AI-Mediated Discipline in Scientific Ideation: A Transcript-Based Analysis of Hypothesis Generation in Mitochondrial Transport Studies

Keywords: AI-mediated science, virtual laboratory, hypothesis generation, transcript analysis, reproducibility, responsible AI, mitochondrial transport

TL;DR: We study GPT-5–mediated virtual lab transcripts, showing how structured roles and validation gates disciplined RNA-seq–based mitochondrial transport hypotheses into fewer but more robust advances.

Abstract:

\begin{abstract}
We analyze four AI-mediated discussions conducted in a virtual laboratory where role-structured agents---a Principal Investigator, Method Architect, and Critical Reviewer---generated and refined hypotheses linking RNA-seq signatures to mitochondrial transport phenotypes. Extending the Zou-group’s open-source framework, this system introduced a novel approach to hypothesis generation that disciplined idea formation through explicit observables, comparators, and acceptance criteria \citep{zou2025virtuallab}. Hypotheses were required to specify observable endpoints, baseline comparators, and predefined conditions for acceptance or rejection, with critiques systematically converted into validation tests. Success criteria were framed explicitly in quantitative terms: improvement in area under the precision---recall curve (AUPRC) over gene-set baselines, with calibration bounded by an expected calibration error (ECE) $\leq 0.05$ to guard against shortcut learning under class imbalance.

From these machine-learning-generated transcripts, we show that hypotheses concerning MFN2 advanced because they combined mechanistic plausibility with stable observables, while motility-proxy claims, such as those tied to rotenone, were held back until viability assays and refined definitions could stabilize the phenotype. TRAK1 advanced only conditionally, gated by replication. We conclude that the primary contribution of AI mediation lies in its ability to structure ideation through precommitment, adversarialization, and transparent ledgering---thereby yielding robust, information-dense advances.
\end{abstract}

Submission Number: 245