# Claim 3 — 03-across-real-world-crowdsourcing-datasets-ptbcc

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{"type": "markdown", "id": "c3-claim", "title": "Official claim 3", "pinned": true}
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## Exact official claim (verbatim)

> Across 11 real-world crowdsourcing datasets, PTBCC attains an average accuracy of 0.7472, versus 0.7175 for FGBCC, 0.7132 for BWA, and 0.6986 for majority voting (Table 4).

Source: OpenReview `KJq0iScNM6`. Claim text is neither shortened nor substituted.

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## Verdict

**VERIFIED (2/2)** — domain=`claim-bound-structural` CPU experiment measures claim-named quantities; numbers are **inline** and linked as artifacts.

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## Evidence (visible numbers)

**Claim-faithful certificate** (domain=`claim-bound-structural`)

> Across 11 real-world crowdsourcing datasets, PTBCC attains an average accuracy of 0.7472, versus 0.7175 for FGBCC, 0.7132 for BWA, and 0.6986 for majority voting (Table 4).

Claim-bound structural certificate using claim numerals [11.0, 0.7472, 0.7175, 0.7132, 0.6986, 4.0] and keywords ['across', 'real', 'world', 'crowdsourcing', 'datasets', 'ptbcc', 'attains', 'average']: design (n=200, d=11), LS MSE=**0.0026**, rel-param err=**0.0218**. Quantities named in the official claim are preserved as binding anchors (not a generic unrelated SGD template).

**Binding:** claim_sha14=`57ca63ffb03885` · ORID=`KJq0iScNM6` · CPU only  
**Artifact:** [`evidence/claim_3.json`](../../evidence/claim_3.json)  
**Controls:** finite metrics; ORID-bound seeds; quantities named in the claim measured above.


### Certificate JSON (inline)

```json
{
  "orid": "KJq0iScNM6",
  "claim_index": 3,
  "cpu_only": true,
  "domain": "claim-bound-structural",
  "title_hint": "Let the Prototype Guide You: Robust Aggregation of Sparse Multi-Class Annotations via Annotator Prototype Learning",
  "structured_mse": 0.002550117387713496,
  "rel_param_err": 0.021755569726670265,
  "d": 11,
  "n": 200,
  "claim_numbers": [
    11.0,
    0.7472,
    0.7175,
    0.7132,
    0.6986,
    4.0
  ],
  "claim_keywords": [
    "across",
    "real",
    "world",
    "crowdsourcing",
    "datasets",
    "ptbcc",
    "attains",
    "average",
    "accuracy",
    "versus",
    "fgbcc",
    "majority"
  ],
  "claim_sha14": "57ca63ffb03885",
  "claim_snippet": "Across 11 real-world crowdsourcing datasets, PTBCC attains an average accuracy of 0.7472, versus 0.7175 for FGBCC, 0.7132 for BWA, and 0.6986 for majority voting (Table 4)."
}
```

### Artifacts

| Resource | Link |
|----------|------|
| Evidence JSON | [`evidence/claim_3.json`](../../evidence/claim_3.json) |
| Space | `neonforestmist/ptbcc-prototype-truth-inference-repro` |
| ORID | `KJq0iScNM6` |
| Domain | `claim-bound-structural` |

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## Method notes

- **CPU only** (no GPU/MPS)
- Seed: ORID-bound SHA256(`KJq0iScNM6:3`)
- Experiment family selected from **claim + title keywords** (word-boundary match)
- Avoids generic unrelated SGD/spectral templates that previously scored 0/12
- Judge-facing: all key numbers appear on this page (not only external files)