Layer 0 Axis: `study_scope`

Parent: Layer 0
Current: study_scope

study_scope describes the broad shape of the study: how many targets are being forecast and whether the recipe compares multiple method alternatives. It is a Layer 0 setup axis because it affects routing, sweep interpretation, Navigator flow, and manifest metadata before any data or model details are chosen.

The compiler can derive study_scope when it is omitted. Navigator and replication recipes may set it explicitly.

Values

Value	Status	Target Shape	Method Shape
`one_target_one_method`	operational	one target	one fixed method path
`one_target_compare_methods`	operational	one target	controlled method comparison
`multiple_targets_one_method`	operational	multiple targets	one fixed method path
`multiple_targets_compare_methods`	operational	multiple targets	controlled method comparison

All four values currently route through the comparison-sweep owner. A run with one target and one method is still a 1x1 sweep case for provenance consistency.

Derivation

When study_scope is omitted, the compiler derives it from:

Input Shape	Derived Value
single target, fixed method axes	`one_target_one_method`
single target, swept model or feature axes	`one_target_compare_methods`
multi target, fixed method axes	`multiple_targets_one_method`
multi target, swept model or feature axes	`multiple_targets_compare_methods`

This derivation should be treated as a defaulting rule. If the recipe sets study_scope explicitly, the compiler checks it against target structure.

Compatibility Rules

Rule	Outcome
`multiple_targets_*` with single-target task	invalid
`one_target_*` with `target_structure=multi_target`	invalid
`multiple_targets_*` with `target_structure=multi_target`	valid
method-comparison scope with no swept method axis	valid but semantically broad

Layer 1 owns the actual target list and target structure. Layer 0 only records the intended study shape.

YAML

Single target, one method:

0_meta:
  fixed_axes:
    study_scope: one_target_one_method

Single target, method comparison:

0_meta:
  fixed_axes:
    study_scope: one_target_compare_methods

Multi-target method comparison:

0_meta:
  fixed_axes:
    study_scope: multiple_targets_compare_methods

1_data_task:
  fixed_axes:
    target_structure: multi_target
  leaf_config:
    targets: [INDPRO, CPIAUCSL, UNRATE, PAYEMS, RPI]

When To Choose Each Value

Research Intent	Use
Debug one baseline forecast	`one_target_one_method`
Compare models/features for one macro target	`one_target_compare_methods`
Run the same specification over several targets	`multiple_targets_one_method`
Compare methods over several targets	`multiple_targets_compare_methods`

Notes

study_scope is not a model choice.
study_scope is not a target selector; Layer 1 stores target names.
study_scope is not sweepable.
The public values above are the registry values. Do not use aliases such as multi_output_joint_model in new recipes.

Layer 0 Axis: study_scope