Aquatic Systems under Stress, <i>c.</i> 1000–1350
Bibliographic record
Abstract
The high-medieval demographic and economic growth in which fishers and their customers shared had detectable environmental consequences. Prevailing agricultural practices plus increased human and other wastes damaged river systems and polluted both flowing and still waters. Contemporaries were aware of some such effects; others emerge only in modern scientific archaeology. Rulers and others blamed perceived declines in the quantity and quality of fish on overfishing. Present-day studies of long-running assemblages of fish remains detect local depletion of favoured varieties and shrinking average size of more common species. Some fishes (eel) and some fisheries (for herring) of previously limited importance increased their contribution to European diets. An exotic species, common carp, hitherto present in Europe only in the lower Danube, spread westwards into waters made warmer and siltier by human activities. In large thirteenth-century assemblages (but with regional variations), more accessible herring, eel, codfishes, and small cyprinids become dominant. Not all change had human origin; natural dynamics also played a role. High medieval centuries saw the crest, then decline, of climatic warming, with concomitant regional differences in precipitation, seasonality, riverine and estuarine hydrology, and even shifts in stratification and water chemistry of the Baltic. Changed habitats let heat-tolerant fishes spread west, while a herring-dominated regime in the Baltic peaked and slowly yielded to greater presence of cod. Knowingly or not, humans and animals had to adapt.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".