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Record W4393780946 · doi:10.5281/zenodo.6845099

Geometric Control on Seismic Rupture and Earthquake Sequence along the Yingxiu-Beichuan Fault with Implications for the 2008 Wenchuan Earthquak

2022· dataset· en· W4393780946 on OpenAlexaff
Lei Zhang, Yajing Liu, Duo Li, Hongyu Yu, Changrong He

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsGeological Survey of CanadaMcGill University
Fundersnot available
KeywordsGeologySeismologySequence (biology)Fault (geology)Normal fault

Abstract

fetched live from OpenAlex

A 65000 years seismic sequence is numerical simulated using TriBIE on the unplanar fault plane with variation normal stress. The code is now available in an open-source Git-hub project, https://github.com/daisy20170101/TriBIE/tree/normal_stress_variation. The modeling will output the bianary format files of normal stress, fault slip velocity, shear stress, slip during the interseismic loading and coseismic rupture stage, respectively. Since it is impossible to output the data at every time step, especially for the large-scale fault model. Thus, during the interseismic loading, we set a constant time interval to output data and the t-inter-***.dat file will record every time, when the data is outputted. During coseimic rupture, t-cos-**.dat file records time of outputing data. So, the size of t-inter-**.dat and t-cos-**.dat file is the number of outputting steps.The fault plane is discretized into 3,1440 elements and the simulation is carried out by parallel computing on 6 servers with 120 CPUs . Each CPU will dispose data of 262 elements.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.164
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.033
GPT teacher head0.233
Teacher spread0.201 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

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