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Record W2414358872 · doi:10.1017/cjn.2015.42

“Tinkle Tinkle Little Girl, How We Wonder Why You Can’t”: An Unusual AIDP-like Syndrome in a Toddler

2015· article· en· W2414358872 on OpenAlexaffvenue
Thilinie Rajapakse, Claire Hinnell, Xing‐Chang Wei, Jean K. Mah, Jong M. Rho

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2015
Typearticle
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsFraser HealthAlberta Children's Hospital
Fundersnot available
KeywordsToddlerGirlWonderContent (measure theory)Action (physics)PsychologyDevelopmental psychologySocial psychologyMathematicsPhysics

Abstract

fetched live from OpenAlex

Acute inflammatory demyelinating polyradiculoneuropathy (AIDP) is most frequently associated with rapidly progressive flaccid paralysis and areflexia.The estimated childhood incidence of AIDP (0-15 years of age) is 0.34 to 1.34 per 100,000 per year and the diagnosis of AIDP is often delayed in up to 2/3 of preschool age children due to nonspecific clinical symptoms and intrinsic difficulties in performing neurological examinations in this age group. 1 Further contributing to diagnostic inaccuracy is the presence of AIDP variants such as Miller-Fisher syndrome and the pharyngeal-cervical-brachial variant.The major concern with such phenotypic variations is that misdiagnosis or delay in treatment can have substantial effects on acute mortality and chronic morbidity.1 We report a case of a three year-old previously healthy girl with a purely autonomic variant of an AIDP-like syndrome consisting only of urinary and stool retention with nerve root enhancement with normal strength, (CSF) and nerve conduction studies responsive to intravenous immunoglobulin (IVIG) treatment.

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)0.003
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.090
GPT teacher head0.282
Teacher spread0.191 · 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
GenreEmpirical

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
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicHereditary Neurological DisordersFrench-language works237,207