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Record W4409727755 · doi:10.1039/d4em00558a

Physicochemical differences between wildfire pyrogenic carbon and slow-pyrolysis biochar suggest variations in elemental transport potential

2025· article· en· W4409727755 on OpenAlexafffund
Katherine N. Snihur, Lingyi Tang, Kelly Rozanitis, Daniela Gutierrez Rueda, Cody N. Lazowski, Daniels Kononovs, Logan Swaren, Murray K. Gingras, Janice P.L. Kenney, Shannon L. Flynn, Kurt O. Konhauser, Daniel S. Alessi

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsMacEwan UniversityLaurentian UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNewcastle University
KeywordsBiocharPyrolysisEnvironmental chemistryCarbon fibersEnvironmental scienceCharcoalChemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

>7.8), and a less thermally mature mineral composition and surface functionality. Together these differences in properties result in markedly different leaching behaviors and suggest that F-PyC and slow pyrolysis B-PyC play different roles in elemental transport. Consequently, this work supports earlier claims that B-PyC is not a suitable proxy for the F-PyC, particularly with respect to elemental transport in fluvial environments. Our work highlights the necessity for research specifically focusing on F-PyC to accurately quantify the contribution of wildfires to global elemental cycling, presently and in the geologic past.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.208
Teacher spread0.205 · 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 teacher head, not a consensus.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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