Modelling copepod development: current limitations and a new realistic approach
Bibliographic record
Abstract
Abstract Gentleman, W. C., Neuheimer, A. B., and Campbell, R. G. 2008. Modelling copepod development: current limitations and a new realistic approach. – ICES Journal of Marine Science, 65: 399–413. To predict the influence of environmental variability on copepod dynamics and production, models must account for the effects of temperature and food on stage-dependent time-scales. Here, data for development-time means and variance of Calanus finmarchicus are used to quantify the limitations of existing models. Weight-based individual models are sensitive to uncertain parameters, such as moulting weights, assimilation efficiency, and environmental dependencies, making them highly difficult to calibrate. The accuracy of stage-based population models using ordinary differential equations depends on model structure, with some predicted generation times being incorrect by months. Even when large numbers of age classes are used to reduce modelled variability, it is not possible to make variability consistent with the data. Accuracy of mean times for stage-based population models using difference equations requires a small time-step, which results in large numbers of age classes and modelled variability that is underestimated by orders of magnitude, unless a probabilistic moult fraction is used. We present a new stage-based individual model that avoids the limitations of other models and successfully represents C. finmarchicus mean development timing and associated variability. This approach can be adapted easily for other species, as well as dynamic environmental conditions.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".