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Record W2785860411 · doi:10.1016/j.ijid.2018.02.002

Scurvy as a mimicker of osteomyelitis in a child with autism spectrum disorder

2018· article· en· W2785860411 on OpenAlexaff
Laura M. Kinlin, Ana C. Blanchard, Shawna Silver, Shaun K. Morris

Bibliographic record

VenueInternational Journal of Infectious Diseases · 2018
Typearticle
Languageen
FieldNursing
TopicVitamin C and Antioxidants Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsScurvyMedicineAutism spectrum disorderOsteomyelitisAutismPediatricsContext (archaeology)Vitamin deficiencyAscorbic acidVitamin CIntensive care medicineVitaminSurgeryInternal medicinePsychiatryBiology

Abstract

fetched live from OpenAlex

A case of scurvy in a 10-year-old boy with autism spectrum disorder is described. His clinical presentation was initially thought to be due to osteomyelitis, for which empirical antimicrobial therapy was initiated. Further invasive and ultimately unnecessary investigations were avoided when scurvy was considered in the context of a restricted diet and classic signs of vitamin C deficiency. Infectious diseases specialists should be aware of scurvy as an important mimicker of osteoarticular infections when involved in the care of patients at risk of nutritional deficiencies.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.005
GPT teacher head0.280
Teacher spread0.275 · 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

Citations30
Published2018
Admission routes1
Has abstractyes

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