@@ -121,6 +121,8 @@ export default function AssistantTextClassification({
121121 let filteredSentences = [ ] ;
122122 let filteredCategories = { } ;
123123
124+ const REPORTING_LABEL = "Reporting" ;
125+
124126 // Separate important sentences from categories, filter by threshold
125127 for ( let label in classification ) {
126128 if ( label === importantSentenceKey ) {
@@ -137,16 +139,23 @@ export default function AssistantTextClassification({
137139 }
138140 }
139141 } else {
140- // Filter categories above confidenceThreshold unless machine generated text or subjectivity
142+ // machine generated text and subjectivity
141143 if (
142144 credibilitySignal === machineGeneratedTextTitle ||
143145 credibilitySignal === subjectivityTitle
144146 ) {
145147 filteredCategories [ label ] = classification [ label ] ;
146- } else if (
147- // news framing and news genre
148- classification [ label ] [ 0 ] . score >= confidenceThresholdLow
149- ) {
148+ } else if ( credibilitySignal === keyword ( "news_genre_title" ) ) {
149+ // set default news genre value if category below threshold
150+ label === REPORTING_LABEL
151+ ? ( filteredCategories [ label ] = classification [ label ] )
152+ : classification [ label ] [ 0 ] . score >= confidenceThresholdLow
153+ ? ( filteredCategories [ label ] = classification [ label ] )
154+ : ( filteredCategories [ REPORTING_LABEL ] = [
155+ { indices : [ 0 , - 1 ] , score : confidenceThresholdLow } ,
156+ ] ) ;
157+ } else if ( classification [ label ] [ 0 ] . score >= confidenceThresholdLow ) {
158+ // filter news framing categories above threshold
150159 filteredCategories [ label ] = classification [ label ] ;
151160 }
152161 }
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