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Impact of habitat area and isolation on species body-size distribution

2016· article· en· W2625471956 on OpenAlexaff
Claire Jacquet, David Mouillot, Michel Kulbicki, Dominique Gravel

Bibliographic record

VenueFaculty of 1000 Research Ltd · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsOpen peer reviewPlant biologyIsolation (microbiology)HabitatBiologyDistribution (mathematics)EcologyPhysiologyZoologyMedicineBioinformaticsBotanyMathematics

Abstract

fetched live from OpenAlex

The Theory of Island Biogeography predicts how area and isolation, through colonization and extinction dynamics, influence the equilibrium species richness on insular habitats, such as ponds, forest fragments or coral reefs. However, this theory remains silent about the body-size distribution within species assemblages, a determinant aspect of community structure for ecosystem functioning. To fill this gap, we develop models of island biogeography that predict body-size distribution as a function of habitat area and isolation. We compare the model predictions to the body-size distribution of piscivorous and herbivorous fish found in tropical reefs, using a published database of 991 tropical reef-associated fish species and their occurence in 134 locations worldwide.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.001

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 head0.049
GPT teacher head0.361
Teacher spread0.313 · 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 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

Citations0
Published2016
Admission routes1
Has abstractno

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