{"id":"W2150113369","doi":"10.1002/qua.20745","title":"Using symbolic computing in building probabilistic models for atoms","year":2005,"lang":"en","type":"article","venue":"International Journal of Quantum Chemistry","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Probabilistic logic; Formalism (music); Wave function; Atom (system on chip); Beryllium; Hydrogen atom; Statistical physics; Computer science; Physics; Quantum mechanics; Group (periodic table); Artificial intelligence","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":[0.001836428,0.0008807771,0.001292642,0.001504191,0.0009739088,0.002705013,0.001525343,0.0009374812,0.003622518],"category_scores_gemma":[0.008591429,0.0004762709,0.001308437,0.001458207,0.003324418,0.003155824,0.002162915,0.001398975,0.0005633195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001667986,"about_ca_system_score_gemma":0.001544466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002628159,"about_ca_topic_score_gemma":0.002862714,"domain_scores_codex":[0.9986573,0.0006400662,0.00006132526,0.0001189394,0.0004321135,0.00009021212],"domain_scores_gemma":[0.9971761,0.002090337,0.0001893683,0.0002983031,0.000171597,0.00007424076],"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":[0.00002080625,0.00001302874,0.000197717,0.00005473787,0.00002044578,0.0000485386,0.00009318021,0.6245863,0.0005269331,0.3641078,0.0002787297,0.01005174],"study_design_scores_gemma":[0.000003485471,0.000005572137,0.00001233361,0.000008402971,0.00000270753,0.000006700071,0.000008017398,0.7949878,0.0002524917,0.2042511,0.0004564558,0.000004837086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0203355,0.0001572468,0.9749395,0.0003319211,0.0000234689,0.00003145575,0.0001011933,0.0003653103,0.003714289],"genre_scores_gemma":[0.6080109,0.0005017677,0.3882525,0.0001298237,0.00006818274,0.0002487081,0.0002914174,0.0002470476,0.002249681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003622518,"threshold_uncertainty_score":0.01211858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04019996082946911,"score_gpt":0.3397471126021403,"score_spread":0.2995471517726712,"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."}}