---
title: "school-student-vidtvorant-rust — Mova code model"
description: "Mova code model of world/src/knowledge.rs.groupant/student-vidtvorant.groupant/rust_approximant.rs: components with their labels, obernants and the…"
url: "https://groupants.elamur.ai/free/en/mova/world/src/knowledge.rs.groupant/student-vidtvorant.groupant/rust_approximant.rs.groupant/"
---
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This page as HTML: <https://groupants.elamur.ai/free/en/mova/world/src/knowledge.rs.groupant/student-vidtvorant.groupant/rust_approximant.rs.groupant/>

# school-student-vidtvorant-rust

The groupant beside world/src/knowledge.rs.groupant/student-vidtvorant.groupant/rust_approximant.rs in the Mova repository: what the code computes, what it never does, how to go back from its outputs, its invariants, cost and checks.

## Facts

- **kind:** groupant
- **status:** executable vidtvorant no cap met
- **source:** [`world/src/knowledge.rs.groupant/student-vidtvorant.groupant/rust_approximant.rs`](https://github.com/ElamurAI/mova-free/blob/main/world/src/knowledge.rs.groupant/student-vidtvorant.groupant/rust_approximant.rs)
- **source SHA-256:** `b2aecccebe8252d5…`
- **part of:** [school-student-vidtvorant](https://md.groupants.elamur.ai/free/en/mova/world/src/knowledge.rs.groupant/student-vidtvorant.groupant/)
- **repository folder:** [`world/src/knowledge.rs.groupant/student-vidtvorant.groupant/rust_approximant.rs.groupant`](https://github.com/ElamurAI/mova-free/tree/main/world/src/knowledge.rs.groupant/student-vidtvorant.groupant/rust_approximant.rs.groupant)
- **repository commit:** `48f2e6f74146`

> **Implementation material.** A Mova code model describes this code at one source revision: partial models, finite checks and their stated scope. It is not a reviewed general exposition, and its labels are shown as written, never raised.

## Components

| component | label | where |
|---|---|---|
| **approximant** | source derived | [forward](#forward) |
| **ast** | partial | `syntax.json` |
| **cost** | measured 2026 11 04 | [cost](#cost) |
| **descriptant** | present | [epoch-memory](#epoch-memory) |
| **invariant** | source derived | [invariant](#invariant) |
| **tests** | executed bounded checks | [tests](#tests) |

## Obernants

The typed relations around the forward model: the behaviour complement (what the code never does), the reverse reconstruction (every input compatible with an output) and specialised views.

| id | type | label | where |
|---|---|---|---|
| `school-student-vidtvorant-rust-behavior-complement` | behavior_complement | partial source derived model | [behavior-complement](#behavior-complement) |
| `school-student-vidtvorant-rust-reverse-reconstruction` | reverse_reconstruction | partial source derived model | [reverse-reconstruction](#reverse-reconstruction) |

## Model text


File model of `rust_approximant.rs`, the executable code of the student's vidtvorant. The vidtvorant itself (subject,
domain, observations, error and performance profile, conformance) is described in [../model.md](https://md.groupants.elamur.ai/free/en/mova/world/src/knowledge.rs.groupant/student-vidtvorant.groupant/); this
file models the code.

### forward

`words` = `knowledge::words` (alphanumeric split, length > 1, stop and negation words out, `mentions::stem`).
`Memory::read_line` appends a line (lesson, word set, negation flag, numbers) and indexes its words.
`predict(mem, lesson, question, options, params)`: tail cut; question words; gap flag selects the gate; anchors by
shared-word counts (current lesson first, strongest only, ten); targets (anchor/next/linked); per option own lines;
features `[asked, echo, missing, neg-mismatch, route×4, current]`; score `w·f`; structured and ≥ gate to count; best
and best-current per option; lesson-first pool; argmax (score, current) with earlier index on ties; subset/extra
rule outside lesson-first; unique counted number override. `replay` reads a course lesson by lesson and calls back
per traced question. `fit`: averaged integer perceptron over the training fold, updating only on supported
disagreements. `TimeModel::fit`: least squares on ln ns with ridge 1e-6, Gauss–Jordan with partial pivoting.

### invariant

Deterministic: ordered maps and sets only, no randomness, no clock in prediction or fit. `predict` never panics on
the declared inputs (empty question words or no options return the guess). Weights change only by
`φ(student choice) − φ(predicted choice)`. The time model's coefficients are finite when the design matrix has full
rank; a zero pivot leaves the coefficient 0.

### cost

`read_line`: O(w log V). `predict`: O(P_q + Σ_options (P_o + T·w_o)) for posting-list sizes P, targets T ≤ 30 and
option words w_o. `fit`: epochs × replay. `TimeModel::fit`: O(n·7² + 7³). Measured 2026-11-04: 40–48 µs median per
prediction on one P-core thread.

### behavior-complement

The code does not parse, tag, look up WordNet, read the kind base or rules, touch the file system, the network,
the student's state or any production path; it does not certify a bound; it does not predict exercises or learning.

### reverse-reconstruction

A returned prediction is compatible with every question/option/memory triple with the same word bags, gap flag,
negation flags, numbers and line-to-lesson map; fitted weights are compatible with a cone of weight vectors.

### tests

Six unit tests, run with `cargo test --release -p mova-approx --example student_vidtvorant` (the runner includes
this file): stemming and stop words; supported option wins and an unread topic guesses first; the support gates
(and the no-gap gate only without a gap); current lesson first; fit moves only on disagreement and only inside the
training fold; time model recovers a planted law to 0.1%.

### epoch-memory

2026-11-04: first version; the module is included by path from the runner, so it compiles only with it.