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Use of Stereoscopy for Dam Break Flow Measurement

2004· article· en· W2002404645 on OpenAlex
J. Eaket, Faye Hicks, A. E. Peterson

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Hydraulic Engineering · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStereoscopyTracking (education)GeologyFlow (mathematics)Computer visionPoint (geometry)Channel (broadcasting)Particle (ecology)Artificial intelligenceComputer scienceRemote sensingGeometryMathematics

Abstract

fetched live from OpenAlex

This investigation explored the applicability of video stereoscopy for the measurement of unsteady open channel flows. Specifically, the three-dimensional water surface profile and flow velocities associated with scale model dam break events were considered. Stereo images of the unsteady flow event were obtained using three, time-synchronized, video cameras situated above the tank such that, at all times, the area of interest was captured by at least two of the three cameras. To establish a point of reference from image to image, floating plastic tracking particles were placed on the water surface. The three-dimensional coordinates of the particles were then calculated using the camera positions and the locations of the individual plastic particles in the stereo images. Particle velocities were also deduced from the analysis of consecutive images. Based on this preliminary investigation we conclude that video stereoscopy is a promising method for measuring highly dynamic flows.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score0.333

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 head0.024
GPT teacher head0.216
Teacher spread0.192 · 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