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Record W3128161282 · doi:10.1039/d0em00425a

Chemical recovery and browning of Nova Scotia surface waters in response to declining acid deposition

2021· article· en· W3128161282 on OpenAlexafffundabout
David Redden, Benjamin F. Trueman, Dewey Dunnington, Lindsay E. Anderson, Graham A. Gagnon

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNova scotiaDeposition (geology)Environmental chemistryColloidBrowningSurface waterAluminiumAcid depositionEnvironmental scienceChemistryMetallurgyEnvironmental engineeringOceanographyMaterials scienceGeologySoil scienceFood science

Abstract

fetched live from OpenAlex

). We identified increasing aluminum trends in 46 of 61 lakes, and we show using size-exclusion chromatography that binding to organic and iron-based colloids may help to explain these trends. To the extent that increases in apparent colour are explained by chromophoric dissolved organic matter (DOM), they imply greater binding capacity for metals in surface waters, and greater capacity for DOM to stabilize metal (oxyhydr)oxide colloids.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.257
Teacher spread0.246 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations31
Published2021
Admission routes3
Has abstractyes

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