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An attempt to create the holistic flow chart of forest resources

2020· article· en· W3107619345 on OpenAlexaboutno aff
Hongjun Wang, Atsushi Takano, Ken Taro Tamura

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsChartFlow chartOrganizational chartSustainabilitySustainable developmentMaterial flow analysisProduct (mathematics)Forest productResource (disambiguation)Environmental resource managementBusinessForest managementEnvironmental economicsComputer scienceEnvironmental scienceEngineeringEconomicsAgroforestryEcologySystems engineeringWaste managementMathematics

Abstract

fetched live from OpenAlex

Abstract The environmental development of a building has an important role to play in terms of the sustainable development of our society. Against this background, wood and wood-based products have lately attracted notable attention as promising construction materials due to then-unique environmental properties, such as renewability and carbon storage capacity. For the sustainable use of wood, a relevant balance between supply and demand of forest resources is significant. However, little work has been conducted on a comprehensive understanding of forest resources flow. The objective of this study was. therefore, to draw an integrated chart of forest resources flow including forest conditions, round wood production, wood product manufacturing, wood stock in buildings and waste management at the end of product life, mainly focusing on building material flow. The flow charts were drawn for five countries (Japan. Finland. Germany, Sweden and Canada) based on statistical data. Instead of directly showing numerical information, the chart is presented as an infographic in order to promote intuitive understanding of the contents. The chart is intended as a basis for the development of sustainable forest resource circulation. This paper focuses on introducing the chart as such ad briefly discusses how the chart can be utilized for further study in relation with SDGs.

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 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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.999

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 studies0.0010.004
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.228
Teacher spread0.209 · 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 teacher head, not a consensus.

Study designObservational
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

Citations2
Published2020
Admission routes1
Has abstractyes

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