Bibliographic record
Abstract
But within a few years of his visit in 1905, the Big Pasture, as the area was known, was drained by the Big Ditch, a massive project that turned that “disease-infested swamp” into fertile, productive farmland.Nearly a century later, William Crawford dreamt of walking in Teddy's hunting boots at a restored Hackberry Flats. But in the early 1990s, when the wetland restoration idea began to circulate, it was hard to imagine the arid, 4-square-mile depression just south of Frederick, Oklahoma had ever been a wetland.But Crawford and others rolled up their sleeves, and today what was once rows of wheat and milo is now the 7,000-acre Hackberry Flat Wildlife Management Area, an important wetland stopover for thousands of shorebirds, wading birds, and waterfowl that migrate along the central fly-way from the Gulf Coast to Canada.Hackberry Flat's uniqueness comes from its playa soils. The clay soil doesn't allow water to penetrate the ground so the water sits inside a bowl-shaped depression, nourishing a wetland. Although for centuries the area was a rare oasis for many migratory bird species, early farmers deemed the land
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 | 0.000 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.322 | 0.146 |
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".