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Record W4302400008 · doi:10.5281/zenodo.7009891

IPBES Sustainable Use of Wild Species Assessment - Summary for policymakers - Data management report for Figure SPM.2

2022· report· en· W4302400008 on OpenAlexaff
Jean‐Marc Fromentin, Marla R. Emery, John Donaldson, Marie-Claire Danner, Agnès Hallosserie, Daniel Kieling, Ganesan Balachander, Elizabeth Barron, Nicolas Casajus, Ram Prasad Chaudhary, Maria A. Gasalla, Marwa Waseem A. Halmy, Christina C. Hicks, Brenda Parlee, Mi Sun Park, Jake Rice, Tamara Ticktin, Derek P. Tittensor

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typereport
Languageen
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsDalhousie UniversityFisheries and Oceans CanadaUniversity of Alberta
Fundersnot available
KeywordsEnvironmental resource managementGeographyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Data Management Report for Figure SPM.2 of the Summary for policymakers of the thematic assessment of the sustainable use of wild species of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES)

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)0.009
metaresearch head score (Gemma)0.012
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.093
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0040.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0700.057

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 head0.113
GPT teacher head0.305
Teacher spread0.192 · 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
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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