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Record W2008888466 · doi:10.1186/cc14053

Diagnostic and prognostic evaluation of soluble CD14 subtype for sepsis in critically ill patients: a preliminary study

2014· article· en· W2008888466 on OpenAlexfundno aff
Alfredo Focà, Cinzia Peronace, Vito Marano, GS Barreca, AG Lamberti, Nadia Marascio, Aldo Giancotti, R Puccio, Liberto Mc

Bibliographic record

VenueCritical Care · 2014
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsnot available
FundersChildren's Health FoundationConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa e Inovação do Estado de Santa CatarinaFinanciadora de Estudos e ProjetosCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorJapan Society for the Promotion of ScienceRussian Foundation for Basic ResearchLondon Health Sciences Centre
KeywordsProcalcitoninSepsisMedicineCD14Critically illIntensive care medicineImmunologyInternal medicineBioinformaticsBiologyImmune system

Abstract

fetched live from OpenAlex

Sepsis, a leading cause of death in critical care patients, is the result of complex interactions between the infecting microorganisms and the host responses that influence clinical outcomes [ 1 ]. Reliable biochemical markers that enable early diagnosis are still needed. A new marker, presepsin (soluble CD14 subtype, sCD14-ST) is a circulating fragment of 13 kDa of soluble CD14 that originates from the cleavage of the CD14 expressed on the surface membranes of monocytes/macrophages. sCD14-ST has been shown to increase significantly in patients with sepsis [ 2 ]. In our study we compare diagnostic performance of presepsin, C-reactive protein (CRP) and procalcitonin (PCT).

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.081
GPT teacher head0.391
Teacher spread0.310 · 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 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

Citations24
Published2014
Admission routes1
Has abstractyes

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