{"id":"W2017049754","doi":"10.1016/j.camwa.2013.11.006","title":"Numerical approximation of time evolution related to Ginzburg–Landau functionals using weighted Sobolev gradients","year":2013,"lang":"en","type":"article","venue":"Computers & Mathematics with Applications","topic":"Numerical methods in engineering","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University; McMaster University","funders":"Higher Education Commission, Pakistan","keywords":"Sobolev space; Mathematics; Mathematical analysis; Energy (signal processing); Applied mathematics; Statistics","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":[0.0001233456,0.0002052228,0.0003073051,0.0002071906,0.00006748262,0.00002951747,0.000207584,0.00007720954,0.00004905753],"category_scores_gemma":[0.00001738026,0.000190393,0.00005272152,0.0008631271,0.00003875732,0.0001473781,0.00003512228,0.0001358122,0.0001818705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001656922,"about_ca_system_score_gemma":0.00001528344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005827666,"about_ca_topic_score_gemma":4.153918e-8,"domain_scores_codex":[0.9988065,0.00002054566,0.000469705,0.0002115255,0.0002458582,0.0002459121],"domain_scores_gemma":[0.9990264,0.0001736808,0.0001067297,0.0003989709,0.0001462309,0.0001480129],"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":[0.00000404912,0.0002213514,0.0001746969,0.0004211252,0.0001924755,3.998542e-7,0.0005383338,0.9471267,0.02404598,0.01171277,0.000666748,0.01489532],"study_design_scores_gemma":[0.0001829724,0.00003025267,0.000373607,0.0001084913,0.00003581147,0.00001619152,0.00002625041,0.985709,0.0008088464,0.01224255,0.0002449082,0.0002210911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02912467,0.00003658996,0.9687744,0.00004561841,0.00008959105,0.001003207,0.000005354112,0.0004037117,0.000516855],"genre_scores_gemma":[0.1937015,0.000002071933,0.8057993,0.00001270938,0.00003432102,0.0003498678,0.00001794903,0.00005438054,0.00002784414],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1645769,"threshold_uncertainty_score":0.7764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009098982427565997,"score_gpt":0.2289672524913798,"score_spread":0.2198682700638138,"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."}}