Get quick answers to your questions about the article from our AI researcher chatbot
{'id': 'https://openalex.org/W3081254653', 'doi': None, 'title': 'Dynamic earthquake rupture across complex 3D fracture networks', 'display_name': 'Dynamic earthquake rupture across complex 3D fracture networks', 'publication_year': 2019, 'publication_date': '2019-12-13', 'ids': {'openalex': 'https://openalex.org/W3081254653', 'mag': '3081254653'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'http://ui.adsabs.harvard.edu/abs/2019AGUFM.S51E0444G/abstract', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S4306501062', 'display_name': 'AGU Fall Meeting Abstracts', 'issn_l': None, 'issn': None, 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': None, 'host_organization_name': None, 'host_organization_lineage': [], 'host_organization_lineage_names': [], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'article', 'type_crossref': 'journal-article', 'indexed_in': [], 'open_access': {'is_oa': False, 'oa_status': 'closed', 'oa_url': None, 'any_repository_has_fulltext': False}, 'authorships': [{'author_position': 'first', 'author': {'id': 'https://openalex.org/A5016717269', 'display_name': 'Alice‐Agnes Gabriel', 'orcid': 'https://orcid.org/0000-0003-0112-8412'}, 'institutions': [{'id': 'https://openalex.org/I8204097', 'display_name': 'Ludwig-Maximilians-Universität München', 'ror': 'https://ror.org/05591te55', 'country_code': 'DE', 'type': 'education', 'lineage': ['https://openalex.org/I8204097']}], 'countries': ['DE'], 'is_corresponding': False, 'raw_author_name': 'A. A. Gabriel', 'raw_affiliation_strings': ['Ludwig-Maximilians-University of Munich'], 'affiliations': [{'raw_affiliation_string': 'Ludwig-Maximilians-University of Munich', 'institution_ids': ['https://openalex.org/I8204097']}]}, {'author_position': 'last', 'author': {'id': 'https://openalex.org/A5077081496', 'display_name': 'Sebastian Anger', 'orcid': None}, 'institutions': [{'id': 'https://openalex.org/I8204097', 'display_name': 'Ludwig-Maximilians-Universität München', 'ror': 'https://ror.org/05591te55', 'country_code': 'DE', 'type': 'education', 'lineage': ['https://openalex.org/I8204097']}], 'countries': ['DE'], 'is_corresponding': False, 'raw_author_name': 'S. Anger', 'raw_affiliation_strings': ['Ludwig-Maximilians-University of Munich'], 'affiliations': [{'raw_affiliation_string': 'Ludwig-Maximilians-University of Munich', 'institution_ids': ['https://openalex.org/I8204097']}]}], 'countries_distinct_count': 1, 'institutions_distinct_count': 1, 'corresponding_author_ids': [], 'corresponding_institution_ids': [], 'apc_list': None, 'apc_paid': None, 'fwci': 0.315, 'has_fulltext': False, 'cited_by_count': 2, 'citation_normalized_percentile': {'value': 0.529782, 'is_in_top_1_percent': False, 'is_in_top_10_percent': False}, 'cited_by_percentile_year': {'min': 71, 'max': 75}, 'biblio': {'volume': '2019', 'issue': None, 'first_page': None, 'last_page': None}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T13018', 'display_name': 'Machine Learning for Earthquake Early Warning Systems', 'score': 0.9936, 'subfield': {'id': 'https://openalex.org/subfields/1702', 'display_name': 'Artificial Intelligence'}, 'field': {'id': 'https://openalex.org/fields/17', 'display_name': 'Computer Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, 'topics': [{'id': 'https://openalex.org/T13018', 'display_name': 'Machine Learning for Earthquake Early Warning Systems', 'score': 0.9936, 'subfield': {'id': 'https://openalex.org/subfields/1702', 'display_name': 'Artificial Intelligence'}, 'field': {'id': 'https://openalex.org/fields/17', 'display_name': 'Computer Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T10535', 'display_name': 'Landslide Hazards and Risk Assessment', 'score': 0.9872, 'subfield': {'id': 'https://openalex.org/subfields/2308', 'display_name': 'Management, Monitoring, Policy and Law'}, 'field': {'id': 'https://openalex.org/fields/23', 'display_name': 'Environmental Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T11512', 'display_name': 'Anomaly Detection in High-Dimensional Data', 'score': 0.9844, 'subfield': {'id': 'https://openalex.org/subfields/1702', 'display_name': 'Artificial Intelligence'}, 'field': {'id': 'https://openalex.org/fields/17', 'display_name': 'Computer Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/earthquake-detection', 'display_name': 'Earthquake Detection', 'score': 0.620007}, {'id': 'https://openalex.org/keywords/real-time-seismology', 'display_name': 'Real-Time Seismology', 'score': 0.583329}, {'id': 'https://openalex.org/keywords/seismic-phase-picking', 'display_name': 'Seismic Phase Picking', 'score': 0.569096}, {'id': 'https://openalex.org/keywords/high-dimensional-data', 'display_name': 'High-Dimensional Data', 'score': 0.519412}, {'id': 'https://openalex.org/keywords/deep-learning', 'display_name': 'Deep Learning', 'score': 0.511247}, {'id': 'https://openalex.org/keywords/earthquake-rupture', 'display_name': 'Earthquake rupture', 'score': 0.45529652}], 'concepts': [{'id': 'https://openalex.org/C43369102', 'wikidata': 'https://www.wikidata.org/wiki/Q2307625', 'display_name': 'Fracture (geology)', 'level': 2, 'score': 0.56992954}, {'id': 'https://openalex.org/C127313418', 'wikidata': 'https://www.wikidata.org/wiki/Q1069', 'display_name': 'Geology', 'level': 0, 'score': 0.54936343}, {'id': 'https://openalex.org/C2780490779', 'wikidata': 'https://www.wikidata.org/wiki/Q16966490', 'display_name': 'Earthquake rupture', 'level': 3, 'score': 0.45529652}, {'id': 'https://openalex.org/C165205528', 'wikidata': 'https://www.wikidata.org/wiki/Q83371', 'display_name': 'Seismology', 'level': 1, 'score': 0.45117632}, {'id': 'https://openalex.org/C187320778', 'wikidata': 'https://www.wikidata.org/wiki/Q1349130', 'display_name': 'Geotechnical engineering', 'level': 1, 'score': 0.15757814}, {'id': 'https://openalex.org/C175551986', 'wikidata': 'https://www.wikidata.org/wiki/Q47089', 'display_name': 'Fault (geology)', 'level': 2, 'score': 0.10251844}], 'mesh': [], 'locations_count': 1, 'locations': [{'is_oa': False, 'landing_page_url': 'http://ui.adsabs.harvard.edu/abs/2019AGUFM.S51E0444G/abstract', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S4306501062', 'display_name': 'AGU Fall Meeting Abstracts', 'issn_l': None, 'issn': None, 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': None, 'host_organization_name': None, 'host_organization_lineage': [], 'host_organization_lineage_names': [], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}], 'best_oa_location': None, 'sustainable_development_goals': [{'score': 0.59, 'display_name': 'Climate action', 'id': 'https://metadata.un.org/sdg/13'}], 'grants': [], 'datasets': [], 'versions': [], 'referenced_works_count': 0, 'referenced_works': [], 'related_works': ['https://openalex.org/W3210839296', 'https://openalex.org/W3201158330', 'https://openalex.org/W3152295486', 'https://openalex.org/W3128443162', 'https://openalex.org/W3125289512', 'https://openalex.org/W3118333177', 'https://openalex.org/W3110212805', 'https://openalex.org/W3109073477', 'https://openalex.org/W3089036501', 'https://openalex.org/W3047819467', 'https://openalex.org/W3028274337', 'https://openalex.org/W3013520558', 'https://openalex.org/W3012544498', 'https://openalex.org/W3006280584', 'https://openalex.org/W3004539325', 'https://openalex.org/W3001925456', 'https://openalex.org/W2996534163', 'https://openalex.org/W2993319764', 'https://openalex.org/W2989796175', 'https://openalex.org/W2084764058'], 'abstract_inverted_index': None, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W3081254653', 'counts_by_year': [{'year': 2020, 'cited_by_count': 2}], 'updated_date': '2024-08-20T01:31:09.118670', 'created_date': '2020-09-01'}