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Record W7164937836 · doi:10.5281/zenodo.20716232

U Trio (USL-5UE-URF Trio) as a socio-economic-environmental karma system that leads us rapidly to the sustainable, resource- based, renewable energy-based, circular economy overcoming the top 5 most critical global crises or challenges (Draft 1)

2015· article· en· W7164937836 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInnovation, Sustainability, Human-Machine Systems
Canadian institutionsHyperion Technologies (Canada)
Fundersnot available
KeywordsKarmaGlobal imbalancesGovernment (linguistics)Renewable energyEmerging markets

Abstract

fetched live from OpenAlex

This paper is for overco ming the TOP 5 most critical global crises or challenges of our time for 5 Es (in Education, Economy, Energy, Environment, and Equality), all simultaneously within next 20 -25 years or so with the back up plans lining up one after another with the USL 2, 3, 4, 5+ (depending on the monitored progress of the nations around the world). We first briefly describe what USL, 5UEs, and URF Trio are and then give the brief summary of the solutions in terms of the total costs and the time frames to complete the resolu tions. 2 Tabla de contenido ABSTRACT ................................ ................................ ................................ ................................ ........ 1

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.860
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.000
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 head0.048
GPT teacher head0.290
Teacher spread0.242 · 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