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oai:figshare.com:article/34049210 2026-10-01T17:44:21Z category_146 category_734 category_931 category_811 portal_5 item_type_1 month_year_10_2026

<p>Forecasts of the Coupled prompt with covariate integration versus the No-Covariate prompt across datasets, forecast horizons, and covariates for both validation and test sets.</p> Mohammadmahdi Ghasemloo (25157978) Alireza Moradi (657965) Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified Mathematical Sciences not elsewhere classified sparked growing interest representative prompting strategies reducing prediction errors leveraging auxiliary knowledge large language models conduct sensitivity analyses time series forecasting appropriate prompt design prompt design informed forecasting incorporating time prompt structure xlink "> work explores wide range use gpt service operations rapid adoption quantify uncertainty proposed framework incorporating covariates including applications findings underscore existing approaches dependent covariates censored settings analysis reveals <p>Forecasts of the Coupled prompt with covariate integration versus the No-Covariate prompt across datasets, forecast horizons, and covariates for both validation and test sets.</p> 2026-10-01T18:00:03Z Image Figure 10.1371/journal.pone.0358970.g002 https://figshare.com/articles/figure/_p_Forecasts_of_the_Coupled_prompt_with_covariate_integration_versus_the_No-Covariate_prompt_across_datasets_forecast_horizons_and_covariates_for_both_validation_and_test_sets_p_/34049210 CC BY 4.0