MétaCan
Menu
Back to cohort
Record W2979289668 · doi:10.1093/pch/pxz100

Morbilliform rash and conjunctival injection in a febrile child

2019· article· en· W2979289668 on OpenAlexaff
Alexander K. C. Leung, Kin Fon Leong, Consolato Sergi

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsAlberta Children's HospitalUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsKuala lumpurMedicineRashLibrary scienceFamily medicinePediatricsSurgery

Abstract

fetched live from OpenAlex

A 10-year-old Malay boy living in Malaysia presented with fever, rhinorrhea, cough, and red and watery eyes for 3 days. The child also had malaise, anorexia, headache, and photophobia. His parents could not recall whether he had been in contact with anyone unwell. There was no history of recent travel or drug taking. His parents did not know his immunization history well. On examination, the child’s temperature was 39.5°C, heart rate 93 beats per minute, respiratory rate 24 breaths per minute, and blood pressure 100/60 mm Hg. Diffuse bilateral conjunctival injection was noted (Figure 1). Examination of the oral cavity showed multiple small white papules on an erythematous background on the posterior buccal mucosa bilaterally (Figure 2). The pharynx was erythematous. Shotty lymph nodes were noted in the cervical areas bilaterally. The patient developed an erythematous morbilliform rash on the face the following day (Figure 1). The rash became confluent as it spread to the neck, trunk, and extremities over the next 2 days. The rash lasted for 7 days and faded in the same directional pattern as it appeared. Fever subsided and fine desquamation was noted as the rash faded.

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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.002
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 head0.007
GPT teacher head0.234
Teacher spread0.228 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicRabies epidemiology and controlFrench-language works237,207