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Record W2121020638 · doi:10.1017/s0022215113000856

Are UK otorhinolaryngologists maintaining their research output?

2013· article· en· W2121020638 on OpenAlexaboutno aff
Kunal Kulkarni, Medini Kulkarni, Jeremy J. Ramsden, P Silva

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2013
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsnot available
Fundersnot available
KeywordsOtorhinolaryngologyFellMedicineConverseHead and neck surgeryDemographySurgeryGeographyMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: In the general surgical and anaesthetic literature, there has been a decline in research output originating from the UK. This study analysed the 10 globally leading and 2 UK leading otorhinolaryngology journals to determine whether this trend was also reflected within otorhinolaryngology. METHODS: Citable research output was analysed from 4 individual years, over a 10-year period (2000-2010), to determine absolute output, geographical mix and article type. RESULTS: The proportion of research output from the UK and Ireland grew 22.8 per cent among the leading global otorhinolaryngology journals, but fell 28.6 per cent among the leading two UK otorhinolaryngology journals. The converse trend was true for the USA and Canada. Output from European and the rest of the world grew among both sets of journals, while Japanese output fell. 'Research' articles remained the most prevalent type. CONCLUSION: These results are encouraging as they refute the fall in UK research output observed by other authors. In the face of growing challenges, it is important to maintain published output so that the fate that has befallen other specialties is not mirrored within UK otorhinolaryngology.

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)0.017
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0060.003

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 head0.189
GPT teacher head0.500
Teacher spread0.311 · 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; both teacher heads agree on what is shown here.

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

Citations6
Published2013
Admission routes1
Has abstractyes

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