Bibliographic record
Abstract
In 2008, the National Marine Fisheries Service (NMFS) reported (pdf) that the U.S. imported close to 2.4 million t (5.3 billion lbs) of edible fishery products valued at $14.2 billion dollars. Finfish in all forms (fresh, frozen, and processed) accounted for 48% of the imports and shellfish accounted for an additional 36% of the imports. Overall, shrimp were the highest single-species import, accounting for 24% of the total fishery products imported into the United States. T una and Salmon were the highest imported finfish accounting for 18% and 10% of the total imports respectively. The majority of fishery products imported came from China, Thailand, Canada, Indonesia, Vietnam, Ecuador, and Chile. The U.S. exported close to 1.2 million t (2.6 billion lbs) valued at $3.99 billion in 2008. In fact, of all the imports into the U.S., 40,233 t (88.7 million lbs) were re-exported after being further processed in the U.S.. Finfish accounted for 75% of the exports, whereas shellfish only accounted for 11% of the exports. Salmon and various gr oundfish species were the top finfish exports at 12% and 10 % of total exports. Additionally , lobster accounted for 2% of the total exports. The U.S. primarily exports fishery products to China, Japan, Canada, South Korea, Germany, and the Netherlands. Although selling their catch directly to the public might bring a fisherman a better price, it is difficult because their schedules are often incompatible with shore-based market hours. Therefore, most fishermen sell their catch to a dockside buyer or a primary processor, who in turn makes these products available to retailers or the public. T o learn more about the process of fish getting to the markets see Seafood Markets – How are Fish Processed?. Historically fishmongers, people who sell fish, and fish markets were only found in seaside towns, but with the advent of refrigeration and rapid transportation, fish can be bought in almost all regions of the world. T oday there are many markets where fishery products are auctioned, the largest being the Tsukiji market in Japan, which functions as both a wholesale and retail
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 | 0.000 | 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) | 0.007 | 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".