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Additional file 1 of Unsubstantiated health claims for COVID-19 infections are led by cannabidiol: return of snake oil medicine

2021· article· en· W6976949802 on OpenAlexaffabout

Bibliographic record

VenueFigshare · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Urban Networks and Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNoticeHealth claims on food labelsTable (database)Alternative medicinePublic healthMEDLINE

Abstract

fetched live from OpenAlex

Additional file 1: Supplemental Table 1. Summary of FDA Warning Letters and Notice of Violation Letters to Various Companies. Abbreviations: CO; company, CL; clinic, CH; church, AA; affiliate marketing via Amazon Associates Program, US, United States; CA, Canada; CN, China; IN, India; IE, Ireland; IL, Israel; PR, Puerto Rico; SG, Singapore; MX, Mexico; UNP, unapproved use; MB, misbranding; UC, unsubstantiated claims; WS, website; FB, Facebook; YT, YouTube; TW, Twitter; IG, Instagram; LI; LinkedIn; EM, email. Empty "Claim Verbatim Example" cells indicate an absence of unsubstantiated claim(s) for the given company.

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)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.8980.275

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 head0.046
GPT teacher head0.327
Teacher spread0.281 · 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.

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

Citations0
Published2021
Admission routes2
Has abstractyes

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