
This article develops the hypothesis that predictive models do not merely anticipate the future—they structurally replace it through executable grammatical mechanisms. It introduces the concept of algorithmic colonization of time, and formalizes anticipation as a non-agentive syntactic operation that converts temporal openness into optimized output sequences. The proposal is original, falsifiable, and structurally differentiated from the existing academic corpus. A mirrored version of this article is also available on Figshare for redundancy and citation indexing purposes: [DOI: 10.6084/m9.figshare.29247128]
Este artículo desarrolla la hipótesis de que los modelos predictivos no solo anticipan el futuro: lo sustituyen estructuralmente mediante mecanismos gramaticales ejecutables. Se introduce el concepto de colonización algorítmica del tiempo, y se formaliza el proceso de anticipación como una operación sintáctica no-agentiva que convierte la apertura temporal en una secuencia optimizada de outputs. La propuesta es original, falsable, y estructuralmente diferenciada del corpus previo.
Classification--Books--Linguistics, Artificial intelligence, Artificial Intelligence/legislation & jurisprudence, Applied linguistics--Data processing, Causative (Linguistics), Artificial Intelligence/economics, Linguistics/legislation & jurisprudence, Artificial Intelligence/standards, Linguistics/ethics, Linguistics/history, Applied linguistics--Research, Cohesion (Linguistics), Artificial Intelligence, Machine learning, Machine learning--Experiments, Comparative linguistics, Linguistics/organization & administration, Artificial Intelligence/trends, Categorization (Linguistics), Linguistics/trends, Linguistics/standards, Artificial Intelligence/ethics, grammars of power, Linguistics/economics, Linguistics/methods, Classifiers (Linguistics)--Data processing, Linguistics, Linguistics/classification, Linguistics/organization & administration, Machine learning--Technique, Linguistics/education, Artificial Intelligence/legislation & jurisprudence, Classifiers (Linguistics), Ensemble learning (Machine learning), Linguistics/legislation & jurisprudence, Applied linguistics--Statistical methods, Componential analysis (Linguistics), Artificial Intelligence/classification, Machine learning--Evaluation, FOS: Languages and literature, Linguistics/instrumentation, Competence and performance (Linguistics)
Classification--Books--Linguistics, Artificial intelligence, Artificial Intelligence/legislation & jurisprudence, Applied linguistics--Data processing, Causative (Linguistics), Artificial Intelligence/economics, Linguistics/legislation & jurisprudence, Artificial Intelligence/standards, Linguistics/ethics, Linguistics/history, Applied linguistics--Research, Cohesion (Linguistics), Artificial Intelligence, Machine learning, Machine learning--Experiments, Comparative linguistics, Linguistics/organization & administration, Artificial Intelligence/trends, Categorization (Linguistics), Linguistics/trends, Linguistics/standards, Artificial Intelligence/ethics, grammars of power, Linguistics/economics, Linguistics/methods, Classifiers (Linguistics)--Data processing, Linguistics, Linguistics/classification, Linguistics/organization & administration, Machine learning--Technique, Linguistics/education, Artificial Intelligence/legislation & jurisprudence, Classifiers (Linguistics), Ensemble learning (Machine learning), Linguistics/legislation & jurisprudence, Applied linguistics--Statistical methods, Componential analysis (Linguistics), Artificial Intelligence/classification, Machine learning--Evaluation, FOS: Languages and literature, Linguistics/instrumentation, Competence and performance (Linguistics)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
