---
title: "translation-meta-ibm — Mova code model"
description: "Mova code model of tools/translate/src/ibm.rs: components with their labels, obernants and the model text."
url: "https://groupants.elamur.ai/free/en/mova/tools/translate/src/ibm.rs.groupant/"
---
Elamur: [Mova](https://md.mova.elamur.ai/free/en/) · [Dictionary](https://md.dictionary.elamur.ai/free/en/) · [Research](https://md.research.elamur.ai/free/en/) · **Groupants**

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# translation-meta-ibm

The groupant beside tools/translate/src/ibm.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:** partial source bound model
- **source:** [`tools/translate/src/ibm.rs`](https://github.com/ElamurAI/mova-free/blob/main/tools/translate/src/ibm.rs)
- **source SHA-256:** `57fbc820f996dbfa…`
- **repository folder:** [`tools/translate/src/ibm.rs.groupant`](https://github.com/ElamurAI/mova-free/tree/main/tools/translate/src/ibm.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** | partial | [approximant](#approximant) |
| **ast** | partial | `syntax.json` |
| **composition** | partial | [composition](#composition) |
| **cost** | symbolic source derived | [invariant](#invariant) |
| **descriptant** | present | [descriptant](#descriptant) |
| **invariant** | partial | [invariant](#invariant) |
| **tests** | bounded native receipts | [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 |
|---|---|---|---|
| `behavior_complement` | behavior_complement | partial source derived model | [behavior_complement](#behavior-complement) |
| `reverse_reconstruction` | reverse_reconstruction | partial source derived model | [reverse_reconstruction](#reverse-reconstruction) |
| `row_mass` | row_mass | partial source derived model | [row_mass](#row-mass) |
| `null_competition` | null_competition | partial source derived model | [null_competition](#null-competition) |
| `duplicate_prior` | duplicate_prior | partial source derived model | [duplicate_prior](#duplicate-prior) |
| `vocab_order` | vocab_order | partial source derived model | [vocab_order](#vocab-order) |

## Parts

- [translation-meta-ibm-align](https://md.groupants.elamur.ai/free/en/mova/tools/translate/src/ibm.rs.groupant/align.groupant/)

## Model text


### descriptant

#### Description and epoch memory

Vocab assigns sorted unique IDs1.., missing0. train_prior builds sorted cooccurrence/prior rows, initializes uniform, repeats fractional counts against NULL then adds prior pseudocounts and normalizes positive rows. align maximizes t*exp(-2*relative-distance) over NULL*.3.

##### Prospective epoch 2026-10-31

Models predicted metadata loss, bounded coordinate transport and deterministic tie selection before test changes. Production bytes are preserved; only five inline synthetic tests were appended across the group.

##### Observation epoch 2026-10-31

Selected named native tests are bound in tests.md; raw receipts are external under $MOVA_DATA/runs/octopus-wave32-tr_meta-2026-10-31. Syntax is generated twice and byte-compared. This is partial syntax without macro expansion or semantic resolution.

##### Gaps

No real annotator/model loads, corpus translation, teacher calls, GPU, full training/evaluation, or language-accuracy claim. No executable percentage surrogate is supplied: an appropriate reference metric/domain is not established. Supported future caps are1/2/5/10 percent only. Residual reconstruction is conditional on retained diagnostics and is not persistent learning.

##### Independent review clarification — 2026-10-31

Row-mass normalization is an ideal real-arithmetic relation; the implementation uses f64 and may round away from exact mass1. The synthetic normalization assertion uses1e-12 for its fixed fixture only. No universal machine-arithmetic error bound follows. This documentation correction follows the external wave32 rt_core cross-review; source and native receipts are unchanged.

### approximant

#### Forward relation

Vocab assigns sorted unique IDs1.., missing0. train_prior builds sorted cooccurrence/prior rows, initializes uniform, repeats fractional counts against NULL then adds prior pseudocounts and normalizes positive rows. align maximizes t*exp(-2*relative-distance) over NULL*.3.

### invariant

#### Invariant and cost

##### Domain and preservation

Source IDs<=nf, nf+1 and vocab ids representable; alpha finite nonnegative, sums finite; no claim for NaN/negative priors. Prior duplicates intentionally counted.

##### Cost

Initial storage Q=sum (|f|+1)|e|+prior entries before dedup; sort each column. Iterations O(I*(sum |e|(|f|+1) log Rmax+R+P log Rmax)) time and O(Q+R+nf) memory; align O(|e||f|log Rmax).

Counters and allocation arithmetic must remain representable. String/map costs include compared bytes; finite evidence is not a throughput estimate.

### composition

#### Local composition

The child isolates the translation-meta-ibm-align relation inside this source. Its observation is a projection of the complete file relation described in approximant.md; costs overlap and must not be added twice. The remaining code supplies context/table inputs and consumes outputs. External joins: meta MTok feeds profile, Hebrew encoder, fwt and rules; meta LCS feeds logic and alignment-based training; Strong labels optionally override IBM ownership. No runtime chain between all children is asserted.

### models

## Typed models

Subject: exact source hash in manifest; observation is one call or the stated finite training pass. All models are partial source-derived relations, not universal proof. Domain and resource assumptions are in invariant.md. The baseline exclusion is an inner source-derived claim on that domain; reverse is a compatible-antecedent relation. Specialized relations hold fixed the parameters and tables unless stated otherwise. Evidence uses the named checks in tests.md; individual assertions cover only finite parts, other branches remain prospective.

### behavior_complement

Unlisted row/column lookup returns0; zero score cannot beat NULL tie. Training does not load a linguistic model or corpus itself.

### reverse_reconstruction

Rows admit many repeated/reordered training pairs and priors yielding same normalized counts. Alignment output identifies inequality cells in row probabilities, not unique lexical meaning.

### row_mass

In ideal real arithmetic, nonempty initialized rows and positive-total normalized rows have mass1; zero-total rows retain their previous values. Actual f64 divisions and summation introduce rounding, so exact machine mass1 is not guaranteed. The synthetic1e-12 assertion is finite evidence for its fixture, not a universal error bound.

### null_competition

Best starts(t(0,e)*.3,None); strict greater keeps NULL ties.

### duplicate_prior

Each duplicate e in prior adds alpha again despite row deduplication.

### vocab_order

Sorted lexical ID map independent of occurrence order;0 aliases unknown and NULL.

### tests

#### Checks and evidence

- ibm::tests::learns_a_toy_dictionary
- ibm::wave32::zero_prior_and_normalization

Exact cargo commands use package translate, binary translate, --offline --locked and -- --exact --test-threads=1. External native-commands.json lists every name; debug and release run twice, numerical status and named outcomes retained. Some tests target other portions of the file; this fragment has source reasoning plus only the overlapping assertions.

Compiled controls mutate production decision expressions and restore exact original bytes; see external mutations.json and restoration receipt. No assertion-only mutation is counted. The evidence summary is authoritative for completed receipts. Scoped source reasoning and finite tests do not establish total branch coverage.

##### Recorded 2026-10-31 result

This source contributes 2 exact named checks to the 18-check group. Every name passes twice in debug and twice in release, with identical sorted outcomes. A compiled production mutation in ibm.rs was rejected by its selected runtime assertion; its original and restored SHA-256 match. All 18 checks pass again after all nine restorations. There were nine rejected production mutations, zero assertion-only mutations and zero surviving controls in this batch. Nine source projections matched byte-for-byte across two generations. No original production bytes changed.

The augmented-registry check has no owned source or fragment diagnostic. Only root-owned inference-core/mova child/source bindings await integration. A first isolated-registry experiment was unsuitable because the checker inspects unrelated existing sidecars; those failures are retained separately and are not counted as semantic controls.