A Comparative Review of Thermography as a Breast Cancer Screening Technique
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.
Bibliographic record
Abstract
Breast cancer is the most frequently diagnosed cancer of women in North America. Despite advances in treatment that have reduced mortality, breast cancer remains the second leading cause of cancer induced death. Several well established tools are used to screen for breast cancer including clinical breast exams, mammograms, and ultrasound. Thermography was first introduced as a screening tool in 1956 and was initially well accepted. However, after a 1977 study found thermography to lag behind other screening tools, the medical community lost interest in this diagnostic approach. This review discusses each screening tool with a focus brought to thermography. No single tool provides excellent predictability; however, a combination that incorporates thermography may boost both sensitivity and specificity. In light of technological advances and maturation of the thermographic industry, additional research is required to confirm the potential of this technology to provide an effective non-invasive, low risk adjunctive tool for the early detection of breast cancer.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it