Genotypic‐specific responses caused by prolonged drought stress in smooth bromegrass (<i>Bromus inermis</i>): Interactions with mating systems
Bibliographic record
Abstract
Abstract The consequences of recurrent drought events compared with a single drought, and drought's interaction with deliberate selfing compared with open‐pollination on postdrought recovery and persistence of smooth bromegrass, are not clear. This research was conducted to investigate the effects of recurrent drought stresses compared with a single drought on stress response, poststress recovery and persistence of full‐sib and half‐sib progenies of smooth bromegrass. During this study, 25 selfed (S1) and 25 open‐pollinated (OP) progenies of smooth bromegrass created in 2012 were evaluated in the field under normal and recurrent drought stress during 2013–2016. After the first harvest of above‐ground biomass in 2016, irrigation was withheld in both environments for 2 months; plants were subsequently re‐watered and evaluated. Recurrent drought stress changed the relationships between different traits. Moreover, prolonged drought stress resulted in increased plant productivity (recovery aerial biomass; RABI) of S1 and OP populations in recurrent drought stress compared with normal environment. Mandatory selfing increased persistence of smooth bromegrass genotypes but did not affect recovery after prolonged drought stress. Results revealed that, selecting among S1 families would be more effective than OP ones.
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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 | 0.000 | 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) | 0.000 | 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 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".