Bibliographic record
Abstract
This report presents the results of vegetation monitoring efforts in 2022 at Agate Fossil Beds National Monument (AGFO) by the Northern Great Plains Inventory and Monitoring Network (NGPN) and the Northern Great Plains Fire Ecology Program (NGPFire). This was the tenth year of combined monitoring efforts. In 2022, crew members from NGPN visited 6 long-term plant community monitoring (PCM) plots to collect data on the upland mixed-grass prairie plant communities at AGFO. This work is part of a long-term monitoring program established to better understand the condition of the vegetation community and how it changes over time. NGPN staff collected species richness, herb-layer height, native and non-native species abundance, ground cover, and site disturbance data at each plot. The NGPFire crew visited an additional 11 PCM and Fire Plant Community Monitoring (FPCM) plots in the North Carnegie, River-North, River-Middle, and River-South Burn Units to better understand the effects of prescribed fire on vegetation. In 2012, NGPN began monitoring plots within the riparian corridor of the Niobrara River. This year, NGPN evaluated 12 riparian community monitoring (RCM) plots. In 2022, the monitoring crews identified 130 unique plant species in 29 monitoring plots. Of these species, 29 are exotic species for the park. We observed two species, Canada thistle (Cirsium arvense) and musk thistle (Carduus nutans), that are noxious in the state of Nebraska. Pale yellow iris (Iris pseudacorus), an exotic species of concern for the park, was observed at 8 of the 13 RCM plots monitored. The majority of upland and riparian plots had more native than exotic absolute cover. The most commonly observed disturbance was soil disturbance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".