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Record W2074503293 · doi:10.1155/2013/894153

Study of the Effects of Changing Physiological Conditions on Dielectric Properties of Breast Tissues

2013· article· en· W2074503293 on OpenAlexaff
Abas Sabouni, Camerin Hahn, Sima Noghanian, Edward R. Sauter, Tim Weiland

Bibliographic record

VenueISRN Biomedical Imaging · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsPolytechnique Montréal
FundersOffice of Experimental Program to Stimulate Competitive Research
KeywordsDielectricMicrowaveMaterials scienceBiological tissueBiomedical engineeringEx vivoChemistryIn vivoBiophysicsMedicineBiologyOptoelectronicsBiotechnology

Abstract

fetched live from OpenAlex

This paper addresses the changes in the physical characteristics (temperature and water/blood content) of breast tissue under different physiological conditions. We examined ex vivo specimens of breast tissue excised at the time of surgery to study the effects of physiological conditions on dielectric properties. We observed that the dielectric properties strongly depend on tissue physiological state. When the biological tissues undergo physiological changes, such as those due to disease or those induced by external changes such as variations in the environmental temperature, the microscopic processes deviate from their normal state and impact the overall dielectric properties. This suggests that microwave imaging might be used to monitor the physiological conditions of the body.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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

Citations18
Published2013
Admission routes1
Has abstractyes

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