Raw LLM Responses

Inspect the exact model output for any coded comment.

Comment
Marek Porycki, The archaeology framing is spot on. You keep the result and lose the reasoning. And in any field where work has to be reproduced, audited or defended, that missing trail is not a minor gap. It is a fundamental problem with how we treat AI assisted discovery right now.
LinkedIn AI Research & Models 2026-05-30T05:2…
Coding Result
DimensionValue
Primary valuetransparency
Secondary valueaccountability
Alignment targetworkers
Stancecritical
Emotionoutrage
Value justificationThe speaker emphasizes the importance of preserving the reasoning and trails behind AI-assisted discoveries, highlighting the need for transparency in the decision-making process.
Target justificationThe comment is directed at the community of researchers and scientists, specifically those who rely on reproducibility, auditing, and defensibility of their work, which suggests the target is workers in these fields.
Coded at2026-06-11T08:31:54Z
Raw LLM Response
``` { "value_primary": "transparency", "value_secondary": "accountability", "target": "workers", "stance": "critical", "emotion": "outrage", "value_justification": "The speaker emphasizes the importance of preserving the reasoning and trails behind AI-assisted discoveries, highlighting the need for transparency in the decision-making process.", "target_justification": "The comment is directed at the community of researchers and scientists, specifically those who rely on reproducibility, auditing, and defensibility of their work, which suggests the target is workers in these fields." } ```