Attenuated total reflection Fourier-transform infrared (ATR-FTIR) imaging of tissues and live cells
Bibliographic record
Abstract
FTIR spectroscopic imaging is a label-free, non-destructive and chemically specific technique that can be utilised to study a wide range of biomedical applications such as imaging of biopsy tissues, fixed cells and live cells, including cancer cells. In particular, the use of FTIR imaging in attenuated total reflection (ATR) mode has attracted much attention because of the small, but well controlled, depth of penetration and corresponding path length of infrared light into the sample. This has enabled the study of samples containing large amounts of water, as well as achieving an increased spatial resolution provided by the high refractive index of the micro-ATR element. This review is focused on discussing the recent developments in FTIR spectroscopic imaging, particularly in ATR sampling mode, and its applications in the biomedical science field as well as discussing the future opportunities possible as the imaging technology continues to advance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".