TE-dependent analysis of multi-echo fMRI with tedana
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
Functional magnetic resonance imaging (fMRI) is a popular method for in vivo neuroimaging. Modern fMRI sequences are often weighted towards the blood oxygen level dependent (BOLD) signal, which is closely linked to neuronal activity This weighting is achieved by tuning several parameters to increase the BOLD-weighted signal contrast. One such parameter is "TE," or echo time. TE is the amount of time elapsed between when protons are excited (the MRI signal source) and measured. Although the total measured signal magnitude decays with echo time, BOLD sensitivity increases The optimal TE maximizes the BOLD signal weighting based on a number of factors, including several MRI scanner parameters (e.g., field strength), imaged tissue composition (e.g., grey vs. white matter), and proximity to air-tissue boundaries.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it