The Associations of Nutritive Seed Value on Bird Feeding Preference: A Multiple-offer, Observational Bird Feeding Experiment
Bibliographic record
Abstract
In the winter, birds are resource limited and demand more energy for migration and the enduranceof harsh winter conditions. Through the use of bird feeders, humans can help to supplement a bird’sincreased requirements. This experiment intends to examine which seeds wild, wintering, west-coast birdspecies prefer and the association between nutritional value of a seed and its respective consumption. Ioffered sunflower, millet, hemp seed and peanuts simultaneously using identical bird feeders hung on thesame tree in western Canada. Bird seed consumption at the end of experimental trials revealed that 2.5 g(SD= ±0.50 g) of sunflower seeds, 1.88 g (SD= ±0.40 g) of millet, 1.56 g (SD= ±0.30 g) of hemp seedsand 0.74 g (SD= ±0.25 g) of peanuts were consumed on average. Seed intake was related to bird seedpreference and I found statistical differences in the amount of seeds consumed (Friedman Test, X2= 15,n= 5, p= 0.0018). Seed consumption comparisons revealed that peanuts were the least preferred seed (p 0.05) and sunflowers were preferred compared topeanuts and hemp seed (p 0.05). Pearson’s correlation test associatingseed preference to total energy (r= 0.11), protein (r= 0.078), lipid (r= 0.26) and carbohydrate (r= -0.22)content were not found to be significant (p > 0.05). To assess correlations, connections were made tomigratory behavior, differences in biochemical processes required to digest nutrients, seasonal shift andpresence of harmful secondary compounds. Overall, I found sunflower seeds as being the seed ofpreference due to the seeds having the highest mean of consumption and a balanced nutritionalcomposition; which can be used to attract and aid the most birds in the winter.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".