{"paper":{"title":"A multi-modal dataset for insect biodiversity with imagery and DNA at the trap and individual level","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Akshita Gupta, Amlan Kar, Amy Thompson, Arielle Farrell, Bess Hardwick, Brendan Furneaux, Deirdre Kerdraon, Ellen Nein, Erik Kristensen, Evgeny V. Zakharov, Gaia Banelyte, Graham W. Taylor, Hanna Rogers, Hannu Autto, Iuliia Zarubiieva, Jaclyn McKeown, Jayme Sones, Jeremy deWaard, Johanna Orsholm, John Quinto, Maija Sujala, Nao Ito, Nicolas Chazot, Oula Kalttop\\\"a\\\"a, Paula Schmitz, Scott C. Lowe, Stephanie deWaard, Tomas Roslin, Tommi Mononen","submitted_at":"2025-07-09T16:03:06Z","abstract_excerpt":"Insects comprise millions of species, many experiencing severe population declines under environmental and habitat changes. High-throughput approaches are crucial for accelerating our understanding of insect diversity, with DNA barcoding and high-resolution imaging showing strong potential for automatic taxonomic classification. However, most image-based approaches rely on individual specimen data, unlike the unsorted bulk samples collected in large-scale ecological surveys. We present the Mixed Arthropod Sample Segmentation and Identification (MassID45) dataset for training automatic classifi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.06972","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.06972/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}