LocationRecommendationResult
assumptions object
axis_reasons object[]required
Possible values: [age, household_income, gender, education_level, number_of_children, racial_group, home_ownership, household_with_children, household_size]
boundary objectrequired
- integer[]
- string[]
experiment_configuration_patches object[]
United StatesPossible values: [Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming]
target_population objectrequired
year object
- string
- null
non_us_target_population object
- NonUSDemographicBoundary
- null
Country-appropriate demographic boundary for non-US populations.
Mirrors the US DemographicBoundary but uses holodeck's Non-USA axes.
Field value vocabularies are constrained (via enums / Literal) to the
exact non-US checkbox options, so any off-vocabulary LLM value is rejected
at the boundary and the frontend prefill needs only a key rename. Note the
non-US axes deliberately drop household income and racial group and model
household composition as household_with_children (Yes/No) plus a
categorical household_size rather than a numeric child count.
Possible values: [Some College, High School Diploma, Less than high school, High School but no diploma, Bachelors, Associates, Masters, PhD]
Possible values: [Male, Female]
Possible values: [Own, Rent]
Possible values: [1, 2, 3, 4, More than 4 people]
Possible values: [Yes, No]
population_configuration objectrequired
recommended_states object[]required
Possible values: [high, medium, low]
lowestimated_population_size object
- integer
- null
Possible values: [unknown, meets_threshold, below_threshold]
unknownrank object
- integer
- null
Possible values: [Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming]
target_population object
- DemographicBoundary
- null
Possible values: [Some College, High School Diploma, Less than high school, High School but no diploma, Bachelors, Associates, Masters, PhD]
Possible values: [Male, Female]
Possible values: [0, 1, 2, 3, 4+]
Possible values: [Mixed race, White, African American, Asian or Pacific Islander, Other race, American Indian or Alaska Native]
{
"assumptions": {},
"axis_reasons": [
{
"axis": "age",
"boundary": [
0
],
"reason": "string"
}
],
"experiment_configuration_patches": [
{
"country": "United States",
"state": "Alabama",
"target_population": {},
"why_prompt": "string",
"year": "string"
}
],
"non_us_target_population": {
"age": [
0
],
"education_level": [
"Some College"
],
"gender": [
"Male"
],
"home_ownership": [
"Own"
],
"household_size": [
"1"
],
"household_with_children": [
"Yes"
]
},
"population_configuration": {},
"rationale": "string",
"recommended_states": [
{
"confidence": "low",
"estimated_population_size": 0,
"feasibility_status": "unknown",
"fit_note": "string",
"rank": 0,
"state": "Alabama"
}
],
"target_population": {
"age": [
0
],
"education_level": [
"Some College"
],
"gender": [
"Male"
],
"household_income": [
0
],
"number_of_children": [
"0"
],
"racial_group": [
"Mixed race"
]
},
"warnings": [
"string"
]
}