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Record W4391874815 · doi:10.1139/er-2023-0074

Dissolved black carbon in aquatic environments with an emphasis on lacustrine systems: a review

2024· review· en· W4391874815 on OpenAlexvenueno aff
Sumbul Saeed, Rahat Riaz, Gan Zhang, Jun Li, Riffat Naseem Malik

Bibliographic record

VenueEnvironmental Reviews · 2024
Typereview
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
Fundersnot available
KeywordsdBcEnvironmental scienceCarbon cycleCarbon fibersEarth scienceCarbon blackFluvialOceanographyEnvironmental chemistryEcologyGeologyEcosystemChemistryStructural basinMaterials sciencePaleontologyBiology

Abstract

fetched live from OpenAlex

Dissolved black carbon (DBC) is the remobilized soluble fraction of black carbon (BC). DBC, present in all aquatic environments, is a heterogeneous mixture of various pyrogenic aromatics. For a long time, oceans were solely considered to be the largest pool of DBC. However, recent research indicates that lakes might also contain significant concentrations of DBC. Anthropogenic BC emissions and seasonal changes driven by climate change could increase DBC flux to glacial and fluvial lacustrine systems with unique effects. In this article, current knowledge concerning the formation, sources, transportation, fate, and environmental implications of DBC in lacustrine networks is presented. Furthermore, ambiguities pertaining to terminology and methodologies used in the separation and quantification of DBC are also reviewed, and research gaps that should be addressed in future studies are highlighted. Constraining DBC dynamics and residence times in lacustrine systems could provide valuable insights into anthropogenic perturbations of the global carbon cycle.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.038
GPT teacher head0.311
Teacher spread0.273 · 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
GenreReview

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

Citations3
Published2024
Admission routes1
Has abstractyes

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Same venueEnvironmental ReviewsSame topicToxic Organic Pollutants ImpactFrench-language works237,207