Detection of Neuron Specific Enolase (NSE) with the Protein Biosensor Based on Imaging Ellipsometry
Bibliographic record
Abstract
Tumor markers can provide convincing evidence for tumor angiogenesis in early-stage, so that the need for novel and effective methods which can detect tumor markers rapidly, sensitively and reliably is consequently being subjected to extensive interest. The biosensor based on imaging ellipsometry (BIE) is developed for the detection of Neuron specific enolase (NSE) as a trial and its diagnosis performance is evaluated. Anti-NSE antibody as ligand is immobilized on protein A modified silicon substrate to form NSE sensing surface. Then, NSE test is carried out with the setup of a calibration curve for clinical quantitative detection purpose. The relationship between BIE signal y (grayscale value) and NSE concentration x (ng/ml) is y=19.6 lg(x) + 70.1 and the limit of detection achieves 2 ng/ml. The specificity, reproducibility and accuracy for NSE detection with BIE are all adequate to clinical diagnosis requirements. 149 serum samples have been detected quantitatively with BIE and their results are in agreement with a commercial ELISA immunoassay.
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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 | 0.000 | 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".