lick text

README.md

@@ -114,13 +114,13 @@ Related preparations are [TopicNet/WOS-5736](https://huggingface.co/datasets/Top
 
 ## Files and integrity
 
-The package contains `.gitattributes`, this card, [SHA256SUMS](SHA256SUMS), the verbatim [SOURCE_README.txt](SOURCE_README.txt), `data/noow.csv`, `data/bow.csv`, [labels](data/labels.json), [splits](data/splits.json) and [hierarchy](data/hierarchy.json). Run `sha256sum -c SHA256SUMS` from the package root to check every publication file except the checksum list itself. Git internals are excluded from the list.
+The package contains `.gitattributes`, this card, [SHA256SUMS](SHA256SUMS), the verbatim [SOURCE_README.txt](SOURCE_README.txt), `data/noow.csv`, `data/bow.csv`, [labels](data/labels.json), [splits](data/splits.json) and [hierarchy](data/hierarchy.json). Run `sha256sum -c SHA256SUMS` from the package root to check the listed files.
 
 ## Rights, limitations and citation
 
 The [official version 6 release](https://data.mendeley.com/datasets/9rw3vkcfy4/6) declares CC BY 4.0. [SOURCE_README.txt](SOURCE_README.txt) is preserved verbatim, including Copyright (c) 2017 Kamran Kowsari, the permission notice and the request to cite HDLTex. Preserve the copyright and permission notices in copies or substantial portions and cite the source. The release license does not establish that all abstracts or other third-party content are free of additional rights.
 
-Source selection, historical coverage and class imbalance limit generalization. Source hierarchy codes are preserved without inferred corrections. Grouping limits known duplicate leakage but does not establish that every semantic duplicate was detected. Normalization changes text and does not guarantee current facts, absence of personal information or suitability for downstream decisions.
+Source selection, historical coverage and class imbalance limit generalization. Source hierarchy codes are preserved without inferred corrections. Family grouping reduces known duplicate leakage, but some semantic duplicates may remain. The abstracts may contain personal information and outdated claims. Assess the corpus's suitability for your application before relying on it for decisions.
 
 Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, Kiana Jafari Meimandi, Matthew S. Gerber and Laura E. Barnes (2017). [*HDLTex: Hierarchical Deep Learning for Text Classification*](https://arxiv.org/abs/1709.08267), IEEE ICMLA. DOI: [10.1109/ICMLA.2017.0-134](https://doi.org/10.1109/ICMLA.2017.0-134).
 

SHA256SUMS

@@ -1,5 +1,5 @@
-9e75dd981de037ec3769f24f790e126bc5a160b6871f510214e68dc70649aeeb  .gitattributes
-e8244a5f98ca2bd16c76c65a00eea3473429f7ba453763ef0a1a0d556d40ca36  README.md
+947f03cf79a99d7f9061220c575021c918ae95f64ab75c4112917be804fb51cd  .gitattributes
+253c0b8eba717b399530fe5722588fdb8e7b5d79b8ae3c133124d9984fe2336f  README.md
 6da4ab1e624c4ef61c46600d727770f873ff4db3c15541fb481e7af8a715c0ec  SOURCE_README.txt
 fb9f0b1d6852c6cb23adf1a591cd836d35d3366765ad93d5dea31571b5d6f040  data/bow.csv
 7b862eb58b8c3d2f21511cb16f4f380161609cf876bb857c617ff54fdc1352d6  data/hierarchy.json