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Record W2075874061 · doi:10.1109/mecbme.2014.6783242

Effect of remodeled tumor-induced capillary network on interstitial flow in cancerous tissue

2014· article· en· W2075874061 on OpenAlex
Mostafa Sefidgar, Kaamran Raahemifar, Hossein Bazmara, Majid Bazargan, Mohammad Mousavi, M. Soltani

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicMathematical Biology Tumor Growth
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsInterstitial fluidCapillary actionBlood flowFlow (mathematics)Interstitial spaceDrug deliveryBiomedical engineeringFluid dynamicsAdaptabilityMaterials scienceChemistryPathologyMechanicsMedicineInternal medicineBiologyPhysicsNanotechnology

Abstract

fetched live from OpenAlex

Interstitial fluid flow has been studied by many cancer researchers for investigation on the effect of interstitial flow on drug delivery. This paper formulates blood flow through a capillary network induced by a solid tumor and fluid flow in a tumor's surrounding tissue and investigates the effects of consideration a remodeled network and adaptability of capillary on interstitial flow. Numerical results show that the prediction of interstitial pressure for the remodeled network shows a higher value compared to the rigid one. Results from interstitial fluid and blood distribution in normal and cancerous tissues have beneficial information about the prediction of successive drug delivery.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.303
Teacher spread0.287 · 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

Quick stats

Citations16
Published2014
Admission routes1
Has abstractyes

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Same topicMathematical Biology Tumor GrowthFrench-language works237,207