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Innovative forest products in the circular bioeconomy

2022· article· en· W4282979886 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

VenueOpen Research Europe · 2022
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversité Laval
FundersHorizon 2020 Framework ProgrammeEuropean Commission
KeywordsBusiness

Abstract

fetched live from OpenAlex

<ns4:p> <ns4:bold>Background:</ns4:bold> The forest-based industry has been moving towards the manufacture of bio-based products in response to the increasing concern by consumers and governments regarding the use of non-renewable materials and the generation of residues. Various innovative technologies geared towards reducing the environmental footprint of products and processes are currently being developed and applied in the forest-based industry. This study presents some innovative wood-based products that are about to enter the market or that are already being commercialized but have the potential to expand in market size. </ns4:p> <ns4:p> <ns4:bold>Methods:</ns4:bold> We collected data from interviews and a survey with organisations working with product development and manufacturing, and from the literature. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> Many innovative products that are already produced at an industrial scale, such as cross-laminated timber, wood-based composites, and lyocell, can still increase their market share in the coming years. Some of the up-and-coming products with high potential to substitute fossil-based materials and will likely enter the market in the near future are wood foam, lignin-based adhesives, glycols, bioplastics, and textile fibres. Our study indicates that, although biomass demand is expected to increase, stakeholders do not consider future supply a limiting factor. </ns4:p> <ns4:p> <ns4:bold>Conclusions:</ns4:bold> The ease of market introduction of innovative products relies heavily on the products’ ability to take advantage of existing value chains. Overall, many of the reviewed products have the advantage of being ‘drop-in’. This is because products that require adjustments to production lines are less likely to get into the market without strong external drivers that push for bio-based alternatives. According to stakeholders, the economic viability and the market expansion of these products could be encouraged to a certain extent by EU policies, and certain barriers could be alleviated by reducing bureaucracy, increasing the support for pilot-scale to full-scale production, and increasing subsidies for bio-based alternatives. </ns4:p>

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.696
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.101
GPT teacher head0.332
Teacher spread0.231 · 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