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Record W2807746686 · doi:10.5430/ijba.v9n4p1

How to Manage the Cop21 Policies?

2018· article· en· W2807746686 on OpenAlexvenueno aff
Jan-Erik Lane

Bibliographic record

VenueInternational Journal of Business Administration · 2018
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsTipping point (physics)Climate changeResilience (materials science)Global warmingPermafrostPsychological resilienceThe arcticArcticNatural resource economicsEnvironmental resource managementEnvironmental scienceBusinessPolitical scienceEconomicsEngineeringEcology

Abstract

fetched live from OpenAlex

While the climate and earth scientists now launch the new theory of abrupt climate change with overwhelming evidence about CO2s and the positive feedback lopes from Arctic meltdown and methane emissions from permafrost, the UNFCCC does not speed up the implementation of its promised policies. The social sciences have yet to come up with management plans for global decarbonisation. Resilience is no longer an option when the tipping point is muck closer in time than earlier believed. The key nations are not taking steps towards the saving of mankind from run away global warming.

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)0.019
metaresearch head score (Gemma)0.069
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.069
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0060.004
Scholarly communication0.0160.017
Open science0.0040.007
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.0630.016

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 head0.022
GPT teacher head0.321
Teacher spread0.299 · 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 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
Published2018
Admission routes1
Has abstractyes

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