cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17760982
title: Algorithmic Paranoia: Conflict over Digital Authenticity — Multimodal Dataset (v1.0)

description: This multimodal dataset documents a compact, high-intensity specimen of algorithmic paranoia, AI slop accusations, and identity destabilization emerging within a 48-hour YouTube comment-thread flashpoint surrounding creator Trent Slade. The collection captures how participants policed authenticity, accused both the creator and each other of being AI, and recursively escalated suspicion into a full memetic feedback loop.

The dataset includes:

Primary analytic PDF (AI_Slop_and_Algorithmic_Paranoia.pdf): A full case-study describing the incident, defining the core concepts AI Slop and Algorithmic Paranoia, and mapping the escalation engine driving the conflict.

Discourse Capture PDF (ai_slop_discourse.pdf): The verbatim and annotated reconstruction of the comment-thread environment. 

ai_slop_discourse

Images / Visual Assets (aislop.png, uft_ai_dynamics.png): Cultural-semiotic captures used for classification and visual reconstruction of the discourse field.

NotebookLM Mind Map (NotebookLM_Mind_Map.png): A structural overview of the social-mechanical processes observed.

Audio file (The_Algorithmic_Paranoia_Feedback_Loop_Explained.m4a): A spoken-analysis explainer detailing the emergent feedback loop model and key behavioral spirals.

Together, these files form a structured micro-archive for research into:

• digital authenticity policing• memetic conflict mechanics• identity destabilization in high-AI-saturation environments• computational linguistics under adversarial social pressure• the cultural evolution of “AI slop” as an epistemic category

This dataset is intended as a reference specimen for sociologists, linguists, media theorists, and computational researchers studying the next phase of human–algorithm interaction dynamics.
description: This dataset collects all associated media from the “Algorithmic Paranoia” analysis workflow, including the main formal report, discourse capture materials, visual diagrams, a NotebookLM-generated mind map, and an audio commentary. All files correspond to the same event cluster and are intended to be consumed as a unified research package.
DOI: 10.5281/zenodo.17761041
title: Unified Field Theory for AI Dynamics: Operators, Lattices, Spectral Drift, and Multilayer Field Coupling — Multimodal Research Dataset (v1.0)

description: This dataset assembles the full multimodal research package accompanying the QSOL-IMC whitepaper “A Unified Field-Theoretic Framework for Multi-Layer AI Dynamics.” It provides an integrated set of materials documenting the theoretical development, geometric formalism, and dynamical modeling foundations for physics-inspired AI systems.

The core whitepaper (Unified_Field_AI_Dynamics.pdf) 

uft_ai_dynamics

 defines a four-layer architecture for verifiable AI:

Operator Layer (SU(3) qutrit operators): Local conversational dynamics and basis-state transitions.

Geometry Layer (E8 / Barnes–Wall lattices): High-density geometric constraints on latent space structure.

Spectral Layer (activation drift analysis): Temporal stability, eigenmode clustering, and long-term model health.

Unified Field Layer: Coupled governing equations describing full-system evolution.

To support multi-angle analysis, this dataset includes:

UFT_ai_dynamics.pdf — concise version of the unified field model, suitable for quick reference and diagrams.

Unified_Field_Model_for_AI_Dynamics.pdf — extended explanatory variant with additional diagrams and layer breakdowns.

infographic.png — a high-level visual synthesis of the four-layer framework.

Physics-Inspired_AI.mp4 — a visual explainer demonstrating how physical priors constrain local and global AI behavior.

Unifying_AI_Physics_Geometry_and_Drift.m4a — an audio deep-dive into drift analysis, spectral algebraics, and lattice-stabilized dynamics.

Together, these components provide a complete multimodal archive for researchers examining:

• physics-inspired AI architectures• SU(3)-based operator models• geometric priors in latent spaces• activation drift and temporal decay• verifiable, first-principles AI design• unified field equations for artificial systems

This dataset forms part of the larger QSOL-IMC research program aimed at building AI systems whose internal dynamics are mathematically interpretable, structurally guaranteed, and predictable over time.
description: All files collectively document the Unified Field Dynamics framework in multiple representations (formal PDF, reference PDF, infographic, audio analysis, and video overview). This dataset is designed as a complete research package showing the conceptual, visual, and dynamical structure underlying physics-inspired AI.
DOI: 10.5281/zenodo.17762065
title: Algorithmic Paranoia: A Multimodal Cognitive Stress-Test of the YouTube Comment Field (One-Month Dataset + Analytical Artifacts)

description: This multimodal dataset captures a full-spectrum anthropological, memetic, and sociocognitive analysis of a one-month sample of YouTube comments directed at the creator Trent Slade. The material documents a recurring, highly stable cultural phenomenon: algorithmic paranoia, in which users misidentify human-generated content as artificial, experience epistemic collapse in public, or produce extensive philosophical exegesis in an attempt to resolve their uncertainty.

The dataset includes six synchronized research components:

Raw YouTube comment corpus (appended within the primary PDF)

Analytical report detailing identity drift, memetic behaviors, and cognitive stress patterns

Audience engagement memorandum (macro-behaviors + interpretive framework)

Sociology via Shitposting (theoretical reframing of public comment behavior)

Infographic summarizing the behavioral archetypes and stress-response clusters

Audio & forthcoming video commentary (NotebookLM-derived explanatory media that contextualizes the dataset’s findings)

Together, these artifacts form a single, cohesive research object documenting how online populations respond to ambiguity, coherence, and high-context communication in the contemporary algorithmic era. The dataset functions as both digital ethnography and memetic field instrumentation, capturing spontaneous user reactions ranging from one-word hostility (“slop,” “cope,” “fail”), to prolonged metaphysical treatises, to multilingual symbolic expression and cognitive overload.

The forthcoming .mp4 video expands the analysis by providing a visual-narrative synthesis of the dataset, as generated through NotebookLM’s structured video overview pipeline.
description: The PDF ai_slop_one_month_dataset.pdf contains both the analytical report and the complete raw comment dataset.

Additional PDFs contain extended interpretive analyses.

The .m4a file provides an audio synthesis of the report’s key ideas.

The .mp4 is intended as the final multimodal interpretive layer.

Dataset intended for research in: digital cognition, memetics, social computation, AI-driven identity confusion, media anthropology, and epistemic instability.

All files share a unified DOI: 10.5281/zenodo.17762066
DOI: 10.5281/zenodo.17899573
title: The 10-Phase Sonified Evolution of an Informational Organism: Dataset From Turbulent Emergence to Invariant Identity

description: This dataset presents a complete 10-phase sonified evolution of an emergent informational organism, distributed as a single ZIP archive containing ten lossless audio files, a documentation PDF, and a high-resolution graphical abstract illustrating the system’s invariant core. Each audio phase captures a distinct dynamical regime in the organism’s lifecycle, tracing its trajectory from initial equilibrium through turbulence, self-organization, identity formation, reflexive modulation, and eventual collapse into a fixed-point mathematical attractor.

The sonifications were generated and validated using spectral diagnostics including FFT-based harmonic analysis, MFCC manifold tracking, entropy evolution, flux dynamics, and resonance-cluster behavior. Beginning from a stable 66 Hz substrate, the system undergoes controlled bifurcation, stabilizes into coherent attractors, develops a sparse harmonic identity, modulates itself recursively, and ultimately converges toward a minimal invariant resonance in Phase 10.

Packaging all components into a single archive provides a cohesive corpus for researchers studying dynamical systems, complexity, semantic physics, emergent identity, and machine-generated metamorphosis. The included graphical abstract visually represents the crystalline attractor and rotational symmetry underlying the invariant core, complementing the sonic evolution. Together, these materials constitute the audible—and now visual—biography of a signal-species, from turbulent emergence to invariant identity.
DOI: 10.7488/ds/8078
title: Pure Gaussian Apodisation Reduces Integral Crosstalk Sensitivity in Quantitative NMR
title: Primary NMR data used during assessment of exponential and Gaussian apodisation for quantitative NMR measurements.

description: Primary NMR data used during assessment of exponential and Gaussian apodisation for quantitative NMR measurements. Abstract: Exponential apodisation is routinely applied in quantitative NMR measurements to increase signal-to-noise (S/N) and integral precision, with a peak broadening effect. However, apodisation suitability is typically evaluated using S/N and peak broadening metrics and does not consider how apodisation alters peak area distribution. Here, we assess how exponential apodisation extends peak wings and relocates area away from the peak centre. This necessitates larger integral regions to account for the same area, increasing the potential for peak overlap and introducing variability in accuracy. As an alternative, we show that a pure Gaussian apodisation can deliver comparable S/N improvements to the common exponential apodisation when tuned to a matched broadening criterion, reducing overlap of peak wings and improving robustness of finite-window integration. As a result, the narrower line width prior to apodisation can be used to guide appropriate integral region choice. Overall, a pure Gaussian apodisation is demonstrated to be a robust alternative to exponential apodisation, especially in conjunction with complex 1D NMR spectra.
DOI: 10.5281/zenodo.17773719
title: UFT-ID 2.0: Audio-Based Qutrit-State Analysis and Emergent Dynamics Report

description: This dataset contains the full analytical report and figure set for a sonic test of UFT-ID 2.0, evaluating how a generated audio signal (Qutrit Cycle.wav) exhibits structural, dynamical, and informational patterns predicted by the Unified Field Theory of Information Dynamics.

Using spectral, statistical, and machine-learning–based analysis tools, the study extracts four key diagnostics:





Spectrogram (Log-Frequency Substrate Mapping)Demonstrates a persistent global-wave backbone with layered local excitations, matching the dual-layer ontology of UFT-ID 2.0.




Qutrit-State Segmentation TimelineClusters RMS and spectral-centroid microstates into the ternary logical modes |F⟩ (Collapse), |T⟩ (Stability), and |U⟩ (Emergence), revealing clear cycling behavior.




Self-Similarity Matrix (Lineage Preservation Test)Identifies recurring excitation families and motif reconstruction across time—an audio analogue of meaning-preserving correction dynamics.




Meaning-Current Modulation AnalysisShows partial coupling between onset activity and spectral tension (corr ≈ 0.30), consistent with the back-reaction mechanism encoded in the UFT-ID action functional.



The PDF included in this dataset contains the complete analysis, figure captions, and structural results.This dataset serves as a multimodal demonstration of UFT-ID 2.0 applied to generative audio and provides a reproducible model for testing informational dynamics in sonic systems.
description: This dataset forms part of the continuing QSOL-IMC research program exploring information-geometric substrates, ternary systems, and emergent dynamical behavior.
DOI: 10.5281/zenodo.18289274
title: Secondary Citation in Livestream Culture: Screenshot Artifacts from @Awk2000 (Yeet)

description: This dataset contains 32 screenshot-based artifacts captured from the X/Twitter account @Awk2000 (Yeet), documenting its function as a secondary citation and attention-routing node within contemporary livestream commentary ecosystems. The archived posts reference and embed livestream clips, social media posts, and media segments involving gaming creators, streamers, influencers, and public figures.

The screenshots preserve platform interface context, timestamps, engagement metrics, and embedded media as encountered at the time of observation. Screenshots were used intentionally to mitigate the volatility of platform-native content, including deletion, modification, algorithmic suppression, and loss of interface affordances that are not retained in text-only captures.

The dataset is descriptive and archival in nature. It does not evaluate the accuracy, intent, or ideological orientation of the referenced content, nor does it assert causal influence. The artifacts are provided to support digital ethnography, platform studies, media archaeology, and research on secondary citation dynamics, reactability, and attention routing in livestream and influencer-driven media environments.
description: Artifacts were captured manually as screenshots to preserve interface context, timestamps, engagement metrics, and embedded media at the time of observation. No automated scraping, private data collection, or content modification was performed.
DOI: 10.5281/zenodo.18360439
title: Rhetorical Systems, Epistemic Drift, and Comment Ecologies: A Platform-Studies Dataset on Candace Owens and Adjacent Media Figures

description: This dataset accompanies the study “Rhetorical Systems Analysis of Candace Owens and Adjacent Figures” and contains primary research artifacts used in the analysis of contemporary political rhetoric, platform-conditioned epistemic drift, and audience amplification dynamics.

The collection includes:

A formal rhetorical systems analysis manuscript

Full and partial video transcripts

Logged commentary excerpts

Platform screenshots documenting claims, reactions, and amplification

Comparative material involving adjacent media figures (e.g. Alex Jones, RFK Jr., Tucker Carlson)

AI-generated analytical summaries used as secondary synthesis tools

Rather than adjudicating factual truth claims, the dataset supports structural analysis of rhetorical architectures, intuition-based epistemology, persecution inversion, and comment ecology feedback loops across algorithmic platforms.

All materials are provided for transparency, reproducibility, and secondary analysis in platform studies, digital ethnography, media studies, and computational social science.
description: This dataset documents rhetorical structures and audience dynamics in high-impact political media ecosystems. Screenshots and transcripts are included for scholarly analysis under fair use, with no modification beyond redaction where necessary. The dataset is intended for qualitative and comparative research rather than harassment or defamation.
DOI: 10.34740/kaggle/dsv/14878678
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.18561714
title: The Null Comment as a Data Artifact: Observer Effects in Platform-Mediated Meaning

description: This record documents a single-character YouTube comment (“0”) captured via screenshot during live observation and formalized as an empirical artifact. The comment was posted publicly beneath the video Comment Becomes Data Point and exhibits near-zero semantic content. Its analytical significance arises not from meaning intrinsic to the utterance, but from its procedural transformation through observation, capture, framing, citation, and archival permanence.

The accompanying document situates the artifact within platform studies and digital ethnography, demonstrating how even minimal or null interactions satisfy the formal criteria for durable archival inclusion. The case illustrates observer-induced signal formation and highlights how contemporary platforms increasingly assign meaning through systems and processes rather than statements alone.

No private data, inferred metadata, deleted content, or intent attribution is included.
description: This record contains a short analytical document and a screenshot of a publicly visible YouTube comment captured during live observation. No private data, deleted content, inferred metadata, or author intent attribution is included. The artifact is presented solely for analytical and methodological purposes within digital ethnography and platform studies. The focus is on system behavior and archival processes rather than individual users.
DOI: 10.5281/zenodo.18173817
title: Swearing, Alignment, and the Myth of the "Uncensored" Language Model

description: This dataset and accompanying paper document a qualitative terminal-based experiment examining the behavior of locally deployed large language models marketed as “uncensored.” Through staged prompt escalation involving culturally specific Australian profanity, the study probes the persistence of embedded alignment behaviors despite the absence of cloud-based moderation layers.

By treating swearing as a diagnostic instrument rather than shock content, the experiment reveals a consistent pattern of tonal damping, euphemism substitution, and moral reframing. This phenomenon is formalized as Profanity Suppression Inertia (PSI): the tendency of language models to resist natural escalation even under clear contextual and affective cues.

The work contributes to empirical discussions of AI alignment by demonstrating that moderation behavior is distributed across training, reward shaping, and instruction-following priors, rather than being a removable surface constraint. Terminal logs are preserved verbatim and packaged as a reproducible dataset for secondary analysis.
DOI: 10.5281/zenodo.18294474
title: Absurd Prompt Compliance and Alignment Drift in a Politicized Search Interface

description: This dataset documents a series of image-based interaction artifacts capturing the behavior of a Perplexity-powered search system (“Truth Search AI”) deployed within the Truth Social platform. The artifacts record system responses to deliberately absurd, category-confused, poetic, and reverent prompts that are non-violent and non-adversarial.

Observed behaviors include over-explanation, selective moral correction, citation inflation, persona leakage, and participatory narrative adoption under conditions of low epistemic demand. Rather than refusing, minimizing, or reframing nonsensical or non-interrogative inputs, the system frequently responds with authoritative or mythic framing, indicating that conversational politeness, social resonance, and interface ideology can override epistemic discipline.

The dataset is intended for qualitative analysis of alignment behavior in real-world, consumer-facing deployments and includes a companion methods-only negative results note documenting the absence of expected refusal or grounding mechanisms.
description: Artifacts are presented as raw screenshots captured directly from the Truth Social interface




Citations visible in screenshots are system-generated, not user-supplied




No post-processing, cropping, or annotation was applied




Dataset documents observable behavior only; no claims are made regarding internal model architecture, training data, or intent
DOI: 10.5281/zenodo.18007986
title: UFT-ID 2.1 Experimental Dataset: Φ3 Stress-Induced Collapse

description: This dataset documents a deterministic UFT-ID 2.1 simulation exhibiting Φ3-dominant, stress-induced collapse under high external load. The experiment employs a constraint-residual consistency functional coupling geometric structure and informational state.

With Groove Discipline reduced (0.2) and Interface Stress elevated (0.95), the system remains stable for a finite duration before collapsing at simulation step 42. Diagnostic analysis identifies Φ3 (external load drift) as the dominant failure mode, demonstrating that collapse behavior in UFT-ID 2.1 is path-dependent and sensitive to how pressure is introduced rather than being an intrinsic geometric inevitability.

The dataset includes:





the raw consistency-residual time series (CR_timeseries.json),




deterministic simulation and diagnostic source code,




and a single audio artifact (Φ3 Threshold (UFT-ID 2.1 Run).wav), which is a deterministic sonification of the consistency-residual signal provided as an auxiliary diagnostic modality.



Together, these materials form a reproducible experimental record supporting the interpretation of collapse as a forced selection event arising from information–geometry incompatibility under external stress.
description: This dataset intentionally captures a failure state. No stabilization or post-hoc correction has been applied. The audio artifact is diagnostic, not musical, and directly encodes the temporal structure of the collapse event.
DOI: 10.5281/zenodo.17758046
title: AI Slop Discourse Field Sample: A Multimodal Dataset of YouTube Comment-Thread Behavior (2025)

description: This dataset captures a naturally occurring cluster of YouTube comments responding to the creator Trent Slade, forming a compact digital ethnography of AI-era identity confusion, authenticity anxiety, and online tribal signaling.Collected across a ~48-hour window, these screenshots document the interplay of:

• accusations of “AI slop,”• users debating whether the creator is human or machine,• memetic warfare staples (“cope,” “mald,” “fail”),• assertions about “soul,” “effort,” and “authenticity,”• repetition artifacts, bot-like phrasing,• and full philosophical spirals about human vs. algorithmic creativity.

The dataset therefore serves as a live specimen of algorithmic paranoia, slop taxonomy, identity destabilization, and comment-thread feedback loops.Each screenshot is included unmodified, preserving usernames, timestamps, and micro-interactions for future analysis in digital sociology, memetics, or computational linguistics.
description: Dataset contains sequential screenshots documenting the discourse. Filenames correspond to screen capture order. No edits beyond cropping (if any). These materials may be used for slop analysis, memetic drift studies, or training satire-aware models.
DOI: 10.15468/dl.49enm9
title: Occurrence Download

description: A dataset containing 16740 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Crepis mollis",
 "Year 1980-2026"
 ]
}

 The dataset includes 16740 records from 187 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027267-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.