MétaCan
Menu
Back to cohort
Record W3116724967 · doi:10.1016/j.jhazmat.2020.124969

Does habitat quality matter to soil invertebrates in metal-contaminated soils?

2020· article· en· W3116724967 on OpenAlexafffund
Hamzat O. Fajana, Natacha Hogan, Steven D. Siciliano

Bibliographic record

VenueJournal of Hazardous Materials · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSoil waterBioenergeticsBiologyMiteCadmiumEcologyAnimal scienceEnvironmental chemistryChemistryBiochemistry

Abstract

fetched live from OpenAlex

This study investigated the influence of habitat quality (HQ) on the reproduction and bioenergetics (energy reserve and metabolic enzyme activities) of the oribatid mite, Oppia nitens, in response to cadmium (Cd). In the baseline toxicity test, Cd elevated the carbohydrate reserve of adult mites at intermediate Cd concentrations (88 and 175 mg Cd kg−1) but without a change in lipid and protein reserve across 0–700 mg Cd kg−1. The activities of glucose metabolism enzymes, glucose-6-phosphate dehydrogenase (G6PDH) and pyruvate kinase (PK) were inhibited in the mites at 700 mg Cd kg−1. Adult mites reared in high HQ soils had higher reproduction relative to mites from low HQ soils when exposed to Cd in OECD soil, but there was no difference in bioenergetics between mites from low and high HQ soils. Hence, HQ significantly (p = 0.024) influenced the reproduction of mites (i.e., juvenile production) irrespective of the Cd concentration in the OECD soil but did not significantly affect the bioenergetics of the mites. We suggest that habitat quality’s effect could be more significant than metal concentration on the biological fitness (juvenile production) of O. nitens in metal-contaminated soils.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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

Citations5
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Hazardous MaterialsSame topicEnvironmental Toxicology and EcotoxicologyFrench-language works237,207