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Record W4392365912 · doi:10.36371/port.2023.special.12

Roles of Climate Change and Environmental Sustainability

2024· article· en· W4392365912 on OpenAlexaff
Zaki S. Tawfik, Alaa Al-Hamami

Bibliographic record

VenueJournal Port Science Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsSustainabilityClimate changeEnvironmental changeEnvironmental resource managementEnvironmental planningEnvironmental scienceGeographyEcologyGeologyOceanography

Abstract

fetched live from OpenAlex

Climate change is widely acknowledged as a major global challenge with serious environmental, economic, and social repercussions. Iraq is ranked as the world's fifth greatest vulnerable country. The country is facing serious challenges, such as rising temperatures, decreasing rainfall, alkalinity, and the latest dust storms. Given this, combating climate change is an urgent and profound task for Iraq, a complex and difficult mission that will span several generations. To confront the challenge of climate change, a comprehensive climate change mitigation and adaptation framework covering as many climate-related topics as possible and connecting as many interested parties as possible across Iraq is required. It is critical to weather patterns topics such as climate-induced impact assessment, environmental vulnerability, and adaptability and sequels, climate change. Our objective use remote sensing and GIS are to mitigation and adaptation strategies to hold the sustainable weather and an improved understanding of climate, climate-related impacts, and remedies.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.008
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.040
GPT teacher head0.351
Teacher spread0.311 · 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
Published2024
Admission routes1
Has abstractyes

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