{"id":"W2013359618","doi":"10.1002/pmic.201200526","title":"Coupling proteomics and transcriptomics in the quest of subtype‐specific proteins in breast cancer","year":2013,"lang":"en","type":"article","venue":"PROTEOMICS","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Breast cancer; Proteome; Proteomics; Biology; Transcriptome; Tissue microarray; In silico; Microarray analysis techniques; Cancer research; Cancer; Estrogen receptor; Microarray; Oncology; Computational biology; Bioinformatics; Gene expression; Medicine; Gene; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002970944,0.0002348359,0.0003003697,0.00009413069,0.0000741488,0.00005884375,0.0004269672,0.0001962644,0.00008223281],"category_scores_gemma":[0.00001442145,0.0001975297,0.00005174497,0.0002972307,0.0001694708,0.0002055428,0.00006045245,0.0005678802,0.000003556745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001367719,"about_ca_system_score_gemma":0.0000820188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001147945,"about_ca_topic_score_gemma":0.0001724739,"domain_scores_codex":[0.9985379,0.00001672082,0.0005503771,0.0003857707,0.0001612209,0.0003480129],"domain_scores_gemma":[0.9991345,0.0000445612,0.0002191533,0.0004556593,0.00009197857,0.00005412931],"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":[0.00007805997,0.0002085077,0.03159378,0.0002591767,0.000008215421,0.00000186473,0.0007998805,0.0004310325,0.9590808,0.005931477,0.00003161933,0.00157562],"study_design_scores_gemma":[0.00225789,0.00005337157,0.01787982,0.0007266313,0.00002131127,0.00007018744,0.001090775,0.022046,0.9200111,0.03387227,0.0009960226,0.0009746157],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872769,0.0003037089,0.007331969,0.001641885,0.00001387073,0.002844554,0.00009745514,0.00005284421,0.0004367795],"genre_scores_gemma":[0.925948,0.00130119,0.06680921,0.00006361494,0.00006812685,0.005717751,0.00001336444,0.00004555725,0.00003319687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06132894,"threshold_uncertainty_score":0.805503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01285272245368969,"score_gpt":0.2519283513900035,"score_spread":0.2390756289363138,"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."}}