A dynamic level IV multimedia environmental model: Application to the fate of polychlorinated biphenyls in the United Kingdom over a 60-year period
Bibliographic record
Abstract
A dynamic or level IV multimedia model is described and illustrated by application to the fate of three polychlorinated biphenyl (PCB) congeners in the United Kingdom over a 60-year period from their introduction into commerce until the present. Models of this type are shown to be valuable for elucidating the time response of environmental systems to increasing, decreasing, or pulse inputs. The suggestion is made that in addition to the outputs of time-dependent concentrations (which can be compared with monitoring data for validation purposes), it is useful to examine masses, fugacities, and fugacity ratios between media? The relative importance of processes is best evaluated by compiling cumulative intermedia fluxes and quantities lost by reaction and advection and examining the corresponding process rate constants or their reciprocals, the characteristic times. The suggestion is made that uncertainty and sensitivity analyses are desirable, but it must be appreciated that relative sensitivities of input parameters may change during the simulation period, so a single sensitivity analysis conducted at one point in time can be misleading. The use of the model for forecasting future trends in concentration is illustrated. Given the uncertainties in emission and advective inflow rates, the simulation of PCB fate in the United Kingdom is regarded as showing time trends that are in satisfactory agreement with monitoring data.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".