輸入水産食品の有機スズ化合物, DBT, TBT, TPTに関する調査研究
Bibliographic record
Abstract
In order to survey the safety of the imported fishery foods, we purchased 105 imported fish and shellfish samples in Hokkaido and determined the concentration of organotin compounds such as dibutyltin （DBT）, tributyltin （TBT） and triphenyltin （TPT） during the period from 1999 to 2001. The mean values of DBT, TBT and TPT in all samples were 1.8, 3.7 and 1.8 ppb, respectively. When all fish and shellfish were classified according to the kind, the mean value of TBT and TPT was decreased in the order of shellfish, fish, crustacean and cephalopod. The concentration of TBT of the cultivated salmon was higher than that of a natural salmon. The concentrations of the organotin compounds in the littleneck clam, the scallop, and the clam imported from Asian nations were high, and those of the channel mussel imported from the Oceania area, and surf calm from Canada were extremely low. It is thought that the difference in the concentration level of the organotin compounds accumulated in these shellfish reflects the actual condition used in the ocean.The ratios of the samples, whose concentration of DBT, TBT or TPT were less than 10ppb, were 99％, 90％ and 96％, respectively. Since the concentrations of the organotin compounds in the imported fish and shellfish are demonstrated at an overall quite low level, these foods are considered to be safe.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.001 |
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".