MétaCan
Menu
Back to cohort
Record W2892376035 · doi:10.53055/icimod.727

Literature Review of Critical Climate-Stress Moments in the Hindu Kush Himalaya; A Resource Kit

2018· report· en· W2892376035 on OpenAlexaboutno aff
Annemarie Groot, Tejpal Singh, A. Pandey, Giovanna Gioli, Boshra Khalifa Ahmed, Saba Ishaq, Nauman Raza, Tarique Hassan, Abu Syed, Nabir Mamnun

Bibliographic record

Venuenot available
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicClimate change impacts on agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsHinduismResource (disambiguation)GeographyStress (linguistics)Computer sciencePhilosophyReligious studiesLinguistics

Abstract

fetched live from OpenAlex

This resource kit presents a compilation of information on critical climate-stress moments in the Hindu Kush Himalaya (HKH) region. The information is based on a literature review on critical-climate stress moments in agriculture and health due to heat stress and discusses critical moments emerging from downstream and upstream floods. The literature study was carried out by the Himalayan Adaptation, Water and Resilience (HI-AWARE) research project under the Collaborative Adaptation Research Initiative in Africa and Asia with financial support from the UK Government’s Department for International Development and the International Development Research Centre, Ottawa, Canada.

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)0.001
metaresearch head score (Gemma)0.006
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: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0190.022
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.072
GPT teacher head0.332
Teacher spread0.260 · 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
GenreReview

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

Citations5
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicClimate change impacts on agricultureFrench-language works237,207