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Record W7014627516

Product design in plastic materials: the widespread application of plastics in consumer goods and society

2019· article· en· W7014627516 on OpenAlexaboutno aff

Bibliographic record

VenueVirtual Community of Pathological Anatomy (University of Castilla La Mancha) · 2019
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Selection and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsOmnipresenceProduct (mathematics)Product designPlastics industryProcess (computing)Industrial productionIdentification (biology)Production (economics)Quarter (Canadian coin)Industrial design
DOInot available

Abstract

fetched live from OpenAlex

The final quarter of the 20th century witnessed a considerable increase in the application of polymeric materials to an endless array of industrial products. The industry of polymeric materials has shown an impressively vigorous development, coming up with ever more diversified and sophisticated types and families of synthetic materials, each with highly advanced and increasingly more specific attributes, properties, potentialities and functionalities. New possibilities of these polymeric materials led to greater creative freedom for designers, who came to enjoy a large plethora of choices of polymers with which to work to model the plastic material culture at the turn of the 21st century. The environmental impact associated with the production and expandability of consumer products manufactured in plastic, on the other hand, has also accordingly been increasingly addressed. Despite the unquestionable advantages for society (particularly for users’ daily tasks), attention has shifted to the somewhat unforeseeable consequences of the omnipresence of and possible overdependence on plastic materials in society, overloading the environment, as plastic products have allegedly become so pervasive, and needed, in contemporary life. This study places this issue in perspective, relying on a review of the related literature bringing together the fields both of industrial design and materials engineering. It also utilized semi-structured, in-depth interviews carried out with 16 specialists in polymers and industrial design of diversified professional expertise both in Brazil and Italy. Data treatment was done by means of the qualitative technique known as associative analysis of data, consisting of a disciplined process of inductive identification of abstract patterns within already selected, fragmented, and pre-treated data, as they are classified within major conceptual categories which themselves emerge during the treatment stages.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0030.011
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.227
Teacher spread0.204 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2019
Admission routes1
Has abstractyes

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