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Record W2314625983 · doi:10.1097/shk.0000000000000106

The Hemodynamic Response to Blood Loss in the Conscious Rat

2013· article· en· W2314625983 on OpenAlexaff
Brendan P. Troy, David A. Hopkins, Kevin A. Keay

Bibliographic record

VenueShock · 2013
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineGanglionectomyHemodynamicsAnesthesiaHaemodynamic responseCardiac outputVagus nerveHeart rateInternal medicineBlood pressurePathology

Abstract

fetched live from OpenAlex

The hemodynamic response to progressive blood loss passes through three distinct phases: an initial normotensive compensatory phase, a secondary hypotensive decompensatory phase, and a posthemorrhage recompensatory phase. The role of cardiac vagal and cardiac spinal signals in triggering the different phases of the response to hemorrhage was evaluated in the unanesthetized, freely moving rat by observing the effects on the response to 30% blood loss of prior cardiac vagal deafferentation (bilateral vagal rhizotomy) or prior cardiac spinal deafferentation (bilateral stellate ganglionectomy). In comparison to control animals, it was found that (i) cardiac spinal deafferentation significantly delayed the onset of the decompensatory phase, and (ii) cardiac vagal deafferentation slightly potentiated the decompensatory phase and impaired the recompensatory phase. These results indicate that it is cardiac spinal signals, rather than cardiac vagal signals, which in the conscious rat contribute to the triggering and progression of the decompensatory response to blood loss.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.245
Teacher spread0.238 · 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.

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

Citations13
Published2013
Admission routes1
Has abstractyes

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