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Record W4399464286 · doi:10.1016/j.xpro.2024.103025

Protocol to optimize the Rice-Vannucci rat pup model of perinatal asphyxia to ensure predictable hypoxic-ischemic cerebral lesions

2024· article· en· W4399464286 on OpenAlexfundno aff
Jitka Ourednik, Václav Ourednik, Nirmalya Ghosh, Evan Y. Snyder

Bibliographic record

VenueSTAR Protocols · 2024
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsnot available
FundersCerebral Palsy AllianceCerebral Palsy Alliance Research FoundationOntario Ministry of Research, Innovation and ScienceCalifornia Institute for Regenerative Medicine
KeywordsLigationHypoxia (environmental)Rat modelMedicineAsphyxiaCarotid arteriesPerinatal asphyxiaAnesthesiaIschemiaCardiologySurgeryInternal medicineChemistryOxygen

Abstract

fetched live from OpenAlex

The Rice-Vannucci model in rodent pups is subject to substantial loss of animals, result inconsistency, and high lab-to-lab variability in extent and composition of induced injury. This protocol allows for highly predictable and reproducible hypoxic-ischemic cerebral injury lesions in post-natal day 10 Wistar rat pups with no mortality. We describe steps for common carotid artery ligation, brief post-operative normothermia, exposure to hypoxia, and post-hypoxic normothermia. Precise timing and temperature control in each step are crucial for a successful procedure. For complete details on the use and execution of this protocol, please refer to Hartman et al.1

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)0.001
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: Protocol · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0180.006

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 head0.037
GPT teacher head0.334
Teacher spread0.297 · 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
GenreProtocol

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

Citations3
Published2024
Admission routes1
Has abstractyes

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