Bibliographic record
Abstract
There are so many intersections in science and life that often go unnoticed. But in this most recent edition the intricate connections between life, science, and work are readily apparent. The entire editorial team is grateful for the opportunity to review the great work submitted by our authors which highlights how to navigate all of these connections. In the insightful survey by Vaisman et al. we learn that there is an over 50% rate of burnout in Latin American Orthopaedic Surgeons who responded to their survey [[1]Vaisman A. Guiloff R. Contreras M. Casas-Cordero J.P. Calvo R. Figueroa D. Over 50% of self-reported burnout among Latin American orthopaedic surgeons: a cross-sectional survey on prevalence and risk factors.J ISAKOS. 2024; 9: 128-134Google Scholar]. This highlights the need to emphasize wellness and self care within our profession as this is likely a global phenomenon. Further, the impact of sleep dysfunction on PROMIS scores in those who have rotator cuff tears is also evaluated using mixed effects models by Danilkowicz et al. [[2]Danilkowicz R.M. Hurley E.T. Hinton Z.W. et al.Association between sleep dysfunction and Patient-Reported Outcomes Measurement Information System scores in patients with rotator cuff tears.J ISAKOS. 2024; 9: 143-147Google Scholar]. Interestingly, there was a high association between sleep dysfunction and stress, fatigue and elevated pain scores [[2]Danilkowicz R.M. Hurley E.T. Hinton Z.W. et al.Association between sleep dysfunction and Patient-Reported Outcomes Measurement Information System scores in patients with rotator cuff tears.J ISAKOS. 2024; 9: 143-147Google Scholar]. Finally, methodologically sound systematic reviews continue to showcase the best of evidence to inform practice on the most efficient treatment strategies for managing of cartilage defects in the knee and how sex-related differences may impact the rates of Achilles tendon injuries [[3]Tan C.H.B. Huang X.O. Tay Z.Q. Bin Abd Razak H.R. Arthroscopic and open approaches for autologous matrix-induced chondrogenesis repair of the knee have similar results: a meta-analysis.J ISAKOS. 2024; 9: 192-204Google Scholar,[4]Gianakos A.L. Hartman H. Kerkhoffs G.M.M.J. Kennedy J.G. Calder J. Sex differences in biomechanical properties of the Achilles tendon may predispose men to higher risk of injury: a systematic review.J ISAKOS. 2024; 9: 184-191Google Scholar]. Certainly, these overlapping spheres of interaction in these articles showcase how surgeon wellbeing, patient wellbeing, and gender-based research are at the forefront of current research. One then recognizes how we as healthcare providers share this impactful research is also pivotal to facilitate knowledge translation. Artificial intelligence and social medial are two examples of technologies that are changing the dynamic of how information is being processed and shared [[5]Khoriati A.A. Shahid Z. Fok M. et al.Artificial intelligence and the orthopaedic surgeon: a review of the literature and potential applications for future practice: current concepts.J ISAKOS. 2024; 9: 227-233Google Scholar,[6]Feroe A.G. Only A.J. Murray J.C. et al.Use of social media in orthopaedic surgery training and practice: a systematic review.JB JS Open Access. 2024 Jan 16; 9 (00098): e23https://doi.org/10.2106/JBJS.OA.23.00098Google Scholar]. Consequently, we are evaluating these technological developments as an editorial team and pursuing robust strategies focused on how to enhance interaction with JISAKOS publications. Our goals are to increase accessibility and visibility of our journal's content on the internet. Naturally, social media provides a unique opportunity. We have fortified our team by hiring a Social Media Editor, Katherine Paquette, and developed a social media task force currently being led by Emmanouil Brilakis and Yoan Bourgeault-Gagnon. This team continues to grow, and we encourage those who are interested and are social media savvy to reach out to digital@jisakos.com. We aspire to bring exciting and novel ways to communicate research from JISAKOS and use this intersection to bridge knowledge gaps globally. Going forward, all new authors will have the opportunity and are encouraged to share summary videos as well as social media tags for their published article. This will not only improve understanding of the research we publish across a wide readership, but also broaden the distribution and visibility of your research and impact in the field. So do prepare to get more social and interact with JISAKOS!
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.031 | 0.035 |
| Open science | 0.002 | 0.029 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".