Volumetric display of magnetic resonance images using Scopira and OpenGL
Bibliographic record
Abstract
Functional magnetic resonance imaging (fMRI) is a complex imaging modality that provides high resolution, non-invasive maps of neural activity in brain tissue. Neuroscientists use fMRI to probe brain function using complex cognitive and linguistic experiments. An important aspect of these experiments is the visualization of neural activations over a period of time as manifested by voxel intensity of two (or three) dimensional images across the temporal analysis dimension. Scopira is a modular algorithm development framework that consists of a user-friendly visual layout environment with a comprehensive set of scientific algorithms for biomedical data analysis. However, presently it lacks the facility for volumetric display, which is especially important to map neural activations from functional (low resolution) to anatomical (high resolution) images. In this paper, we present a volumetric display and analysis system for fMRI data using Scopira and the OpenGL library. Results have been presented to demonstrate the new software.
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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 | 0.001 |
| 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".