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Record W2585208949 · doi:10.1002/2016jf004018

Spatial variability of active layer thickness detected by ground‐penetrating radar in the Qilian Mountains, Western China

2017· article· en· W2585208949 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2017
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsCarleton University
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsGround-penetrating radarGeologyChinaRadarRemote sensingSeismologyLayer (electronics)GeomorphologyGeodesyGeographyArchaeologyMaterials scienceComposite materialEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

Abstract The active layer plays a key role in geomorphic, hydrologic, and biogeochemical processes in permafrost regions. We conducted a systematic investigation of active layer thickness (ALT) in northeastern Qinghai‐Tibetan Plateau by using ground‐penetrating radar (GPR) with 100 and 200 MHz antennas. We used mechanical probing, pit, and soil temperature profiles for evaluating ALT derived from GPR. The results showed that GPR is competent for detecting ALT, and the error was ±0.08 m at common midpoint co‐located sites. Considerable spatial variability of ALT owing to variation in elevation, peat thickness, and slope aspect was found. The mean ALT was 1.32 ± 0.29 m with a range from 0.81 to 2.1 m in Eboling Mountain. In Yeniu Gou, mean ALT was 2.72 ± 0.88 m and varied from 1.07 m on the north‐facing slope to 4.86 m around the area near the lower boundary of permafrost. ALT in peat decreased with increasing elevation at rates of −1.31 m/km (Eboling Mountain) and −2.1 m/km (Yeniu Gou), and in mineral soil in Yeniu Gou, the rate changed to −4.18 m/km. At the same elevation, ALT on the south‐facing slope was about 0.8 m thicker than that on the north‐facing slopes, while the difference was only 0.18 m in peat‐covered area. Within a 100 m 2 area with a local elevation difference of 0.8 m, ALT varied from 0.68 m to 1.25 m. Both field monitoring and modeling studies on spatial ALT variations require rethinking of the current strategy and comprehensive design.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.354
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it