Lake Mead National Recreation Area Vegetation Monitoring and Analysis: Quarterly Progress Report, Period Ending June 30, 2007
Bibliographic record
Abstract
Executive Summary Weed Sentry staff surveyed several springs and seeps on the Desert Range National Wildlife Refuge, measuring exotic species abundance and plant community composition. In addition, 63 miles were surveyed for exotic species on National Park Service (NPS) land, nine miles on Bureau of Land Management (BLM) land, and 119 miles on U.S. Fish and Wildlife Service (USFWS) land. A total of 867 exotic plants in incipient populations were treated on NPS land, and 53 plants were treated on ISFWS land. Research Assistant Ms. Jessica Spencer assumed coordination duties for Weed Sentry mapping this quarter to replace Ms. Carrie Nazarchyk, who accepted a position with Lake Mead National Recreation Area (Lake Mead NRA). Mr. Alex Suazo was hired to fill this vacant position, and will begin work August 1. NPS ATR Ms. Alice Newton served on the search committee, which was chaired by PI Dr. Scott Abella. A Joint Fire Science grant of $179,000 was awarded this quarter, and will fund projects at Lake Mead NRA and on BLM land to study native species that may be easily established and can compete with exotic annual grasses. Monitoring of four covered MSCHP rare plant species was completed this quarter. In addition, technical assistance and labor was provided to Ms. Newton for establishing exclosures around sticky buckwheat due to concerns about trespass cattle grazing. A gypsum seed bank study was initiated to support ecological restoration of the Northshore Road construction project.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.048 | 0.027 |
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".