De novo sequencing of peptides using MALDI/TOF-TOF
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The recently developed MALDI TOF-TOF instrument yields relatively complex but interpretable fragmentation spectra. When coupled with a straightforward sequence extension algorithm, it is possible to develop complete peptide sequences de novo from the spectra. This approach has been applied to a set of peptides derived from typtic digestion of electrophoretically separated sea urchin egg membrane proteins. When directed to proteins that have been described previously, the results were in essential agreement with those obtained by conventional data base searching approaches, with certain important exceptions. The present method detected errors in published sequences and was able to develop sequences from peptides differing in mass by one dalton (Da). These results show both the power of the present approach and the need for using de novo methods more frequently than may be otherwise appreciated.
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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) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 it