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Record W1965557596 · doi:10.1021/jf801443a

Short-Term Effects of Deinking Paper Sludge on the Dynamics of Soil Carbon, Nitrogen, and Phenolic Compounds

2008· article· en· W1965557596 on OpenAlexafffund
Younes Machrafi, François‐P. Chalifour, Josué Wamegni, Chantal J. Beauchamp

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsUniversité Laval
FundersUniversité Laval
KeywordsChemistryNitrateNitrogenNitrificationSoil carbonEnvironmental chemistryPhenolsAmmonium nitrateGerminationRaw materialAmmoniumAgronomyOrganic chemistrySoil waterEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Applications of deinking paper sludge (DPS) decreased the establishment of some crops, indicating that it may have inhibiting effects. The effects of soil-applied DPS on total carbon (C), nitrogen (N), C:N ratio, and nitrate, ammonium, and phenolic compounds were studied for 2 years. The phytotoxicity of simulated phenolic solutions of raw DPS and DPS-amended soil was investigated. Twelve phenolic compounds were quantified in raw DPS. Vanillin and 3-hydroxy-4-methoxycinnamic acids increased with DPS applications in amended soil for both years. Total soil C and the C:N ratio increased with DPS applications, while nitrate soil content decreased. Germination indices were affected differently by the phenolic compound solution that simulated DPS. This study highlights the lack of availability of nitrate as the main factor involved in the inhibiting effect of DPS. However, other inhibiting effects of phenolic compounds cannot be ruled out since they are known to inhibit nitrification and to trap nitrate into organic N compounds.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.174
Teacher spread0.167 · 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

Citations2
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Agricultural and Food ChemistrySame topicPesticide and Herbicide Environmental StudiesFrench-language works237,207