MétaCan
Menu
Back to cohort
Record W2979735795 · doi:10.1042/bio03706022

Contagion: a worthy entrant in the outbreak film genre

2015· article· en· W2979735795 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

VenueThe Biochemist · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsBC Centre for Disease Control
Fundersnot available
KeywordsZombieOutbreakHumanityParallelsExploitPopulationHistoryVirologySociologyMedicineDemographyPolitical scienceComputer securityLawEngineeringComputer science

Abstract

fetched live from OpenAlex

As researchers working in the fields of genomics, infection and epidemiology, we chose to write about Contagion for this issue. It wasn't much of a choice, a quick bit of Internet research confirmed that there aren't many films about infectious diseases, outbreaks and epidemiology, with the exception of the fairly terrible Outbreak (1995), and the 1970s-tastic sci-fi thriller The Andromeda Strain. What we do have plenty of are zombie flicks, and the parallels to outbreaks have been well recognized. Often starting with a virus or uncharacterized pathogen, zombie films exploit the nature of contagion as ever greater numbers of the population are infected, usually with the film's heroic (World War Z) or hapless (Shaun of the Dead) protagonist tasked with rescuing humanity, or at least staying alive.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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