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Record W1973629032 · doi:10.1002/cssc.200800125

Phytoremediation of Organic Contaminants in Soil and Groundwater

2008· review· en· W1973629032 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemSusChem · 2008
Typereview
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhytoremediationGroundwaterEnvironmental scienceEnvironmental chemistryContaminationSoil contaminationEnvironmental remediationGroundwater contaminationEnvironmental engineeringChemistrySoil waterSoil scienceAquiferGeologyEcologyBiology

Abstract

fetched live from OpenAlex

Phytoremediation is an emerging technology for the clean-up of sites contaminated with hazardous chemicals. The term phytoremediation refers to a number of technologies that use photoautotrophic vascular plants for the remediation of sites contaminated with inorganic and organic contaminants. Phytoremediation of organic contaminants can be organized by considering 1) the green liver concept, which elucidates the metabolism of contaminants in planta versus that of contaminants ex planta (e.g. rhizosphere), 2) processes that lead to complete degradation (mineralization) of contaminants as opposed to those that only lead to partial degradation or transformation, and 3) active plant uptake versus passive processes (e.g. sorption). Understanding of these processes needs an interdisciplinary approach involving chemists, biologists, soil scientists, and environmentalists. This Review presents the basic concepts of phytoremediation of organic contaminants in soil and groundwater using selected contaminants as examples.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.750

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 integrity0.0000.000
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 head0.021
GPT teacher head0.245
Teacher spread0.224 · 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