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Record W2409313926 · doi:10.1016/s1441-2772(23)02099-9

Sepsis research: where have we gone wrong?

2006· article· en· W2409313926 on OpenAlexaff
John C. Marshall

Bibliographic record

VenueCritical Care and Resuscitation · 2006
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsImpossibilityMedicineSepsisIntensive care medicineEconomic shortagePsychological interventionClinical trialDiseaseHost responseImmunologyNursingPathologyLaw

Abstract

fetched live from OpenAlex

Despite a strong biological rationale and no shortage of potential therapeutic targets, attempts to modulate the host response in sepsis over the past two decades have been profoundly disappointing. Even when efficacy has been demonstrated in clinical trials, the magnitude of benefit is small. The author argues that this results not from any intrinsic impossibility of treating sepsis as a disease, nor a lack of biologically efficacious interventions, but rather from shortcomings in three domains of clinical investigation - conceptual, methodological and organisational. (non-author abstract)

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)0.146
metaresearch head score (Gemma)0.257
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.854
Threshold uncertainty score0.774

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1460.257
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0070.008
Science and technology studies0.0060.030
Scholarly communication0.0260.046
Open science0.0060.010
Research integrity0.0240.035
Insufficient payload (model declined to judge)0.0110.008

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 head0.174
GPT teacher head0.445
Teacher spread0.271 · 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.

Study designTheoretical or conceptual
DomainMethods
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

Citations8
Published2006
Admission routes1
Has abstractyes

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