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Record W4285377583 · doi:10.32663/georaf.v6i1.1903

Studi Karakteristik lahan pada kawasan rawan longsor di Kecamatan Koto Parik Gadang Diateh Kabupaten Solok Selatan

2021· article· en· W4285377583 on OpenAlexaff
Nina Ismayani, Ferawati Ferawati, Hary Febrianto

Bibliographic record

VenueJurnal Georafflesia Artikel Ilmiah Pendidikan Geografi · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsWiLAN (Canada)
FundersUniversitas AndalasInstitut Pertanian BogorUniversitas Negeri Padang
KeywordsLandslideHazardForestryGeographyLand useHydrology (agriculture)Hazard analysisEnvironmental scienceGeologyGeomorphologyGeotechnical engineeringCivil engineeringEngineeringEcology

Abstract

fetched live from OpenAlex

This study aims to describe the characteristics of land in a landslide-prone area in Koto Parik Gadang Diateh, South Solok Regency. The design of this research is descriptive survey method, primary data obtained in the field and laboratory, and secondary data from references and literature analysis. This research technique is stratified random. Data analysis is land characteristics descriptively and tabulated criteria for determining physical phenomena in determining the level of landslide hazard. The results of the study explain: the characteristics of the land area there are 7 soil units, the level of landslide hazard, names: (1) the low level of landslide hazard contained in the VI.Qpt.I.Pem.Gleih land unit. (2) The level of landslide hazard is in the land units V3.Mip.III.Pem.Gleih and V4.Pckm.IV. Ht. Gleih. (3) a high level of landslide hazard is found in the V4.Mpip.IV land unit. Pem.Gleih, V4.Qal.IV.Pem.V, V4.Qube.IV. Pem.Gleih and V4.Pckm.V. Pkb.Gleih.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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 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
Published2021
Admission routes1
Has abstractyes

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