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Record W4353004775 · doi:10.30973/progmat/2022.14.1/7

Esquema para autenticación y validación de documentos electrónicos mediante una autoridad certificadora

2022· article· es· W4353004775 on OpenAlexaff
Yair Alejandro Ponciano Santiago, Rogelio Enrique Telona Torres, Juan Rafael González Cadena

Bibliographic record

VenueProgramación matemática y software · 2022
Typearticle
Languagees
FieldSocial Sciences
TopicData Privacy and Cybersecurity
Canadian institutions123 Certification (Canada)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Hoy en día los medios digitales son susceptibles de substitución, modificación, y replicación, a menos que estén explícitamente protegidos con el objetivo de que se pueda confiar en este medio de comunicación. En este contexto en el TecNM campus San Andrés Tuxtla es necesario la implementación de un esquema para la validación y autenticación de documentos con la finalidad de: a) la disminución del consumo del papel, b) agilizar el proceso para emisión-recepción y c) la autenticidad de los documentos creados. El presente trabajo describe cómo implementar una Autoridad Certificadora que permite crear y controlar los certificados emitidos por la misma, así como la firma de los documentos del instituto.

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)0.018
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.018
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.004
Scholarly communication0.0090.010
Open science0.0030.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0080.005

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 head0.024
GPT teacher head0.337
Teacher spread0.313 · 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 designNot applicable
Domainnot available
GenreMethods

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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