Shellfish consumption preferences in an oceanic archipelago
Bibliographic record
Abstract
A survey on shellfish consumption preferences was conducted in the Eastern Atlantic archipelago of Madeira. A total of 402 valid questionnaires were collected from locals older than 15 years old. Gender, age, highest education level, work status and salary were considered in the sample composition. Participants were inquired about frequency, amount and risks associated with consumption, as well as concerns regarding the freshness of seafood. Shellfish appears to be consumed less than once a week, and 79.1% of these consumers prefer limpets. GLM analysis showed that total salary amount was the demographic variable which most affects seafood consumption. The results indicated that the majority of the respondents consume limpets less than once a week, in an amount that varies between a quarter and a half dose. With regard to health concerns, most respondents are conscious of the importance of products’ freshness and approximately half of them are aware of the existence of risks associated with consumption. In general, the awareness about freshness and possible risks of consumption is dependent on the level of education. Limpets are preferably consumed during summer, both grilled and cooked, respectively. The present study provides preliminary information on shellfish consumption trend in the archipelago of Madeira. Raising the awareness of seafood consumers in line with a health surveillance network in preparation in Macaronesia could be an important tool for spreading information related to the risks associated to its consumption.
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 | 0.001 |
| 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".