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Record W3167582400 · doi:10.1038/s41467-021-23955-7

Author Correction: Mature Andean forests as globally important carbon sinks and future carbon refuges

2021· article· en· W3167582400 on OpenAlexaff
Álvaro Duque, Miguel A. Peña, Francisco Cuesta, Sebastian González‐Caro, Peter G. Kennedy, Oliver L. Phillips, Marco Calderón-Loor, Cecilia Blundo, Julieta Carilla, Leslie Cayola, William Farfán-Ríos, Alfredo Fuentes, Ricardo Grau, Jürgen Homeier, María I. Loza-Rivera, Yadvinder Malhi, Agustina Malizia, Lucio R. Malizia, Johanna Andrea Martínez‐Villa, Jonathan A. Myers, Oriana Osinaga‐Acosta, Manuel Peralvo, Esteban Pinto, Sassan Saatchi, Miles R. Silman, J. Sebastián Tello, Andrea Terán-Valdéz, Kenneth J. Feeley

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Environment Research CouncilSight Research UK
KeywordsCarbon sinkCarbon fibersEnvironmental scienceEcologyBiologyComputer scienceClimate changeAlgorithm

Abstract

fetched live from OpenAlex

The numbering in the reference list was incorrect in the original article through numbers 29 to 65. This has now been amended.

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)0.062
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 score0.034
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.062
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0040.003
Scholarly communication0.0050.003
Open science0.0040.003
Research integrity0.0090.019
Insufficient payload (model declined to judge)0.0340.023

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 head0.010
GPT teacher head0.246
Teacher spread0.237 · 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

Citations10
Published2021
Admission routes1
Has abstractno

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