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
For improved interstudy reproducibility, reduced risk of premature failures, and ultimately better patient care, researchers and dentists need to know how to accurately characterize the electromagnetic radiation (light) they are delivering to the resins they are using. The output from a light-curing unit (LCU) is commonly characterized by its irradiance. If this value is measured at the light tip, it describes the radiant exitance from the surface of the light tip, and not the irradiance received by the specimen. The value quoted also reflects only an averaged value over the total measurement area and does not represent the irradiance that the resin specimen is receiving locally or at a different moment in time. Recent evidence has reported that the spectral emission and radiant exitance beam profiles from LCUs can be highly inhomogeneous. This can cause nonuniform temperature changes and uneven photopolymerization within the resin restoration. The spectral radiant power can be very different between different brands of LCUs, and the use of irradiance values derived from dental radiometers to describe the output from an LCU for research purposes is discouraged. Manufacturers should provide more information about the light output from the LCU and the absorption spectrum of their resin-based composite (RBC). Ideally, future assessments and research publications should include the following information about the curing light: 1) radiant power output throughout the exposure cycle and the spectral radiant power as a function of wavelength, 2) analysis of the light beam profile and spectral emission across the light beam, and 3) measurement and reporting of the light the RBC specimen received as well as the output measured at the light tip.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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