Struct Score 

pub struct Score(/* private fields */);

A score guaranteed to be in the range [0.0, 1.0] (f32 precision).

This is the f32 equivalent of Confidence, designed for neural network outputs where f32 is standard (tensors, embeddings, similarity scores).

Why f32?

Neural networks typically operate in f32:

• GPU hardware optimized for f32/f16
• Embeddings use f32 (768 floats per token)
• Logits/softmax outputs are f32

Construction

• Score::new: Returns None if out of range
• Score::saturating: Clamps to [0, 1]
• Score::from_logit: Applies sigmoid (common for NER)

Zero-Cost Abstraction

Score is #[repr(transparent)], meaning it has the exact same memory layout as f32. There is no runtime overhead.

Example

use anno::types::Score;

// From neural network output
let logit = 2.5f32;
let score = Score::from_logit(logit);
assert!(score.get() > 0.9);

// Convert to Confidence (f64) for API consistency
let conf = score.to_confidence();

Implementations

impl Score

pub const MIN: Score

The minimum valid score.

pub const MAX: Score

The maximum valid score.

pub fn new(value: f32) -> Option<Score>

Create a score, returning None if out of range.

pub fn saturating(value: f32) -> Score

Create a score, clamping to [0.0, 1.0].

pub fn from_logit(logit: f32) -> Score

Create from a raw logit by applying sigmoid.

sigmoid(x) = 1 / (1 + e^(-x))

pub fn from_logit_with_temperature(logit: f32, temperature: f32) -> Score

Create from a temperature-scaled logit.

Higher temperature (> 1) = softer distribution. Lower temperature (< 1) = sharper distribution.

pub const fn get(self) -> f32

Get the inner value (guaranteed to be in [0.0, 1.0]).

pub fn to_confidence(self) -> Confidence

Convert to f64 Confidence.

pub fn is_high(self) -> bool

Check if this is “high confidence” (>= 0.9).

pub fn passes(self, threshold: f32) -> bool

Check if this passes a threshold.

Trait Implementations

impl Clone for Score

fn clone(&self) -> Score

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Score

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl Default for Score

fn default() -> Score

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Score

fn deserialize<__D>( __deserializer: __D, ) -> Result<Score, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for Score

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl From<Score> for Confidence

fn from(score: Score) -> Confidence

Converts to this type from the input type.

impl PartialEq for Score

fn eq(&self, other: &Score) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl PartialOrd for Score

fn partial_cmp(&self, other: &Score) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

fn lt(&self, other: &Rhs) -> bool

Tests less than (for self and other) and is used by the < operator.

fn le(&self, other: &Rhs) -> bool

Tests less than or equal to (for self and other) and is used by the <= operator.

fn gt(&self, other: &Rhs) -> bool

Tests greater than (for self and other) and is used by the > operator.

fn ge(&self, other: &Rhs) -> bool

Tests greater than or equal to (for self and other) and is used by the >= operator.

impl Serialize for Score

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Copy for Score

impl StructuralPartialEq for Score