Bibliographic record
Abstract
By Giovanni Marchegiani, BJS Editor Assistant In January, @bjsurgery generated 244 400 impressions, 201 retweets and 407 likes, and gained 440 new followers. The tweet with the highest number of engagements from the BJS account, with over 15 087 impressions, was from the BJS Cutting Edge blog about ‘Angst among surgeons during the COVID-19 crisis’, on behalf of S-COVID Collaborative Group. The second tweet with most engagement (14 400 impressions) was about a recently published original article, the PREDICT Study by Stephensen et al., assessing the role of C‐reactive protein trajectory to predict colorectal anastomotic leak.1 The top tweet mentioning BJS was from @JlRodicio, about the virtual congress of the SEIQ (Sociedad Espanola de Investigaciones Quirurgicas) which will be held on the 11th-12th March (abstracts from the congress will be published in BJS). During the month of January, the BJS twitter account also ranked the five papers with the top Altmetric scores published on the last 6 months.2–6 The five tweets generated a total of 40 000 impressions. Of note, three out of five top-ranking articles were COVID-related2,4,6, including the one with the highest Altmetric score of 256, by the COVIDSurg Collaborative, on delaying surgery for patients with a previous SARS-CoV-2 infection2. The visual abstract posted about the 5-year outcomes of merged data from two randomized clinical trials on laparoscopic Roux-en-Y gastric bypass versus laparoscopic sleeve gastrectomy (SLEEVEPASS and SM-BOSS)7 reached a total of 24 847 impressions and 862 engagements, being the fifth top tweet from @bjsurgery this month. Donohue and Mohan’s paper on pregnancy, parenthood and second-generation bias8 in surgery was extremely popular, with @MarinaYLeft saying ‘As a mum and a surgeon [it] is great to see this article in @BJSurgery. It's not one or the other anymore’. The BJS workshop at ASIT on how to write a conference abstract moved online this year, and despite this change, it remained very popular, with over 175 people dialled in to the webinar.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.831 | 0.797 |
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".