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Record W1847354372 · doi:10.1136/bmj.h3077

Canadian tobacco firms are ordered to pay  8bn for damage from smoking

2015· article· en· W1847354372 on OpenAlexaboutno aff
Owen Dyer

Bibliographic record

VenueBMJ · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealth Services Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPunitive damagesClass actionDamagesPlaintiffMedicineTobacco industryPolitical scienceLawEnvironmental healthState (computer science)

Abstract

fetched live from OpenAlex

Canada’s three major tobacco firms suffered a heavy defeat when the Quebec Superior Court awarded $C15.6bn (£8bn; €11bn; $US13bn) to smokers in what could be a forerunner of further awards in other provinces. The country’s biggest and longest running class action suit involved a million current, former, and deceased smokers, of whom 99 957 had contracted serious smoking related diseases and sought punitive damages. Their cases were represented by the suit of Jean-Yves Blais, who died from lung cancer in 2012. A further 918 218 sued for addiction, represented by the suit of Cecilia Letourneau. Both suits were filed 17 years ago. The defendants, Imperial Tobacco Canada, JTI-Macdonald, and …

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)0.001
metaresearch head score (Gemma)0.004
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 score0.082
Threshold uncertainty score0.333

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0110.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0820.010

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 head0.164
GPT teacher head0.475
Teacher spread0.311 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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