{"id":"W4285196468","doi":"10.1109/tte.2022.3173918","title":"Novel Image-Based Rapid RUL Prediction for Li-Ion Batteries Using a Capsule Network and Transfer Learning","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Transportation Electrification","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Battery (electricity); Computer science; Implementation; Transfer of learning; Preprocessor; Battery pack; Artificial intelligence; Reliability engineering; Machine learning; Simulation; 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":[0.0003336062,0.0005992565,0.0003884649,0.0004883594,0.0001902382,0.0005707075,0.0008333327,0.0005103452,0.001350846],"category_scores_gemma":[0.001010117,0.0001844594,0.0003664898,0.0004025334,0.0002485109,0.001017334,0.0005155455,0.0005481839,0.0003652023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005438368,"about_ca_system_score_gemma":0.0003713709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004478182,"about_ca_topic_score_gemma":0.003850914,"domain_scores_codex":[0.9999022,0.00001233708,0.000004629028,0.00002890173,0.00003391648,0.00001783774],"domain_scores_gemma":[0.9997637,0.00008030613,0.00003076305,0.00002491493,0.00008324817,0.00001701222],"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":[0.0003928727,0.0001721807,0.005393456,0.0001081351,0.00005470668,0.0002351944,0.00009421282,0.5141547,0.02503981,0.002323193,0.00262423,0.4494073],"study_design_scores_gemma":[0.000001675573,0.000019044,0.0002973065,0.000002006585,0.000003881421,0.00001370279,0.000004915377,0.996865,0.002317095,0.0003028923,0.0001691588,0.000003390851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09060361,0.0003802655,0.9049965,0.0001966461,0.00007170767,0.00005114122,0.0001373079,0.001088395,0.002474416],"genre_scores_gemma":[0.901577,0.0003696694,0.09363908,0.00009445137,0.00004183376,0.00007983842,0.000303739,0.00006044582,0.003833851],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004478182,"threshold_uncertainty_score":0.008904219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01926149824181954,"score_gpt":0.2435894760812574,"score_spread":0.2243279778394379,"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."}}