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Record W242429526 · doi:10.22260/isarc2013/0054

Real-Time Information Support for Strategic Safety Inspection on Construction Sites

2013· article· en· W242429526 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the ... ISARC · 2013
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsChecklistSAFERTask (project management)Control (management)ScheduleConstruction site safetyIdentification (biology)Computer scienceRisk analysis (engineering)Risk managementEngineeringSystems engineeringComputer securityBusiness

Abstract

fetched live from OpenAlex

Real-Time Information Support for Strategic Safety Inspection on Construction Sites Hao Zhang, Seokho Chi Pages 506-513 (2013 Proceedings of the 30th ISARC, Montréal, Canada, ISBN 978-1-62993-294-1, ISSN 2413-5844) Abstract: Site inspection is an important component of safety management system. In current practices, the inspectors evaluate the safety condition on a construction site with the assistance of a standardised checklist. However, the checklist emphasizes on evaluating the implementation of safety management system, but provides limited task-specific check items for assessing whether the individual construction tasks are conducted under safe condition and in a safe manner. To address this issue, the research presented in this paper aims to provide safety practitioners with comprehensive and taskspecific safety information to promote effective risk identification and facilitate strategic risk control during site inspection. Specifically, this research first builds a project-specific safety information database, which stores potential risks and control measures for each construction task. The research team then develops a mobile decision support tool to retrieve information from the database and support safer decision-making on site. The tool supports users in two ways: one is to provide daily risk checklists and risk control strategies to guide step-by-step inspection alongside the project schedule; the other is to let users input any safety-related keywords during the safety inspection process and the tool returns relevant safety information by applying text mining algorithms. It is ongoing research. This paper presents an overall research framework and discusses the progress in developing safety database and data retrieval concepts. The outcome of the project will help enhance safety management practices and reduce possible risky working conditions on a construction site. Keywords: Construction safety inspection, Safety information database, Risk identification, Decision support DOI: https://doi.org/10.22260/ISARC2013/0054 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score0.913

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.052
GPT teacher head0.382
Teacher spread0.330 · 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