Bibliographic record
Abstract
The GB at ESICON 2016 entrusted me to take on the reins of the Indian Journal of Endocrinology and Metabolism. And I am deeply thankful. THE PAST IJEM has come a long way since its humble beginnings. The current Editorial Board is fortunate to have inherited the Journal in reasonable health and salutes the efforts of the previous Editorial teams; it also acknowledges the hand-holding by the outgoing Executive Editor Dr AG Unnikrishnan for almost 8 months. THE PRESENT There are several reasons for the members of Endocrine Society of India to be happy about their journal: Predictable bimonthly publication in both print and online versions The journal is indexed with, or included in, the following: DOAJ, Index Copernicus, Indian Science Abstracts, IndMed, PubMed Central, Scimago Journal Ranking, SCOPUS Obviously our primary focus is to highlight and showcase endocrine research in India; but we can be proud that 17% of manuscript submissions for 2017 have come from outside India A moderate rejection rate of around 45% over the years A steady increase in visibility, as evidenced by the increase in citations, especially over the last 2 years. Also, analysis of visitors to the journal website shows significant interest from the USA, UK, Canada, Australia, China, Brazil, Indonesia, South Korea and Egypt. THE FUTURE A crucial part in peer-reviewed journals is played by its Reviewers. I am honestly thankful to all those who respond on time; from personal experience I can well appreciate when some of you are unable to keep to our rather tight timelines. I hope to see a drop in the current non-response rate of Reviewers from around 30%, which would translate into shorter turn-around time for an article. We are working on the possibility of increasing the frequency of publication, so that you get it every month. A felt-need is to set ourselves up for getting an Impact Factor for IJEM. We hope to add flavor to the journal by adding regular sections like ‘Visual Vignette’ and ‘Lessons Learnt’. Additionally we hope to revamp the International Advisory Board. We also need to streamline the process within our system, with greater involvement of the Associate Editors. We are extremely proud of the growing pool of wise and talented Endocrinologists in our country. I appeal to all members, especially the younger generation, to provide inputs for improvements of IJEM; you can do so personally at ESICON 2017 or by emailing me ([email protected]) or, the Executive Editor Dr Sujoy Ghosh ([email protected]). Above all, please do consider IJEM your preferred destination to publish anything related to Endocrinology, whether clinical or, basic science-related. Long live Endocrine Society of India and a robust future for IJEM! “The past may dictate who we are, but we get to determine what we become” — Unknown
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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.010 | 0.020 |
| Insufficient payload (model declined to judge) | 0.215 | 0.178 |
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".