{"id":"W2097275194","doi":"10.1074/mcp.m114.046516","title":"Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray*","year":2015,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Occupational Cancer Research Centre; McGill University and Génome Québec Innovation Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Concordia University","keywords":"Antibody; Colocalization; Receiver operating characteristic; Biomarker; Breast cancer; Mammary tumor; Chemistry; Protein microarray; Molecular biology; Microarray; Biology; Cancer; Pathology; Immunology; Medicine; Internal medicine; Biochemistry; Gene expression; Gene","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":[0.0003514893,0.000211512,0.0003907939,0.0001903157,0.0001077939,0.00002847789,0.0004144034,0.0001485566,0.00001740064],"category_scores_gemma":[0.00002589556,0.0001927118,0.0001386025,0.000839558,0.0001561926,0.0001096808,0.0001481858,0.0002126246,3.069867e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001157193,"about_ca_system_score_gemma":0.0001041746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002801167,"about_ca_topic_score_gemma":0.00002700277,"domain_scores_codex":[0.9983859,0.00008739436,0.0006184905,0.0003812459,0.0002790172,0.0002479667],"domain_scores_gemma":[0.998465,0.000005858346,0.0005886481,0.0006275394,0.0002291202,0.00008381326],"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":[0.00009649141,0.0002858426,0.002798542,0.0001267276,0.00007017987,0.00001010453,0.0002552649,0.008571246,0.987411,0.0003342649,1.826873e-7,0.00004014386],"study_design_scores_gemma":[0.0005292779,0.00004792528,0.0001091799,0.00009642602,0.0001608444,0.000009727922,0.0001609863,0.0203567,0.9779586,0.0003619238,0.00001110623,0.0001973558],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8777342,0.00005426684,0.1210133,0.00001644232,0.000007989264,0.001009442,0.00005936886,0.0000401828,0.00006485017],"genre_scores_gemma":[0.945091,0.000002541494,0.05442587,0.000005597647,0.00002944161,0.0001669685,0.0002235733,0.00004447011,0.00001049942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06735686,"threshold_uncertainty_score":0.7858561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01373707928393697,"score_gpt":0.2990741716103754,"score_spread":0.2853370923264384,"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."}}