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Record W1480407107

Image classification for a time-domain microwave radar system: Experiments with stable modular breast phantoms

2015· article· en· W1480407107 on OpenAlex

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

VenueEuropean Conference on Antennas and Propagation · 2015
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsMicrowave imagingBreast tumorModular designMicrowaveRadarBiomedical engineeringComputer scienceTime domainBreast tissueComputer visionArtificial intelligenceMaterials scienceBreast cancerMedicineTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we report on durable, long-lasting rubber breast phantoms that contain four tissue types (skin, gland, fat, and tumor) that accurately mimic their dielectric properties. An improved fabrication procedure for creating stable high-water content tissue phantoms is demonstrated. The phantoms are made in a modular fashion such that the configuration, including tumor depth, size, and presence of tumor, can be varied as desired. Further, we reconstruct images of the phantoms using our time-domain microwave radar system. The images are then used to test an image classification algorithm that aims to identify if the image under consideration is one of a healthy breast or a breast that contains a malignancy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.028
GPT teacher head0.227
Teacher spread0.199 · 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