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Renal responses to severe haemorrhage in conscious lambs

2012· article· en· W3173428438 on OpenAlexafffundabout
Francine G. Smith, Mohamed Samhan, Qi Wei

Bibliographic record

VenueThe FASEB Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsRenal functionRenal blood flowMedicineUrinary systemInternal medicineUrologyEndocrinology

Abstract

fetched live from OpenAlex

The role of the kidney in the physiological responses to severe degrees of haemorrhage beyond which compensatory mechanisms fail (>25% of vascular volume) has not been investigated in the newborn period. In this study, parameters of glomerular and tubular function were measured for 30 min before (Control, C) and 120 min after haemorrhage of 30% of vascular volume, in conscious, chronically instrumented lambs aged ~one (N=10) and ~six weeks (N=9). Renal plasma flow decreased 30 min after haemorrhage from 1.4±0.5 SD (C) to 0.7±0.2 mL.min −1 .g −1 at one week and from 1.6±0.4 (C) to 0.9±0.4 mL.min −1 .g −1 at six weeks and remained decreased at 120 min. Similarly, glomerular filtration rate decreased from 0.26±0.08 (C) to 0.18±0.14 mL.min −1 .g −1 at one week and from 0.31±0.08 (C) to 0.17±0.08 mL.min −1 .g −1 at six weeks, and remained below C at 120 min. Urinary flow rate also decreased from 3.8±1.6 (C) to 1.8±0.7 uL.min −1 .g −1 by 30 min after haemorrhage at one week and from 3.9±1.5 (C) to 2.2±0.8 uL.min −1 .g −1 at six weeks, and remained below C at 120 min. Clearances of Na + and K + also decreased after haemorrhage in both age groups. These data provide evidence that soon after birth, glomerular and tubular responses to severe blood loss are elicited, though they do not appear to be developmentally regulated. [Supported by the Canadian Institutes of Health Research.]

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.306
Teacher spread0.270 · 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

Citations0
Published2012
Admission routes3
Has abstractyes

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