Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Peter Street Basin is a large (about 60m long) trapezoid-shaped concrete pool connected to Lake Ontario. It was abandoned, and filled with so much garbage that the water was often not even visible under the layers of garbage, with its ownership being as murky as its waters. It is unclear who actually owns it, despite it being part of a marked park that consists almost solely of the Basin itself. Peter Street Basin is surrounded by luxury rental apartments facing what was a garbage dump rife with the terrible stench of dead rats, rotting raccoon corpses, condoms, tampons, etc., and was also a dumping ground for discarded appliances. We undertook a 3-year long project to clean up the Basin, removing thousands of pounds of garbage and cleaning the water to the point where it now meets safe swimming water-quality standards by more than a factor of ten. We propose “MoBase” = Mobility Basin = Base for accessibility, research, and teaching, including paddleboard rentals, and an outdoor teaching and research lab that we call the “TeachBeach”. It is our intent that MoBase will serve as a role-model for freshwater stewardship, advocacy, and outreach to the other Great Lakes and from Atlantic to Pacific coasts and beyond. We envision MoBase as the latest addition to other water-based entities located within a 150m (500ft) radius (20 seconds on-foot) providing a “campus” of safety and accessibiity we name Queens Quay Mobility corridor/campus/cluster/base... (abbrev. “MoQuay”).This article appeared in Mersivity/Waterhci-2025, December Edition, on pages 11-20.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.035 | 0.010 |
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 it