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Record W3030086929 · doi:10.5539/jsd.v13n3p138

Climate Change and the Surge for Pandemics

2020· article· en· W3030086929 on OpenAlexvenueno aff
Durr e Shehvaar, Wardah Idris, Mubashira Ahmed

Bibliographic record

VenueJournal of Sustainable Development · 2020
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicGlobeClimate changeCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakPolitical scienceGlobal warmingSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)SurgeDevelopment economicsGeographyEconomicsEcologyMeteorologyBiology

Abstract

fetched live from OpenAlex

The pandemic of the century has caused great concern about the global environmental crisis. The article outlines the various aspects of the surge of pandemic its link to climate change along with the prospects for the nation-states and how they have seen it as a challenge as it is being seen as taking thousands of lives. In the literature review, the research problem that has been tailored is if the pandemic can create a common awareness about the global climate crisis that has destructive projections for the globe itself. A causal link between the surge of pandemics and climate change that helps spread the viruses has been created. In addition to this, we further argue that the nation-states and their exploitative corporate goals that are manipulating the environment should be curbed through decisive steps.

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.275
GPT teacher head0.381
Teacher spread0.105 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations4
Published2020
Admission routes1
Has abstractyes

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