TAILS N-terminomic and proteomic datasets of healthy human dental pulp
Bibliographic record
Abstract
The Data described here provide the in depth proteomic assessment of the human dental pulp proteome and N-terminome (Eckhard et al., 2015) [1]. A total of 9 human dental pulps were processed and analyzed by the positional proteomics technique TAILS (Terminal Amine Isotopic Labeling of Substrates) N-terminomics. 38 liquid chromatography tandem mass spectrometry (LC-MS/MS) datasets were collected and analyzed using four database search engines in combination with statistical downstream evaluation, to yield the by far largest proteomic and N-terminomic dataset of any dental tissue to date. The raw mass spectrometry data and the corresponding metadata have been deposited in ProteomeXchange with the PXD identifier <PXD002264>; Supplementary Tables described in this article are available via Mendeley Data (10.17632/555j3kk4sw.1).
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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 | 0.001 | 0.001 |
| 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".