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Record W3081505093

Creación de una estrategia de marketing digital para el lanzamiento del software médico Companyon en personas que laboran de forma independiente en el área de la salud en Vancouver, Canadá

2020· dissertation· es· W3081505093 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venueinstname:Universidad Autónoma de Occidente · 2020
Typedissertation
Languagees
FieldSocial Sciences
TopicAdvertising and Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPersonaPolitical scienceCartographyGeographyArt
DOInot available

Abstract

fetched live from OpenAlex

El objetivo de este proyecto es disenar una estrategia de marketing digital para la empresa CompanyOn, la cual ejecuta su operacion en la ciudad de Vancouver en Canada, con el fin de realizar el lanzamiento del software medico de gestion clinica pensado para el uso de los profesionales del area de la salud que laboran de manera independiente, para que puedan administrar y ejecutar su labor clinica de una forma simple y sencilla. A nivel metodologico se ha planteado una estrategia basada en el conocimiento del ecosistema digital, esta se basa en la generacion de contenido de valor para el cliente por medio de los diferentes canales de medios digitales. Dicha estrategia tendra una duracion de seis meses, con el fin de permitir al consumidor interactuar con el contenido y generar trafico al sitio web para producir acciones que se traduzca en engagement

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.312
Teacher spread0.302 · 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