---
title: "mova-whale-pod — Mova code model"
description: "Mova code model of tools/whale/src/pod.rs: components with their labels, obernants and the model text."
url: "https://groupants.elamur.ai/free/en/mova/tools/whale/src/pod.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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# mova-whale-pod

The groupant beside tools/whale/src/pod.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/whale/src/pod.rs`](https://github.com/ElamurAI/mova-free/blob/main/tools/whale/src/pod.rs)
- **source SHA-256:** `1d1ff2f25ab699e0…`
- **repository folder:** [`tools/whale/src/pod.rs.groupant`](https://github.com/ElamurAI/mova-free/tree/main/tools/whale/src/pod.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 | [Forward approximant](#forward-approximant) |
| **ast** | partial | `syntax.json` |
| **composition** | partial | [Composition](#composition) |
| **cost** | partial | [Cost](#cost) |
| **descriptant** | present | [Descriptant](#descriptant) |
| **invariant** | partial | [Invariant](#invariant) |
| **tests** | finite evidence | `tests.md` |

## 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) |

## Model text


### Descriptant

A pod's shared knowledge: one store for all Whales of a batch pod, keyed by normalized term (`knowledge::norm_term`), with provenance per Whale, paper, item and answer. A term one Whale asked is not asked by another; what one Whale learned, every Whale explains with. Bare-category facts go to review instead of knowledge. Source: `tools/whale/src/pod.rs`.

### Forward approximant

open(dir): terms.jsonl (entries), claims.jsonl (first claim per term wins), review.jsonl, answers/. publish(whale, store): under pod.lock, every term item of the store not yet published -> non-bare facts as an entry, bare facts to review, the answer file copied; every asked term key -> a claim. claim(term, whale, paper): under pod.lock, reload; true and recorded only when no claim and no facts exist for the normalized term. items(exclude): entries of other Whales as knowledge items `pod:<whale>:<item>`, ordered by (term, whale, item). answers(): every copied answer text (for the overlap gate).

### Invariant

Appends only, fsynced, under a blocking flock; a (whale, item) pair is published at most once; a normalized term has at most one effective claim; items() depends on the file's content, not its order; answer texts never leave the pod except into the overlap gate.

### Cost

Each claim/publish rereads the three files (linear in pod size: hundreds of lines per batch); items() sorts O(n log n).

### Composition

Parent: whale-workers. Written and read by learn.rs (publish at start and after each round, claim before asking a term, items for Known::of and the gates' item lookup, answers for the Guard); configured by batch.rs (`pod`).

### behavior_complement

Not done: retracting or correcting a fact, choosing between conflicting facts of two Whales beyond «first per relation in the reader's order», sharing sentence or section readings (paper-specific), locking across machines (flock is local), deduplicating identical facts from different Whales. Parallel learners make append order timing-dependent; a Whale's view in a given round therefore depends on what the others had published by then. Evidence status: source-derived model with finite checks, not a proof.

### reverse_reconstruction

Every entry names its Whale, paper, item id and answer hash; with the Whale's own store and the copied answer the source answer is recovered. A claim names who asked first; the facts do not determine the answer text.

### Epoch 2026-11-04 (created)

Measured on a fresh pod with today's real answers replayed (10 papers, 5 Whales, sequential, two identical runs): 81 term entries, 118 claims, 26 review records; no term asked twice across the pod.

### tests.md


pod::tests::one_term_one_question_across_the_pod (2026-11-04): plural and case variants are one term; a claimed or known term is not claimed again; bare facts go to review; other Whales read the entry, the publisher does not; a second open sees the same items. Negative control: `has` ignoring claims turns the test red (restored).