MétaCan
Menu
Back to cohort
Record W2334538460 · doi:10.1155/2004/815795

Opium the Best Remedy

2004· letter· en· W2334538460 on OpenAlexaff
Harold Merskey

Bibliographic record

VenuePain Research and Management · 2004
Typeletter
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsOpiumAddictionInsanityStimulantArabicPsychologyTraditional medicineMedicinePsychiatryHistoryPhilosophy

Abstract

fetched live from OpenAlex

Sydenham was the leading English physician of the 17th century and probably to the present time. He was using a well tried remedy. It had been known by then for about 4000 years, frequently mentioned by Hippocrates, and recognized in use in medieval Europe where it probably came through Arabic traders and was well established in use in Paris by the 12th century (2). Professional concerns up to the time of Sydenham were not about addiction. As can be seen from his text, they were about whether the drug was available in adequate preparations, whether there was any difference between opium and other narcotics, particularly comparing the natural juice with "its artificial preparations" (1) (all of which he thought to be about equal in effect), whether it was stimulant or restorative and invigorating, and whether it was being properly used for all the conditions in which it could be helpful. Addiction, dependence and insanity are not mentioned, although the fact that it could occasionally promote excitement ("frenzy") was known.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.008
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0070.004

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 head0.138
GPT teacher head0.362
Teacher spread0.224 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2004
Admission routes1
Has abstractyes

Explore more

Same venuePain Research and ManagementSame topicPain Management and Placebo EffectFrench-language works237,207