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Record W1967953145 · doi:10.1159/000120808

Computer Modeling of Siphoning for CSF Shunt Design Evaluation

2008· article· en· W1967953145 on OpenAlexaff
James M. Drake, G. Tenti, S. Sivalsganathan

Bibliographic record

VenuePediatric Neurosurgery · 2008
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsShunt (medical)Cerebrospinal fluidMedicineIntracranial pressureHydrocephalusCompartment (ship)Cerebrospinal fluid pressureBiomedical engineeringSurgeryInternal medicine

Abstract

fetched live from OpenAlex

A computer model of the cerebrospinal fluid (CSF) compartment and various shunt designs was developed to simulate CSF dynamics, particularly in the upright position in which siphoning is known to occur. This novel mathematical model of the CSF compartment incorporates negative pressure and volume components that permit simulation of siphoning. The model was tested with data from a previously reported animal experiment. The correspondence between the model simulation and the reported intracranial pressure and CSF shunt flow rate was very good. A simulation of a shunted hydrocephalic patient in the recumbent and upright position was then carried out to examine the effects of a standard shunt valve, an externally adjustable valve, a variable resistance valve, and an antisiphon device. The resulting pressure profiles, which conformed to previously reported data, indicate that this model would be useful for the evaluation of current and future shunt designs.

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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.121
GPT teacher head0.290
Teacher spread0.169 · 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

Citations29
Published2008
Admission routes1
Has abstractyes

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