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Record W4398182665 · doi:10.1007/s00134-024-07369-9

European Society of Intensive Care Medicine clinical practice guideline on fluid therapy in adult critically ill patients. Part 1: the choice of resuscitation fluids

2024· article· en· W4398182665 on OpenAlexaff
Yaseen M. Arabi, Emilie P. Belley‐Côté, Andrea Carsetti, Daniel De Backer, Katia Donadello, Nicole P. Juffermans, Naomi Hammond, Jon Henrik Laake, Dawei Liu, Kathryn Maitland, Antonio Messina, Morten Hylander Møller, Daniele Poole, Rob Mac Sweeney, Jean‐Louis Vincent, Fernando G. Zampieri, Fayez Alshamsi

Bibliographic record

VenueIntensive Care Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineCritically illAnesthesiologyIntensive care medicineResuscitationGuidelinePain medicineIntensive careEmergency medicineAnesthesia

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

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)0.023
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 score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0040.002
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0030.004

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 head0.056
GPT teacher head0.394
Teacher spread0.338 · 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

Citations89
Published2024
Admission routes1
Has abstractno

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