{"id":"W4403466417","doi":"10.26434/chemrxiv-2024-lq0m0","title":"Racial Diversity in Cancer Models: A Call to Action for Nanomedicine Researchers","year":2024,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Call to action; Diversity (politics); Nanomedicine; Racial diversity; Action (physics); Political science; Race (biology); Sociology; Business; Engineering; Physics; Marketing","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":[0.0002089672,0.0001503835,0.0001871758,0.0002381403,0.00002576211,0.00001926781,0.0001737376,0.0002670559,0.00002558375],"category_scores_gemma":[0.00003768848,0.0001515562,0.000058661,0.0002324343,0.00002091045,0.00002936719,0.0003698362,0.0005925731,0.00001459482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006326402,"about_ca_system_score_gemma":0.0000772802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004757481,"about_ca_topic_score_gemma":0.000199146,"domain_scores_codex":[0.9991679,0.000004689571,0.0001442654,0.0002618235,0.0001653065,0.0002560401],"domain_scores_gemma":[0.9996187,0.00002786641,0.000009303991,0.0001537516,0.0000354738,0.000154869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001474173,0.0001536166,0.0002449567,0.02726686,0.0003720322,0.0000172577,0.02010501,0.6234367,0.01404507,0.0003043978,0.192125,0.1217816],"study_design_scores_gemma":[0.0007073795,0.0000610985,0.001986946,0.002313202,0.000105382,0.000001106868,0.0002429177,0.9395549,0.00510449,0.01493403,0.03413831,0.0008502976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9668829,0.003016243,0.0154422,0.004583859,0.007436258,0.0009067392,0.00004282899,0.0005705447,0.001118468],"genre_scores_gemma":[0.9971358,0.0003759529,0.0005590838,0.00004625848,0.0008564877,0.0004116101,0.00004970061,0.00003863681,0.0005264762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3161181,"threshold_uncertainty_score":0.6180281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1670017519408857,"score_gpt":0.3563827379234992,"score_spread":0.1893809859826135,"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."}}