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Record W2138893036 · doi:10.5539/jgg.v5n1p1

Predicting Potential Sites of Covered Karstification

2012· article· en· W2138893036 on OpenAlexvenueno aff
Márton Veress, István Németh, Zoltán Unger, Péter Kéri

Bibliographic record

VenueJournal of Geography and Geology · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicKarst Systems and Hydrogeology
Canadian institutionsnot available
Fundersnot available
KeywordsKarstBedrockGeologyCaveSinkholeGeomorphologyCover (algebra)GeochemistryEarth scienceMining engineeringPaleontologyArchaeologyGeography

Abstract

fetched live from OpenAlex

Our aim was the prediction of karstification. We measured the karstic bedrock and the overlying superficial cover in four areas of Hungary and one area in Romania. One of our tools was the widely used geophysical techniques i.e. VES and multi-electrode method. We also made observations on mountainous, Mediterranean and tropical karsts. In these areas the occurrence of covered karsts, of either syngenetic or postgenetic type, is high. Based on the measured data we determined the conditions under which covered karst formation is possible. For example the conditions that induce syngenetic karstification are: cavities, caves, and shafts within the bedrock, places where the superficial cover is locally thinner, or places where the impermeable beds edge out. An indicator of postgenetic karstification is the presence of lenticular intercalations in the superficial cover (sites of former dolines). Knowing these conditions in any karst area we can readily identify the potential sites where covered karst formation is possible in the near future. If these sites are known, engineering structures can be planned so that potential dangers due to karstification are avoided.

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)0.000
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 score0.007
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2012
Admission routes1
Has abstractyes

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