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Record W1531270063 · doi:10.2175/106143000x137239

Desorptive Behavior of Pentachlorophenol (PCP) and Phenanthrene in Soil–Water Systems

2000· article· en· W1531270063 on OpenAlexaff
C. Fall, Jamal Chaouki, C. Chavarie

Bibliographic record

VenueWater Environment Research · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsPolytechnique Montréal
FundersU.S. Environmental Protection Agency
KeywordsPentachlorophenolPhenanthreneDesorptionSoil waterChemistryAdsorptionEnvironmental chemistryHysteresisSoil scienceChromatographyEnvironmental scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Recent investigations have prompted the need for a better understanding of the complete desorptive behavior of hydrophobic organic compounds in soils. The present study evaluated the irreversibilities associated with the desorption of pentachlorophenol (PCP) and phenanthrene from different types of soils. The study also examined the influence of solid–liquid ratio of the current batch desorption tests, specifically the completeness and accuracy of data gathered for establishing isotherms. Results demonstrated that the desorption of PCP and phenanthrene from contaminated soils can lead to three different types of behavior: complete reversibility, partial reversibility, or total irreversibility. The equilibrium adsorption constant ( K d ) is identified as a key parameter that indirectly sets the extent of hysteresis during the reverse process of desorption. According to the data, irreversibility occurs more in soils with a large adsorption capacity, that is, when K d is approximately 50 mL/g or more in the case of the phenanthrene– and PCP–soil systems evaluated. Furthermore, to facilitate the desorption experiments overall, the study proposes selection criteria for the solid–liquid ratio of batch tests to allow for variations in the adsorption capacity of each soil.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.030
GPT teacher head0.272
Teacher spread0.242 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2000
Admission routes1
Has abstractyes

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