{"as_of":"2026-08-23T18:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a37987905ef1ad87d11eae446e983e04b4ebbd9ba92f1821029dfa74492d0b18","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T14:16:41.288700Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+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/2608.11447/citation-record","integrity":"/paper/2608.11447/integrity","json":"/paper/2608.11447/citation-record.json","paper":"/paper/2608.11447"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2559.2017","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.907795Z","title":"Polyurethane Composite Foams in High-Performance Applications: A Review,","venue":null,"work_id":"0ff3cbed-cbdd-4ecc-a172-f1c12c8b936f","year":2018},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.140017Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:ac921fd02d78625a45bd6b38526835c338061cee85f7f3e028022ec5b641226f","observation_id":"0ea62718-8893-49b2-81e8-5b3bc2db9ff1","resolution":{"observed_at":"2026-08-15T14:16:41.913860Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10924-023-03161-w","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-19T11:03:45.297681Z","title":"Redefining Construction: An In-Depth Review of Sustainable Polyurethane Applications,","venue":"Journal of Polymers and the Environment","work_id":"dab978c7-c2a6-4775-b876-f0d7a07a418f","year":2024},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.145262Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:e7693c7f46e2882a29aec748d427cf1ed08294fe92766379b07d56a301bf9925","observation_id":"02cb1e04-37d8-4cbd-b871-22af61cb47aa","resolution":{"observed_at":"2026-08-15T14:16:41.466535Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10311-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.448899Z","title":"Production of polyols and polyurethane from biomass: a review,","venue":null,"work_id":"d0910a37-4cf1-4fa1-8deb-7b2e39e54165","year":2023},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.149920Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:31ea15bc20131b4b70c3a9739b90e0e1162f000367663e099ab6eef4ceb94cff","observation_id":"3fd26152-a4a7-49ff-b265-e0ef554990ff","resolution":{"observed_at":"2026-08-15T14:16:41.453242Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:42.109915Z","title":"Lignin‐based polyurethane: recent advances and future perspectives,","venue":null,"work_id":"eb0092c7-0b96-4f21-bbdc-2b20ccc2ef18","year":2021},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.154220Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:8415f55877a421f608c7859377cd535d779acf72c0a9ce60c6860631e7b1f078","observation_id":"efdab637-ebbb-448f-90b0-7d7cc5269dde","resolution":{"observed_at":"2026-08-15T14:16:42.114184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10973-015-4434-2","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-19T11:03:45.297681Z","title":"Improved mechanical property, thermal performance, flame retardancy and fire behavior of lignin-based rigid polyurethane foam nanocomposite,","venue":"Journal of Thermal Analysis and Calorimetry","work_id":"fe2aeaea-3904-4734-a6ff-e02f0f559796","year":2015},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.158149Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:08739102c6bf361bc11b6992e48c4b2793fb3b07105bf8c5556aafa013c6d820","observation_id":"597e15fa-638c-40aa-b19e-b11af4caf7c0","resolution":{"observed_at":"2026-08-15T14:16:41.440261Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1039/d0gc00449a","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.420097Z","title":"Lignin-derived bio-based flame retardants toward high-performance sustainable polymeric materials,","venue":null,"work_id":"c70ea7ff-07f8-410a-a62d-98e2b178226f","year":2020},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.162726Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:9d7d27c110771cf1ab62536b08345cd011c732f24099c33a680cea84110dfd9c","observation_id":"1a3e8267-e2b9-47dd-89d2-6f18c6b88f15","resolution":{"observed_at":"2026-08-15T14:16:41.425278Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1177/0021955x05053525","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.408875Z","title":"Cell Morphology and Mechanical Properties of Rigid Polyurethane Foam,","venue":null,"work_id":"9e4d75dd-b516-4673-95d7-80e189fa565f","year":2005},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.167157Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:3b0f54af63809c7d2767fca35637754fb1712e554e1aa8d6a2dc93fe633984df","observation_id":"f6eb13ad-0bdf-4e68-9968-4826af24a300","resolution":{"observed_at":"2026-08-15T14:16:41.412586Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11340-","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.396955Z","title":"Density, Microstructure, and Strain-Rate Effects on the Compressive Response of Polyurethane Foams,","venue":null,"work_id":"b1855313-3c7c-48f7-a4c5-63a35f2e9dd5","year":2022},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.171154Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:bf7a37ecad874ff1983a8a9628bdc63c7a50834db50b598a807accc3792075ff","observation_id":"0662776b-a4f8-400b-ae0a-514b7969e903","resolution":{"observed_at":"2026-08-15T14:16:41.400674Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/pls2.10082","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T11:08:47.750906Z","title":"Machine learning‐based model for predicting the material properties of nanostructured aerogels,","venue":"SPE Polymers","work_id":"761f78a9-b336-4f9d-b804-636a5873a44a","year":2022},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.175108Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:3d453859e5dfc2ea780dbe9a032aa34fa58a9c0102a626063c1622db183cd6aa","observation_id":"269e7344-9942-491d-9c65-7b623f504f6d","resolution":{"observed_at":"2026-08-15T14:16:41.389966Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10973-021-10960-7","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-19T11:03:45.297681Z","title":"Applying machine learning for predicting thermal conductivity coefficient of polymeric aerogels,","venue":"Journal of Thermal Analysis and Calorimetry","work_id":"4409ade0-6ead-4a3c-9c12-dad1e064e590","year":2021},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.179052Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:e0754e1b289d88a45eba2101e4ec36b9165fd4326df97f77653fcb790aeb1f39","observation_id":"86c5deda-028c-4c16-83a3-60448bfe4c33","resolution":{"observed_at":"2026-08-15T14:16:41.378683Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2024.12542","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.836453Z","title":"A developed convolutional neural network model for accurately and stably predicting effective thermal conductivity of gradient porous ceramic materials,","venue":null,"work_id":"6d35b440-482e-464c-a3d5-71f80668a760","year":2024},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.183179Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:ab49c920e2eef08c4f5982f4d690ae930f332b5bc5f4c62b4b0d11e2838fac30","observation_id":"75759a6a-1b8e-4330-aacb-f547774f0f76","resolution":{"observed_at":"2026-08-15T14:16:41.843077Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-15T14:16:41.187382Z","title":"Research on multi-source microstructure image recognition of foam ceramics using convolutional network combine with frequency domain,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.187382Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:3d939d2a9363d6f6b6dcb9743d9f7fd3e3b3b2bdb521d73ae062726fddc51b5b","observation_id":"979a140d-8b6f-492d-b46c-937ca3f7ca07","resolution":{"observed_at":"2026-08-15T14:16:41.187382Z","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":"2026-08-15T14:16:41.191474Z","title":"Predicting 3D particles shapes based on 2D images by using convolutional neural network,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.191474Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:c2e3d21ae136fd77d8776d98e715d04e3dca1d3ecc8aae0add59c3a98ead4bdf","observation_id":"27e9b0fc-f7d6-495b-8b9c-e5941fe276eb","resolution":{"observed_at":"2026-08-15T14:16:41.191474Z","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/jcs8100387","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.354236Z","title":"Predicting Mechanical Properties from Microstructure Images in Fiber-Reinforced Polymers Using Convolutional Neural Networks,","venue":null,"work_id":"a12dd785-bcbc-4833-bc68-0a476bf80380","year":2024},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.195088Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:2b5f46660b8c32a7456f2dac4c702a6f504ee5ffd7a917cdb01f8162437bf289","observation_id":"7c97f379-f74b-43a4-8541-2b5072cacec4","resolution":{"observed_at":"2026-08-15T14:16:41.359401Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:42.096906Z","title":"Adaptive residual convolutional neural network for compressive strength prediction of energetic materials using SEM images,","venue":null,"work_id":"0353e4ae-c74d-4059-bbc5-3f738a0165a6","year":2024},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.198891Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:e2dca0a8a2ecde8b8181be56eff28d866ec4abd45580d6de3a282613485aa02d","observation_id":"204a8c97-48a2-489e-940d-697fd18034f2","resolution":{"observed_at":"2026-08-15T14:16:42.101169Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-15T14:16:41.202798Z","title":"Data-driven prediction of the mechanical behavior of nanocrystalline graphene using a deep convolutional neural network with PCA,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.202798Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:f27c89a3c4fa6352dd9ca11c54018c100fb1f06eba07e54fcb0571159f6d9df0","observation_id":"95b9b2b1-de1f-4b7d-b698-d45b373a2269","resolution":{"observed_at":"2026-08-15T14:16:41.202798Z","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":"2025.12823","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.702542Z","title":"Neural network-optimized imaging for classifying lignin-based polyurethane foams: Linking molecular composition to cellular microstructure using advanced machine learning,","venue":null,"work_id":"4fca254d-4692-4b9d-9f1b-3afacee5e040","year":2025},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.206847Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:364adaa72e03efb8bb303faa7580ca680c78508d9dee3155c4123ce4f6672519","observation_id":"6330a107-c58c-4986-9f76-7943a2c09b96","resolution":{"observed_at":"2026-08-15T14:16:41.708865Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-15T14:16:41.210709Z","title":"Exploring the microstructure–property relationship in polymer foams using advanced statistical methods, machine learning and deep learning: A review,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.210709Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:62e9414aa94baba009a14707d2dbdccc860b865bbcb4e5ffbef5bd0c0a25526b","observation_id":"ab7d3689-bfc7-4bb4-a8b1-6e9c2dcaac48","resolution":{"observed_at":"2026-08-15T14:16:41.210709Z","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/ijms251910810","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.332665Z","title":"Solid-State Structures and Properties of Lignin Hydrogenolysis Oil Compounds: Shedding a Unique Light on Lignin Valorization,","venue":null,"work_id":"16b23c3a-fc6c-4c7f-a9ca-b733e4952adb","year":2024},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.214655Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:f23eab8964d4c29682e80b4e33c73a8b19939398cd80e3ebfcc339196bdc5628","observation_id":"70b6e7d3-76d2-4c11-856b-a23b52e910eb","resolution":{"observed_at":"2026-08-15T14:16:41.337075Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1021/acsapm.1c01081","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.317552Z","title":"Preparation of Mechanically Robust Bio-Based Polyurethane Foams Using Depolymerized Native Lignin,","venue":null,"work_id":"1fc60231-86ee-44b8-be72-0d9b930729a3","year":2021},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.218575Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:e306157bbc3f143323ce3aeb20964f1e2504f5ceb7a5aebbfa2991e6bef45417","observation_id":"fbc8b4c2-9673-472d-aba9-bc15b06963ac","resolution":{"observed_at":"2026-08-15T14:16:41.324262Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:42.084074Z","title":"Toward bio-based epoxy thermoset polymers from depolymerized native lignins produced at the pilot scale,","venue":null,"work_id":"e67042e0-e381-4a3e-bd02-210c38a42803","year":2020},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.222505Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:07b5737e4689b0bdc244366c86df9bb985670577cde348f2405a2eb0c8dfe5ac","observation_id":"fd81fa24-c144-4d21-93e9-4d1622f55f59","resolution":{"observed_at":"2026-08-15T14:16:42.088392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:42.070776Z","title":"Cohen, Statistical power analysis for the behavioral sciences","venue":null,"work_id":"2e6a31f7-e2ab-4dd8-994a-0a1601b1be43","year":2013},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.226004Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:154fa34ad5befedadacfa9a58cf50ce3f53102838eb7b30ed7305dab0449180f","observation_id":"c49071cc-e731-42e9-ae72-a70c392f8202","resolution":{"observed_at":"2026-08-15T14:16:42.075344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:42.055944Z","title":"James, D","venue":null,"work_id":"bd0b61da-de48-4d60-940f-988374e0fed4","year":2013},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.229533Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:1c6cba8178918f26775131249be47ffd9e84bdb3029bff39a324ad7f0988c036","observation_id":"d12b5498-96d7-4fd4-99b2-530e3a04f5b0","resolution":{"observed_at":"2026-08-15T14:16:42.061436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:42.042361Z","title":"A survey on image data augmentation for deep learning,","venue":null,"work_id":"fdeafc82-e791-40a6-982b-9b9b123c416a","year":2019},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.233008Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:47d19a038fc7eafe7b2bbc6a640c414633c845094d6b468faf453604762d6a52","observation_id":"56fcd7fa-ac70-432d-9f76-13764cfe839d","resolution":{"observed_at":"2026-08-15T14:16:42.047099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:42.029162Z","title":"The effectiveness of data augmentation in image classification using deep learning,","venue":null,"work_id":"80c2508f-b126-4a54-a357-f362f77908ac","year":2017},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.236627Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:04f2649540c93379d99684377ad98c4bb2f6ee1640d7183fe0b99c6535ebb8d7","observation_id":"817879bf-87c3-4f4f-a942-d050d50ff184","resolution":{"observed_at":"2026-08-15T14:16:42.033868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.04747","last_updated":"2017-06-15T13:21:04Z","snapshot_observed_at":"2026-08-15T03:49:17.013617Z","submitted_at":"2016-09-15T17:32:34Z","title":"An overview of gradient descent optimization algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.04747","snapshot_observed_at":"2026-08-15T14:16:41.240174Z","title":"An overview of gradient descent optimization algorithms,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.240174Z"},"links":{"cited_paper":"/paper/1609.04747","citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:190389603e36570686dc17a902b545a04ea3289a59c8ca7d92556f0f0cf007c4","observation_id":"3c334701-332d-4cef-a1b6-6c7bfc8d3b60","resolution":{"observed_at":"2026-08-15T14:16:41.240174Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-15T14:16:41.244883Z","title":"A method for stochastic optimization,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.244883Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:30dfb3792fc3babe76904f36747ad3d60a3caa119937409d7ca501cd1849a3f8","observation_id":"5282ec04-a8f7-444c-8f45-451278caefea","resolution":{"observed_at":"2026-08-15T14:16:41.244883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-08-14T20:13:52.872565Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-15T14:16:41.250171Z","title":"Decoupled weight decay regularization,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.250171Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:52d161d8712478190d70fb82c182a8ff6edda417919d3e3e82ae814149e5ceb0","observation_id":"cb30e1df-1223-4e7e-8f57-1cea638baab4","resolution":{"observed_at":"2026-08-15T14:16:41.250171Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:42.016236Z","title":"Practical recommendations for gradient-based training of deep architectures,","venue":null,"work_id":"7132b5fa-d877-45f9-8d32-af928e81f86d","year":2012},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.254732Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:58d8f45de832c33d8d43531c9d0a2cfc6ee9949c91215d3b152dfc6856699a3d","observation_id":"bc644307-1f1d-4a3f-8460-f4976ce682fc","resolution":{"observed_at":"2026-08-15T14:16:42.020383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.03983","last_updated":"2017-05-03T16:28:09Z","snapshot_observed_at":"2026-07-06T05:06:55.589962Z","submitted_at":"2016-08-13T13:46:05Z","title":"SGDR: Stochastic Gradient Descent with Warm Restarts","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.03983","snapshot_observed_at":"2026-08-15T14:16:41.258243Z","title":"Sgdr: Stochastic gradient descent with warm restarts,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.258243Z"},"links":{"cited_paper":"/paper/1608.03983","citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:2fe47606e6634416df7135c72ab0c185838f7bcd9998b87fa2265f0dadb2b281","observation_id":"09c9000a-20f6-472c-a9d9-d8a2d41a5b51","resolution":{"observed_at":"2026-08-15T14:16:41.258243Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:42.002518Z","title":"Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks,","venue":null,"work_id":"b4c3ed00-1f24-4307-8ce5-8464f0998175","year":2018},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.262157Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:5a2d033d35699347eea04a6814e490d1f7fdc57c5d4abea9b08f507ee6fd2336","observation_id":"0895b999-dec8-403a-a692-f35536e496a9","resolution":{"observed_at":"2026-08-15T14:16:42.007290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.988304Z","title":"Pearson correlation coefficient,","venue":null,"work_id":"4cb46914-3dde-4870-bcda-e10fb2eb1db1","year":2009},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.265788Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:b835f74394be37445e269f8ece3b5ae9610a51b151d4126e088ee41c5c6e3123","observation_id":"f8a762cc-d9da-44fc-a749-7a06c6f5b184","resolution":{"observed_at":"2026-08-15T14:16:41.992836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.974196Z","title":"Early stopping-but when?,","venue":null,"work_id":"98d245c7-fe82-4dcb-8aa7-6d0bb3c766f0","year":2002},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.269882Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:564a8230245b7c4eb7ea9978297965e62c59155288335787ad4675948012973a","observation_id":"50b844cd-ce6e-4ef8-8552-dac35560a3f2","resolution":{"observed_at":"2026-08-15T14:16:41.978733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-15T14:16:41.273365Z","title":"Multi-task learning using uncertainty to weigh losses for scene geometry and semantics,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.273365Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:b0292c48634dcf1092463f8f95b969811ae369e7d792478c5a488f6bc88fc640","observation_id":"3a8cf3d6-da2c-46fa-8ad3-ff7eb7748a1f","resolution":{"observed_at":"2026-08-15T14:16:41.273365Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.949014Z","title":"The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation,","venue":null,"work_id":"b16efdbf-c2d9-4159-92ed-8aac590386f5","year":2021},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.276895Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:5e70802427952a1ef5121e7a0969e30ab22baae392506f0d389cc3ae9e6270ee","observation_id":"a642c187-7b3a-4827-a0a4-8edc059ceb32","resolution":{"observed_at":"2026-08-15T14:16:41.954480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.936110Z","title":"Grad-cam: Visual explanations from deep networks via gradient-based localization,","venue":null,"work_id":"687b2461-ac5b-4cff-88c4-a55101c1507f","year":2017},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.281588Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:166c79736db3bcce0c2f45f0db4937bf2e03ef1ff8c80f286d793617f4c56972","observation_id":"9ab185e8-87f8-4710-8011-4fc3aa28a523","resolution":{"observed_at":"2026-08-15T14:16:41.940620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T14:16:41.922353Z","title":"A computationally efficient hybrid neural network architecture for porous media: Integrating convolutional and graph neural networks for improved property predictions,","venue":null,"work_id":"45580952-4e26-434c-9288-9efa3a9aff4c","year":2025},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.285186Z"},"links":{"citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:7e3d540ee514365d57d03f8b3ecc52db91ec71226bd8e84b26875f79b70981e5","observation_id":"234454e7-efed-4820-a0f8-09929bbced5d","resolution":{"observed_at":"2026-08-15T14:16:41.927546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.06418","last_updated":"2025-01-01T03:11:56Z","snapshot_observed_at":"2026-08-18T16:51:08.052249Z","submitted_at":"2023-11-10T22:42:11Z","title":"A Computationally Efficient Hybrid Neural Network Architecture for Porous Media: Integrating Convolutional and Graph Neural Networks for Improved Property Predictions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.06418","snapshot_observed_at":"2026-08-15T14:16:41.288700Z","title":"A computationally efficient hybrid neural network architecture for porous media: Integrating cnns and gnns for improved permeability prediction,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T14:16:41.288700Z"},"links":{"cited_paper":"/paper/2311.06418","citing_paper":"/paper/2608.11447"},"observation_digest":"sha256:68e1db22b489d633731d5e038d4fd604bb88f3a1a9dcb4b2d9a162b209613966","observation_id":"abe16cbe-58c9-483b-9d3d-71ccc3695e16","resolution":{"observed_at":"2026-08-15T14:16:41.288700Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.11447","last_updated":"2026-08-11T21:25:22Z","latest_version":1,"primary_category":"cs.CE","snapshot_observed_at":"2026-08-15T23:10:09.262522Z","submitted_at":"2026-08-11T21:25:22Z","title":"Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":4,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":8,"verified_exact":10,"verified_fuzzy":14},"total_outbound_references":38},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2608.11447."}