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Record W2129112673 · doi:10.5555/1351542.1351865

A simulation-based framework for quantifying the cold regions weather impacts on construction schedules

2007· article· en· W2129112673 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

VenueWinter Simulation Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBaseline (sea)ScheduleCold weatherComputer scienceScheduling (production processes)Operations researchMeteorologyEngineeringOperations managementGeography

Abstract

fetched live from OpenAlex

In cold regions, weather severity has a major impact on construction activities carried out in the open, leading to significant deviations from baseline schedules. Faced with weather uncertainty, setting up the project baseline schedule, against which performance will be measured, can be challenging. Construction planners often depend on their personal judgment and experience to account for the scheduling impact of cold weather. Due to variation in planners' experiences, the regions where their experience was acquired, and the time of year when the planned project is to be executed, the result can be widely differing plans between planners. This paper presents a structured simulation-based approach that attempts to account for the cold weather impacts on project schedule. This approach relies on generating weather sequences similar to the existing historical weather data for the project's geographical region. The impact on productivity and project schedule can then be modeled, leading to consistent schedules.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.623

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 head0.058
GPT teacher head0.315
Teacher spread0.257 · 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