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Record W1974357810 · doi:10.1080/10255842.2013.834894

Numerical model for intraosseous infusion of the human calvarium for hydrocephalus shunting

2013· article· en· W1974357810 on OpenAlexaff
Emeka Nzekwu, Marcela Louie, Daniel Scott, H. Lundgren, Jeff Pugh, Larry W. Kostiuk, Jason P. Carey

Bibliographic record

VenueComputer Methods in Biomechanics & Biomedical Engineering · 2013
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsCovenant HealthAlberta Health ServicesUniversity of Alberta
Fundersnot available
KeywordsCalvariaPorosityPermeability (electromagnetism)SkullCerebrospinal fluidShuntingHydrocephalusGeologyFluid pressureMaterials scienceFluid dynamicsMechanicsGeotechnical engineeringBiomedical engineeringMedicineChemistryPhysicsRadiologyPathologySurgery

Abstract

fetched live from OpenAlex

Hydrocephaly is the defective absorption of cerebrospinal fluid (CSF) into the blood stream. This work is an experimental and computational fluid dynamic modelling study to determine the permeability of the diploë as a potential receptor for CSF. Human calvariae were studied by micro-CT to measure their porosity, the area of flow and develop model geometry. Pressure-flow measurements were conducted on specimens to determine their permeability in the physiological and transverse flow directions to compare with numerical results. The overall porosity and permeability of the calvaria were spatially variable. Results suggest an order of magnitude increase in permeability for a 14% increase in overall porosity based on a small number of samples. Numerical results fell within the experimental infusion tests results. Due to the difficulty and ethical considerations in obtaining adolescent skull samples to perform large-scale testing, the developed model will be invaluable.

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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.326
Teacher spread0.293 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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