MétaCan
Menu
Back to cohort
Record W4307438784

Tablets, ampoules, thermometers, auto-injectable syringes (syrette) developped by the Army Health Service

2019· preprint· fr· W4307438784 on OpenAlexaff
André Frogerais

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2019
Typepreprint
Languagefr
FieldHealth Professions
TopicSafe Handling of Antineoplastic Drugs
Canadian institutionsCanadian Society for the History of Medicine
Fundersnot available
KeywordsAmpouleMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Le Service de Santé des armées développe au début du XX°siècle la production de comprimés et d'ampoules, il va populariser ces deux formes pharmaceutiques. En 1917, il initie la fabrication de thermomètre médicaux et aprés la Seconde Guerre mondiale, les seringues auto-injectables, les syrettes.At the beginning of the 20th century, the Army Health Service developed the production of tablets and ampoules, and they will popularize these new pharmaceutical forms. In 1917, he manufactures the first French medical thermometers. After the Second World War he developed the production of auto-injectable syringes, syrettes.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.021

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 head0.027
GPT teacher head0.286
Teacher spread0.260 · 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
GenreOther

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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueHAL (Le Centre pour la Communication Scientifique Directe)Same topicSafe Handling of Antineoplastic DrugsFrench-language works237,207