{"id":"W2099326137","doi":"10.1016/j.medengphy.2007.11.003","title":"Improved reproducibility of high-resolution peripheral quantitative computed tomography for measurement of bone quality","year":2008,"lang":"en","type":"article","venue":"Medical Engineering & Physics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":231,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Reproducibility; Quantitative computed tomography; Biomedical engineering; Repeatability; Scanner; Peripheral; Nuclear medicine; Medicine; Materials science; Computer science; Bone density; Mathematics; Osteoporosis; Pathology; Artificial intelligence; Internal medicine; Statistics","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":[0.006451549,0.0006407902,0.000635889,0.0006178495,0.0001813192,0.0006875529,0.0006020135,0.0005544035,0.001117436],"category_scores_gemma":[0.009564547,0.0004636401,0.0003030659,0.0005545183,0.0005019253,0.0003189432,0.0005019378,0.0004093582,0.0005446123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001915635,"about_ca_system_score_gemma":0.0003187344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007834649,"about_ca_topic_score_gemma":0.001272728,"domain_scores_codex":[0.9946066,0.00239514,0.0003010428,0.001106219,0.001471092,0.0001200505],"domain_scores_gemma":[0.9941925,0.002357795,0.0006286744,0.001776376,0.0009457225,0.00009873072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001370318,0.000116178,0.06845554,0.0001674913,0.000112532,0.0002767991,0.0004561881,0.001959281,0.8540438,0.0001516821,0.0003528137,0.0725373],"study_design_scores_gemma":[0.0001472168,0.002333424,0.5879488,0.00004729547,0.0003165211,0.005024516,0.0001599938,0.0210438,0.3797163,0.0002781627,0.002854194,0.000129769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8213097,0.002165478,0.1736138,0.00009538949,0.00008134924,0.00008988548,0.0003433336,0.000690097,0.001610955],"genre_scores_gemma":[0.9516868,0.000268235,0.04632454,0.00006938163,0.00004739608,0.0000755415,0.0002406774,0.0001850291,0.001102414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006451549,"threshold_uncertainty_score":0.03411943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05768747993005931,"score_gpt":0.3208059329661042,"score_spread":0.2631184530360449,"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."}}