{"id":"W4391463244","doi":"","title":"Density functional with full exact exchange, balanced nonlocality of correlations, and constraint satisfaction","year":2024,"lang":"en","type":"article","venue":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","topic":"Advanced Algebra and Logic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Chemistry; Los Alamos National Laboratory; National Nuclear Security Administration; Natural Sciences and Engineering Research Council of Canada; Division of Materials Research; U.S. Department of Energy; National Science Foundation","keywords":"Quantum nonlocality; Constraint (computer-aided design); Constraint satisfaction problem; Constraint satisfaction; Mathematics; Statistical physics; Physics; Quantum mechanics; Statistics; Geometry; Quantum entanglement; Quantum","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":[0.0003241357,0.0001148185,0.0001893242,0.0001795672,0.0001204623,0.00007794053,0.0001076009,0.00006683096,0.00002433757],"category_scores_gemma":[0.0000396484,0.00009020964,0.0000394279,0.0004439601,0.0005614163,0.001155668,0.0001075662,0.00008145726,0.000002496331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002511398,"about_ca_system_score_gemma":0.00009863683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001686356,"about_ca_topic_score_gemma":0.00002990464,"domain_scores_codex":[0.9988617,0.00002220576,0.0004092581,0.0002166261,0.0003635239,0.0001267043],"domain_scores_gemma":[0.9991324,0.000162955,0.0002053239,0.0002174689,0.0002080836,0.00007377825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001323289,0.000125186,0.00507284,0.000308531,0.00006330477,0.000002829216,0.00002401328,0.0007719321,0.00339448,0.9546103,0.0008291979,0.03466504],"study_design_scores_gemma":[0.001307438,0.00105305,0.9527393,0.0004193976,0.0001028724,0.0002918665,0.00003606907,0.01176232,0.008275803,0.01438828,0.009073414,0.000550164],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2215494,0.00020895,0.7744103,0.0001475124,0.0002421196,0.0001250748,0.00004844151,0.00007611282,0.003192064],"genre_scores_gemma":[0.9852462,0.0000416171,0.01445698,0.00003082956,0.000008620605,0.000009820525,0.0001722926,0.000002356134,0.0000312499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9476665,"threshold_uncertainty_score":0.3678642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01178020301173418,"score_gpt":0.2194759330768321,"score_spread":0.2076957300650979,"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."}}