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Record W4385238314 · doi:10.1038/s41598-023-38485-z

Evidences for the augmented Cd(II) biosorption by Cd(II) resistant strain Candida tropicalis XTA1874 from contaminated aqueous medium

2023· article· en· W4385238314 on OpenAlexaff
Kaustav Bhattacharyya, Neelanjan Bhattacharjee, Subhadeep Ganguly

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of Alberta
FundersBose InstituteUniversity of Calcutta
KeywordsCadmiumBiosorptionToxicantCandida tropicalisChemistrySewageContaminationEnvironmental chemistryStrain (injury)Aqueous solutionAqueous mediumEnvironmental remediationFood scienceAdsorptionYeastEnvironmental scienceBiologyEnvironmental engineeringToxicityBiochemistryEcologyOrganic chemistry

Abstract

fetched live from OpenAlex

Cadmium is one of the most dreadful heavy metals and is becoming a major toxicant in ground water with increasing concentration above the WHO Guidelines in drinking water (0.003 mg/L). The potential sources of cadmium include sewage sludge, phosphate fertilizers and ingredients like Ni-Cd batteries, pigments, plating and plastics. Cadmium levels are increased in water owing to the use and disposal of cadmium containing ingredients. Water draining from a landfill may contain higher cadmium levels. The authors have tried to evaluate the optimized nutritional conditions for the optimal growth and Cd(II) remediation capacity for a developed Cd(II) resistant yeast strain named Candida tropicalis XTA 1874 isolated from contaminated water-body in West Bengal. By analyzing the optimization conditions, a synthetic medium was developed and the composition has been given in the main text. The strain showed much better Cd(II) adsorption capacity under the optimized nutritional conditions (Mean removal = 88.077 ± 0.097%).

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

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