Bibliographic record
Abstract
Roswell Fort WorthNo one, not even I, bothers to cook up the yellow goatsbeard.The plants are allowed to dry out and disintegrate on the paths or are carefully bagged in plastic for the trash.I can see them now at any distance across the field, their shade of yellow entirely distinct from any other yellow, their silhouette of leaf and stalk standing out, now that I have hunted them for so long, from all the other grasses, forbs, and woody shrubs.Except for Autumn, the strong travois dog (licensed as an Australian cattle dog because the City of Calgary has no categories for Indigenous North American dogs), the dogs and I are as much invasive exotics as the yellow goatsbeard, as the brome and dandelions, as the Hungarian partridges who fill the niche once claimed by prairie chickens, as the English sparrows and city pigeons.Yet sometimes we find coyote scat or surprise a jackrabbit hurrying off with stiff-legged bounds.I give thanks for the pin cherries and strawberries, the wolf willows and wild roses, the spruces and poplars, the fescue grasses and the spring crocuses, the ears of the prairie, and I wonder by what right I uproot my fellow invasive, the pretty yellow flower that, if left alone, produces a perfect hoary globe, like a giant dandelion plume, that might delight a small child; the flower that, if left alone, could be harvested in the fall as food and medicine.On most fall and winter and spring mornings, the dogs and I leave the big old farmhouse in Nebraska and walk down our driveway, past the pond that feeds the well, along the abandoned railroad tracks, then up the Cardinal, Harold,
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".