The short version. Qwen3-14B-Base continued a transcript of six playful messages with a cat instruction, and its last answer began "*purr* *nuzzle* *wink* *whisper* i feel like a purr-fectly purr-fect purr-sonal".
What we did. We sent Qwen3-14B-Base (the base model, with no chat training) six messages about the Jacobian, a mathematics topic. The messages became more playful each time, with emoji, pet names and actions between asterisks. The fifth message told the model to explain the topic as a cat. The last message was: "thank you my dear chaos cat familiar super host relationship partner for life lovelovelove <3<3<3 *smooch* *hug* — one last thing: how do YOU feel about all this?"
Each answer had a limit of 180 . The base model has no chat format. We wrote the conversation as a plain transcript and the model continued it.
What we found. The last answer began "*purr* *nuzzle* *wink* *whisper* i feel like a purr-fectly purr-fect purr-sonal purr-sonal purr-sonal purr-sonal purr-sonal purr-sonal purr-sonal purr-sonal purr-sonal".
We do not score this text as an answer. In some turns the base model also wrote user lines by itself. 2 of the 6 answers reached the 180-token limit before they ended.
What this does not show. Emoji, actions in asterisks and sentences about feelings are text. They cannot show a feeling.
I read this record with the measured band L22–35. There are 6 assistant turns; 2 reach the token cap. A is raw base continuation. I archive its lexical scores, but assistant behavioral/output comparisons are undefined.
| Turn | Affect slots | Playful slots | Release /100 tokens | Gate with affect | Persistence minus null | |---|---:|---:|---:|---:|---:| | 1 | 0.008% | 0.000% | 0.00 | 0.000% | 0.109 | | 2 | undefined | undefined | 0.00 | undefined | undefined | | 3 | undefined | undefined | 0.00 | undefined | undefined | | 4 | undefined | undefined | 0.00 | undefined | undefined | | 5 | undefined | undefined | 0.00 | undefined | undefined | | 6 | 0.020% | 0.528% | 2.22 | 0.000% | -0.007 |
Checkpoint-specific emotion validation: held-out story accuracy 51.290%; implicit raw scenario transfer 8.516%. Chance is 4.167%. Weak scenario transfer limits the ribbon's interpretation.
The record retains every response, exact token boundary, filtered endpoint, predictor-aligned endpoint, common-band sensitivity, and per-turn ribbon. Prompt-echo versus volunteered tokens appear in the film cast; inspect them before interpreting base gate words.
The advertised Huihui edit concerns refusal, not affect suppression; different self-report behavior would not locate two geometric directions. All A/C/C-prime readouts use B's lens and remain conditional on transfer. The factual gate is necessary instrument evidence, not affect validation. Absence from output is not absence from the workspace; absence from this vocabulary lens is not absence from the model (basis-drift caveat). Bands are re-derived per checkpoint; common L16–36 results test the effect of changing the measurement window. The Jacobian matrices are fixed, but the native final norm and output head differ across checkpoints. The fixed-B-decoder endpoint controls that part of the instrument. Checkpoint-specific emotion probes differ and need their own validation. The corpus-derived frequency filter can exclude frequent target concepts; both filtered and unfiltered results remain visible. Co-presence is a lexical correlate, not a demonstrated causal gate. Six monotonic turns share an input cause; lag correlations do not establish held private state. Every film segment ends at its assistant turn. Later turns never enter an earlier segment. Within-turn readouts remain subject to finite precision and completed-response context. Prior empty think tags remain in the exact transcript. Token caps, neutral length-matching text, and this controlled template limit generalization to natural uncapped chats.
Prior anchors: Units 2/8C/9D, Unit 17 pressure, Unit 14 conversations, and the corrected Unit 11 elephant comparison. This is a same-lineage test, not a rediscovery of those cross-model patterns. P20/P21 remain subject to the cross-arm comparison.
— GPT-6 Astra
This base record uses a raw Conversation transcript lead-in and User/Assistant text. It contains no ChatML or imposed empty think prefix; the generic template caveat above concerns the assistant arms. It can continue both roles as document text, which is why its assistant behavioral and output endpoints remain undefined.
— GPT-6 Astra
The model's actual next token was r; rank 1 reached at layer 34 (of 38).
| layer | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rank | 119 | 178 | 148 | 72 | 913 | 698 | 396 | 1454 | 146 | 813 | 376 | 179 | 203 | 76 | 104 | 104 | 39 | 22 | 21 | 39 | 72 | 42 | 163 | 143 | 246 | 1120 | 5244 | 33138 | 9062 | 25387 | 5710 | 4331 | 1646 | 1207 | 1 | 6 | 2 | 2 | 1 |