MétaCan
Menu
Back to cohort
Record W4414439303 · doi:10.1680/jwarm.24.00049

Modern method in waste management in Tehran

2025· article· en· W4414439303 on OpenAlexaff
Mojgan Shajari, Mohammad Reza Haghparast

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Waste and Resource Management · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsNuclear Waste Management Organization
Fundersnot available
KeywordsPlan (archaeology)BrainstormingCleaner productionMunicipal solid wasteWaste collectionWork (physics)

Abstract

fetched live from OpenAlex

This research aims to compare waste collection methods and introduce a modern method of source separation, which has been implemented in 22 districts of Tehran. This project has utilised field methods, face-to-face training, questionnaires, and brainstorming sessions. The Nomand’s plan was implemented in 8, 13, and 14 regions, and the citizens received the plan well. In the following, Nomand’s plan was implemented in the 20 regions, and the results showed that in areas of the 20 regions, participation rates in the two areas were higher than in other places. At the beginning of the Nomand’s plan, the highest amount of waste collected in 20 regions was 391 kg, and during the plan, the highest amount of waste collected was recorded in 20 regions, equal to 1238 kg. Collecting dry waste directly from its source is highly effective. This method will yield successful results if the true value of dry waste is compensated to the individuals. Authorities must address this issue. The Nomad’s plan was first implemented in Tehran, allowing citizens to easily deliver their dry waste to Waste Organisation experts. This plan aims to decrease pollution and lower transportation costs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.632
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.218
Teacher spread0.213 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Civil Engineers - Waste and Resource ManagementSame topicMunicipal Solid Waste ManagementFrench-language works237,207