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Record W7080187892

Rollen för negativa utsläpp för att bidra till att klara Parisavtalets långsiktiga mål

2023· article· en· W7080187892 on OpenAlexaff

Bibliographic record

VenueDiva portal (Dalarna University Library) · 2023
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsGreenhouse gasAtmosphere (unit)Carbon dioxideCarbon dioxide removalClimate changeCarbon fibersOvershoot (microwave communication)Global warming
DOInot available

Abstract

fetched live from OpenAlex

This report delves into the multifaceted dimensions of carbon dioxide removal methods. The report discusses the role of carbon dioxide removal methods in contributing to attaining the long-term goal of the Paris Agreement and investigates best practices in the implementation of the collaborative instruments under Article 6 for their incentivisation and scaling. The present climate policy and actual decision-making are still centred on achieving net-zero carbon emissions but the long-term challenge is the inevitable reversal of the overshoot, requiring carbon removal to outpace residual emissions, leading to net negative emissions globally. The report discusses the need to assign responsibility for climate overshoot reversal in order to guarantee the viability of a global net-negative GHG economy. The report analyses and proposes ways to address risks associated with carbon removal, including mitigation deterrence, that carbon removed from the atmosphere might be re-released, carbon-leakage effects, and challenges related to monitoring mitigation outcomes. It offers recommendations based on these deliberations.

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)0.000
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.182
Teacher spread0.170 · 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.

Study designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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