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Record W2905106223 · doi:10.1136/bmjebm-2018-111121

Drug discovery today: no molecules required

2018· article· en· W2905106223 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

VenueBMJ evidence-based medicine · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical and Physical Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDrug discoveryDrugComputer scienceMedicineComputational biologyData sciencePharmacologyBioinformaticsBiology

Abstract

fetched live from OpenAlex

During the last fifteen years, numerous peer-reviewed journals published articles about the incredible properties of so-called release-active “drugs” (RADs).1–24 It is claimed that these “drugs” are effective against tick-borne encephalitis, influenza, hemorrhagic fever with renal syndrome, meningococcal meningitis, herpes, HIV, and other viral and bacterial infections, diabetes, erectile dysfunction, sleep disorders, obesity, chronic inflammatory joint diseases, attention deficit hyperactivity disorder, chronic cerebral ischemia, benign prostatic hypertrophy, alcoholism, allergies, and many other health problems.18 25 In addition, it was publicly announced that they would provide new opportunities to overcome antibiotic resistance and significantly improve the prospects for the treatment of certain forms of cerebral palsy, schizophrenia, and stroke.26 Surprisingly, these innovative “drugs” contain no active molecules and can be considered a new brand of homeopathy. This indicates one of two possibilities: either we are at the brink of a revolution in medicine or that something went wrong with research published in numerous academic journals. We argue that the latter explanation is more likely and that this conclusion has severe implications for the scientific and healthcare enterprises. Release-active ‘drugs’ (RADs)1–24 are manufactured by a single Russian company called OOO ‘NPF ‘Materia Medica Holding’ (MMH).25 26 According to the original patent by its founder and CEO Epstein et al ,27 these preparations consist of ‘ activated forms of ultra-low doses of antibodies conventionally designated as potentiated (dynamised) antibodies (by analogy with the terminology used in homeopathic literature) for treatment of various pathological syndromes ’. The problem is that typical dilutions of the active ingredient are so high (from 1:1024 to 1:101991) that no molecules of the initial antibodies should be present in the ‘drug’ itself. The inventors claim that although the ‘drugs’ activity ‘ originates from the initial substance, it does not depend on its negligible …

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Editorial
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.033
GPT teacher head0.318
Teacher spread0.285 · 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