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Record W2254367010 · doi:10.2217/pmt.15.58

Post-Tonsillectomy Pain Control: Consensus Or Controversy?

2015· review· en· W2254367010 on OpenAlex
Natasha Cohen, Doron D. Sommer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePain Management · 2015
Typereview
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTonsillectomyMedicineAnalgesicIntensive care medicineHealth professionalsPain controlHealth carePostoperative painPain managementPhysical therapySurgeryAnesthesia

Abstract

fetched live from OpenAlex

Pediatric post-tonsillectomy analgesia continues to be highly debated and an area of active research. Tonsillectomy pain can lead to significant patient morbidity, and incur potentially avoidable healthcare costs. Moreover, the various analgesic classes, each present their own risk profiles and unique side effects when used in children post-tonsillectomy. This review delineates the clinical and pathophysiological basis for post-tonsillectomy pain, types of analgesics and their risk profiles, as well as special considerations in this clinical population and a review of alternative analgesic treatment options. This article presents a summary of recent literature and discusses evidence-based management options to aid medical and allied health professionals who may encounter these patients.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.052
GPT teacher head0.364
Teacher spread0.312 · 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