MétaCan
Menu
Back to cohort
Record W1995323572 · doi:10.1016/j.ejcts.2004.11.017

Reply to Sersar et al.

2004· article· en· W1995323572 on OpenAlexaff
FW Sellke, Marc Ruel

Bibliographic record

VenueEuropean Journal of Cardio-Thoracic Surgery · 2004
Typearticle
Languageen
FieldMedicine
TopicHematological disorders and diagnostics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

We agree that cardiopulmonary bypass activates the many plasma protein systems including those listed and certain blood cell types including platelets, neutrophils, monocytes, endothelial cells, and lymphocytes. We also agree that these changes, along with the numerous neurohumoral vasoactive substances that are released during CPB can have a marked effect on vasomotor tone and vascular permeability after cardiac surgery. These vascular changes can markedly affect the recover of patients after cardiac surgery. Our review of vasomotor dysfunction after cardiac surgery was not intended to be an exhaustive review of the etiology of all pathologic changes that occur during cardiac surgery, but rather briefly review the changes that occur in the regulation of vascular tone only. The pathologic processes leading to altered vascular tone and permeabilty are still relatively poorly understood. While some of the processes listed by Dr Sameh do undoubedly account for some of the vascular alterations observed, there is little definitive proof of this for all cases. It was hoped by many that off bypass (OPCAB) coronary revascularization might lessen the vasomotor changes that occur after cardiac surgery, but this in many cases this has not been observed. Because of a lack of definitive information regarding the cause of vascular changes after cardiac surgery, further investigation will be necessary to fully elucidate the answer. We appreciate your comments.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.041
GPT teacher head0.315
Teacher spread0.274 · 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 designNot applicable
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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Cardio-Thoracic SurgerySame topicHematological disorders and diagnosticsFrench-language works237,207