BLASSO rhodopsin predictor: description
Description of BLASSO rhodopsin predictor
Bayesian LASSO regression that predicts a rhodopsin's absorption wavelength from predefined physicochemical features of the amino acids in its sequence, without using its three-dimensional structure.
Replace a placeholder description with a sourced functional description (issue #88). Historical releases retain the original value.
Evidence
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
Evidence table
Inspect claims, sources and review details
Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.
One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
7 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Claimed field description Context-only references | RhoMax 2024 primary article uc20260930-source-rhomax-2024: Introduction (the approach of Inoue et al. 'utilizes the Bayesian LASSO ... based on predefined physicochemical features of amino acids. This approach does not take into account the geometric three-dimensional (3D) structure'); Comparison to Previous Methods Version: 2024 journal article; XML pinned by SHA-256 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Previous value Named prediction method identified in the cited primary source. Exact fitted configurations and scores are separate records. Context-only references | RhoMax 2024 primary article uc20260930-source-rhomax-2024: Introduction (the approach of Inoue et al. 'utilizes the Bayesian LASSO ... based on predefined physicochemical features of amino acids. This approach does not take into account the geometric three-dimensional (3D) structure'); Comparison to Previous Methods Version: 2024 journal article; XML pinned by SHA-256 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Source location uc20260930-source-rhomax-2024: Introduction (the approach of Inoue et al. 'utilizes the Bayesian LASSO ... based on predefined physicochemical features of amino acids. This approach does not take into account the geometric three-dimensional (3D) structure'); Comparison to Previous Methods Context-only references | RhoMax 2024 primary article uc20260930-source-rhomax-2024: Introduction (the approach of Inoue et al. 'utilizes the Bayesian LASSO ... based on predefined physicochemical features of amino acids. This approach does not take into account the geometric three-dimensional (3D) structure'); Comparison to Previous Methods Version: 2024 journal article; XML pinned by SHA-256 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Claimed value Bayesian LASSO regression that predicts a rhodopsin's absorption wavelength from predefined physicochemical features of the amino acids in its sequence, without using its three-dimensional structure. Context-only references | RhoMax 2024 primary article uc20260930-source-rhomax-2024: Introduction (the approach of Inoue et al. 'utilizes the Bayesian LASSO ... based on predefined physicochemical features of amino acids. This approach does not take into account the geometric three-dimensional (3D) structure'); Comparison to Previous Methods Version: 2024 journal article; XML pinned by SHA-256 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Description Replace a placeholder description with a sourced functional description (issue #88). Historical releases retain the original value. Context-only references | RhoMax 2024 primary article uc20260930-source-rhomax-2024: Introduction (the approach of Inoue et al. 'utilizes the Bayesian LASSO ... based on predefined physicochemical features of amino acids. This approach does not take into account the geometric three-dimensional (3D) structure'); Comparison to Previous Methods Version: 2024 journal article; XML pinned by SHA-256 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Relationship: subject uc20260930-method-blasso-rhodopsin-predictor Context-only references | RhoMax 2024 primary article uc20260930-source-rhomax-2024: Introduction (the approach of Inoue et al. 'utilizes the Bayesian LASSO ... based on predefined physicochemical features of amino acids. This approach does not take into account the geometric three-dimensional (3D) structure'); Comparison to Previous Methods Version: 2024 journal article; XML pinned by SHA-256 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Name BLASSO rhodopsin predictor: description Context-only references | RhoMax 2024 primary article uc20260930-source-rhomax-2024: Introduction (the approach of Inoue et al. 'utilizes the Bayesian LASSO ... based on predefined physicochemical features of amino acids. This approach does not take into account the geometric three-dimensional (3D) structure'); Comparison to Previous Methods Version: 2024 journal article; XML pinned by SHA-256 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-11-02-a7f03c9e55a5 · Record review: source checked
1 source record and release history
- RhoMax 2024 primary article · Original source · 2024 journal article; XML pinned by SHA-256
Technical metadata and extraction receipts
Stable ID: metadata-correction-cb3769975b7f722c1f9f
- areas
- proteins-complexes
- field
- description
- previous value
- Named prediction method identified in the cited primary source. Exact fitted configurations and scores are separate records.
- value
- Bayesian LASSO regression that predicts a rhodopsin's absorption wavelength from predefined physicochemical features of the amino acids in its sequence, without using its three-dimensional structure.
- source locator
- uc20260930-source-rhomax-2024: Introduction (the approach of Inoue et al. 'utilizes the Bayesian LASSO ... based on predefined physicochemical features of amino acids. This approach does not take into account the geometric three-dimensional (3D) structure'); Comparison to Previous Methods
- review
- method: automated-source-review; ai-assisted-source-review; reviewer: claude; reviewer note: Extractor: Claude integrator agent for issue #88. Reviewer: a separate Claude review agent, independent of the extractor; no human review claimed.; date: 2026-10-11; method note: Compared the store diff with origin/main, read each new description against its cited source passage and checked the licence of each new source record.; note: Approved. Checked the 10 method and model descriptions against their sources (EVmutation, GEMME and RSALOR abstracts, the FramePool k-mer random forests, the RhoMax BLASSO text) and spot-checked the 49 mRNABench rows against Appendix A; all accurate. Licences on the 3 new sources match their Europe PMC records. At the reviewer's suggestion, the en dash printed in some checkpoint names is written as a hyphen in the descriptions.; receipt: data/omics/qa-descriptions-20261011-a/review.json
Related records
- subject: BLASSO rhodopsin predictor