{"id":"W4402945037","doi":"10.1016/j.apenergy.2024.124527","title":"Unified carbon emissions and market prices forecasts of the power grid","year":2024,"lang":"en","type":"article","venue":"Applied Energy","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Agentúra na Podporu Výskumu a Vývoja; European Commission; St. Thomas University","keywords":"Power grid; Grid; Environmental science; Carbon market; Environmental economics; Greenhouse gas; Carbon fibers; Economics; Power (physics); Natural resource economics; Business; Computer science; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006331876,0.0001233745,0.0001130948,0.00005241183,0.00003669723,0.00002234384,0.0001101907,0.00007120785,0.00005614769],"category_scores_gemma":[0.000004663878,0.00008597071,0.00003736066,0.0002240646,0.00003701556,0.00002620178,0.00005845622,0.00009750038,5.7728e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001541163,"about_ca_system_score_gemma":0.00001362249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004711685,"about_ca_topic_score_gemma":0.00003308471,"domain_scores_codex":[0.9994487,0.000006436941,0.0001457983,0.0001325202,0.0001008654,0.0001657237],"domain_scores_gemma":[0.99968,0.00007658826,0.00001616011,0.0001702384,0.000007254455,0.00004972998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005330164,0.00006230563,0.0004092476,0.000851589,0.0005673557,0.00003042406,0.002838148,0.05648209,0.1600593,0.6218587,0.03017634,0.1266113],"study_design_scores_gemma":[0.0004340997,0.00004973016,0.001580312,0.0005405683,0.00009906284,0.00004075958,0.0002597237,0.1355947,0.1747974,0.006664692,0.6791974,0.0007415721],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3626733,0.001765369,0.0002554408,0.00004740003,0.001212568,0.00004653019,0.000009884016,0.0002609019,0.6337286],"genre_scores_gemma":[0.9987789,0.0001175757,0.0001451079,0.00002099437,0.00009855571,0.00001306849,0.000003284805,0.00003178431,0.0007907019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.649021,"threshold_uncertainty_score":0.3505784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005868094616551806,"score_gpt":0.1831957130026488,"score_spread":0.177327618386097,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}