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Record W2040473090 · doi:10.1520/jte20140126

Experimental Study of Geobagged Reservoir Siltations for Backfill Applications

2014· article· en· W2040473090 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 Testing and Evaluation · 2014
Typearticle
Languageen
FieldEngineering
TopicMaterials Engineering and Processing
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsStockpileDispose patternGeotextileReuseGeotechnical engineeringEnvironmental scienceCivil engineeringPetroleum engineeringGeologyEngineeringWaste management

Abstract

fetched live from OpenAlex

Abstract Infrastructure sustainability has become a major global concern. Massive reservoir siltations (RS) have seriously disrupted the service of many reservoirs worldwide. The dredged siltations are difficult to stockpile, or dispose of, because of their high water content and soft nature. This study explores a novel approach using RS to produce controlled low-strength materials (CLSM), reinforced with geobags that are used for storage and backfill applications. Test results have shown that, initially, geobags provided a significant contribution to the strength improvement of an RS-based CLSM. However, effective reinforcement appears to be highly dependent upon the type of geotextile and the original strength of the RS-CLSM. The results show a promising solution for reusing reservoir siltations and ensuring a sustainable approach for the mitigation of a silted reservoir.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.190

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.066
GPT teacher head0.331
Teacher spread0.265 · 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