GRANULAR-AGGREGATE MAPPING IN THE RANDOM ISLAND AND TUG POND MAP AREAS (NTS MAP AREAS 2C/4 AND 2D/1) EASTERN NEWFOUNDLAND
Bibliographic record
Abstract
Granular-aggregate mapping in 2012 took place in the Random Island (NTS 2C/4) and the Tug Pond (NTS 2D/1) map areas. Granular-aggregate mapping is part of a continuing regional survey to locate aggregate deposits, to alleviate construction problems resulting from aggregate shortages and poor-quality aggregate. Several granular deposits were identified as suitable for construction aggregates. These are located near Shoal Harbour Pond, Southwest River, Dark Hole Brook, Black River Pond, Tug Pond, Deep Bight River, and in the Western Pond–Frost Pond–Maxs Pond areas. All the deposits are believed to contain clean sources of gravel and sand, and range in volume from about 7 000 to 5 000 000 m 3 of aggregate. Some deposits are within 1 km of major road access points. Other deposits are less accessible, or are too small to recommend as potential resource areas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".