2020 Annual report : regreening program
Bibliographic record
Abstract
After 34 years of reclamation activity in the City of Greater Sudbury, the Regreening Program has progressed beyond spreading limestone, fertilizer and grass/legume seed mix.Now that stands of trees are providing canopy cover, it is time to help jump-start the forest development process and address issues outlined in the Biodiversity Action Plan.In 2012, the Regreening Program created 30 temporary employment opportunities, reclaimed 4.1 hectares of barren land at a variety of locations, and planted over 70,000 tree seedlings and almost 50,000 shrubs/understory trees throughout Greater Sudbury.External funding, material and in-kind contributions enabled the implementation of the second year of the 5 Year Plan 2011-2015.A quick summary of accomplishments is shown in the table to the right.VETAC's Urban Landscape sub-committee continued with the eighth annual "Ugliest Schoolyard Contest".The grand prize winner was cole St-Joseph in Sudbury.In all, 17 local businesses, corporations and special interest groups provided funding, materials and offered services to complete the schoolyard regreening project.Corporate funding from Xstrata Nickel in the amount of $75,000 enabled the Committee to extend the prize package to four runner-up schools: .s.Hanmer, Chelmsford P.S., Ernie Checkeris P.S. and Copper Cliff P.S. Schoolyard transformations occurred from late
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".