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Record W4396799387 · doi:10.1007/s10811-024-03252-8

Correction to: The Kelp Forest Challenge: A collaborative global movement to protect and restore 4 million hectares of kelp forests

2024· article· en· W4396799387 on OpenAlexaff
Aaron M. Eger, J. David Aguirre, Marı́a Altamirano, Nur Arafeh‐Dalmau, Nina Larissa Arroyo, Anne Bauer-Civiello, Rodrigo Beas‐Luna, Trine Bekkby, Alecia Bellgrove, Scott Bennett, Blanca Bernal, Caitlin O. Blain, Jordi Boada, Simon Branigan, Jasmine Bursic, Bruno Cevallos, Chang-Geun Choi, Sean D. Connell, Christopher E. Cornwall, Hannah S. Earp, Norah Eddy, Leeann B. Ennis, Annalisa Falace, Ana Margarida Ferreira, Karen Filbee‐Dexter, Hunter Forbes, Prue Francis, João N. Franco, Karen Gray Geisler, Anita Giraldo‐Ospina, Alejandra V. González, Swati Hingorani, Rietta Hohman, Ljiljana Iveša, Sara Kaleb, JP Keane, Sophie J. I. Koch, Kira A. Krumhansl, Lydia B. Ladah, Dallas J. Lafont, Cayne Layton, Duong Minh Le, Lynn Chi Lee, SD Ling, Steve I. Lonhart, Luis Malpica‐Cruz, Luisa Mangialajo, Amy McConnell, Tristin Anoush McHugh, Fiorenza Micheli, Kelsey I. Miller, Margalida Monserrat, Juan C. Montes‐Herrera, Bernabé Moreno, Christopher J. Neufeld, Shane Orchard, Betsy Peabody, Ohad Peleg, Albert Pessarrodona, Jacqueline B. Pocklington, Simon Reeves, Aurora M. Ricart, Finnley Ross, F. Schanz, Maria J. Schreider, Mohammad Sedarat, Shannen M. Smith, Samuel Starko, Elisabeth M. A. Strain, Laura Tamburello, Brian Timmer, Jodie E. Toft, Roberto A. Uribe, S.W.K. van den Burg, Julio A. Vásquez, Reina J. Veenhof, Thomas Wernberg, Georgina Wood, José Alberto Zepeda-Domínguez, Adriana Vergés

Bibliographic record

VenueJournal of Applied Phycology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsBamfield Marine Sciences CentreParks CanadaUniversity of VictoriaBedford Institute of OceanographyFisheries and Oceans CanadaRaincoast Conservation Foundation
Fundersnot available
KeywordsKelpKelp forestGeographyAgroforestryEcologyForestryFisheryEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

In this article the author name Aaron Eger was written twice, Alecia was missing, and Christopher Edward Cornwall should be Christopher Edward. The original article has been corrected.

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)0.003
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 score0.040
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.067
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0070.013
Insufficient payload (model declined to judge)0.0400.027

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 head0.006
GPT teacher head0.244
Teacher spread0.238 · 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
Published2024
Admission routes1
Has abstractyes

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