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Record W1539612700 · doi:10.5772/32508

Separate Collection Systems for Urban Waste (UW)

2012· book-chapter· en· W1539612700 on OpenAlexaboutno aff
Antonio Gallardo Izquierdo, Mriam Prades, Mara Dd, J Maldonado-Hodar Francisco

Bibliographic record

VenueInTech eBooks · 2012
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceWaste managementEngineering

Abstract

fetched live from OpenAlex

Various solutions for separate collection have emerged in order to fulfil all the objectives stipulated by legislation and local authorities in various countries for the recovery of municipal waste. Germany uses the Dual System, in which packaging waste is collected separately by a network belonging to companies selling consumer products. Separation of the organic fraction is mandatory in the Netherlands. In France and Spain, the governments are the responsible for designing mechanisms to implement the separate collection of packaging waste and achievement of the goals stipulated by European legislation. In the USA and Canada in the early 1990s, many cities with residential areas containing singlefamily homes began pilot schemes for separate collection, with waste separated at source into two, three and four fractions.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.011

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 head0.028
GPT teacher head0.243
Teacher spread0.215 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations11
Published2012
Admission routes1
Has abstractyes

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