{"meta": {"count": 856, "db_response_time_ms": 58, "page": 1, "per_page": 3, "groups_count": null, "x_query": {"oql": "works where full text has (Matbench Discovery)", "oqo": {"get_rows": "works", "filter_rows": [{"column_id": "fulltext.search", "value": "Matbench Discovery", "operator": "has"}]}, "url": "/works?filter=fulltext.search:Matbench Discovery&per_page=3"}, "cost_usd": 0.001}, "results": [{"title": "Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions", "publication_year": 2023, "primary_location": {"id": "pmh:oai:arXiv.org:2308.14920", "is_oa": true, "landing_page_url": "http://arxiv.org/abs/2308.14920", "pdf_url": "https://arxiv.org/pdf/2308.14920", "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": "cc-by", "license_id": "https://openalex.org/licenses/cc-by", "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": null, "raw_type": "text"}, "doi": "https://doi.org/10.48550/arxiv.2308.14920"}, {"title": "Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm", "publication_year": 2020, "primary_location": {"id": "doi:10.1038/s41524-020-00406-3", "is_oa": true, "landing_page_url": "https://doi.org/10.1038/s41524-020-00406-3", "pdf_url": "https://www.nature.com/articles/s41524-020-00406-3.pdf", "source": {"id": "https://openalex.org/S4210232664", "display_name": "npj Computational Materials", "issn_l": "2057-3960", "issn": ["2057-3960"], "is_oa": true, "is_in_doaj": true, "is_core": true, "host_organization": "https://openalex.org/P4310319908", "host_organization_name": "Nature Portfolio", "host_organization_lineage": ["https://openalex.org/P4310319908", "https://openalex.org/P4310319965"], "host_organization_lineage_names": ["Nature Portfolio", "Springer Nature"], "type": "journal"}, "license": "cc-by", "license_id": "https://openalex.org/licenses/cc-by", "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "npj Computational Materials", "raw_type": "journal-article"}, "doi": "https://doi.org/10.1038/s41524-020-00406-3"}, {"title": "A framework to evaluate machine learning crystal stability predictions", "publication_year": 2025, "primary_location": {"id": "doi:10.1038/s42256-025-01055-1", "is_oa": true, "landing_page_url": "https://doi.org/10.1038/s42256-025-01055-1", "pdf_url": "https://www.nature.com/articles/s42256-025-01055-1.pdf", "source": {"id": "https://openalex.org/S2912241403", "display_name": "Nature Machine Intelligence", "issn_l": "2522-5839", "issn": ["2522-5839"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319908", "host_organization_name": "Nature Portfolio", "host_organization_lineage": ["https://openalex.org/P4310319908", "https://openalex.org/P4310319965"], "host_organization_lineage_names": ["Nature Portfolio", "Springer Nature"], "type": "journal"}, "license": "cc-by", "license_id": "https://openalex.org/licenses/cc-by", "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Nature Machine Intelligence", "raw_type": "journal-article"}, "doi": "https://doi.org/10.1038/s42256-025-01055-1"}], "group_by": []}