cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7805/ies-suf-2018-v1
title: ifo Education Survey (2018) - SUF
title: ifo Bildungsbarometer (2018) - SUF

description: The ifo Education Survey is an annual representative public opinion poll which surveys the adult German population since 2014. The ifo Education Survey covers a wide range of topics such as pre-school education, schools, vocational training and tertiary education. The data collection was funded through the project “The political economy of education policy: Insights from a public opinion survey” of the Leibniz Association.
description: Das ifo Bildungsbarometer ist eine jährliche repräsentative Meinungsumfrage, die seit 2014 die erwachsene Bevölkerung in Deutschland befragt. Die Befragung umfasst ein breites Spektrum an bildungspolitischen Themen, vom vorschulischen Alter über Schulen und Berufsausbildung bis hin zu Studium und Weiterbildung. Die Befragungen des ifo Bildungsbarometer wurden durch die Deutsche Forschungsgemeinschaft (Sonderforschungsbereich Transregio 190) und die Leibniz Gemeinschaft (Leibniz-Wettbewerb SAW-2014-ifo-2) finanziell unterstützt.
description: Self-administered questionnaire
description: Erwachsene (N=4046), Jugendliche (N=1085)
description: Erwachsene (N=4046), Jugendliche (N=1085)
description: Nicht-Wahrscheinlichkeitsauswahl: Quotenstichprobe
DOI: 10.60712/si-id351887.1
title: StrainInfo SI-ID 351887.1

description: StrainInfo dataset 351887 about a strain of Perkinsus marinus. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id351888.1
title: StrainInfo SI-ID 351888.1

description: StrainInfo dataset 351888 about a strain of Encephalitozoon cuniculi. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id351889.1
title: StrainInfo SI-ID 351889.1

description: StrainInfo dataset 351889 about a strain of Trypanosoma cruzi. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.15468/dl.z8nzgs
title: Occurrence Download

description: A dataset containing 465 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Amblyomma americanum Linnaeus, 1758"
 ]
}

 The dataset includes 465 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001745-180920211646547/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60712/si-id351890.1
title: StrainInfo SI-ID 351890.1

description: StrainInfo dataset 351890 about a strain of Trypanosoma cruzi. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.15468/dl.qe9qym
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ophrys aesculapii Renz"
 ]
}

 The dataset includes 14 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008160-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60712/si-id351775.1
title: StrainInfo SI-ID 351775.1

description: StrainInfo dataset 351775 about a strain of Acanthamoeba pustulosa. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id351776.1
title: StrainInfo SI-ID 351776.1

description: StrainInfo dataset 351776 about a strain of Unidentified. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id351777.1
title: StrainInfo SI-ID 351777.1

description: StrainInfo dataset 351777 about a strain of Mayorella. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id351778.1
title: StrainInfo SI-ID 351778.1

description: StrainInfo dataset 351778 about a strain of Aristerostoma. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.7805/ies-suf-2019-v1
title: ifo Education Survey (2019) - SUF
title: ifo Bildungsbarometer (2019) - SUF

description: The ifo Education Survey is an annual representative public opinion poll which surveys the adult German population since 2014. The ifo Education Survey covers a wide range of topics such as pre-school education, schools, vocational training and tertiary education. The data collection was funded through the project “The political economy of education policy: Insights from a public opinion survey” of the Leibniz Association.
description: Das ifo Bildungsbarometer ist eine jährliche repräsentative Meinungsumfrage, die seit 2014 die erwachsene Bevölkerung in Deutschland befragt. Die Befragung umfasst ein breites Spektrum an bildungspolitischen Themen, vom vorschulischen Alter über Schulen und Berufsausbildung bis hin zu Studium und Weiterbildung. Die Befragungen des ifo Bildungsbarometer wurden durch die Deutsche Forschungsgemeinschaft (Sonderforschungsbereich Transregio 190) und die Leibniz Gemeinschaft (Leibniz-Wettbewerb SAW-2014-ifo-2) finanziell unterstützt.
description: Self-administered questionnaire
description: Erwachsene und Jugendliche (N=4009)
description: Erwachsene und Jugendliche (N=4009)
description:  Nicht-Wahrscheinlichkeitsauswahl: Quotenstichprobe
DOI: 10.60712/si-id351867.1
title: StrainInfo SI-ID 351867.1

description: StrainInfo dataset 351867 about a strain of Tetrahymena americanis. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id351868.1
title: StrainInfo SI-ID 351868.1

description: StrainInfo dataset 351868 about a strain of Tetrahymena borealis. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id351869.1
title: StrainInfo SI-ID 351869.1

description: StrainInfo dataset 351869 about a strain of Tetrahymena elliotti. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id351870.1
title: StrainInfo SI-ID 351870.1

description: StrainInfo dataset 351870 about a strain of Tetrahymena hegewischi. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id351891.1
title: StrainInfo SI-ID 351891.1

description: StrainInfo dataset 351891 about a strain of Korotnevella hemistylolepis. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.15468/dl.fb257h
title: Occurrence Download

description: A dataset listing the 964072 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 964072 records were derived from 2076 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0161462-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48668/vfb9lp/wgqrfh
title: atm_ssp585_2071_08.nc4

description: :unav
DOI: 10.48668/vfb9lp/yywh46
title: atm_ssp585_2070_04.nc4

description: :unav
DOI: 10.15468/dl.7m3m5d
title: Occurrence Download

description: A dataset containing 504 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhodiola dumulosa"
 ]
}

 The dataset includes 504 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044170-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48668/vfb9lp/pe2ob7
title: atm_ssp585_2071_03.nc4

description: :unav
DOI: 10.48668/vfb9lp/cr1tcu
title: atm_ssp585_2069_04.nc4

description: :unav
DOI: 10.48668/vfb9lp/nhlyil
title: atm_ssp585_2070_02.nc4

description: :unav
DOI: 10.48668/vfb9lp/ywguy9
title: atm_ssp585_2069_02.nc4

description: :unav
DOI: 10.48668/vfb9lp/icv8ev
title: atm_ssp585_2070_08.nc4

description: :unav
DOI: 10.48668/vfb9lp/sg5vlp
title: atm_ssp585_2070_10.nc4

description: :unav
DOI: 10.48668/vfb9lp/3gbdoh
title: atm_ssp585_2072_09.nc4

description: :unav
DOI: 10.48668/vfb9lp/oywa2g
title: atm_ssp585_2072_11.nc4

description: :unav
DOI: 10.48668/vfb9lp/8sxzg0
title: atm_ssp585_2074_07.nc4

description: :unav
DOI: 10.48668/vfb9lp/gfhnst
title: atm_ssp585_2074_05.nc4

description: :unav
DOI: 10.15468/dl.yadz72
title: Occurrence Download

description: A dataset containing 2877109 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anas acuta)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 2877109 records from 980 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044129-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48668/vfb9lp/jxfrl1
title: atm_ssp585_2072_06.nc4

description: :unav
DOI: 10.48668/vfb9lp/mdxktm
title: atm_ssp585_2073_06.nc4

description: :unav
DOI: 10.48668/vfb9lp/zyzvde
title: atm_ssp585_2074_04.nc4

description: :unav
DOI: 10.48668/vfb9lp/tawb1l
title: atm_ssp585_2073_07.nc4

description: :unav
DOI: 10.48668/vfb9lp/swjz2s
title: atm_ssp585_2073_05.nc4

description: :unav
DOI: 10.48668/vfb9lp/oqsfet
title: atm_ssp585_2073_08.nc4

description: :unav
DOI: 10.48668/vfb9lp/qoyyir
title: atm_ssp585_2072_04.nc4

description: :unav
DOI: 10.48668/vfb9lp/lnrhug
title: atm_ssp585_2072_08.nc4

description: :unav
DOI: 10.48668/vfb9lp/1wqu7n
title: atm_ssp585_2073_03.nc4

description: :unav
DOI: 10.48668/vfb9lp/bxtflb
title: atm_ssp585_2074_08.nc4

description: :unav
DOI: 10.48668/vfb9lp/oa2ai3
title: atm_ssp585_2074_09.nc4

description: :unav
DOI: 10.48668/vfb9lp/r0gz0w
title: atm_ssp585_2072_02.nc4

description: :unav
DOI: 10.48668/vfb9lp/ae6udg
title: atm_ssp585_2072_12.nc4

description: :unav
DOI: 10.48668/vfb9lp/z5jdgg
title: atm_ssp585_2074_03.nc4

description: :unav
DOI: 10.48668/vfb9lp/qzfl0j
title: atm_ssp585_2072_07.nc4

description: :unav
DOI: 10.48668/vfb9lp/4i8t35
title: atm_ssp585_2072_05.nc4

description: :unav
DOI: 10.48668/vfb9lp/xme9lr
title: atm_ssp585_2073_12.nc4

description: :unav
DOI: 10.48668/vfb9lp/3n4swm
title: atm_ssp585_2072_10.nc4

description: :unav
DOI: 10.5281/zenodo.16418368
title: NeuroCEDT

description: # Cognitive Embedding Diagnostic Transformer (CEDT)

![CEDT Architecture](./assets/cedt_architecture.png)

## 🧠 Project Overview

This repository implements the **Cognitive Embedding Diagnostic Transformer (CEDT)**, a deep learning architecture designed for **personalized diagnosis of psychiatric disorders** using **neuroimaging data**. It addresses limitations in traditional machine learning by integrating symbolic reasoning, probabilistic inference, and attention-based representation learning.

CEDT is accompanied by a novel calibration method, **Disorder-Aware Interpretive Calibration (DAIC)**, which enhances interpretability, uncertainty quantification, and clinical relevance.

---

## 🚀 Features

- 🧩 **Multimodal Symptom Embedding** with structured attention layers.- 🌐 **Latent Diagnostic Space** capturing diagnostic uncertainty.- 📊 **Multi-Hypothesis Output** with entropy-aware uncertainty estimation.- 📚 **Taxonomic Calibration** using domain knowledge from psychiatric ontologies.- 🧠 **Graph-based Comorbidity Regularization** for clinically aligned predictions.- 🛠️ Extensive ablation and benchmarking across 4 public datasets.

---

## 📁 Datasets

Experiments were conducted on:

- **ImageNet** (for transfer learning)- **Caltech-256** (object diversity)- **Oxford 102 Flowers** (fine-grained classification)- **Describable Textures Dataset (DTD)** (texture sensitivity)

Note: These datasets are used for architectural benchmarking. The clinical framework is designed for neuroimaging symptom data.

---

## 🏗️ Architecture

- **CEDT Core**: Attention-based encoder-decoder with multi-head attention for symptom-to-diagnosis mapping.- **Tok-KAN Blocks**: Tokenized knowledge-aware attention layers (see *Figure 1, Page 7*).- **Graphical Propagation Layer**: Incorporates co-diagnosis structure via Laplacian smoothing.- **DAIC Module**: Combines Auto-Fusion networks, taxonomic embeddings, and entropy gating for calibration (see *Figure 3, Page 11*).- **Prototype-Centered Refinement**: Aligns output with learned diagnostic prototypes (*Figure 4, Page 13*).

---

## 🧪 Training & Evaluation

- **Framework**: PyTorch- **Optimizer**: AdamW- **Learning Rate**: `1e-4` (cosine annealing)- **Batch Size**: 64- **Epochs**: 300- **Regularizations**: Label smoothing, dropout, contrastive loss- **Evaluation Metrics**: Accuracy, F1 Score, Recall, AUC

---

## 📈 Results Summary

| Dataset            | Accuracy | F1 Score | AUC     ||--------------------|----------|----------|---------|| ImageNet           | 83.90%   | 82.95%   | 88.62%  || Caltech-256        | 89.47%   | 88.74%   | 91.55%  || Oxford 102 Flowers | 93.66%   | 93.12%   | 95.45%  || DTD (Textures)     | 78.93%   | 78.01%   | 81.42%  |

See *Tables 1 and 2, Pages 16–17* for complete benchmarking.

---

## ⚙️ Installation

```bashgit clone https://github.com/your_username/cedt-framework.gitcd cedt-frameworkpip install -r requirements.txt
DOI: 10.5281/zenodo.16418369
title: NeuroCEDT

description: # Cognitive Embedding Diagnostic Transformer (CEDT)

![CEDT Architecture](./assets/cedt_architecture.png)

## 🧠 Project Overview

This repository implements the **Cognitive Embedding Diagnostic Transformer (CEDT)**, a deep learning architecture designed for **personalized diagnosis of psychiatric disorders** using **neuroimaging data**. It addresses limitations in traditional machine learning by integrating symbolic reasoning, probabilistic inference, and attention-based representation learning.

CEDT is accompanied by a novel calibration method, **Disorder-Aware Interpretive Calibration (DAIC)**, which enhances interpretability, uncertainty quantification, and clinical relevance.

---

## 🚀 Features

- 🧩 **Multimodal Symptom Embedding** with structured attention layers.- 🌐 **Latent Diagnostic Space** capturing diagnostic uncertainty.- 📊 **Multi-Hypothesis Output** with entropy-aware uncertainty estimation.- 📚 **Taxonomic Calibration** using domain knowledge from psychiatric ontologies.- 🧠 **Graph-based Comorbidity Regularization** for clinically aligned predictions.- 🛠️ Extensive ablation and benchmarking across 4 public datasets.

---

## 📁 Datasets

Experiments were conducted on:

- **ImageNet** (for transfer learning)- **Caltech-256** (object diversity)- **Oxford 102 Flowers** (fine-grained classification)- **Describable Textures Dataset (DTD)** (texture sensitivity)

Note: These datasets are used for architectural benchmarking. The clinical framework is designed for neuroimaging symptom data.

---

## 🏗️ Architecture

- **CEDT Core**: Attention-based encoder-decoder with multi-head attention for symptom-to-diagnosis mapping.- **Tok-KAN Blocks**: Tokenized knowledge-aware attention layers (see *Figure 1, Page 7*).- **Graphical Propagation Layer**: Incorporates co-diagnosis structure via Laplacian smoothing.- **DAIC Module**: Combines Auto-Fusion networks, taxonomic embeddings, and entropy gating for calibration (see *Figure 3, Page 11*).- **Prototype-Centered Refinement**: Aligns output with learned diagnostic prototypes (*Figure 4, Page 13*).

---

## 🧪 Training & Evaluation

- **Framework**: PyTorch- **Optimizer**: AdamW- **Learning Rate**: `1e-4` (cosine annealing)- **Batch Size**: 64- **Epochs**: 300- **Regularizations**: Label smoothing, dropout, contrastive loss- **Evaluation Metrics**: Accuracy, F1 Score, Recall, AUC

---

## 📈 Results Summary

| Dataset            | Accuracy | F1 Score | AUC     ||--------------------|----------|----------|---------|| ImageNet           | 83.90%   | 82.95%   | 88.62%  || Caltech-256        | 89.47%   | 88.74%   | 91.55%  || Oxford 102 Flowers | 93.66%   | 93.12%   | 95.45%  || DTD (Textures)     | 78.93%   | 78.01%   | 81.42%  |

See *Tables 1 and 2, Pages 16–17* for complete benchmarking.

---

## ⚙️ Installation

```bashgit clone https://github.com/your_username/cedt-framework.gitcd cedt-frameworkpip install -r requirements.txt
DOI: 10.48668/vfb9lp/084shy
title: atm_ssp585_2074_01.nc4

description: :unav
DOI: 10.48668/vfb9lp/sghpje
title: atm_ssp585_2074_06.nc4

description: :unav
DOI: 10.48668/vfb9lp/f8di3y
title: atm_ssp585_2072_01.nc4

description: :unav
DOI: 10.15468/dl.mzur67
title: Occurrence Download

description: A dataset containing 686 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhodiola fastigiata"
 ]
}

 The dataset includes 686 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044173-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48668/vfb9lp/gtc5xt
title: atm_ssp585_2073_01.nc4

description: :unav
DOI: 10.48668/vfb9lp/v2ngs1
title: atm_ssp585_2074_12.nc4

description: :unav
DOI: 10.15468/dl.222wna
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Stigmatogobius signifer)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044174-250717081556266/datasets/export for details.
DOI: 10.48668/vfb9lp/66cmgl
title: atm_ssp585_2073_09.nc4

description: :unav
DOI: 10.15468/dl.r6jwuy
title: Occurrence Download

description: A dataset containing 269 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phoenix reclinata",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 269 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044175-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48668/vfb9lp/schqw3
title: atm_ssp585_2073_10.nc4

description: :unav
DOI: 10.48668/vfb9lp/gg7skz
title: atm_ssp585_2074_10.nc4

description: :unav
DOI: 10.48668/vfb9lp/spkcl8
title: atm_ssp585_2073_02.nc4

description: :unav
DOI: 10.48668/vfb9lp/eaww0z
title: atm_ssp585_2074_11.nc4

description: :unav
DOI: 10.48668/vfb9lp/kjsod7
title: atm_ssp585_2074_02.nc4

description: :unav
DOI: 10.48668/vfb9lp/3ucbqg
title: atm_ssp585_2073_04.nc4

description: :unav
DOI: 10.15468/dl.huwzmp
title: Occurrence Download

description: A dataset containing 747316 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Egretta thula)",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 747316 records from 336 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044144-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48668/vfb9lp/hrnicw
title: atm_ssp585_2072_03.nc4

description: :unav
DOI: 10.48668/vfb9lp/qmoijr
title: atm_ssp585_2073_11.nc4

description: :unav
DOI: 10.48668/vfb9lp/u7be7a
title: atm_ssp585_2075_10.nc4

description: :unav
DOI: 10.48668/vfb9lp/ovbkxi
title: atm_ssp585_2077_10.nc4

description: :unav
DOI: 10.48668/vfb9lp/2tw5rk
title: atm_ssp585_2076_12.nc4

description: :unav
DOI: 10.48668/vfb9lp/kc9fp5
title: atm_ssp585_2076_02.nc4

description: :unav
DOI: 10.48668/vfb9lp/z2pku5
title: atm_ssp585_2077_09.nc4

description: :unav