FILTER FLUOROMETRIC TRACING FOR CONTAMINANT TRANSPORT MODELINGRyan
Bibliographic record
Abstract
Filter Fluorometric Tracing for Contaminant Transport Modeling Ryan Adams University of Western Ontario Advisor: Professor Chris Smart Contaminant transport in surface streams can be studied through analysis of the breakthrough curve obtained from fluorescent tracers and parameterized through analytical and statistical models. The new Turner Designs Cyclops fluorometer was evaluated in laboratory and field settings and used to generate 142 breakthrough curves in Medway Creek, Ontario. The instrument proved prone to interference from scattering and natural organic matter and generated quite noisy data. High background levels were removed through interpolation of pre and post trace values. Analytical and statistical modeling of the tracer breakthrough curves was compromised by tail data. A crude analogue approach generated more robust travel time, peak concentration and dispersion parameters, characteristic of reach and discharge, but could not characterize the tracer tail. The instrument is imperfect, but can generate abundant data allowing multiple traces to be run. The indeterminacy of the tracer tail is attributed to periodic exchange with proximal dead zones
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".