Growth models and longevity of freshwater pearl mussels (<i>Margaritifera margaritifera</i>) in Spain
Bibliographic record
Abstract
Growth rates of populations of the freshwater pearl mussel, Margaritifera margaritifera (L., 1758), in northwestern Spain were analysed based on measurements of annual annuli and using two nonlinear functions for length-at-age data sets: von Bertalanffy's growth model and a hyperbolic function. These populations reach the smallest maximum shell length (90.5 mm) and have the shortest life-span (35 years) and the highest growth rate (k in von Bertalanffy's model >0.1·year –1 , on average) known for this species. The two models were similar in performance and were well fitted (around 99%) to shell-length-at-age data, although the hyperbolic function appears to be applicable only from 6 years of age. The growth rate (either k or k' from the hyperbolic function) showed a large and significant variation across populations, both among and within drainages.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".