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Dendrogeomorphic Potential of the Himalaya – Case Studies of Process Dating of Natural Hazards in Kullu Valley, Himachal Pradesh

2017· article· en· W2793338246 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

VenueCurrent Science · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsImpact
Fundersnot available
KeywordsLandslideFlash floodNatural hazardRockfallContext (archaeology)Natural (archaeology)Physical geographyGeographyGeologyDendrochronologyClimate changeSnowNatural disasterDebris flowDebrisArchaeologyGeomorphologyFlood mythMeteorologyOceanography

Abstract

fetched live from OpenAlex

Trees impacted by the forces of natural processes such as flash floods, snow avalanches, landslides, rockfalls or earthquakes, record these events and exhibit growth disturbances in their growth-ring series. As a consequence, these disturbances provide an excellent signal for the spatio-temporal reconstruction of past natural hazard activity and a means to date and document past disasters. In the context of the Indian Himalayas Climate Change Adaptation Programme (IHCAP; http://www.ihcap.in/), a field trip was carried out in May 2014 to define suitable sites for dendrogeomorphic research in Kullu valley, Himachal Pradesh. Several tree species and sites where recent and past process activity can be reconstructed were inventoried, namely flash floods in the Beas and Sainj rivers as well as snow avalanches in Solang valley. Through this exploratory analysis, we ascertain that tree-ring techniques have wide applicability in the analysis of natural hazards, not only in the Kullu region but also in other geographical contexts of the Himalayas.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.025
GPT teacher head0.329
Teacher spread0.304 · 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