Finless porpoises (<i>Neophocaena asiaeorientalis</i>) in the East China Sea: insights into feeding habits using morphological, molecular, and stable isotopic techniques
Bibliographic record
Abstract
Describing feeding habits of cetaceans is crucial to understanding their feeding strategies and conservation status. Here, both morphological and molecular techniques were employed to identify the stomach contents of 122 finless porpoises (Neophocaena spp.) in the East China Sea for insight into their short-term feeding habits, and stable isotopes of δ13C and δ15N were used to analyze prey resource use and trophic position as a manifestation of their long-term feeding habits. In total, 33 prey species consisting of 19 teleosts, seven crustaceans, five cephalopods, and two gastropods were identified. In both short- and long-term analyses, teleosts represented primary prey, cephalopods and crustaceans were secondary prey, and gastropods were occasional prey; but the primary prey species composition differs between the short- and long-term diets. The composition of stomach contents showed sexual and age-related variation. This finding is supported by stable isotopic analyses, which indicated the separation of trophic position of adult males, adult females, and young males. In general, finless porpoises prey on species that are primarily caught by fisheries.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 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".