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Record W167119282 · doi:10.5751/es-01342-1001r04

Invasive Species and the Cultural Keystone Species Concept

2005· article· en· W167119282 on OpenAlexvenueno aff
Martín A. Núñez, Daniel Simberloff

Bibliographic record

VenueEcology and Society · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsKeystone speciesEcologyEcosystemTransformative learningAbundance (ecology)Environmental ethicsGeographyBiologySociology

Abstract

fetched live from OpenAlex

The concept of the keystone species (Paine 1966, 1969, Power et al. 1996) has been a transformative notion in ecology. Keystone species were originally narrowly defined to be those whose importance to community and ecosystem structure, composition, and function is disproportionate to their abundance. Even this narrow definition fostered great insight into the nature of particular ecosystems and of threats to them (Power et al. 1996). However, in ecological circles the term came to be more casually used to mean any species that has a very large impact on the ecosystem, no matter how abundant it is (Simberloff 2003), and this casual usage has led to attacks on the concept on the grounds that it is so vague that it is meaningless (e.g., Mills et al. 1993). The phrase has even been freely and loosely borrowed outside ecology; for example, it has migrated into business and economics (Iansiti and Levien 2004).

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.016
Scholarly communication0.0040.007
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.030
GPT teacher head0.202
Teacher spread0.172 · 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 designTheoretical or conceptual
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

Citations63
Published2005
Admission routes1
Has abstractyes

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