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Record W2085726813 · doi:10.4236/abb.2013.49114

Cytokine release in sepsis

2013· article· en· W2085726813 on OpenAlexaff
Ian Burkovskiy, Joel Sardinha, Juan Zhou, Christian H.K. Lehmann

Bibliographic record

VenueAdvances in Bioscience and Biotechnology · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSepsisMedicineIntensive care medicinePathophysiologyImmunologyImmune systemCytokinePathologicalBioinformaticsBiologyInternal medicine

Abstract

fetched live from OpenAlex

Despite the advances in the therapeutic approaches, health care protocols and policies, sepsis continues to be an important problem in clinical medicine. High lethality of sepsis cases calls for a detailed and critically important study of the pathophysiology of sepsis. In this review, we discuss pathomechanisms of sepsis and the role of cytokines that are released in sepsis. We propose that the systemic levels of cytokines are not always reflecting the pathological picture and the immune status of the patient. One of the emerging approaches which may bring an effective treatment strategy exploits the endocannabinoid system for its immunomodulatory properties. Following from that, the research in this particular field is very important as it can bring understanding behind the complicated pathophysiology of sepsis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.234
Teacher spread0.229 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations20
Published2013
Admission routes1
Has abstractyes

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