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Record W2407645657 · doi:10.5860/choice.194550

The quiet extinction: stories of North America's rare and threatened plants

2016· article· en· W2407645657 on OpenAlexaboutno aff

Bibliographic record

VenueChoice Reviews Online · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThreatened speciesQUIETExtinction (optical mineralogy)HistoryGeographyAstronomyGeologyPhysicsBiologyPaleontologyEcology

Abstract

fetched live from OpenAlex

In the United States and Canada, thousands of species of native plants are edging toward the brink of extinction, and they are doing so quietly. They are slipping away inconspicuously from settings as diverse as backyards and protected lands. The factors that have contributed to their disappearance are varied and complex, but the consequences of their loss are immeasurable. With extensive histories of a cast of familiar and rare North American plants, The Quiet Extinction explores the reasons why many of our native plants are disappearing. Curious minds will find a desperate struggle for existence waged by these plants and discover the great environmental impacts that could come if the struggle continues. Kara Rogers relates the stories of some of North America's most inspiring rare and threatened plants. She explores, as never before, their significance to the continent's natural heritage, capturing the excitement of their discovery, the tragedy that has come to define their existence, and the remarkable efforts underway to save them. Accompanied by illustrations created by the author and packed with absorbing detail, The Quiet Extinction offers a compelling and refreshing perspective of rare and threatened plants and their relationship with the land and its people.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.056
GPT teacher head0.269
Teacher spread0.213 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2016
Admission routes1
Has abstractyes

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