Bio-Energetic Value of the Flathead and Smith Valleys in Northwest Montana for Spring Waterfowl Migration
Bibliographic record
Abstract
The abundance of lakes, rivers, streams, wetlands, and agricultural lands of the Flathead and Smith Valleys in northwest Montana attracts a significant number of migratory waterfowl moving from wintering grounds to breeding habitats each spring. These diverse habitats provide food and resting areas for thousands of waterfowl and other waterbirds each year. These valleys are also undergoing rapid habitat transformation due to growth in human population with concomitant conversions from rural agricultural and riparian habitats to more residential and commercial development. To quantify the current extent, distribution, importance, and species that use this area as a spring stopover, we initiated a randomly stratified, weekly, simultaneous waterfowl survey of selected areas from early March through April. We began in spring 2010 and will continue through spring 2012. The data will be extrapolated to the entire study area and for the 2-month period to develop an estimate of total annual waterfowl feeding days by species. Habitat data are also being incorporated. Preliminary results from first 2 years of data indicate that the 4 most common migrant waterfowl species, in order of total numbers counted, are Mallard, Northern Pintail, Canada Goose, and American Wigeon. Preliminary extrapolations of waterfowl survey data in terms of bioenergetics will be summarized.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".