Dataset of protein changes induced by cold acclimation in red clover (Trifolium pratense L.) populations recurrently selected for improved freezing tolerance
Bibliographic record
Abstract
The data provide an overview of proteomic changes in red clover (Trifolium pratense L.) in response to cold acclimation and recurrent selection for superior freezing tolerance. Proteins were extracted from crowns of two red clover cultivars grown under non-acclimated or cold-acclimated conditions, and plants obtained from the initial genetic background (TF0) and from populations obtained after three (TF3) and four cycles (TF4) of recurrent selection for superior freezing tolerance. Proteins were analyzed using a two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) coupled to mass spectroscopy (MS and MS/MS). Differentially regulated proteins were subsequently identified using MALDI TOF/TOF analysis. The data are related to a recently published research article describing proteome composition changes associated with freezing tolerance in red clover, "A proteome analysis of freezing tolerance in red clover (Trifolium pratense L.)" (Bertrand et al., 2016 [1]). They are available in the ProteomeXchange Consortium database via the PRIDE partner repository under the dataset identifier PRIDE: PXD003689.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".