Neostigmine improved acute colonic pseudo-obstruction quickly and effectively
Bibliographic record
Abstract
TherapeuticsJanuary 1, 2000Neostigmine improved acute colonic pseudo-obstruction quickly and effectivelySander Veldhuyzen van Zanten, MD, PhDSander Veldhuyzen van Zanten, MD, PhDVictoria General Hospital, Halifax, Nova Scotia, Canada (S.V.V.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/ACPJC-2000-132-1-019 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareFacebookTwitterLinkedInRedditEmail Source CitationPonec RJ, Saunders MD, Kimmey MB. Neostigmine for the treatment of acute colonic pseudo-obstruction. N Engl J Med. 1999;341:137-41. https://pubmed.ncbi.nlm.nih.gov/10403850References1 Rex DK. Colonoscopy and acute colonic pseudo-obstruction. Gastrointest Endosc Clin N Am. 1997;7:499-508. [PMID: 9177149] Google Scholar2 Laine L. Management of acute colonic pseudo-obstruction. N Engl J Med. 1999;341:192-3. [PMID: 10403858] Google Scholar Author, Article, and Disclosure InformationAffiliations: Victoria General Hospital, Halifax, Nova Scotia, Canada (S.V.V.) PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails January 1, 2000Volume 132, Issue 1Page: 19KeywordsAbdominal painAtropineBlood pressureBradycardiaCecumColonColonoscopyCreatinineDrugsHeart rateSystolic pressure ePublished: 9 March 2020 Issue Published: January 1, 2000 Copyright & PermissionsCopyright © 2000 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".