<title>Near-infrared spectroscopic approach to assess tissue viability following a thermal injury</title>
Bibliographic record
Abstract
A recurrent problem in the assessment of thermal injuries is the ability to accurately identify the depth and extent of injury. Generally, the depth of a burn injury determines and is inversely related to the ability of the skin to restore and regenerate itself. Burns involve damage to the dermis in varying amounts, reducing the dermal blood supply and altering the skin hemodynamics. Near infrared spectroscopic imaging was used to non-invasively assess the changes that occur in the early (1-3 h) post-burn period. The study used an accurate porcine model to investigate the potential of near infrared spectroscopic imaging to accurately distinguish between burns of varying severity. Data analysis was carried out using a two-way and three-way data decompositions techniques to investigate the spectral changes related to burns. Burn injuries drastically alter the physical and optical properties of the tissue. Thermal destruction of cutaneous vasculature disrupts perfusion and oxygen delivery to the affected tissue. The results demonstrated that near infrared spectroscopic imaging might provide a new tool for an objective clinical assessment of burn injuries.
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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 | 0.001 | 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".