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Record W1610677667 · doi:10.1002/047147844x.aw2210

Plant and Microorganism Selection for Phytoremediation of Hydrocarbons and Metals

2004· other· en· W1610677667 on OpenAlexaboutno aff
Terry McIntyre

Bibliographic record

VenueWater Encyclopedia · 2004
Typeother
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsnot available
Fundersnot available
KeywordsPhytoremediationEnvironmental scienceHeavy metalsContaminationProtocol (science)MetalloidWaste managementEnvironmental protectionEnvironmental chemistryEngineeringChemistryBiologyEcologyMetal

Abstract

fetched live from OpenAlex

Abstract Information on plants and other organisms that have the potential for phytoremediation of contaminants aids in the planning and establishment of removal and restoration projects for contaminated sites. Environment Canada is compiling databases on plants, bacteria, fungi, and other organisms that remediate petroleum hydrocarbons and accumulate metals and metalloids. The databases PHYTOPET (for PHYTOremediation of PETroleum hydrocarbon contaminants) and PHYTOREM (for PHYTOREmediation of Metals) are user‐friendly, searchable, and summarize all the known literature. Environment Canada has also drafted a Protocol, “Environmental Technology Verification (ETV) Protocol for Metal Contaminants.” The program provides suppliers of specified environmental technologies and services that meet the required criteria, with the right to use the licensed ETV verification mark.

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 score0.672
Threshold uncertainty score0.870

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)0.0010.000

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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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