A Review of Grass Carp and Related Species Literature on Diet, Behavior, Toxicology, and Physiology Focused on Informing Development of Controls for Invasive Grass Carp Populations in North America
Bibliographic record
Abstract
Grass carp (Ctenopharyngodon idella) are globally important in aquaculture and aquatic vegetation control. However, escaped grass carp have established invasive populations. A targeted keyword search was performed on a carp (order: Cypriniformes) literature database maintained by the U.S. Geological Survey to identify literature relevant to grass carp. Additional sources cited in reviewed documents and provided by numerous reviewers were also included. There were three focus areas designed to provide support for invasive grass carp management: (1) diet and behavior; (2) physiological constraints, toxicity, and biology; and (3) gut physiology. Each focus area provides information to guide development of potential pathways for invasive grass carp control. Information from other carp species was used to fill in gaps where grass carp information was lacking and provide additional, potential research directions. Diet-related information included food selection and aquacultural diet formulations. Behavioral information included stimuli and non-physical barriers to attract, repel, or stop movement. Physiological constraints, toxicology, reproductive control, and biological control provide a research review for control options. Gut physiology and related control pathways provide knowledge to improve toxin or pathogen delivery. This review provides a basis for developing approaches and research for controlling invasive grass carp populations, aquaculture, and native population management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".