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Record W1583906128 · doi:10.1017/cbo9780511627057

Geomorphology and Global Environmental Change

2009· book· en· W1583906128 on OpenAlexaff
Olav Slaymaker, Tom Spencer

Bibliographic record

VenueCambridge University Press eBooks · 2009
Typebook
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnvironmental changeClimate changeGeographyScope (computer science)Global changeEnvironmental resource managementSustainabilityEnvironmental planningPhysical geographyEnvironmental scienceEcologyOceanographyGeology

Abstract

fetched live from OpenAlex

How will global environmental change affect the landscape and our interaction with it? Apart from climate change, there are other important catalysts of landscape change, including relief, hydroclimate and runoff, sea level variations and human activity. This volume summarises the geomorphic implications of global environmental change, analysing such effects on lakes, rivers, coasts, reefs, rainforests, savannas, deserts, glacial features, and mountains. Providing a benchmark statement from the world's leading geomorphologists on the state of, and potential changes to, the environment, this book is invaluable for advanced courses on geomorphology and environmental science, and as a reference for research scientists. Interdisciplinary in scope, with a primary audience of Earth and environmental scientists, geographers, geomorphologists and ecologists, it also has a wider reach to those concerned with the social, economic and political issues raised by global environmental change, and is useful to policy makers and environmental managers.

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)0.000
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.025
GPT teacher head0.175
Teacher spread0.150 · 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

Citations105
Published2009
Admission routes1
Has abstractyes

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