{"id":"W2971881853","doi":"10.1186/s13058-019-1189-x","title":"Targeting myeloid-derived suppressor cells in combination with primary mammary tumor resection reduces metastatic growth in the lungs","year":2019,"lang":"en","type":"article","venue":"Breast Cancer Research","topic":"Immune cells in cancer","field":"Immunology and Microbiology","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Centre for Applied Research in Cancer Control; Occupational Cancer Research Centre; University of British Columbia","funders":"University of British Columbia; Canadian Institutes of Health Research; Terry Fox Foundation; Michael Smith Health Research BC","keywords":"Myeloid-derived Suppressor Cell; Spleen; Bone marrow; Medicine; Cancer research; Immune system; Pathology; Myeloid; Primary tumor; Mammary tumor; Haematopoiesis; Metastasis; Immunology; Suppressor; Cancer; Biology; Breast cancer; Stem cell; Internal medicine","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":[0.002640212,0.0001982057,0.0003119019,0.0004732345,0.0001755822,0.00006672095,0.0007085962,0.0001115657,0.0005099176],"category_scores_gemma":[0.00005171836,0.0001414813,0.00004043554,0.0009770998,0.0003088516,0.0003758969,0.0002002617,0.001269149,0.0001641246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005545712,"about_ca_system_score_gemma":0.0004878513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004009903,"about_ca_topic_score_gemma":0.0002371952,"domain_scores_codex":[0.996327,0.00173288,0.0003603455,0.0005191241,0.0002859524,0.0007747318],"domain_scores_gemma":[0.9986572,0.0005454453,0.0001165023,0.0003708157,0.0002914763,0.00001855904],"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":[0.001961844,0.0002800747,0.00618967,0.0002438202,0.00006837481,0.00003634131,0.002076325,0.00008814568,0.984324,0.0002058825,0.003011417,0.001514047],"study_design_scores_gemma":[0.007970944,0.0005912072,0.2043388,0.0005799518,0.00002383207,0.0002616294,0.004151426,0.00008730265,0.7781548,0.0004978851,0.002828344,0.0005138948],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911979,0.002374969,0.00001591349,0.002543722,0.0005156164,0.001561636,0.00003875526,0.0000286701,0.001722814],"genre_scores_gemma":[0.9974228,0.000306828,0.00007764473,0.0001727574,0.00003377316,0.0006213757,0.00008025525,0.00003443183,0.001250133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2061693,"threshold_uncertainty_score":0.6061801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01816707238717546,"score_gpt":0.2903287783800996,"score_spread":0.2721617059929242,"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."}}