MétaCan
Menu
Back to cohort
Record W2019760565 · doi:10.3389/fphys.2011.00063

The Genetic Component of the Forced Diving Bradycardia Response in Mammals

2011· article· en· W2019760565 on OpenAlexafffund
Andreas Fahlman, Brian L. Bostrom, Kiran H. Dillon, David R. Jones

Bibliographic record

VenueFrontiers in Physiology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBradycardiaComponent (thermodynamics)BiologyHeart rateEndocrinology

Abstract

fetched live from OpenAlex

We contrasted the forced diving bradycardia between two genetically similar (inbred) rat strains (Fischer and Buffalo), compared to that of outbred rats (Wistar). The animals were habituated to forced diving for 4 weeks. Each animal was then tested during one 40 s dive on each of 3 days. The heart rate (f(H)) was measured before, during, and after each dive. Fischer and Buffalo exhibited marked difference in dive bradycardia (Fischer: 120.9 ± 14.0 beats min(-1) vs. Buffalo: 92.8 ± 12.8 beats min(-1), P < 0.05). Outbred rats showed an intermediate response (103.0 ± 30.9 beats min(-1)) but their between-animal variability in mean dive f(H) and pre-diving resting f(H) were higher than the inbred strains (P < 0.05), which showed no difference (P > 0.05). The decreased variability in f(H) in inbred rats as compared with the outbred group indicates that reduced genetic variability minimizes variability of the diving bradycardia between individuals. Heritability within strains was assessed by the repeatability (R) index and was 0.93 ± 0.05 for the outbred, 0.84 ± 0.16 for Buffalo, and 0.80 ± 0.12 for Fischer rats for f(H) during diving. Our results suggest that a portion of the mammalian diving bradycardia may be a heritable trait.

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)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.015
GPT teacher head0.201
Teacher spread0.186 · 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

Citations17
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in PhysiologySame topicPhysiological and biochemical adaptationsFrench-language works237,207