Bibliographic record
Abstract
• A few minor editorial changes were suggested. The revised meeting notes will be posted as final on the FASC webpage. • A member inquired if the IESO tracks the number of “hits ” on the FASC meeting minutes that are posted on the IESO website. IESO staff indicated that the IESO only tracks the number of hits on select publications (e.g. Ontario Reliability Outlook). Agenda Item 2: Review of outstanding action items • IESO staff noted the following regarding outstanding action items: o The next Outlook will include a statement about Lennox Generating Station. o The request for the IESO to establish a service that provides market information updates to handheld wireless devices was communicated to IESO Customer Relations. • A member reiterated the need for consistency between the OPA’s and IESO’s assumptions about expected in‐service dates for new projects. • A member asked how many years will be covered in the next Ontario Reliability Outlook (ORO) if there is no coal replacement plan. IESO staff indicated that the study period for the next ORO is unknown at this time. 1 Forecasts and Assessments Standing-Committee of the IESO
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.475 | 0.240 |
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".