Protein labeling and biotinylation of peptides during spot synthesis using biotin <b><i>p</i></b>‐nitrophenyl ester (biotin‐ONp)
Bibliographic record
Abstract
Biotin-labeled peptides are used for numerous biochemical and microbiological applications. Due to the strong affinity of biotin to streptavidin, the detection of biotinylated molecules is very sensitive. A powerful technique for parallel synthesis and high-throughput screening of peptides is the spot synthesis. One example for the use of spot synthesis is the screening of biotinylated peptides synthesized on cellulose membranes, which is particularly favorable for the investigation of protease cleavage sites. Additionally, in combination with biotinylated protein samples, the spot technique can be used for investigations of peptide-protein and protein-protein interactions. Here, we present our results of the use biotin p-nitrophenyl ester (biotin-ONp) in spot synthesis and as a reagent for biotin-labeling of protein samples.
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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".