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Record W4394550868 · doi:10.6084/m9.figshare.13399118

Metadata record for: Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

2020· dataset· en· W4394550868 on OpenAlexfundno aff
Scientific Data Curation Team

Bibliographic record

VenueFigshare · 2020
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicInvertebrate Taxonomy and Ecology
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilDeutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-LeipzigBundesministerium für Bildung und ForschungAcademy of FinlandRussian Foundation for Basic ResearchAgence Nationale de la RechercheDeutsche ForschungsgemeinschaftNatural Sciences and Engineering Research Council of CanadaEuropean Commission
KeywordsEarthwormMetadataAbundance (ecology)Biomass (ecology)Diversity (politics)GeographyEcologyEnvironmental scienceBiologyWorld Wide WebComputer scienceAnthropologySociology

Abstract

fetched live from OpenAlex

This dataset contains key characteristics about the data described in the Data Descriptor Global data on earthworm abundance, biomass, diversity and corresponding environmental properties. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format ---------------------------------------------------------------- Please remove before publishing. manuscript number: SDATA-20-00920 edit url: https://scientificdata.metadata-creator.com/?id=ag5maWdtZXRhLTIzMDExMXIXCxIKU3VibWlzc2lvbhiAgICgzKucCgw Related publications: https://doi.org/10.1126/science.aax4851 Please remove before publishing. ----------------------------------------------------------------

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)0.003
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.374
Threshold uncertainty score0.893

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.011
Science and technology studies0.0010.001
Scholarly communication0.0040.006
Open science0.0030.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.3740.335

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 head0.141
GPT teacher head0.231
Teacher spread0.090 · 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.

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
Published2020
Admission routes1
Has abstractyes

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