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Record W2883601832 · doi:10.7203/metode.9.11417

Natural enemies and biodiversity: The double-edged sword of trophic interactions

2018· article· en· W2883601832 on OpenAlex
Alexandre Mestre, Robert D. Holt

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

VenueMètode Revista de difusió de la investigació · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsSWORDTrophic levelBiodiversityEcologyNatural (archaeology)BiologyGeographyComputer scienceWorld Wide WebArchaeology

Abstract

fetched live from OpenAlex

Natural enemies, that is, species that inflict harm on others while feeding on them, are fundamental drivers of biodiversity dynamics and represent a substantial portion of biodiversity as well. Along the life history of the Earth, natural enemies have been involved in probably some of the most productive mechanisms of biodiversity genesis; that is, adaptive radiation mediated by enemy-victim coevolutionary processes. At ecological timescales, natural enemies are a fundamental piece of food webs and can contribute to biodiversity preservation by promoting stability and coexistence at lower trophic levels through top-down regulation mechanisms. However, natural enemies often produce dramatic losses of biodiversity, especially when humans are involved.

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)0.000
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 score0.684
Threshold uncertainty score0.315

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 studies0.0000.001
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 head0.036
GPT teacher head0.233
Teacher spread0.197 · 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