MétaCan
Menu
Back to cohort
Record W7165670267 · doi:10.5281/zenodo.20810646

Deliverable D1.2 - Report on the available frameworks and tools for building constituency and expectations management

2023· article· en· W7165670267 on OpenAlexaff
Kora Dvorski, Hrvoje Čeprnja, Patrik Krstinić, Morgane Bouvet, Lois Watt, Venla Ala-Harja, Maëlla Sicard, Francesca Frau, Piera Pala, Riku Varjopuro, Kaisa J. Raatikainen, Sebastian Valanko, Eirini Glyki, Annaïk Van Gerven, Ivana Stojanović, Mariana Mata Lara, Rita Lecci, Francesco De Franco

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsInternational Submarine Engineering (Canada)
FundersEuropean Commission
KeywordsDeliverableFocus (optics)StakeholderKey (lock)Knowledge base

Abstract

fetched live from OpenAlex

This report is developed to provide a knowledge base for building constituency and expectations management for effective, efficient and resilient (networks of) MPAs/OECMs, specifically with focus on bottom-up processes and stakeholder engagement.

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)0.012
metaresearch head score (Gemma)0.023
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: none
Teacher disagreement score0.163
Threshold uncertainty score0.546

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0030.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1630.156

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 head0.047
GPT teacher head0.255
Teacher spread0.208 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicSustainability and Climate Change GovernanceFrench-language works237,207