lick text

README.md

@@ -237,13 +237,13 @@ 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 The abstracts may contain personal information and outdated claims.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
-e888c4293f207a1abe0e1e08b736561fed5829c4325d0618e2e7f9c9ff329fa7  README.md
+947f03cf79a99d7f9061220c575021c918ae95f64ab75c4112917be804fb51cd  .gitattributes
+064bbac56c74a367495853267385e811c88c1be941d622804195341590dfbd7b  README.md
 6da4ab1e624c4ef61c46600d727770f873ff4db3c15541fb481e7af8a715c0ec  SOURCE_README.txt
 039c213b7d7cc3dd2256418443bfc23a8a3e927eadd87ffe5ac08a34f692aebd  data/bow.csv
 1f714d3a953c7e3517f647f431d9a5d75f429b05574e66336166f2d5476a1f47  data/hierarchy.json