The history and ecology of Cisco <i>Coregonus artedi</i> in the Laurentian Great Lakes
Bibliographic record
Abstract
Cisco Coregonus artedi are a schooling, coldwater, zooplanktivorous fish native to the northern United States and Canada. They were once one of the most abundant fish species in the region, supporting large commercial fisheries in all five of the Great Lakes. Overfishing, habitat degradation, and impacts from invasive species such as Rainbow Smelt Osmerus mordax and Alewife Alosa pseudoharengus lead to the collapse of these fisheries by the mid 1900’s. Recently, there has been an increased momentum for restoring Cisco populations in the Great Lakes due to their role as native prey fish species for predators such as Lake Trout Salvelinus namaycush and Atlantic Salmon Salmo salar. Here I present a general overview of Cisco biology, detail the history of the commercial fishery in the Great Lakes, and look ahead to future restoration and recovery goals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".