Third-party measurement of entrant designs, transcribed from the pinned source; not reproduced.
1 evaluation · 1 result. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: Cradle lead optimisation of a cetuximab single-chain variable fragment | Protocol: Adaptyv EGFR competition BLI affinity Dataset: Adaptyv EGFR competition round 2 tested designs | 1.21 nM Dissociation constant (KD for EGFR by BLI of the overall competition winner, an optimised cetuximab scFv) nanomolar · lower Uncertainty: Not reported by the source: No interval is printed for this value in the prose; the repository records per-replicate fits. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCradle lead optimisation in Adaptyv round 2: Adaptyv EGFR competition BLI affinity uc-binder-20261022-protocol-adaptyv-bli-affinity Aggregation: Not reported Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025); Adaptyv EGFR design competition round 2 results repository · Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' |
Source checking is not independent reproduction. Release 2026-10-22-1b7cf027e4f6.
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Release 2026-10-22-1b7cf027e4f6 · Evidence verified: Not verified
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Adaptyv EGFR competition BLI affinity
Metadata review: source checked. Unreported conditions prevent automatic comparisons.
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18 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Comparison: adaptation Not reported Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | missing or unspecified No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
| Comparison: aggregation Over the designs tested in the stated round Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
| Comparison: budget Not reported Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | missing or unspecified No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
| Comparison: dataset version Adaptyv EGFR Binder Design Competition round 2, results revealed December 2024 Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
| Comparison: inputs EGFR structure; entrants chose their own inputs and workflow Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
| Comparison: metric implementation KD for EGFR by BLI of the overall competition winner, an optimised cetuximab scFv Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
| Comparison: population Not reported Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | missing or unspecified No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
| Comparison: protocol id uc-binder-20261022-protocol-adaptyv-bli-affinity Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
| Comparison: split Not reported Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | missing or unspecified No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
| Origin independent_paper Context-only references | Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition (Cotet et al., bioRxiv 2025) Section 3.2: 'The overall winner of the competition (by binding affinity), and the winner of R2, was the ML-guided lead optimization strategy of Cradle, with a binding affinity of 1.21 nM' Version: bioRxiv preprint version 1 | not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of a mutable web page. The hash describes that retrieval, not a stable artifact. |
Release 2026-10-22-1b7cf027e4f6 · Record review: source checked
Stable ID: uc-binder-20261022-eval-adaptyv-cradle-r2-affinity