A.5 Neuropathology of eight cases of the New Brunswick cluster of Neurological Syndrome of Unknown Cause (NSUC)
Bibliographic record
Abstract
Background: In March 2021, at a press conference, the presence of a cluster of patients, claimed to have a novel neurological syndrome, was announced in New Brunswick. These patients were suggested to have symptoms reminiscent of CJD. The onset of disease was between 2015 and 2021. The size of this cluster has been reported as approximately 50 cases. Further news publications have suggested that various environmental factors were causing this disease. Methods: Between 2019 and 2021 eight patients have died in this cluster. Their neuropathological findings are reported here. Results: There was one case of metastatic carcinoma, one case of FTLD-TDP43, one case of neocortical Lewy body pathology, one case of neocortical Lewy body pathology and AD, 2 cases of AD with vascular pathology, one case of mainly vascular pathology, and one case without significant pathology (consistent with patient’s history). In all these patients no evidence for a prion disease was found, nor novel pathology. Conclusions: We suggest that these 8 patients represent a group of misclassified clinical diagnoses. Classical probability theorem based statistical evaluation shows that this group of deceased patients is representative for the entire cluster at a p=0.0001 level, which would suggest that the entire cluster is based on misdiagnoses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".