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Record W4200427037 · doi:10.33774/miir-2021-0lpf2

Investigating Fontan Failure Using Mathematical Modeling

2021· preprint· en· W4200427037 on OpenAlexaff
Matthew G. Doyle, Ferran Brosa Planella, Jen Bryson, Brooks Emerick, Daniel Fong, Casey Johnson, Ayşe Kabataş, Greg Murphy, Tracy L. Stepien, Isaac Tate

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsFontan procedureMedicineCardiologyHeart failureInternal medicineVentricleHemodynamics

Abstract

fetched live from OpenAlex

Babies born with a single functioning heart ventricle instead of two require a series of surgeries during the first few years of life to redirect their blood flow, resulting in a Fontan circulation. Patients with Fontan circulations have excellent early survival; however, over time, their circulations begin to fail, ultimately resulting in their death. Currently, the only treatment for failing Fontan circulation is a heart transplant; however, many Fontan patients do not survive long enough to receive a donor heart. One of the reasons for this is a lack of understanding of the Fontan failure cascade. Often patients are identified as failing when they do not have enough time left to receive a heart transplant. The objective of this problem is to develop mathematical models of healthy and failing Fontan circulations to i) improve our understanding of Fontan failure from a hemodynamic perspective, and ii) identify physiologically-relevant ranges of parameters.

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)0.004
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: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.090
GPT teacher head0.342
Teacher spread0.252 · 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
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

Citations0
Published2021
Admission routes1
Has abstractyes

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