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Record W6946365270 · doi:10.25976/54dz-2g47

Mackenzie Hg in streamwater survey 2018-2020

2023· dataset· en· W6946365270 on OpenAlexaboutno aff

Bibliographic record

VenueDataStream · 2023
Typedataset
Languageen
FieldImmunology and Microbiology
TopicToxoplasma gondii Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)STREAMSHydrology (agriculture)Stable isotope ratioSurface waterDrainage basinLatitude

Abstract

fetched live from OpenAlex

This dataset was produced as part of an investigation into the sources of mercury (Hg) in streams of the lower Mackenzie River Basin (MRB), carried out between 2018 and 2020 by scientists from Uppsala University, the Swedish University of Agricultural Sciences, Stockholm University, and Trent University in Peterborough, Ontario. Sampling in 2018 was carried out between 8-30 June at 19 sites between latitudes 59° and 68° N. Between 14 June 2019 and 3 March 2020, additional samples were collected by community partners at 2-3 month intervals from 4 rivers. Only basic water properties and dissolved Hg levels are reported here. Additional parameters, including stable isotopes of Hg, C, O and H, as well as radiocarbon, are reported and archived elsewhere.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.119
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.019

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 head0.037
GPT teacher head0.308
Teacher spread0.271 · 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
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
Published2023
Admission routes1
Has abstractyes

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