D18-F04-A11 · QUALITY & DISTRESS · SYNTHETIC DATA

Dechow F-Score for Misstatement Risk

Change one synthetic accounting driver, watch seven predictors, logit, probability, unconditional benchmark, and scaled score recompute, and explain the result without crossing F equals 1.0, 1.85, or 2.45.

The learning loop

1 · PredictName the direction before moving a driver.
2 · InspectFind the ratio, signal, contribution, or residual that changed.
3 · ReconcileTie the components to the raw score or model residual.
4 · BoundInterpret the screen without turning it into a finding.
Make a prediction before stepping

Base → current bridge

Scenario base
Current state
Headline delta

Keyboard: Left/Right step, Home resets, and Space plays or pauses when focus is outside a form control.

Current model output

Frozen equation

logit=-7.893+.790RSST+2.518ΔREC+1.191ΔINV+1.979SOFT+.171ΔCS-.932ΔROA+1.029ISSUE; F=logistic(logit)/.0037

Component and diagnostic ledger

Changed cards are purple. Start here before interpreting the headline.

Response across 61 states

Model output across the selected accounting scenarioA deterministic synthetic sensitivity line with the current state marked.

Interpretation gate

Boundary: F equals 1.0, 1.85, or 2.45

Visible intermediate: seven predictors, logit, probability, unconditional benchmark, and scaled score

Open exact point-in-time input and structured output

Input

Output


Synthetic teaching data only. A model score or residual is a historically specified screen—not an audit conclusion, rating, fraud finding, default forecast, or investment recommendation.