Qiskit Tomography and Noise Mitigation with a Measurement Mid-Execution

I’m struggling to get a program running where I have a circuit with a measurement and reset mid-execution and I want to use noise mitigation and state tomography together.

The circuit is defined

qreg_q = QuantumRegister(2, "q")
creg_c = ClassicalRegister(1, "c")

qc = QuantumCircuit(qreg_q, creg_c)

qc.u(1, 1, 1, qreg_q[0])

qc.cu(1, 0, 0, 0, qreg_q[0], qreg_q[1])
qc.cx(qreg_q[1], qreg_q[0])
qc.measure(qreg_q[1], creg_c[0])
qc.reset(qreg_q[1])

N.B I don’t need the measurement result here.

I then create my tomography circuits from this

from qiskit.ignis.verification.tomography import state_tomography_circuits, StateTomographyFitter
qpt_circs = state_tomography_circuits(qc, qreg_q[0])

and the calibration circuits

import qiskit.ignis.mitigation.measurement as mc

cal_qr = QuantumRegister(2)
cal_cr = ClassicalRegister(2)

meas_calibs, state_labels = mc.complete_meas_cal(qublit_list=[0])

Using a simulator with a noise-model

backend = provider.get_backend('ibmqx2')
sim = AerSimulator.from_backend(backend)

I run the calibration circuit

job_cal = sim.run(meas_calibs, shots=8192)

meas_fitter = mc.CompleteMeasFitter(job_cal.result(), state_labels)

I then run the tomography circuits

qpt_circs_compiled = transpile(qpt_circs, sim)
job_tomo = sim.run(qpt_circs_compiled, shots=8192)

result = job_tomo.result()

tomo_state = StateTomographyFitter(result, qpt_circs)

I’m able to obtain a state from the result with tomography

state = tomo_state.fit()

However the noise mitigation fails

meas_filter = meas_fitter.filter
mitigated_results = meas_filter.apply(result)

with QiskitError: "Unexpected state label '0 0', verify the fitter's state labels correspond to the input data".

It seems to me that the tomography circuits add a second classical register that the noise mitigation circuits isn’t configured to process properly. How can I get around this so I can mitigate the noise in my density matrix output?