MétaCan
Menu
Back to cohort
Record W1965743895 · doi:10.1016/j.ijoa.2013.01.001

A meta-analysis of the effect of inspired oxygen concentration on the incidence of surgical site infection following cesarean section

2013· review· en· W1965743895 on OpenAlexaff
Michelle Klingel, Sunil V. Patel

Bibliographic record

VenueInternational Journal of Obstetric Anesthesia · 2013
Typereview
Languageen
FieldMedicine
TopicSurgical site infection prevention
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineIncidence (geometry)Surgical site infectionSection (typography)Meta-analysisAnesthesiaObstetricsSurgeryInternal medicineOptics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: aff_core · design weight: 5595.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: high

Meta-analysis answering a clinical question about oxygen concentration and surgical site infection; a synthesis method used, not studied.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

This meta-analysis answers a clinical question about surgical-site infection after cesarean section rather than studying synthesis methodology.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Meta-analysis answering a clinical SSI/cesarean oxygen question; uses synthesis, does not study it.

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)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.036
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.057
GPT teacher head0.339
Teacher spread0.281 · 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.

Study designMeta-analysis
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

Citations26
Published2013
Admission routes1
Has abstractno

Explore more

Same venueInternational Journal of Obstetric AnesthesiaSame topicSurgical site infection preventionFrench-language works237,207