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Record W2887260765 · doi:10.1186/s40677-018-0103-7

Framework for developing risk to life evaluation criteria associated with landslides in Canada

2018· article· en· W2887260765 on OpenAlex
Renato Macciotta, Lianne Lefsrud

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeoenvironmental Disasters · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaTransport Canada
KeywordsRisk analysis (engineering)Natural hazardRisk assessmentHazardRisk managementLandslideMultiple-criteria decision analysisEnvironmental resource managementComputer scienceEnvironmental planningBusinessEngineeringOperations researchEnvironmental scienceGeographyComputer security

Abstract

fetched live from OpenAlex

The application of quantitative risk assessments is increasing for decision-making in many industries and contexts, with the evaluation of risks against some adopted criteria. In this article, we review risk criteria developed and used for landslide management, in particular criteria associated with risk to life. We show that while this natural hazard is encountered worldwide, the social and regulatory contexts under which evaluation criteria are developed can vary significantly. Thus, the applicability of developed criteria to any specific situation should be assessed before adopting them elsewhere. We describe selected considerations for developing risk evaluation criteria, propose a framework for defining these criteria in Canada, and assess the applicability of previously proposed criteria. Examples of risk criteria development and adoption for new and existing residential developments and for railway employees are presented to illustrate some of these concepts.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.082
GPT teacher head0.361
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