Bibliographic record
Abstract
To locate and identify pathology of the central nervous system (CNS) noninvasively and with a high degree of specificity is an objective pursued by means of several imaging modalities and with varying degrees of success. Some, for example X-ray, computed tomography (CT), and ultrasonography, provide purely structural information, whereas others, namely positron emission tomography (PET) and single photon emission computed tomography (SPECT), give rise largely to functional data. The principal advantage of the structural technique of CT is one of high spatial resolution, whereas the primary advantage of low resolution PET is one of high specificity. Ultimately, nuclear magnetic resonance (NMR) promises to provide both high-resolution structural images and lower-resolution functional data, but at the moment only the imaging application is well enough developed for widespread clinical use. It is the imaging application of NMR that is the subject of this article, whereas the highly promising, functional-data-providing spectroscopy will be dealt with in a companion article by J. W. Pritchard.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".