MétaCan
Menu
Back to cohort
Record W6926346891 · doi:10.2112/si65-225

Characterization of aeolian streamers using time-average videography

2013· other· en· W6926346891 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

VenueResearch Portal (King's College London) · 2013
Typeother
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsUniversity of GuelphTrent University
Fundersnot available
KeywordsAeolian processesRangingEulerian pathVideographyTemporal scalesCharacterization (materials science)Field (mathematics)

Abstract

fetched live from OpenAlex

Aeolian streamers are common in prototype saltation systems. Streamers are elongate, flow-aligned features within which the concentrations of saltating grains are large relative to a spanwise average concentration. The occurrence of streamers introduces substantial spatial and temporal variability in local sand transport rates. There have been few studies to attempt to characterize the scales of streamers, and the results of those studies have been constrained because they use Eulerian approaches to measure an inherently Lagrangian process. We describe the results from a field experiment designed to address this methodological problem. Field experiments were conducted at Jericoacoara, Ceará, Brazil, in October, 2011. The wind field was measured with ultrasonic anemometers and ruggedized thermal probes. Transport rates were measured using Miniphones, Wenglor Particle Counters, and hose traps. A set of three video cameras, deployed in a triangular array, was used to capture images of streamers. The field of vision for the central, upwind-facing camera was a minimum of about 15 m, expanding to more than 100 m in the middle distance. Video images were time-averaged over a number of intervals, ranging from 1-64 seconds, to establish characteristic path lengths and spatial and temporal scales. The results of these analyses show that this methodological approach is technically sound. Streamer characteristics are center-to-center spacings of about 1 m, length-scales exceeding 50 m and time scales of individual streamers exceeding 64 s.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.521
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.307
Teacher spread0.282 · 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