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Record W4405434868 · doi:10.22489/cinc.2024.330

A Novel Computational Model of the Zebrafish Atrial Action Potential and Intracellular Calcium Transient

2024· article· en· W4405434868 on OpenAlexfundno aff
Zachary D. Long, Ludovica Cestariolo, J.M. Ferrero, Alex Quinn, José Félix Rodríguez Matas

Bibliographic record

VenueComputing in cardiology · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsnot available
FundersDalhousie University
KeywordsZebrafishCalcium in biologyTransient (computer programming)Computer scienceIntracellularCalciumAction (physics)ChemistryPhysicsBiochemistry

Abstract

fetched live from OpenAlex

The zebrafish has emerged as a valuable experimental model for studying cardiac electrophysiology and arrhythmias, yet there are no detailed computational models specific to its atrial action potential (AP) and intracellular calcium (Ca 2+ ) transient (CaT).We present a novel zebrafish-specific model, integrating experimental data from microelectrode and optical mapping recordings in the adult heart.We used a combination of experimental measurements and simulations to calibrate the model and validate it against additional experimental data.The model successfully reproduces experimentally observed atrial AP and CaT under various physiological conditions, offering a valuable tool for future work involving disease modelling, drug screening, and the investigation of cardiac arrhythmias.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.024
GPT teacher head0.281
Teacher spread0.256 · 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 designSimulation or modeling
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

Citations0
Published2024
Admission routes1
Has abstractyes

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