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Record W2994184113 · doi:10.32672/jse.v5i1.1597

Evaluasi Pengelolaan Limbah Bahan Berbahaya dan Beracun (B3) di PT. X

2019· article· en· W2994184113 on OpenAlexaff
Siti Amalia Fajriyah, Eka Wardhani

Bibliographic record

VenueJurnal Serambi Engineering · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHazardous wasteWaste managementFlammable liquidEnvironmental scienceHousehold hazardous wasteMunicipal solid wasteEngineeringMobile incineratorWaste collection

Abstract

fetched live from OpenAlex

Disposal of the residual production of an industry containing hazardous and toxic materials can have a negative impact on the environment and human health. PT. X The Spinning Division is a company engaged in spinning yarn that produces hazardous waste in the production process, especially in machine maintenance. The hazardous waste produced is in the form of used TL lamps, contaminated cotton waste, used oil, and used hazardous packaging. The hazardous waste is toxic, corrosive and flammable. The purpose of this study is to compare the existing conditions of hazardous waste management with applicable regulations. The study was conducted by directly observing the existing conditions and scoring using Guttman scale. The research variables include sorting, storing, collecting, transporting, utilizing, processing and landfill hazardous waste. The results showed that the management of hazardous waste in PT. X The Spinning Division gets a score 34.3% which is categorized “Poor”.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0270.003

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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations18
Published2019
Admission routes1
Has abstractyes

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