Minimal assay detects population-level senescence in the aquatic plant Lemna minor
Bibliographic record
Abstract
At the population level, senescence occurs when older individuals have an increased risk of death and reduced reproduction compared to younger individuals. We investigated senescence in the aquatic plant Lemna minor (common duckweed), an important species for plant senescence research. Our objectives were to (1) confirm or refute the presence of population-level senescence in this model species; (2) develop a minimal assay of senescence requiring only once-weekly data collection; and (3) test whether there were appreciable differences in senescence in plants grown in glass compared to polystyrene petri dishes, with an aim to reducing single-use plastic waste and long-term research materials costs. We found that weekly survival arced downward with age when viewed on a semi-log plot, and weekly production of descendants decreased with age, with both findings indicating population-level senescence that matched previous work using more frequent data-collection (per Objectives 1 and 2). Additionally, we found no noteworthy differences in senescence between plants grown in glass versus polystyrene petri dishes (per Objective 3). The use of weekly data collection could liberate personnel resources for other research-group functions, and could make the Lemna system suitable for senescence- or demography-education exercises. The use of glass dishes could reduce lab waste and expense.
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.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.011 |
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".