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Record W2161097947 · doi:10.1111/mec.12093

Two <scp>D</scp>ecades of <scp>M</scp>olecular <scp>E</scp>cology: where are we and where are we heading?

2012· article· en· W2161097947 on OpenAlexaboutno aff
Eveline T. Diepeveen, Walter Salzburger

Bibliographic record

VenueMolecular Ecology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsEvolutionary ecologyBiologyEcologyPhylogeographyMolecular ecologyGenomicsEnvironmental ethicsSociologyGeneticsGenomeHost (biology)Phylogenetics

Abstract

fetched live from OpenAlex

The twentieth anniversary of the journal Molecular Ecology was celebrated with a symposium on the current state and the future directions of the field. The event, organized by Tim Vines and Loren Rieseberg, took place on the opening day of the First Joint Congress on Evolutionary Biology organized by the American Society of Naturalists (ASN), the Canadian Society for Ecology and Evolution (CSEE), the European Society for Evolutionary Biology (ESEB), the Society for the Study of Evolution (SSE) and the Society of Systematic Biologists (SSB) in Ottawa (Canada) from 6–10 July 2012. The get together of these five societies created a truly international and exciting “Evolution conference” and the ideal framework for the Molecular Ecology symposium. Its thirteen talks were grouped into the five different subject areas of the journal: Speciation and Hybridization; Landscape Genetics, Phylogeography and Conservation; Ecological Genomics and Molecular Adaptation; Kinship, Parentage and Behaviour; Ecological Interactions. Each session was followed by a panel discussion on the future direction of the subfield. That more than 300 colleagues registered for this special symposium illustrates the broad interest in, and appreciation of, molecular ecology – both the field and the journal.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.110
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.1100.027

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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
GenreReview

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

Citations3
Published2012
Admission routes1
Has abstractyes

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