Bibliographic record
Abstract
PET has seen rapid progression in recent years, with applications in oncology leading the way. The glucose analog (18)F-FDG is the most commonly used PET radiopharmaceutical and has been shown to accumulate avidly in several different neoplasms, including cancers of the lung. The following discussion will review the physiologic basis for the uptake of (18)F-FDG in lung neoplasms and demonstrate the utility of (18)F-FDG PET in lung cancer. A brief review of other PET radiopharmaceuticals in lung cancer imaging, and dual-modality PET/CT scanners, will be presented. Upon completion of this article, the reader should be able to describe the pharmacokinetics of (18)F-FDG and discuss the efficacy of (18)F-FDG PET scans in the evaluation of solitary pulmonary nodules, disease staging, and monitoring response to therapy. Additionally, the reader should be able to compare (18)F-FDG PET with conventional anatomic imaging and describe some of the technical challenges of PET/CT fusion imaging.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".