// ms = microservice 
var msList = ThingTemplates["PredictionMicroserver"].GetIncomingDependencies(); 
var ms = new Object(); 
logger.warn(msList[0].name); 
var listLength = msList.length; 
  
// Determine the prediction microservice 
for (var x=0; x < listLength; x++) { 
    if (msList[x].type=="Thing") { 
    ms = msList[x]; 
        } 
}

var datasetRef = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape({
	infoTableName : "InfoTable",
	dataShapeName : "concreteDS"
});

datasetRef.AddRow({
Cement: inputFromMash.Cement,
Slag: inputFromMash.Slag,
FlyAsh: inputFromMash.FlyAsh,
Water: inputFromMash.Water,
Superplasticizer: inputFromMash.Superplasticizer,
CoarseAggregate: inputFromMash.CoarseAggregate,
FineAggregate: inputFromMash.FineAggregate,
Age: inputFromMash.Age
})

var dataset = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape({
	infoTableName : "InfoTable",
	dataShapeName : "AnalyticsDatasetRef"
});

var newEntry = new Object();
	newEntry.data = datasetRef; 

dataset.AddRow(newEntry);

var Model_Guid = me.modelID;
// result: INFOTABLE dataShape: AnalyticsPredictionScores
var predictiveScores = Things[ms.name].RealtimeScore({
	modelUri: "results:/models/" + Model_Guid,
    datasetRef: dataset
});

var result = predictiveScores.rows[0].modelOutputs.rows[0].fieldValue;