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Record W4214744496 · doi:10.14704/nq.2022.20.2.nq22019

The Development of a Quantum-based Ontology for the Description of the Reality Experienced in NDEs by Using Computerized NLP Analytics

2022· article· en· W4214744496 on OpenAlexaff
Raul Valverde, Chet Swanson

Bibliographic record

VenueNeuroQuantology · 2022
Typearticle
Languageen
FieldPsychology
TopicParanormal Experiences and Beliefs
Canadian institutionsConcordia University
Fundersnot available
KeywordsOntologyConsciousnessComputer scienceUpper ontologyQuantumProcess ontologyCognitive scienceNarrativeArtificial intelligenceEpistemologyPsychologySemantic WebLinguisticsPhysicsPhilosophyQuantum mechanics

Abstract

fetched live from OpenAlex

According to the survival hypothesis, a person's personality and consciousness survive the death of the physical body. Ontology is a well-established theoretical branch of philosophy concerned with representations of reality. This research proposes the use of computer natural language processing (NLP), databases, structured query language and near-death experiences (NDEs) narratives to develop a quantum ontology based on the quantum hologram theory of physics and consciousness. This research proposes the use of a quantum ontology to represent the incomprehensible aspects of near-death experiences. The research demonstrates how to validate ontology constructs within a quantum ontology, demonstrating the methodology's potential for the development of a consciousness model based on the quantum paradigm.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0020.006
Scholarly communication0.0050.014
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.147
GPT teacher head0.380
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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