MétaCan
Menu
Back to cohort
Record W4402012947 · doi:10.3844/ajbbsp.2024.250.258

Effects of Soil Storage at Freezing Temperatures on Soil Enzymatic Activities

2024· article· en· W4402012947 on OpenAlexafffund
Ainsley Lougheed, K. K. Nkongolo

Bibliographic record

VenueAmerican journal of biochemistry & biotechnology/American journal of biochemistry and biotechnology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Soil, Plant Science
Canadian institutionsLaurentian University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSoil enzymeEnvironmental scienceSoil scienceChemistryEnzymeEnzyme assayBiochemistry

Abstract

fetched live from OpenAlex

Soil enzyme activities are good indicators of soil health. It has been hypothesized that soil storage before analysis might affect microbial function. The objective of the present study was to determine if soil storage at -20 and -80°C affects soil enzymatic activities. Soil samples were collected and stored for four weeks at -20 and -80°C. Activities of nine enzymes were measured in fresh samples and every two weeks during storage. Overall, nine enzymes were targeted including β-Glucosidase (BG), Cellobiohydrolase (CBH), β-N-Acetylglucosaminidase (NAGase), Aryl Sulfatase (AS), Acid Phosphatase (AP), Alkaline Phosphatase (AlP), Glycine Aminopeptidase (GAP), Leucine Aminopeptidase (LAP) and Peroxidase (PER). With the exception of GAP and LAP, no significant differences were observed between samples stored at -20°C for 2 weeks compared to controls. Storage at -80°C for two weeks resulted in a decrease in all the enzyme activities except for PER, BG, and LAP. With the exception of PER, storage at -20 and -80°C decreases the activities of all the enzymes tested after four weeks of storage. These changes varied with specific enzyme targeted. Further studies should be conducted to determine how these low storage temperatures affect microbial diversity and abundance.

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), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.003
GPT teacher head0.190
Teacher spread0.187 · 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 designBench or experimental
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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueAmerican journal of biochemistry & biotechnology/American journal of biochemistry and biotechnologySame topicAgriculture, Soil, Plant ScienceFrench-language works237,207