feat(survey): add IETF landscape survey (kappa, phase0, rerate), gaps update; bump wimse-ect; gitignore run logs

workspace/drafts/landscape-survey/sections/00-abstract.tex

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+\begin{abstract}
+Between 2024 and 2026 the Internet Engineering Task Force (IETF) saw a sharp
+rise in Internet-Drafts addressing AI agents and autonomous systems: monthly
+submissions in our corpus grew from an average of 3.7 (June 2024--May 2025) to
+38.8 (since June 2025), peaking at 106 in March 2026---roughly $35\times$ a
+typical 2024 month. We present a quantitative survey of this emerging area
+based on a curated corpus of 524 AI/agent-related IETF Internet-Drafts spanning
+January 2024 to May 2026. We characterise the corpus along four axes: temporal
+submission dynamics, thematic category distribution, authorship and
+working-group structure, and semantic redundancy measured through text
+embeddings. Two findings stand out: the area is overwhelmingly
+\emph{pre-standardization}---87\% of drafts are individual submissions not
+adopted by any working group---and it is semantically dense, with 32\% of
+drafts having a near-duplicate (cosine $>0.9$) elsewhere in the corpus.
+Because the thematic categories are produced by an LLM-assisted pipeline, we
+explicitly quantify their reliability through a two-model re-rating experiment:
+categorical assignment is substantially reproducible (Cohen's $\kappa = 0.65$),
+whereas LLM ordinal \emph{quality} scores such as novelty and overlap are not
+($\kappa_w = 0.13$--$0.21$). We therefore report the category landscape but
+deliberately exclude quality scores from our findings, and we argue this
+distinction is a general caution for the growing practice of LLM-assisted
+corpus analysis. All data, queries, and rating artifacts are released for
+reproduction.
+\end{abstract}