All you need to read in the other general journals
Bibliographic record
Abstract
Lancet2008, doi: 10.1016/S0140-6736(08)61121-6 Evidence of harms and benefits of epidural perioperative anaesthesia and analgesia in non-cardiac surgery has been going both ways. On one hand they provide better postoperative pain relief than parenteral opioid therapy, prevent lung related complications, and reduce the response to surgical stress, but on the other they are associated with rare but serious complications. A population based, retrospective, cohort study in Ontario, Canada, has looked into epidural anaesthesia’s effect on a new outcome—30 day postoperative mortality. The 259 037 participants, aged at least 40 years, underwent elective non-cardiac surgery of intermediate to high risk between 1994 and 2004. The researchers used propensity scores to match and compare people who had epidural anaesthesia or analgesia with those who did not. Epidural anaesthesia and analgesia were mildly protective: 1.7% of people who received such treatment died within 30 days of surgery, compared with 2.0% of people who did not (relative risk 0.89 (95% CI 0.81 to 0·98), P=0.02).⇑ The small absolute benefit (risk reduction of 0.2% with a number needed to treat of 477) doesn’t support the use of epidural anaesthesia or analgesia as a means of improving survival in people undergoing non-cardiac surgery. However, argue the authors, the study does support their safety when they are used for other reasons, such as postoperative pain control, when they also might confer a small survival benefit. JAMA2008;300:655-62 [OpenUrl][1][CrossRef][2][PubMed][3] Mental health interventions for children exposed to armed conflict are recognised as important parts of secondary prevention of adverse mental health outcomes. More such interventions are being implemented in conflict ridden regions, but few have been tested for effectiveness in controlled studies. In a theme issue of JAMA on violence and human rights, a new cluster randomised trial helps fill this knowledge … [1]: {openurl}?query=rft.jtitle%253DJAMA%26rft.stitle%253DJAMA%26rft.issn%253D0002-9955%26rft.aulast%253DTol%26rft.auinit1%253DW.%2BA.%26rft.volume%253D300%26rft.issue%253D6%26rft.spage%253D655%26rft.epage%253D662%26rft.atitle%253DSchool-Based%2BMental%2BHealth%2BIntervention%2Bfor%2BChildren%2BAffected%2Bby%2BPolitical%2BViolence%2Bin%2BIndonesia%253A%2BA%2BCluster%2BRandomized%2BTrial%26rft_id%253Dinfo%253Adoi%252F10.1001%252Fjama.300.6.655%26rft_id%253Dinfo%253Apmid%252F18698064%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1001/jama.300.6.655&link_type=DOI [3]: /lookup/external-ref?access_num=18698064&link_type=MED&atom=%2Fbmj%2F337%2Fbmj.a1338.atom
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 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.499 | 0.432 |
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".