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Record W2063038848 · doi:10.1017/s0022215106003495

ENT in general practice: training, experience and referral rates

2006· article· en· W2063038848 on OpenAlexaboutno aff
Philip J. Clamp, Sulekha Gunasekaran, David D. Pothier, M. W. Saunders

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineReferralGlobal Positioning SystemOtorhinolaryngologyTraining (meteorology)General practiceQuarter (Canadian coin)Family medicineMedical educationSurgery

Abstract

fetched live from OpenAlex

A postal survey of 500 general practitioners (GPs) in south-west England was undertaken to evaluate the levels of undergraduate and postgraduate otolaryngology training and/or experience received by GPs in that area. Most GPs had received two weeks of undergraduate training in ENT, which had involved no formal assessment. Three-quarters of GPs considered this inadequate. A quarter of GPs had completed a hospital post in ENT prior to entering general practice, most of which lasted three months. Sixty-one per cent of GPs had received some formal postgraduate training in ENT, in the form of courses, lectures or hospital training sessions. Almost half of the GPs considered this inadequate. Seventy-five per cent of GPs stated they would like further training in ENT. Subjective estimates of referral rates to hospital ENT specialist clinics varied considerably. This study illustrates the variability and level of dissatisfaction regarding ENT training amongst GPs at both undergraduate and postgraduate levels.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.307
Teacher spread0.276 · 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 designObservational
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

Citations69
Published2006
Admission routes1
Has abstractyes

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