A Moisture index approach to characterizing climates for moisture management of building envelopes
Bibliographic record
Abstract
We develop a dual-modality device that combines the anatomical imaging capabilities of optical coherence tomography (OCT) with the functional capabilities of laser-induced fluorescence (LIF) spectroscopy. OCT provides cross-sectional images of tissue structure to a depth of up to 2 mm with approximately 10-microm resolution. LIF spectroscopy provides histochemical information in the form of emission spectra from a given tissue location. The OCT subsystem utilizes a superluminescent diode with a center wavelength of 1300 nm, whereas a helium cadmium laser provides the LIF excitation source at wavelengths of 325 and 442 nm. Preliminary data are obtained on eight postmortem aorta samples, each 10 mm in length. OCT images and LIF spectra give complementary information from normal and atherosclerotic portions of aorta wall. OCT images show structures such as intima, media, internal elastic lamina, and fibrotic regions. Emission spectra ratios of 520/490 (325-nm excitation) and 595/635 (442-nm excitation) could be used to identify normal and plaque regions with 97 and 91% correct classification rates, respectively. With miniaturization of the delivery probe and improvements in system speed, this dual-modality device could provide a valuable tool for identification and characterization of atherosclerotic plaques.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".