% ARCHIVED INTERNAL NOTES: not included in the four-page submission draft. % Source: main.tex before the 2026-09-17 local-evidence restructure. % Provisional annotation workload and protocol notes, not model results. % Table references refer to the previous manuscript layout. % Upstream 2026-09-17 merge: semantic evaluation remains deferred in main.tex. % Protocol-v1 opportunity AP is superseded: ENTRY cannot cross another other % onset/intervening wearer activity; multi-competitor INT must not use an % arbitrary onset. Re-run protocol v2 and audit labels before semantic claims. % Retained upstream semantic qualitative plan (not compiled in main.tex): \subsection{Qualitative Floor-Event Analysis} We will compare EgoSpeak with the final matched model on human-confirmed examples selected by pre-declared event subtype rather than post-hoc score extremes. Each case will align participant-resolved activity, minimal transcript context, the opportunity anchor and competing-risk censor, and the two models' causally emitted wearer forecasts. The comparison will include a genuine wearer entry, an other-to-other false-entry opportunity, and an INT-yield paired with a non-takeover overlap; a shared failure case will be retained when space permits. \begin{figure*}[t] \centering \fbox{\parbox[c][0.115\textheight][c]{0.965\textwidth}{ \centering \textbf{Qualitative comparison placeholder}\\[0.7em] \begin{tabular}{ccc} Case A: wearer entry & Case B: other$\rightarrow$other HN & Case C: INT-yield / failed takeover\\ participant timeline + transcript & opportunity anchor + censor & EgoSpeak vs. proposed forecast\\ \end{tabular} }} \caption{Planned qualitative floor-event comparison. Final panels will use human-confirmed protocol-v2 cases and show the same causal source time for both models; the figure is a layout placeholder and contains no result claim.} \label{fig:qualitative_floor_events} \end{figure*} \begin{table}[h] \caption{LLM pre-label workload before human adjudication. Agreement is between two independent passes.} \label{tab:behavior_annotation_stats} \centering \scriptsize \begin{tabular}{@{}lrr@{}} \hline Measure & EasyCom S1--4 & Ego4D AV val \\ \hline Candidates & 2,128 & 3,608 \\ AI positive & 367 & 541 \\ AI hard negative & 1,017 & 1,174 \\ AI excluded & 744 & 1,893 \\ Two-pass agreement & 93.4\% & 82.1\% \\ Human-confirmed & 0 & 0 \\ \hline \end{tabular} \end{table} \appendix \section{LLM-Assisted Behavioral Event Annotation} \label{app:event_annotation} EasyCom's raw speech boundaries are acoustic annotations rather than floor labels. We preserve them unchanged for dense forecasting and create a separate behavioral-event layer. Its design principle is to anchor an observed wearer behavior first and then retrieve the conversational opportunity that could make that behavior meaningful. False-positive opportunities are mined independently because, by definition, many contain no wearer transition. \subsection{Positive-event mining} \textbf{Wearer activity transitions.} We preserve every raw wearer $0\!\rightarrow\!1$ and $1\!\rightarrow\!0$ boundary as a semantic review candidate. Candidate construction does not merge short silence gaps, infer within-turn resumption, or decide whether overlapping speech constitutes takeover. It only records participant-resolved temporal and transcript facts. The source intervals and dense targets remain unchanged. \textbf{Wearer entry.} Every raw wearer onset at $t_b$ is proposed as one wearer-entry review item. We search backward within the retrieval window for non-wearer offsets and store each one with its response delay and factual indicators of intervening wearer speech, intervening other onsets, and concurrent activity. These are possible context anchors rather than deterministically admissible causes. The LLM and human reviewer decide whether the boundary is a genuine new entry, a within-turn resumption, a wearer backchannel, or an excluded non-event. A preceding release is not required for a positive entry: the wearer may enter after a release, from silence, or while another speaker remains active. When a release clearly prompts the entry, the LLM or human may select one supplied option; neither may invent or move a timestamp. \textbf{INT-yield.} Every raw wearer offset $t_y$ is proposed as an INT-yield review item. The generator records the current wearer activity-run start, all nearby non-wearer onsets and offsets, activity immediately before and after $t_y$, whether an other speaker is pre-existing or begins during wearer speech, strict and 50-ms-tolerant boundary crossing, overlap duration, the next speech onset, transcripts, and target-of-speech metadata. Relations such as $t_w