diff --git a/crates/core/src/lib.rs b/crates/core/src/lib.rs
index 1ef9e6a..087d76a 100644
--- a/crates/core/src/lib.rs
+++ b/crates/core/src/lib.rs
@@ -3,5 +3,5 @@ pub mod models;
 pub mod scoring;
 
 pub use affinity::TopicAffinities;
-pub use models::{Article, Feed, ReadingEvent, ReadingOutcome};
-pub use scoring::{score_article, RelevanceInputs};
+pub use models::{Article, Feed, ReadingEvent, ReadingOutcome, RelevanceInputs};
+pub use scoring::score_article;
diff --git a/crates/core/src/models.rs b/crates/core/src/models.rs
index e79bf68..716128b 100644
--- a/crates/core/src/models.rs
+++ b/crates/core/src/models.rs
@@ -1,3 +1,4 @@
+use crate::affinity::TopicAffinities;
 use chrono::{DateTime, Utc};
 use serde::{Deserialize, Serialize};
 use uuid::Uuid;
@@ -58,3 +59,16 @@ pub enum ReadingOutcome {
     /// Explicitly marked not relevant, independent of whether it was opened.
     Dismissed,
 }
+
+/// Inputs to the final blended relevance score for one article, see
+/// `scoring::score_article`.
+pub struct RelevanceInputs<'a> {
+    /// Cosine similarity (0.0-1.0, already renormalized from [-1,1] if
+    /// needed) between article and preference-profile embeddings.
+    pub embedding_score: f32,
+    /// LLM judgment (0.0-1.0), `None` if the article didn't clear the
+    /// embedding shortlist threshold and so was never sent to the LLM.
+    pub llm_score: Option<f32>,
+    pub topics: &'a [String],
+    pub affinities: &'a TopicAffinities,
+}
diff --git a/crates/core/src/scoring.rs b/crates/core/src/scoring.rs
index fe64420..8d4a3f9 100644
--- a/crates/core/src/scoring.rs
+++ b/crates/core/src/scoring.rs
@@ -1,16 +1,4 @@
-use crate::affinity::TopicAffinities;
-
-/// Inputs to the final blended relevance score for one article.
-pub struct RelevanceInputs<'a> {
-    /// Cosine similarity (0.0-1.0, already renormalized from [-1,1] if
-    /// needed) between article and preference-profile embeddings.
-    pub embedding_score: f32,
-    /// LLM judgment (0.0-1.0), `None` if the article didn't clear the
-    /// embedding shortlist threshold and so was never sent to the LLM.
-    pub llm_score: Option<f32>,
-    pub topics: &'a [String],
-    pub affinities: &'a TopicAffinities,
-}
+use crate::models::RelevanceInputs;
 
 /// Weights are deliberately conservative: the LLM judgment dominates when
 /// present (it has read the actual content), the embedding score is a
diff --git a/crates/db/src/articles.rs b/crates/db/src/articles.rs
index 2b4f4ea..aa2fa45 100644
--- a/crates/db/src/articles.rs
+++ b/crates/db/src/articles.rs
@@ -6,11 +6,11 @@ use chrono::Utc;
 use diesel::prelude::*;
 use diesel_async::RunQueryDsl;
 use feedsignal_core::Article;
+use schema::articles::dsl;
 use uuid::Uuid;
 
 impl Db {
     pub async fn insert_article(&self, article: &Article) -> Result<()> {
-        use schema::articles::dsl;
         let mut conn = self.pool.get().await?;
         let topics = serde_json::to_string(&article.topics)?;
         diesel::insert_into(dsl::articles)
@@ -36,7 +36,6 @@ impl Db {
     /// Articles above the embedding-similarity threshold that haven't been
     /// through the (slower) LLM scoring stage yet.
     pub async fn shortlist_for_llm_scoring(&self, threshold: f32, limit: i64) -> Result<Vec<Uuid>> {
-        use schema::articles::dsl;
         let mut conn = self.pool.get().await?;
         let ids: Vec<String> = dsl::articles
             .filter(dsl::embedding_score.ge(threshold))
@@ -55,7 +54,6 @@ impl Db {
         &self,
         article_id: Uuid,
     ) -> Result<Option<(String, String, Vec<String>, f32)>> {
-        use schema::articles::dsl;
         let mut conn = self.pool.get().await?;
         let row: Option<(String, String, String, Option<f32>)> = dsl::articles
             .filter(dsl::id.eq(article_id.to_string()))
@@ -63,13 +61,16 @@ impl Db {
             .first(&mut conn)
             .await
             .optional()?;
-        Ok(match row {
+
+        let result = match row {
             Some((title, summary, topics_json, score)) => {
                 let topics: Vec<String> = serde_json::from_str(&topics_json).unwrap_or_default();
                 Some((title, summary, topics, score.unwrap_or(0.0)))
             }
             None => None,
-        })
+        };
+
+        Ok(result)
     }
 
     pub async fn store_llm_result(
@@ -100,7 +101,6 @@ impl Db {
         feed_id: Option<Uuid>,
         limit: i64,
     ) -> Result<Vec<RankedArticleRow>> {
-        use schema::articles::dsl;
         let mut conn = self.pool.get().await?;
         // SQLite sorts NULL before any value, so `DESC` already puts NULL
         // `final_score`s last — no separate NULLS LAST clause needed here.
diff --git a/crates/web/src/api/mod.rs b/crates/web/src/api/mod.rs
index 62211e5..63ca899 100644
--- a/crates/web/src/api/mod.rs
+++ b/crates/web/src/api/mod.rs
@@ -1,5 +1,5 @@
 pub mod articles;
-mod dto;
 pub mod feeds;
+mod models;
 
-pub use dto::{ArticleView, FeedView};
+pub use models::{ArticleView, FeedView};