Bibliographic record
Abstract
Independent component analysis (ICA) and statistical parametric mapping (SPM) are two commonly used methods of analyzing fMRI measurements. Typically, these methods are applied separately to the measurements to produce brain maps indicating active brain regions in response to a stimulus or a performed task. However, ICA can also be used to develop a hemodynamic response model that can be used as a regressor in SPM of fMRI measurements. This may lead to a more accurate method of localizing brain activity that corresponds to performing a task or to various pathologies. In this study, BOLD fMRI data were acquired from a subject performing a finger flexion task in a block design paradigm. Both spatial and temporal ICA was performed on the subject's BOLD fMRI measurements. Two hemodynamic response model signals were generated from ICA results to use as regressors in SPM of the subject data. IC maps and SPM-generated brain maps of the subject data using the canonical hemodynamic response model and the ICA-derived models were compared. In all cases, there was significant overlap in voxel activations
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".