Bibliographic record
Abstract
potential application rates or dates of application based on measured concentration of pesticides in soil samples. The samples are usually taken some time after the application date so the pesticide has been subject to dissipation from the site of application through chemical and biological degradation and offsite movement in water. During registration of a product, registrants are required to provide environmental fate data to the U.S. Environmental Protection Agency (EPA). One requirement is denoted as terrestrial field dissipation (TFD) where the pesticide is applied to a soil and soil samples are taken over time to provide an estimate of the rate of disappearance. The rate of disappearance denoted TFD half-life (t ) can be used in a back calculation to provide estimates of initial soil application rates. Methodology The U.S. EPA and Health Canada issued a collaborative North American Free Trade Agreement guidance document on the conduct of a TFD study and eventual mathematical derivation of t value (Corbin et al., 2006). The document explains the use of a first-order kinetic decay function to describe pesticide dissipation. The equation is: Eq. 1. \t M = M0e-kt
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.279 | 0.118 |
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".