`nexyron.model_materialized_drop`

Generic Description

nexyron.model_materialized_drop drop one cached materialized model artifact

CALL nexyron.procedures()
YIELD name, description, parameters, output_columns
WHERE name = 'nexyron.model_materialized_drop'
RETURN name, description, parameters, output_columns

Semantic model procedures score, evaluate, compare, explain, materialize, and inspect registered models that are bound to named datasets or snapshots.

Consumer-Level Explanation

This procedure is part of the abstraction artifact and refresh runtime. It manages built outputs, freshness, dependency visibility, or queued rebuild work rather than changing the underlying abstraction contract itself.

Parameters

name: Model name Required.

Output Columns

name
scenario
dropped

Example Contract Prerequisite

The executable Cypher blocks on this page query nexyron.procedures() so they work in an empty database and stay synchronized with the live procedure registry. A direct CALL nexyron.model_materialized_drop(...) requires the named abstraction contracts, artifacts, features, snapshots, datasets, models, or policies referenced by that call to exist first; otherwise the runtime correctly fails with an unknown-contract error rather than inventing state.

Conceptual Explanation

The important thing about nexyron.model_materialized_drop is that it stays inside the same Cypher and abstraction-contract runtime as the rest of Nexyron. That means it can compose with named abstractions, time-aware snapshot contracts, document-style payloads, graph-native identity, and later model or policy layers without forcing you to move into a separate tool first.

More Detailed Explanation

In practical queries, start by deciding the row grain you want after the call: one row per node, one row per path, one row per registry object, one row per artifact, or one row per summary. Then keep that grain explicit with YIELD and named projections. That is the difference between a useful planner-facing example and a vague call that downstream tooling cannot safely compose. For contract-driven abstraction procedures, the executable examples on these pages intentionally inspect procedure metadata unless the required named artifacts are created in the same example.

Advanced Example

CALL nexyron.procedures()
YIELD name, parameters, output_columns
WHERE name = 'nexyron.model_materialized_drop'
RETURN name,
       [p IN parameters | p.name] AS parameter_names,
       output_columns
ORDER BY name

Real Use Cases

Evaluate, compare, and operationalize retention-risk models directly against named abstraction datasets before moving a candidate model into campaign or service decisioning.
Score live member cohorts from the same feature contract used offline so risk review, calibration review, and production serving stay on one contract path.

Real Limitations And Tradeoffs

This surface is contract-driven. If the registered feature, snapshot, dataset, model, or policy definition is weak, the procedure will faithfully execute that weak contract rather than silently repairing it.
Materialized artifacts improve reuse, but they add freshness and invalidation concerns that on-demand execution avoids.
Reported quality or causal metrics are only as defensible as the dataset, split, and temporal contract supplied underneath.