The Prairie Naturalist, Vol. 42, Issue 3/4, December 2010
Bibliographic record
Abstract
EDITOR'S NOTE: REPORTING RESULTS OF DATA ANALYSIS, PREPARING SCIENTIFIC MANUSCRIPTS, AND WEBSITE DEVELOPMENT EFFORTS • Christopher N. Jacques Current Distribution of Rare Fishes in Eastern Wyoming Prairie Streams • Christina E. Barrineau, Elizabeth A. Bear, and Anna C. Senecal Diets of Nesting Swainson's Hawks in Relation to Land Cover in Northwestern North Dakota • Robert K. Murphy Resource Selection of Greater Prairie-Chicken and and Sharp-Tailed Grouse Broods in Central South Dakota • Mark A. Norton, Kent C. Jensen, Anthony P. Leif, Thomas R. Kirschenmann, and Gregory A. Wolbrink Population Characteristics of Central Stonerollers in Iowa Streams • Scott M Bisping, Jesse R. Fischer, Michael C. Quist, and Andrew J. Schaefer Seasonal Yellow Perch Harvest in Two Dissimilar South Dakota Fisheries • Casey W Schoenebeck, Michael L. Brown, and David 0. Lucchesi Cropland Nesting by Long-billed Curlews in Southern Alberta • James H. Devries, Steven O. Rimer, and Elizabeth M Walsh Population and Diet Assessment of White Bass in Lake Sharpe, South Dakota • Andrew E. Ahrens, Travis W Schaeffer, Melissa R. Wuellner, and David W Willis Examination of Owl Pellets for Northern Pocket Gophers at Crescent Lake National Wildlife Refuge, Nebraska • Stacey L. Bonner and Keith Geluso Summer Activity Pattern and Home Range of Northern Pocket Gophers in an Alfalfa Field • Jon C. Pigage and Helen K. Pigage Correlation of Mature Walleye Relative Abundance to Egg Density • Jordan D. Katt, Casey W Schoenebeck, Keith D. Koupal, Brian C. Peterson, and W. Wyatt Hoback BOOK REVIEWS Grouse of the Plains and Mountains - The South Dakota Story, by Lester D. Flake, John W. Connelly, Thomas R. Kirschenmann, and Andrew J. Lindbloom • Brent E. Jamison Weeds of the Midwestern United States & Central Canada, by Charles T. Bryson and Michael S. DeFelice • James Stubbendieck
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.143 | 0.077 |
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".