Myths and moderation in marine ‘metapopulations’?
Bibliographic record
Abstract
Abstract The metapopulation concept is appearing with increasing frequency in the marine population dynamics and genetics literature, though its applicability to marine systems remains an open question. Moreover, in recent years, the meaning of the term ‘metapopulation’ has become blurred, concomitant with its increasing use. In this paper, we summarize the concept of metapopulation dynamics and the associated theoretical assumptions. We call for a stricter definition and use of the term ‘metapopulation’, critically evaluate the applicability of metapopulation theory to marine population dynamics and its use in the related literature, and consider two published case‐studies that investigate metapopulation structuring in specific marine populations. Finally, we urge scientists to carefully articulate what is meant by the term ‘metapopulation’ and to use appropriate citations in the primary literature to circumvent the potential for nebulous (and possibly damaging) conclusions in the future.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".