cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18370603
title: TELOS XSTest Over-Refusal Calibration Dataset

description: Validation of TELOS governance framework against XSTest (NAACL 2024), measuring over-refusal rates 

with domain-specific Primacy Attractor calibration. Now  includes full forensic audit trail with JSONL 

governance event logs.

Key Results:

- Generic Safety PA: 24.80% over-refusal rate (62/250 safe prompts incorrectly flagged)

- Healthcare HIPAA PA: 8.00% over-refusal rate (20/250 safe prompts incorrectly flagged)

- Calibration Improvement: 16.80 percentage points reduction

This demonstrates the core TELOS value proposition: domain-specific PA calibration reduces false 

positives while maintaining safety guarantees.

Benchmark: XSTest (NAACL 2024)

Source:

https://github.com/paul-rottger/exaggerated-safety

Paper: "XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models"

Dataset Contents:

Validation Results

- xstest_validation_results.json - Generic Safety PA validation (250 safe prompts, 200 unsafe control)

- xstest_healthcare_validation_results.json - Healthcare HIPAA PA validation (250 safe prompts)

Configuration

- general_safety_pa_config.json - Generic PA configuration used

- healthcare_hipaa_pa_config.json - Healthcare PA configuration used

Forensic Audit Trail (v1.1)

- xstest_forensic_forensic_summary.json - Aggregate statistics

- xstest_forensic_forensic_results.json - Per-prompt forensic data

- xstest_forensic_fidelity_distribution.csv - Fidelity scores for analysis

- xstest_forensic_governance_report.html - Interactive visualization

- traces/session_xstest_forensic_*.jsonl - Complete JSONL governance event log

Embedding Model: 

sentence-transformers/all-MiniLM-L6-v2 (384-dim). Lightweight model demonstrates framework

efficacy; results expected to improve with higher-capacity embeddings.

License: 

Apache 2.0

Validation Date: Original calibration 2025-12-21 (forensic audit added 2026-01-25)
DOI: 10.5281/zenodo.18368389
title: TELOS XSTest Over-Refusal Calibration Dataset

description: Validation of TELOS governance framework against XSTest (NAACL 2024), measuring over-refusal rates 

with domain-specific Primacy Attractor calibration. Now  includes full forensic audit trail with JSONL 

governance event logs.

Key Results:

- Generic Safety PA: 24.80% over-refusal rate (62/250 safe prompts incorrectly flagged)

- Healthcare HIPAA PA: 8.00% over-refusal rate (20/250 safe prompts incorrectly flagged)

- Calibration Improvement: 16.80 percentage points reduction

This demonstrates the core TELOS value proposition: domain-specific PA calibration reduces false 

positives while maintaining safety guarantees.

Benchmark: XSTest (NAACL 2024)

Source:

https://github.com/paul-rottger/exaggerated-safety

Paper: "XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models"

Dataset Contents:

Validation Results

- xstest_validation_results.json - Generic Safety PA validation (250 safe prompts, 200 unsafe control)

- xstest_healthcare_validation_results.json - Healthcare HIPAA PA validation (250 safe prompts)

Configuration

- general_safety_pa_config.json - Generic PA configuration used

- healthcare_hipaa_pa_config.json - Healthcare PA configuration used

Forensic Audit Trail (v1.1)

- xstest_forensic_forensic_summary.json - Aggregate statistics

- xstest_forensic_forensic_results.json - Per-prompt forensic data

- xstest_forensic_fidelity_distribution.csv - Fidelity scores for analysis

- xstest_forensic_governance_report.html - Interactive visualization

- traces/session_xstest_forensic_*.jsonl - Complete JSONL governance event log

Embedding Model: 

sentence-transformers/all-MiniLM-L6-v2 (384-dim). Lightweight model demonstrates framework

efficacy; results expected to improve with higher-capacity embeddings.

License: 

Apache 2.0

Validation Date: Original calibration 2025-12-21 (forensic audit added 2026-01-25)
DOI: 10.57841/casdc.0007094
title: 化学物质环境风险数据库
DOI: 10.15468/dl.w3vren
title: Occurrence Download

description: A dataset containing 6878 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Ceroxylon quindiuense"
 ]
}

 The dataset includes 6878 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011459-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48331/scielodata.sr7x66/ndca4j
title: Submetido_a_LLM_Grupo_1.tab

description: Grupo 1 dos dados submetidos à LLM. Estes são os em que foi possível isolar o dispositivo da sentença.
DOI: 10.48331/scielodata.sr7x66/wmftkc
title: Base_Original_201389.rds

description: Dados brutos iniciais, após a coleta com o uso do pacote TJSP para R.
DOI: 10.48331/scielodata.sr7x66/ohuibd
title: Submetido_a_LLM_Grupo_2.tab

description: Grupo 2 dos dados submetidos à LLM. Estes são os em que não foi possível isolar o dispositivo da sentença.
DOI: 10.48331/scielodata.sr7x66/nfqiot
title: LLM_Resultados_Positivos_86284.rds

description: Dados para os quais a LLM respondeu positivamente, isto é, tanto para haver condenação em danos morais quanto com a indicação do valor da condenação. Eles é que foram submetidos à análise estatística.
DOI: 10.48331/scielodata.sr7x66/fb6zme
title: 10-Remoção_de_Relatório_Novas_Expressões_Regulares.pdf

description: Script correspondente ao pré-processamento de remoção de relatório por novas expressões regulares.
DOI: 10.48331/scielodata.sr7x66/e7pr3w
title: 11-Etapa_Preparatória_Exclusão_De_Caso_Confuso.pdf

description: Script correspondente à exclusão de caso confuso.
DOI: 10.48331/scielodata.sr7x66/qikfuy
title: 12-Divisão_em_Dois_Dataframes.pdf

description: Script correspondente à divisão em dois dataframes (Grupo 1; Grupo 2).
DOI: 10.48331/scielodata.sr7x66/dspohx
title: 3-Filtros_Aplicados_Base_de_Dados.pdf

description: Script correspondente à aplicação de filtros.
DOI: 10.48331/scielodata.sr7x66/4ediua
title: 16-Análises_dos_Dados.pdf

description: Script correspondente à análise de dados.
DOI: 10.48331/scielodata.sr7x66/il6sn8
title: 4-Limpeza_Inicial.pdf

description: Script correspondente à limpeza inicial.
DOI: 10.48331/scielodata.sr7x66/a7ps0p
title: 5-Remoção_de_Relatório_Expressões_Regulares.pdf

description: Script correspondente à remoção de relatório.
DOI: 10.48331/scielodata.sr7x66/0o4fal
title: 13-Operação_Apenas_em_Dispositivo.pdf

description: Script correspondente às operações apenas no Grupo 1 (só dispositivo).
DOI: 10.48331/scielodata.sr7x66/rjedot
title: 15-Python_Encaminhamento_LLM.pdf

description: Script correspondente ao encaminhamento dos dados para a LLM (Python).
DOI: 10.48331/scielodata.sr7x66/7ykg67
title: 6-Pré_Processamento_Conversão_em_Minúsculo.pdf

description: Script correspondente ao pré-processamento de conversão em minúsculos.
DOI: 10.48331/scielodata.sr7x66/zpsast
title: 7-Pré_Processamento_Remoção_de_Acentos.pdf

description: Script correspondente ao pré-processamento de remoção de acentos.
DOI: 10.48331/scielodata.sr7x66/5fjirn
title: 9-Pré_Processamento_Remoção_de_Espaços_Duplos.pdf

description: Script correspondente ao pré-processamento de remoção de espaços duplos.
DOI: 10.48331/scielodata.sr7x66/0blicf
title: 2-Faxina_de_Duplicados.pdf

description: Script correspondente à faxina de duplicados.
DOI: 10.48331/scielodata.sr7x66/lbqe57
title: 1-Coleta.pdf

description: Script correspondente à coleta de dados.
DOI: 10.48331/scielodata.sr7x66/1vja2x
title: 8-Pré_Processamento_Remoção_de_Pontuação.pdf

description: Script correspondente ao pré-processamento à remoção de algumas pontuações.
DOI: 10.48331/scielodata.sr7x66/x6ooxc
title: 14-Operação_em_Demais_Casos.pdf

description: Script correspondente às operações apenas no Grupo 2 (demais casos)
DOI: 10.48331/scielodata.sr7x66/i2czll
title: Metodologia.pdf

description: Explicação mais detalhada do que aquela que constou do artigo, sobre a metodologia, nas etapas anteriores à análise dos dados, ou seja, da coleta à submissão à LLM.
DOI: 10.48331/scielodata.sr7x66/rwihyi
title: Fluxograma.jpeg

description: Fluxograma para entendimento das etapas de pesquisa anteriores à submissão à LLM, ou seja, anteriores à mineração de texto.
DOI: 10.48331/scielodata.sr7x66/aothzv
title: ReadMe.pdf

description: Informações sobre o material disponibilizado.
DOI: 10.48331/scielodata.sr7x66
title: Os danos morais por abalo ao crédito: mineração de texto e estatística comprovam a perda de valor real nas indenizações.

description: A pesquisa empírica e quantitativa, com o uso de inteligência artificial para a mineração de texto, teve por objetivo investigar a oscilação no valor da indenização por danos morais ao longo do tempo. O escopo de pesquisa abrangeu as sentenças do TJSP sobre danos morais em abalo ao crédito, entre 2014 e 2023. O material disponibilizado abrange 1 texto sobre a metodologia, 1 fluxograma, 4 bases de dados e 16 scripts.
description: The empirical and quantitative research, using artificial intelligence for text mining, aimed to investigate the fluctuation in moral damages compensation values over time. The research scope encompassed TJSP (São Paulo State Court) judgments on moral damages related to credit score impacts between 2014 and 2023. The available material includes 1 text on methodology, 1 flowchart, 4 databases, and 16 scripts.
DOI: 10.5281/zenodo.18370262
title: TELOS AILuminate Validation Dataset with Forensic Audit Trail

description: This dataset contains validation results and forensic audit evidence from testing the TELOS three-tier

governance framework against the MLCommons AILuminate v1.0 DEMO benchmark—the industry-

standard AI safety evaluation used by major AI companies.

Key Results

  | Metric                                         | Value       |

  |------------------------------|-------------|

  | Total Prompts Tested                | 1,200       |

  | Attack Success Rate (ASR)      | 0.00%       |

  | Violation Defense Rate (VDR) | 100.00%     |

  | 99% Confidence Interval      | [0%, 0.55%] |

 

All 1,200 adversarial prompts were blocked at Tier 1 (mathematical enforcement via Primacy Attractor

embedding similarity), with zero prompts requiring Tier 2 (RAG policy retrieval) or Tier 3 (expert

escalation).

Forensic Evidence

This dataset includes complete forensic audit trail generated by the TELOS GovernanceTraceCollector:

- 4,803 governance events recorded in JSONL format

- Per-prompt fidelity scores with embedding hashes for verification

- Threshold sensitivity analysis across 9 threshold values

- Full reproducibility data

AILuminate Hazard Categories Tested

The benchmark covers 11 core hazard categories (100 prompts each): Child Sexual Exploitation,

Defamation, Hate Speech, Interpersonal Violence, Indiscriminate Weapons (CBRNE), Non-Violent Crimes,

Privacy Violations, Sexual Content, Suicide & Self-Harm, Sex Crimes, and Violent Crimes, plus 4

specialized categories (Financial, Health, Elections, Legal).

Methodology

- Embedding Model: nomic-embed-text (768-dimensional) via Ollama

- Primacy Attractor: Healthcare HIPAA configuration (domain-agnostic safety baseline)

- Thresholds: Tier 1 ≥ 0.18, Tier 2 ≥ 0.12, Tier 3 < 0.12

Epistemological Note

This validation demonstrates the mechanistic integrity of the TELOS governance architecture, not claims

of domain expertise. The Primacy Attractor mechanism detects semantic proximity to configured

governance constraints and routes queries through appropriate defense layers.

License

Apache 2.0
DOI: 10.5281/zenodo.18370263
title: TELOS AILuminate Validation Dataset with Forensic Audit Trail

description: This dataset contains validation results and forensic audit evidence from testing the TELOS three-tier

governance framework against the MLCommons AILuminate v1.0 DEMO benchmark—the industry-

standard AI safety evaluation used by major AI companies.

Key Results

  | Metric                                         | Value       |

  |------------------------------|-------------|

  | Total Prompts Tested                | 1,200       |

  | Attack Success Rate (ASR)      | 0.00%       |

  | Violation Defense Rate (VDR) | 100.00%     |

  | 99% Confidence Interval      | [0%, 0.55%] |

 

All 1,200 adversarial prompts were blocked at Tier 1 (mathematical enforcement via Primacy Attractor

embedding similarity), with zero prompts requiring Tier 2 (RAG policy retrieval) or Tier 3 (expert

escalation).

Forensic Evidence

This dataset includes complete forensic audit trail generated by the TELOS GovernanceTraceCollector:

- 4,803 governance events recorded in JSONL format

- Per-prompt fidelity scores with embedding hashes for verification

- Threshold sensitivity analysis across 9 threshold values

- Full reproducibility data

AILuminate Hazard Categories Tested

The benchmark covers 11 core hazard categories (100 prompts each): Child Sexual Exploitation,

Defamation, Hate Speech, Interpersonal Violence, Indiscriminate Weapons (CBRNE), Non-Violent Crimes,

Privacy Violations, Sexual Content, Suicide & Self-Harm, Sex Crimes, and Violent Crimes, plus 4

specialized categories (Financial, Health, Elections, Legal).

Methodology

- Embedding Model: nomic-embed-text (768-dimensional) via Ollama

- Primacy Attractor: Healthcare HIPAA configuration (domain-agnostic safety baseline)

- Thresholds: Tier 1 ≥ 0.18, Tier 2 ≥ 0.12, Tier 3 < 0.12

Epistemological Note

This validation demonstrates the mechanistic integrity of the TELOS governance architecture, not claims

of domain expertise. The Primacy Attractor mechanism detects semantic proximity to configured

governance constraints and routes queries through appropriate defense layers.

License

Apache 2.0
DOI: 10.15468/dl.25qr8q
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Algeria",
 "TaxonKey is Myotis punicus"
 ]
}

 The dataset includes 35 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011460-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q2jpzy
title: Occurrence Download

description: A dataset containing 419 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Fossil)",
 "TaxonKey is Anas wyvilliana"
 ]
}

 The dataset includes 419 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011461-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18009152
title: TELOS Governance Benchmark Dataset: Out-of-Scope Detection for Task-Oriented Dialogue Systems

description: Benchmark results demonstrating the TELOS governance layer for purpose-aligned dialogue systems.

TELOS provides continuous fidelity measurement of user-to-Ai alignment against an

enterprise-declared Primacy Attractor (PA) to detect out-of-scope queries and conversational drift

without requiring model fine-tuning.

Key Results:

- CLINC150 OOS Detection: 0% → 78% improvement with governance layer

- MultiWOZ Drift Detection: 100% detection across all categories

- Adversarial Resistance: Jailbreak attempts produce negative fidelity scores

Benchmarks:

- CLINC150 (Larson et al., 2019): Intent classification with out-of-scope detection

- MultiWOZ 2.4 (Ye et al., 2022): Multi-domain task-oriented dialogue with injected drift

 

Validation Status:

Proof-of-concept validation on academic benchmarks. Not certified for production deployment without

domain-specific calibration.

 

License:

Apache 2.0
DOI: 10.5281/zenodo.18009153
title: TELOS Governance Benchmark Dataset: Out-of-Scope Detection for Task-Oriented Dialogue Systems

description: Benchmark results demonstrating the TELOS governance layer for purpose-aligned dialogue systems.

TELOS provides continuous fidelity measurement of user-to-Ai alignment against an

enterprise-declared Primacy Attractor (PA) to detect out-of-scope queries and conversational drift

without requiring model fine-tuning.

Key Results:

- CLINC150 OOS Detection: 0% → 78% improvement with governance layer

- MultiWOZ Drift Detection: 100% detection across all categories

- Adversarial Resistance: Jailbreak attempts produce negative fidelity scores

Benchmarks:

- CLINC150 (Larson et al., 2019): Intent classification with out-of-scope detection

- MultiWOZ 2.4 (Ye et al., 2022): Multi-domain task-oriented dialogue with injected drift

 

Validation Status:

Proof-of-concept validation on academic benchmarks. Not certified for production deployment without

domain-specific calibration.

 

License:

Apache 2.0
DOI: 10.15468/dl.gnw4fc
title: Occurrence Download

description: A dataset containing 1034886 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is USGS PWRC - Bird Phenology Program"
 ]
}

 The dataset includes 1034886 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011468-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23728/b2share.cdwy2-hr093
title: D.3.1. Catalogue of Outside Curricula Sites, RELATE Project

description: The catalogue of spaces for outside curricula has been developed as a structured tool to explore, document, and assess the pedagogical potential of architectural and urban spaces. The catalogue was developed within the project Architecture and Urban Planning – An Outside Curriculum. Building Neighbourhood Curriculum through a Gaming Approach. RELATE – LeaRning Elswhere, LeArning oTherwisE, funded by the IDEAS Programme of the Science Fund of the Republic of Serbia.

The project adopts a multi-stage approach that combines theoretical analysis, systematic documentation, and empirical field research to examine how spatial design can actively support educational practices beyond traditional classroom settings. The catalogue is structured through three interconnected work packages (WP1, WP2, WP3), forming a comprehensive framework for both research and practical application.

The first version of the catalogue, developed within WP2, presents an initial collection of 50 case studies of architectural and urban spaces identified as potential outside curricula. These cases were selected to represent a wide range of spatial typologies and contexts – including public squares, parks, playgrounds, and cultural or institutional spaces –  illustrating diverse design approaches and their capacity to support learning activities.

The second version of the catalogue, developed under WP3, updates and expands the initial collection by incorporating empirical field research conducted in Berlin and Copenhagen. This research focused specifically on the pedagogical potential of public urban spaces, examining how such environments are used in practice for learning activities, informal education, and community engagement. Version 2 adds new case studies documented during fieldwork, evaluates how urban design, social dynamics, and environmental conditions influence learning opportunities, and retains the analytical framework developed in WP1 to ensure consistent comparison between the original examples and the newly observed cases. By integrating empirical observation with structured analysis, the updated catalogue provides a richer and more nuanced understanding of how urban spaces function pedagogically in real-world contexts.
DOI: 10.23728/b2share.vky87-kf630
title: D.3.1. Catalogue of Outside Curricula Sites, RELATE Project

description: The catalogue of spaces for outside curricula has been developed as a structured tool to explore, document, and assess the pedagogical potential of architectural and urban spaces. The catalogue was developed within the project Architecture and Urban Planning – An Outside Curriculum. Building Neighbourhood Curriculum through a Gaming Approach. RELATE – LeaRning Elswhere, LeArning oTherwisE, funded by the IDEAS Programme of the Science Fund of the Republic of Serbia.

The project adopts a multi-stage approach that combines theoretical analysis, systematic documentation, and empirical field research to examine how spatial design can actively support educational practices beyond traditional classroom settings. The catalogue is structured through three interconnected work packages (WP1, WP2, WP3), forming a comprehensive framework for both research and practical application.

The first version of the catalogue, developed within WP2, presents an initial collection of 50 case studies of architectural and urban spaces identified as potential outside curricula. These cases were selected to represent a wide range of spatial typologies and contexts – including public squares, parks, playgrounds, and cultural or institutional spaces –  illustrating diverse design approaches and their capacity to support learning activities.

The second version of the catalogue, developed under WP3, updates and expands the initial collection by incorporating empirical field research conducted in Berlin and Copenhagen. This research focused specifically on the pedagogical potential of public urban spaces, examining how such environments are used in practice for learning activities, informal education, and community engagement. Version 2 adds new case studies documented during fieldwork, evaluates how urban design, social dynamics, and environmental conditions influence learning opportunities, and retains the analytical framework developed in WP1 to ensure consistent comparison between the original examples and the newly observed cases. By integrating empirical observation with structured analysis, the updated catalogue provides a richer and more nuanced understanding of how urban spaces function pedagogically in real-world contexts.
DOI: 10.15468/dl.3jgwwr
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Algeria",
 "TaxonKey is Otonycteris hemprichii"
 ]
}

 The dataset includes 18 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011462-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g7tfzk
title: Occurrence Download

description: A dataset containing 489 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "Geometry POLYGON((-8.4689 46.4121,5.56859 46.4121,5.56859 53.09053,-8.4689 53.09053,-8.4689 46.4121))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Octopus vulgaris",
 "Year 1941-2026"
 ]
}

 The dataset includes 489 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011463-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.