Bibliographic record
Abstract
Dear Colleague, As the days go by, this quarter of the year is not only extremely hot but also very wet. In many areas of our land, there are huge landslides and grave floods bringing life to a standstill and causing an economic and environmental catastrophe. Hopefully, better days are soon to follow. The first article titled “Effect and clinical outcomes of vaccination in COVID-19-positive previous coronary revascularized patients” from Baku clearly demonstrates the value of coronavirus disease 2019 (COVID-19) vaccination in patients with prior coronary revascularization who later became COVID-19 positive. This is a must-read article. The second article from Srinagar, India, is again very timely. It is titled “Musculoskeletal disorders in patients on statin therapy: Prospective observational study in a tertiary care hospital” and is authored by Dr Dangroo et al. This is a good study on statin-associated muscle symptoms in 250 participants. As clinical cardiologists, we must listen to the patients’ complaints carefully and do relevant investigations, proper counseling, and if required, a change of medication. The third article is by Dr. Narendra Sreekanth Tirumala and colleagues from Kurnool, India, titled “Effect of bromocriptine on the left ventricular function in patients with peripartum cardiomyopathy: A single center prospective cohort study.” This is an interesting concept, albeit, on a small number of patients. The fourth study, titled “Assessment of self-monitoring of blood pressure among hypertensive patients in tertiary health care, northwestern Nigeria” from Gusau, Zamfara State, Nigeria, is a thought-provoking article. It shows how patients take even a simple thing like home blood pressure monitoring so casually. It is also a message to clinicians to probably spend more time to educate the patients. The fifth contribution “Raccoon eyes and heart failure” from Dr. AK Singhal and Dr. Raghav Bansal from the All India Institute of Medical Sciences, New Delhi, and Medanta, Gurugram, respectively, is again a reminder of the power of clinical examination, electrocardiography, and transthoracic echocardiography. A good read. The final contribution is a tribute to a great friend, humane physician, and a stalwart in echocardiography – Dr. Roberto M Lang – who recently breathed his last but will always be remembered for spearheading and spreading the art and science of echocardiography. So, dear reader, this issue is an interesting mix of clinical topics that we encounter in the day-to-day practice of cardiology. Do write back.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.159 | 0.101 |
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".