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Record W2787525774 · doi:10.1139/cjz-2017-0249

American alligator (<i>Alligator mississippiensis</i>) embryos tightly regulate intracellular pH during a severe acidosis

2018· article· en· W2787525774 on OpenAlexaffvenue
Ryan B. Shartau, Dane A. Crossley, Zachary F. Kohl, Ruth M. Elsey, Colin J. Brauner

Bibliographic record

VenueCanadian Journal of Zoology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAlligatorHypercarbiaAmerican alligatorBiologyAcidosisIntracellular pHHypoxia (environmental)EmbryoTurtle (robot)Acid–base homeostasisAnatomyBiochemistryEndocrinologyCell biologyIntracellularChemistryOxygenEcology

Abstract

fetched live from OpenAlex

Crocodilian nests naturally experience high CO2(hypercarbia), which leads to increased blood Pco2and reduced blood pH (pHe) in embryos; their response to acid–base challenges is not known. During acute hypercarbia, snapping turtle embryos preferentially regulate tissue pH (pHi) against pHereductions. This is proposed to be associated with CO2tolerance in reptilian embryos and is not found in adults. In the present study, we investigated pH regulation in American alligator (Alligator mississippiensis (Daudin, 1802)) embryos exposed to 1 h of hypercarbia hypoxia (13 kPa Pco2, 9 kPa Po2). Hypercarbia hypoxia reduced pHeby 0.42 pH unit, while heart and brain pHiincreased, with no change in the pHiof other tissues. The results indicate that American alligator embryos preferentially regulate pHi, similar to snapping turtle embryos, which represents a markedly different strategy of acid–base regulation than what is observed in adult reptiles. These findings suggest that preferential pHiregulation may be a strategy of acid–base regulation used by embryonic reptiles.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.194
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 designObservational
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

Citations9
Published2018
Admission routes2
Has abstractyes

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