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Record W6911520053 · doi:10.5281/zenodo.13643213

IAM_COMPACT_D6.6_Report_on_drivers_barriers_and_policy_analysis

2024· article· en· W6911520053 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

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Environmental Impact
Canadian institutionsCanadian Anesthesia Research Foundation
FundersEuropean Commission
KeywordsLeverage (statistics)Key (lock)Work (physics)

Abstract

fetched live from OpenAlex

The goal of this report is to create concrete understanding of mitigation barriers, enablers, and trends toward NDC implementation within inter-related political, social, economic, structural, technological, and individual changes, by performing a deep dive into critical sectors. To this end, the report synthesises the latest available scientific knowledge on mitigation enablers, barriers, and suitable policy options from a universal perspective. The report is based on a document analysis relying on past and upcoming IPCC reports as well as other authoritative sources. It focuses on five key sectors: Industry, Energy, Transport, Buildings, and AFOLU. The global synthesis is intended to inform the analysis of four country case studies, namely Ethiopia, Kenya, Sri Lanka, and Ukraine. It also elaborates policy options available to leverage potentials and overcome challenges, paying due attention to country-specific conditions, thereby allowing the discussion of strategies that can help effectively overcome obstacles and enhance NDCs and their implementation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.704
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1620.034

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 head0.043
GPT teacher head0.265
Teacher spread0.223 · 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