<i>Ascophyllum nodosum</i>Extract and Its Organic Fractions Stimulate<i>Rhizobium</i>Root Nodulation and Growth of<i>Medicago sativa</i>(Alfalfa)
Bibliographic record
Abstract
The effects of the seaweed Ascophyllum nodosum extracts (ANE) on nitrogen (N)–fixing nodules and growth of alfalfa plants were studied under greenhouse conditions. The treatment of alfalfa roots increased the number of total nodules per plant with ANE (69%) and organic sub-fractions methanol (20%) and chloroform (35%) at 1 g L−1 concentration. The number of functional nodules was greater per plant in ANE (36%) and its organic sub-fraction chloroform (105%). Maximum increase in shoot length was observed in ANE-treated plants (42%) and chloroform-treated plants (42%). Root length was longer in the chloroform fraction (15%), whereas the shoot dry-weight accumulation was greater in plants treated with ANE (118%), methanol (85%), and chloroform (85%) than the control. Root dry-weight accumulation increased in plants treated with ANE (118%) and chloroform (69%) compared to the control. Further studies are under way to identify the chemical components in ANE and organic fractions.
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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) | 0.001 | 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".