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Record W3209148074 · doi:10.5281/zenodo.4920414

IPBES-IPCC co-sponsored workshop report synopsis on biodiversity and climate change

2021· article· en· W3209148074 on OpenAlexaff
Hans‐Otto Pörtner, Robert J. Scholes, John Agard, Emma Archer, Xuemei Bai, David K. A. Barnes, Michael T. Burrows, Lena Chan, Wai Lung Cheung, Sarah E. Diamond, Camila I. Donatti, Carlos M. Duarte, Nico Eisenhauer, Wendy Foden, Maria A. Gasalla, Collins Handa, Thomas Hickler, Ove Hoegh‐Guldberg, Kazuhito Ichii, Ute Jacob, Gregory Insarov, Wolfgang Kiessling, Paul Leadley, Rik Leemans, Lisa A. Levin, Michelle Lim, Shobha Maharaj, Shunsuke Managi, Pablo A. Marquet, Pamela McElwee, Guy F. Midgley, Thierry Oberdorff, David Obura, Balgis Osman Elasha, Ram Pandit, Unai Pascual, Aliny P. F. Pires, Alexander Popp, Victoria Reyes‐García, Mahesh Sankaran, Josef Settele, Yunne‐Jai Shin, Sintayehu W. Dejene, Pete Smith, Nadja Steiner, Bernardo B. N. Strassburg, Raman Sukumar, Christopher H. Trisos, Adalberto Luís Val, Jianguo Wu, Edvin Aldrian, Camille Parmesan, Ramón Pichs-Madruga, Alex D. Rogers, Sandra Dı́az, Markus Fischer, Shizuka Hashimoto, Sandra Lavorel, Ning Wu, Hien T. Ngo

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Environmental Impact
Canadian institutionsFisheries and Oceans CanadaUniversity of British Columbia
Fundersnot available
KeywordsClimate changeBiodiversityEnvironmental resource managementPolitical scienceEnvironmental planningEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

The Synopsis presents the main conclusions of the first-ever IPCC-IPBES co-sponsored workshop which took place in December 2020. The workshop explored diverse facets of the interaction between climate and biodiversity, from current trends to the role and implementation of nature-based solutions and the sustainable development of human society. This Synopsis is underpinned by the Scientific Outcome, which includes seven sections, the complete references and the report glossary. You can find the Scientific Outcome here https://doi.org/10.5281/zenodo.4659158

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)0.004
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.098
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0980.057

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 head0.084
GPT teacher head0.269
Teacher spread0.185 · 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
GenreOther

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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicClimate Change and Environmental ImpactFrench-language works237,207