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Record W2956117663 · doi:10.36456/waktu.v9i1.897

Setyo Purwoto : Reaktor Pengolah Air Bersih IPTEK Bagi Masyarakat Untuk Daerah Rawan Banjir

2011· article· id· W2956117663 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

VenueWaktu · 2011
Typearticle
Languageid
FieldEngineering
TopicEngineering and Technology Innovations
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsAlkalinityPhysicsChemistryNuclear chemistryEnvironmental chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Air dari genangan banjir sebagai air baku diproses dengan model reactor kompak berupa 3 (tiga) kolom tabung dengan 7 treatment : filterisasi, kemudian dialirkan lewat kran untuk dikontakkan dengan PAC, lalu masuk pada adsorben Zeolit, dilanjutkan dengan exchange resin kation untuk mereduksi kation dari air, kemudian exchange diteruskan ke resin anion. Setelah keluar dari ion exchange, pembubuhan larutan kaporit diinjeksikan guna pembunuhan bakteri. Untuk menghilangkan bau, dilakukan absorbansi menggunakan CA. Dari hasil treatment diperoleh kesimpulan bahwa : Pengolahan air banjir dengan model reactor kompak berupa 3 (tiga) kolom tabung dengan 7 treatment, yaitu : Filter, Poly Aluminium Chloride (PAC), Zeolit, Resin Kation, Resin Anion, Kaporit, dan Karbon Aktip (CA) mampu menurunkan parameter parameter : Warna 8.00 TCU, TDS 142.00 ppm, Kekeruhan 4.80 NTU, Kesadahan Total 586.50 ppm, Kalsium Hardness 305.00 ppm, Magnesium Hardness 51.80 ppm, Klorida 69.00 ppm, Alkalinity P 14.40 ppm, Alkalinity M 194.00 ppm, e-Coli 3.00 sat/100 ml.

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)0.000
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 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: Empirical
Teacher disagreement score0.340
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.016
GPT teacher head0.186
Teacher spread0.170 · 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