MétaCan
Menu
Back to cohort
Record W3094283144 · doi:10.7202/1072238ar

The Smell of Air Pollution

2020· article· en· W3094283144 on OpenAlexvenueaboutno aff
Robert G. Armstrong

Bibliographic record

VenueOntario History · 2020
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Oil pollutionPetroleum industryGeographyBusinessEnvironmental protectionEnvironmental engineeringEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

Beginning in 1858, Enniskillen Ontario was the site of Canada’s first oil industry. Over the course of the next twenty-seven years, Canada’s oil industry struggled to sell Enniskillen oil because it possessed a pungent odour. Although using one’s olfactory senses is biological, how people choose to interpret odours is influenced by their cultural context. As a result, different populations reacted to the odour of Enniskillen oil based on their socioeconomic and geographic context. In Britain, people responded negatively to the smell of the oil, going so far as trying to ban the importation of oil from Canada. Across cities in Ontario, people raised complaints about the smell of the oil, but their concerns were largely ignored by municipal officials. In the oil region of Enniskillen, the locals were largely unbothered by the oil, despite living in a region that had been polluted to such an extent that the air was permeated with the smell of oil.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.453

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.159
GPT teacher head0.220
Teacher spread0.061 · 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 designObservational
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

Citations1
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueOntario HistorySame topicOlfactory and Sensory Function StudiesFrench-language works237,207