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Record W1994089985 · doi:10.1097/pec.0b013e31815f6fa8

Oropharyngeal Injuries in Children

2007· review· en· W1994089985 on OpenAlexaff
Tal Marom, Eyal Russo, Yoram Ben-Yehuda, Yehudah Roth

Bibliographic record

VenuePediatric Emergency Care · 2007
Typereview
Languageen
FieldMedicine
TopicTraumatic Ocular and Foreign Body Injuries
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineReferralHead and neckEmergency medicineAuditIntervention (counseling)Emergency treatmentPediatricsSurgeryFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Oral cavity and oropharyngeal injuries are common among pediatric patients seen in emergency rooms for head and neck trauma. The appropriate treatment of such injuries is often controversial. PATIENTS AND METHODS: Audit of 6 months' admissions to the pediatric emergency room in a secondary care referral center. Sixty-four patients were treated for various injuries. Charts were reviewed for relevant data. RESULTS: Description of distribution of types and sites of injuries and discussion of treatment recommendations. CONCLUSIONS: Most of oropharyngeal injuries heal without any intervention and therefore can be left untreated after being diagnosed. However, in certain injuries, treatment is indicated for better outcome results.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.361
Teacher spread0.329 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2007
Admission routes1
Has abstractyes

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