MétaCan
Menu
Back to cohort
Record W2809378179 · doi:10.1016/j.jrmge.2018.05.002

The relationship between diameter and depth of potholes eroded by running water

2018· article· en· W2809378179 on OpenAlexafffund
Shaocheng Ji, Le Li, Wei Zeng

Bibliographic record

VenueJournal of Rock Mechanics and Geotechnical Engineering · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPothole (geology)GeologySedimentGeomorphologyErosionAbrasion (mechanical)Stream powerGrindingBedrockHydrology (agriculture)CanyonAggradationFluvialMineralogyGeotechnical engineeringMaterials science

Abstract

fetched live from OpenAlex

Geometrical analyses of 3930 potholes (3565 fluvial potholes, 237 marine potholes and 128 hillside potholes) from 33 localities in the world reveal a consistent, linear relationship: D = Nh + M, where h and D are, respectively, the depth and mean diameter of pothole, M is a critical size of the initial concavities (seminal potholes) that subsequently underwent growth, and N is the ratio of diameter expanding (wall erosion) speed to deepening (floor abrasion) speed. For the stream potholes, N is generally less than 1 with an average value of 0.67, M varies from 5.3 cm to 40.5 cm with an average of 20 cm, and N decreases gently with increasing M. However, the marine and hillside potholes are generally characterized by N > 1 and M < 10–14 cm, and a power-law relationship N = 4.24M−0.78 (coefficient of determination R2 = 0.75, M is in cm) exists. The results indicate that depth increases faster than diameter for stream potholes due to the larger size of grinding stones (>5–10 cm), while depth increases slower than diameter for marine potholes and hillside potholes due to the smaller size of grinding stones (<5–10 cm). The pothole h-D relationship is nearly independent of rock type. Knowledge of the pothole depth–diameter relationship is useful in a number of contexts, including simulation of hydraulic dynamics, theoretical considerations of erosion, comprehension of channel incision and development of canyons and gorges, and accurate estimation of excavation volume and mechanical strength of potholed bedrock in the design and stability analysis of hydraulic and environmental engineering projects (e.g. dam construction and river dredging).

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.160

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations36
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Rock Mechanics and Geotechnical EngineeringSame topicHydrology and Sediment Transport ProcessesFrench-language works237,207