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Record W4286851894 · doi:10.3791/55261-v

Neurodevelopmental Reflex Testing in Neonatal Rat Pups

2017· article· en· W4286851894 on OpenAlexaff
Antoinette T. Nguyen, Edward A. Armstrong, Jerome Y. Yager

Bibliographic record

VenueJournal of Visualized Experiments · 2017
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsReflexCerebral palsyMedicineGuidelineNeurosciencePediatricsPsychologyPhysical medicine and rehabilitationPathology

Abstract

fetched live from OpenAlex

Neurodevelopmental reflex testing is commonly used in clinical practice to assess the maturation of the nervous system. Neurodevelopmental reflexes are also referred to as primitive reflexes. They are sensitive and consistent with later outcomes. Abnormal reflexes are described as an absence, persistence, reappearance, or latency of reflexes, which are predictive indices of infants that are at high risk for neurodevelopmental disorders. Animal models of neurodevelopmental disabilities, such as cerebral palsy, often display aberrant developmental reflexes, as would be observed in human infants. The techniques described assess a variety of neurodevelopmental reflexes in neonatal rats. Neurodevelopmental reflex testing offers the investigator a testing method that is not otherwise available in such young animals. The methodology presented here aims to assist investigators in examining developmental milestones in neonatal rats as a method of detecting early-onset brain injury and/or determining the effectiveness of therapeutic interventions. The methodology presented here aims to provide a general guideline for investigators.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.075
GPT teacher head0.452
Teacher spread0.377 · 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 teacher head, 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

Citations30
Published2017
Admission routes1
Has abstractyes

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