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A rural and remote trail of dedication

2005· article· en· W2334073388 on OpenAlexaboutno aff
Barbara Sharp

Bibliographic record

VenuePACEsetterS · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsCreaturesAridDesert (philosophy)GeographyQuarter (Canadian coin)WetlandChinaArchaeologyEcologyPolitical scienceNatural (archaeology)

Abstract

fetched live from OpenAlex

Villagers in the heart of the Xinjiang Uygur Autonomous region, which makes up a quarter of the Chinese territory, cope remarkably well living in a gravel desert despite an annual mean rainfall of less than 25mm. In Canada farmers are still reeling from the Brown Christmas of '98 when drought swept the prairies from British Columbia into southern Ontario, while across Australia's central deserts deadly taipans remain among the few creatures to thrive in the cruel oppressive heat. Welcome to just some of the arid lands on our planet. The World Conservation Union estimates that dryland regions cover 47 percent of the world's surface, and are inhabited by almost two billion people. And then there are the inhospitable wetlands and ice-capped regions.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.134
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0100.001
Scholarly communication0.0010.001
Open science0.0000.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1340.015

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 head0.005
GPT teacher head0.204
Teacher spread0.200 · 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
GenreOther

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
Published2005
Admission routes1
Has abstractyes

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