Fish Safety and Quality from the Perspective of Globalization
Bibliographic record
Abstract
ABSTRACT Major developments in the field of fish safety and quality have had a significant impact on international trade during the last few decades. Technological developments in fish handling and processing coupled with increasing consumer food safety and quality awareness have resulted in the adoption of HACCP-based systems and scientifically-based risk assessment methodologies. This is reflected in international regulatory framework of the SPS and TBT Agreements of the WTO and the normative work of CODEX Alimentarius. Based on available food borne illness reports, the decrease in food borne diseases has coincided with the implementation of HACCP-based food safety assurance measures. However, fish safety and quality issues related to indigenous microorganisms, chemical or veterinary drugs are increasingly of concern. This reflects the need for a food chain approach in the analysis of hazards and risks to develop integrated risk management strategies. However, a food chain approach also requires substantial multidisciplinary scientific information given the need of science-based risk analysis. This paper discusses these issues in terms of their practical implications and limitations. FAO provides direct assistance to member countries via the CODEX Committees and other expert groups with a focus on training and capacity building in developing countries. In response to increasing demands for pertinent and succinct scientific and technical information upon which to conduct adequate hazard and risk analysis, the FAO has launched the Aquatic Food Programme in collaboration with the Canadian Food Inspection Agency with the expectation of creating a peer reviewed comprehensive knowledge base of integrated aquatic food to safety and quality information from a food chain approach. This paper also discusses the major activities of the FAO Fisheries Department to assist member countries and promote international cooperation for the use of scientifically-based fish safety and quality standards.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".