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Record W2594276414

Metodologija izračuna emisije ugljičnog dioksida

2015· dissertation· sh· W2594276414 on OpenAlexaboutno aff
Dražen Tumara

Bibliographic record

Venuenot available
Typedissertation
Languagesh
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon dioxideGreenhouse gasEnvironmental scienceNitrous oxideKyoto ProtocolMethaneCarbon dioxide equivalentCarbon dioxide removalEnvironmental engineeringChemistryEcology
DOInot available

Abstract

fetched live from OpenAlex

This paper contains an overview of legislative framework related to the problem of climate change, especially the segment important for development of methodology of carbon dioxide emissions calculation. The role of methodology of carbon dioxide emissions calculation in reduction of total emissions as part of the Kyoto Protocol is also defined. One of the responsibilities of the Kyoto Protocol parties is to establish national greenhouse gas inventories which consist of annual calculations of carbon dioxide emissions on a defined area. The principle of carbon dioxide emissions calculation is listed according to the instructions of the Intergovernmental Panel on Climate Change (IPCC) from 2006. The calculation encompasses those emissions which are consequences of anthropogenic activities and are not subject of The Montreal Protocol on Substances that Deplete the Ozone Layer. Those substances are: carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons and perfluorocarbons (HFCs and PFCs), sulphur hexafluoride (SF6) and indirect greenhouse gases: carbon monoxide (CO), nitrous oxides (NOx), non-methane volatile organic compounds (NMVOCs) and sulphur dioxide (SO2). The methodology covers areas of energetics and industrial processes, use of solvents, agriculture, land use, land-use changes, forestry, and waste management. The methodology of carbon dioxide emissions calculation in the field of energetics in Croatia is elaborated in detail. The analysis of movement of carbon dioxide emissions in the field of energetics considering the main social and economic parameters has been made. The analysis includes movements in the past, as well as estimates of carbon dioxide emissions in the near future.

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 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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.508
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1510.010

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 head0.023
GPT teacher head0.291
Teacher spread0.268 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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