{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:HFAJ3JUYFF3672Y4ZY24EWM6MP","short_pith_number":"pith:HFAJ3JUY","schema_version":"1.0","canonical_sha256":"39409da6982977efeb1cce35c2599e63d15c45dc0d6425fd3caab9541212a2b8","source":{"kind":"arxiv","id":"2402.00438","version":1},"attestation_state":"computed","paper":{"title":"The GREENBOT dataset: Multimodal mobile robotic dataset for a typical Mediterranean greenhouse","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Fernando Ca\\~nadas-Ar\\'anega, Francisco Rodriguez, Jose Carlos Moreno, Jose Luis Blanco-Claraco","submitted_at":"2024-02-01T09:08:29Z","abstract_excerpt":"This paper introduces an innovative dataset specifically crafted for challenging agricultural settings (a greenhouse), where achieving precise localization is of paramount importance. The dataset was gathered using a mobile platform equipped with a set of sensors typically used in mobile robots, as it was moved through all the corridors of a typical Mediterranean greenhouse featuring tomato crop. This dataset presents a unique opportunity for constructing detailed 3D models of plants in such indoor-like space, with potential applications such as robotized spraying. For the first time to the be"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2402.00438","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2024-02-01T09:08:29Z","cross_cats_sorted":[],"title_canon_sha256":"40423bcfb3fb4e9d2744208e4c6a9e8d3c8fc4ebccd1a32e40bdd6a16561ae3a","abstract_canon_sha256":"d257979f388c8a8585a2213e58e3afdcb7a485f5fd29236c20253c4b9a16f64a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:56:20.778528Z","signature_b64":"eXZsyDPh572MI76KiRpDFcrGIMBzNvUIBdMPMBvhqMHQXWNZ3iX7THs0OCRUZx6BL5MFUrgN89vye4x1NXbNBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"39409da6982977efeb1cce35c2599e63d15c45dc0d6425fd3caab9541212a2b8","last_reissued_at":"2026-07-05T07:56:20.777908Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:56:20.777908Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The GREENBOT dataset: Multimodal mobile robotic dataset for a typical Mediterranean greenhouse","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Fernando Ca\\~nadas-Ar\\'anega, Francisco Rodriguez, Jose Carlos Moreno, Jose Luis Blanco-Claraco","submitted_at":"2024-02-01T09:08:29Z","abstract_excerpt":"This paper introduces an innovative dataset specifically crafted for challenging agricultural settings (a greenhouse), where achieving precise localization is of paramount importance. The dataset was gathered using a mobile platform equipped with a set of sensors typically used in mobile robots, as it was moved through all the corridors of a typical Mediterranean greenhouse featuring tomato crop. This dataset presents a unique opportunity for constructing detailed 3D models of plants in such indoor-like space, with potential applications such as robotized spraying. For the first time to the be"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00438","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/2402.00438/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2402.00438","created_at":"2026-07-05T07:56:20.777973+00:00"},{"alias_kind":"arxiv_version","alias_value":"2402.00438v1","created_at":"2026-07-05T07:56:20.777973+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00438","created_at":"2026-07-05T07:56:20.777973+00:00"},{"alias_kind":"pith_short_12","alias_value":"HFAJ3JUYFF36","created_at":"2026-07-05T07:56:20.777973+00:00"},{"alias_kind":"pith_short_16","alias_value":"HFAJ3JUYFF3672Y4","created_at":"2026-07-05T07:56:20.777973+00:00"},{"alias_kind":"pith_short_8","alias_value":"HFAJ3JUY","created_at":"2026-07-05T07:56:20.777973+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HFAJ3JUYFF3672Y4ZY24EWM6MP","json":"https://pith.science/pith/HFAJ3JUYFF3672Y4ZY24EWM6MP.json","graph_json":"https://pith.science/api/pith-number/HFAJ3JUYFF3672Y4ZY24EWM6MP/graph.json","events_json":"https://pith.science/api/pith-number/HFAJ3JUYFF3672Y4ZY24EWM6MP/events.json","paper":"https://pith.science/paper/HFAJ3JUY"},"agent_actions":{"view_html":"https://pith.science/pith/HFAJ3JUYFF3672Y4ZY24EWM6MP","download_json":"https://pith.science/pith/HFAJ3JUYFF3672Y4ZY24EWM6MP.json","view_paper":"https://pith.science/paper/HFAJ3JUY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2402.00438&json=true","fetch_graph":"https://pith.science/api/pith-number/HFAJ3JUYFF3672Y4ZY24EWM6MP/graph.json","fetch_events":"https://pith.science/api/pith-number/HFAJ3JUYFF3672Y4ZY24EWM6MP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HFAJ3JUYFF3672Y4ZY24EWM6MP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HFAJ3JUYFF3672Y4ZY24EWM6MP/action/storage_attestation","attest_author":"https://pith.science/pith/HFAJ3JUYFF3672Y4ZY24EWM6MP/action/author_attestation","sign_citation":"https://pith.science/pith/HFAJ3JUYFF3672Y4ZY24EWM6MP/action/citation_signature","submit_replication":"https://pith.science/pith/HFAJ3JUYFF3672Y4ZY24EWM6MP/action/replication_record"}},"created_at":"2026-07-05T07:56:20.777973+00:00","updated_at":"2026-07-05T07:56:20.777973+00:00"}