Evidence map›Paper›PMID 28461426›Full record

ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2017

Industry 1.61803: the transition to an industry with reduced material demand fit for a low carbon future.

Julian M Allwood, Timothy G Gutowski, André C Serrenho, Alexandra C H Skelton, Ernst Worrell

Abstract read
In one paragraph

Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Julian M AllwoodDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK jma42@cam.ac.uk.ORCID http://orcid.org/0000-0003-0931-3831
Timothy G GutowskiDepartment of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.ORCID http://orcid.org/0000-0001-7019-6887
André C SerrenhoDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK.ORCID http://orcid.org/0000-0002-0962-0674
Alexandra C H SkeltonDepartment of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK.ORCID http://orcid.org/0000-0001-6402-4528
Ernst WorrellCopernicus Institute of Sustainable Development, Heidelberglaan 2, 3548 Utrecht, The Netherlands.ORCID http://orcid.org/0000-0002-0199-9755

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Arising from a discussion meeting in September 2016, this editorial introduces a special issue on the transition to a future industrial system with greatly reduced demand for material production and attempts to synthesize the main findings. The motivation for such a transition is to reduce industrial greenhouse gas emissions, but unlike previous industrial transformations, there are no major stakeholders who will pursue the change for their own immediate benefit. The special issue, therefore, explores the means by which such a transition could be brought about. The editorial presents an overview of the opportunities identified in the papers of the volume, presents examples of actions that can be taken today to begin the process of change and concludes with an agenda for research that might support a rapid acceleration in the rate of change.This article is part of the themed issue 'Material demand reduction'.

Indexed as

climate change mitigationmaterial demand reductionpolicytransition

Identifiers

PMID28461426
PMCPMC5415643

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.