OptionalcadenceRecurrence; defaults to 'Monthly' (the 1st of every month at 00:00).
OptionalcontextServer-side context user (required for data isolation + audit on the saved row).
The MJ: ML Models id to score with.
OptionalnameOptional Record Process name; a descriptive default is generated when omitted.
OptionaloutputOptional. The target-entity column to write the prediction into (e.g.
'RenewalScore'). Omit for generic output — each run's predictions are
recorded in the process run history (MJ: Process Run Details) only; no
write-back column and no scoring binding are created.
OptionalprimaryPrimary-key field on the target entity (defaults to 'ID').
OptionalproviderMetadata provider to create the entity object against (defaults to the global).
The records each run scores. Populate EXACTLY ONE of: filter, viewId, listId, all.
The entity whose rows are scored (e.g. 'Memberships').
OptionaltimezoneTimezone the cron is evaluated in (defaults to 'UTC').
OptionalvalueWhich prediction value to write — numeric 'score' (default) or 'class' label.
Inputs for createScheduledModelScoring. The required trio —
modelId,targetEntityName, and exactly onescopeselector — is the minimum to bind a model to a recurring scoring run; everything else has a sensible default (monthly cadence,IDprimary key, numeric score, UTC, generated name).Two output modes, driven by whether
outputFieldis supplied:outputFieldpresent): each run writes the prediction into that target column AND aMJ: ML Model Scoring Bindingslineage row is created.outputFieldomitted): each run records its predictions in the process run history (MJ: Process Run Details) only — no write-back column and no scoring binding.