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Record W4382537058 · doi:10.1038/s41477-023-01446-5

Masting is uncommon in trees that depend on mutualist dispersers in the context of global climate and fertility gradients

2023· article· en· W4382537058 on OpenAlexaff
Tong Qiu, Marie‐Claire Aravena Acuña, Davide Ascoli, Yves Bergeron, Michał Bogdziewicz, Thomas Boivin, Raúl Bonal, Thomas Caignard, Maxime Cailleret, Rafael Calama, Sergio Donoso Calderón, J. Julio Camarero, Chia‐Hao Chang‐Yang, Jérôme Chave, Francesco Chianucci, Benoı̂t Courbaud, Andrea Cutini, Adrian J. Das, Nicolas Delpierre, Sylvain Delzon, Michael C. Dietze, Laurent Dormont, Josep María Espelta, Timothy J. Fahey, William Farfán-Ríos, Jerry F. Franklin, Catherine A. Gehring, Gregory S. Gilbert, Georg Gratzer, Cathryn H. Greenberg, Arthur Guignabert, Qinfeng Guo, Andrew Hacket‐Pain, Arndt Hampe, Qingmin Han, Jan Holík, Kazuhiko Hoshizaki, Inés Ibáñez, Jill F. Johnstone, Valentin Journé, Thomas Kitzberger, Johannes M. H. Knops, Georges Künstler, Hiroko Kurokawa, Jonathan G. A. Lageard, Jalene M. LaMontagne, François Lefèvre, Theodor D. Leininger, Jean‐Marc Limousin, James A. Lutz, Diana Macias, Anders Mårell, Eliot J. B. McIntire, Christopher M. Moore, Emily Moran, Renzo Motta, Jonathan A. Myers, Thomas A. Nagel, Shoji Naoe, Mahoko Noguchi, Michio Oguro, Robert Parmenter, Ian S. Pearse, Ignacio Manuel Pérez-Ramos, Łukasz Piechnik, Tomasz Podgórski, John R. Poulsen, Miranda D. Redmond, Chantal D. Reid, Kyle C. Rodman, Francisco Rodríguez‐Sánchez, Pavel Šamonil, Javier Sanguinetti, C. Lane Scher, Barbara Seget, Shubhi Sharma, Mitsue Shibata, Miles R. Silman, Michael A. Steele, Nathan L. Stephenson, Jacob N. Straub, Samantha Sutton, Jennifer J. Swenson, Margaret Swift, Peter A. Thomas, María Uriarte, Giorgio Vacchiano, Amy V. Whipple, Thomas G. Whitham, Andreas P. Wion, S. Joseph Wright‬, Kai Zhu, Jess K. Zimmerman, Magdalena Żywiec, James S. Clark

Bibliographic record

VenueNature Plants · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsCanadian Sport Centre PacificUniversité du Québec en Abitibi-Témiscamingue
FundersDivision of Environmental BiologyAgence Nationale de la RechercheU.S. Forest ServiceU.S. Geological SurveyNational Institute of Advanced Industrial Science and TechnologyNarodowa Agencja Wymiany AkademickiejSight Research UKNatural Environment Research CouncilGordon and Betty Moore FoundationU.S. Department of AgricultureNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsBiologyEcologyContext (archaeology)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.286
Teacher spread0.262 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations33
Published2023
Admission routes1
Has abstractno

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