Rate-controlled cone penetration tests in permafrost
Bibliographic record
Abstract
Cone penetration tests (CPTs) were carried out in the summers of 1999 and 2000 in a permafrost mound near Umiujaq, in northern Quebec, Canada, to study the cryostratigraphy and assess the creep behaviour of permafrost. A new linear pushing system using an actuator technology was specifically designed and developed to accurately control the penetration rate of the cone in the permafrost. This system has a load capacity of about 113 kN at a maximum penetration rate of 1.5875 cm/s and a stroke of 120 cm and can provide constant penetration rates as low as 4 × 106 cm/s. It can be disassembled in pieces for easy hand transport and use in remote locations. Two different types of CPT were performed in the permafrost mound: stratigraphic profiling and creep test. The first type is a quasi-static CPT at a penetration rate of 0.1 cm/s, providing a stratigraphic profile of permafrost in terms of the measurement of penetrometer sensors as a function of depth. The second type is a series of quasi-static CPTs at incremental rates of penetration, from 104 to 102 cm/s, carried out in a homogeneous layer to study the creep behaviour of permafrost. Five distinct zones (unfrozen and frozen active layer, permafrost, cryotic but unfrozen ground, and perennially noncryotic ground) can be identified in the stratigraphic profiles. The creep exponents calculated from the creep tests range from 12 to 35 for the ice-poor frozen active layer and from 4 to 11 for the ice-rich permafrost. Key words: cone penetration test, permafrost, rate-controlled, creep behaviour, cryostratigraphy.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".