{"id":"W3155023328","doi":"10.1140/epjb/s10051-022-00296-y","title":"Variational autoencoder analysis of Ising model statistical distributions and phase transitions","year":2022,"lang":"en","type":"article","venue":"The European Physical Journal B","topic":"Theoretical and Computational Physics","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Autoencoder; Ising model; Statistical physics; Statistical model; Phase (matter); Physics; Mathematics; Statistics; Computer science; Artificial intelligence; Quantum mechanics; Artificial neural network","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":[0.0002593217,0.00008265008,0.0001583255,0.00004318343,0.0006060165,0.00004139744,0.0001460443,0.000002706753,0.0001542657],"category_scores_gemma":[0.000004534727,0.00006103394,0.0001597794,0.0003363145,0.0001488975,0.00006345004,0.00008161451,0.0002997393,0.000003145455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001404955,"about_ca_system_score_gemma":0.00003941142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001934184,"about_ca_topic_score_gemma":3.149299e-8,"domain_scores_codex":[0.9989433,0.0003629739,0.0002004058,0.0001075636,0.0002637396,0.0001219697],"domain_scores_gemma":[0.9994544,0.0002165326,0.00009705318,0.00008875647,0.00006304577,0.000080217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001918704,0.0004667645,0.00002093026,6.636343e-7,0.0003506152,0.000001398962,0.0004706293,0.2914077,0.0003295047,0.6989799,0.0001958736,0.007756849],"study_design_scores_gemma":[0.0002593878,0.0000365669,0.0009708809,0.00000117374,0.0004723835,0.00000218762,0.0001009661,0.5351524,0.000006712105,0.4629178,0.00002806401,0.00005156083],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1023769,0.000005064678,0.8890267,0.0005233853,0.00002260862,0.00003910955,0.001572485,0.000007702326,0.006426038],"genre_scores_gemma":[0.9983066,2.040812e-7,0.001156779,0.00003865476,0.0002753441,0.000002571441,0.0001867359,0.000008685295,0.00002443094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8959297,"threshold_uncertainty_score":0.4661051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076063375439506,"score_gpt":0.2670491802102377,"score_spread":0.2562885464558426,"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."}}