{"id":"W1832475695","doi":"10.1186/bcr1193","title":"Magnetic resonance spectroscopy of breast cancer tissue used for tumor classification and lymph node prediction","year":2005,"lang":"en","type":"article","venue":"Breast Cancer Research","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kingston Health Sciences Centre","funders":"Regione Marche; Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Associazione Italiana per la Ricerca sul Cancro; National Cancer Institute; KWF Kankerbestrijding; Fondation de France; Norges Forskningsråd; Cancer Research UK; Kreftforeningen; Ministerstvo Zdravotnictví Ceské Republiky; Morris Animal Foundation; Deutsche Forschungsgemeinschaft; Universitetet i Oslo; Macquarie University; Breast Cancer Campaign; Kræftens Bekæmpelse; Instituto de Salud Carlos III; Florida State University; National Institutes of Health; U.S. Department of Health and Human Services; U.S. Department of Defense","keywords":"Surgical oncology; Breast cancer; Medicine; Lymph node; Pathology; Magnetic resonance imaging; Cancer; Oncology; Radiology; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004796002,0.0003848541,0.0006394912,0.001941478,0.0002722784,0.0004658894,0.000298411,0.0003975055,0.001755731],"category_scores_gemma":[0.0008916521,0.0001394907,0.0001967925,0.001541335,0.0001984268,0.0001902957,0.0002300503,0.0002025689,0.001110566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001953436,"about_ca_system_score_gemma":0.0002496625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007054345,"about_ca_topic_score_gemma":0.0009757287,"domain_scores_codex":[0.9995832,0.00007585956,0.00004999409,0.0001156633,0.0001405871,0.00003469257],"domain_scores_gemma":[0.9996263,0.00005464601,0.00009178877,0.00005845834,0.0001368775,0.00003195185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001566142,0.0002848826,0.2257208,0.0007021732,0.000145189,0.00162139,0.0002010688,0.0003973109,0.6617844,0.0001661436,0.001529563,0.1058809],"study_design_scores_gemma":[0.00006553908,0.001583421,0.7515356,0.0001908574,0.0005089658,0.01042403,0.0005562103,0.003734039,0.2122981,0.0003759559,0.01867491,0.00005236266],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9563657,0.01310132,0.01989471,0.0001116813,0.0001541142,0.0004081865,0.006069141,0.0002281329,0.003666897],"genre_scores_gemma":[0.9420622,0.008281277,0.03933056,0.0001407587,0.0001361108,0.0004038143,0.007618015,0.0000983038,0.001928972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001941478,"threshold_uncertainty_score":0.005873561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.047434028590686,"score_gpt":0.4197763735547578,"score_spread":0.3723423449640718,"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."}}