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Record W2464661095 · doi:10.18773/austprescr.2004.001

Are new drugs as good as they claim to be?

2004· article· en· W2464661095 on OpenAlexaffabout
Joel Lexchin

Bibliographic record

VenueAustralian Prescriber · 2004
Typearticle
Languageen
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsYork UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineBusinessIntensive care medicine

Abstract

fetched live from OpenAlex

Approval of new drugs by the Therapeutic Goods Administration is no guarantee that they are superior or even equivalent to drugs already on the market. The drug evaluation process only assesses quality, safety and efficacy, not the therapeutic value of a drug. Assessments of the value of new drugs from Canada, France and the USA all show that at best one third of new drugs offer some additional clinical benefit and perhaps as few as 3% are major therapeutic advances.

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)0.030
metaresearch head score (Gemma)0.082
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.082
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0040.033
Scholarly communication0.0190.020
Open science0.0020.004
Research integrity0.0130.010
Insufficient payload (model declined to judge)0.0150.006

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 head0.072
GPT teacher head0.367
Teacher spread0.295 · 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
DomainEvaluation
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

Citations8
Published2004
Admission routes2
Has abstractyes

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