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Record W1957283370

Letter To the Editor: 'Comment J'ai Vaincu la Douler et l'Inflammation Chronique Par l'Alimentation' by J Lagacè.

2013· letter· en· W1957283370 on OpenAlexaboutno aff
Giuliana Scarpati, M Pintore

Bibliographic record

VenuePubMed · 2013
Typeletter
Languageen
FieldMedicine
TopicGlycogen Storage Diseases and Myoclonus
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGerontologyPsychology
DOInot available

Abstract

fetched live from OpenAlex

Stubbing pain in the hands, finger joints blocked, severe pain in the back and knees, insomnia, depression. life of Dr. Jacqueline Lagace, like that of millions of people suffering from arthritis and osteoarthritis, is an ordeal, until the day he encounters in the hypotoxic diet Dr. Seignalet and decided to try This is the introduction to the book Comment j'ai vaincu la douleur et l'inflammation chronique par l'alimentation of Jaqueline Lagace, Canadian physician specializing in virology and immunology. In this book Dr. Lagace explains the basics of the Seignalet nutrition who believes that this system has a preventive or beneficial in many diseases. Seignalet advocates a return to an ancestral type of nutrition, his scheme is based on a primarily qualitative approach of diet, he dismisses the food they considered potentially harmful to the human organism (foods cooked at high temperature and also, among others, wheat and dairy products, organic foods and favors). This nutritional approach is variously called by the author ancestral diet, diet or feeding hypotoxic original type. mechanisms of action proposed by the author to explain the pathogenesis associated with certain foods and the effectiveness of their removal are not scientifically proven. sample used is not sufficient for a reliable statistical approach that includes: study on a large number of patients with double blind method and rate quantified as positive, negative and with a controlled follow-up. scheme Seignalet currently, despite the efforts required by its implementation and very reserved attitude of some of the scientific community about its effectiveness. Seignalet Jean (1936-2003), pioneer of renal transplantation in Languedoc-Roussillon was oriented nutrition through his research in immunology. He developed theories about the relationship between diet and the onset of various diseases.In his clinical practice, it has tested these theories on his patients by offering them a nutritional model that classifies hypotoxic. The power or third medicine that outlines the principles of this method dietetics, the mechanisms proposed to explain how certain foods may be involved in different pathologies and results Seignalet have observed his patients as a result of nutritional change.These results are sorted by ailments, some ill-treated by conventional medicine, would be put into remission by the treatment applied rigorously. For Seignalet, our genetic heritage from the Paleolithic hunter-gatherers did not have time to adapt to the modern diet.This mismatch is a key to understanding certain diseases. Under the influence of various factors.(genetic enzyme deficiencies, predisposing ground, allergies) and environmental factors such as the modern diet (including, gluten, milk proteins and products of cooking at high temperature) or frequent intake of chemicals such as antibiotics, mucosal Intestinal be attacked, undermined and rendered too porous, allowing easy passage into the bloodstream of macromolecules and bacterial food. According to the theory proposed by Seignalet in this state that is characteristic of hyper-intestinal permeability (leaky gut syndrome), the passage of exogenous molecules cause a chronic inflammatory process and immune response, depending on terrain would lead to the development of autoimmune disease, a disease known for clogging or elimination of diseases known. food residue or bacteria would be captured by the immune system and then directed to natural excretory, causing inflammation of the target organ. When excess food waste disposal capacity of the body, they accumulate in the extracellular environment, causing fatigue and certain immune system molecules, structures similar to those of

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)0.004
metaresearch head score (Gemma)0.025
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 score0.021
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.005
Open science0.0030.001
Research integrity0.0210.026
Insufficient payload (model declined to judge)0.0090.009

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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