The linear predictor is unchanged by , , . Without constraints, different parameter triples therefore give the same rates and likelihood. Identifiability requires choosing one representative of this redundancy.
Taking the first levels as reference yields . Then
These identify all three free parameters, while is the model's no-interaction constraint. The zero reference effects fix a parametrization; they do not remove the baseline rate or impose equal rates across groups.

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