Simulation of the Endangered Honey Bee Species Through High Performance Computing: A Research Proposal
Bibliographic record
Abstract
When honey bees face obstacles to their survival, so do we humans, because honey bees pollinate 80 per cent of the worlds crops and contribute to almost 10 per cent of our food supply. In order to help honey bees, students created a simulation to measure the effects nature and humans have on their survival. Many of the obstacles are measurable by high performance computers, and such research could help us find solutions to the extinction of the world’s greatest pollinators. Quand les abeilles facent à des obstacles à leur survie, donc nous (les humains) aussi luttent avec des difficultés, car les abeilles pollinisent 80 pour cent des cultures mondiales et contribuent à près de 10 pour cent de notre approvisionnement alimentaire. Afin d'aider les abeilles, les étudiants créé une simulation pour mesurer les effets de la nature et les humains ont sur leur survie. Plusieurs obstacles sont mesurables par des ordinateurs de haute performance, et de telles recherches pourraient nous aider à trouver des solutions à l'extinction des plus grands pollinisateurs de la planète.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".