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Record W1980022263 · doi:10.3791/50994

<em>In utero</em> Measurement of Heart Rate in Mouse by Noninvasive M-mode Echocardiography

2013· article· en· W1980022263 on OpenAlexafffund
Woo-Jin Kim, Nabil G. Seidah, Annik Prat

Bibliographic record

VenueJournal of Visualized Experiments · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsMontreal Clinical Research Institute
FundersCanadian Institutes of Health Research
KeywordsIn uteroMedicineHeart diseaseHeart failureCardiologyDiseaseEtiologyInternal medicinePhysiologyPregnancyFetusBiology

Abstract

fetched live from OpenAlex

Congenital heart disease (CHD) is the most frequent noninfectious cause of death at birth. The incidence of CHD ranges from 4 to 50/1,000 births (Disease and injury regional estimates, World Health Organization, 2004). Surgeries that often compromise the quality of life are required to correct heart defects, reminding us of the importance of finding the causes of CHD. Mutant mouse models and live imaging technology have become essential tools to study the etiology of this disease. Although advanced methods allow live imaging of abnormal hearts in embryos, the physiological and hemodynamic states of the latter are often compromised due to surgical and/or lengthy procedures. Noninvasive ultrasound imaging, however, can be used without surgically exposing the embryos, thereby maintaining their physiology. Herein, we use simple M-mode ultrasound to assess heart rates of embryos at E18.5 in utero. The detection of abnormal heart rates is indeed a good indicator of dysfunction of the heart and thus constitutes a first step in the identification of developmental defects that may lead to heart failure.

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: Methods · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.007

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 head0.024
GPT teacher head0.366
Teacher spread0.342 · 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
GenreMethods

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
Published2013
Admission routes2
Has abstractyes

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