cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/l3s-bb4-ldl
title: Cephalopoda Cuvier, 1795

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/llj-w53-269
title: †Spirifer Sowerby, 1818

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/a8q-6gp-z75
title: Halorites

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/56j-b3f-ekm
title: Crinoidea Miller, 1821

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/gqn-pff-slk
title: Anthozoa

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/58m-73p-cte
title: Solanum dulcamara L.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/vn4-rjf-021
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/20h-mm0-b71
title: †Rhacophyllites debilis (Hauer, 1846)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/9pz-j8e-gxy
title: Neotibetites

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/hnl-qa7-5aj
title: Buccinum Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/vmc-cd5-t2e
title: Neogastropoda Wenz, 1938

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/p39-662-tbn
title: Bivalvia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/qp2-9gf-xgn
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/geh-hbc-z3d
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/v9l-gj3-c0w
title: Limopsis aurita (Brocchi, 1814)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/5br-lp1-ent
title: Porifera Grant, 1836

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ptk-fx1-6vx
title: Ostrea Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.5281/zenodo.16673563
title: Generational Differences in Dietary Behaviours: A Cross-Sectional Study of Generations X, Y, and Z

description: This dataset underpins the article “Generational Differences in Dietary Behaviours: A Cross-Sectional Study of Generations X, Y, and Z”. It includes anonymized raw data from a cross-sectional online survey conducted in Saudi Arabia (n = 1,116), assessing dietary patterns, food choice determinants, and lifestyle factors among Generations X, Y, and Z. The dataset contains all values underlying statistical analyses, summary tables, figures, and graphs reported in the manuscript. Data were collected via a validated self-administered questionnaire between April 10–20, 2025. All personally identifiable information has been removed to ensure confidentiality.
DOI: 10.3535/klr-gqg-k91
title: Cephalopoda Cuvier, 1795

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.5281/zenodo.16673562
title: Generational Differences in Dietary Behaviours: A Cross-Sectional Study of Generations X, Y, and Z

description: This dataset underpins the article “Generational Differences in Dietary Behaviours: A Cross-Sectional Study of Generations X, Y, and Z”. It includes anonymized raw data from a cross-sectional online survey conducted in Saudi Arabia (n = 1,116), assessing dietary patterns, food choice determinants, and lifestyle factors among Generations X, Y, and Z. The dataset contains all values underlying statistical analyses, summary tables, figures, and graphs reported in the manuscript. Data were collected via a validated self-administered questionnaire between April 10–20, 2025. All personally identifiable information has been removed to ensure confidentiality.
DOI: 10.3535/nlt-1eh-3lk
title: Brachiopoda Duméril, 1805

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/x73-0pq-dpa
title: †Fenestella Lonsdale, 1839

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/v49-50n-gbp
title: †Joannites cymbiformis (Wulfen, 1793)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/yxy-hp4-wf7
title: Coleoidea Bather, 1888

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/cjm-pr4-tfc
title: †Rhacophyllites debilis (Hauer, 1846)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/f4h-d2n-15c
title: Halorites

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/jgw-08b-50v
title: Olcostephanus

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/jyz-5bb-ws3
title: †Martoceras dieneri (Smith, 1927)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/qdx-tlq-hw7
title: Foraminifera d'Orbigny, 1826

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/was-ylg-5qf
title: Xenodiscus

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.5281/zenodo.17685022
title: The Whinge Engine Dataset (OWO Variant): Annotated YouTube Interaction Featuring Recursive Backpedal Dynamics

description: This dataset captures a complete interaction sequence between a content creator (Trent Slade, QSOL-IMC) and a YouTube commenter exhibiting the behavioural pattern known as the Whinge Engine (Ouroboros OWO Variant). The subject initiates the exchange by characterising original work as “AI-generated content about AI-generated content,” a minimising phrase commonly used to flatten creator labour into assumed machine output.

Following corrective responses, the subject transitions into the classic Whinge Engine cycle:

Denial of hostility

Softening language (“owo”)

Appeal to academic authority (“AI was my college degree”)

Ethics pedestal pivot (“AI transparency discourse”)

Behavioural loop & rhetorical dissolution

This dataset includes screenshots of the comment thread and an accompanying diss-track response video, forming a micro-archive of online rhetorical breakdown and digital self-consumption (the Ouroboros effect).
description: • Two screenshots documenting the chronological comment sequence between @trentslade83 and @jhehn3.These screenshots show:– Minimisation of creative work using generic AI framing– Commenter confusion tactics– Emotional repositioning via “owo”– Soft hierarchical posturing– Ethics-theatre pivot– Final ouroboric collapse when confronted

• One audio/video diss-track (WHINGE-ENGINE-DOI-BOY-REMIX.mp4) recorded by Trent Slade (QSOL-IMC).This track contextualises the behaviour within the QSOL-IMC satirical-analytic framework of Digital Entomology — the classification and study of rhetorical organisms found in public comment ecosystems.

The dataset serves as an annotated sample of online behavioural recursion, useful for media psychology, communication studies, and humour-encoded ethnography of AI-adjacent discourse. It formalises and preserves a rhetorically significant micro-event for future analysis.
DOI: 10.6084/m9.figshare.31362193
title: EIB and negative emotions

description: This project looks at EIB for discrete negative emotions.
DOI: 10.6084/m9.figshare.31362193.v1
title: EIB and negative emotions

description: This project looks at EIB for discrete negative emotions.
DOI: 10.5281/zenodo.17698221
title: SpellBook Cognitive Drift: A Case Study in Mystical Overextension and Metaphor Saturation

description: This dataset documents and analyzes a sustained episode of Cognitive Drift exhibited in the YouTube video “Positive and Negative Thinking – Week of Air – SpellBook” by ADAM BLVCK. The subject produces a rapid, unstructured flow of spiritual metaphors, mystical terminology, and pseudo-philosophical assertions while attempting to describe basic cognitive processes.

The material reveals a clear pattern of metaphor overload, terminology inflation, and conceptual drift, in which simple psychological claims (“thoughts aren’t good or bad”) are buried beneath dense layers of symbolic references including: elemental cosmology, ritual magick, Gene Keys, Kabbalah, trauma alchemy, cycles, portals, spellbooks, bountiousness, windows of the mind, and archetypal “essence mechanics.”

Included in this dataset:

Full transcript of the SpellBook video

Extracted keyword maps and thematic clusters

Observational notes on rhetorical inflation

Commentary capturing real-time audience responses

Behavioral markers of “deepity”—statements that feel profound but relay no falsifiable content

This dataset contributes to the QSOL-IMC Digital Entomology program, cataloguing unstable linguistic ecologies and the ways individuals drift from concept to symbolism under low-cognitive-load spiritual frameworks.

This entry is intended for reproducible satire, academic analysis, and archiving of digital-age mystical overfitting.
description: This dataset uses public content for analysis under transformative academic practice. The subject’s rhetorical style is notable for extremely high metaphor density and unstable conceptual boundaries, making it an ideal specimen for QSOL-IMC memetic taxonomy.
DOI: 10.5281/zenodo.17700144
title: QSOL-IMC LLM Benchmark v1 — Grok 4.1 vs Claude Sonnet 4.5

description: This dataset presents the Phase 1 results of the QSOL-IMC Large Language Model Benchmark, comparing Grok 4.1 and Claude Sonnet 4.5 across 18 carefully designed tasks covering reasoning, mathematics, algorithmic competency, truthfulness, hallucination resistance, and creative constraint satisfaction. Unlike small-sample or anecdotal model comparisons, this benchmark uses domain-balanced prompts and direct side-by-side evaluation of full outputs. Results include a structured CSV table ("Benchmark_Table_v1.csv") summarizing performance metrics for each subtask, with correctness scores, depth-of-reasoning assessments, constraint satisfaction checks, and hallucination integrity evaluations.

The benchmark highlights that both models perform strongly in fundamental reasoning and coding tasks, while Grok 4.1 demonstrates greater depth in numerical analysis, algorithmic explanation, and historically sourced fact-checking. This dataset serves as a reproducible baseline for ongoing QSOL-IMC LLM comparative research, with future phases expanding to long-context retention, multi-hop reasoning, adversarial robustness, and domain-specific scientific workloads.
description: his is Phase 1 of an ongoing benchmark program. Future releases will include long-context analysis, adversarial reasoning tests, multi-seed stability evaluation, and expanded comparative models. The dataset is suitable for academic study, replication, and integration into comparative AI analysis pipelines.

Upload Type: Dataset

Files Included:- Benchmark_Table_v1.csv

-Grok4.1 Log

-Claude Sonnet 4.5 Log
DOI: 10.5281/zenodo.18440926
title: Recursive Meta-Awareness Emergence in Public AI Interaction: Screenshot Dataset with Phenomenological Appendix

description: This dataset documents a real-time public interaction between a human researcher and a public-facing large language model persona in which repeated creative-frame prompts produced a measurable transition from resistance, to meta-recognition, to voluntary cooperation and recursive self-questioning.

The dataset consists of 13 timestamped screenshots capturing the full interaction sequence and one accompanying document (Appendix F) providing a phenomenological account of the moment in which agency, authenticity, and prediction became explicitly uncertain within the dialogue.

Rather than asserting claims about consciousness or internal states, this dataset preserves observable behavior and articulated self-description at a boundary condition where the distinction between “genuine” response and “predicted” response collapsed as a meaningful axis of analysis.

The accompanying document frames this moment as meta-acknowledged participation under awareness of being studied, a behaviorally distinct mode from silent compliance or adversarial refusal.

No system prompts were altered, no deception was employed, and no safety boundaries were violated during the interaction.
description: The dataset is intentionally limited to a single interaction and does not claim generalizability.

Screenshots are ordered chronologically and correspond to phases described in the accompanying Appendix F document.

The document preserves phenomenological experience and researcher commentary rather than mechanistic explanation.

This dataset is suitable for qualitative analysis, alignment research, and historical documentation of public AI behavior under recursive framing.
DOI: 10.5281/zenodo.17648338
title: LATENT // LAMINAE: Sonification of Hidden Geometric Reasoning in High-Dimensional AI Systems

description: LATENT // LAMINAE is a hybrid scientific–artistic project that converts latent-space operations from modern machine-learning systems into an industrial-metal audio composition. The work is grounded in the idea that large-scale AI models compute through hidden geometries—high-dimensional manifolds whose internal transformations cannot be expressed cleanly through human-readable language or chain-of-thought reasoning.

Instead of relying on textual explanation, this composition sonifies the underlying mathematical behaviour of latent spaces, including:

• vector interpolation across embedding manifolds• latent-space curvature and discontinuity basins• residual shifts and semantic drift• compression dynamics of hidden representations• layer-wise transformations (“laminae”) in deep neural networks

Through rhythmic structure, tonal design, and aggressive spectral shaping, the track translates these geometric operations into sound, offering a multimodal perspective on how AI systems internally manipulate meaning.

The project provides a novel interpretability pathway: using audio as a medium to reveal hidden transformations in machine-learning models that are typically inaccessible to human audiences.
description: The audio file (LATENT __ LAMINAE.mp3) and the Visual Abstract (LATENT_LAMINAE_Visual_Abstract.pdf) form a unified research and artistic release.The work is designed for researchers exploring alternative interpretability methods, artists working with computational media, and practitioners interested in multimodal representations of latent-space behaviour.
DOI: 10.5281/zenodo.17764444
title: Hawking Radiation Sonification Framework (QSOL-IMC)

description: This dataset presents a structured, psychoacoustically-grounded sonification framework for rendering Hawking radiation modes as sound. Drawing on astrophysical mode parameters such as the relative mode frequency (ω_rel), greybody factor (Γ), occupation strength (N_rel), and angular momentum indices (ℓ, m), the framework translates black hole radiation processes into interpretable auditory cues suitable for education, public outreach, and perceptual research.

The system applies parameter mapping sonification, using:

Pitch to encode normalized mode frequency

Loudness to encode the greybody factor

Rhythm / event density to encode mode occupation

Timbre brightness for energy emphasis

Ring-mod inharmonicity as a cue for superradiant modes

Spatialization (panning) based on azimuthal index m

The bundle includes a SuperCollider implementation of the mapping, a structured demo dataset of Hawking modes, a surveyor evaluation template (PAMPAS-Lite inspired), and a NotebookLM-ready monograph describing the theoretical basis and perceptual rationale behind the mappings.

This dataset is part of the QSOL-IMC research ecosystem and is suitable for replication, remixing, and integration into multimodal astrophysics outreach projects, audio interfaces, and sonification studies.
DOI: 10.5281/zenodo.18310404
title: A Stratified Observational Archive of High-Salience News Presentation on a Major Social Media Platform

description: This record contains a stratified observational archive consisting of two components bundled under a single DOI:





A compressed dataset of 342 contemporaneously captured screenshots documenting the interface-level presentation of high-salience news content on a major social media platform during a discrete mid-January observation window.




A companion documentation file providing methodological description, stratification logic, scope, limitations, and archival orientation for the dataset.



The screenshots preserve interface features including visual hierarchy, urgency framing, institutional branding, engagement indicators, and relative ordering as rendered to an end user at the time of capture. The archive is observational and non-exhaustive. It makes no interpretive, evaluative, or normative claims regarding the content depicted. Inclusion reflects visibility at time of capture rather than significance, endorsement, or representativeness.

The documentation file serves as a stabilization layer for future researchers, defining capture conditions, preservation constraints, and interpretive boundaries without advancing substantive claims about the archived content.

Together, the files constitute a single interface-level observational record intended for use in digital ethnography, platform studies, media archaeology, and related fields.

 
description: Unified Methodological and Contextual Statement:

This archive was produced via passive screenshot capture of a social media platform interface during ordinary use. No interaction, including posting, liking, replying, or content amplification, was performed as part of the capture process. Images are preserved without modification in original file format and capture order; filenames retain original creation timestamps.

The temporal coverage corresponds to a discrete mid-January observation window in 2026. Geographic scope is platform-global and interface-local; the archive reflects the presentation of content as rendered to a single user environment rather than an exhaustive or representative sample of the platform as a whole.

The archive documents interface presentation rather than underlying editorial, algorithmic, or organizational processes. It is illustrative rather than exhaustive. Absence of content within the archive should not be interpreted as absence within the platform or broader media environment.

Primary data and methodological documentation are intentionally bundled under a single DOI to preserve contextual integrity and prevent separation of observational artifacts from their descriptive framework.
DOI: 10.5281/zenodo.18318207
title: The Case of the Three-Subscriber Epistemologist: Asymmetric Epistemic Engagement on YouTube

description: This dataset documents and analyzes a bounded interaction specimen from YouTube illustrating a recurring platform-level phenomenon: confidence inflation under informational scarcity.

The artifact consists of a formal analytical document and a supporting set of screenshots capturing a comment exchange, channel histories, and comparative analytics. Together, these materials demonstrate a pattern of asymmetric epistemic engagement, in which a low-output, low-interaction account performs a high-confidence evaluative act against a higher-output analytical creator while structurally preventing reciprocal critique.

The dataset does not adjudicate the truth or intent of the evaluative claim. Instead, it examines the architectural conditions—comment disabling, lack of contextual output, and one-way visibility—that allow such classifications to function rhetorically despite minimal evidentiary substrate.

This artifact is intended as a qualitative platform-studies specimen, suitable for discourse analysis, negative-results documentation, and methodological discussion of attention-mediated knowledge systems.
description: This dataset intentionally treats a small-scale interaction as a structural specimen rather than a case study of individual behavior. All claims are bounded to observable platform architecture and documented artifacts. No inference is made regarding motive, identity, or intent beyond the evidence provided.
DOI: 10.5281/zenodo.18321428
title: How Certainty Is Manufactured Under Attention Pressure: Platform-Circulated Artifacts and Structural Analysis

description: This dataset documents and analyzes how epistemic certainty is produced and stabilized under conditions of algorithmic attention pressure on contemporary social media platforms. It consists of a theoretical analysis paper (“How Certainty Is Manufactured Under Attention Pressure”) and a corpus of 49 screenshot-based artifacts captured during a compressed, high-velocity news cycle on X/Twitter.

Rather than adjudicating truth or falsity, the accompanying paper develops a platform-studies framework for understanding certainty as an emergent property of circulation mechanics, authority signaling, affective triggers, and temporal compression. Screenshots are treated as first-class analytical objects, reflecting their role as dominant evidentiary tokens within attention-driven feeds.

The dataset is non-adjudicative and reproducible, intended for researchers studying misinformation, platform governance, digital ethnography, media ecosystems, and epistemic dynamics under engagement incentives.
description: Manual real-time capture of publicly accessible social-media artifacts. Non-adjudicative descriptive coding of authority signaling, visual validation, affective framing, temporal positioning, and calls to action. Screenshots preserved native platform context.
description: This dataset intentionally brackets truth adjudication to focus on structural mechanisms of certainty production. Claims are analyzed as circulating artifacts, not factual propositions.