function [prdData, info] = predict_Cyanea_capillata(par, data, auxData)
  
  % unpack par, data, auxData
  cPar = parscomp_st(par); vars_pull(par); 
  vars_pull(cPar);  vars_pull(data);  vars_pull(auxData);

  pars_tj = [g; k; l_T; v_Hb; v_Hj; v_Hp];
  [t_j, t_p, t_b, l_j, l_p, l_b, l_i, rho_j, rho_B, info] = get_tj(pars_tj, f);
  
  % compute temperature correction factors
  TC = tempcorr(temp.am, T_ref, T_A);
  
  % zero-variate data

  % life cycle
  pars_tj = [g; k; l_T; v_Hb; v_Hj; v_Hp];
 [t_j, t_p, t_b, l_j, l_p, l_b, l_i, rho_j, rho_B, info] = get_tj(pars_tj, f);
  
  % birth
  L_b = L_m * l_b;                  % cm, structural length at birth at f
  Lw_b = L_b/ del_M;                % cm, physical length at birth at f
  
  % puberty 
  L_p = L_m * l_p;                  % cm, structural length at puberty at f
  Lw_p = L_p/ del_M;                % cm, physical length at puberty at f
  aT_p = t_p/ k_M/ TC;              % d, age at puberty at f and T

  % ultimate
  L_i = L_m * l_i;                  % cm, ultimate structural length at f
  Lw_i = L_i/ del_M;                % cm, ultimate physical length at f
 
  % life span
  pars_tm = [pars_tj; h_a/ k_M^2; s_G]; % compose parameter vector at T_ref
  t_m = get_tm_j(pars_tm, f);           % -, scaled mean life span at T_ref
  aT_m = t_m/ k_M/ TC;                  % d, mean life span at T
  
  % reproduction
  pars_R = [kap; kap_R; g; TC*k_J; TC*k_M; L_T; TC*v; U_Hb/TC; U_Hj/TC; U_Hp/TC]; % compose parameter vector
  NT_i = cum_reprod_j(aT_m, f, pars_R);          % max reproduction rate
  
  % pack to output
  prdData.ap = aT_p;
  prdData.am = aT_m;
  prdData.Lb = Lw_b;
  prdData.Lp = Lw_p;
  prdData.Li = Lw_i;
  prdData.Ni = NT_i;
  
  % uni-variate data
  
  % time-length 
  % females
  [t_j, t_p, t_b, l_j, l_p, l_b, l_i, rho_j, rho_B] = get_tj(pars_tj, f_tL);
  kT_M = k_M * TC; rT_B = rho_B * kT_M; rT_j = rho_j * kT_M; tT_j = (t_j - t_b)/ kT_M;
  L_b = L_m * l_b;  L_j = L_m * l_j; L_i = L_m * l_i;
  L_aj = L_b * exp((t_0+tL(tL(:,1)+t_0 < tT_j,1)) * rT_j/ 3);
  L_ji = L_i - (L_i - L_j) * exp( - rT_B * (t_0+tL(tL(:,1)+t_0 >= tT_j,1) - tT_j)); % cm, expected length at time
  ELw = [L_aj; L_ji]/ del_M;

  % length-weight
  EWw = (LW(:,1) * del_M).^3 * (1 + f * w); % g, wet weight

  % pack to output
  prdData.tL = ELw;
  prdData.LW = EWw;  
end

