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Record W6969457796 · doi:10.5683/sp3/xw0qqu

Impact of cadaver decomposition on soil organic matter chemistry and bacterial responses during varying seasonal conditions within a temperate human taphonomic facility

2025· dataset· fr· W6969457796 on OpenAlexafffundabout

Bibliographic record

VenueBorealis · 2025
Typedataset
Languagefr
Field
Topic
Canadian institutionsUniversity of WindsorUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTemperate climateOrganic matterTaphonomyDecompositionSoil organic matterNutrientSoil water

Abstract

fetched live from OpenAlex

Data consists of chemical and bacterial analyses collected from soil sampled at varying distances (0-100 cm) and horizons (A and B) from decomposing human remains deposited during warm (n = 3) or cold (n =3) seasonal conditions at the REST[ES] facility (Bécancour, Québec). This was done to evaluate the environmental impact of human decomposition, particularly on soil nutrient and energy fluxes. Les données proviennent d'analyses chimiques et bactériennes recueillies à partir d'échantillons de sol prélevés à différents distances (0-100 cm) et horizons (A et B) des restes humains déposés pendant des conditions saisonnières chaudes (n = 3) ou froides (n = 3) au site de recherche REST[ES] (Bécancour, Québec). Ces analyses ont été réalisées pour évaluer l'impact environnemental de la décomposition cadavérique, notamment sur les flux de nutriments et d'énergie dans les sols. (2020-08-10)

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.883
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.005

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 head0.011
GPT teacher head0.288
Teacher spread0.277 · 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
GenreDataset

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

Citations0
Published2025
Admission routes3
Has abstractyes

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