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Record W6950505080 · doi:10.5683/sp3/nvpq3n

Replication Data for: Long-term environmental changes in the Canadian boreal zone: Synthesizing temporal trends from lake sediment archives to inform future sustainability

2025· dataset· en· W6950505080 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversité LavalConcordia UniversityUniversité du Québec à MontréalEnvironment and Climate Change CanadaMcGill University
Fundersnot available
KeywordsSustainabilityReplication (statistics)BorealSedimentClimate changeEnvironmental data

Abstract

fetched live from OpenAlex

Metadata, Lead (Pb) concentration data, and chlorophyll a data required to reproduce the analysis contained in the paper. These data are stored in Zenodo and can be found here: https://zenodo.org/records/7876605.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Dataset
About the Canadian research system: no · About a Canadian topic: yes
Not applicablelow
gptno category
Domain: not available · Genre: Dataset
About the Canadian research system: no · About a Canadian topic: yes
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.010
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 score0.079
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.012
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0790.036

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 head0.023
GPT teacher head0.298
Teacher spread0.275 · 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

Labeled directly by 2 models reading the full record.

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
Published2025
Admission routes2
Has abstractyes

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