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Record W2981644229 · doi:10.4095/226354

Probabilistic seismic hazard maps for Albania

2004· report· en· W2981644229 on OpenAlexaffabout
Shyqyri Aliaj, J Adams, S Halchuk, E. Sulstarova, V. Peçi, Betim Muço

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsProbabilistic logicHazardSeismologySeismic hazardGeologyComputer scienceGeographyArtificial intelligence

Abstract

fetched live from OpenAlex

Albania is a Balkan country with high rate of seismicity, and earthquake risk reduction has been an important, on-going socioeconomic concern. We adapt the experience and methods used for Canadian seismic hazard maps to present, for the first time, probabilistic spectral hazard maps for Albania. A revised catalogue of Albanian earthquakes, from 58 A.D. to 2000, with magnitude Ms>4.5 in the region between 39/N and 43/N and 18.5/E and 21.5/E was used in this study. Ten seismic source zones are used to define the seismicity. We have used the Ambraseys et al. (1996) strong ground motion relations for rock to produce 5% damped spectral acceleration values at 0.2, 0.5, 1.0 and 2.0 seconds (as well as peak ground acceleration) for a return period of 0.0021 per annum (equivalent to a 10% chance of non-exceedence in 50 years). The four spectral parameters maps will allow the construction of site-specific Uniform Hazard Spectra for all of Albania, and are suggested as the basis of the next version of the KTP-N.2-89 Technical Aseismic Regulations to improve earthquake-resistant design code in Albania.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.249
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations60
Published2004
Admission routes2
Has abstractyes

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