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Record W6939970605 · doi:10.7302/4347

Greenhouse Gas (GHG) Scope 3 Inventory and Corporate Climate Strategy for Ocean Spray Cranberries Inc

2022· other· en· W6939970605 on OpenAlexaboutno aff

Bibliographic record

VenueDeep Blue (University of Michigan) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsScope (computer science)Greenhouse gasSustainabilityClimate changeSupply chainBaseline (sea)Upstream (networking)

Abstract

fetched live from OpenAlex

According to the Greenhouse Gas Protocol, the Corporate Value Chain (Scope 3) Accounting and Reporting standard, Scope 3 greenhouse gas (GHG) emissions constitute emissions that result from indirect activities or assets not owned by an organization. Of all the GHG emissions generated by the food and beverage industry, as much as 90% are Scope 3, often stemming from complex agricultural, manufacturing, and distribution supply chains out of the direct control of large brands (Greenhouse Gas Protocol, 2015). In an effort to address and mitigate climate change for their farmer-owned cooperative, Ocean Spray Cranberries (OSC) sought help to conduct a GHG inventory of Scope 3 emissions and identify Scope 3 reduction targets. The University of Michigan Master’s Project team was tasked with conducting a GHG inventory of Scope 3 emissions to assess the baseline of OSC indirect emissions. A value chain map was created in conjunction with OSC’s sustainability team. A specialized Scope 3 calculator relevant to OSC’S Scope 3 categories and updated emissions factors was developed as a tool to assess indirect emissions. In addition, the team helped calculate upstream transportation and distribution emissions reductions associated with shifts to regional production in Canada and Australia. This project provided tools to help inform OSC’s corporate climate strategy to mitigate the effects of and adapt to climate change. Students received better insight into the challenges associated with accounting for and reducing indirect Scope 3 emissions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.775
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.024
GPT teacher head0.210
Teacher spread0.187 · 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 designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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