{"id":"W4200034447","doi":"10.1002/eem2.12326","title":"Diagnosing Battery Degradation via Gas Analysis","year":2021,"lang":"en","type":"article","venue":"Energy & environment materials","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Institute of Infection and Immunity; Bundesministerium für Bildung und Forschung","keywords":"Battery (electricity); Degradation (telecommunications); Original equipment manufacturer; Lithium-ion battery; Process engineering; Lithium (medication); Mass spectrometry; Gas analysis; Computer science; Materials science; Chemistry; Engineering; Chromatography; Physics","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":[0.0006404521,0.0008210935,0.0004836831,0.001701092,0.0004332123,0.0007488157,0.0007931851,0.001165765,0.00170965],"category_scores_gemma":[0.001075428,0.0002494967,0.0002818529,0.0008269551,0.0003089142,0.001027383,0.0005435412,0.0004686429,0.00091929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004543272,"about_ca_system_score_gemma":0.0003383677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001482441,"about_ca_topic_score_gemma":0.002772185,"domain_scores_codex":[0.9994386,0.00007802876,0.0000298529,0.0001345997,0.0002735482,0.0000452954],"domain_scores_gemma":[0.9996232,0.000108686,0.0000470589,0.00002881458,0.0001791042,0.00001306801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004076587,0.0001147763,0.01832893,0.0005815278,0.00006506547,0.0004297502,0.0002769314,0.002695448,0.8915221,0.0008280908,0.002019815,0.08272993],"study_design_scores_gemma":[0.00001654071,0.0002714412,0.009490959,0.00006400355,0.0000667166,0.0005410081,0.0004030435,0.03625965,0.9405537,0.001189461,0.01109799,0.00004551117],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7330042,0.01009675,0.2274556,0.0007261469,0.0005053032,0.0005517921,0.003781099,0.006172926,0.01770626],"genre_scores_gemma":[0.9137565,0.004906397,0.07371683,0.0005248124,0.000097303,0.0003391017,0.001210092,0.0001963823,0.005252659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00170965,"threshold_uncertainty_score":0.005719304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007028342423839012,"score_gpt":0.1899272404750015,"score_spread":0.1828988980511624,"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."}}