MétaCan
Menu
Back to cohort
Record W4220820299 · doi:10.5281/zenodo.5973079

Measurement Recommendations and Guidelines for the Global Terrestrial Network for Permafrost (GTN-P)

2022· report· en· W4220820299 on OpenAlexaff
Dimtry Streletskiy, Jeannette Noetzli, Sharon L. Smith, Gonçalo Vieira, Philippe Schoeneich, Filip Hrbáček, Anna Irrgang

Bibliographic record

VenueDORA WSL (Swiss Federal Institute for Forest, Snow and Landscape Research) · 2022
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
FundersEuropean Commission
KeywordsPermafrostEnvironmental scienceEarth sciencePhysical geographyComputer scienceRemote sensingGeographyGeologyOceanography

Abstract

fetched live from OpenAlex

This document provides the definitions used by the GTN-P Network, as well as a short description commonly used measurement techniques and sampling recommendations and guidelines. This is a provisional document. It will be substituted by the Permafrost Best Practices that will be published as part of the Update of the World Meteorological Organization Guide No. 8.

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)0.015
metaresearch head score (Gemma)0.027
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: Methods · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.027
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.011
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0040.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0260.024

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 head0.365
GPT teacher head0.420
Teacher spread0.055 · 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
GenreMethods

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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueDORA WSL (Swiss Federal Institute for Forest, Snow and Landscape Research)Same topicClimate change and permafrostFrench-language works237,207