Assessment of repeated reference measurements to inform the validity of optical breast spectroscopy
Bibliographic record
Abstract
Mammographic breast density is a strong breast cancer risk factor, and its routine clinical measurement could potentially be used to identify women at higher risk of breast cancer and/or monitor primary prevention strategies. Previous reports of optical breast spectroscopy (OBS), a novel approach to measuring breast density, demonstrated that it is safe (no ionizing radiation), portable, low-cost, and does not require image interpretation but have been limited to small, single-center studies. Reference measurements taken on a phantom breast prior to and after each woman's OBS assessment are required for the calibration of the system transfer function as a part of processing participant data. To inform the validity of participant data, a detailed description of the reference measurements and a repeatability analysis of these measurements taken before and after participant assessment is presented. Reference measurements for OBS from 539 women aged 18-40 years were obtained as a part of a high-throughput epidemiological pilot study. Of these, measurements from 20 women with no useable data due to device failure (3.7%) were excluded and from another 12 women due to user error. The intra-class correlation (ICC) within complete pairs of reference data (taken before and after assessment) was high (all ICC > 0.84). The analysis presented here confirms the OBS participant data as valid for use in ongoing epidemiological research, providing further supporting evidence of OBS as a measure of breast density. A novel method of measuring breast density is needed to bridge large gaps in the knowledge of breast density in younger women and its relation to later-life breast cancer risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".