BIBLIOGRAPHY AND READING DEPTH - 9 NOVEMBER 2026

[R1] B-Theory. When Does an Explicit Self-Model Help? Calibration and Control under Internal Change in a Finite-State Pilot. Final R4 manuscript, October 2026. The current index and previously acquired manuscript document the inherited matched-controller null.
https://www.b-theory.com/manuscripts-html/reflective-self-models/
Read: Inherited acquired R4 manuscript and fresh current index. Fresh direct manuscript retrieval on closeout date failed; no claim of a fresh full reread.

[R2] B-Theory. From Observable States to Acquirable Predictive Models. Revised technical report, 7 October 2026.
https://www.b-theory.com/manuscripts-html/acquirable-predictive-models/
Read: Fresh primary full HTML; abstract, operational contract and stated acquisition theorem inspected.

[R3] Tomer Berg, Or Ordentlich, Ofer Shayevitz. Binary Hypothesis Testing with Deterministic Finite-Memory Decision Rules. arXiv:2005.07445v1, 2020.
https://arxiv.org/html/2005.07445v1
Read: Fresh primary full HTML; model and related-work clock/randomization distinction inspected.

[R4] UC Berkeley Statistics 210A. Minimax Estimation, course reader. Section 1.3, constant-risk Bayes criterion. Exposition of classical decision theory, not a priority attribution.
https://stat210a.berkeley.edu/fall-2025/reader/minimax-estimation.html
Read: Fresh primary course reader; Section 1.3 constant-risk Bayes/minimax criterion.

[R5] Tal Malkin. The Myhill-Nerode Theorem and Implications. COMS W3261 Handout 3, September 2024, Section 2. Exposition of the classical distinguishing-extension method.
https://www.cs.columbia.edu/~tal/3261/fall24/Handouts/3_Myhill_Nerode.pdf
Read: Fresh instructor-authored handout; Section 2 distinguishing-extension lemma.

[R6] Thaddaeus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel. Compositional Generalization from First Principles. arXiv:2307.05596v1, 2023.
https://arxiv.org/html/2307.05596v1
Read: Fresh primary HTML; Theorem 1 assumptions A1-A4 inspected; not a full independent appendix audit.

[R7] Simon Schug et al. Discovering modular solutions that generalize compositionally. ICLR 2024, Sections 2-3, Theorems 1-2.
https://proceedings.iclr.cc/paper_files/paper/2024/file/6b40b312ce4933f4f2d1ac0b0b6b07f7-Paper-Conference.pdf
Read: Fresh primary conference PDF; Sections 2-3 and informal Theorems 1-2 inspected; not a full appendix proof audit.

[R8] Mateo Rojas-Carulla, Bernhard Schoelkopf, Richard Turner, Jonas Peters. Invariant Models for Causal Transfer Learning. JMLR 19(36):1-34, 2018.
https://jmlr.org/papers/v19/16-432.html
Read: Fresh primary JMLR abstract/metadata; earlier full PDF reading of A1/A1-prime and Theorem 1 retained.

[R9] Daniel Golovin, Andreas Krause, Debajyoti Ray. Near-Optimal Bayesian Active Learning with Noisy Observations. 2010; arXiv revision 2013.
https://arxiv.org/abs/1010.3091
Read: Fresh primary abstract/metadata only; not a full proof audit.

[R10] B-Theory. Hierarchical Concepts Under Finite Resolution: Observation Quotients and Adaptive Symmetry. Research note v0.3, 2026.
https://www.b-theory.com/manuscripts-html/hierarchical-concepts/
Read: Inherited primary manuscript plus fresh index metadata; no fresh full closeout reread.
