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Record W4403013382 · doi:10.1016/j.jtumed.2024.09.009

Orthopedic research productivity of KSA: First bibliometric analysis

2024· article· en· W4403013382 on OpenAlexaboutno aff
Abdulaziz Z. Alomar, Nouf Altwaijri, Khalid I. Khoshhal

Bibliographic record

VenueJournal of Taibah University Medical Sciences · 2024
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
FundersDeanship of Scientific Research, King Saud UniversityKing Saud University
KeywordsProductivityOrthopedic surgeryMedicineSurgeryEconomics

Abstract

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Purpose: Medical research is a crucial indicator of a nation's reputation and development. However, there are concerns about the limited orthopedic research in Kingdom of Saudi Arabia (KSA). Therefore, this study conducted bibliometric analysis to investigate orthopedic research output from KSA. Methods: PubMed database for orthopedic articles, with a minimum of one KSA-affiliated orthopedic author published from the year 2000 onwards, was searched. This excluded duplicate articles, corrections, letters, editorials, commentaries, and brief communications. The titles of the included articles, publication years, first and corresponding authors' primary affiliations and countries, countries and institutes of research, and total citations were noted. Thereafter, year-wise research contribution, top contributing and collaborating nations, top contributing affiliations, study types, levels of evidence, journal distribution, their impact factor, h-index and quartile-related information, and citation trends were analyzed. Results: The search strategy yielded 1047 eligible articles. An increasing trend in research contributions in recent years was observed, with the least number of articles (8) contributed in 2005 and the most (140) in 2023. The research was conducted in KSA for most articles (83.48%). Authors from Canada collaborated in 3.44% of the articles. King Saud University was the top contributing institution (17.38% of all articles). There were 66 (6.30%) basic science studies and 873 (83.3%) clinical studies. Among non-basic science studies, 84.51% had level IV evidence. Overall, 73.83% of articles had either first/corresponding or both authorships from KSA-affiliated orthopedic authors. The eligible articles were published in 303 journals, with a mean impact factor of 3.04 (range 0.4-51.1, 165 journals) and a mean h-index of 59.2 (range 1-367, 277 journals). Overall, 31.23% of articles with quartile information available were published in first-quartile journals. Conclusions: The orthopedic research productivity in KSA is limited. However, there has been an increasing trend in orthopedic research in recent years. Nevertheless, the quality of clinical research, particularly the level of evidence, needs improvement. Therefore, further efforts should be made to strengthen research opportunities and encourage research participation among orthopedic and medical institutes.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometricsMetaresearch
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometricsMetaresearch
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.162
metaresearch head score (Gemma)0.114
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1620.114
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.7530.947
Science and technology studies0.0010.003
Scholarly communication0.0010.002
Open science0.0060.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.709
GPT teacher head0.612
Teacher spread0.097 · 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

Labeled directly by 2 models reading the full record.

Study designObservational
DomainEvaluation
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

Citations3
Published2024
Admission routes1
Has abstractyes

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