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Deformation analysis: the Caspary approach

2020· article· en· W3013889879 on OpenAlexaboutno aff
Veton Hamza, Tomaž Ambrožič, Bojan Stopar

Bibliographic record

VenueGeodetski vestnik · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsDeformation (meteorology)GeologyOceanography

Abstract

fetched live from OpenAlex

Deformation analysis: the caspary approachIn this paper, the theoretical background of the Caspary method of geodetic deformation analysis is described and implemented in a simulated geodetic network in which two epochs of measurements are used.The Caspary approach foresees congruence testing of the geodetic network, the determination of the stable points between two analysed epochs, the transformation of the geodetic network using S-transformation, the calculation of displacements, and, in the last step, the graphical presentation of displacement vectors.Results obtained from the presented example are similar to those presented in the Hannover, Karlsruhe, Delft, Fredericton, München, and robust methods.V članku je opisan postopek Caspary, ki je eden izmed postopkov deformacijske analize.Značilnosti tega postopka so testiranje skladnosti geodetske mreže, določitev stabilnosti točk med dvema terminskima izmerama, transformacija geodetske mreže s transformacijo S, izračun premikov in grafična predstavitev vektorjev premikov.V članku je najprej podano teoretično ozadje postopka, nato je postopek uporabljen na primeru simuliranih meritev dveh terminskih izmer.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.034
GPT teacher head0.196
Teacher spread0.162 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations6
Published2020
Admission routes1
Has abstractyes

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