MétaCan
Menu
Back to cohort
Record W6143347

Complexité de la phrase en langue de spécialité: mythe ou réalité? Le cas de la langue médicale

2006· article· fr· W6143347 on OpenAlexaff
Maurice Rouleau

Bibliographic record

VenuePanace@: Revista de Medicina, Lenguaje y Traducción · 2006
Typearticle
Languagefr
FieldArts and Humanities
Topiclinguistics and terminology studies
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPhilosophyHumanitiesPhraseLinguistics
DOInot available

Abstract

fetched live from OpenAlex

espanolSe dice que la frase especializada es compleja, porque es larga. Por otro lado, la frase medica, tal como se define en el presente trabajo, es tan larga como la frase general, tomada esta como punto de referencia. De ahi podria concluirse que la frase medica tiene la misma complejidad que la frase general. Sin embargo, no es asi. Comparadas con frases generales de la misma longitud, las frases medicas son menos complejas. Esa menor complejidad radica en un mayor empleo de oraciones independientes. Ademas, cuando el medico recurre a oraciones subordinadas, estas son menos complejas que las que utiliza el redactor general. En resumen, la complejidad no es una caracteristica que se pueda aplicar indistintamente a toda frase especializada. La frase medica, como se define aqui, es una excepcion. EnglishOn one hand, specialized sentences are said to be because they are long. On the other, sentences in medical texts, as defined in the present study, are as long as those found in general texts. It would then be tempting to conclude that medical sentences are as complex as general ones. However, this is not the case. Medical sentences compared to general sentences of the same length appear less complex. Their lower complexity relates to a greater use of independent clauses. In addition, subordinate clauses used by physicians are less complex than those used by general writers. Therefore, it can hardly be said that complexity characterizes all specialized sentences. Medical sentences, as defined here, would be an exception. francaisD'une part, la phrase specialisee est generalement dite complexe parce que longue . D'autre part, la phrase medicale, telle que definie dans la presente etude, est aussi longue que la phrase generale, prise comme point de reference. Il serait donc tentant de conclure que la phrase medicale est aussi complexe que la phrase generale. Or, tel n'est pas le cas. A longueur egale, la phrase medicale est moins complexe que la phrase generale. Cette moindre complexite se traduit par un emploi preferentiel de phrases dites independantes. De plus, quand le medecin recourt a des phrases a subordonnees, ces dernieres sont toujours moins complexes, c'est-a-dire qu'elles contiennent moins de verbes conjugues, que celles qu'utilise le redacteur general. Bref, la complexite n'est pas une caracteristique qui s'applique sans distinction a toute phrase specialisee. La phrase medicale, telle que definie, fait nettement figure d'exception.

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.012
Scholarly communication0.0070.008
Open science0.0000.002
Research integrity0.0020.002
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 head0.023
GPT teacher head0.296
Teacher spread0.273 · 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
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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venuePanace@: Revista de Medicina, Lenguaje y TraducciónSame topiclinguistics and terminology studiesFrench-language works237,207