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Record W2529420783 · doi:10.5751/es-01609-110232

Editorial: Special Feature on Scenarios for Ecosystem Services

2006· editorial· en· W2529420783 on OpenAlexaffvenue
Stephen R. Carpenter, Elena M. Bennett, Garry Peterson

Bibliographic record

VenueEcology and Society · 2006
Typeeditorial
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsMcGill University
FundersWinslow FoundationUniversity of Wisconsin-Madison
KeywordsEcosystem servicesFeature (linguistics)Environmental resource managementEcosystemEcosystem managementComputer scienceEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

The Millennium Ecosystem Assessment (MA, http ://www.MAweb.org) was the first global assessment of ecosystem services. The purpose of an assessment is to synthesize peer-reviewed scientific information in a form that is relevant to policy, but does not prescribe policy. The overarching goals of the MA were to synthesize information about the status, trends, and plausible futures of ecosystem services, as well as the policy instruments available for governing or managing ecosystem services.

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)0.005
metaresearch head score (Gemma)0.017
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0050.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0070.004
Open science0.0040.001
Research integrity0.0150.020
Insufficient payload (model declined to judge)0.0260.020

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 head0.003
GPT teacher head0.206
Teacher spread0.203 · 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
GenreEditorial

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

Citations38
Published2006
Admission routes2
Has abstractyes

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