Additional file 1 of High-resolution time-series transcriptomic and metabolomic profiling reveals the regulatory mechanism underlying salt tolerance in maize
Bibliographic record
Abstract
Additional file 1: Fig S1. The schematic of likelihood ratio test to detect SSET genes. Fig S2. Temporal clustering of 5331 SSET genes. Fig S3. Generation of ZmGLK44 Crispr and transgenic line. Fig S4. The metabolic profiles of proline and myo-inositol. Fig S5. Temporal expression profile of MIPS-coding genes in HLZY and JI853 Fig S6. Prediction accuracy of all 310 detected metabolites. Fig S7. Phylogenic analysis and temporal expression profile of 6 GLN-coding genes in maize. Fig S8. Identification of ZmGLN2 stop-gained mutant in maize EMS bank. Fig S9. Na+ levels, K+ levels, and Na+/K+ ratio change among ZmGLK44 OE, KO, and wild-type plants under CK and salt stress conditions. Fig S10. Na+ levels, K+ levels, and Na+/K+ ratio change between gln2 mutants and wild-type plants under CK and salt stress conditions. Fig S11. The Venn diagram of DEGs between gln2 mutant and wild-type plants under CK and salt conditions Fig S12. Expression levels of genes involved in proline metabolism in gln2 mutant compared with wild-type plants in CK and salt conditions.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.908 | 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".