Herbivorous Grass Carp (Ctenopharyngodon idella) Exhibit Greater Olfactory Response to Amino Acids Than Filter-Feeding Bighead (Hypophthalmichthys nobilis) and Silver Carp (Hypophthalmichthys molitrix)
Bibliographic record
Abstract
Due to their invasiveness in North America, grass (Ctenopharyngodon idella), bighead (Hypophthalmichthys nobilis), and silver carp (Hypophthalmichthys molitrix) are management priorities. Comparing electrophysiological responses to olfactory cues, such as amino acids, could help identify stimuli to facilitate management efforts (i.e., repellants or baits). We assessed olfactory response magnitude to individual amino acids between fish species using electro-olfactogram recording techniques (EOG). We measured EOG responses (peak EOG magnitude) of juvenile grass (n = 21), bighead (n = 21), and silver carp (n = 22) to 10−4 molar amino acid solutions containing one of L-alanine, L-arginine, L-aspartic acid, L-asparagine, L-glutamine, or L-glutamic acid. Amino acid EOG responses differed across species; grass carp had the greatest mean EOG response. Statistical analyses showed no inter- or intra-specific differences in EOG response among amino acids. The greater EOG response of grass carp matched their selective grazing habits compared to more passive, generalist-tending, filter-feeding bighead and silver carp. All amino acids elicited significant EOG responses in all species, meaning they are candidates for future behavioral research. Such research could explore the management potential of amino acids, testing if amino acids are attractants or deterrents that could facilitate the removal of these fishes by congregating and/or directing movement.
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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".