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Record W4281780527 · doi:10.1016/j.ecoenv.2022.113706

Application of Non-invasive Micro-test Technology (NMT) in environmental fields: A comprehensive review

2022· review· en· W4281780527 on OpenAlexaff
Mengxuan Han, Huan Yang, Guo Yu, Pingping Jiang, Shaohong You, Lei Zhang, Hua Lin, Jie Liu, Yi Shu

Bibliographic record

VenueEcotoxicology and Environmental Safety · 2022
Typereview
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of Alberta
FundersScience and Technology Major Project of GuangxiNational Natural Science Foundation of China
KeywordsPhytoremediationEnvironmental scienceMicroelectrodeField (mathematics)Biochemical engineeringComputer scienceHeavy metalsNanotechnologyEnvironmental chemistryMaterials scienceChemistryEngineering

Abstract

fetched live from OpenAlex

Non-invasive Micro-test Technology (NMT) is a selective microelectrode technique which can detect the flux rates and three-dimensional motion directions of ions or molecules into and out of living organisms in situ without damaging the sample. It has the advantages of maintaining sample integrity, high temporal and spatial resolution, and being able to measure multiple sites simultaneously. In this paper we provide a comprehensive review on the development of NMT in recent years. Its principles, characteristics, and the differences with other microelectrode techniques are introduced. We discuss the applications of NMT in the field of phytoremediation, plant resistance, water quality monitoring, and toxicity mechanisms of heavy metals on organisms. Furthermore, the challenges and future prospects of NMT in the environmental field are presented.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.246
Teacher spread0.238 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations29
Published2022
Admission routes1
Has abstractyes

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