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Record W2615715471 · doi:10.14740/jnr.v7i3.443

Development of New-Onset Chronic Inflammatory Demyelinating Polyneuropathy Following Exposure to a Water-Damaged Home With High Airborne Mold Levels: A Report of Two Cases and a Review of the Literature

2017· review· en· W2615715471 on OpenAlexvenueno aff
Allan Lieberman, Luke Curtis, Andrew Campbell

Bibliographic record

VenueJournal of Neurology Research · 2017
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunotoxicology and immune responses
Canadian institutionsnot available
Fundersnot available
KeywordsChronic inflammatory demyelinating polyneuropathyMedicinePathologicalNeurocognitiveChronic fatigueAttention deficitsPediatricsPathologyPhysical therapyImmunologyCognitionPsychiatryChronic fatigue syndrome

Abstract

fetched live from OpenAlex

The exact pathological processes and triggers for chronic inflammatory demyelinating polyneuropathy (CIDP) are not well understood. We report two patients who developed CIDP after living in a badly water-damaged home which contained very high levels of airborne mold. We also present a short review of the related literature linking exposure to mold and mycotoxins with neurological problems. The patients had nerve conduction velocities, clinical exam findings, and (in one patient) a sural nerve biopsy consistent with CIDP. The patients also developed other new-onset chronic health problems including chronic fatigue, asthma, and neurocognitive problems such as memory and attention deficits. Clinicians who treat patients with CIDP and other peripheral neuropathies need to consider and document environmental and occupational exposures (such as indoor water damage and heavy mold growth) as potential triggers for neurological damage. J Neurol Res. 2017;7(3):59-62 doi: https://doi.org/10.14740/jnr413e

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.095
GPT teacher head0.391
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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