{"as_of":"2026-08-16T16:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d373a64756144d9655c05a3efae6e1daeae5566a41fcc032b6f046dc9a291b0f","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":14,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:03:09.160586Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T19:28:52.438084Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-08-09T13:47:39.994084Z","title":"Scalable diffusion for materials generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02016","last_updated":"2025-02-04T05:07:13Z","snapshot_observed_at":"2026-08-15T05:51:57.049991Z","submitted_at":"2025-02-04T05:07:13Z","title":"A Periodic Bayesian Flow for Material Generation","version":1},"reference_index":118,"source":"arxiv_source","source_observed_at":"2026-08-09T13:47:39.994084Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2502.02016"},"observation_digest":"sha256:4ea62ffda6a733a884ff7a37e53c1b5079529447b22e110a65f31a4c0a4ae2db","observation_id":"3c4aa084-6db7-46a3-a814-f6962092e253","resolution":{"observed_at":"2026-08-09T13:47:39.994084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-08-09T04:20:16.744232Z","title":"Scalable diffusion for materials generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.03638","last_updated":"2025-05-23T20:39:27Z","snapshot_observed_at":"2026-08-15T22:58:27.742566Z","submitted_at":"2025-02-05T21:48:48Z","title":"SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models","version":3},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-09T04:20:16.744232Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2502.03638"},"observation_digest":"sha256:5c25cae768425a148c50d0032c8fa898856670ccd0695ba56b5f847581af982a","observation_id":"b866040d-edc1-4d4e-aeda-de2882e1a32f","resolution":{"observed_at":"2026-08-09T04:20:16.744232Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-08-08T17:14:51.156162Z","title":"arXiv preprint arXiv:2311.09235 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.05970","last_updated":"2025-02-09T17:37:36Z","snapshot_observed_at":"2026-08-10T23:27:53.875460Z","submitted_at":"2025-02-09T17:37:36Z","title":"Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T17:14:51.156162Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2502.05970"},"observation_digest":"sha256:1a8c7f9c3acc90defedc9614b9de39b2ba9043c3e27c1d9c2bc303958bc856b2","observation_id":"86aa63b3-ed14-4f6d-9e71-ca97a21bdfbd","resolution":{"observed_at":"2026-08-08T17:14:51.156162Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-08-16T12:03:09.160586Z","title":"Yang, et al., Scalable Diffusion for Materials Generation, doi:10.48550/arXiv.2311.09235, http://arxiv.org/abs/2311.09235","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.14110","last_updated":"2025-04-18T23:54:25Z","snapshot_observed_at":"2026-08-16T12:22:16.613036Z","submitted_at":"2025-04-18T23:54:25Z","title":"System of Agentic AI for the Discovery of Metal-Organic Frameworks","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T12:03:09.160586Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2504.14110"},"observation_digest":"sha256:911f6a25d66aa1ac9c97aaa2ea121f0f5354d19920a40ba5cb6eb94ec9a9f577","observation_id":"62cac5f2-2e9b-48f7-acaf-e2c86fcf1b2b","resolution":{"observed_at":"2026-08-16T12:03:09.160586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-08-16T10:57:54.585141Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.16893","last_updated":"2025-09-07T02:16:35Z","snapshot_observed_at":"2026-08-16T10:50:53.828359Z","submitted_at":"2025-04-23T17:21:03Z","title":"Crystal structure prediction with host-guided inpainting generation and foundation potentials","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T10:57:54.585141Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2504.16893"},"observation_digest":"sha256:dc29cf07d479e30e92f7ef0dce8acd1c0abf337f837c62a3cc85136c4c2b54df","observation_id":"772c6278-7a8b-4708-bde3-75c2644bafed","resolution":{"observed_at":"2026-08-16T10:57:54.585141Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-08-15T16:39:48.793740Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02723","last_updated":"2025-09-02T18:19:26Z","snapshot_observed_at":"2026-08-16T07:04:06.371435Z","submitted_at":"2025-09-02T18:19:26Z","title":"Generative AI for Crystal Structures: A Review","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-15T16:39:48.793740Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2509.02723"},"observation_digest":"sha256:d8b98ec577a651e77db407e072211d3216907a853dc5de162a9513f21685939a","observation_id":"32ce111c-0c65-4e4c-9ee1-50e0607328a2","resolution":{"observed_at":"2026-08-15T16:39:48.793740Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-08-03T21:42:05.525501Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2511.14426","last_updated":"2026-05-28T17:48:10Z","snapshot_observed_at":"2026-08-13T11:56:58.685965Z","submitted_at":"2025-11-18T12:29:19Z","title":"MiAD: Mirage Atom Diffusion for De Novo Crystal Generation","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T21:42:05.525501Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2511.14426"},"observation_digest":"sha256:fbe9af02c4ff1e0008d0579638cc28c85fb884cbf2bdeb397644ba5c3061ab6a","observation_id":"7bda2eca-693b-4120-b735-9ec601f9219e","resolution":{"observed_at":"2026-08-03T21:42:05.525501Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-08-03T20:04:40.138503Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.21299","last_updated":"2026-06-22T13:58:44Z","snapshot_observed_at":"2026-08-13T03:53:10.736330Z","submitted_at":"2025-11-26T11:42:28Z","title":"Discovery and recovery of crystalline materials with property-conditioned transformers","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T20:04:40.138503Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2511.21299"},"observation_digest":"sha256:9b1d5afddd48cc73c06943f29cf411d2e658b4024823f2b7bf6afff1874c6220","observation_id":"ba781553-cee1-4af3-b34d-3bb25605ac89","resolution":{"observed_at":"2026-08-03T20:04:40.138503Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":"2311.09235","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-07-03T19:28:52.438084Z","title":"arXiv preprint arXiv:2311.09235 (2023)","venue":null,"work_id":"2c8efd19-1a09-4667-8ef0-838637e2924a","year":2023},"citing_paper":{"arxiv_id":"2602.20210","last_updated":"2026-05-25T04:14:15Z","snapshot_observed_at":"2026-08-13T15:40:11.856726Z","submitted_at":"2026-02-23T03:59:47Z","title":"Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-25T07:09:14.913144Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2602.20210"},"observation_digest":"sha256:2298362b85e174ffd3b0cdc399acdc65e8542dab6a0fd6dead91579040e73eb5","observation_id":"0ae01416-60a9-49d6-b444-86d0261eaf70","resolution":{"observed_at":"2026-05-25T07:10:27.669398Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-08-02T21:39:38.955818Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.20210","last_updated":"2026-05-25T04:14:15Z","snapshot_observed_at":"2026-08-13T15:40:11.856726Z","submitted_at":"2026-02-23T03:59:47Z","title":"Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T21:39:38.955818Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2602.20210"},"observation_digest":"sha256:680ba18ea25188c913df9a62d9385cfdff31b2661ffaa78a9473130c368289c1","observation_id":"f75ee35d-3df1-4477-96da-0b97aa1a2352","resolution":{"observed_at":"2026-08-02T21:39:38.955818Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":"2311.09235","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-07-03T19:28:52.438084Z","title":"arXiv preprint arXiv:2311.09235 (2023)","venue":null,"work_id":"2c8efd19-1a09-4667-8ef0-838637e2924a","year":2023},"citing_paper":{"arxiv_id":"2605.17254","last_updated":"2026-06-09T02:22:55Z","snapshot_observed_at":"2026-08-13T12:45:17.266726Z","submitted_at":"2026-05-17T04:31:46Z","title":"CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-20T13:39:56.672175Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2605.17254"},"observation_digest":"sha256:66469708d4663ebe2a4d9d4efa0088fb99796a313004c33c2b4c3c734f5d49e0","observation_id":"3f6499b9-20f7-4242-9799-5c0b5768a201","resolution":{"observed_at":"2026-05-20T13:43:19.676871Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":"2311.09235","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-07-03T19:28:52.438084Z","title":"arXiv preprint arXiv:2311.09235 (2023)","venue":null,"work_id":"2c8efd19-1a09-4667-8ef0-838637e2924a","year":2023},"citing_paper":{"arxiv_id":"2605.17254","last_updated":"2026-06-09T02:22:55Z","snapshot_observed_at":"2026-08-13T12:45:17.266726Z","submitted_at":"2026-05-17T04:31:46Z","title":"CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-22T09:31:47.827675Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2605.17254"},"observation_digest":"sha256:38b1ffb9da7fed1821afd3a9bd2132e00d204d845efaece2ecef124d7b04608c","observation_id":"e2e20c72-a756-4049-ad5f-2153e2f9e789","resolution":{"observed_at":"2026-05-22T09:34:47.008706Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":"2311.09235","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-07-03T19:28:52.438084Z","title":"arXiv preprint arXiv:2311.09235 (2023)","venue":null,"work_id":"2c8efd19-1a09-4667-8ef0-838637e2924a","year":2023},"citing_paper":{"arxiv_id":"2605.17254","last_updated":"2026-06-09T02:22:55Z","snapshot_observed_at":"2026-08-13T12:45:17.266726Z","submitted_at":"2026-05-17T04:31:46Z","title":"CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials","version":4},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-30T19:47:39.298750Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2605.17254"},"observation_digest":"sha256:57fee1cd54ce43874a7d42f33823e7e67847443a7c01546c75b0fd8a05fceabd","observation_id":"3f16c26d-9407-49f7-9a8e-a1cc1ad298c1","resolution":{"observed_at":"2026-06-30T19:55:01.691591Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation","version":2},"cited_work":{"arxiv_id":"2311.09235","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.09235","snapshot_observed_at":"2026-07-03T19:28:52.438084Z","title":"arXiv preprint arXiv:2311.09235 (2023)","venue":null,"work_id":"2c8efd19-1a09-4667-8ef0-838637e2924a","year":2023},"citing_paper":{"arxiv_id":"2606.17445","last_updated":"2026-06-16T03:00:52Z","snapshot_observed_at":"2026-08-15T10:39:54.303780Z","submitted_at":"2026-06-16T03:00:52Z","title":"Toward Controllable Catalyst Inverse Design via Large-Scale Autoregressive Pretraining","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T01:49:05.946138Z"},"links":{"cited_paper":"/paper/2311.09235","citing_paper":"/paper/2606.17445"},"observation_digest":"sha256:fa34e4a6e744883ddf500912724da1bf3dfc33e313c5ac78b719b94c835b8e2f","observation_id":"c3005ed2-969e-4f04-95e3-ae5f26ac1fce","resolution":{"observed_at":"2026-07-03T19:28:52.439784Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2311.09235/citation-record","integrity":"/paper/2311.09235/integrity","json":"/paper/2311.09235/citation-record.json","paper":"/paper/2311.09235"},"outbound":[],"paper":{"arxiv_id":"2311.09235","last_updated":"2024-06-03T20:07:00Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T14:51:00.993491Z","submitted_at":"2023-10-18T15:49:39Z","title":"Scalable Diffusion for Materials Generation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2311.09235."}