On the public citation graph

An integrated GNN-LLM framework for automated task-level safety risk assessment leveraging retrieval-augmented scenario generation

https://doi.org/10.2139/ssrn.6532324
0 signed · 18 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.autcon.2018.03.022openalex-snapshot
Safety leading indicators for construction sites: A machine learning approach
inferredcites →https://doi.org/10.1016/j.autcon.2018.12.016openalex-snapshot
Construction site accident analysis using text mining and natural language processing techniques
inferredcites →https://doi.org/10.1016/j.autcon.2019.102974openalex-snapshot
Machine learning predictive model based on national data for fatal accidents of construction workers
inferredcites →https://doi.org/10.1016/j.autcon.2020.103089openalex-snapshot
Deep learning and network analysis: Classifying and visualizing accident narratives in construction
inferredcites →https://doi.org/10.1016/j.autcon.2020.103145openalex-snapshot
Automatically learning construction injury precursors from text
inferredcites →https://doi.org/10.1016/j.autcon.2020.103310openalex-snapshot
Knowledge graph for identifying hazards on construction sites: Integrating computer vision with ontology
inferredcites →https://doi.org/10.1016/j.autcon.2023.105102openalex-snapshot
Construction safety predictions with multi-head attention graph and sparse accident networks
inferredcites →https://doi.org/10.1016/j.eswa.2014.10.009openalex-snapshot
Decision tree analysis of construction fall accidents involving roofers
inferredcites →https://doi.org/10.1016/j.heliyon.2023.e13389openalex-snapshot
Data mining of the essential causes of different types of fatal construction accidents
inferredcites →https://doi.org/10.1016/j.jlp.2011.03.004openalex-snapshot
Risk analysis and assessment methodologies in the work sites: On a review, classification and comparative study of the scientific literature of the period 2000–2009
inferredcites →https://doi.org/10.1016/j.ssci.2011.01.003openalex-snapshot
Occupational risk assessment in construction industry – Overview and reflection
inferredcites →https://doi.org/10.1016/j.ssci.2014.10.006openalex-snapshot
Overview and analysis of safety management studies in the construction industry
inferredcites →https://doi.org/10.1016/j.ssci.2015.11.020openalex-snapshot
Predicting safety behavior in the construction industry: Development and test of an integrative model
inferredcites →https://doi.org/10.1016/j.ssci.2019.06.034openalex-snapshot
Predicting types of occupational accidents at construction sites in Korea using random forest model
inferredcites →https://doi.org/10.1016/j.ssci.2020.104616openalex-snapshot
Predicting and analyzing injury severity: A machine learning-based approach using class-imbalanced proactive and reactive data
inferredcites →https://doi.org/10.1145/3447548.3467350openalex-snapshot
Are we really making much progress?
inferredcites →https://doi.org/10.3390/buildings15183379openalex-snapshot
Large Language Models for Construction Risk Classification: A Comparative Study
inferredcites →https://doi.org/10.3390/ijerph17228395openalex-snapshot
Developing an Ensemble Predictive Safety Risk Assessment Model: Case of Malaysian Construction Projects
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.