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Record W2963295242 · doi:10.1097/ogx.0000000000000696

Guidelines for Perioperative Care in Gynecologic/Oncology: Enhanced Recovery After Surgery (ERAS) Society Recommendations—2019 Update

2019· article· en· W2963295242 on OpenAlexaff
Gregg Nelson, Jamie N. Bakkum‐Gamez, Eleftheria Kalogera, Gretchen Glaser, Alon D. Altman, Larissa A. Meyer, Jolyn Taylor, Maria D. Iniesta, Javier Lasala, Gabriel E. Mena, Michael J. Scott, Chelsia Gillis, Kevin M. Elias, Lena Wijk, Jeffrey Huang, Jonas Nygren, Olle Ljungqvist, Pedro T. Ramírez, Sean C. Dowdy

Bibliographic record

VenueObstetrical & Gynecological Survey · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of ManitobaUniversity of Calgary
Fundersnot available
KeywordsMedicineGynecologic oncologyPerioperativeClinical OncologyGeneral surgeryIntensive care medicineGynecologyOncologyInternal medicineSurgeryCancer

Abstract

fetched live from OpenAlex

(Abstracted from Int J Gynecol Cancer 2019; doi: 10.1136/ijgc-2019-000356) Enhanced Recovery After Surgery (ERAS) is a global initiative dedicated to improving gynecologic/oncology surgical quality with attention to both clinical outcomes and economic impact. The ERAS guidelines, first published in February 2016, require updates on a regular basis in order to keep up with contemporary literature and evidence.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.359
Teacher spread0.300 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations17
Published2019
Admission routes1
Has abstractyes

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