Strategies and tools for studying the metabolism and function of γ-aminobutyrate in plants. II. Integrated analysis
Bibliographic record
Abstract
γ-Aminobutyrate (GABA) is a ubiquitous nonprotein amino acid that accumulates in plants in response to abiotic and biotic stresses. In a companion paper, we discussed the origin of GABA from glutamate and subsequent catabolism to succinic semialdehyde and either succinate or γ-hydroxybutyrate (GHB), and the characteristics of genes and proteins responsible for GABA permease, glutamate decarboxylase, GABA transaminase, succinic semialdehyde dehydrogenase, and succinic semialdehyde reductase activities. In this paper, we explore gene expression and transcript–metabolite relationships during the response to abiotic stress, and describe phenotypes of genetic mutants and relationships of GABA metabolism to other plant functions. Evidence indicates that both gene-dependent and -independent processes are involved in the response of the GABA pathway to abiotic stresses. Study of stress-specific responses and their interplay with the C/N network and various signalling pathways would be more informative if circadian rhythms and light–dark transitions upon imposition of the stress were always taken into account, and relevant genes and metabolites simultaneously profiled in wild-type plants or genetic mutants.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".