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Record W4401899229 · doi:10.20527/jtb.v10i02.200

Analisis Neraca Air Sub Das Martapura

2021· article· id· W4401899229 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

VenueJurnal Teknologi Berkelanjutan · 2021
Typearticle
Languageid
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

Sungai Martapura merupakan Sungai yang melintasi Kabupaten Banjar dan Kota Banjarmasin yang termasuk dalam DAS. Sungai ini bermuara ke Sungai Barito yang bagian hulunya merupakan persimpangan antara Sungai Riam Kiwa dan Sungai Riam Kanan. Sub DAS E merupakan bagian dari Sub DAS Martapura. Neraca air merupakan analisis hasil pendekatan terhadap nilai-nilai proses hidrologi yang terjadi di lapangan. Metode Neraca Air (Water Balance) membandingkan antara ketersediaan air dengan kebutuhan air yang ada. Tujuan dari penelitian ini adalah tersedianya perhitungan neraca air yang dapat dijadikan dasar untuk menghasilkan konsep alokasi air dalam bentuk rencana penyediaan air tahunan. Analisa ketersediaan air didasarkan pada perhitungan debit aliran dasar hasil perhitungan FJ Mock. Didapatkan hasil perhitungan Neraca Air pada debit tahun kering (80%) mengalami surplus.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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