MétaCan
Menu
Back to cohort
Record W2391732116

Migration Prediction Model of Chemical Substances from Limited Thickness Paper Plastic Packaging Material and Its Verification

2011· article· en· W2391732116 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

VenuePackaging Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsFood packagingDiffusionPlastic packagingPartition (number theory)Materials sciencePartition coefficientThermodynamicsComputer scienceComposite materialMathematicsMechanical engineeringChemistryEngineeringChromatographyPhysics
DOInot available

Abstract

fetched live from OpenAlex

According to actual system of paper/plastic packaging-compound-food,diffusion equations were built based on one-dimensional Fick diffusion theory.Partition coefficient kCP between paper and plastic was considered in the prediction model.Analytical solutions were obtained under specific initial conditions and boundary conditions.In addition,the migration of migrant 1-hydroxycyclohexyl-1-phenyl ketone and benzyldimethyl ketal from paper-plastic materials 4015 and 3312 into different food simulant at 60 ℃ was studied.The experimental migration data based on experiment and calculated values based on the model were analyzed.The results showed that calculated values are higher than the experimental values.The higher calculated values were caused because of the worst-case values of DC.As far as this DC is concerned,this model can ensure the using safety of packaging.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.702

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)0.0000.000

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 head0.018
GPT teacher head0.170
Teacher spread0.152 · 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