{"as_of":"2026-08-15T03:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d2392c944c0df9cec63869bd2785749488e5bacb3ab59b2307da10b78fbadda4","coverage":[{"denominator":16,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T13:27:41.272230Z","state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2508.00898/citation-record","integrity":"/paper/2508.00898/integrity","json":"/paper/2508.00898/citation-record.json","paper":"/paper/2508.00898"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:43.505709Z","title":"Sánchez Velázquez1, Mingbo Cai2, 3, Andrew Coney1, Álvaro J","venue":null,"work_id":"120e9ef5-9ec9-46cc-bef7-3004fadd4318","year":2018},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.223663Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:2ab5ee235b773f37b9911ae93a2fc739ea1e4e20f1aad988a55bdb05cbfc0e6a","observation_id":"af3774e1-b47b-4b0e-bb0a-d5475f29422d","resolution":{"observed_at":"2026-08-06T13:27:43.695896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.496298Z","title":"This observation aligns with the bias-variance trade-off, as described by (Belkin et al., 2019)","venue":null,"work_id":"1364f24e-9924-48fe-9b35-da58687cf546","year":2019},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.256446Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:b4b7d4fa1cc94e3b27801abe9bcc8293d84b82da934d9b3ae526caa3cea15923","observation_id":"9fe6f95a-43a7-47cf-a96c-d7c3a6b68fef","resolution":{"observed_at":"2026-08-06T13:27:41.502582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:42.970303Z","title":"2 Related works This paper aims to evaluate hybrid Deep Learning models for video frame predic-tion","venue":null,"work_id":"d821fb8d-ec66-41eb-b7f5-50300478e546","year":2013},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.231202Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:24cd371159653c79f0b9c1820334d6a8754f0b5b6ff7dfbe65970a072e773af3","observation_id":"69abe739-0a59-481d-bf22-40a8438c5fee","resolution":{"observed_at":"2026-08-06T13:27:43.102341Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:42.108853Z","title":"As can be seen in the previous Figure, the workflow implies different Deep Learning models that are defined as follows","venue":null,"work_id":"f5244e6e-43d1-4beb-b106-c7a9f4fc92d4","year":1987},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.240790Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:a6828fc4d31010c8518288d324b3c7c2f3d7083a57dd288ac1207d3c868bbb16","observation_id":"7b7922e6-44b0-4f5e-bad9-9878fa653b74","resolution":{"observed_at":"2026-08-06T13:27:42.263461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.478148Z","title":"excellent prediction","venue":null,"work_id":"af520982-4366-40aa-8e4f-93ffac04797d","year":1931},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.260257Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:9eab6ced5ced4830172e8aa437f13e52db91be9067f84910472ff9929b5d2d69","observation_id":"1099aa3e-361a-450a-be48-b85399e8835f","resolution":{"observed_at":"2026-08-06T13:27:41.486305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.648776Z","title":"∑(𝑦#− ŷ#)%","venue":null,"work_id":"8ac017bd-8fb3-4b58-9c27-cd68a2327eda","year":2004},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.250502Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:ecc1aebcb3af08597ab90683518a418a74c33fc9dd2058e9d90cc6aae01c5054","observation_id":"3e4704ef-ae6a-4c5c-a040-3615ccea5f33","resolution":{"observed_at":"2026-08-06T13:27:41.738490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.514991Z","title":"First, before training the models, the creation of the training, validation, and test subsets is needed","venue":null,"work_id":"84f8c903-6a49-438c-bec9-85dcbcb7c506","year":2012},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.253405Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:aa6c002b094c4719fd760bb5d421bb3d43980b515bd64ee1a75da859a57470e8","observation_id":"44144c3c-77ed-4a1c-829f-9d451648ecbe","resolution":{"observed_at":"2026-08-06T13:27:41.545804Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.456456Z","title":null,"venue":null,"work_id":"edb64ebf-25a1-45c9-8934-98e4be8c14eb","year":2025},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.263345Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:a06af110d536868856a6b627f1dc1c34492bbb50d06c38fc6bfcbae035101cb9","observation_id":"4651710e-f1f2-4ab9-87c7-857b8b784767","resolution":{"observed_at":"2026-08-06T13:27:41.466348Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.432475Z","title":"This significant reduction trans-lates directly into a smaller carbon footprint and longer battery life when the models are deployed on embedded or edge devices","venue":null,"work_id":"a5a96f17-21ff-490d-92d2-c0cc3fbb64d1","year":2024},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.266237Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:8d5523b407584d90a19a5b6fdec3d89cd3181a5853ec44e2f83f509f1db17faa","observation_id":"8a4eea92-e932-4668-8930-aad5677cda4a","resolution":{"observed_at":"2026-08-06T13:27:41.442151Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.272230Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.272230Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:d2a04e8d636e04c9422c69aa235a57447266d1d311fb7ce761c0311a60dd8c39","observation_id":"05777608-911b-4b66-8907-d9871a267be5","resolution":{"observed_at":"2026-08-06T13:27:41.272230Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.269296Z","title":"V., Al-Shehari, T., Alsadhan, N","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":846,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.269296Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:2876523c952858d34443482e15dba5ce81fd537a6a8d9c2df42a7693f6ddaff3","observation_id":"554a6c8a-4632-4f44-96a9-6a6e23a2183d","resolution":{"observed_at":"2026-08-06T13:27:41.269296Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.959236Z","title":"Regarding (Kemal Pola & Saban Öztürk, 2023), GRUs simplify the internal structure of LSTM cells by reducing the number of gates, thereby decreasing the model's time complexity","venue":null,"work_id":"19c85c77-59cb-4880-b0ed-fb09e8cee391","year":2023},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.244180Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:e170fb22336bd38449a2d090672fb4bf6d8ce0c81389920f74afde0e74d21fd3","observation_id":"ed4b7bee-44a1-4cd0-b9f0-5994ac61d11d","resolution":{"observed_at":"2026-08-06T13:27:42.044108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:41.800238Z","title":"∑∣𝑦#− ŷ#∣","venue":null,"work_id":"c6bd098c-92d2-4728-b1d9-f754b6b5cdd3","year":2019},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.247220Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:acba348124860c3b028d2d0c0783ed6be0af53ac8f2eb68a41e36fdbd04e94e3","observation_id":"c2c4544d-6e07-4867-9b16-3823735a149d","resolution":{"observed_at":"2026-08-06T13:27:41.870473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:42.399361Z","title":null,"venue":null,"work_id":"0ace8556-53c7-48b0-8619-d28b66ac81ed","year":2024},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.237517Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:049459e708d3fe0415562e552c10fbd41997691f1211be66bf5578253660c8d2","observation_id":"7d7d421e-6c20-4051-a6b7-26312647d4aa","resolution":{"observed_at":"2026-08-06T13:27:42.579716Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:42.708569Z","title":"They find that the ConvLSTM model, which explicitly captures temporal and spatial patterns, outperforms GANs in predicting fu-ture frames","venue":null,"work_id":"4a9060dc-f0cc-4e63-853b-64ff8390f3d4","year":2022},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.234278Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:c2d7d05ada191589517f79254281c5619805cedf7273ac2dd182b0dbe37fdf00","observation_id":"406af1d9-9be7-4dea-a8e5-7c3f8f07409b","resolution":{"observed_at":"2026-08-06T13:27:42.818635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:27:43.231463Z","title":null,"venue":null,"work_id":"938abb8e-43d1-4610-a8d7-bb93fa008d45","year":2012},"citing_paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T13:27:41.227675Z"},"links":{"citing_paper":"/paper/2508.00898"},"observation_digest":"sha256:06739bdb18f8740718dcc491519fdb5a7a710e310bfa2d9723247b76157ab870","observation_id":"c5350249-2d5f-41e5-a7c1-13a36a74ecb4","resolution":{"observed_at":"2026-08-06T13:27:43.349950Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.00898","last_updated":"2025-07-28T10:07:00Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-06T13:27:40.013890Z","submitted_at":"2025-07-28T10:07:00Z","title":"Benefits of Feature Extraction and Temporal Sequence Analysis for Video Frame Prediction: An Evaluation of Hybrid Deep Learning Models"},"reference_resolution":{"displayed":16,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":0,"verified_fuzzy":11},"total_outbound_references":16},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2508.00898."}