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Record W3090592491 · doi:10.1080/26395916.2020.1819426

The science-policy interface on ecosystems and people: challenges and opportunities

2020· article· en· W3090592491 on OpenAlexaff
Patricia Balvanera, Sander Jacobs, Harini Nagendra, Patrick O’Farrell, Peter Bridgewater, Émilie Crouzat, Nicolas Dendoncker, Sean Goodwin, Karin Gustafsson, Andrew N. Kadykalo, Cornelia B. Krug, Fernanda Ayaviri Matuk, Ram Pandit, Juan Emilio Sala, Matthias Schröter, Carla-Leanne Washbourne

Bibliographic record

VenueEcosystems and People · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsCarleton University
Fundersnot available
KeywordsEcosystemInterface (matter)Focus (optics)Environmental resource managementEcologySociologyBusinessEnvironmental ethicsEnvironmental scienceGeographyBiology

Abstract

fetched live from OpenAlex

The complex links and feedbacks between ecosystems and people are now sharply in focus. Our growing understandings of the complex relations between ecosystems and people, the social and ecological ...

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)0.007
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0080.017
Scholarly communication0.0250.018
Open science0.0010.013
Research integrity0.0110.013
Insufficient payload (model declined to judge)0.0390.006

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 head0.036
GPT teacher head0.236
Teacher spread0.200 · 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 designTheoretical or conceptual
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

Citations52
Published2020
Admission routes1
Has abstractyes

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