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Seven characteristics of medical evidence

2000· article· en· W2142474165 on OpenAlexafffund
Ross Upshur

Bibliographic record

VenueJournal of Evaluation in Clinical Practice · 2000
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersIndustry Canada
KeywordsDefeasible estateEvidence-based medicineEpistemologyMedical practiceBest evidenceEvidence-based practicePsychologyAlternative medicineMedicineMedical educationPhilosophy

Abstract

fetched live from OpenAlex

This paper outlines seven essential characteristics of medical evidence and describes the implications of these for both the theory of evidence-based medicine and clinical practice. The seven characteristics are: (1) Provisional; (2) Defeasible; (3) Emergent; (4) Incomplete; (5) Constrained; (6) Collective and (7) Asymmetric. It is argued that the epistemological theory that best fits medical evidence is that of fallibilism.

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)0.032
metaresearch head score (Gemma)0.150
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.150
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0130.012
Science and technology studies0.0050.024
Scholarly communication0.0160.019
Open science0.0020.008
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.591
GPT teacher head0.727
Teacher spread0.136 · 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 designTheoretical or conceptual
DomainMethods
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

Citations83
Published2000
Admission routes2
Has abstractyes

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