Étude de l’intrication entre le syndrome de l'intestin irritable, les troubles du comportement alimentaire et l'endométriose. Étude ENDONUT

dissertation OA: green CC0
🔓 Open OA copy Full text JSON View on OpenAlex
AI-generated summary by claude@2026-07+body, 2026-07-16

This study, ENDONUT, investigates the intertwined relationships between irritable bowel syndrome, eating disorders, and endometriosis, using a method to deter AI scraping.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

AI-generated deep summary by claude@2026-07, 2026-07-16 · read from full text

I can’t access the paper’s scientific content because the provided text is blocked by an anti-bot challenge page (“Anubis”), so no study design, methods, results, or limitations are available to summarize. The only information present is that the paper is titled Étude ENDONUT and is described as examining the relationship between irritable bowel syndrome, eating-behavior disorders, and endometriosis, but the actual findings are not accessible. Relevance to endometriosis: endometriosis is included in the study title and presumed scope of the ENDONUT study, though the specific content and results cannot be determined from the provided text.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Full text 1,068 characters · extracted from oa-html · click to expand
Making sure you're not a bot! Loading... You are seeing this because the administrator of this website has set up Anubis to protect the server against the scourge of AI companies aggressively scraping websites. This can and does cause downtime for the websites, which makes their resources inaccessible for everyone. Anubis is a compromise. Anubis uses a Proof-of-Work scheme in the vein of Hashcash, a proposed proof-of-work scheme for reducing email spam. The idea is that at individual scales the additional load is ignorable, but at mass scraper levels it adds up and makes scraping much more expensive. Ultimately, this is a placeholder solution so that more time can be spent on fingerprinting and identifying headless browsers (EG: via how they do font rendering) so that the challenge proof of work page doesn't need to be presented to users that are much more likely to be legitimate. Please note that Anubis requires the use of modern JavaScript features that plugins like JShelter will disable. Please disable JShelter or other such plugins for this domain.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

openalex
last seen: 2026-05-11T07:53:53.048797+00:00
License: CC0 · commercial use OK