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Record W4321253287 · doi:10.3389/fpubh.2023.1064576

Bibliometric and visualized analysis of scientific publications on rehabilitation of rotator cuff injury based on web of science

2023· article· en· W4321253287 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers in Public Health · 2023
Typearticle
Languageen
FieldComputer Science
TopicScientific Research and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsRotator cuffRehabilitationWeb of scienceTelerehabilitationRotator cuff injuryMedicineBibliometricsPhysical therapyPhysical medicine and rehabilitationMedical educationLibrary scienceComputer scienceTelemedicineMeta-analysisSurgeryHealth carePathologyPolitical science

Abstract

fetched live from OpenAlex

Background Since the discovery of rehabilitation as an intervention for rotator cuff injury, its impact on the recovery of rotator cuff injury has attracted crucial attention, and the number of related studies is increasing worldwide. There were no bibliometric and visualized analysis studies in this field. This study aimed to investigate the research hotpots and trends in the rehabilitation of rotator cuff injury via bibliometric and visualized analysis and to identify the future development of clinical practice. Method The publications regarding rehabilitation of rotator cuff injury from inception to December 2021 were obtained from the Web of Science Core Collection database. The trends of publications, co-authorship and co-occurrence analysis and visualized analysis were carried out using Citespace, VOSviewer, Scimago Graphica software, and R Project. Results A total of 795 publications were included in this study. The number of publications significantly increased yearly. The United States published the highest number of related papers and the papers published by the United States had the highest citations. The University of Laval, the University of Montreal and Keele University were the top 3 most contributive institutions. Additionally, the Journal of Shoulder and Elbow Surgery was the journal with the highest number of publications. The most common keywords were “rotator cuff”, “rehabilitation”, “physical therapy”, “management”, and “telerehabilitation”. Conclusion The total number of publications has shown a steady upward trend. The cooperation between countries globally was still relatively lacking, and therefore it is necessary to strengthen cooperation between different countries and regions to provide conditions for multi-center, large sample, and high-quality research. In addition to the relatively mature rehabilitation of rotator cuff injury such as passive motion or exercise therapy, telerehabilitation has also attracted much attention with the progress of science.

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)0.013
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.2430.474
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.382
Teacher spread0.337 · 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