Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Since the inception of magnetic resonance imaging, thousands of studies have appeared in the literature reporting on multiple imaging techniques. However, there is a paucity of neuroimaging research programs developed by nurse scientists. OBJECTIVES: The purpose of this article is to introduce the nurse scientist to complex neuroimaging methods with the ultimate goal of creating impetus for future use of brain imaging in nursing research. METHODS: This article reviews common neuroimaging methods, presents vocabulary frequently used in neuroimaging work, provides information on access to resources in neuroimaging education, and discusses considerations for use of neuroimaging in research. RESULTS: Ten imaging modalities are reviewed, including structural and functional magnetic resonance imaging, computed tomography, positron emission tomography, and encephalography. DISCUSSION: Choosing an imaging modality for research depends on the nature of the research question, needs of the patient population of interest, and resources available to the novice and seasoned nurse scientist. Neuroimaging has the potential to innovate the study of symptom science and encourage interdisciplinary collaboration in research.
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.
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 | 0.051 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it