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Record W1558163894 · doi:10.5772/19784

In Vitro Leukocyte Adhesion in Endothelial Tissue Culture Models Under Flow

2012· book-chapter· en· W1558163894 on OpenAlexaff
Scott Cooper, Melissa Dick, Alexander Emmott, Paul Jonak, Lonie Rouleau, L. Richard

Bibliographic record

VenueInTech eBooks · 2012
Typebook-chapter
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsMcGill University
Fundersnot available
KeywordsIn vitroAdhesionTissue cultureCell biologyImmunologyChemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

Atherosclerosis, an inflammatory disease which causes thickening and stiffening of arteries, is a major cause of death in the United States (Lloyd-Jones et al., 2010). These deaths occur because of vessel occlusion created by atherosclerotic plaques and thrombus shedding, leading to heart attack, ischemia, or stroke. Atherosclerosis is expected to be the leading cause of death worldwide within 10 years (Lloyd-Jones et al., 2010). Inflammation plays a significant role in the initiation and progression of atherosclerosis. The cells that line the arteries, endothelial cells (ECs), mediate the inflammatory process. The forces created by blood flow affect the inflammatory response of ECs and the interaction with blood components. This chapter summarizes the background in our recent studies on the response of ECs to blood forces and the interaction of inflammatory cells.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.525
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.291
Teacher spread0.254 · 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 designBench or experimental
Domainnot available
GenreOther

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

Citations2
Published2012
Admission routes1
Has abstractyes

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