sGAL: a computational method for finding surface exposed sites in proteins suitable for Cys-mediated cross-linking
Bibliographic record
Abstract
UNLABELLED: sGAL is a computer program designed to find pairs of sites suitable for introducing chemical cross-links into proteins. sGAL takes a protein structure file in PDB format as input, truncates each residue sequentially to its gamma side chain atom to mimic mutation to Cys, and calculates the exposed surface area of the gamma atom. The user then inputs the minimum and maximum lengths of the cross-linker. sGAL provides as output pairs of residues that would have exposed gamma atom separations that fall within this range. Furthermore, if a line joining the pair of gamma atoms contacts more than a given number of buried atoms, that pair is discarded. In this way, sites for which the protein would sterically interfere with cross-linking are avoided. AVAILABILITY: http://www.chem.utoronto.ca/staff/GAW/links.html; (Surface Racer is also required see: http://monte.biochem.wisc.edu/~tsodikov/surface.html).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".