R code for multi-species size spectrum mode with seasonality
Bibliographic record
Abstract
R code for multi-species size spectrum model to accompany the paper: Samik Datta & Julia L. Blanchard. 2016. The effects of seasonal processes on size spectrum dynamics. Canadian Journal of Fisheries & Aquatic Sciences. 73(4): 598-610, https://doi.org/10.1139/cjfas-2015-0468 This code is a modification of the original multispecies size spectrum model published by Blanchard et al. 2014 (Journal of Applied Ecology, doi/10.1111/1365-2664.12238), which has been now generalised as an R package 'mizer' Scott, Blanchard & Andersen 2014 (doi/10.1111/2041-210X.12256and https://cran.r-project.org/web/packages/mizer/index.html). Modifications to the underlying model equations can be found in SizeBasedModel.R. This involved adding a seasonal plankton bloom and seasonal fish reproduction process. The code used to produce simulations and paper figures is in SeasonalityPaperResults.R.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.434 | 0.261 |
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".