{"id":"W6977112632","doi":"10.60692/a1sh9-fzc67","title":"Detailed experimentation and prediction of thermophysical properties in lauric acid-based nanocomposite phase change material using artificial neural network","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Phase Change Materials Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Nanocomposite; Viscosity; Nanoparticle; Phase (matter); Mean absolute percentage error; Scanning electron microscope; Lauric acid; Fourier transform infrared spectroscopy; Thermal conductivity","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":[0.0002022425,0.0001345394,0.0002048232,0.0002988433,0.00005596213,0.000104509,0.00006064166,0.00006930038,0.00000811892],"category_scores_gemma":[0.000002950636,0.0001187685,0.0000250683,0.0003324083,0.00002664594,0.0005919843,0.00003093841,0.00004409441,0.00002068937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009123178,"about_ca_system_score_gemma":0.000008799612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008879299,"about_ca_topic_score_gemma":4.437382e-7,"domain_scores_codex":[0.9989412,0.00007679525,0.0004510311,0.00008852969,0.0002063764,0.0002360046],"domain_scores_gemma":[0.9997146,0.000003569249,0.0000803648,0.0001159785,0.00004390955,0.00004163614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001124047,0.00001902662,0.01030961,0.003113235,0.0000580781,0.00001221928,0.08258259,0.05530616,0.8460417,0.00002340927,0.00001250483,0.001397483],"study_design_scores_gemma":[0.0008860815,0.00005148732,0.005767399,0.000157687,0.000007505876,0.000002961963,0.001134864,0.6547855,0.3371206,4.788855e-7,9.213039e-7,0.00008447878],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997683,0.000005630176,0.0007231423,0.000004280918,0.0004746296,0.0006471002,0.0001711131,0.0002768564,0.00001424527],"genre_scores_gemma":[0.9993628,2.056458e-7,0.00004770554,0.000005895698,0.0002329447,0.0002398815,0.0000926951,0.00001735678,4.994093e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5994794,"threshold_uncertainty_score":0.4843239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1446146047184909,"score_gpt":0.2742927100681095,"score_spread":0.1296781053496185,"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."}}