{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:7KLAX5I7DIM26YTMPPIFVLOLWE","short_pith_number":"pith:7KLAX5I7","canonical_record":{"source":{"id":"2108.03320","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-08-06T22:25:46Z","cross_cats_sorted":[],"title_canon_sha256":"695b4703fd0ec45199a1557bb36c309050a4d33679589ccc2a972dd270d06015","abstract_canon_sha256":"f01bd3b8cefa23eba9ce846d12712b3b6b013136ab5007f904b24b2aa6469d36"},"schema_version":"1.0"},"canonical_sha256":"fa960bf51f1a19af626c7bd05aadcbb1096d30b06e4c5cc1c57f3efae76eaf0c","source":{"kind":"arxiv","id":"2108.03320","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.03320","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"arxiv_version","alias_value":"2108.03320v1","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.03320","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"pith_short_12","alias_value":"7KLAX5I7DIM2","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"pith_short_16","alias_value":"7KLAX5I7DIM26YTM","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"pith_short_8","alias_value":"7KLAX5I7","created_at":"2026-07-05T03:03:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:7KLAX5I7DIM26YTMPPIFVLOLWE","target":"record","payload":{"canonical_record":{"source":{"id":"2108.03320","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-08-06T22:25:46Z","cross_cats_sorted":[],"title_canon_sha256":"695b4703fd0ec45199a1557bb36c309050a4d33679589ccc2a972dd270d06015","abstract_canon_sha256":"f01bd3b8cefa23eba9ce846d12712b3b6b013136ab5007f904b24b2aa6469d36"},"schema_version":"1.0"},"canonical_sha256":"fa960bf51f1a19af626c7bd05aadcbb1096d30b06e4c5cc1c57f3efae76eaf0c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:03:51.665076Z","signature_b64":"AVAHy+niYzYrtnizptLK5UUq67YSDyfnZ/PaVRXOiVZxFtWY5fIEzWo70QsKAxzNjR4qD3U29oKfRtwqFZwsCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa960bf51f1a19af626c7bd05aadcbb1096d30b06e4c5cc1c57f3efae76eaf0c","last_reissued_at":"2026-07-05T03:03:51.664591Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:03:51.664591Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2108.03320","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:03:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rnLpk9gTztnejs6TKz2GjP8Ux+3QcuBwXc13clq4tYbHKgPqGCt8WYTa/dUdOBOmPY4DctL6M+rRezYLyrzMAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T17:48:01.307628Z"},"content_sha256":"fc987263f66bcd55e67e6327ac306a9b697314801a2c3d1573698aa9f852a70e","schema_version":"1.0","event_id":"sha256:fc987263f66bcd55e67e6327ac306a9b697314801a2c3d1573698aa9f852a70e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:7KLAX5I7DIM26YTMPPIFVLOLWE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Deep Neural Network Approach for Crop Selection and Yield Prediction in Bangladesh","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Amitabha Chakrabarty, Tanhim Islam, Tanjir Alam Chisty","submitted_at":"2021-08-06T22:25:46Z","abstract_excerpt":"Agriculture is the essential ingredients to mankind which is a major source of livelihood. Agriculture work in Bangladesh is mostly done in old ways which directly affects our economy. In addition, institutions of agriculture are working with manual data which cannot provide a proper solution for crop selection and yield prediction. This paper shows the best way of crop selection and yield prediction in minimum cost and effort. Artificial Neural Network is considered robust tools for modeling and prediction. This algorithm aims to get better output and prediction, as well as, support vector ma"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.03320","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/2108.03320/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:03:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NkxvEBUuMuoBrfZ4Kk0Dxx5GBHH0KXs/q7jGDCJMO8Zx+S2Xbm12w/PrUvUWDvqRKETZp2bQOJaImfnoZrOTCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T17:48:01.307998Z"},"content_sha256":"2d6a6c4e7c49da498dcbd3b237ae198a1224a48a3d5b44347f9f98166630f2af","schema_version":"1.0","event_id":"sha256:2d6a6c4e7c49da498dcbd3b237ae198a1224a48a3d5b44347f9f98166630f2af"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7KLAX5I7DIM26YTMPPIFVLOLWE/bundle.json","state_url":"https://pith.science/pith/7KLAX5I7DIM26YTMPPIFVLOLWE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7KLAX5I7DIM26YTMPPIFVLOLWE/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-17T17:48:01Z","links":{"resolver":"https://pith.science/pith/7KLAX5I7DIM26YTMPPIFVLOLWE","bundle":"https://pith.science/pith/7KLAX5I7DIM26YTMPPIFVLOLWE/bundle.json","state":"https://pith.science/pith/7KLAX5I7DIM26YTMPPIFVLOLWE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7KLAX5I7DIM26YTMPPIFVLOLWE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:7KLAX5I7DIM26YTMPPIFVLOLWE","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"f01bd3b8cefa23eba9ce846d12712b3b6b013136ab5007f904b24b2aa6469d36","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-08-06T22:25:46Z","title_canon_sha256":"695b4703fd0ec45199a1557bb36c309050a4d33679589ccc2a972dd270d06015"},"schema_version":"1.0","source":{"id":"2108.03320","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.03320","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"arxiv_version","alias_value":"2108.03320v1","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.03320","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"pith_short_12","alias_value":"7KLAX5I7DIM2","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"pith_short_16","alias_value":"7KLAX5I7DIM26YTM","created_at":"2026-07-05T03:03:51Z"},{"alias_kind":"pith_short_8","alias_value":"7KLAX5I7","created_at":"2026-07-05T03:03:51Z"}],"graph_snapshots":[{"event_id":"sha256:2d6a6c4e7c49da498dcbd3b237ae198a1224a48a3d5b44347f9f98166630f2af","target":"graph","created_at":"2026-07-05T03:03:51Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2108.03320/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Agriculture is the essential ingredients to mankind which is a major source of livelihood. Agriculture work in Bangladesh is mostly done in old ways which directly affects our economy. In addition, institutions of agriculture are working with manual data which cannot provide a proper solution for crop selection and yield prediction. This paper shows the best way of crop selection and yield prediction in minimum cost and effort. Artificial Neural Network is considered robust tools for modeling and prediction. This algorithm aims to get better output and prediction, as well as, support vector ma","authors_text":"Amitabha Chakrabarty, Tanhim Islam, Tanjir Alam Chisty","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-08-06T22:25:46Z","title":"A Deep Neural Network Approach for Crop Selection and Yield Prediction in Bangladesh"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.03320","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:fc987263f66bcd55e67e6327ac306a9b697314801a2c3d1573698aa9f852a70e","target":"record","created_at":"2026-07-05T03:03:51Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"f01bd3b8cefa23eba9ce846d12712b3b6b013136ab5007f904b24b2aa6469d36","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-08-06T22:25:46Z","title_canon_sha256":"695b4703fd0ec45199a1557bb36c309050a4d33679589ccc2a972dd270d06015"},"schema_version":"1.0","source":{"id":"2108.03320","kind":"arxiv","version":1}},"canonical_sha256":"fa960bf51f1a19af626c7bd05aadcbb1096d30b06e4c5cc1c57f3efae76eaf0c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa960bf51f1a19af626c7bd05aadcbb1096d30b06e4c5cc1c57f3efae76eaf0c","first_computed_at":"2026-07-05T03:03:51.664591Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:03:51.664591Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AVAHy+niYzYrtnizptLK5UUq67YSDyfnZ/PaVRXOiVZxFtWY5fIEzWo70QsKAxzNjR4qD3U29oKfRtwqFZwsCg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:03:51.665076Z","signed_message":"canonical_sha256_bytes"},"source_id":"2108.03320","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fc987263f66bcd55e67e6327ac306a9b697314801a2c3d1573698aa9f852a70e","sha256:2d6a6c4e7c49da498dcbd3b237ae198a1224a48a3d5b44347f9f98166630f2af"],"state_sha256":"48638e33b9e7e9ef52ffd8f26d247f147c6c824198729c4706eaefbc8bbaf3a6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mmZQj+9I1NFtKPy/om/DoG/Kuriq2pXGsEwkxoYZUJxAz6VQNNj3BYifcHhj8tSRrVZN3MgrDosFHAwJedYdCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-17T17:48:01.310222Z","bundle_sha256":"ab8e8b17c550b01c51576c8d58ba489c9a08b3e9d8f439f9f3977538af2287af"}}