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Record W2014155922 · doi:10.1080/19440049.2011.644588

Identification and quantification of the migration of chemicals from plastic baby bottles used as substitutes for polycarbonate

2012· article· en· W2014155922 on OpenAlexaboutno aff
Sandro Valzacchi

Bibliographic record

VenueFood Additives & Contaminants Part A · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsnot available
Fundersnot available
KeywordsEuropean unionBottlePolycarbonatePolypropylenePulp and paper industryForensic engineeringMaterials scienceBusinessComposite materialEngineering

Abstract

fetched live from OpenAlex

The results of a study on the analytical identification and quantification of migration of chemicals from plastics baby bottles found in the European Union market made of materials that are now present as substitutes for polycarbonate (PC) are reported. A total of 449 baby bottles with a focus on first age or sets of bottles were purchased from 26 European Union countries, Canada, Switzerland and the USA. From this collection, which contained several duplicates, a total of 277 baby bottles were analysed. The materials included different types of plastic such as PC, polyamide (PA), polyethersulphone (PES), polypropylene (PP), but also silicone, and from the United States a co-polyester marketed under the trade name Tritan™. The bottles were subjected to the conventional migration test for hot fill conditions, i.e. 2 h at 70°C. The simulant used was that specified in European Union legislation (2007/19/EC) for milk, i.e. 50% ethanol. In a first phase 1, migration was conducted since the scope of this investigation was a screening rather than a true compliance testing check. Second and third migrations were performed on selected articles when migrated substances exceeded limits specified in the legislation. In order to verify some materials, a portion of the bottle was cut to run an FT-IR fingerprint to confirm the nature of the polymer. The migration solutions in general showed a low release of substances. Results showed that bottles made of PP and silicones showed a greater number of substances in the migration solutions and in greater quantity. Chemicals from PP included alkanes, which could be found in >65% of the bottles at levels up to 3500 µg kg⁻¹; and benzene derivatives in 17% of the baby bottles and found at levels up to 113 µg kg⁻¹. Some substances were found on a regular basis such as plasticisers, esters and antioxidants (e.g. tris(2,4-di-tert-butylphenyl)phosphate, known as Irgafos 168. Some substances found were not included in the Community positive list, which means that those should not be found even in the first migration. Such substances included 2,6-di-isopropylnaphthalene (DIPN), found in 4% of the bottles at levels up to 25 µg kg⁻¹, 2,4-di-tert-butyl phenol (in 90% of the bottles at levels up 400 µg kg⁻¹). Moreover, bisphenol A (BPA) was detected and quantified in baby bottles made of PA, but limited to one brand and model specific (but labelled BPA free). Results for baby bottles made of silicone also indicated the presence of components, e.g. potentially coming from inks (benzophenone, diisopropyl naphtahalene - DIPN, which could come for example from the presence of instruction leaflets in the bottles). In the case of silicone, phthalates were also found in relevant concentrations, with levels for DiBP and DBP from the first migration test of 50-150 µg kg⁻¹ and DEHP at levels 25-50 µg kg⁻¹.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.017
GPT teacher head0.296
Teacher spread0.280 · 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
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

Citations108
Published2012
Admission routes1
Has abstractyes

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Same venueFood Additives & Contaminants Part ASame topicEffects and risks of endocrine disrupting chemicalsFrench-language works237,207