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Record W6999831562

Direct Analysis of Plasticizers in Aqueous Samples by Atomspheric Pressure Chemical Ionization-Tandem Mass Spectrometry (APCI-MS-MS

2003· article· en· W6999831562 on OpenAlexaboutno aff

Bibliographic record

VenueLincoln (University of Nebraska) · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsnot available
Fundersnot available
KeywordsPlasticizerExtraction (chemistry)PhthalateSample preparationPolymerAdipateMass spectrometryAqueous solution
DOInot available

Abstract

fetched live from OpenAlex

The widespread manufacture of plastics requires the similarly ubiquitous use of plasticizers. Plasticizers such as bis(2-ethylhexyl) adipate (DOA) and bis(2-ethylhexyl) phthalate (DOP) enhance polymer strength and flexibility and are found in polymeric products such as cosmetics, detergents, and building and storage products (1). However, these additives are not bound to the polymer matrix and are subject to leaching. A recent Health Canada report warned that DOP may leach from medical devices and cause harm to infants, young boys, pregnant women, and nursing mothers (2). The United States Environmental Protection Agency (US. EPA) estimates that over 450,000 pounds of DOA were released to land and water during the period of 1987-1993 (3). Several methods exist for the determination of plasticizers in aqueous samples. For example, U.S. EPA methods 506 and 525.1 ma)) be used to analyze drinking water for DOA and DOE among other organic compounds (4,5). Extraction of the analytes from the water matrix is achieved by either liquid-liquid extraction or by passing the sample through a solid-phase extraction disk. Extracts are analyzed by gas chromatography (GC) with either photoionization (method 506) or mass spectrometric detection (MS) (method 525.1). Recently, a liquid chromatography-mass spectrometry (LC-MS) method for the analysis of plasticizers in water was reported (6). Regardless of the instrumental method employed, all of these methods require sample volumes ranging from 200 to 1000 mL in addition to lengthy liquid-liquid or solid-phase extraction procedures. Furthermore, both soluble and immiscible analytes are partitioned into the organic phase and quantitated as though the entire quantity were completely soluble in the sample. Not only does the extractionless method reported here reduce the sample volume required for analysis, but it also drastically reduces the labor required to prepare the samples. .

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.231
Teacher spread0.226 · 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
GenreMethods

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
Published2003
Admission routes1
Has abstractyes

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