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Record W3210410852 · doi:10.32920/ryerson.14665386.v1

Determining the Sustainability of Land-Applying Biosolids to Agricultural Lands Using Environmentally-Relevant Terrestrial Biota

2021· preprint· en· W3210410852 on OpenAlexafffund
Karen Joan Puddephatt

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsToronto Metropolitan University
FundersMinistry of Education, IndiaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsBiosolidsLumbricus terrestrisBiotaEnvironmental scienceEarthwormAgricultureSustainabilityTerrestrial ecosystemEnvironmental protectionEnvironmental chemistryAgronomyEcologyEnvironmental engineeringBiologyChemistryEcosystem

Abstract

fetched live from OpenAlex

Biosolids, the treated solid by-product of a WWPT, have been land-applied for decades as a means of disposal of an inexpensive form of fertilizer. However, research has shown that many chemicals such as pharmaceuticals, herbicides, pesticides, plasticizers, detergents, or heavy metals pass through the WWTP, often unaltered, and potentially end up in the biosolids. Therefore, a need to determine if the land-application of biosolids has an impact on terrestrial biota exists. In this work, six different organisms were used including Folsomia candida, Lumbricus terrestris, Zea mays, Glycine max, Phaseolus vulgaris, and Brassca rap. It was determined that government protocols were inadequate since they either prescribed organisms not environmentally-relevant or only looked at initial growth stages such as germination and emergence and not at effect, if any, on subsequent generations. Thus, new protocols were developed. Additionally, it was concluded that very little impact was seen on any of the terrestrial biota examined.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.001
Research integrity0.0010.000
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 head0.036
GPT teacher head0.306
Teacher spread0.270 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

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