Changes in bacterial communities in chilled American lobster (Homarus americanus) tissues following mortality
Bibliographic record
Abstract
Studies evaluating bacteria growing on dead American lobster (Homarus americanus) are typically based on a single observation of the post-mortem period. In this study, seventy-five lobsters were euthanized to evaluate changes in microbiological composition between sexes, and in gut, tail, and claw tissues over a 4-day period under chilled (4 °C) storage. The hygienic quality of meat decreased over the storage period but remained acceptable (<6 log CFU/g). Metagenomic analysis showed alpha and beta diversity differed by tissue type throughout storage time. Photobacterium spp. Were the primary spoilage bacteria identified in gut (49%) and tail (89%) but were less abundant in the claw (11%). Photobacterium spp. Abundance were unchanged in the gut over the sampling period, whereas their proportion increased in the tail (62%) and claw (32%) over the sampling period. Unlike other studies, Photobacterium phosphoreum was the predominant species detected. The detection of bacteria not previously reported in American lobster suggest there could be an association between the microbiota in lobster tissues with their diet and/or habitat, and these factors could influence the spoilage bacteria inhabiting these tissues. Findings identify an opportunity to recover tail and claw meat from dead lobsters with a quality acceptable for human consumption.
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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".