Association Prediction by Rules Still Returns Itemsets

If I use this code with an association model, it still returns itemsets for me - when it should be returning only nodes with rules associated with them (according to sqlserverdatamining.com). If I try adding 'AND $PROBABILITY > .25' to the where clause, it returns 0 results for every query I try. Any clue why this may be happening?

Code Snippet

SELECT FLATTENED
(SELECT * FROM PredictAssociation([Product],20,
INCLUDE_NODE_ID,INCLUDE_STATISTICS)
WHERE $NODEID<>'')
FROM
[ProductRecommend]
PREDICTION JOIN
OPENQUERY([ds],
'SELECT
[PRODUCTCLASSID],[DESCRIPTION]
FROM
[Product_Table]
WHERE
[PRODUCTCLASSID] = ''1234'' AND [DESCRIPTION] = ''DESC''
') AS t

ON
[ProductRecommend].[Product].[PRODUCTCLASSID] = t.[PRODUCTCLASSID] AND
[ProductRecommend].[Product].[DESCRIPTION] = t.[DESCRIPTION]

This query returns more relevant results than those lacking the filtering by $NODEID, however the results should have higher probabilities than .047! Please help! Thanks!

Okay, I just reconstructed the same query using my data in a relational mining model (instead of OLAP) and got reasonable results. Would anyone know how to fix this for OLAP or be able to point me in a direction where I could go to learn how to do it? Thanks.

|||What is the MINIMUM_PROBABILITY value for the OLAP mining model?
Is it different than the one from the relational model?

One more thing (which you probably know already) -- the query you posted initially executes one prediction (PredictAssociation ... 20) for each row in the data source query (does not group together multiple input rows belonging to the same transaction).
Basically, only rules having a single item on the left hand side will be used in prediction.