Bibliographic record
Abstract
Dear Readers, We are thrilled to bring you the first issue of the ninth volume of POCUS Journal. Published since 2016, POCUS Journal is the only multi-disciplinary, peer-reviewed, POCUS-focused journal that is free for authors and readers alike. We are grateful for the vision of our founder Dr. Amer and for the support of CINQUILL Medical Publishers, Inc. as we enter our ninth year of publication. POCUS is an ever-changing field as clinicians seek out better and faster solutions for patient care at the bedside. We at POCUS Journal continue to evolve as well. Our editorial board is growing to meet the demands of our high volume and high-quality manuscript submissions. We welcome Dr. Andre Kumar of Stanford University and Dr. Manpreet Malik of Emory University to the Internal Medicine section. We also welcome Dr. Andrea of the University of Southern California to the Pediatrics section. Natalie joins us from Queen’s University as the Social media Editor. If you haven’t seen her high-yield on social media I highly encourage you to visit POCUS Journal on X and Instagram for summaries of research articles and other content published in our journal. A journal our size also needs help with statistics, and we are excited that Nicholas has joined our team from the University of Toronto as Statistical Editor. We also have a new Editorial Director of Artificial Intelligence, Dr. Bredon Crawford. We are the first journal to feature an AI bot on our website, which is thanks to Dr. Crawford. Its name is “PJ” and you can find it on the bottom right of our website: www.pocusjournal.com. And finally, we are excited to have had Kathryn Matsushita join our team as , helping us preserve our standard of high quality publishing as the volume of submitted articles and size of our issues continues to grow. With the addition of these new members, I also share the bittersweet news that our Managing Editor Braeden Hill will be leaving POCUS Journal to pursue MD/PhD studies at The University of Toronto. started at POCUS Journal in 2020 as Social Media Editor and his contributions these past few years have been remarkable. We welcome Laura Guzman of Queen’s University into the role of Managing Editor. Every issue I oversee at POCUS Journal strikes me as better than the last, with fascinating cases and important research that answers key questions related to point of care ultrasound. This issue is no exception. Please find our author guidelines here: https://pocusjournal.com/author-guidelines/ Sincerely, Benjamin T. Galen, MD Department of Medicine, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY Editor-In-Chief POCUS Journal
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".