5. Creating a Master Plan for Parrot's Bay Conservation Area
Bibliographic record
Abstract
Over the past 20 years the Cataraqui Region Conservation Authority (CRCA) has been purchasing the area surrounding Parrot’s Bay in hopes to conserve wildlife habitat. By collaborating with CRCA, our aim is to gain insight through research of the surrounding area and examination of case studies from other conservation areas, to create the most effective conservation plan for Parrot’s Bay. The goal is to minimize the negative impacts of recreational trails and activities on wildlife within the conservation area. Such impacts include the disruption of migratory patterns, the relocation of animals into the area and fragmentation of habitat due to trail location. By identifying key species and their migration patterns within Parrot’s Bay we will design a plan that will cater to the species inhabiting the land while minimizing the anthropogenic effects on the natural habitats. Another key factor in the design of Parrot’s Bay is the issue of urban sprawl, which is very prevalent in this region. Our project will seek to minimize the effects of urban sprawl on the conservation area through the use of land planning and management policies. The outcome we hope to achieve is the formation of a master plan for Parrot’s Bay, to link all acquired land in order to prioritize and manage wildlife species most effectively.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.006 |
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".