# Literature verification notes

Canonical bibliography support for Series II / Paper 01.

Verification date: 2026-08-14.

1. Salganik, Dodds & Watts (2006). Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market. Science 311(5762):854-856. DOI 10.1126/science.1121066.
2. Horvat, Vlasceanu, Robertson & Watts (2024). Collective Dynamics Behind Success: Regularities, Mechanisms, and Predictive Signals. Nature Communications 15:10701. DOI 10.1038/s41467-024-54612-4.
3. Zhu et al. (2021). Popularity-Opportunity Bias in Collaborative Filtering. WSDM 2021. DOI 10.1145/3437963.3441820.
4. Wang et al. (2025). Item-centric Exploration for Cold Start Problem. RecSys 2025, 987-990. DOI 10.1145/3705328.3748113.
5. Stavrova et al. (2025). Scientific Publications That Use Promotional Language in the Abstract Receive More Citations and Public Attention. Communications Psychology 3:118. DOI 10.1038/s44271-025-00293-8.
6. Kang et al. (2025). Limited Diffusion of Scientific Knowledge Forecasts Collapse. Nature Human Behaviour 9:268-276. DOI 10.1038/s41562-024-02041-0.
7. Lorenz-Spreen et al. (2019). Accelerating Dynamics of Collective Attention. Nature Communications 10:1759. DOI 10.1038/s41467-019-09311-w.

Boundary notes:
- AMNESS and the formal Quality Non-Determinacy Theorem are introduced in this paper.
- The theorem is structural: it states that if success genuinely depends on non-quality variables, quality alone cannot universally determine success.
- The rank-reversal example is constructive, not an empirical law that low-quality items usually outperform high-quality items.
- Existing cultural-market, recommendation, cold-start, communication, and diffusion research provides empirical mechanisms consistent with the separation of quality, exposure, popularity, and success.
- The paper does not claim a universal scalar measure of quality.