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Record W2120456806 · doi:10.1017/s002221511300265x

Hearing outcome of early postnatal exposure to hypoxia in Sprague–Dawley rats

2014· article· en· W2120456806 on OpenAlexaff
Sam J. Daniel, Matthew McIntosh, Olubunmi V. Akinpelu, Charles Rohlicek

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2014
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsMcGill UniversityMcGill University Health CentreMontreal Children's Hospital
Fundersnot available
KeywordsAuditory brainstem responseHypoxia (environmental)BrainstemAbnormalityMedicineAudiologyHearing lossInternal medicineAnimal modelEndocrinologyAnesthesiaChemistryOxygen

Abstract

fetched live from OpenAlex

Abstract Objective: To determine the effect of experimentally induced hypoxia, in the first 10 days of life, on physiological hearing in a Sprague–Dawley rat model. Methods: A prospective, controlled animal study was carried out using 22 male rat pups. The rats in the hypoxic group (n = 12) were reared in hypoxia for the first 10 days of life, and subsequently reared in normoxia, while those in the control group (n = 10) were reared in normoxia for the duration of the experiment. Hearing was assessed using auditory brainstem response testing at approximately 72 days of age. Results: The hypoxia group had higher auditory brainstem response thresholds for all frequencies tested (more pronounced at 16 kHz), compared with controls. Wave I–V inter-peak latencies were more prolonged in the hypoxic rats, while both groups had similar wave I latencies. Conclusion: Chronic postnatal hypoxia induced permanent hearing loss in this Sprague–Dawley rat model. Prolonged wave I–V inter-peak latencies suggested functional abnormality in the central auditory pathway.

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 score0.001
Threshold uncertainty score0.004

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 integrity0.0000.001
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 head0.022
GPT teacher head0.285
Teacher spread0.263 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

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