Struct DecayAwareSalienceObjective 

pub struct DecayAwareSalienceObjective {
    pub decay_rate: f64,
}

Scores a NoteCandidate by salience with configurable temporal decay.

The decay formula is determined by the configured DecayModel (injected at construction time). The default DecayModel::Exponential uses the note’s own decay_factor: salience * exp(-decay_factor * age_days).

This objective participates in WeightedObjective composition alongside RrfFusionObjective and TemporalRecencyObjective to form the full recall scoring pipeline.

Fields

decay_rate: f64

Exponential decay rate k (>= 0.0). Score = salience * exp(-k * age_days). Corresponds to the per-note decay_factor parameter stored on memory notes.

Implementations

impl DecayAwareSalienceObjective

pub fn new(decay_rate: f64) -> Self

Create a new objective with the given exponential decay rate.

decay_rate = 0.01 gives a ~69-day half-life (default for memory notes).

pub fn default_memory() -> Self

Default memory decay rate: 0.01 (~69-day half-life).

Trait Implementations

impl Objective<NoteCandidate> for DecayAwareSalienceObjective

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.