MétaCan
Menu
← Back to cohort
Record W4200625615 · doi:10.1038/s41467-021-27681-y

Publisher Correction: Species richness and identity both determine the biomass of global reef fish communities

2021· erratum· en· W4200625615 on OpenAlexaff
Jonathan S. Lefcheck, Graham J. Edgar, Rick D. Stuart‐Smith, Amanda E. Bates, Conor Waldock, Simon J. Brandl, Stuart Kininmonth, SD Ling, J. Emmett Duffy, Douglas B. Rasher, Aneil F. Agrawal

Bibliographic record

VenueNature Communications · 2021
Typeerratum
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversity of TorontoUniversity of VictoriaMemorial University of Newfoundland
Fundersnot available
KeywordsSpecies richnessFish <Actinopterygii>Biomass (ecology)ReefCoral reef fishFisheryEcologyIdentity (music)BiologyGeography

Abstract

fetched live from OpenAlex

Authors and Affiliations Tennenbaum Marine Observatories Network and MarineGEO Program, Smithsonian Environmental Research Center, Edgewater, MD, 21037, USA Jonathan S. Lefcheck & J. Emmett Duffy Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS, 7001, Australia Graham J. Edgar, Rick D. Stuart-Smith & Scott D. Ling Department of Ocean Sciences, Memorial University of Newfoundland, St. John’s, NF, A1C 5S7, Canada Amanda E. Bates Department of Biology, University of Victoria, Victoria, BC, V8P 5C, Canada Amanda E. Bates Landscape Ecology, Institute of Terrestrial Ecosystems, ETH Zürich, CH-8092, Zürich, Switzerland Conor Waldock Aquatic Ecology and Evolution, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland Conor Waldock Department of Marine Science, The University of Texas at Austin, Marine Science Institute, Port Aransas, TX, 78373, USA Simon J. Brandl School of Marine Studies, The University of South Pacific, Laucala Bay Road, Suva, Fiji Islands Stuart Kininmonth Bigelow Laboratory for Ocean Sciences, East Boothbay, ME, 04544, USA Douglas B. Rasher Department of Ecology & Evolutionary Biology, University of Toronto, Toronto, ON, M5S 3B2, Canada Aneil F. Agrawal Authors Jonathan S. Lefcheck View author publications You can also search for this author in PubMed Google Scholar Graham J. Edgar View author publications You can also search for this author in PubMed Google Scholar Rick D. Stuart-Smith View author publications You can also search for this author in PubMed Google Scholar Amanda E. Bates View author publications You can also search for this author in PubMed Google Scholar Conor Waldock View author publications You can also search for this author in PubMed Google Scholar Simon J. Brandl View author publications You can also search for this author in PubMed Google Scholar Stuart Kininmonth View author publications You can also search for this author in PubMed Google Scholar Scott D. Ling View author publications You can also search for this author in PubMed Google Scholar J. Emmett Duffy View author publications You can also search for this author in PubMed Google Scholar Douglas B. Rasher View author publications You can also search for this author in PubMed Google Scholar Aneil F. Agrawal View author publications You can also search for this author in PubMed Google Scholar Corresponding author Correspondence to Jonathan S. Lefcheck .

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)0.004
metaresearch head score (Gemma)0.067
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: Other · Consensus signal: none
Teacher disagreement score0.141
Threshold uncertainty score0.473

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.067
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0030.002
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.1410.069

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 head0.022
GPT teacher head0.270
Teacher spread0.248 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueNature Communications→Same topicCoral and Marine Ecosystems Studies→French-language works237,207→