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Record W2086743034 · doi:10.1021/es703145t

Building a Model Based on Scientific Consensus for Life Cycle Impact Assessment of Chemicals: The Search for Harmony and Parsimony

2008· article· en· W2086743034 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

VenueEnvironmental Science & Technology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCitationLibrary scienceHarmony (color)ReuseComputer scienceOperations researchEngineeringArt

Abstract

fetched live from OpenAlex

Achieving consensus among scientists is often a challenge?particularly in model development. In this article we describe a recent scientific consensus-building process for Life Cycle Impact Assessment (LCIA) models applied to chemical emissions?including the strategy, execution, and results of a process that used model comparison to achieve parsimony. This process has succeeded in establishing a transparent LCIA consensus model. We present the lessons that may be adapted by similar consensus processes in other fields. \nLCIA characterizes potential impacts on human health and the environment attributable to chemical emissions over the life cycle of a product. LCIA relies on substance-specific characterization factors (CFs) that combine exposure potential and toxicity to represent the relative contribution of the substance to health and environmental impacts (1). LCIA focuses on comparative assessment, using approaches adapted from risk assessment. In 2003, in response to large variations in available methods, an international model comparison/consensus process was initiated. This process was under the umbrella of the Life Cycle Initiative, a joint effort of the United Nations Environment Program (UNEP) and the Society of Environmental Toxicology and Chemistry (SETAC) (2). The process encompassed an international group of model developers responsible for the most commonly-used worldwide LCIA characterization models and focused on characterization of human and ecosystem health impacts. It also involved disciplinary experts in fate and transport, exposure assessment, health risk assessment, and ecotoxicology.\nThe comparison/consensus process fostered a common understanding among the participants of which model elements contribute most to the relative magnitude of LCIA characterization factors. It became clear that with a careful focus on the most influential model elements a consensus model could be established. Experience dictated that a more transparent model would be more likely to gain and retain acceptance and wide-spread use. The need for consistent documentation and transparency led the participants to create an entirely new model, building on contributions from the existing models. This required consensus on essential model elements, provided robust results consistent with existing models, and made parsimony a guiding principle. The tangible outcome is "USEtox", named in recognition of the UNEP-SETAC Life Cycle Initiative under which it was developed. The model is supported by all participating model teams as a basis for future global recommendations of LCIA characterization factors.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.013
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.020
GPT teacher head0.314
Teacher spread0.294 · 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