{"id":"W2016504103","doi":"10.1016/j.crad.2014.05.112","title":"Enhancing multimodality functional and molecular imaging using glucose-coated gold nanoparticles","year":2014,"lang":"en","type":"article","venue":"Clinical Radiology","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"Canadian Breast Cancer Research Alliance; Breast Cancer Alliance","keywords":"Medicine; Multimodality; Nanoparticle; Colloidal gold; Molecular imaging; Nanotechnology; Biomedical engineering; In vivo; Linguistics","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":[0.0006371107,0.0001651137,0.0003467005,0.00004637349,0.00004999482,0.00001868158,0.00009580543,0.00014936,0.00002159662],"category_scores_gemma":[0.0004867019,0.0001616582,0.00008147406,0.00009268191,0.0002119728,0.00009727351,0.00004503021,0.0002686307,0.00001925701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000568896,"about_ca_system_score_gemma":0.0000213768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001323368,"about_ca_topic_score_gemma":0.000009522661,"domain_scores_codex":[0.9986687,0.00009427563,0.000534839,0.0002780975,0.00008048482,0.0003435802],"domain_scores_gemma":[0.9989041,0.0006247984,0.00005647211,0.0002286308,0.0000398708,0.0001461174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003599059,0.00001800366,0.01504028,0.00002333626,0.00006076453,0.000009522088,0.00002565146,0.004204847,0.9720739,0.0004169202,0.0001246656,0.00796617],"study_design_scores_gemma":[0.002399425,0.0001246074,0.02195012,0.00005173376,0.0001136595,0.0001286559,0.00002876324,0.6664017,0.2995551,0.004674572,0.004019255,0.0005523987],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9145045,0.0008170735,0.08321283,0.00005555183,0.0009864056,0.0000900434,0.000003008619,0.00019821,0.0001324048],"genre_scores_gemma":[0.9956313,0.00006939057,0.003524122,0.0004825017,0.0002397609,0.000005010336,0.000006541548,0.00003657829,0.00000481606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6725187,"threshold_uncertainty_score":0.6592231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02538499720509306,"score_gpt":0.2872119517324987,"score_spread":0.2618269545274056,"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."}}