{"id":"W2945480173","doi":"10.1149/2.1051908jes","title":"Analysis of Thousands of Electrochemical Impedance Spectra of Lithium-Ion Cells through a Machine Learning Inverse Model","year":2019,"lang":"en","type":"article","venue":"Journal of The Electrochemical Society","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lithium (medication); Computer science; Artificial neural network; Electrical impedance; Equivalent circuit; Inverse; Process (computing); Ion; Software; Biological system; Algorithm; Electronic engineering; Machine learning; Chemistry; Electrical engineering; Voltage; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004440905,0.0007888558,0.000707375,0.001036704,0.0002739551,0.0007272748,0.0007700477,0.0007882508,0.001164769],"category_scores_gemma":[0.001544058,0.0003117655,0.0007988395,0.000821791,0.0002348029,0.001049666,0.000426894,0.0007946724,0.0008417263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004318735,"about_ca_system_score_gemma":0.0005450659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002718127,"about_ca_topic_score_gemma":0.003585125,"domain_scores_codex":[0.9997347,0.00002799126,0.0000186901,0.00009425885,0.0001082101,0.00001608848],"domain_scores_gemma":[0.9996328,0.00013416,0.00004203185,0.00007770556,0.0001004614,0.00001279721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000223633,0.0002919232,0.008754924,0.0003710253,0.0001960826,0.000394795,0.0002795685,0.3715621,0.1203029,0.00201309,0.003519106,0.4920909],"study_design_scores_gemma":[0.000007140154,0.00004373716,0.002427639,0.000009646909,0.00001537141,0.0001278807,0.00003262331,0.9766088,0.01726903,0.001623553,0.001815151,0.00001949882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1083298,0.0002811023,0.884364,0.0002045712,0.00003682641,0.00006152812,0.0006151372,0.004778893,0.00132808],"genre_scores_gemma":[0.5911719,0.0003852798,0.4016373,0.0001138321,0.00003470186,0.0001977265,0.003070614,0.000226258,0.00316238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002718127,"threshold_uncertainty_score":0.005404651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008173864861577689,"score_gpt":0.245873893904802,"score_spread":0.2377000290432243,"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."}}