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10.5281/zenodo.7129964 | 10.5281/zenodo.7129964 | null | PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation | ConferencePaper | 2022-11-28 | null | [{"title":"PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation"}] | {"name":"Advances in Neural Information Processing Systems 35 (NeurIPS 2022)"} | 2022 | [{"date":"2022-11-28","dateType":"Issued"}] | [{"identifier":"arXiv:2212.07514","identifierType":"arXiv"}] | [{"relatedIdentifier":"10.5281/zenodo.7129965","relatedIdentifierType":"DOI","relationType":"HasVersion"}] | [] | [] | [{"description_type":"Abstract","field":"descriptions","field_index":0,"lang":null,"raw_text":"The promise of Mobile health (mHealth) is the ability to use wearable sensors to monitor a person's physiology at high frequencies during daily life to enable temporally-precise health interventions. However, a major challeng... | [] | cern.zenodo | cern | "https://zenodo.org/doi/10.5281/zenodo.7129964" | "findable" | "2022-10-12T03:03:10Z" | "2023-12-15T17:28:27Z" | "en" | dois/updated_2023-12/part_0026.jsonl.gz | 9,048 | [] | 2 | true | null | [{"char_end":173,"char_start":0,"chunk_prob":0.997285008430481,"description_type":"Other","detection_method":"cascade","field":"descriptions","field_index":1,"lang":null,"no_answer_prob":0.384765625,"source_text":"This work is supported in part by NIH P41-EB028242-01A1, NIH 7-R01-MD010362-03, and the National Science F... | [
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10.5281/zenodo.7129965 | 10.5281/zenodo.7129965 | null | PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation | ConferencePaper | 2022-11-28 | null | [{"title":"PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation"}] | {"name":"Advances in Neural Information Processing Systems 35 (NeurIPS 2022)"} | 2022 | [{"date":"2022-11-28","dateType":"Issued"}] | [{"identifier":"oai:zenodo.org:7129965","identifierType":"oai"},{"identifier":"arXiv:2212.07514","identifierType":"arXiv"}] | [{"relatedIdentifier":"10.5281/zenodo.7129964","relatedIdentifierType":"DOI","relationType":"IsVersionOf"}] | [] | [] | [{"description_type":"Abstract","field":"descriptions","field_index":0,"lang":null,"raw_text":"The promise of Mobile health (mHealth) is the ability to use wearable sensors to monitor a person's physiology at high frequencies during daily life to enable temporally-precise health interventions. However, a major challeng... | [] | cern.zenodo | cern | "https://zenodo.org/doi/10.5281/zenodo.7129965" | "findable" | "2022-10-12T03:03:09Z" | "2023-12-15T17:28:27Z" | "en" | dois/updated_2023-12/part_0026.jsonl.gz | 9,049 | [] | 2 | true | null | [{"char_end":173,"char_start":0,"chunk_prob":0.997285008430481,"description_type":"Other","detection_method":"cascade","field":"descriptions","field_index":1,"lang":null,"no_answer_prob":0.384765625,"source_text":"This work is supported in part by NIH P41-EB028242-01A1, NIH 7-R01-MD010362-03, and the National Science F... | [
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10.5281/zenodo.10392095 | 10.5281/zenodo.10392095 | null | Artificial Neural Networks-generated Dataset: pH, Total Alkalinity, and Hydrogen Ion Concentration in Ría de Vigo (NW Spain), 1995–2020 | Dataset | 2023-12-15 | null | [{"title":"Artificial Neural Networks-generated Dataset: pH, Total Alkalinity, and Hydrogen Ion Concentration in Ría de Vigo (NW Spain), 1995–2020"}] | {"name":"Zenodo"} | 2023 | [{"date":"2023-12-15","dateType":"Issued"}] | [] | [{"relatedIdentifier":"10.5281/zenodo.10392096","relatedIdentifierType":"DOI","relationType":"HasVersion"}] | [{"award_acronym":null,"award_id":null,"award_identifiers":[],"award_number":"IN606A-2022/025","award_program":null,"award_title":"Programa de axudas á etapa predoutoral da Xunta de Galicia","funder_id":"02vcxyt85","funder_name":"Axencia Galega de Innovacion"},{"award_acronym":null,"award_id":null,"award_identifiers":[... | [{"awardNumber":"IN606A-2022/025","awardTitle":"Programa de axudas á etapa predoutoral da Xunta de Galicia","funderIdentifier":"02vcxyt85","funderIdentifierType":"ROR","funderName":"Axencia Galega de Innovacion"},{"awardNumber":"TED2021-132188B-I00","awardTitle":"REDEIRA","funderIdentifier":"05r0vyz12","funderIdentifie... | [{"description_type":"Abstract","field":"descriptions","field_index":0,"lang":null,"raw_text":"This dataset comprises input data from INTECMAR and the predicted outcomes. The variables and their units are as follows:\n\nstation: 'Station ID [1-6]'\n\nyear: 'Year [1995-2020]'\n\nmonth: 'Month [1-12]'\n\nday: 'Day'\n\nla... | [] | cern.zenodo | cern | "https://zenodo.org/doi/10.5281/zenodo.10392095" | "findable" | "2023-12-15T17:56:28Z" | "2023-12-15T17:56:28Z" | null | dois/updated_2023-12/part_0026.jsonl.gz | 9,223 | [] | 1 | true | null | [{"char_end":1128,"char_start":832,"chunk_prob":0.9969245791435242,"description_type":"Abstract","detection_method":"cascade","field":"descriptions","field_index":0,"lang":null,"no_answer_prob":0.02978515625,"source_text":"This dataset comprises input data from INTECMAR and the predicted outcomes. The variables and the... | [
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10.5281/zenodo.10392096 | 10.5281/zenodo.10392096 | null | Artificial Neural Networks-generated Dataset: pH, Total Alkalinity, and Hydrogen Ion Concentration in Ría de Vigo (NW Spain), 1995–2020 | Dataset | 2023-12-15 | null | [{"title":"Artificial Neural Networks-generated Dataset: pH, Total Alkalinity, and Hydrogen Ion Concentration in Ría de Vigo (NW Spain), 1995–2020"}] | {"name":"Zenodo"} | 2023 | [{"date":"2023-12-15","dateType":"Issued"}] | [{"identifier":"oai:zenodo.org:10392096","identifierType":"oai"}] | [{"relatedIdentifier":"10.5281/zenodo.10392095","relatedIdentifierType":"DOI","relationType":"IsVersionOf"}] | [{"award_acronym":null,"award_id":null,"award_identifiers":[],"award_number":"IN606A-2022/025","award_program":null,"award_title":"Programa de axudas á etapa predoutoral da Xunta de Galicia","funder_id":"02vcxyt85","funder_name":"Axencia Galega de Innovacion"},{"award_acronym":null,"award_id":null,"award_identifiers":[... | [{"awardNumber":"IN606A-2022/025","awardTitle":"Programa de axudas á etapa predoutoral da Xunta de Galicia","funderIdentifier":"02vcxyt85","funderIdentifierType":"ROR","funderName":"Axencia Galega de Innovacion"},{"awardNumber":"TED2021-132188B-I00","awardTitle":"REDEIRA","funderIdentifier":"05r0vyz12","funderIdentifie... | [{"description_type":"Abstract","field":"descriptions","field_index":0,"lang":null,"raw_text":"This dataset comprises input data from INTECMAR and the predicted outcomes. The variables and their units are as follows:\n\nstation: 'Station ID [1-6]'\n\nyear: 'Year [1995-2020]'\n\nmonth: 'Month [1-12]'\n\nday: 'Day'\n\nla... | [] | cern.zenodo | cern | "https://zenodo.org/doi/10.5281/zenodo.10392096" | "findable" | "2023-12-15T17:56:28Z" | "2023-12-15T17:56:28Z" | null | dois/updated_2023-12/part_0026.jsonl.gz | 9,224 | [] | 1 | true | null | [{"char_end":1128,"char_start":832,"chunk_prob":0.9969245791435242,"description_type":"Abstract","detection_method":"cascade","field":"descriptions","field_index":0,"lang":null,"no_answer_prob":0.02978515625,"source_text":"This dataset comprises input data from INTECMAR and the predicted outcomes. The variables and the... | [
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10.5281/zenodo.10392420 | 10.5281/zenodo.10392420 | null | Corona speeches mini corpus | Dataset | 2023-12-15 | null | [{"title":"Corona speeches mini corpus"}] | {"name":"Zenodo"} | 2023 | [{"date":"2023-12-15","dateType":"Issued"}] | [] | [{"relatedIdentifier":"10.5281/zenodo.10392421","relatedIdentifierType":"DOI","relationType":"HasVersion"}] | [{"award_acronym":null,"award_id":null,"award_identifiers":[],"award_number":"281511265","award_program":null,"award_title":"Collaborative Research Center 1252 Prominence in Language","funder_id":"018mejw64","funder_name":"Deutsche Forschungsgemeinschaft"}] | [{"awardNumber":"281511265","awardTitle":"Collaborative Research Center 1252 Prominence in Language","funderIdentifier":"018mejw64","funderIdentifierType":"ROR","funderName":"Deutsche Forschungsgemeinschaft"}] | [{"description_type":"Abstract","field":"descriptions","field_index":0,"lang":null,"raw_text":"This data collection (mini corpus) collects fifteen speeches of three speakers, Emmanuel Macron, Pedro Sánchez, and Angela Merkel, with five speeches per speaker. Four of their speeches are from between March and June, 2020, ... | [] | cern.zenodo | cern | "https://zenodo.org/doi/10.5281/zenodo.10392420" | "findable" | "2023-12-15T18:19:54Z" | "2023-12-15T18:19:54Z" | null | dois/updated_2023-12/part_0026.jsonl.gz | 9,349 | [] | 2 | true | null | [{"char_end":256,"char_start":30,"chunk_prob":0.9919379353523254,"description_type":"Other","detection_method":"cascade","field":"descriptions","field_index":1,"lang":null,"no_answer_prob":0.1328125,"source_text":"Funding and acknowledgements\n\nThe research was funded by the Deutsche Forschungsgemeinschaft (DFG, Germa... | [
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1425.9592929738574
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194
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10.5281/zenodo.10392421 | 10.5281/zenodo.10392421 | null | Corona speeches mini corpus | Dataset | 2023-12-15 | null | [{"title":"Corona speeches mini corpus"}] | {"name":"Zenodo"} | 2023 | [{"date":"2023-12-15","dateType":"Issued"}] | [{"identifier":"oai:zenodo.org:10392421","identifierType":"oai"}] | [{"relatedIdentifier":"10.5281/zenodo.10392420","relatedIdentifierType":"DOI","relationType":"IsVersionOf"}] | [{"award_acronym":null,"award_id":null,"award_identifiers":[],"award_number":"281511265","award_program":null,"award_title":"Collaborative Research Center 1252 Prominence in Language","funder_id":"018mejw64","funder_name":"Deutsche Forschungsgemeinschaft"}] | [{"awardNumber":"281511265","awardTitle":"Collaborative Research Center 1252 Prominence in Language","funderIdentifier":"018mejw64","funderIdentifierType":"ROR","funderName":"Deutsche Forschungsgemeinschaft"}] | [{"description_type":"Abstract","field":"descriptions","field_index":0,"lang":null,"raw_text":"This data collection (mini corpus) collects fifteen speeches of three speakers, Emmanuel Macron, Pedro Sánchez, and Angela Merkel, with five speeches per speaker. Four of their speeches are from between March and June, 2020, ... | [] | cern.zenodo | cern | "https://zenodo.org/doi/10.5281/zenodo.10392421" | "findable" | "2023-12-15T18:19:54Z" | "2023-12-15T18:19:54Z" | null | dois/updated_2023-12/part_0026.jsonl.gz | 9,350 | [] | 2 | true | null | [{"char_end":256,"char_start":30,"chunk_prob":0.9919379353523254,"description_type":"Other","detection_method":"cascade","field":"descriptions","field_index":1,"lang":null,"no_answer_prob":0.1328125,"source_text":"Funding and acknowledgements\n\nThe research was funded by the Deutsche Forschungsgemeinschaft (DFG, Germa... | [
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194
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End of preview. Expand in Data Studio
DataCite candidate funding release
Private release from the September 2026 DataCite source. The upstream corpus contains 136,014,694 records. Its description pattern screen selected 795,879 source rows. Models examine those candidates, and this release retains statement-positive source rows. Records and DOIs are not deduplicated.
This run classified 795,879 rows from a published input of 795,879 rows; exported 178,390 positives and retained 617,489 negatives in durable classification checkpoints. Smoke selection: False.
record_json preserves the complete imported parser record and namespaced candidate evidence. Original funding and funding_references are separate from extracted_funders predictions. Statements include original description indices, language/type provenance, and offsets in the normalized source_text. Template fallback has null chunk and no-answer probabilities. Original parser errors remain in record_json and errors.
Extraction arrays align with statement order. Successful empty lists, funder-bearing responses, ParseError and InputTooLong terminal errors are reported per statement. Counts in coverage.json report rows, structured-funding entries, and statement outcomes by original funding group and client; these are not counts of unique cached requests.
Pinned models:
- base: meta-llama/Llama-3.1-8B-Instruct at 0e9e39f249a16976918f6564b8830bc894c89659
- chunk: cometadata/funding-chunk-classifier-modernbert-base at f69ad93c22f3b7e76544eb8fe15ba4af69cd1f2e
- lora: cometadata/funding-extraction-llama-3.1-8b-instruct-artifact-data-mix-grpo-mixed-reward at 5a2696f6422ac5ecab8d2b474ad58e1d934a3e66
- mb: answerdotai/ModernBERT-base at 8949b909ec900327062f0ebf497f51aef5e6f0c8
- span: cometadata/funding-extraction-modernbert-base-spanhead at 1e00313fe334fbe8ef93f48e17db3a7be6456789
Load the private dataset configuration 202609-candidates-20261012T023436Z-d784b3-enrichment at the exact published commit. The root card declares the release-specific Parquet loading paths.
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