MétaCan
Menu
Back to cohort
Record W4381621792 · doi:10.31315/psb.v4i1.8876

Indeks Pencemaran Air Permukaan Pada Kawasan Sumur Tua Minyak Bumi Di Desa Wonocolo, Kecamatan Kedewan, Kabupaten Bojonegoro, Provinsi Jawa Timur

2023· article· id· W4381621792 on OpenAlexaff
Bima Ahmad Fatahillah, Agus Bambang Irawan, Aditya Pandu Wicaksono

Bibliographic record

VenueProsiding Seminar Nasional Teknik Lingkungan Kebumian SATU BUMI · 2023
Typearticle
Languageid
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Penambangan minyak bumi di kawasan sumur tua Desa Wonocolo masih menggunakan teknologi dan peralatan sederhana dan dikerjakan tangan langsung oleh pekerja di lokasi Oleh karena itu, seluruh proses produksi dan distribusi dikendalikan oleh pekerja, yaitu masyarakat lokal dengan latar belakang yang berbeda-beda. Aliran limpasan dari air yang dihasilkan membawa semua potensi sumber pencemaran yang salah satunya adalah minyak lemak ke sungai sebagai aliran. Penelitian ini dilakukan untuk mengetahui status kualitas sungai menggunakan studi baku mutu dan menghitung indeks pencemaran. Metode utama yang digunakan meliputi pengambilan sampel air berdasarkan penggunaan lahan dan intensitas aktivitas sumur minyak. Kemudian dilakukan analisis data sampel di laboratorium untuk mengetahui kualitas air untuk parameter yang akan digunakan dalam perhitungan indeks pencemaran (suhu, pH, minyak lemak, TDS, TSS, COD). Data kualitas air diolah sebagai evaluasi kualitas air dengan menghitung indeks pencemaran. Hasil perhitungan indeks pencemaran menunjukkan sebagian besar potongan sungai dengan nilai diantara 1 sampai dengan 5 dan dikategorikan tercemar ringan.Kata Kunci: Evaluasi Kualitas Air; Indeks Pencemaran; Minyak Lemak; Pengelolaan Lingkungan; Sumur Tua Wonocolo

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, 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 score0.050
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0030.002
Scholarly communication0.0010.002
Open science0.0050.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0000.003

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 head0.036
GPT teacher head0.272
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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProsiding Seminar Nasional Teknik Lingkungan Kebumian SATU BUMISame topicWater Quality Monitoring TechnologiesFrench-language works237,207