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Record W2013054294 · doi:10.1002/ebch.168

Three commentaries on ‘Corticosteroids for treating dengue shock syndrome’, with introduction by EBCH editor

2007· article· en· W2013054294 on OpenAlexaff
Joan Robinson, Bridget Wills, Scott B. Halstead, Joseph L. Mathew

Bibliographic record

VenueEvidence-Based Child Health A Cochrane Review Journal · 2007
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineSystematic reviewCochrane collaborationDengue feverShock (circulatory)Intensive care medicineAlternative medicinePathologyInternal medicineMEDLINEPolitical scienceCochrane LibraryLaw

Abstract

fetched live from OpenAlex

Abstract This is a commentary on a Cochrane review, published in this issue of EBCH, first published as: Panpanich R, Sornchai P, Kanjanaratanakorn K. Corticosteroids for treating dengue shock syndrome. Cochrane Database of Systematic Reviews 2006, Issue 3. Art. No.: CD003488. DOI: 10.1002/14651858.CD003488.pub2. Further information for this Cochrane review is available in this issue of EBCH in the accompanying EBCH Summary and Characteristics and Key Findings Tables articles. Copyright © 2007 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd. The Cochrane Collaboration

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)0.056
metaresearch head score (Gemma)0.319
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.056
Threshold uncertainty score0.295

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0560.319
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0050.006
Science and technology studies0.0050.005
Scholarly communication0.0070.010
Open science0.0080.005
Research integrity0.0440.040
Insufficient payload (model declined to judge)0.0170.006

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 head0.020
GPT teacher head0.339
Teacher spread0.319 · 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
GenreCommentary

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

Citations2
Published2007
Admission routes1
Has abstractyes

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