Fix stale task references in Croissant limitations

etg_croissant.json

@@ -105,7 +105,7 @@
   "rai:dataCollectionRawData": "Raw scraped HTML is not distributed. The processed JSONL files are the primary artifact. Collection and preprocessing scripts are available in the src/etg/collectors/ directory of the code repository.",
   "rai:dataCollectionMissingData": "Coverage is limited by public API availability, rate limits, and pagination depth for forum sources. Posts behind authentication walls are excluded. Some timestamps reflect scraping date rather than original publication date. Author information is pseudonymized and not recoverable. Some legacy forum imports do not preserve thread structure.",
   "rai:dataPreprocessingProtocol": "HTML tags stripped from forum post content; HTML entities unescaped; text truncated at 8000 characters; encoding errors replaced with Unicode replacement character (U+FFFD); source provenance normalized into source_dataset, source_layer, forum_id, and optional thread/category fields; exact duplicates removed across sources by normalized-text SHA-256 fingerprint; Task 3 benchmark inputs strip explicit severity labels, CVSS score lines, and CVSS vectors after label extraction; author strings pseudonymized via SHA-256 hashing of source-namespaced author identifiers.",
-  "rai:dataLimitations": "Forum sources skew toward English-language Western cybersecurity communities; threats emerging from non-English communities may be underrepresented. High-volume historical forum imports skew toward 2015\u20132017 or earlier. Task 1 labels are weak CVE-linkage labels, not human exploit-semantics annotations; CVE-index absence is not a manual negative annotation. Task 2 is a quality-controlled metadata-linkage benchmark, not manually validated CVE-link ground truth. Tasks 4 and 5 use weak ternary labels derived from CVE metadata and actionability cues, not human labels. Approximately 8.18% near-duplicate content remains after exact deduplication. The corpus contains 1,569,263 rows under eight tokens useful for interaction analysis but not text classification.",
+  "rai:dataLimitations": "Forum sources skew toward English-language Western cybersecurity communities; threats emerging from non-English communities may be underrepresented. High-volume historical forum imports skew toward 2015\u20132017 or earlier. Task 1 labels are weak CVE-linkage labels, not human exploit-semantics annotations; CVE-index absence is not a manual negative annotation. Task 2 signal detection uses weak labels derived from CVE metadata and actionability cues, not human annotations. Task 3 shares the same label methodology as Task 1 under a stricter CVE-disjoint constraint. Approximately 8.18% near-duplicate content remains after exact deduplication. The corpus contains 1,569,263 rows under eight tokens useful for interaction analysis but not text classification.",
   "rai:dataBiases": "English-language bias: the corpus is predominantly English with multilingual content (Russian, Turkish, Persian, Arabic, Chinese) limited to deepdarkcti and several community sources. Temporal bias: bulk of structured NVD records begin in 2002; high-volume forum imports cluster around 2015\u20132017. Source selection bias: only publicly indexed or API-accessible sources are included, potentially underrepresenting closed or invitation-only communities. CISA KEV covers only actively exploited vulnerabilities, over-representing critical severity relative to true distribution. Western-centric community selection may underrepresent threat actors operating primarily in non-English forums.",
   "rai:personalSensitiveInformation": "No private communications, medical records, financial records, or government classified information is intentionally included. All text was collected from publicly accessible sources. Author strings are pseudonymized via SHA-256 hashing of source-namespaced author identifiers; original author strings are not recoverable from the released dataset. Public forum usernames are not distributed. The release supports takedown and correction requests through the repository issue tracker.",
   "rai:dataUseCases": "Intended uses: defensive cybersecurity research, temporal retrieval, provenance-aware benchmark design, vulnerability lifecycle analysis, exploit prediction and early warning systems, cross-lingual threat intelligence, graph neural network research on exploit\u2013CVE\u2013fix commit knowledge graphs, and pre-training domain-adapted language models for cybersecurity. Prohibited uses: training systems for automated exploit code generation or malware; de-anonymizing forum participants or linking pseudonymous identities outside approved research protocols; operational blocking, law-enforcement, or employment decisions based solely on model outputs; republishing source text from metadata_or_pointer_only sources.",