Cannibals by night? In situ video monitoring reveals diel shifts in inter- and intra-specific predation on the American lobster
Bibliographic record
Abstract
We conducted tethering experiments in the field to evaluate day–night differences in the identity and frequency of predators encountered by the American lobster (Homarus americanus) in coastal Maine, USA. Separate daytime and nighttime deployments were conducted using tethered lobsters under infrared-illuminated video surveillance. Supplemental tethering trials without video surveillance provided further quantitative information on diel and size-specific predation patterns. We found crabs to be the most common predators during the day, whereas lobsters prevailed at night. Contrary to expectations, we measured higher predation rates at night than during the day, suggesting that nocturnal interactions with conspecifics may play a more important role in lobster population regulation than previously thought when lobster population densities are high and large predatory fish are rare. As large predatory groundfish have been depleted in the Gulf of Maine, lobster populations have reached historic highs, making density-dependent feedbacks such as cannibalism more likely.
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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".