{"id":"W2108736937","doi":"10.1016/j.nucmedbio.2011.06.004","title":"[18F]-fluoroestradiol quantitative PET imaging to differentiate ER+ and ERα-knockdown breast tumors in mice","year":2011,"lang":"en","type":"article","venue":"Nuclear Medicine and Biology","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; BC Cancer Agency; Université de Sherbrooke","funders":"Canadian Institutes of Health Research; Canadian Breast Cancer Research Alliance; Université de Sherbrooke; Breast Cancer Alliance","keywords":"Gene knockdown; Estrogen receptor; Standardized uptake value; Biodistribution; Positron emission tomography; Cancer research; Estrogen receptor alpha; Fluorodeoxyglucose; Chemistry; Medicine; Cell culture; Nuclear medicine; Pathology; Breast cancer; In vitro; Biology; Cancer; 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":[0.0002035398,0.0001507474,0.0003701276,0.0001735596,0.00005183479,0.000004470949,0.00008149301,0.00003979033,0.0002911017],"category_scores_gemma":[0.00009788198,0.0001035818,0.00002181839,0.0001538442,0.0004382342,0.0000325811,0.00007412133,0.0002405374,0.00001431347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001506661,"about_ca_system_score_gemma":0.0000174611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001135706,"about_ca_topic_score_gemma":0.00002232148,"domain_scores_codex":[0.9990321,0.00004637449,0.0002664155,0.0003388062,0.00006166469,0.0002546583],"domain_scores_gemma":[0.9994178,0.00006360241,0.00005396796,0.0001539536,0.00004253025,0.000268085],"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":[0.001055282,0.0007669227,0.3161732,0.0004134864,0.0001508107,0.0006749173,0.01424612,2.951672e-8,0.4579313,0.07390902,0.03707081,0.09760807],"study_design_scores_gemma":[0.00464223,0.002711812,0.9406564,0.001506121,0.0002653434,0.006175937,0.004186985,0.00205726,0.0007294146,0.00839195,0.02804091,0.0006356264],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973923,0.0002450223,0.0002747682,0.02250637,0.00004206965,0.0003356137,0.00001103754,0.00008742065,0.002574751],"genre_scores_gemma":[0.9870871,0.0002560981,0.008181856,0.004297517,0.00007922068,0.00001754154,0.00001816891,0.00001840646,0.00004413003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6244832,"threshold_uncertainty_score":0.4223945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0581411124380397,"score_gpt":0.3324825280717296,"score_spread":0.2743414156336899,"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."}}