Bibliographic record
Abstract
n' after a page number indicates the endnote number.A accessibility 36, 249 as barrier to aging well 47, 48 infrastructure accessibility 18, 105 lack of 27, 36 MD users 31, 33-7 Nova Scotia 191-2 parking accessibility 34 recommendations 34-5, 36-7, 47, 77 AFC (Age-Friendly City, WHO) 4-9, 115, 133, 223 Age-Friendly City Framework 5, 89, 110 age-friendly domains and key factors 5 apolitical nature 7 budget and funding 8, 9 City of Toronto 8 critiques 6-7, 128 framework 5-6 government and 4, 5-6, 7, 249 history 4-5 Indigenous Canada 199, 201, 223-4, 229-30, 234-6 leadership 8-9 Ontario 7, 8, 223 Ontario: Finding the Right Fit 223-4, 229-30 policy implementation 7 politics and 8 recommendations 9, 128 success 8-9 voluntary policy 7, 8 WHO Age-Friendly City status 6, 74, 113, 169 ageism 46, 77, 94, 111-12, 137, 253 anti-ageism 48, 102-3, 112 definition 102 as greatest challenge 254LGBTQ community and frail older adults 94, 102-3, 250 rural Canada 146, 158, 169 women
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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".