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Record W3012087359 · doi:10.3390/w12030800

Mycoremediation of Old and Intermediate Landfill Leachates with an Ascomycete Fungal Isolate, Lambertella sp.

2020· article· en· W3012087359 on OpenAlexaff
G. Siracusa, Qiuyan Yuan, Ilaria Chicca, A. Bardi, Francesco Spennati, Simone Becarelli, David B. Levin, Giulio Munz, Giulio Petroni, Simona Di Gregorio

Bibliographic record

VenueWater · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEnzyme-mediated dye degradation
Canadian institutionsUniversity of Manitoba
FundersUniversità di PisaFondazione Pisa
KeywordsLeachateBiomass (ecology)Chemical oxygen demandLaboratory flaskEnvironmental chemistryContaminationBiochemical oxygen demandStrain (injury)Environmental scienceChemistryBioreactorEnvironmental engineeringPulp and paper industryBiologySewage treatmentEcologyOrganic chemistry

Abstract

fetched live from OpenAlex

In the present study, an Ascomycete fungal strain, Lambertella sp., isolated from environmental polluted matrices, was tested for the capacity to reduce the contamination and the toxicity of intermediate and old landfill leachates. Batch tests in flasks, under co-metabolic conditions, were performed with two different old leachates, with suspended and immobilized Lambertella sp. biomass, resulting in a soluble chemical oxygen demand depletion of 70% and 45%, after 13 and 30 days, respectively. An intermediate landfill leachate was treated in lab-scale reactors operating in continuous conditions for three months, inoculated with immobilized Lambertella sp. biomass, in absence of co-substrates. The Lambertella sp. depleted the corresponding total organic carbon by 90.2%. The exploitability of the Lambertella sp. strain was evaluated also in terms of reduction of phyto-, cyto-, and mutagenicity of the different Landfill Leachates at the end of the myco-based treatment, resulting in an efficient depletion of leachate clastogenicity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.154

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.181
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 teacher head, 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

Citations15
Published2020
Admission routes1
Has abstractyes

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