{"id":"W4224280391","doi":"10.1097/rli.0000000000000867","title":"From Dose Reduction to Contrast Maximization","year":2022,"lang":"en","type":"article","venue":"Investigative Radiology","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Emergent BioSolutions (Canada)","funders":"","keywords":"Reduction (mathematics); Contrast (vision); Maximization; Computer science; Mathematics; Artificial intelligence; Mathematical optimization","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":[0.00008040352,0.00009923728,0.0002257296,0.0001103262,0.0001300087,0.000004934254,0.00004776215,0.00003532048,0.00062008],"category_scores_gemma":[0.0001171089,0.00009092045,0.00004245388,0.0002253363,0.0001314094,0.00002741066,0.00004421706,0.0001217818,0.000059208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002245479,"about_ca_system_score_gemma":0.00006741521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002912706,"about_ca_topic_score_gemma":0.000005726176,"domain_scores_codex":[0.9991366,0.0001715518,0.0001570236,0.0002750103,0.0001087971,0.0001510063],"domain_scores_gemma":[0.9995105,0.00006094001,0.00005945476,0.0001634392,0.00004380343,0.0001618105],"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":[0.0007828441,0.0009146918,0.0850249,0.00001188711,0.0007083435,0.0005291732,0.009479819,0.004571589,0.781334,0.00937082,0.09565244,0.01161943],"study_design_scores_gemma":[0.01043641,0.004933416,0.7182878,0.00005671741,0.0004884971,0.00169269,0.004211812,0.001095413,0.1737795,0.03519085,0.04925473,0.0005721088],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847239,0.000215464,0.00009383071,0.0134798,0.0004122107,0.0004557421,0.00006727625,0.00005138345,0.0005004281],"genre_scores_gemma":[0.9948443,0.000007614704,0.002293067,0.001832185,0.0002433434,0.0003561154,0.0003154431,0.00001338253,0.0000945665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6332629,"threshold_uncertainty_score":0.6789442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02986675005364214,"score_gpt":0.2744330888360821,"score_spread":0.24456633878244,"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."}}