Uncanny Valley Mori Curve Position Estimator
Interpolate actual independently matched Mori-style likeness/affinity observations, not a fabricated universal uncanny-valley curve or its causal location. Independently matched empirical calibration, piecewise linear, no extrapolation; not a universal physiological, psychological, causal or aesthetic threshold.
Description
A likeness-affinity relationship must come from a particular set of observations rather than an assumed universal curve.
A likeness-affinity relationship must come from a particular set of observations rather than an assumed universal curve.1
This tool interpolates caller-matched responses and returns the local slope within that calibration.
When to use Uncanny Valley Mori Curve Position Estimator
Use this tool to interpolate caller-matched responses and returns the local slope within that calibration.
How to use Uncanny Valley Mori Curve Position Estimator and how it works
- Establish the observations, units, reference context and assumptions described below.
- Enter callerMatchedCoordinates, callerMatchedResponses, queryCoordinate and run the tool.
- Read result.interpolatedMatchedResponse, result.localMatchedSlope using the meanings and sign conventions below.
- Correct any rejected inputs and rerun; independently review the result under the stated scope.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| callerMatchedCoordinates | At least two finite strictly increasing coordinates for the matched empirical calibration. | array of number | Required; branch conditions below |
| callerMatchedResponses | Finite response observations in coordinate order; units belong to the declared calibration. | array of number | Required; branch conditions below |
| queryCoordinate | Finite query within the supplied coordinate range, endpoints included. | number | Required; finite; branch conditions below |
Supply aligned finite coordinate and response arrays, at least two strictly increasing coordinates, and a finite query within both endpoints. Linearly interpolate the response and return the segment slope. At an interior knot the slope uses the segment to its right; the last endpoint uses the final segment. Responses need not be monotone, and no universal uncanny-valley curve or extremum is inferred.
response=y_i+(y_(i+1)-y_i)*(query-x_i)/(x_(i+1)-x_i); slope=(y_(i+1)-y_i)/(x_(i+1)-x_i) Use the stated ordering, units and branch conditions.
| Output field | Meaning | Value type |
|---|---|---|
| result | Object containing the fields below. | object |
| result.interpolatedMatchedResponse | Piecewise-linear response in the supplied response unit. | number |
| result.localMatchedSlope | Slope of the selected segment in response units per coordinate unit. | number |
{
"input": {
"callerMatchedCoordinates": [
1,
2,
3
],
"callerMatchedResponses": [
2,
4,
8
],
"queryCoordinate": 2.5
},
"output": {
"result": {
"interpolatedMatchedResponse": 6,
"localMatchedSlope": 4
}
}
}Limitations and assumptions
The calculation depends on independently established observations, coefficients and the matching units. It does not collect data, choose a treatment or target, establish model applicability or provide a validated forecast. Interpret its result within the branch conditions and assumptions above.
Supply explicit values and dense aligned arrays. Unexpected fields, wrong types and nonfinite scalar values are rejected; fixed-token, alignment and other branch conditions are explained above. A successful false flag, empty match list or unknown-evidence list differs from an input error. Extremely large inputs or nonrepresentable results may fail.
Alternative or Complementary methods
Use Processing Fluency Disfluency Depth Tradeoff Lookup for a related operation: Processing ease and difficulty can have different effects under different tasks and stimulus conditions.
Use Mere Exposure Effect Zajonc Familiarity Preference Lookup for a related operation: Mere-exposure findings concern repeated encounters under specified experimental conditions.
References
Similar or alternative tools
- Processing Fluency Disfluency Depth Tradeoff Lookup
Processing ease and difficulty can have different effects under different tasks and stimulus conditions.
- Mere Exposure Effect Zajonc Familiarity Preference Lookup
Mere-exposure findings concern repeated encounters under specified experimental conditions.