The influence of diet on the assimilation efficiency of 47 polychlorinated biphenyl congeners in Japanese koi (<i>Cyprinus carpio</i>)
Bibliographic record
Abstract
The influence of diet on polychlorinated biphenyl (PCB) assimilation was investigated by measuring dietary assimilation efficiencies (AEs) for 47 PCB congeners in juvenile koi (Cyprinus carpio) fed five experimental diets. Two of the diets were naturally contaminated and were obtained by collecting mayflies from Lake Erie (ON, Canada) and emerald shiners from the Detroit River (MI, USA). The remaining diets consisted of commercial fish pellets (lipid contents from 6.7 to 24%) that were contaminated by spiking with a PCB mixture. Experimental fish were held individually to quantify the amount of food consumed per fish and, following a 48-h fasting period to facilitate food digestion and assimilation; AEs were determined by mass balance. Fish fed the benthic invertebrate food exhibited the highest PCB AEs (70-101%) and were significantly elevated compared to the other diet treatments (AEs ranging from 23 to 87%). The PCB AEs for fish fed emerald shiners did not differ from those fed pellet formulations. Variation among PCB AEs was not related to diet lipid content. For all diet treatments, PCB AEs were significantly related to chemical hydrophobicity. The relationship between chemical AE and n-octanol/water partition coefficient (K(OW)) was best explained by a linear model compared to a two-phase resistance model. Overall, PCB AEs were observed to be dependent on both diet type and chemical hydrophobicity, with both factors contributing nearly equally to the variation measured in this toxicokinetic parameter.
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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".