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Record W2105060690 · doi:10.1136/jech.2004.031633

A landmark for popperian epidemiology: refutation of the randomised Aldactone evaluation study

2005· review· en· W2105060690 on OpenAlexaboutno aff
Elard Koch

Bibliographic record

VenueJournal of Epidemiology & Community Health · 2005
Typereview
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineObservational studyArgument (complex analysis)Perspective (graphical)EpidemiologyPopulationEpistemologyInternal medicineArtificial intelligence

Abstract

fetched live from OpenAlex

In 1999 a great multi-site clinical trial known as the randomised Aldactone evaluation study (RALES) showed that the use of spironolactone importantly reduced complications attributable to chronic heart failure without major negative side effects. Recently, RALES has been questioned by a large scale observational study in the Ontario population. In contrast with predictions, the complications and mortality increased dramatically because of hyperkalaemia, reaching dimensions that from a public health perspective are comparable to an epidemic. This review analyses both researches in the light of Karl Popper's science theory applying the modus tollens syllogism to the reality proposed by the main empirical enunciations that ensue from its epidemiological designs. RALES is deductively refuted because of the non-fulfillment of auxiliary assumptions that would act as reciprocal potential falsifiers in both studies, taking the logical form of a bi-conditional argument of the type: (a) P-then-Q and (b) Q-if-X(P), X(P) being a set of potential falsifiers of Q as part of the explicit falsity content of P. From this popperian model, implications for clinical research are discussed.

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)0.125
metaresearch head score (Gemma)0.207
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.875
Threshold uncertainty score0.659

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1250.207
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.004
Science and technology studies0.0020.028
Scholarly communication0.0040.011
Open science0.0030.005
Research integrity0.0100.022
Insufficient payload (model declined to judge)0.0020.001

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 head0.379
GPT teacher head0.560
Teacher spread0.180 · 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 designNot applicable
DomainMethods
GenreReview

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

Citations15
Published2005
Admission routes1
Has abstractyes

Explore more

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