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Record W7071200294

Role of removals in contributing to the long-term goals of the Paris Agreement

2023· other· en· W7071200294 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIIASA PURE (International Institute of Applied Systems Analysis) · 2023
Typeother
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsGreenhouse gasCarbon dioxide removalOvershoot (microwave communication)Climate changeCarbon dioxideAtmosphere (unit)Carbon fibersClimate change mitigationClimate policy
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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.261
Teacher spread0.250 · 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