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Record W2031291407 · doi:10.1177/1753465808088903

Review: Surfactant protein D: A lung specific biomarker in COPD?

2008· review· en· W2031291407 on OpenAlexafffund
Don D. Sin, Payam S. Pahlavan, S. F. Paul Man

Bibliographic record

VenueTherapeutic Advances in Respiratory Disease · 2008
Typereview
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsSt. Paul's Hospital
FundersCanada Research ChairsMichael Smith Health Research BC
KeywordsMedicineCOPDBiomarkerPulmonary surfactantLungSurfactant protein AIntensive care medicineInternal medicineChemical engineeringBiochemistry

Abstract

fetched live from OpenAlex

A major impediment in the development of novel drugs for chronic obstructive pulmonary disease (COPD) has been the scarcity of a well-validated, robust, and easily obtainable intermediate end point such as serum biomarkers. To date the best serum biomarkers in COPD have been non-speci"c pro-in"ammatory molecules synthesized largely by extra-pulmonary organs. In COPD, an ideal biomarker would be one that (1) was produced mostly in the lungs (and was reliably measurable in the peripheral circulation using commercially available kits), (2) changed with the clinical status of patients or with relevant exposures; and (3) had inherent functional attributes that suggested a possible causal role in the pathogenesis of the disease. In this paper, we review one promising systemic biomarker that ful"lls some of these criteria, surfactant protein D (SPD).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.841
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.132
GPT teacher head0.463
Teacher spread0.331 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations57
Published2008
Admission routes2
Has abstractyes

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