Human-artificial intelligence interaction can shape what scholarly inquiry becomes about. This study examines research-object formation in two isolated scholarly trajectories developed by the same expert researcher with Claude and ChatGPT under matched starting conditions. Both used the same five-session, 843-turn project corpus, frozen research problem, initial prompt, publication objective, and conduct rules. The subsequent scholarly-development conversations were reconstructed ex post through consequential-event analysis, a Socioduality relational-process overlay, and tracing into completed manuscripts. Both trajectories shifted the continuity problem from recall toward usability, then developed different research objects: continuity labour and distributed, evolving project state. Failed analytical units, rejected explanations, counterexamples, and changes in analytical scale shaped these objects and propagated into research questions, methods, findings, evidence logic, and theoretical contributions. Consequential scholarly change, reciprocal relational continuity, and local substantive re-formation had distinct boundaries; continued interaction did not itself establish epistemic endorsement. The findings demonstrate empirically constrained research-object formation under matched scholarly starts. For systems supporting sustained scholarly knowledge work, they motivate recoverable analytical provenance, inspectable proposal status, and source-faithful contribution records.

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