{"id":"W6912995136","doi":"10.5683/sp3/uypydj","title":"Battery Aging Dataset for 15 Minute Fast Charging of Samsung 30T Cells","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Battery (electricity); State of charge; State of health; Charge cycle; Accelerated aging; Lithium-ion battery; Charge (physics); Trickle charging; Reliability (semiconductor)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00128148,0.0008885752,0.001311514,0.001031054,0.0001885438,0.0001618244,0.001819,0.0004506858,0.00009116301],"category_scores_gemma":[0.0003037583,0.0009571398,0.0003623651,0.0006260605,0.0001899757,0.0003068216,0.0007662584,0.0005311777,0.002071047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002378664,"about_ca_system_score_gemma":0.0002214356,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08854308,"about_ca_topic_score_gemma":0.03432471,"domain_scores_codex":[0.99537,0.0001728079,0.001144392,0.00122349,0.0009221153,0.001167215],"domain_scores_gemma":[0.9947459,0.0006699439,0.001185484,0.002933887,0.0001867235,0.000278108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006382047,0.00008520007,0.000004638154,0.001759753,0.000343416,0.000112821,0.00005241682,0.00004791724,0.001236268,0.00000254778,0.9960869,0.000204295],"study_design_scores_gemma":[0.0007950208,0.00004990911,0.00007274751,0.0007311613,0.0006694015,0.00001149088,0.0001006382,0.0001274418,0.002071258,0.00002612848,0.9944621,0.0008826499],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007794806,0.0001549536,0.00005784133,0.00009193332,0.0005789757,0.001144244,0.9977628,0.0001787493,0.00002269641],"genre_scores_gemma":[0.000001078281,0.0001749987,0.0003748445,0.0003198503,0.001081894,0.0002841751,0.9972181,0.0004451479,0.00009994087],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05421836,"threshold_uncertainty_score":0.9992879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03997095196001812,"score_gpt":0.29972535420744,"score_spread":0.2597544022474219,"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."}}