nordic fMRI Solution - Products for Enhancing the Development of a Functional Imaging Clinical Practice
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
In the last few years we have witnessed increased adoption of functional magnetic resonance imaging (fMRI) technology in clinical settings. fMRI is rapidly gaining acceptance as a pre-operative planning tool. Functional imaging data provide critical information to the neurosurgeon for considering therapeutic approaches that might not be considered due to procedural risk. The goal is to accurately delineate tissue pathology from surrounding eloquent cortex and examine vital connections between brain regions, aiding decision-making and maintaining a balance between a more aggressive resection approach and reducing post-operative deficits. In this article we describe the solution NordicNeuroLab has developed to support this technology and illustrate the method employed in the Department of Neurosurgery at Pecs University Medical School in Hungary to assess pre-operative risk and plan surgery for patients with brain tumours.
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 | 0.003 | 0.010 |
| 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 it