Bibliographic record
Abstract
This upload contains processed chromatogram matrices for 411 CF-MS experiments. Database search and protein quantitation was performed with MaxQuant (version 1.6.5.0), and potential contaminants, reverse hits, and proteins identified only by modified peptides were filtered out. Multiple chromatograms are provided for each experiment, corresponding to different protein quantitation strategies. These include iBAQ, MaxLFQ, MS1 intensity, and spectral counts, for label-free datasets, and the isotopologue ratio for SILAC or dimethyl labelling datasets. Each directory also contains a metadata file, which contains further information about each row in the corresponding chromatogram matrices output by MaxQuant. Chromatograms are also provided for phosphorylation sites detected in a separate MaxQuant search including STY phosphorylation as a variable modification (in the "Phosphorylation" directory). Separate chromatograms are provided for raw phosphosite intensities and the ratio between modified and unmodified phosphosite intensities (phosphorylation stoichiometries). For datasets collected with SILAC or dimethyl labelling, isotopologue ratio chromatograms are also provided. For TMT datasets, reporter intensities for phosphosites were not output by MaxQuant, meaning that only aggregate measurements of phosphosite intensity and stoichiometry over all experiments in the TMT plex could be obtained. In addition to processed chromatograms, which are provided in the "Chromatograms" directory, the upload also contains the raw output files ('proteinGroups.txt' and 'Phospho(STY) sites.txt') from each MaxQuant search. These files are provided within the "Protein groups" directory. Complete MaxQuant outputs for each experiment are available from the PRIDE repository (see the manuscript for accession).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.484 | 0.430 |
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".