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').
The provider every read and the entity creation go through (no fallback to the global provider).
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.