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Using Bayes' theorem and the quantum formalism, one can infer unobserved variables from observed variables in a quantum experiment [1]. Quantum mechanics specifies the physical relations among these variables. These relations can be expressed as a joint probability distribution which can then be factorized into a causal model. Based on [2-3] we propose a simple causal model in which the transformation between two sequential measurements is a collider for the hidden variables and observables associated with each measurement; conditioning on this collider induces a correlation between the measurements. This perspective helps explain why the model has been overlooked: it involves future-input dependence, in that the collider variable is an effect of variables in its future---the hidden variable and the observable associated with the second measurement. [1] Di Biagio, A., Donà, P., & Rovelli, C. (2021). The arrow of time in operational formulations of quantum theory. Quantum, 5, 520. [2] Price, H., & Wharton, K. (2021). Entanglement swapping and action at a distance. Foundations of Physics, 51(6), 105. [3] Price, H., & Wharton, K. (2025). Taming entanglement. arXiv preprint arXiv:2507.15128.