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Record W1637021372 · doi:10.31227/osf.io/6nzka

PEMANFATAN SISTEM INFORMASI GEOGRAFIS (SIG) UNTUK PEMETAAN IMBUHAN AIRTANAH DAN KERENTANAN AIRTANAH DI KAWASAN KARST (STUDI KASUS DI KECAMATAN PALIYAN DAN KECAMATAN SAPTOSARI, KABUPATEN GUNUNGKIDUL)

2017· article· id· W1637021372 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageid
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhysicsForestryGeography

Abstract

fetched live from OpenAlex

Pemetaan imbuhan airtanah dan kerentanan airtanah merupakan bagian yang penting dalam upaya pengelolaan kawasan karst. Penelitian ini dilakukan di sebagian Kawasan Karst Gunungsewu di Kecamatan Paliyan dan Kecamatan Saptosari, Kabupaten Gunungkidul. Penelitian ini bertujuan untuk mengetahui sebaran spasial tingkat imbuhan airtanah dan tingkat kerentanan pencemaran airtanah. Metode yang digunakan dalam penelitian ini adalah APLIS yang memanfaatkan sistem informasi geografis (SIG) dengan analisis tumpangsusun (overlay). Variabel yang digunakan dalam penelitian ini adalah ketinggian tempat (elevasi) dari permukaan laut, kemiringan lereng, litologi (batuan), zona infiltrasi, dan tanah. Hasil penelitian menunjukkan bahwa nilai imbuhan airtanah dan tingkat kerentanan airtanah meliputi tingkat sangat rendah sampai dengan tinggi.

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.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0090.003
Scholarly communication0.0030.002
Open science0.0060.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.004

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 head0.024
GPT teacher head0.231
Teacher spread0.207 · 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

Quick stats

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicGeological and Geophysical StudiesFrench-language works237,207