SOIL MOISTURE IMPACT ON BIOMASS PARTITIONING AND RELATIVE CHLOROPHYLL CONTENT FOR LEGUME GRASS MIXTURES IN A CONTROLLED ENVIRONMENT
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Drought is a widespread abiotic stress that impacts plant growth, productivity and survival.A randomized complete block design pot experiment was conducted to determine the effects of drought on above-ground biomass, root biomass, root/shoot (R/S) and relative leaf chlorophyll content (SPAD) of monoculture and legume-grass mixtures at the Swift Current Research and Development Centre (SCRDC) of Agriculture and Agri-Food Canada (AAFC).The legumes were Canadian milk-vetch (Astragalus canadensis) and white prairie-clover (Dalea candida).The grasses were northern wheatgrass (Elymus lanceolatus) and side-oats grama (Bouteloua curtipendula).Three water treatments (40%, 60% and 80% field capacity) and three cuts were the abiotic factors applied.Except for monoculture side-oats grama, multiple-species forage mixtures were more adaptable than a simple grass-legume mixture or monoculture in a water-limiting environment.The forage mixtures of Canadian milk-vetch and northern wheatgrass tolerated lower moisture levels than the other mixtures.Decreased soil moisture resulted in decreased total biomass and altered biomass allocation to roots resulting in higher R/S ratios in stressed seedlings.The SPAD value of Canadian milk -vetch mixture decreased with water stress, and white prairie-clover+ northern wheatgrass and white prairie-clover+ northern wheatgrass+ Canadian milk-vetch were better adapted to low soil moisture than the monocultures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it