Additional file 1 of Enhancing monolignol ferulate conjugate levels in poplar lignin via OsFMT1
Bibliographic record
Abstract
Supplementary Material 1: Methods S1. Generation, selection, and cultivation of transgenic hybrid poplar. Supplemental Figure S1. Expression of OsFMT in transformed poplars. Supplemental Figure S2. Height and diameter of OsFMT transgenic poplars. Supplemental Figure S3. Autofluorescence microscopy of petiole cross-section of OsFMT poplars and controls. Supplemental Figure S4. Saccharification efficiency of OsFMT, AsFMT, and WT poplar trees. Supplemental Figure S5. Chemical shifts of model compounds for ferulate coupling products. Supplemental Table S1. The HSQC NMR subunit distribution (given on an S + G = 100% basis) and the major lignin interunit structures. Supplemental Table S2. The quantified DFRC monomers reported for the native lignin monomer and not that of the derivatized substructures. Supplemental Table S3. UV-Vis spectra of preparations of EL (enzyme lignin) for estimations of ferulate content.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.866 | 0.288 |
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".