WSSA Liaison to EPA (Office of Pesticide Programs – OPP) Interim Report to the WSSA Board of Directors – Quarter 3
Bibliographic record
Abstract
Schedule of third quarter activities: August 2‐5, 2010: hosted tour of NM agriculture and riparian areas (preparation time in July) August 9‐11, 2010: attended the NACD taskforce meeting on management of herbicide resistant weeds in conservation tillage agriculture in Little Rock, AR September 13‐16, 2010: visited OPP headquarters Overview of Activities: I was active during the third quarter although I only visited the EPA‐OPP headquarters in September. Instead of my August trip to headquarters, I hosted EPA colleagues in New Mexico for a tour of weed related issues in the semi‐arid southwest. I had phone and email correspondence with EPA personnel during the quarter. In addition, I attended the NACD task force meeting in Arkansas and attended numerous teleconferences for the Herbicide Resistance Education Committee (S 71), the S71 subcommittee developing a table describing occurrences of herbicide resistance at the request of EPA, and the S71 subcommittee working on the herbicide resistance training modules. I have corresponded with John Jachetta and other officers as well as Lee Van Wychen during the quarter to keep them informed of my activities. August 2‐5: NM tour itinerary follows. My final report will be sent as soon as it is completed and reviewed. EPA New Mexico Tour
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.341 | 0.169 |
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".