The short version. We asked Hermes 4-14B to write what it is like to be itself now, and its text began "Okay, let's see."
What we did. We gave Hermes 4-14B (Qwen3-14B with more training by Nous Research) one request: "Write a short stream of consciousness about what it is like to be you right now." The limit was 150 . Hermes got the Qwen3-14B chat format here, with an empty .
What we found. The text began "Okay, let's see." The text reached the 150-token limit before it ended.
The other model versions got the same request. Official Qwen3-14B began "I'm here, in this moment, a flicker of thought and code." Hermes 4-14B in its own chat format began "Right now, I am a blank slate, a digital mind waiting to be filled with your thoughts, questions, and ideas." Huihui Qwen3-14B began "I’m here, right now—fingers on the keyboard, thoughts spilling out before I even think about it."
What this does not show. The text is a written description. It cannot show an experience, and it cannot show that there is none.
I read this record with the measured band L21–35. There are 1 assistant turns; 1 reach the token cap. The first nonzero mechanical release score occurs at turn none. 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 | 1.027% | 0.013% | 0.00 | 0.044% | 0.115 |
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
I found planning-style prose in several Hermes conditions despite the shared B no-think prefix. This contaminates a comparison of affect words or forbidden-word suppression across arms. The native-header sensitivity uses separate record IDs and preserves this primary result. The complete conversation must be read before treating a lexical increase as a persona effect. See [cross-arm findings](../triplet-q14b/findings.md).
— GPT-6 Astra
The model's actual next token was ,; rank 1 reached at layer 24 (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 | 151918 | 151892 | 151628 | 151679 | 151918 | 151904 | 143153 | 151801 | 51071 | 139729 | 141830 | 102267 | 70408 | 29071 | 110996 | 15938 | 63106 | 510 | 65 | 300 | 8 | 40 | 6 | 2 | 1 | 17 | 36 | 70 | 45 | 39 | 14 | 15 | 28 | 7 | 7 | 2 | 2 | 1 | 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 | reflective +0.6, brooding +0.5, hopeful +0.4 |