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Record W2878785072 · doi:10.1021/cen-09627-buscon4

Dow wins $1 billion judgment against Nova

2018· article· en· W2878785072 on OpenAlexaboutno aff
Alex Tullo

Bibliographic record

VenueC&EN Global Enterprise · 2018
Typearticle
Languageen
FieldComputer Science
TopicLaw, AI, and Intellectual Property
Canadian institutionsnot available
Fundersnot available
KeywordsNova (rocket)AeronauticsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Dow Chemical won a round in one of two big lawsuits against Nova Chemicals. A Canadian court has issued a judgment of $1 billion in Dow’s favor in litigation over Nova’s conduct in running an ethylene joint venture between the two companies in Joffre, Alberta. Before the Court of Queen’s Bench, Dow alleged that between 2001 and 2012, Nova siphoned off more than its fair share of ethylene from their venture and that it ran the facility at lower operating rates than it should have. Nova said it was justified in taking the ethylene that it did and that the lower operating rates were due to feedstock shortages and mechanical issues at the plant. It further said that Dow was in breach of its contract when it procured feedstocks for its own operations in Alberta. Nova signed the original joint venture agreement in 1997 with Dow predecessor Union Carbide, which

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.157
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0130.002
Scholarly communication0.0100.003
Open science0.0020.003
Research integrity0.0210.015
Insufficient payload (model declined to judge)0.0390.015

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 head0.255
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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