MétaCan
Menu
Back to cohort
Record W1991721421 · doi:10.1089/sur.2009.9930

Diagnosis and Management of Complicated Intra-Abdominal Infection in Adults and Children: Guidelines by the Surgical Infection Society and the Infectious Diseases Society of America

2010· article· en· W1991721421 on OpenAlexaff
Joseph S. Solomkin, John E. Mazuski, John S. Bradley, Keith A. Rodvold, Ellie J. C. Goldstein, Ellen Jo Baron, Patrick J. O’Neill, Anthony W. Chow, E. Patchen Dellinger, Soumitra R. Eachempati, Sherwood L. Gorbach, Mary Hilfiker, Addison K. May, Avery B. Nathens, Robert G. Sawyer, John G. Bartlett

Bibliographic record

VenueSurgical Infections · 2010
Typearticle
Languageen
FieldMedicine
TopicAppendicitis Diagnosis and Management
Canadian institutionsSt. Michael's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineGuidelinePediatric Infectious DiseaseSurgical InfectionsEnterocolitisNecrotizing enterocolitisIntensive care medicineGeneral surgeryAppendicitisPediatricsInternal medicinePathologyAntibiotics

Abstract

fetched live from OpenAlex

Evidence-based guidelines for managing patients with intra-abdominal infection were prepared by an Expert Panel of the Surgical Infection Society and the Infectious Diseases Society of America. These updated guidelines replace those previously published in 2002 and 2003. The guidelines are intended for treating patients who either have these infections or may be at risk for them. New information, based on publications from the period 2003-2008, is incorporated into this guideline document. The panel has also added recommendations for managing intra-abdominal infection in children, particularly where such management differs from that of adults; for appendicitis in patients of all ages; and for necrotizing enterocolitis in neonates.

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)0.003
metaresearch head score (Gemma)0.010
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.293
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.

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

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

Citations631
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSurgical InfectionsSame topicAppendicitis Diagnosis and ManagementFrench-language works237,207