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
Recent advances in fiber optics, sources and detectors, imaging, and computer-controlled instrumentation have stimulated a period of unprecedented growth in the development of photonics technologies for a wide variety of diagnostic and therapeutic clinical applications. These include the application of quantitative optical spectroscopy and imaging for the detection of precancerous lesions in the uterine cervix, a topic of interest at the Second International Conference on Cervical Cancer, which was held April 11-14, 2002. Investigators have applied the Littenberg method of emerging technology assessment to new optical methods used to detect cervical neoplasia. Currently, such technologies as fluorescence spectroscopy (the combination of fluorescence and diffuse reflectance spectroscopy), tri-modal spectroscopy, and light-scattering spectroscopy that probe the spectral characteristics of tissue are being investigated. Optical technologies that create images of subcellular structure without biopsy subsequent to pathology that currently are under investigation include in vivo confocal imaging and optical coherence tomography. Numerous small studies have demonstrated the potential of these optical technologies. What remains to be elucidated are the fundamental biophysical origins of variations in remitted optical signals between normal and dysplastic tissue. Large multicenter randomized controlled trials are needed to confirm the detection and imaging capabilities of optical technology. Furthermore, the development of contrast agents that could boost detection with these technologies is needed, and basic biologic characterization of signals should be pursued. Applying the Littenberg assessment will help ensure that superior, not simply alternative, technologies are implemented.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it