Peat coring and sampling techniques used at Geological Survey of Canada (1993-2003)
Bibliographic record
Abstract
Most peatlands in Canada take the form of bog or fen but some swamps and marshes have sufficient accumulations of organic materials (40 cm or more) to be classed as peatlands. Most environmental, ecological, or biogeochemical studies of peatlands require stratigraphic sampling and sub-sampling. Peatlands are water-saturated and, over large areas of Canada, they are permafrost-bearing and isolated. Hence, core collection presents many challenges. When choosing the sampling site, it is wise to first use a soil probe with sufficient extensions to test the depth and character of the peat accumulation. For past peatland projects at GSC, cores were collected at depth from permafrost-bearing peat using the CRREL coring kit. A continuous undisturbed core was produced in segments of up to 20 cm from one drilled hole. The segments were retrieved from the hole using a core catcher. Use of the CRREL device took at least 2 people and was difficult. As soon as the motor on the CRREL device stopped, water from the melting of the ice around the cutting head quickly began to refreeze and, if not pulled up immediately, the head was stuck (on one occasion permanently) in the hole. To collect at depth in unfrozen peatlands, the Macaulay corer, referred to also as the modified Russian borer, was effective and not too difficult to use. It is a chambered-type side filling sampler with a T-handle and 1 m long extension rods. Continuous cores were collected in 50 cm segments to the contact with mineral sediment. After the first 1 or 2 extension rods were added, 2 or more people were needed to pull the corer up from the hole. Neither the CRREL work nor the Macaulay were useful for sampling peat at or near the surface. Above the water table in an unfrozen peatland or above permafrost in frozen ones, it worked best to cut out blocks of peat using a large butcher knife and small clippers. If a continuous core of surface peat materials was needed, a Wardenaar-style corer was used for the uppermost 90 cm.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".