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Record W2940911396 · doi:10.1503/cmaj.180635

Enhanced recovery after surgery: implementing a new standard of surgical care

2019· review· en· W2940911396 on OpenAlexaffvenueabout
Alon D. Altman, Limor Helpman, Jacob McGee, Vanessa Samouëlian, Marie-Hélène Auclair, Harinder Brar, Gregg Nelson

Bibliographic record

VenueCanadian Medical Association Journal · 2019
Typereview
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsMcMaster UniversityUniversité de MontréalUniversity of British ColumbiaUniversity of ManitobaWestern University
Fundersnot available
KeywordsMedicineMultidisciplinary approachPerioperativeSurgeryComplication

Abstract

fetched live from OpenAlex

KEY POINTS Enhanced recovery after surgery (ERAS) is an evidence-based and multidisciplinary perioperative care pathway and a surgical quality improvement initiative, which has been shown to promote patient mobilization, reduce complication rates after surgery, decrease hospital length of stay and

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.095
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.019
GPT teacher head0.303
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations148
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Medical Association JournalSame topicEnhanced Recovery After SurgeryFrench-language works237,207