{"as_of":"2026-08-16T01:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b7d866c58d447ee4c4b5a1f9776a2dbaf9fd5c388f5325b910f958b2a9107e39","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T09:08:29.490187Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.20880/citation-record","integrity":"/paper/2607.20880/integrity","json":"/paper/2607.20880/citation-record.json","paper":"/paper/2607.20880"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41524-023-00984-y","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Adaptively driven X-ray diffraction guided by machine learning for autonomous phase identification","venue":"npj Computational Materials","work_id":"e9c3af4c-c2b8-4421-aa24-6ce572d3f2c2","year":2023},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:24.873012Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:1e07b3d3b97b365dae4e1d9e1811518818d555adc047ca8d6b3b3d1ac36c37b3","observation_id":"50b7dad2-2d0a-4a70-ae42-eba4a6342e90","resolution":{"observed_at":"2026-08-01T09:13:30.652487Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1039/d4dd00190g","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Au- tonomous robotic experimentation system for powder X-ray diffraction","venue":"Digital Discovery","work_id":"a96f9019-c479-462c-8d63-54159910e566","year":2024},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:24.915499Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:ed13249f0d30ca3b2246dcfa0a42b6c89ba74dae7c95a16460771edd02806b11","observation_id":"eb662632-1fd1-43a4-bd66-060b248f2a49","resolution":{"observed_at":"2026-08-01T09:13:30.604216Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:25.079621Z","title":"Automatedphase mapping of high-throughput X-ray diffraction data encoded with domain-specific materials science knowledge","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:25.079621Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:bd9631c78d24674a7c1cfaf96d3dfb30aea9f064ec254b2c9244470d0d0ed727","observation_id":"42c9e7df-3858-48d9-a8da-1c46bd5cd30a","resolution":{"observed_at":"2026-08-01T09:08:25.079621Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1021/acscombsci.0c00037","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"High-throughput and autonomous grazing incidence X-ray diffraction mapping of organic combinatorial thin-film library driven by machine learning","venue":"ACS Combinatorial Science","work_id":"d4dd5eac-72ba-4819-af69-03b3d8df276c","year":2020},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:25.236493Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:933238f1bf46c0641f890617d65840b76cd5df85d3857fe7694ff2ba017a3f7a","observation_id":"11bbc695-52e1-44cb-940b-8cbc9e49efe6","resolution":{"observed_at":"2026-08-01T09:13:30.519736Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:25.370976Z","title":"Chemical analysis by X-ray diffraction","venue":null,"work_id":null,"year":1938},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:25.370976Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:1f218698bbccadf65d1437950480abde88c4d27fc6fb5e722231160b07f347c7","observation_id":"5c2a45d9-a0d7-4226-b3b8-98d951030f7d","resolution":{"observed_at":"2026-08-01T09:08:25.370976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1107/s0021889876010959","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A fast search–match program for powder diffraction analysis","venue":"Journal of Applied Crystallography","work_id":"3f7bcd65-178d-436f-8525-b6a7e7a88668","year":1976},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:25.530594Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:bd1562b98844db0f000899e259cadb76530e53d2cc67455b2d397bc74388f5be","observation_id":"fdcaa1f0-e432-4c32-a65f-23ebab6b80c4","resolution":{"observed_at":"2026-08-01T09:13:30.448768Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:25.674756Z","title":"A profile refinement method for nuclear and magnetic structures","venue":null,"work_id":null,"year":1969},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:25.674756Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:447c445015dfc559eee6dc543f95b127ecbb6393beffeec011db92b6bb72903b","observation_id":"ea7ae787-0ead-4671-8f79-4c79b783ac40","resolution":{"observed_at":"2026-08-01T09:08:25.674756Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:25.798500Z","title":"Quantitative phase analysis from neutron powder diffraction data using the Rietveld method","venue":null,"work_id":null,"year":1987},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:25.798500Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:3ce3cb38e2df5c01cd93b417fbe2ffb9719f2f6b43aba72f5bbf64b569b917c5","observation_id":"a36e6e09-2152-4123-b238-fcf4d51b7278","resolution":{"observed_at":"2026-08-01T09:08:25.798500Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/min12020205","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"X-ray diffraction techniques for mineral characterization:Areviewforengineersofthefundamentals,applications,andresearchdirections","venue":"Minerals","work_id":"cc684177-94db-4662-aafd-3541343c4602","year":2022},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:25.945127Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:30688359950283b6a5dce8752d226bff0f6abc22c3d6c508814433c0c3762749","observation_id":"a157c7c8-861a-4924-9565-fb808d918a39","resolution":{"observed_at":"2026-08-01T09:13:30.369839Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1107/s1600576722004708","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Multi- variate versus traditional quantitative phase analysis of X-ray powder diffraction and fluorescence data of mixtures showing preferred orientation and microabsorption","venue":"Journal of Applied Crystallography","work_id":"8689fa05-5e8c-4e47-95af-a7b9758c296a","year":2022},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:26.028360Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:b68236492ef5ccdbaf7e36cc8e14f4411a729a00e38f865348c1303a12a6a1cf","observation_id":"cf878a46-a834-4f81-8bc7-2c76a2c7f793","resolution":{"observed_at":"2026-08-01T09:13:30.299025Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:26.170239Z","title":"Automated data analysis for powder X-ray diffraction using machine learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:26.170239Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:4316bb227c55e495a30e4e7b8339944fd2313565e89f826a1f905626a90cc32a","observation_id":"52a81404-96fb-4292-a4d5-12d9f7927ad8","resolution":{"observed_at":"2026-08-01T09:08:26.170239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41524-023-01164-8","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Auto- matedclassificationofbigX-raydiffractiondatausingdeeplearningmodels","venue":"npj Computational Materials","work_id":"829a7555-118c-4e49-ad71-e41a082876ac","year":2023},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:26.228184Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:7501a6cb820e915c54b03ba325eafc596ac9bb475d8747f9737849288a027b33","observation_id":"732301d7-854b-43ae-80a4-5099a9064574","resolution":{"observed_at":"2026-08-01T09:13:30.228609Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[{"edge_observation":{"observed_at":"2026-08-01T12:20:09.713686+00:00","source":"paper_reference_links","state":"open"},"event_date":"2024-06-24","event_type":"correction","notice_doi":"10.1038/s41524-024-01317-3","provenance":{"observed_at":"2026-07-11T03:08:28.659246+00:00","source":"crossref","source_record_id":"10.1038/s41524-024-01317-3->10.1038/s41524-023-01164-8:correction"}}],"reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:26.322017Z","title":"Machine learning in X-ray diffraction for materials discovery and characterization","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:26.322017Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:4f9a0807d56d50f9bc7db229bb2feae281f9b5ea55408b0368f576b9ada9b369","observation_id":"038ff89b-4772-42ff-862d-28b5a8f9b63f","resolution":{"observed_at":"2026-08-01T09:08:26.322017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1021/acs.jpcc.3c05147","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deeplearningmodels to identify common phases across material systems from X-ray diffraction","venue":"The Journal of Physical Chemistry C","work_id":"9408df2d-f189-4ee1-825b-9c783275972c","year":2023},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:26.441075Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:95213fc93ed7d2f3fc2da911939ee449e01ba2846c1e76b1e334857111445821","observation_id":"87f6ead4-852b-4599-9c46-fa341ddd2c83","resolution":{"observed_at":"2026-08-01T09:13:30.168638Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:26.553834Z","title":"Crystallographic phase identifier of a convolutional self-attention neural network (CPICANN) on powder diffraction patterns","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:26.553834Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:9193d3c5ed1593bf2968e7a57db9099c9376d4fbf32e8fec60bf8382d585da2d","observation_id":"914359a3-5a80-4482-b8f4-d4353ec9a5d3","resolution":{"observed_at":"2026-08-01T09:08:26.553834Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:26.725555Z","title":"Crystal structure assignment for unknown compounds from X-ray diffraction patterns with deep learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:26.725555Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:f6c2e49afd4adc8620e662add996bf24867e3f018d176e4654209a26f937b880","observation_id":"46ce85b6-102a-49ae-8a25-8eb11a592acb","resolution":{"observed_at":"2026-08-01T09:08:26.725555Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:26.838504Z","title":"A deep- learningtechniqueforphaseidentificationinmultiphaseinorganiccompoundsusingsyntheticXRD powder patterns","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:26.838504Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:ece583c05339b6e6ba362dbac4f06b3c69b2078c02b57c9cfcab37e1f0e8c1c3","observation_id":"4450c4d6-603d-4eac-ae64-12ffc6ffdc01","resolution":{"observed_at":"2026-08-01T09:08:26.838504Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:26.988095Z","title":"Machine learning-driven crystal system prediction for perovskites using augmented XRD data","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:26.988095Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:653c7e759259ffb5ea6bf6d208c7dbf492e601cead25f57cc79a4abd82006afc","observation_id":"7b837b1b-4817-4652-834a-2e6913c82e97","resolution":{"observed_at":"2026-08-01T09:08:26.988095Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41524-025-01743-x","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Interpretable X-ray diffraction spectra analysis using confidence evaluated deep learning enhanced by template element replacement","venue":"npj Computational Materials","work_id":"82828882-0f07-4a41-9496-c750974ca10a","year":2025},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:27.110531Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:43605800ef738e20cb62577eef3634c64ae683cd3ffc8f2f5adad688c2e7aa45","observation_id":"df5746f7-13c3-4c2d-b845-7bedc147eb93","resolution":{"observed_at":"2026-08-01T09:13:30.069667Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:27.271569Z","title":"XQueryer: an intelligent crystal structure identifier for powder X-ray diffraction","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:27.271569Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:a2f5592215591942ef8424d56e955198b63b93c18a7300454cebd32737a851df","observation_id":"f1601d12-ee0f-418f-90c5-f4e6874d24e0","resolution":{"observed_at":"2026-08-01T09:08:27.271569Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:27.350064Z","title":"Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:27.350064Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:04f6b9fc103278331abf697d56089d2eb7038e65281034aa17c270a1f0229798","observation_id":"6541a45c-d137-40b2-afc1-8487acf5774b","resolution":{"observed_at":"2026-08-01T09:08:27.350064Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1103/physrevb.99.245120","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Neural network based classification of crystal symmetries from X-ray diffraction patterns","venue":"Physical review. B./Physical review. B","work_id":"bffa91f5-bdc3-4551-a5ec-7425c4e2e0f7","year":2019},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:27.478717Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:0f6368613d0bc2e75a533f4f4e5a086ed9779d282d9fc93f9c1daa47c084fcde","observation_id":"c9fede17-81dd-49db-83d1-551535cd90d1","resolution":{"observed_at":"2026-08-01T09:13:30.000137Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:27.583356Z","title":"Crystal symmetry classification from powder X-ray diffraction patterns using a convolutional neural network","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:27.583356Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:f31fcf40a0d6e40428ec87b02dad0037c0ad024a20b3a63997e590ee1074657f","observation_id":"74603ca5-63df-4acf-9ee4-f9649fa8e1c5","resolution":{"observed_at":"2026-08-01T09:08:27.583356Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:27.653395Z","title":"Exploring supervised machine learning for multi-phase identification and quantification from powder X-ray diffraction spectra","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:27.653395Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:ca55e247558789a57b45d3b669e7f4c38e2eb1e42656b327adabc300cb70d1fb","observation_id":"473fc9b4-81ae-43ab-8870-6e70f0d4b2e7","resolution":{"observed_at":"2026-08-01T09:08:27.653395Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41467-026-70035-9","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Equivariant diffusion solution for inorganic crystal structure determination from powder X-ray diffraction data","venue":"Nature Communications","work_id":"c9825887-ed64-4ede-afb9-a336a4c62746","year":2026},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:27.756431Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:eec8d15dea0f05ea1df71d339c9b4b75212f7bc758798fc9a59f8fec2a734ac4","observation_id":"b6ab620a-2efb-4dd4-8196-87a402e47419","resolution":{"observed_at":"2026-08-01T09:13:29.912250Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1038/s41524-026-02015-y","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"KAN-enhanced contrastive learning: the accelerator of crystal structure 17 identification from XRD patterns","venue":"npj Computational Materials","work_id":"c1225535-2bb4-4e91-ab7d-d361bdb2c522","year":2026},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:27.852612Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:dfdb85227bd564b439c7f3dcf0c9c8cd31719d9d958758f3601cf7dbf4a6a73b","observation_id":"062fc674-a641-442d-b40c-76ec2152a5b3","resolution":{"observed_at":"2026-08-01T09:13:29.868933Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:27.947170Z","title":"Identifying crystal structures beyond known prototypes from X-ray powder diffraction spectra","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:27.947170Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:0276d49dffb6592549220a3ee0fa258df1b64984cf598b631bb75acb559c38b9","observation_id":"842a0f32-07ee-415c-88ac-6589899e5116","resolution":{"observed_at":"2026-08-01T09:08:27.947170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:28.044755Z","title":"Dara: Automated multiple-hypothesis phase identification and refinement from powder X-ray diffraction","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:28.044755Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:1ebd24847b0b6f27c63455e94a3fb6ce3578536d9799b909e598bcdf994a41cd","observation_id":"5cfabfe7-064d-4a65-a6b7-572cbeaeb535","resolution":{"observed_at":"2026-08-01T09:08:28.044755Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1360/ssc-2022-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:13:29.767536Z","title":"Atomly.net materials database and its application in inorganic chemistry","venue":null,"work_id":"0a81c0fd-0def-45ad-978b-cb006991198b","year":2023},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:28.112383Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:988b86021edc1b40b5c0ebdcab4b23d3d775d99421593091816a3c5f39dae2b2","observation_id":"e22e45d1-1990-45bf-a731-cd64a29307db","resolution":{"observed_at":"2026-08-01T09:13:29.791600Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.scib.2024.08.039","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"GPTFF: A high-accuracy out-of-the-box universal AI force field for arbitrary inorganic materials","venue":"Science Bulletin","work_id":"29a93b36-c025-4896-af74-9cd322422195","year":2024},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:28.215940Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:5af29bbbc964852c038cffbe49382d6dc3f29f786c91295508faf7887170e733","observation_id":"128eeeff-29f1-4443-95f6-45a0c1bb103e","resolution":{"observed_at":"2026-08-01T09:13:29.752122Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:28.346011Z","title":"X-ray line profile analysis on the deformation microstructure of Al-bearing high-Mn steels","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:28.346011Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:ed2fe2c93eeb745a623d71632e48d5927a75055c57d8dbecb5e2f06962bde10a","observation_id":"8846b58f-7703-47d8-9a8b-b9cd13f43845","resolution":{"observed_at":"2026-08-01T09:08:28.346011Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:28.473951Z","title":"Computational investigation into XRD peak broadening effects with discrete dislocation dynamics in additively manufactured 316L stainless steel","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:28.473951Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:1ccfb34be8727fb6181a5ea45f385b483cf04f9f53f2d6326f4571c8987e9817","observation_id":"819ccea5-6e1c-4fbd-b53e-c0b26e10038a","resolution":{"observed_at":"2026-08-01T09:08:28.473951Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:28.577354Z","title":"Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:28.577354Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:16448b7c8f94fc9ffa7d5a21e1c03bc40b98981f8412506c1aee08275383180d","observation_id":"1cb582a9-657b-4f1f-81a3-783ad7031846","resolution":{"observed_at":"2026-08-01T09:08:28.577354Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/tbdata.2019","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:13:29.628520Z","title":"Billion-scale similarity search with GPUs","venue":null,"work_id":"6c70ee00-a990-45c8-903e-9c2c5c112764","year":2021},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:28.780997Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:7efb840aff49e4af35dfdfc1bc6fd8fab79801f260de3a5c47100b6d92334187","observation_id":"84854e98-198d-425a-afbe-a3fe0ad1b26c","resolution":{"observed_at":"2026-08-01T09:13:29.687456Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:28.903279Z","title":"Milvus: A purpose-built vector data management system","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:28.903279Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:559b104d22f240fd9b495e9c65201a14224f513a0533e945dcc87b181f43fae7","observation_id":"dcf51aa8-748e-4d86-b264-0a9b0d78962b","resolution":{"observed_at":"2026-08-01T09:08:28.903279Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:29.042533Z","title":"Survey of vector database management systems","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:29.042533Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:4bd84d871d99831c85e826b87b944cebabea519d9c1aa7db7e7748d647a844e5","observation_id":"6a0d8a97-2110-4984-b0af-6e64242272c5","resolution":{"observed_at":"2026-08-01T09:08:29.042533Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:29.105472Z","title":"VBASE: Unifying online vector similarity search and relational queries via relaxed monotonicity","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:29.105472Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:b76927f1bfb5745a6a55b8f8fae76f404741df12f004502a7c7b51254fe0b40e","observation_id":"51166b32-e6cc-47cb-abe5-87091ea15a55","resolution":{"observed_at":"2026-08-01T09:08:29.105472Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:29.192538Z","title":"The power of databases: the RRUFF project","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:29.192538Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:8e4ebe6e85033f3eff16e2e74f2b55454433d1fbe1a3c8bbd15e131db04310f7","observation_id":"ca78d830-14e0-43fa-af4a-c0b2a78ce6e9","resolution":{"observed_at":"2026-08-01T09:08:29.192538Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:29.290193Z","title":"GSAS-II: the genesis of a modern open-source all purpose crystallography software package","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:29.290193Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:805f791c0b3a1feb7a2e262f306da5f4870d8d0c4c28084152caf4dda45897d1","observation_id":"1e17f31d-df82-4b79-b77b-5b1a008e7ed9","resolution":{"observed_at":"2026-08-01T09:08:29.290193Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1063/1.2717168","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Density functional theory analysisof the structuraland electronic properties of rutile andanatase polytypes: Performances of different exchange-correlation functionals","venue":"The Journal of Chemical Physics","work_id":"0eb469de-8f0a-4061-b4fc-fb8b2f471081","year":2007},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:29.490187Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:74be38f229ab3f623c37eafdde531ac1682c724a539af2278bd14ec2ad77a986","observation_id":"45a61478-80a4-4255-bff9-2a5087078964","resolution":{"observed_at":"2026-08-01T09:13:29.585017Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:08:29.380181Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction","version":2},"reference_index":549,"source":"pdf_text","source_observed_at":"2026-08-01T09:08:29.380181Z"},"links":{"citing_paper":"/paper/2607.20880"},"observation_digest":"sha256:b9c819f0b2e47c94e1f2d157f0914fce266a979b4702b0e9988d6bab02cbb44e","observation_id":"0fd0772e-542d-4f7b-99aa-7f666db7bc36","resolution":{"observed_at":"2026-08-01T09:08:29.380181Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.20880","last_updated":"2026-07-26T14:31:38Z","latest_version":2,"primary_category":"cond-mat.mtrl-sci","snapshot_observed_at":"2026-08-15T18:00:48.374142Z","submitted_at":"2026-07-23T03:00:54Z","title":"MatDiffract: A Material-Informed Automated Analysis Platform for X-ray Powder Diffraction"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":6,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":20,"verified_exact":15,"verified_fuzzy":0},"total_outbound_references":41},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.20880."}