Data from: Demographic senescence in the aquatic plant Lemna gibba L. (Araceae)
Bibliographic record
Abstract
Abstract Senescence is progressive, age-related bodily deterioration, accompanied at the population level by declines in average survival and fecundity (i.e., ‘demographic senescence’). Demographic senescence of plants has been investigated in only a few species, including small, floating macrophytes in the genus Lemna (family Araceae, subfamily Lemnoideae – the ‘duckweeds’). Unlike most plant species, Lemna ramets exhibit determinate growth, potentially rendering them more likely to experience demographic senescence. Here, our objective was to investigate senescence in a Lemna species not previously studied in this context, L. gibba L., toward the long-term goal of conducting cross-species comparative analyses. In a longitudinal lab study, we investigated a cohort of 334 individual L. gibba fronds, whose survival and reproduction we followed daily from birth (defined by the date a focal frond detached from its parent) to death (defined by the date a focal frond’s last daughter detached). We fit survival data to exponential, Weibull, Gompertz, and logistic models, the first of which represents ‘no senescence’. The logistic model was found to have the greatest support (AICC weight >0.99), indicating strong age-related declines in survival. We fit reproduction data using a generalized estimating equation approach, which showed a significant age-related decline in the predicted probability of daily reproduction – from 0.61 at age 3 days to 0.23 at age 52 days (i.e., after excluding the first two days of reproduction data to account for the initial, pre-reproductive phase of the L. gibba lifecycle). These age-related declines provide strong evidence that L. gibba does exhibit demographic senescence, consistent with evidence from congeneric species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.008 | 0.002 |
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".