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Record W4394252906 · doi:10.6084/m9.figshare.16815578

Additional file 4 of Location of studies and evidence of effects of herbivory on Arctic vegetation: a systematic map

2022· dataset· en· W4394252906 on OpenAlexaff
Eeva M. Soininen, Isabel C. Barrio, Ragnhild Bjørkås, Katrín Björnsdóttir, Dorothée Ehrich, Kelly A. Hopping, Elina Kaarlejärvi, Anders Lorentzen Kolstad, Svetlana Abdulmanova, Robert G. Björk, C. Guillermo Bueno, Isabell Eischeid, Rebecca Finger Higgens, Jennifer S. Forbey, Charles Gignac, Olivier Gilg, Michael den Herder, Hildur Søndergaard Holm, Bernice C. Hwang, Jane Uhd Jepsen, Stefaniya Kamenova, Ilona Kater, Amanda M. Koltz, J. A. Kristensen, Chelsea J. Little, Petr Macek, Karen Marie Mathisen, Daniel B. Metcalfe, Jesper Bruun Mosbacher, Martin Alfons Mörsdorf, Taejin Park, Jeffrey Propster, Aradhana Roberts, Emmanuel Serrano, Marcus P. Spiegel, Mariana Tamayo, Maria Tuomi, Megha Verma, Katariina Vuorinen, Maria Väisänen, René van der Wal, Megan Wilcots, Nigel G. Yoccoz, James D. M. Speed

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsSimon Fraser UniversityUniversité Laval
Fundersnot available
KeywordsVegetation (pathology)HerbivoreArcticThe arcticArctic vegetationGeographyEcologyPhysical geographyBiologyOceanographyGeologyTundra

Abstract

fetched live from OpenAlex

Additional file 4. Coding template and description of coded variables. Coding template used for data entry, including descriptions of coded variables, definitions of dropdown menus and references to the spatial data sources for variables extracted from other data sources.

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)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.648
Threshold uncertainty score0.501

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.013
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.6480.100

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 head0.047
GPT teacher head0.249
Teacher spread0.202 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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