Struct RrfFusionObjective 

pub struct RrfFusionObjective;

Scores a candidate by its pre-computed RRF fusion score.

Returns rrf_score unchanged, or 0.0 when the field is absent. Implements Objective for both RetrievalCandidate and NoteCandidate so the same objective can be used in the general retrieval pipeline and the memory recall pipeline.

Trait Implementations

impl Objective<NoteCandidate> for RrfFusionObjective

fn score(&self, candidate: &NoteCandidate, _context: &ObjectiveContext) -> f64

Evaluate a single candidate.

fn name(&self) -> &str

Get the name of this objective.

fn precision(&self, _candidate: &T, _context: &ObjectiveContext) -> f64

Precision (inverse variance) of the score estimate; default 1.0 (fully trusted).

fn passes_score(&self, score: f64, context: &ObjectiveContext) -> bool

Check if a score passes the threshold; non-finite scores never pass.

fn passes(&self, candidate: &T, context: &ObjectiveContext) -> bool

Check if a candidate passes the threshold.

fn batch_score( &self, candidates: &[T], context: &ObjectiveContext, ) -> Vec<(usize, f64)>

Score a batch of candidates and return passing (index, score) pairs.

fn select<'a>( &self, candidates: &'a [T], context: &ObjectiveContext, ) -> Vec<Selection<&'a T>>

Select all passing candidates in score-descending order.

fn select_top<'a>( &self, candidates: &'a [T], n: usize, context: &ObjectiveContext, ) -> Vec<Selection<&'a T>>

Select the top N candidates by precision-weighted score.

impl Objective<RetrievalCandidate> for RrfFusionObjective

fn score( &self, candidate: &RetrievalCandidate, _context: &ObjectiveContext, ) -> f64

Evaluate a single candidate.

fn name(&self) -> &str

Get the name of this objective.

fn precision(&self, _candidate: &T, _context: &ObjectiveContext) -> f64

Precision (inverse variance) of the score estimate; default 1.0 (fully trusted).

fn passes_score(&self, score: f64, context: &ObjectiveContext) -> bool

Check if a score passes the threshold; non-finite scores never pass.

fn passes(&self, candidate: &T, context: &ObjectiveContext) -> bool

Check if a candidate passes the threshold.

fn batch_score( &self, candidates: &[T], context: &ObjectiveContext, ) -> Vec<(usize, f64)>

Score a batch of candidates and return passing (index, score) pairs.

fn select<'a>( &self, candidates: &'a [T], context: &ObjectiveContext, ) -> Vec<Selection<&'a T>>

Select all passing candidates in score-descending order.

fn select_top<'a>( &self, candidates: &'a [T], n: usize, context: &ObjectiveContext, ) -> Vec<Selection<&'a T>>

Select the top N candidates by precision-weighted score.