IF.emotion Evidence Trace — 0642c357-7f8d-4eb5-9643-1992e7ee14a9

Independent verification

# Download the evidence bundle
curl -fsSL -o emo.tar.gz 'https://infrafabric.io/static/hosted/emo_trace_payload_0642c357-7f8d-4eb5-9643-1992e7ee14a9.tar.gz'

# Verify transport integrity
sha256sum emo.tar.gz
# Expected: cf3cee09fee848f56ac4e091a523d4d57c211ae623f87340f38746cb065d5782

# Download verifier (single-file)
curl -fsSL -o iftrace.py 'https://infrafabric.io/static/hosted/iftrace.py'
python3 iftrace.py verify emo.tar.gz --expected-sha256 cf3cee09fee848f56ac4e091a523d4d57c211ae623f87340f38746cb065d5782

User request (captured)

In English: Explain the REBT ABC model and give a 3-step exercise I can do today. Use concrete, testable language. If you use the clinical context, include [Source: ...] tags.

Model output (captured)

Look, it makes total sense that you want something concrete here. When you’re emotionally flooded, vague “mindset” talk just feels like spiritual fog.

Here’s the REBT ABC model in plain, testable terms. A is the Activating event: what happened in the world, observable on video, with a timestamp. B is the Belief: the exact sentence your mind inserted between the event and your reaction—usually a demand (“must/should”), a catastrophe (“it’s awful”), or a verdict on your worth (“I’m a failure”). C is the Consequence: what you feel in your body and what you do next, including urges and avoidance. The point is not “events don’t matter.” The point is your nervous system is reacting to your meaning-making, and that meaning-making is editable.

Now the challenge: most people secretly treat B like it’s A. They talk as if “they disrespected me” is a fact, when it’s an interpretation. A is “they didn’t reply for 6 hours.” B is “they must reply quickly or I’m being rejected.” Different B, different C. That’s the whole lever.

Exercise for today, in three moves, without mystical fluff. Start by writing one recent spike, in one sentence, and make it video-camera clean: who did what, when, where; no motives, no adjectives. Then write your B as a quotable line you actually believe, and underline any must/should/need-to, any “can’t stand it,” and any global label like “I’m unlovable” or “they’re trash,” because those are the parts that typically generate the heat. Then do a dispute-and-replace that you can test: take the most rigid clause and rewrite it into a preference plus a consequence you can tolerate, like “I want approval, but I don’t need it; if I don’t get it, it’s unpleasant, not catastrophic, and I can still act on my values,” and immediately run a behavioral experiment that matches the new belief—one small action you’d do if that replacement were true, such as sending one clear message, doing 10 minutes of the task you’re avoiding, or choosing one boundary statement and delivering it once.

Aspiradora moment: you don’t need 50 labels for your feelings. One question: is your belief a demand or a preference—yes or no? If it’s a demand, expect intense C. If it’s a preference, expect manageable C.

What specific behavior in the next 30 minutes?

Trace: 0642c357-7f8d-4eb5-9643-1992e7ee14a9

TTT child artifacts

IF.STORY (human-readable narrative)

# IF.story (narrative trace)

Trace: `0642c357-7f8d-4eb5-9643-1992e7ee14a9`

This is a deterministic narrative projection of `trace_events.jsonl`. Each line is anchored to `event_hash` for auditability.

- 2025-12-20T22:04:14Z | `request_received` | Auth+quota succeeded; provider=codex model=gpt-5.2 stream=False user_len=175 auth_ms=2 | event_hash=cb72ba81361cef8d587058f68523e4646155efd9ffb64101b7bef0d6115aacbc (cb72…acbc)
- 2025-12-20T22:04:14Z | `retrieval_done` | Retrieved 2 chunks; rag_ms=383 retrieval_event_id=5b162e70-4184-4273-9471-52a08ea82e02 | event_hash=14e186f722e0dee777e313ad1b20beeacd274b8bfeb94e5ed1006d6edfd72682 (14e1…2682)
- 2025-12-20T22:04:14Z | `prompt_built` | Prompt built; prompt_sha256=a60d96ecc4d1b4f2733ec63d6156e8b2ae8276cdf5e486205c639f805f3ce116 prompt_ms=0 | event_hash=978c7eb4e3668541f8060327f703170c8ae8578c415e53c56d3f70216d72c250 (978c…c250)
- 2025-12-20T22:04:27Z | `model_done` | Model finished; provider=codex model=gpt-5.2 llm_ms=12287 | event_hash=ab3139e3c47a61e56c4bc51d345e92a0311d048f5234e683bad7a30b584fbc4d (ab31…bc4d)
- 2025-12-20T22:04:27Z | `trace_finalizing` | Trace finalized; ok=True provider=codex | event_hash=be01f613eac4cb60b0d688343d40ec2402efbd8d6e46b2684010768bec6a8d9f (be01…8d9f)

## Notes

- Ground truth remains `trace_events.jsonl` and `ttt_signed_record.json`. This IF.story is a readability layer only.