{"id":"W2500230478","doi":"10.1142/9789812778161_0006","title":"CALCULATION OF VERTICAL IONIZATION POTENTIALS USING A DENSITY FUNCTIONAL TOTAL-ENERGY DIFFERENCE APPROACH","year":2002,"lang":"en","type":"book-chapter","venue":"Recent advances in computational","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ionization; Energy density; Energy (signal processing); Atomic physics; Physics; Computational physics; Mathematics; Statistics; Engineering physics; Ion; Quantum mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001215939,0.0001974789,0.0002953963,0.0001121417,0.00008373171,0.00001755222,0.00008772294,0.0001438965,0.0005302792],"category_scores_gemma":[0.0000233047,0.0002011991,0.00009650471,0.0001264536,0.0001511002,0.0001689539,0.00009427928,0.0001341308,0.00001471394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003484902,"about_ca_system_score_gemma":0.00001767435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003352178,"about_ca_topic_score_gemma":0.000002481068,"domain_scores_codex":[0.998175,0.00005684227,0.0004853267,0.0004000209,0.0007355887,0.0001472812],"domain_scores_gemma":[0.9994939,0.00008049975,0.0001866468,0.0001217113,0.00006300962,0.00005421475],"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":[0.00001913755,0.00009039952,0.0022984,0.00002222964,0.00002356389,0.000001678539,0.00003294525,0.9770028,0.0001653924,0.007943993,0.00002261287,0.01237687],"study_design_scores_gemma":[0.0004570285,0.00003587741,0.01679629,0.0001811427,0.0001060225,0.00001745533,0.000006412591,0.9180036,0.0002405899,0.06047553,0.00316169,0.0005183494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01671927,0.001048248,0.9712439,0.00008259131,0.0004129172,0.0001567082,0.00001880433,0.00003591023,0.01028172],"genre_scores_gemma":[0.9610392,0.001177299,0.01967579,0.00003411436,0.0003248705,0.000007687548,0.0007448063,0.00004609856,0.01695009],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9515681,"threshold_uncertainty_score":0.8204661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03827627260018048,"score_gpt":0.2535035002239011,"score_spread":0.2152272276237206,"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."}}