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Record W4213262515 · doi:10.1080/26395916.2022.2032356

Advancing research on ecosystem service bundles for comparative assessments and synthesis

2022· article· en· W4213262515 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEcosystems and People · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsMcGill University
FundersMarcus och Amalia Wallenbergs minnesfondVetenskapsrådetSvenska Forskningsrådet Formas
KeywordsEcosystem servicesBundleEcosystemService (business)Environmental resource managementTotal human ecosystemKey (lock)BusinessComputer scienceEcologyEcosystem healthEnvironmental scienceBiologyComputer securityMarketing

Abstract

fetched live from OpenAlex

Social-ecological interactions have been shown to generate interrelated and reoccurring sets of ecosystem services, also known as ecosystem service bundles. Given the potential utility of the bundles concept, along with the recent surge in interest it is timely to reflect on the concept, its current use and potential for the future. Based on our ecosystem service bundle experience, expertise, and ecosystem service bundle analyses, we have found critical elements for advancing the utility of ecosystem service bundle concept and deepening its impact in the future. In this paper we 1) examine the different conceptualizations of the ecosystem service bundle concept; 2) show the range of benefits of using a bundles approach; 3) explore key issues for improving research on ecosystem service bundles, including indicators, scale, and drivers and relationships between ecosystem services; and 4) outline priorities for the future by facilitating comparisons of ecosystem service bundle research.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.052
GPT teacher head0.335
Teacher spread0.283 · 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