The environmental impact and development direction of grass carp, <i>Ctenopharyngodon idella,</i> aquaculture
Bibliographic record
Abstract
Abstract Grass carp, Ctenopharyngodon idella, is the largest freshwater aquaculture fish species worldwide. However, its environmental impacts are increasingly controversial. In this paper, we considered the production of a 1500 g commercial grass carp as an example, analyzed through a life cycle assessment. The results showed that the indicators of global warming potential (GWP), acidification potential, eutrophication potential, freshwater eco‐toxicity potential (FAETP), land competition (LC), and fossil energy consumption of producing 1 kg of grass carp were equivalent to 5.7267 kg of CO2, 0.0648 kg of 1,4‐DCB0, 0.0010 kg of P, 0.0276 kg of SO2, 8.2951 m2, 0.3491 kg of oil, respectively, and were mainly from feed processing and water pollution. Compared with pig, beef, and sheep production, grass carp production has lower environmental impacts, but in terms of GWP, FAETP, and LC were significantly higher than chicken production, especially water pollution and discharge, which is an important consideration. This study clarifies the direction of grass carp production and key focus areas include producing low carbon and nitrogen emission feed, application of ecological engineering aquaculture system, intelligent mechanization technology and equipment.
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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 | 0.000 | 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) | 0.001 | 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".