Bibliographic record
Abstract
The general extent, outlet location at North Bay, and shoreline tilt pattern of glacial Lake Algonquin were established by Spencer, Gilbert, Taylor, and Goldthwait about a century ago. Chapman and Harrison in the mid 1900s identified several eastward outlets and suggested correlations to named water planes as retreating ice lowered Algonquin levels. The present work supplements the meagre available North Bay shoreline elevation data with about 30 new points. Probable Cedar Point, Payette, Sheguiandah, and Korah shorelines are identified; several lower levels have no known outlets. Algonquin shoreline tilts are about 1.4 metres per kilometre. Using Nipissing shoreline elevations for correlation, North Bay data are compared with Sudbury data, showing closely similar trends, but with offsets of Algonquin shorelines probably attributable to errors from 120‑kilometre-long projections and 5 000‑year changes in uplift pattern. Of 24 radiocarbon dates compiled from the literature, 16 are on gyttja. Some of these incorporate old carbon error and require further testing with dates on terrestrial plant macrofossils. Available data remain sparse and require more basic mapping to improve ice-margin/shoreline correlations near the outlet area.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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; 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".