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Record W2600139153 · doi:10.21037/atm.2017.03.38

Pokémon GO: snake oil or miracle cure for physical inactivity?

2017· letter· en· W2600139153 on OpenAlexaff
Jean‐Philippe Chaput, Allana G. LeBlanc

Bibliographic record

VenueAnnals of Translational Medicine · 2017
Typeletter
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of OttawaChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsPanacea (medicine)MiracleMedicinePolitical scienceAlternative medicineLaw

Abstract

fetched live from OpenAlex

The term "snake oil" was popularized in the early 1900s as a miracle cure-all, and later, after uncovering that it was made up of no more than mineral water and turpentine, it was coined as a term for someone selling products with fraudulent, questionable, or unverifiable benefits (1). Pokémon GO, released in July 2016, quickly became the world's most downloaded smartphone application, surpassing Twitter and Candy Crush within the first two weeks of its release (2). Initial reports and anecdotal evidence suggested that Pokémon GO might be the panacea researchers have been searching for to solve the global physical inactivity crisis. However, less than a year later, we understand that after the initial excitement subsided, Pikachu was not able maintain an increase in habitual physical activity. Pokémon GO may be just snake 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 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)0.001
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.369
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.156
GPT teacher head0.449
Teacher spread0.293 · 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.

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

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

Citations13
Published2017
Admission routes1
Has abstractyes

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