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Record W6967864828 · doi:10.5281/zenodo.13449633

EXIOBASE-hybrid - Consequential System

2025· dataset· en· W6967864828 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typedataset
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCapital goodCore modelMarginal landElectricityProduct (mathematics)Marginal productCapital (architecture)Metadata

Abstract

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Introduction The Consequential System of EXIOBASE hybrid is an extended version of EXIOBASE hybrid (Merciai & Schmidt, 2018), a multi-regional hybrid input-output database. This system is particularly notable for its incorporation of models that address indirect land use changes (iLUC) and marginal electricity generation mix, alongside the inclusion of capital goods in its core input-output framework. These extensions enhances the model's capability in assessing long-term environmental consequences of human activities. Indirect land use change (iLUC): The model details land use-related environmental impacts by integrating indirect land use change activity accounting, such as deforestration and intensification, based on Schmidt et al. (2015). The model is first introduced into EXIOBASE by Schmidt & De Rosa (2018). Marginal electricity mix: The model developed a long-term marginal electricity mix based on detailed characteristics of different electricity generation technologies. The underlying methodology is described in Muñoz et al. (2015) and its implementation in EXIOBASE is described in Merciai & Schmidt (2017) Capital endogenization: The model fill the gap in capital goods use by activities by distributing capital goods use to industrial and final demand activities. Data catalog Version 3.8-beta2 (bw) NOTE: This version is a Brightway-optimized release. It features expanded product resolution, improved product balance, efficient data structure and numerous bugfixes. Click here for a step-by-step import tutorial for Brightway2, and here for a detailed code explanation. io_metadata provides the classification metadata for intermediate and elementary flows. technosphere_value_table is the technosphere matrix values representing inter-sectoral flows of products and services. index_table_hiot is the index table linking technosphere values to activities and products. extensions_value_table provides the biosphere extensions including emissions, resource use, and other environmental flows. index_table_extensions provides index for extension flows, allowing linkage to environmental impact categories. product_value_table is the diagonal entries of the technosphere matrix representing the supply of products and services. Version 3.8-beta1 NOTE: This version, EXIOBASE-hybrid v3.8-beta1, is a test release. As it is still under development, some results and data flows may contain bugs or inaccuracies. We encourage users to thoroughly review the data and report any issues or inconsistencies they encounter. EXIOBASE-hybrid v3.8-beta1 GHG emission intensities provides the GHG footprint of production and market activities, expressed in both hybrid and monetary units. EXIOBASE-hybrid v3.8-beta1_transaction_matrix is the transaction matrix. EXIOBASE-hybrid v3.8-beta1_final_demand is the final demand. EXIOBASE-hybrid v3.8-beta1_emission is the emission extension. EXIOBASE-hybrid v3.8-beta1 for SimaPro instructions explains how to access and use the dataset in SimaPro, including different configuration options. EXIOBASE-hybrid v3.8-beta1 SimaPro_database is the dataset formatted for direct use in SimaPro, linked to the configuration outlined in "Option 1" of the SimaPro instructions. EXIOBASE-hybrid v3.8-beta1_SimaPro database is the dataset provided in CSV format, which can be imported into SimaPro, linked to the configuration outlied in "Option 2" of the SimaPro instructions. Version 3.3.18-ext1 MR_extended_HIOT_2011_v3_3_18_VA is the value added account extension. Version 3.3.18 MR_extended_HIOT_2011_v3_3_18_act_emissions is the emission extension. MR_extended_HIOT_2011_v3_3_18_incl_invest is the transaction matrix. MR_extended_HIOT_2011_v3_3_18_incl_invest_FD is the final demand. MR_extended_HIOT_2011_v3_3_18_reference_flow is the reference flow table for matrix normalization. References Merciai, S., & Schmidt, J. (2017). Land Use Change and Electricity Models in a Multi-regional Hybrid Input Output Framework. In 25th IIOA Conference in Atlantic City. https://lca-net.com/files/IIOA-paper-19-23-June-2017_iLUC-and-electricity-models-in-a-multi-regional-HIOT.pdf Merciai, S., & Schmidt, J. (2018). Methodology for the construction of global multi‐regional hybrid supply and use tables for the EXIOBASE v3 database. Journal of Industrial Ecology, 22(3), 516-531. Muñoz I, Schmidt J, de Saxcé M, Dalgaard R, Merciai S. (2015). Inventory of country specific electricity in LCA – consequential scenarios. Version 3.0. Report of the 2.-0 LCA Energy Club. 2.-0 LCA consultants, Aalborg https://lca-net.com/p/3935 Schmidt, J., Weidema, B. P., & Brandão, M. (2015). A framework for modelling indirect land use changes in Life Cycle Assessment. Journal of Cleaner Production, 99, 230–238. https://doi.org/10.1016/j.jclepro.2015.03.013 Schmidt, J., & De Rosa, M. (2018). Enhancing Land Use Change modelling with IO data. SETAC Europe 28th Annual Meeting. https://lca-net.com/files/SETAC_Rome_Schmidt_DeRosa_Extended-abstract_20180515.pdf

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.270
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.005

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 head0.032
GPT teacher head0.274
Teacher spread0.242 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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