{"id":"W6949504189","doi":"10.5281/zenodo.16429971","title":"Deep Neural Control Module (DNCM) AI-Driven Adaptive Deep Learning Control Framework for Islanded DC Microgrids in Space Habitats and UAVs","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"NASA Deep Space Network; Deep learning; Photovoltaic system; Space (punctuation); Power (physics); Control (management); Artificial neural network; Microgrid","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004120254,0.0005289906,0.0003894906,0.0001914121,0.000226211,0.0005428668,0.001042725,0.0006642647,0.002912428],"category_scores_gemma":[0.0006001318,0.0001978983,0.0003667558,0.0002270765,0.0003753813,0.0003631015,0.0007943427,0.001095823,0.0003518929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000712295,"about_ca_system_score_gemma":0.001075845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01219602,"about_ca_topic_score_gemma":0.01531476,"domain_scores_codex":[0.9998875,0.0000198567,0.000005397314,0.00002944351,0.00003257409,0.00002527966],"domain_scores_gemma":[0.99985,0.00004494341,0.00001479661,0.00001385675,0.00006198217,0.00001443016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003075221,0.00003942633,0.0002546372,0.00004170856,0.0000223958,0.00003086456,0.00001553864,0.9371335,0.001849999,0.007317348,0.001482227,0.05178167],"study_design_scores_gemma":[0.000001638487,0.000008376569,0.00002232525,0.000001771664,0.00000158038,0.0000020205,8.875269e-7,0.9987381,0.0001878755,0.0007901515,0.0002443043,9.33165e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01352835,0.0004307101,0.9780245,0.0003235195,0.0000989451,0.00003966932,0.0001017173,0.0007379139,0.006714729],"genre_scores_gemma":[0.8688719,0.0003173167,0.1189429,0.0003458528,0.00007106194,0.0002111778,0.0002387654,0.00007552258,0.01092549],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01219602,"threshold_uncertainty_score":0.02425003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00863287966186867,"score_gpt":0.2120797245478464,"score_spread":0.2034468448859777,"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."}}