Bibliographic record
Abstract
Confused? Not sure where you are? Don't worry. You're still reading Medical Education. This is just a new format. Really. Take a look at the bottom of the page… it's right there in black type (if you're viewing the PDF): Medical Education. 2020;54. Whimsy aside, it would be completely understandable if the change is a little unsettling. We've tweaked a number of style components in recent years, but it has been ages since we altered anything as dramatically as this. Medical Education has been branded in a particular way that makes it easily recognisable and, to tell the truth, I personally prefer the previous design. So, why change what has worked for so long? First, it's arguably as good for journals as it is for education practice to shake things up every now and then.1 Despite my having had the same haircut for 25 years (although there's now less to cut), I don't think everything should be as static. Second, the publishing industry is moving increasingly towards a web-first ecosystem in which priority is given to tailoring material for online or device-based reading habits. Over time we have seen growing proportions of readers choose HTML over PDF format and recent numbers indicate that almost 60% of users now prefer HTML. Thus, although we are not eliminating the PDF format and will thereby continue to support the 40%, it seems sensible to shift investment in continued development in a manner that aligns with readers' behaviour, which includes formatting in a manner that more easily aligns with HTML presentations. Third, and most importantly, by changing to a standard used by our publisher (Wiley), we can make production more efficient. Having a unique style means that the journal takes more effort to typeset and data from Wiley's other journals suggest that turnaround times for the average article were reduced by 15-20% when the new streamlined design was introduced. In other words, by changing our format we are able to get authors’ words into readers’ minds more quickly. I'll be the first to admit to hesitation over such a wholesale change. I like how easily recognisable the source journal is when I encounter new articles. However, in keeping with the spirit of the issue in which this editorial is published, in which we scrutinise our mythology,2 it is noteworthy that business leaders have begun to question whether or not branding matters as much as it once did.3 I'll also admit that the new style has been growing on me as I have become more familiar with it; as such, I don't think it will be long before the new look feels as normal and appealing as the old. Wish I could say the same about my hair.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.020 | 0.018 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.238 | 0.144 |
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".