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Record W2327644145 · doi:10.1061/40940(307)42

Role of Instrumentation in Assessment of Complex Ground Conditions

2007· article· en· W2327644145 on OpenAlexaboutno aff
Vishnu Diyaljee, Murthy Pariti

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
Fundersnot available
KeywordsTerrainInstrumentation (computer programming)Natural (archaeology)Computer scienceCivil engineeringRisk analysis (engineering)EngineeringEnvironmental scienceEnvironmental resource managementConstruction engineeringGeologyGeographyBusinessCartography

Abstract

fetched live from OpenAlex

Slope indicators are commonly used in the evaluation and assessment of ground conditions affecting the highway infrastructure of roads and bridges when historic evidence, airphoto interpretation or judgment suggest that the natural or existing ground might develop instability problems through new construction or natural processes. During the planning and design stages of the re-alignment of two major Primary Highway routes in the Southern Region of Alberta, office studies and site reconnaissance indicated the possibility of slope instability concerns. These concerns warranted the installation of slope indicators to determine their validity and measures, if any, to ensure the suitability of the proposed routes. The slope indicator monitoring concurred with the projections of the site and office reviews allowing decisions to be made to ensure construction of the bridges and highways in stable terrain. These two case studies demonstrate the importance of using instrumentation to validate site observations and opinions, and to allow for sound decision-making.

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)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.011
GPT teacher head0.287
Teacher spread0.276 · 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 designObservational
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
Published2007
Admission routes1
Has abstractyes

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