{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:DJEXO6FP5MOJQSJE3EPGODUJ4E","short_pith_number":"pith:DJEXO6FP","schema_version":"1.0","canonical_sha256":"1a497778afeb1c984924d91e670e89e139fead4a66bef20bf7c1043e58dabb54","source":{"kind":"arxiv","id":"1310.7226","version":1},"attestation_state":"computed","paper":{"title":"ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS based metabolomics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.GN"],"primary_cat":"q-bio.QM","authors_text":"Carlos A. Labate, Diego M. Salvanha, Emilien L. Jamin, Fabien Jourdan, Fabien Letisse, Ricardo R. Silva, Ricardo Z.N. V\\^encio, Simone Guidetti-Gonzalez","submitted_at":"2013-10-27T18:31:30Z","abstract_excerpt":"We present ProbMetab, an R package which promotes substantial improvement in automatic probabilistic LC-MS based metabolome annotation. The inference engine core is based on a Bayesian model implemented to: (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and; (ii) allow sensitive selection of biologically meaningful biochemical reactions databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the ann"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1310.7226","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2013-10-27T18:31:30Z","cross_cats_sorted":["q-bio.GN"],"title_canon_sha256":"7a23905cd4da5db5a50cd025da315b58649170081c2a25d21599249ee138d94b","abstract_canon_sha256":"1d795bdadacb5c7df993e0d45c67c79826a1d21e4f9562a00ed445f7e584df02"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:00:12.329526Z","signature_b64":"S5M5b8SM9R1VfS8JWY/aBelU+ciuMrbGOqjWsnum+SwigkUlbV0g2ApshDaAp8QB2h6hlN+ytfJYMrUd21OeAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1a497778afeb1c984924d91e670e89e139fead4a66bef20bf7c1043e58dabb54","last_reissued_at":"2026-05-18T03:00:12.328704Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:00:12.328704Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS based metabolomics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.GN"],"primary_cat":"q-bio.QM","authors_text":"Carlos A. Labate, Diego M. Salvanha, Emilien L. Jamin, Fabien Jourdan, Fabien Letisse, Ricardo R. Silva, Ricardo Z.N. V\\^encio, Simone Guidetti-Gonzalez","submitted_at":"2013-10-27T18:31:30Z","abstract_excerpt":"We present ProbMetab, an R package which promotes substantial improvement in automatic probabilistic LC-MS based metabolome annotation. The inference engine core is based on a Bayesian model implemented to: (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and; (ii) allow sensitive selection of biologically meaningful biochemical reactions databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the ann"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1310.7226","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1310.7226","created_at":"2026-05-18T03:00:12.328833+00:00"},{"alias_kind":"arxiv_version","alias_value":"1310.7226v1","created_at":"2026-05-18T03:00:12.328833+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1310.7226","created_at":"2026-05-18T03:00:12.328833+00:00"},{"alias_kind":"pith_short_12","alias_value":"DJEXO6FP5MOJ","created_at":"2026-05-18T12:27:43.054852+00:00"},{"alias_kind":"pith_short_16","alias_value":"DJEXO6FP5MOJQSJE","created_at":"2026-05-18T12:27:43.054852+00:00"},{"alias_kind":"pith_short_8","alias_value":"DJEXO6FP","created_at":"2026-05-18T12:27:43.054852+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DJEXO6FP5MOJQSJE3EPGODUJ4E","json":"https://pith.science/pith/DJEXO6FP5MOJQSJE3EPGODUJ4E.json","graph_json":"https://pith.science/api/pith-number/DJEXO6FP5MOJQSJE3EPGODUJ4E/graph.json","events_json":"https://pith.science/api/pith-number/DJEXO6FP5MOJQSJE3EPGODUJ4E/events.json","paper":"https://pith.science/paper/DJEXO6FP"},"agent_actions":{"view_html":"https://pith.science/pith/DJEXO6FP5MOJQSJE3EPGODUJ4E","download_json":"https://pith.science/pith/DJEXO6FP5MOJQSJE3EPGODUJ4E.json","view_paper":"https://pith.science/paper/DJEXO6FP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1310.7226&json=true","fetch_graph":"https://pith.science/api/pith-number/DJEXO6FP5MOJQSJE3EPGODUJ4E/graph.json","fetch_events":"https://pith.science/api/pith-number/DJEXO6FP5MOJQSJE3EPGODUJ4E/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DJEXO6FP5MOJQSJE3EPGODUJ4E/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DJEXO6FP5MOJQSJE3EPGODUJ4E/action/storage_attestation","attest_author":"https://pith.science/pith/DJEXO6FP5MOJQSJE3EPGODUJ4E/action/author_attestation","sign_citation":"https://pith.science/pith/DJEXO6FP5MOJQSJE3EPGODUJ4E/action/citation_signature","submit_replication":"https://pith.science/pith/DJEXO6FP5MOJQSJE3EPGODUJ4E/action/replication_record"}},"created_at":"2026-05-18T03:00:12.328833+00:00","updated_at":"2026-05-18T03:00:12.328833+00:00"}