{"id":"W2309364959","doi":"10.1149/ma2013-01/4/113","title":"In-Situ Characterization of Active Materials in Ni-MH and Li-Ion Batteries by Electrochemical Acoustic Emission Method","year":2013,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Electrochemistry; Characterization (materials science); In situ; Acoustic emission; Ion; Materials science; Analytical Chemistry (journal); Nanotechnology; Electrode; Chemistry; Composite material; Physics; Physical chemistry; Environmental chemistry; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001476411,0.0001836614,0.0001680963,0.000160221,0.0001374376,0.0002459314,0.0003662434,0.0002739992,0.002340378],"category_scores_gemma":[0.0002850659,0.0001407147,0.00009981365,0.0001268644,0.0001456528,0.0003813045,0.000123372,0.0002509287,0.0003792773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001207288,"about_ca_system_score_gemma":0.00006245275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003322306,"about_ca_topic_score_gemma":0.0008032921,"domain_scores_codex":[0.9999057,0.00001185672,0.000006417145,0.00002238337,0.00003928111,0.00001428135],"domain_scores_gemma":[0.9998955,0.00004487624,0.00001347478,0.00001039573,0.00002807161,0.000007711908],"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":[0.00003594909,0.000008192273,0.0001152606,0.00004203303,0.000002080241,0.00001404206,0.00001892782,0.00002569227,0.9983755,0.00003885704,0.00003210541,0.001291417],"study_design_scores_gemma":[0.00000213755,0.00002648291,0.0007742654,0.000001790544,0.000004271818,0.00003613238,0.00001996767,0.000428918,0.9979793,0.00001907118,0.0007061951,0.00000141758],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831686,0.001290002,0.01148008,0.000114107,0.00004492268,0.00003218194,0.0003923911,0.0001118652,0.003366],"genre_scores_gemma":[0.9935635,0.0003127189,0.0027667,0.00001959947,0.000008342774,0.00002275281,0.0001828318,0.00002012035,0.003103456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002340378,"threshold_uncertainty_score":0.007829368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006513060644238403,"score_gpt":0.2391601649256449,"score_spread":0.2326471042814065,"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."}}