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Record W4381621773 · doi:10.31315/psb.v4i1.8840

Pengaruh Limbah Cair Industri Batik Terhadap Status Mutu Airtanah di Kalurahan Ngentakrejo, Kapanewon Lendah, Kabupaten Kulonprogo

2023· article· id· W4381621773 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

VenueProsiding Seminar Nasional Teknik Lingkungan Kebumian SATU BUMI · 2023
Typearticle
Languageid
FieldComputer Science
TopicEdcuational Technology Systems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsEnvironmental science

Abstract

fetched live from OpenAlex

Daerah Desa Ngentakrejo Kecamatan Lendah, Kabupaten Kulon Progo memiliki beberapa industri batik yang salah satunya diketahui tidak melakukan pengolahan terhadap air buangan limbah cair sehingga berpotensi menimbulkan pencemaran airtanah di sekitarnya. Tujuan dari penelitian yang dilakukan adalah menganalisis status mutu air tanah dengan metode Indeks Pencemaran. Metode pengumpulan data (kondisi geofisik kimia) yang digunakan adalah metode survei lapangan dan pemetaan. Penentuan status mutu air tanah dilakukan dengan menggunakan metode Indeks Pencemaran. Analisis kualitas air tanah dan air limbah dilakukan dengan metode uji lab. Pengambilan sampel air tanah dilakukan dengan metode purposive sampling sesuai arah aliran airtanah. Hasil dari penelitian diketahui status mutu airtanah di lokasi penelitian memiliki nilai 3,459 ; 3,972 dan 4,446 yang termasuk kategori tercemar ringan. Limbah cair industri batik yang diuji terbukti melebihi baku mutu pada parameter BOD dan TSS.Kata Kunci: Airtanah; Limbah Cair Batik; Pencemaran Air; Status Mutu

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.007
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0050.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0000.002

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 head0.045
GPT teacher head0.281
Teacher spread0.236 · 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