cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17929648
title: Comprehensive Empirical Dataset: 120+ Pages of AI-Automated Assessment Artifacts (Volume 3: Question Design, OCR, and Feedback Automation via IAT Model)

description: This dataset serves as the primary empirical evidence for the "Assessment Automation" module of the Integrated AI Triade (IAT) model. It compiles over 120 pages of instructional artifacts generated by teachers who utilized Generative AI to streamline the evaluation workflow, shifting from manual correction to strategic analysis.

Dataset Scope: The document demonstrates the practical application of AI in reducing teacher workload while enhancing feedback quality. It includes unique examples of bridging the analog-digital gap using AI vision tools.

Structure of the Compendium: The artifacts are organized according to the IAT Assessment Protocols (Session 3):

 

1.      Smart Question Design: AI-generated questions tailored to specific cognitive levels (Bloom's Taxonomy).

2.      Automated Quiz Generation: Rapid creation of structured quizzes and answer keys.

3.      Digitization (OCR) Artifacts: Real-world examples of converting students' handwritten assignments into digital text for AI analysis.

4.      AI-Generated Descriptive Feedback: Personalized, evidence-based feedback generated by AI based on student responses.

 

Methodology: These materials were produced during professional development workshops (2025). All personal data has been anonymized.
DOI: 10.5281/zenodo.17929649
title: Comprehensive Empirical Dataset: 120+ Pages of AI-Automated Assessment Artifacts (Volume 3: Question Design, OCR, and Feedback Automation via IAT Model)

description: This dataset serves as the primary empirical evidence for the "Assessment Automation" module of the Integrated AI Triade (IAT) model. It compiles over 120 pages of instructional artifacts generated by teachers who utilized Generative AI to streamline the evaluation workflow, shifting from manual correction to strategic analysis.

Dataset Scope: The document demonstrates the practical application of AI in reducing teacher workload while enhancing feedback quality. It includes unique examples of bridging the analog-digital gap using AI vision tools.

Structure of the Compendium: The artifacts are organized according to the IAT Assessment Protocols (Session 3):

 

1.      Smart Question Design: AI-generated questions tailored to specific cognitive levels (Bloom's Taxonomy).

2.      Automated Quiz Generation: Rapid creation of structured quizzes and answer keys.

3.      Digitization (OCR) Artifacts: Real-world examples of converting students' handwritten assignments into digital text for AI analysis.

4.      AI-Generated Descriptive Feedback: Personalized, evidence-based feedback generated by AI based on student responses.

 

Methodology: These materials were produced during professional development workshops (2025). All personal data has been anonymized.
DOI: 10.15468/kvvw6b
title: Fossil Collections of Natural History Museum

description: Fossil collections of Natural History Museum, Institute of Science and Technology, Tribhuvan University, Swayambhu, Kathmandu, Nepal
DOI: 10.15468/dl.raavuv
title: Occurrence Download

description: A dataset containing 1616 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Egretta eulophotes"
 ]
}

 The dataset includes 1616 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052452-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5286/isis.e.rb2520368-1
title: Exploiting Mesoporous Materials for Cryogenic Differential Condensation: A Novel Approach to Hydrogen and Deuterium Separation

description: This research aims to significantly improve hydrogen isotope separation by looking at how isotopes condense differently inside tiny, porous materials. We'll examine the detailed process of hydrogen (H₂) and deuterium (D₂) condensing in a material called PCN-222, and similar ones, using a technique called neutron powder diffraction (NPD). This lets us see exactly how the isotopes behave within the material's pores. We believe that this condensation effect, especially in pores of a certain size (2-50 nm), can separate isotopes better and hold more of them compared to traditional methods. By carefully changing the temperature and pressure, we'll figure out what factors are most important for isotope condensation and separation. This includes looking at how the structure of the pores and mixtures of isotopes affect the process. Our experiments, using the NIMROD instrument, will give us a much clearer picture of the structural changes and separation mechanisms that happen during condensation. This could lead to separating isotopes efficiently at higher temperatures, reducing losses during hydrogen storage. This work will pave the way for new and improved isotope separation technologies based on condensation.
DOI: 10.5286/isis.e.rb2520368
title: Exploiting Mesoporous Materials for Cryogenic Differential Condensation: A Novel Approach to Hydrogen and Deuterium Separation

description: This research aims to significantly improve hydrogen isotope separation by looking at how isotopes condense differently inside tiny, porous materials. We'll examine the detailed process of hydrogen (H₂) and deuterium (D₂) condensing in a material called PCN-222, and similar ones, using a technique called neutron powder diffraction (NPD). This lets us see exactly how the isotopes behave within the material's pores. We believe that this condensation effect, especially in pores of a certain size (2-50 nm), can separate isotopes better and hold more of them compared to traditional methods. By carefully changing the temperature and pressure, we'll figure out what factors are most important for isotope condensation and separation. This includes looking at how the structure of the pores and mixtures of isotopes affect the process. Our experiments, using the NIMROD instrument, will give us a much clearer picture of the structural changes and separation mechanisms that happen during condensation. This could lead to separating isotopes efficiently at higher temperatures, reducing losses during hydrogen storage. This work will pave the way for new and improved isotope separation technologies based on condensation.
DOI: 10.15468/dl.cywpmj
title: Occurrence Download

description: A dataset containing 1640 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Scarus zelindae"
 ]
}

 The dataset includes 1640 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052454-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17924395
title: Comprehensive Empirical Dataset: 600+ Pages of AI-Resistant Performance Tasks Designed by Teachers via IAT Model (Volume 1: Task Design Artifacts)

description:  

This extensive dataset serves as the primary empirical evidence for the "Task Design" module of the Integrated AI Triade (IAT) model. It contains over 600 pages of instructional artifacts generated by diverse cohorts of teachers during four separate professional development courses held in 2024-2025.

Dataset Scope:

The document compiles hundreds of unique "AI-Resistant" performance tasks designed by novice educators who utilized Generative AI as a "Design Partner." The sheer volume of this dataset demonstrates the scalability and reproducibility of the IAT framework across different subjects and grade levels.

Structure of the Compendium:

The dataset is organized into three distinct pedagogical patterns:

1.    Scenario-Based Tasks: Real-world problem-solving simulations.

2.    Comparative Analysis Tasks: Critical evaluation of AI-generated conflicting viewpoints.

3.    Creation & Critique Tasks: Higher-order thinking exercises involving the refinement of AI outputs.

Methodology:

These artifacts were produced using the specific prompt engineering protocols detailed in the IAT Technical Report. All personal data has been anonymized for ethical compliance.
DOI: 10.5281/zenodo.17924394
title: Comprehensive Empirical Dataset: 600+ Pages of AI-Resistant Performance Tasks Designed by Teachers via IAT Model (Volume 1: Task Design Artifacts)

description:  

This extensive dataset serves as the primary empirical evidence for the "Task Design" module of the Integrated AI Triade (IAT) model. It contains over 600 pages of instructional artifacts generated by diverse cohorts of teachers during four separate professional development courses held in 2024-2025.

Dataset Scope:

The document compiles hundreds of unique "AI-Resistant" performance tasks designed by novice educators who utilized Generative AI as a "Design Partner." The sheer volume of this dataset demonstrates the scalability and reproducibility of the IAT framework across different subjects and grade levels.

Structure of the Compendium:

The dataset is organized into three distinct pedagogical patterns:

1.    Scenario-Based Tasks: Real-world problem-solving simulations.

2.    Comparative Analysis Tasks: Critical evaluation of AI-generated conflicting viewpoints.

3.    Creation & Critique Tasks: Higher-order thinking exercises involving the refinement of AI outputs.

Methodology:

These artifacts were produced using the specific prompt engineering protocols detailed in the IAT Technical Report. All personal data has been anonymized for ethical compliance.
DOI: 10.3886/e241207
title: Italian Non-Probability 2022 Election Poll

description: Polling dataset with voting preferences, area location, age, gender, employment status, education and previous vote obtained from social media after the Italian National elections of September 2022. <br>data.Rdata contains the dataset, while poptable.Rdata contains the population tables obtained from the Italian census for adjustment.
DOI: 10.3886/e241207v2
title: Italian Non-Probability 2022 Election Poll

description: Polling dataset with voting preferences, area location, age, gender, employment status, education and previous vote obtained from social media after the Italian National elections of September 2022. <br>data.Rdata contains the dataset, while poptable.Rdata contains the population tables obtained from the Italian census for adjustment.
DOI: 10.15468/dl.k97k3g
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Oreotrochilus chimborazo chimborazo"
 ]
}

 The dataset includes 43 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052455-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14154683
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.qusqje
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pelecanus philippensis"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052456-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rkbj8j
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Scyliorhinus besnardi"
 ]
}

 The dataset includes 22 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052457-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xn58q5
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (South America, North America)",
 "TaxonKey is Dioscorea trifoliata"
 ]
}

 The dataset includes 57 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052458-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17833532
title: Revisión sistemática sobre algoritmos de aprendizaje federado (Federated Learning, FL) en Inteligencia Artificial de las cosas, (Artificial Intelligence of things, TinyML)

description: Revisión sistemática sobre algoritmos de aprendizaje federado (Federated Learning, FL) en Inteligencia Artificial de las cosas, (Artificial Intelligence of things,TinyML).
DOI: 10.5281/zenodo.17929785
title: Revisión sistemática sobre algoritmos de aprendizaje federado (Federated Learning, FL) en Inteligencia Artificial de las cosas, (Artificial Intelligence of things, TinyML)

description: Revisión sistemática sobre algoritmos de aprendizaje federado (Federated Learning, FL) en Inteligencia Artificial de las cosas, (Artificial Intelligence of things,TinyML).
DOI: 10.15468/dl.7e27zt
title: Occurrence Download

description: A dataset containing 5219 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pandion haliaetus"
 ]
}

 The dataset includes 5219 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052459-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rcjx2r
title: Occurrence Download

description: A dataset containing 302 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sparisoma tuiupiranga"
 ]
}

 The dataset includes 302 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052460-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s5seny
title: Occurrence Download

description: A dataset containing 18924 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Tayassu pecari"
 ]
}

 The dataset includes 18924 records from 190 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052461-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gxv5r3
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (South America, North America)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Dioscorea trifoliata"
 ]
}

 The dataset includes 22 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052463-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30246877
title: Somoulay et al. manuscript - Ataxin-2-like promotes translation of nonpolyadenylated reovirus mRNA

description: Abstract: Mammalian orthoreovirus (reovirus) nonstructural protein μNS nucleates viral factories (VFs), which are sites of viral genome replication, protein synthesis, and particle assembly. Reovirus mRNAs are not polyadenylated, yet these transcripts are efficiently translated. To identify host factors associated with translation in VFs, we conducted a proteomics screen and identified ataxin-2-like (ATXN2L) as a μNS-interacting protein. CRISPR-mediated gene knockout (KO) of ATXN2L impairs reovirus replication. The ATXN2L RNA-binding domains are required for reovirus replication and association with the 3’ terminus of nonpolyadenylated reovirus mRNAs. Synthesis of viral proteins is diminished in ATXN2L-KO cells following reovirus infection. Translation of a reovirus reporter construct is diminished following transfection of ATXN2L-KO cells with nonpolyadenylated mRNA but not with polyadenylated mRNA. These data identify ATXN2L as an essential mediator of translation of nonpolyadenylated reovirus mRNA.
DOI: 10.6084/m9.figshare.30246877.v1
title: Somoulay et al. manuscript - Ataxin-2-like promotes translation of nonpolyadenylated reovirus mRNA

description: Abstract: Mammalian orthoreovirus (reovirus) nonstructural protein μNS nucleates viral factories (VFs), which are sites of viral genome replication, protein synthesis, and particle assembly. Reovirus mRNAs are not polyadenylated, yet these transcripts are efficiently translated. To identify host factors associated with translation in VFs, we conducted a proteomics screen and identified ataxin-2-like (ATXN2L) as a μNS-interacting protein. CRISPR-mediated gene knockout (KO) of ATXN2L impairs reovirus replication. The ATXN2L RNA-binding domains are required for reovirus replication and association with the 3’ terminus of nonpolyadenylated reovirus mRNAs. Synthesis of viral proteins is diminished in ATXN2L-KO cells following reovirus infection. Translation of a reovirus reporter construct is diminished following transfection of ATXN2L-KO cells with nonpolyadenylated mRNA but not with polyadenylated mRNA. These data identify ATXN2L as an essential mediator of translation of nonpolyadenylated reovirus mRNA.
DOI: 10.15468/dl.c49x32
title: Occurrence Download

description: A dataset containing 38395 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation)",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pelophylax perezi"
 ]
}

 The dataset includes 38395 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052464-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hf8x4z
title: Occurrence Download

description: A dataset containing 245 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Stellifer brasiliensis"
 ]
}

 The dataset includes 245 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052465-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17929651
title: A Three-Dose Prophylactic Vaccine Against Food Allergy in Early Childhood: A Mechanistic, Bayesian, and Falsifiable Conceptual Framework

description: Food allergy (FA) affects 6--8% of children globally, with no approved prophylactic intervention. This manuscript proposes a comprehensive, pre-clinically grounded, and falsifiable framework for a three-dose prophylactic vaccine administered at 2, 4, and 12 months of age, integrated into the WHO Expanded Program on Immunization (EPI). The vaccine utilizes hypoallergenic peptides from major allergens---peanut (Ara h 2), egg (ovomucoid), and milk (\( \alpha_{s1} \)-casein)---encapsulated in GE11-functionalized lipid nanoparticles (LNPs) and adjuvanted with Pam3Cys + MPLA to promote regulatory T cell (Treg)-mediated tolerance. Key aspects addressed include biocompatibility, antigen dosing, LNP stability, lymphatic trafficking, and immunological non-interference in the multivalent formulation. A mechanistic ordinary differential equation (ODE) model captures the temporal dynamics of discrete dosing through a pharmacokinetically informed antigen input function \( A(t) \), adjusted for maternal antibody interference. Bayesian inference calibrates the model using data from the LEAP and EAT trials via a bridging parameter \( \phi \), with validation through global sensitivity analysis. The proposal is completed with a WHO-aligned cost-benefit analysis and a phased clinical roadmap (Phases I--III). No funding was received for this work.
DOI: 10.15468/dl.adbcn6
title: Occurrence Download

description: A dataset containing 112 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anchoa januaria"
 ]
}

 The dataset includes 112 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052466-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17929783
title: Comprehensive Empirical Dataset: 170+ Pages of AI-Generated Smart Analytical Rubrics (Volume 4: Assessment Criteria & Performance Descriptors via IAT Model)

description: This dataset represents the fourth and final volume of the empirical evidence series for the Integrated AI Triade (IAT) model. It contains over 170 pages of "Smart Analytical Rubrics" designed by teachers to ensure fair, transparent, and objective assessment in classrooms.

 

Dataset Scope: The document documents the cognitive workflow of educators moving from subjective grading to criteria-based assessment using Generative AI. It showcases how AI acts as a "Pedagogical Partner" to articulate complex standards of learning.

 

Structure of the Compendium: The artifacts follow the specific "Rubric Design Protocol" (Lesson 4 of IAT):

 

1.      Criteria Extraction: Identifying key dimensions of learning (e.g., Critical Thinking, Scientific Accuracy).

2.      Level Definition: Establishing clear performance scales (Novice, Apprentice, Master).

3.      Descriptor Generation: Using AI to write precise behavioral descriptions for each level, minimizing ambiguity in grading.

4.      Final Rubric Assembly: Ready-to-use assessment matrices.

 

Research Significance: This volume completes the IAT implementation cycle, proving that AI can significantly enhance "Assessment Literacy" among teachers and promote educational equity through standardized evaluation tools.
DOI: 10.5281/zenodo.17929784
title: Comprehensive Empirical Dataset: 170+ Pages of AI-Generated Smart Analytical Rubrics (Volume 4: Assessment Criteria & Performance Descriptors via IAT Model)

description: This dataset represents the fourth and final volume of the empirical evidence series for the Integrated AI Triade (IAT) model. It contains over 170 pages of "Smart Analytical Rubrics" designed by teachers to ensure fair, transparent, and objective assessment in classrooms.

 

Dataset Scope: The document documents the cognitive workflow of educators moving from subjective grading to criteria-based assessment using Generative AI. It showcases how AI acts as a "Pedagogical Partner" to articulate complex standards of learning.

 

Structure of the Compendium: The artifacts follow the specific "Rubric Design Protocol" (Lesson 4 of IAT):

 

1.      Criteria Extraction: Identifying key dimensions of learning (e.g., Critical Thinking, Scientific Accuracy).

2.      Level Definition: Establishing clear performance scales (Novice, Apprentice, Master).

3.      Descriptor Generation: Using AI to write precise behavioral descriptions for each level, minimizing ambiguity in grading.

4.      Final Rubric Assembly: Ready-to-use assessment matrices.

 

Research Significance: This volume completes the IAT implementation cycle, proving that AI can significantly enhance "Assessment Literacy" among teachers and promote educational equity through standardized evaluation tools.
DOI: 10.34740/kaggle/dsv/14154852
title: Antutu Benchmark