`observation` cannot be extracted when `population` and `observation` names are the same

collect_adam_mapping() searches keywords in the following order: population > observation > parameter > analysis. Therefore, when population and observation are defined with the same name, population is prioritized in variable lookup. As a result, if variables specified in var of population do not exist in data_observation, an error occurs.

This may cause an error in collect_observation_record(). For example:

meta <- meta_adam(population = adsl, observation = adae) |>
  define_plan(plan = plan(analysis = "ae_forest_plot",
                          population = "apat",
                          observation = "apat",
                          parameter = "any-AE"           
  )) |>
  define_population(name = "apat",
                    group = "TRTA",
                    subset = SAFFL == "Y" ,
                    label = "All Participants as Treated Population",
                    var = c("USUBJID", "TRTA", "RACE", "SEX", "AGE", "AGEU")) |>
  define_observation(name = "apat",
                     group = "TRTA",
                     subset = SAFFL == "Y" ,
                     label = "All Participants as Treated Population") |>
  define_analysis(name = "ae_forest_plot",
                  label = "Interactive AE Forest Plot") |>
  define_parameter(name = "any-AE",
                   subset = SAFFL == "Y",
                   label = "Any AEs",
                   var = "AEDECOD", soc = "AEBODSYS", term1 = "", term2 = "") |>
  meta_build()

collect_observation_record(meta, "apat", "apat", "any-AE")

Start by reading collect_adam_mapping() and collect_observation_record(), then reproduce the supplied meta_adam() example with matching population and observation names. Done means the observation is resolved correctly without attempting to use population variables that are absent from data_observation.