anchor.diff:  !******************************************************************************
   !******************************************************************************
   SUBROUTINE fort_evaluate(rslt, periods_payoffs_systematic, mapping_state_idx, periods_emax, states_all, shocks_cholesky, data_array, periods_draws_prob)
  +
  +    !   DEVELOPMENT NOTES
  +    !
  +    !   This routine accepts assumed shape arrays to allow its use during parallel execution as well. This is also the reasoning behind relaxing the alignment with the PYTHON counterpart.
   
       !/* external objects        */
   
  
positive.code: !------------------------------------------------------------------------------
  
      ! Construct auxiliary objects
      shocks_cov = MATMUL(shocks_cholesky, TRANSPOSE(shocks_cholesky))
      is_deterministic = ALL(shocks_cov .EQ. zero_dble)
  
      ! Initialize container for likelihood contributions
      crit_val = zero_dble
  
      j = 1
  
      DO i = 0, num_agents_est - 1
  
          DO period = 0, num_periods -1
  
              ! Extract observable components of state space as well as agent decision.
              exp_a = INT(data_array(j, 5))
  
negative.code:             ! Adjust  and record likelihood contribution
              crit_val(j) = prob_obs
  
          END DO
  
      ! Scaling
      crit_val = clip_value(LOG(crit_val), -HUGE_FLOAT, HUGE_FLOAT)
      rslt = -SUM(crit_val) / num_obs
  
      ! If there is no random variation in payoffs and no agent violated the implications of observed wages and choices, then the evaluation return a value of one.
      IF (is_deterministic) THEN
  