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Record W2442131692 · doi:10.4193/rhin10.300

Recalcitrant Rhinosinusitis, the diagnosis and treatment and evaluation of results

2010· editorial· en· W2442131692 on OpenAlexaff
W.J. Fokkens

Bibliographic record

VenueRhinology Journal · 2010
Typeeditorial
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineChronic rhinosinusitisSinusitisIntensive care medicineDermatologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Chronic Rhinosinusitis can be a debilitating disease. Since ancient times people are aware of this disease and potential treatments. In most patients rinsing with NaCl, and medical treatment, like local corticosteroids and if necessary (long term) antibiotics is an effective treatment. In a subpopulation this medical treatment is insufficient and FESS is necessary. In most studies FESS has been reported to be effective in over 80% of the cases. However in a small group of patients even the combination of medical and surgical treatment fails, the disease of these patients is often termed recalcitrant rhinosinusitis

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0030.001
Research integrity0.0080.015
Insufficient payload (model declined to judge)0.0040.005

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 head0.047
GPT teacher head0.352
Teacher spread0.305 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2010
Admission routes1
Has abstractyes

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