Bibliographic record
Abstract
Hall. The Public Forum was hosted by City Councillor John Filion, Chair of the Toronto Board of Health, and Councillor Paula Fletcher, Chair of the Parks & Environment Committee. The purpose of the Forum was to increase dialogue between Metrolinx and the community on measures being taken to address health and environmental concerns about proposed expansions and to enable Metrolinx to consider additional input from the public. Many issues and concerns were raised by participants in the Public Forum, the most common of which were: a) diesel exhaust will add to the health burden on local and vulnerable populations; b) the diesel train expansion does not benefit the local community; c) diesel locomotives are old, polluting technology; and d) electrification has not been sufficiently considered to date. This report discusses and comments on the key issues and questions that arose during the Public Forum and recommends that it be forwarded to Metrolinx for their consideration and to address the comments and concerns that are identified in this report. A second public forum will be organized to discuss the draft results of the GO System Electrification Study once they are available. The Medical Officer of Health and Metrolinx have agreed to participate in this second forum.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.724 | 0.468 |
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".