`data[i, "γ (N/m)"] ~ Normal(γ_pred, σ)` disallowed in Turing.jl in v0.42? how to fix?

Specific Domains Probabilistic Programming
1

a Turing.jl breaking changes question:
I updated ↑ Turing v0.41.1 ⇒ v0.42.8, then my code broke.

is data[i, "γ (N/m)"] ~ Normal(γ_pred, σ) disallowed now? see code and error below.

I looked for breaking changes in 0.42.0 release here but didn’t see a breaking change regarding this.

many years ago, I learned from the Bayesian ODE tutorial here and it changed to a vectorized statement data[:, i] ~ arraydist(Poisson.(q .* predicted[i] .+ ϵ)) but I tried a similar expression, and the error remains!

the code

@model function cmc_model(data::DataFrame)
	# surface tension of pure water
	@assert data[1, "[S] (mol/m³)"] == 0.0
	γ₀_obs = data[1, "γ (N/m)"]
		
	#=
	prior distributions
	=#
	γ₀ ~ Normal(γ₀_obs, σ)    # N/m
	a ~ Uniform(0.001, 0.1)   # N/m
	K ~ Uniform(0.0, 10000.0) # (mol/m³)⁻¹
	if surfactant == "OTG"
		c★ ~ Uniform(0.0, 30.0)  # mol / m³
	elseif surfactant == "Triton-X-100"
		c★ ~ LogUniform(0.001, 10.0)  # mol / m³
	end
	
	#=
	show data
	=#
	for i = 2:nrow(data)
		# surfactant concentration
		cᵢ = data[i, "[S] (mol/m³)"]
		
		# predicted surface tension
		γ_pred = γ_model(cᵢ, γ₀, a, K, c★)
		
		data[i, "γ (N/m)"] ~ Normal(γ_pred, σ)
	end
	
	return nothing
end

the error

MethodError: no method matching possible(::typeof(BangBang._setindex!), ::DataFrames.DataFrame, ::Float64, ::Int64, ::String)
The function `possible` exists, but no method is defined for this combination of argument types.