bioinformatics; Gene expression; Cancer","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":[0.00007749294,0.0001025774,0.0001390757,0.00007310836,0.00004620514,0.00001740871,0.0001637353,0.0001038983,0.00001504777],"category_scores_gemma":[0.00001572287,0.00008670533,0.0001305489,0.0001705207,0.00002448156,0.000002128533,0.00008936447,0.00001820886,0.000004314458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003648167,"about_ca_system_score_gemma":0.0001246783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006980258,"about_ca_topic_score_gemma":0.001424929,"domain_scores_codex":[0.9991845,0.00002518085,0.0001661258,0.000365194,0.00003272146,0.0002262369],"domain_scores_gemma":[0.9994674,0.00001290949,0.00004893456,0.0003269581,0.00006876447,0.0000750644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004781573,0.00003584872,0.07516426,0.000008728614,0.00009115114,4.656195e-7,0.000003863431,0.0006497256,0.9175659,0.0001967553,0.0005282745,0.005707168],"study_design_scores_gemma":[0.0009832344,0.0001344797,0.3430371,0.0000219301,0.0004332052,0.000009551052,0.00005491491,0.0002326679,0.6160764,0.001310341,0.0370576,0.0006486088],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8122847,0.0005878109,0.1856513,0.0003282652,0.00001966079,0.0002791215,0.0008116617,0.00001454063,0.00002292504],"genre_scores_gemma":[0.9936308,0.0005519733,0.004494196,0.0002554753,0.000106061,0.0004683884,0.0001213948,0.00002158226,0.0003501358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3014896,"threshold_uncertainty_score":0.3535741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02200235472780732,"score_gpt":0.3249354036397241,"score_spread":0.3029330489119168,"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."}}