<i>Great Plains Research: A Journal of Natural and Social Sciences</i> Volume 19, Number 1 (Spring 2009): Table of Contents
Bibliographic record
Abstract
Social Sciences\nSocioeconomic Impacts of Developing Wind Energy in the Great Plains (F. Larry Leistritz and Randal C. Coon) .............. 3\nArcheological Interpretation of the Frontier Battle at Mud Springs, Nebraska (Peter Bleed and Douglas D. Scott) .............. 13\nNatural Sciences\nCauses and Impacts of Salinization in the Lower Pecos River (Christopher W. Hoagstrom) .............. 27\nNear-Surface Soil-Water Monitoring for Water Resources Management on a Wide-Area Basis in the Great Plains (Hubbard, You, Sridhar, Hunt, Korner, and Roebke) .............. 45\nPrecipitation Event Size Controls on Long-Term Abundance of Opuntia Polyacantha (Plains Prickly-Pear) in Great Plains Grasslands (Lauenroth, Dougherty, and Singh) .............. 55\nEcology of Small Mammals, Vegetation, and Avian Nest Survival on Private Rangelands in Nebraska (Fricke, Kempema, and Powell) .............. 65\nMarginal Value of Irrigation Water Use in the South Saskatchewan River Basin, Canada (Antony Samarawickrema and Suren Kulshreshtha) .............. 73\nHistorical Changes in the Occurrence and Distribution of Freshwater Mussels in Kansas ( Angelo, Cringan, Hays, Goodrich, Miller, VanScoyoc, and Simmons) .............. 89\nBook Reviews .............. 127\nNews and Notes .............. 143
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.131 | 0.040 |
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".