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Record W7029553614

Laboratory Evaluation of Cemented Paste Backfill Shear Strength Development Up to 600 kPa

2022· dissertation· W7029553614 on OpenAlexfundno aff

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsShearing (physics)Compressive strengthShear strength (soil)Shear (geology)Direct shear testStrength of materialsLaboratory test
DOInot available

Abstract

fetched live from OpenAlex

Cemented Paste Backfill (CPB) is increasingly favoured as a backfill method in underground mining. The mechanical behaviour of CPB is critical for a rational mix design. This study focused on shear strength development of CPB using a laboratory vane apparatus, complemented by other assessments of CPB’s properties including set times, and changes in Electrical Conductivity. The effects of vane insertion and shearing rate were studied. A comparison was made between the laboratory vane shear strength (LVSS) and unconfined compressive strength (UCS). A constant relationship between LVSS and UCS was found to depend on mix design, but they did not follow the assumption of undrained clay behaviour. The experimental results suggest that the laboratory vane test can be used reliably on relatively soft materials, thereby giving a shear strength index for CPB. However, more work is required to determine how this measured vane shear strength is best used for backfill 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.311
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes1
Has abstractyes

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