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Record W2079776499 · doi:10.14740/jmc.v5i9.1753

Occult Vertebral Osteomyelitis, a Diagnostic Conundrum

2014· article· en· W2079776499 on OpenAlexvenueno aff
Brijesh Patel, Adam Forman, Vilma Drelichman, Michael Marshall

Bibliographic record

VenueJournal of Medical Cases · 2014
Typearticle
Languageen
FieldMedicine
TopicInfectious Diseases and Tuberculosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVertebral osteomyelitisOsteomyelitisOccultCulpritAbdominal painGold standard (test)ModalitiesRadiologySurgeryPathologyInternal medicine

Abstract

fetched live from OpenAlex

Vertebral osteomyelitis is a well-known but uncommon condition. Typical presenting features include fever, back pain with local tenderness and neurologic symptoms. In absence of these typical findings, vertebral osteomyelitis can be difficult to diagnose. Staphylococcus species are the most common causes. In most cases, inflammatory markers are elevated. Blood cultures can be very useful to identify the culprit organism(s). Though various imaging modalities are available, an MRI is considered gold standard for the diagnosis. Our patient presents with non-specific abdominal pain that masqueraded vertebral osteomyelitis leading to paralysis. J Med Cases. 2014;5(9):505-508 doi: http://dx.doi.org/10.14740/jmc1753w

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)0.001
metaresearch head score (Gemma)0.010
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0030.003
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.012
GPT teacher head0.285
Teacher spread0.273 · 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
Published2014
Admission routes1
Has abstractyes

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