Bibliographic record
Abstract
From time to time, the JOGC will receive queries about submitting non-scientific content for publication. Members of industry and those in the medical community will sometimes ask about including small write-ups in our “magazine”, and authors will occasionally submit manuscripts that contain minimal data and/or express their opinion on specific topics with no supporting evidence. As the JOGC is a scientific journal, these sorts of submissions are not appropriate for our publication, even though they may be well written and factually sound. These types of manuscripts would be more appropriate for a newsletter. Indeed, there are distinct differences between the two types of publications. Scientific journals contain peer-reviewed articles with hard data that are measurable and objective. Medical journals, including the JOGC, play a key role in advancing medical knowledge and fostering evidence-based practice through the publication of original scholarly articles and practice guidelines. In contrast, newsletters do not provide rigorous evidence, are usually not peer-reviewed, and tend to present one-dimensional examination of a particular issue. They contain soft data and are often subjective based on author views and interpretations. Confusion may come from the fact that scientific journals and newsletters reach many readers with the same interests. And while newsletters might cite articles published in a scientific journal, the opposite is seldom true. By this definition, the JOGC is a scientific, medical journal, not a newsletter. It publishes research findings relevant to health care professionals, as well as academic and medical communities in general. Its priorities include publishing original research articles, preferably based on quantitative research, and systematic reviews or meta-analyses. Appropriate manuscripts containing results of a preliminary study that could lead to further investigation, or commentary on a recently published article in the JOGC, could be considered for publication as research letters. With the recent acquisition of an impact factor of 1.8, the JOGC is solidifying its status as an esteemed, scientific journal in the field of obstetrics and gynaecology. We invite authors to continue submitting high-quality, original papers. Once published, we will share work on our social networking platforms to enhance the exposure. Authors could also opt in to one of our Open Access publication options to boost reach, increase citations, and contribute to building the JOGC’s reputation as Canada’s national journal for obstetrics and gynaecology research.
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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.051 | 0.040 |
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".