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Record W2325650867 · doi:10.1111/2041-210x.12569

<scp>codyn</scp>: An<scp>r</scp>package of community dynamics metrics

2016· article· en· W2325650867 on OpenAlexaff
Lauren M. Hallett, Sydney K. Jones, A Macdonald, Matthew B. Jones, Dan F. B. Flynn, Julie Ripplinger, Peter Slaughter, Corinna Gries, Scott L. Collins

Bibliographic record

VenueMethods in Ecology and Evolution · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of British Columbia
FundersUniversity of CaliforniaNational Science Foundation
KeywordsR packageStability (learning theory)Computer scienceNull modelCovarianceDiversity (politics)Rank (graph theory)Term (time)EcologyData scienceStatisticsMachine learningMathematicsBiologySociology

Abstract

fetched live from OpenAlex

Summary New analytical tools applied to long‐term data demonstrate that ecological communities are highly dynamic over time. We developed an r package, library(“codyn”) , to help ecologists easily implement these metrics and gain broader insights into ecological community dynamics. library(“codyn”) provides temporal diversity indices and community stability metrics. All functions are designed to be easily implemented over multiple replicates. Temporal diversity indices include species turnover, mean rank shifts and rate of community change over time. Community stability metrics calculate overall stability and patterns of species covariance and synchrony over time, and include a null‐modelling method to test significance. Finally, library(“codyn”) contains vignettes that describe methods and reproduce figures from published papers to help users contextualize and apply functions to their own data.

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)0.005
metaresearch head score (Gemma)0.024
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: Software · Consensus signal: Software
Teacher disagreement score0.124
Threshold uncertainty score0.413

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.024
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0040.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1240.083

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 head0.024
GPT teacher head0.320
Teacher spread0.296 · 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
GenreSoftware

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

Citations311
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueMethods in Ecology and EvolutionSame topicEcology and Vegetation Dynamics StudiesFrench-language works237,207