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Record W1847611437 · doi:10.3791/52581

Instrumentation of Near-term Fetal Sheep for Multivariate Chronic Non-anesthetized Recordings

2015· article· en· W1847611437 on OpenAlexafffund
Patrick Burns, Hai Lun Liu, Shikha Kuthiala, Gilles Fecteau, André Desrochers, Lucien Daniel Durosier, Mingju Cao, Martin G. Frasch

Bibliographic record

VenueJournal of Visualized Experiments · 2015
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsMedicineFetusUmbilical cordHypothermiaAnesthesiaHypoxia (environmental)In vivoBlood samplingChorioamnionitisBiologyPregnancyInternal medicineImmunology

Abstract

fetched live from OpenAlex

The chronically instrumented pregnant sheep has been used as a model of human fetal development and responses to pathophysiologic stimuli such as endotoxins, bacteria, umbilical cord occlusions, hypoxia and various pharmacological treatments. The life-saving clinical practices of glucocorticoid treatment in fetuses at risk of premature birth and the therapeutic hypothermia have been developed in this model. This is due to the unique amenability of the non-anesthetized fetal sheep to the surgical placement and maintenance of catheters and electrodes, allowing repetitive blood sampling, substance injection, recording of bioelectrical activity, application of electric stimulation and in vivo organ imaging. Here we describe the surgical instrumentation procedure required to achieve a stable chronically instrumented non-anesthetized fetal sheep model including characterization of the post-operative recovery from blood gas, metabolic and inflammation standpoints.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.046
GPT teacher head0.432
Teacher spread0.386 · 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

Citations17
Published2015
Admission routes2
Has abstractyes

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