Historic Trends of Dechloranes 602, 603, 604, Dechlorane Plus and Other Norbornene Derivatives and Their Bioaccumulation Potential in Lake Ontario
Bibliographic record
Abstract
Temporal trends and seasonal variation of Dechloranes (Dec) 602, 603, 604, and Chlordene Plus (CP) in Niagara River suspended sediment, a Lake Ontario sediment core, and Lake Ontario lake trout were investigated, with Mirex and Dechlorane Plus (DP) included for comparison. Temporal concentration trends were generally consistent in each of the media for all compounds with the lowest concentrations observed in or after the late 1990s. In Niagara River suspended sediments, all compounds showed seasonal variation over a year with distinct profiles observed. The relative concentration patterns observed were total DP > Mirex > Dec 602 and Dec 604 > Dec 603 > CP in suspended sediments and sediment cores, whereas Mirex was highest in lake trout, followed by Dec 602 and DP. Dec 602 concentrations were 50 to 380 times greater than those of DP in lake trout, indicating Dec 602 has a greater bioaccumulation potential. The estimated biota-sediment accumulation factor (BSAF) for Dec 602 was much greater than for DP in Lake Ontario, and was greater than those calculated for PBDEs, indicating that assessment of some dechlorane compounds is merited if use is ongoing or planned.
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 | 0.001 | 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".