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Record W2965098057

Le emissioni di metano nelle reti di gas naturale

2014· article· it· W2965098057 on OpenAlexaboutno aff
L. Celenza, Marco Dell’Isola, Giorgio Ficco

Bibliographic record

VenueCINECA IRIS Institutial research information system (Parthenope University of Naples) · 2014
Typearticle
Languageit
FieldEnvironmental Science
TopicEnvironmental Policies and Emissions
Canadian institutionsnot available
Fundersnot available
KeywordsPhysics
DOInot available

Abstract

fetched live from OpenAlex

Il metano è considerato responsabile per circa l’8% dell’e" etto serra in quanto, malgrado le ridotte quantità rispetto ad altri gas serra come l’anidride carbonica, presenta un potenziale di riscaldamento globale circa 20 volte maggiore rispetto a quest’ultima. Numerosi studi dimostrano che una delle principali fonti di emissione di metano è rappresentata dalla filiera del gas naturale, ovvero produzione, trasporto-stoccaggio e distribuzione. Molti Paesi, come la Spagna, il Canada, la Germania e la Grecia, hanno aumentato le proprie emissioni di gas metano fino al 10% tra il 1990 e il 2002, e di conseguenza la concentrazione di metano in atmosfera continua ad aumentare con un tasso medio annuo superiore all’1%. Tali emissioni costituiscono, oltre a uno spreco energetico e un elemento di impatto ambientale, un fattore di disequilibrio nel bilancio di massa delle reti. Per questo, in numerose reti di trasporto e distribuzione del gas naturale sono state incentivate e programmate campagne e studi per la ricerca e la stima delle perdite e per la loro riduzione.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.027
GPT teacher head0.246
Teacher spread0.219 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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