Risk, diagnostic error, and the clinical science of consciousness
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 recent years, a number of new neuroimaging techniques have detected covert awareness in some patients previously thought to be in a vegetative state/unresponsive wakefulness syndrome. This raises worries for patients, families, and physicians, as it indicates that the existing diagnostic error rate in this patient group is higher than assumed. Recent research on a subset of these techniques, called active paradigms, suggests that false positive and false negative findings may result from applying different statistical methods to patient data. Due to the nature of this research, these errors may be unavoidable, and may draw into question the use of active paradigms in the clinical setting. We argue that false positive and false negative findings carry particular moral risks, which may bear on investigators' decisions to use certain methods when independent means for estimating their clinical utility are absent. We review and critically analyze this methodological problem as it relates to both fMRI and EEG active paradigms. We conclude by drawing attention to three common clinical scenarios where the risk of diagnostic error may be most pronounced in this patient group.
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 | 0.034 | 0.226 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.023 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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