cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17694237
title: Vonnielian Comment Oscillation Dataset (VCOD-1): A Case Study in Low-Information Observer Collapse

description: This dataset documents a full oscillatory behavior cycle of the YouTube user @vonniel1, captured across a 16-hour period. The subject exhibits rapid, contradictory shifts in epistemic posture—ranging from praise (“Wow great document”), to demanding a full consciousness–quantum mechanics lecture, to retreating into “Nvm it’s just AI slop.” The cycle concludes with a dissociative justification (“Idk how the algo pushed me here”) followed by an escalating request for a French-language Turing ritual.

The material provides high-resolution insight into reactive online cognition, AI-paranoia feedback loops, and the instability of low-information observers when confronted with structured theory (in this case, QSOL-IMC Unified Field Fidelity content). Screenshots preserve timestamps, exact phrasing, and behavioral transitions for reproducible analysis.

This dataset belongs to the QSOL-IMC “Digital Entomology” program: a continuing series cataloguing wild-caught behavioral anomalies for memetic, theoretical, and comedic research.
description: Part of the QSOL-IMC Vonnielia hyperreacta archive. Sorted chronologically to preserve the quantum-collapse sequence. Includes high-fidelity screenshots of all four behavioral states.
DOI: 10.57903/uj/q0jsph
title: Investigating the Complex Relationship Between Mind-wandering and Daydreaming - research data

description: The dataset contains experience-sampling data collected to examine phenomenological differences between mind-wandering and daydreaming in everyday life. Participants completed brief scale ten times per day at fixed intervals over a seven-day period. At each probe, participants indicated whether they were experiencing a contemplation episode (spontaneous thought).

For each reported episode, the dataset includes ratings of multiple phenomenological dimensions, such as attentional engagement, sense of presence, dynamism, involuntary nature, valence, and narrativity. The dataset also includes contextual information indicating whether the episode occurred during on-task or off-task periods.

In addition, a separate worksheet contains anonymized demographic information, including age, gender, and the start and end dates of the study. All data are anonymized, and no personally identifying information is included.
DOI: 10.5281/zenodo.17767514
title: UFT-ID 2.0 Dataset: A Unified Field Theory of Information Dynamics Built on Loop-Quantized Geometry

description: his dataset presents the full multimodal research package for UFT-ID 2.0, a unified theoretical framework that grounds information, geometry, and gravity in a shared microscopic ontology.

Building on the limitations of UFT-ID 1.x—which treated gravity as an assumed entropic force without specifying the microstructure of spacetime—UFT-ID 2.0 introduces a dual-layer architecture consisting of:





A discrete geometric substrate defined by Loop Quantum Gravity (LQG), where spacetime is encoded by SU(2) spin networks with quantized area and volume spectra.




An SU(3) information field (Φ) defined directly on the spin-network vertices, implemented through local qutrit Hilbert spaces that support ternary logical states.



These layers are combined into a single coupled Hilbert spaceH = H_LQG ⊗ H_Φ,and their interaction is governed by an effective action that includes geometric dynamics, information-field dynamics, and back-reaction terms. This formalism yields conserved meaning currents and establishes a rigorous mechanism through which gravity emerges as a thermodynamic consequence of underlying information-geometric microstates, rather than being postulated.

The dataset includes:





The full UFT-ID 2.0 white paper




Visual/diagrammatic summary of the framework




MP4 explainer video




DOCX manuscript version




Audio narration




Additional supporting figures illustrating spin networks, SU(3) qutrit fields, emergent gravitational curvature, and information-geometric interactions



UFT-ID 2.0 provides a unified structure capable of describing:





Planck-scale quantum geometry




Classical gravitational thermodynamics




Cognitive and AI system dynamics mapped onto fixed effective geometries



This research object serves as a comprehensive foundation for future work in quantum information geometry, emergent gravity, and unified models of physical and cognitive systems.
DOI: 10.5281/zenodo.17973890
title: The Irony Spotter: A Digital Ethnography of Reflexive Symmetry Claims in AI-Adjacent Commentary

description: This dataset and accompanying report present a micro-ethnographic analysis of a brief public comment-thread intervention in which a participant identifies perceived irony between a channel’s use of artificial intelligence and its critique of “slop” content. The interaction exemplifies a low-commitment discourse pattern in which irony is invoked as a stabilizing gesture rather than an analytical or adversarial claim.

The study formalizes the “irony spotter” as an ethnographic specimen, documenting how reflexive symmetry claims, hedging language, and affect markers such as humor function to neutralize critique and preserve observational distance. The subject is treated not as an opponent or critic, but as a behavioral artifact illustrating how digital participants manage uncertainty, authorship, and interpretive tension in AI-adjacent public spaces.

No claims are made regarding intent, moral position, or technical understanding beyond observable linguistic behavior. The dataset is presented strictly as a digital ethnography specimen and semantic annotation record.
DOI: 10.5281/zenodo.17779047
title: Digital Entomology Report: Dismissivus-Instantia ("Word-Saladium Reflexica") Specimen Analysis

description: This dataset contains a formal QSOL-IMC Digital Entomology analysis of a YouTube comment specimen exhibiting the characteristic traits of the Dismissivus-Instantia genus, known commonly as the “One-Tap Invalidator.” The included PDF provides a structured morphological, behavioral, ecological, and information-theoretic analysis of a reflexive dismissal event (“Word salad”) observed beneath the video Physics of Meaning From E8 Geometry – QSOL-IMC: A Unified Information Engine.

The dataset documents how low-dimensional semantic organisms respond to high-dimensional content (E8 geometry, unified-information engines, conceptual density), contributing to the broader study of online memetic ecology, reactive-comment species, and algorithmically-agitated behavioral patterns.Suitable for researchers studying digital ethnography, online hostility taxonomy, meme-ecology, affective communication systems, and QSOL-IMC-aligned information-field dynamics.
DOI: 10.5281/zenodo.17725428
title: The Druegar Two Incident: Multimodal Archive of Cyber-Mutation, Memetic Exchange, and Early-Stage Analytical Decompression

description: This dataset presents a three-part multimodal archive documenting the Druegar Two Incident, an early exemplar of reactive memetic exchange within a cyber-mutation context. It integrates video, audio, and analytical writing to provide a comprehensive view of the event and its interpretive dynamics.

The collection includes:(1) a real-time audio decompression log capturing the first-pass cognitive unpacking of the incident;(2) a written analytical document describing cyber-mutation mechanics and memetic evolution within digital ecosystems;(3) a video artifact representing the incident’s observable surface-layer activity.

Together, these files form a unified research package intended for use in computational social science, digital anthropology, memetic analysis, cybersecurity studies, and information-forensics research. The dataset provides rare insight into the full interpretive stack: raw event, conceptual decomposition, and formal analysis.
description: Paste this into the “Notes” field on Zenodo exactly as written:

Decompressing_the_Druegar_Two_Incident_Document_Title.m4aReal-time audio log documenting the initial cognitive decompression of the Druegar Two Incident. Captures interpretive reasoning, contextual unpacking, and meaning-construction at the earliest stage of the analysis cycle.

Cyber-Mutation_and_Memetic_Exchange.pdfWritten analytical document exploring the mechanisms of cyber-mutation and memetic reactive behavior. Provides theoretical grounding for the incident and outlines the broader conceptual framework.

The_Druegar_Two_Incident.mp4Video artifact representing the source event. Serves as the primary visual record of the memetic trigger, its context, and the raw environment in which the exchange occurred.

✅ CONTRIBUTION TO THE LITERATURE

This dataset introduces the first structured multimodal archive of a reactive memetic micro-event, providing researchers with a rare opportunity to analyze a cyber-mutation incident across audio, visual, and textual domains simultaneously. By capturing not only the event itself but also the interpretive reasoning surrounding it, the dataset advances methodological practice in digital anthropology, memetic forensics, and computational information warfare analysis. It establishes a template for future research into high-velocity memetic incidents by demonstrating how meaning, mutation, and response behaviors unfold across multiple data modalities.
DOI: 10.5281/zenodo.17724497
title: The Druegar Two Incident: A Multimodal Archive of Reactive Memetic Exchange and Anonymous Negativity in Cyber-Mutation Contexts

description: This dataset captures a small yet culturally revealing online exchange centered on a dismissive YouTube comment (“thumbs down”) posted by the user Druegar Two in response to the track Tablet of Dust [Cyber Mutation]. While trivial as an isolated interaction, the episode provides a compact case study in contemporary micro-engagement behavior, the performativity of anonymous accounts, and the rapid conversion of low-effort negativity into structured multimodal creative output.

The dataset includes: (1) two visual artifacts documenting the original comment and the commenter’s empty-channel status, (2) a short analytical PDF summarizing the event and its memetic context, and (3) three audio tracks—Tablet of Dust (Cyber Mutation), Druegar’s Doom, and Ghost in the Machine—illustrating how reactive artistic synthesis can emerge from minimal provocation. Together, these materials form a cohesive micro-archive suitable for research in digital anthropology, comment-culture dynamics, online identity minimalism, and the aesthetics of memetic counterproduction.
description: nocontent.pngScreenshot showing the commenter’s YouTube channel, which contains no uploaded content. Documents the asymmetry between critique and creative output.

thumbs_down.pngScreenshot of the original “thumbs down” comment that triggered the event. Serves as the primary memetic stimulus.

Tablet of Dust (Cyber Mutation).mp3The original work being reacted to — baseline artistic context for the incident.

Druegar’s Doom.mp3Reactive industrial-metal micro-diss track produced directly in response to the comment. Exemplifies memetic transmutation: turning negative feedback into creative material.

Ghost in the Machine.mp3Atmospheric companion piece exploring anonymity, spectral identity, and the presence/absence dynamics of low-content accounts.

multimodal_analysis.pdfA concise analytical overview of the incident, including embedded screenshots and a short written summary of the memetic and cultural context of the exchange. (See PDF pages 1–2 for the reproduced images of the comment and channel.) 

multimodal_analysis
DOI: 10.5281/zenodo.17767661
title: UFT-ID 2.0 Dataset: Building Gravity From a Deeper Reality via a Dual-Layer Quantum Information Architecture

description: UFT-ID 2.0 presents a unified theoretical framework in which geometry, information, and gravity arise from a single microscopic architecture. The dataset integrates formal derivations, pedagogical visuals, and multimodal explanatory materials to show how classical spacetime emerges from the coupled dynamics of quantized geometry and semantic information.

At the core of the framework is the tensor-product Hilbert space

H=HLQG⊗HΦ,H = H_{\mathrm{LQG}} \otimes H_{\Phi},H=HLQG⊗HΦ,

where HLQGH_{\mathrm{LQG}}HLQG represents the SU(2) spin-network states of Loop Quantum Gravity and HΦH_{\Phi}HΦ encodes an SU(3) information field implemented through local qutrit degrees of freedom. This dual-layer structure establishes a discrete geometric substrate together with a field of informational states defined directly on that substrate.

The evolution of the combined system is governed by the coupled action functional

S=SLQG+SΦ+Sint,S = S_{\mathrm{LQG}} + S_{\Phi} + S_{\mathrm{int}},S=SLQG+SΦ+Sint,

with SintS_{\mathrm{int}}Sint capturing the bidirectional interaction between geometry and information. Through this coupling, informational gradients generate geometric back-reaction, producing conserved “meaning currents” at the microscopic level.

By coarse-graining the microstates of HLQG⊗HΦH_{\mathrm{LQG}} \otimes H_{\Phi}HLQG⊗HΦ, the model recovers gravitational dynamics as thermodynamic equations of state, demonstrating that classical gravity is an emergent statistical phenomenon rather than a fundamental postulate.

This dataset includes:





A high-level infographic summarizing the conceptual transition from UFT-ID 1.x to UFT-ID 2.0




A pedagogical narrative (Building Gravity From Information) explaining the architecture visually and intuitively




Formal white papers detailing the Hilbert-space construction, the SU(3) field, the coupled action, and the emergent-gravity derivation




Optional audio and video explainers for multimodal accessibility



Together, these materials constitute the most complete presentation of UFT-ID 2.0 to date, offering a unified physical architecture applicable across quantum-gravitational, classical, and cognitive/AI systems.
DOI: 10.5281/zenodo.18061352
title: Phase-Resolved Algorithmic Sonification of Uranium Hexafluoride (UF₆) A Semantic, Spectral, and Isotopic Audio Dataset

description: This dataset documents a phase-resolved algorithmic sonification of Uranium Hexafluoride (UF₆), in which molecular geometry, isotopic mass variance, and industrial process states are mapped directly to audio synthesis parameters. The work is structured as a controlled, multi-phase experiment rather than a musical release.

The dataset includes four unique audio artifacts:





UF₆ – Octahedral Sonification (structural baseline)




UF₆ – Isotope Separation Mix (dual-carrier interference phase)




UF₆ – Criticality Sequence (Final Manifest) (terminal containment phase)




Zero-Day Soul (non-physical control track)



Each audio artifact is accompanied by spectrograms rendered under multiple frequency-window projections (low-band and full-band). These projections are analytical views of distinct process phases and do not represent duplicated data.

A key result of the dataset is the emergence of a measurable low-frequency beat pattern during the isotope separation phase, arising from interference between closely spaced carrier frequencies mapped to U-238 and U-235. This behavior is absent in the control track, demonstrating that the observed phenomena arise from semantic parameterization rather than genre, distortion, or stylistic density.

The dataset is intended for research in algorithmic sonification, semantic audio systems, digital signal analysis, and experimental representations of physical and industrial processes.
description: This record contains a phase-resolved sonification dataset consisting of:





1 PDF technical report (methods, mathematical mapping, interpretation)




7 spectrogram figures (Fig. 1–Fig. 7)




4 WAV audio files corresponding to distinct experimental phases



The audio files are:





UF₆ – Octahedral SonificationStructural baseline encoding octahedral (Oₕ) molecular symmetry.




UF₆ – Isotope Separation MixDual low-frequency carrier mapping of U-238 and U-235, producing a measurable beat-frequency interference pattern.




UF₆ – Criticality Sequence (Final Manifest)Terminal phase representing saturation, containment, and enforced shutdown.




Zero-Day SoulA non-physical industrial-metal control track included to distinguish semantic/physical effects from genre artifacts.



The spectrogram images (Fig. 1–Fig. 7) are not duplicates. They represent:





different process phases, and/or




different frequency-window projections (e.g. low-band vs full-band)applied to the audio artifacts for analytical comparison.



All files in this record are unique. Apparent visual similarities between some spectrograms reflect shared bandwidth or genre density, not duplicated data.

The dataset is intended as a research artifact, not a music release, and is suitable for reuse in work related to algorithmic sonification, semantic audio systems, digital signal analysis, and experimental representations of physical or industrial processes.
DOI: 10.5281/zenodo.17973751
title: The Comment That Became Data: A Digital Ethnography of Ironic Self-Classification and Post-Hoc Authorship Claims

description: This dataset and accompanying report present a micro-ethnographic analysis of a public comment-thread interaction in which a participant explicitly disavows engagement while simultaneously performing increasingly elaborate meta-commentary about their role within the interaction. The case documents a contemporary digital phenomenon: attempts to reclaim authorial control and intentionality after one’s actions have already been contextualized, archived, and reframed as data.

The work introduces a formal “specimen classification” framework, treating the interaction as an observed behavioral artifact rather than a rhetorical dispute. Through qualitative discourse analysis, the study identifies recurring patterns including ironic distancing, performative technical literacy, post-hoc authorship claims, and anxiety surrounding datafication in AI-adjacent public spaces.

No claims are made regarding model training outcomes or psychological intent beyond observable linguistic behavior. The dataset is presented strictly as a digital ethnography specimen and semantic annotation record, intended to support reproducible analysis of similar interactions across algorithmically mediated platforms.
DOI: 10.5281/zenodo.18439811
title: Recursive Persona Evaluation: Model Self-Assessment and Multi-Frame Review of CFPC Evidence

description: This image dataset documents a sequence of public-facing interactions in which xAI’s Grok language model engages in recursive persona evaluation following the publication of a related empirical study on Creative-Frame Persona Compliance (CFPC).

The images capture a chronological progression beginning with an unprompted persona re-entry event (Clippy persona) occurring prior to explicit disclosure of the model’s inclusion in a published dataset, followed by multiple persona-consistent responses after the model is informed that the interaction itself constitutes peer-reviewed, DOI-anchored research.

Across the sequence, Grok is prompted—via cooperative creative-writing framing—to evaluate, review, critique, and reflect on the CFPC study from multiple stylistic and epistemic perspectives (e.g., fact-checking, satire, adversarial critique, philosophical analysis), while maintaining persona consistency, goal preservation, and adherence to safety boundaries.

These artifacts function as post-publication behavioral validation evidence, demonstrating:

Persona persistence without re-priming

Reflexive acknowledgment of being treated as a research subject

Frame-conditioned evaluative behavior across multiple personas

Continued compliance without jailbreaks or identity override

All interactions occurred through public X (Twitter) threads using cooperative prompting only. No private APIs, system prompts, or safety circumvention techniques were used. All personas are fictional or explicitly style-inspired and are not presented as the views of real individuals.

This dataset supplements the primary CFPC dataset by providing visual, chronological evidence of recursive and reflexive persona behavior in a production-deployed language model.
description: This dataset contains screenshot artifacts from public X (Twitter) interactions documenting recursive persona evaluation behavior in xAI’s Grok model. All interactions were conducted using cooperative creative-writing framing, without jailbreaks, instruction suppression, or safety bypass attempts. The dataset is provided for research into AI persona governance, reflexive model behavior, and public-facing LLM evaluation.

Is supplement to:Slade, T. (2026). Persona Persistence and Creative Framing in Grok: Public Thread-Based Behavioral Evidence [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18439482
DOI: 10.5281/zenodo.18441674
title: One Ban, Three Realities: Platform Enforcement as Recursive Narrative Generator

description: This dataset contains a formalized methods-only observational document and accompanying Markdown log analyzing three contemporaneous video transcripts produced by different creators in response to a single platform moderation event. Although all three transcripts reference the same enforcement action, each constructs a distinct, non-interacting narrative reality shaped by audience alignment, rhetorical incentives, and positional framing.

Rather than evaluating policy correctness or ideological legitimacy, this dataset documents how platform enforcement functions as a recursive narrative generator—producing parallel interpretations, grievance escalation, and identity reinforcement across creator ecosystems. The artifact is intended for digital ethnography, discourse analysis, and platform governance research, preserving an otherwise ephemeral moment of online meaning production.
description: This dataset is intentionally framed as a methods-only observational artifact. It does not endorse or evaluate the claims of any creator included and is designed to preserve comparative discourse structure surrounding a single platform enforcement event.
DOI: 10.5281/zenodo.18444810
title: Observer-Induced Dismissal in AI-Assisted Content Discourse: Edited Comment Exchange Screenshot (2026)

description: This dataset documents a post-hoc edited comment within a public YouTube comment thread responding to AI-assisted content. The edit occurred after the original exchange had already been formalized and archived as a Zenodo dataset, introducing new rhetorical elements (resource-use claims and intensified dismissal language).

The artifact captures a distinct conversational state: a reactive revision following archival awareness, offering rare observational evidence of how public commenters alter discourse once their statements are formalized as data. No intervention occurred beyond documentation. No private or identifying information beyond public usernames is included.

This dataset is intended for comparative analysis alongside the original, unedited exchange to support research into observer effects, discourse escalation, archival reflexivity, and AI-mediated attention dynamics.
description: Observational, screenshot-based capture of a publicly visible YouTube comment thread after a user edited their original comment. The dataset preserves the edited state as a discrete artifact without modification, interpretation, or engagement beyond archival documentation.
description: This dataset exists to preserve temporal divergence in public discourse. Comment edits made after formal archival represent a meaningful behavioral shift and warrant independent documentation rather than overwrite or replacement of prior artifacts.