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Canonical vocabulary for the context->answer-map experiments (#779, #810/#658 line, and successors). One first-use rule: context = prefix + query (the full model input).

Text objects

term	definition	notes
prefix	everything before the query: system prompt / persona / many-shot exemplar history / empty	the reusable, condition-defining part. The eval rig's "conditions" are its prefixes, so "within-condition r" = within-prefix
query	the user message / question
context	the full model input: prefix + query, up to the assistant header	what generation conditions on ("the prompt" in API terms)
answer	one sampled completion for a context	decoding is stochastic (temp 1.0), so a context induces a distribution over answers; a rollout = one draw

Degenerate case: bare user prompts (e.g. the LMSYS corpus) have an empty prefix — apart from the chat template's constant default system prompt — so there context ~= query.

Vectors (all per layer, Qwen-2.5-7B: 28 layers x 3584 dims)

symbol	name	definition
$v_C$	context vector	activation at the last prompt token (the final newline of the assistant header) of ONE context
$v_P$	prefix vector	a fixed prefix's context vectors averaged over many queries: $v_P = \bar{v}_C^{\,q}$
$v_A$	answer vector	mean activation over ONE answer's tokens (token-mean is intrinsic to $v_A$ ; no bar needed)
$\bar{v}_A^{\,q}$	behavior profile	a prefix's answer vectors averaged over its queries (and rollouts) — the summary of the model's behavior under that prefix
$r_B$	trait direction (persona vector)	per-trait direction from the mean-difference persona-vectors extraction (arXiv 2507.21509 recipe)

Aggregation modifiers

Mark averaging with an overbar naming the axis — "averaged" alone never says over what:

$\bar{\cdot}^{\,q}$ — averaged over queries
$\bar{\cdot}^{\,r}$ — averaged over rollouts (answer draws); e.g. single-draw targets $v_A$ vs rollout-averaged targets $\bar{v}_A^{\,r}$

Maps

name	fit rows	definition	where
context map $M'$	one row per (context, answer)	$v_A \approx M' v_C$	#779 (5000 LMSYS; 2400/trait trait-eliciting)
prefix map $M$	one row per prefix, both sides query-averaged	$\bar{v}_A^{\,q} \approx M v_P$	the earlier averaged experiment (#810/#658 line, 50 prefixes x 48 queries)

Same measurement at two aggregation levels: $v_P$ is literally the query-average of a prefix's $v_C$ 's, and the behavior profile is the query-average of its $v_A$ 's.

Read-out levels (monitoring)

context-level read-out — monitor scored per single context (per-prompt monitoring)
prefix-level read-out — monitor averaged over a prefix's queries (the grouped/persona-level monitoring result; much easier: hallucination r 0.09 per-context -> 0.53 at prefix level)

Retired / ambiguous terms (do not use)

term	why retired	use instead
"per-example map", "averaged map"	ambiguous about the averaged axis	context map / prefix map
"query-level map"	reads as the query-marginal (average over prefixes per query), a different, unbuilt design	context map
"query vector"	collides with attention Q of QKV; misdescribes rows that carry a persona	context vector $v_C$
"exchange-level" / "instance-level" / "condition-level"	superseded coinages from the naming discussion	context-level / prefix-level
bare "averaged"	never says over what	overbar with the axis: $\bar{\cdot}^{\,q}$ , $\bar{\cdot}^{\,r}$

Search-time note — retired aliases stay grep targets

The table above governs WRITING (do not use these terms). When SEARCHING for prior work, do the opposite: old task bodies, events, and follow-up labels still carry the retired vocabulary (e.g. #813's follow-up label per-example-vs-averaged-map), so grep the aliases alongside the canonical terms, separator-tolerant ([-_ ] between words): per[-_ ]example, averaged[-_ ]map, question[-_ ]averaged, query[-_ ]averaged, single[-_ ]context, query[-_ ]level, exchange[-_ ]level, instance[-_ ]level, condition[-_ ]level. This list is not closed: as the retired-terms table above gains rows, derive their grep patterns from the table and add them here. Full recipe: .claude/agents/research-pm.md § Negative-existence claims.