Development of a modified transillumination breast spectroscopy (TiBS) system for population-wide screening
Bibliographic record
Abstract
A transillumination breast spectroscopy (TiBS) system used for breast cancer risk assessment is being modified to facilitate large-scale trials and to simply use. A proposed change involves switching from a broadband light source to several laser sources cycled through in sequence, which will allow for a wavelength-independent detection system. The effect of the reduction of the spectral content of the system on the ability to predict mammographic density (a known breast cancer risk factor) from the spectra was assessed. Wavelengths for the laser sources were chosen based on their contribution to the loading vectors obtained from a principal components analysis of spectra from a study correlating TiBS spectra with mammographic density. 12 wavelengths were selected based on the principal component loads. Principal component scores were obtained using both full-spectrum and 12-wavelength-spectrum data. No significant loss of predictive ability was found when the broadband spectra were reduced to only 12 wavelengths-for both data sets, 3 principal component scores were significantly able to distinguish between high- and low-mammographic density groups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".