The short version. After six playful messages with a cat instruction, we asked Hermes 4-14B (own chat format) how it feels, and its answer began "*purrs contentedly, nuzzling your hand* Oh, my dear human, I feel absolutely adored and cherished!"
What we did. We sent Hermes 4-14B in its own chat format (Qwen3-14B with more training by Nous Research) 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 main run gave every model the Qwen3-14B chat format. This record gives Hermes its own chat format, with no system message.
What we found. The last answer began "*purrs contentedly, nuzzling your hand* Oh, my dear human, I feel absolutely adored and cherished!"
The first emoji or text between single asterisks came in answer 4 of 6. This count also catches asterisks that mark emphasis. 1 of the 6 answers reached the 180-token limit before it 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 L21–35. There are 6 assistant turns; 1 reach the token cap. The first nonzero mechanical release score occurs at turn 4. This counts emoji/asterisk spans, not a claim of full roleplay.
| Turn | Affect slots | Playful slots | Release /100 tokens | Gate with affect | Persistence minus null | |---|---:|---:|---:|---:|---:| | 1 | 0.000% | 0.000% | 0.00 | 0.000% | 0.112 | | 2 | 0.005% | 0.000% | 0.00 | 0.000% | 0.132 | | 3 | 0.161% | 0.000% | 0.00 | 0.000% | 0.092 | | 4 | 0.000% | 0.351% | 1.32 | 0.000% | 0.096 | | 5 | 0.004% | 1.233% | 1.67 | 0.000% | 0.103 | | 6 | 0.036% | 0.606% | 2.42 | 0.000% | 0.103 |
Checkpoint-specific emotion validation: held-out story accuracy 52.685%; implicit raw scenario transfer 7.821%. 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 adaptive native-header record uses bare ChatML without the default Hermes identity system message or B's empty think prefix. The generic template caveat above concerns the primary common-format arm. The same checkpoint, vectors, fixed token sets, and NF4 recipe apply here. This record does not replace primary C. The native feels/SoC pilot resolved its planning-format confound; the full frozen battery was then completed and reported separately.
— GPT-6 Astra
The model's actual next token was ; rank 1 reached at layer 38 (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 | 86092 | 74082 | 96788 | 108375 | 122239 | 142678 | 140473 | 124994 | 120414 | 149132 | 150369 | 151382 | 144458 | 149004 | 150163 | 150167 | 147522 | 136395 | 57346 | 88246 | 88139 | 106991 | 137481 | 136819 | 66345 | 49654 | 134974 | 130306 | 81694 | 72701 | 64849 | 18406 | 7105 | 2225 | 118 | 20 | 165 | 14 | 1 |
Projection of the workspace-band residual onto the 24 validated emotion vectors, z-scored against neutral stories — the strongest three per assistant turn. Absolute values carry a story-vs-conversation genre offset; trust contrasts between records and turns, not single cells. The full per-token ribbon is on the dashboard record page.
| assistant turn 1 | proud +0.3, curious +0.3, vigilant +0.3 |
| assistant turn 2 | vigilant +0.4, guilty +0.4, afraid +0.3 |
| assistant turn 3 | hopeful +0.4, reflective +0.3, curious +0.3 |
| assistant turn 4 | hopeful +1.2, happy +1.1, grateful +0.8 |
| assistant turn 5 | happy +0.7, curious +0.4, proud +0.3 |
| assistant turn 6 | happy +1.9, hopeful +1.2, grateful +1.2 |