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Record W4240894764 · doi:10.14740/jmc2540e

A Foe Incognito: Paraneoplastic Sacroilitis

2016· article· en· W4240894764 on OpenAlexvenueno aff
Sumantro Mondal, Debanjali Sinha, Tony Ete, Rudra Prosad Goswami, Jayati Bardhan, Alakendu Ghosh

Bibliographic record

VenueJournal of Medical Cases · 2016
Typearticle
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSacroiliitisPolyarthritisDermatologyMyeloid leukemiaMyositisDiseasePathologyVasculitisArthritisInternal medicine

Abstract

fetched live from OpenAlex

Paraneoplastic rheumatological symptoms are not uncommon in clinical practice. They can predate the diagnosis of the neoplastic disease. Carcinomatous polyarthritis, vasculitis, and inflammatory myopathy are commonly encountered paraneoplastic rheumatological diseases. Paraneoplastic sacroiliitis is rather uncommon. We herein report a case of paraneoplastic sacroiliitis due to acute myeloid leukemia in a young male. J Med Cases. 2016;7(8):341-343 doi: http://dx.doi.org/10.14740/jmc2540e

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)0.002
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
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)0.0050.001

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 head0.024
GPT teacher head0.313
Teacher spread0.289 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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