Bibliographic record
Abstract
The indiangrasses belong to the genus Sorghastrum. The name Sorghastrum comes from Sorghum and the Latin suffix astrum (a poor imitation of), indicating the resemblance to Sorghum (Gould, 1975). The genus consists of approximately 20 species, primarily in tropical and subtropical Africa and the Americas (Watson and Dallwitz, 1992). Eight species and one subspecies are identified in the Germplasm Resources Information Network (GRIN, 2003), with distributional ranges from Canada, the USA, Cuba, Mexico, South America, and tropical Africa. In North America, indiangrass [Sorghastrum nutans (L.) Nash], slender indiangrass [S. elliottii (c. Mohr) Nash], and lopsided indiangrass [S. secundum (Elliott) Nash] are indigenous (Hitchcock, 1971). Indiangrass is the most important and widely distributed of the Sorghastrum species, with slender indiangrass and lopsided indiangrass limited to the southeastern USA (Hitchcock, 1971; Sutherland, 1986; Diggs et aI., 1999). There is some disagreement in the literature concerning the botanical name for indiangrass. Baum (1967) believes that indiangrass should be classified as S. avenaceum (Michx.) Nash, but Gould (1975) and Sutherland (1986) indicate that S. nutans (L.) Nash is correct. Sorghastrum nutans (L.) Nash will be used in this chapter as the correct botanical name, based on the classification of Gould (1975) and Sutherland (1986), and will focus on it because of its prominence and broad distribution.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.143 | 0.080 |
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".