MétaCan
Menu
Back to cohort
Record W4366594403 · doi:10.21203/rs.3.rs-2828854/v1

Three-dimensional electrical impedance tomography (EIT) to study regional ventilation/perfusion (V/Q ) ratios in anesthetized pigs

2023· preprint· en· W4366594403 on OpenAlexaff
Shannon Larrabee, Sarah Nugen, Alejandro Bruhn, Symon Stowe, Andy Adler, Manuel Martin‐Flores, Joaquín Araos

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldEngineering
TopicElectrical and Bioimpedance Tomography
Canadian institutionsCarleton University
FundersCollege of Veterinary Medicine, Cornell University
KeywordsElectrical impedance tomographyPerfusionTomographyNuclear medicinePhysicsGold standard (test)Ventilation (architecture)High resolutionMedicineGeologyCardiologyRadiologyOptics

Abstract

fetched live from OpenAlex

Abstract This study aimed to develop a 3D method for assessing V/Q̇ ratios in a pig model of hemodynamic perturbations using electrical impedance tomography (EIT). In order to evaluate whether the physiological coherence of changes in EIT-derived V/Q̇ ratios, global EIT-derived V/Q̇ mismatch were compared with global gold-standards. The study found regional heterogeneity in the distribution of V/Q̇ ratios in both the ventrodorsal and craniocaudal directions. Although global EIT-derived indices of V/Q̇ mismatch consistently underestimated both low and high V/Q̇ mismatch compared to global gold standards, the direction of the change was similar. We have made the software available at no cost for other researchers to use. Future studies should compare regional V/Q̇ ratios determined by our method against other regional, high-resolution methods such as SPECT or PET scan.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.345
Teacher spread0.291 · 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
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueResearch SquareSame topicElectrical and Bioimpedance TomographyFrench-language works237,207