Bibliographic record
Abstract
Most dual-energy computed tomography (DECT) scanners currently in clinical use, such as dual-source scanners (Siemens AG, Forchheim, Germany) or rapid kilovolt peak (kVp) switching scanners (GE Healthcare, Waukesha, WI), can perform acquisitions in either single-energy computed tomography (SECT) or DECT mode.Indeed, in practice, when the additional information provided by the DECT mode is deemed to be superfluous for the clinical question at hand, Disclosures: R. Forghani has acted as a consultant for GE Healthcare and has served as a speaker at lunch and learn sessions titled "Dual-Energy CT Applications in Neuroradiology and Head and Neck Imaging" sponsored by GE Healthcare at the 27th and 28th Annual Meetings of the Eastern Neuroradiological Society in 2015 and 2016 (no personal compensation or travel support for these sessions).B. De Man is CT Business Portfolio Leader and Manager of Image Reconstruction Laboratory, GE Global Research.R. Gupta declares no relevant conflict of interest.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".