{"id":"W2996676511","doi":"10.1021/acsaem.9b01695","title":"Effective Mass Transport Properties in Lithium Battery Electrodes","year":2019,"lang":"en","type":"article","venue":"ACS Applied Energy Materials","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec à Montréal; General Motors Corporation","keywords":"Thermal diffusivity; Scanning electrochemical microscopy; Electrolyte; Materials science; Electrode; Lithium (medication); Diffusion; Porosity; Battery (electricity); Ionic conductivity; Lithium-ion battery; Electrochemistry; Nanotechnology; Chemistry; Composite material; Power (physics); Thermodynamics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002495541,0.0003620428,0.0005669729,0.0001380963,0.00002678392,0.00005503956,0.0002563928,0.0001578853,0.0005672071],"category_scores_gemma":[0.000003562338,0.0003355067,0.00001994434,0.00012623,0.00003719177,0.0002076656,0.00003406339,0.00007760026,0.0001994894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001325279,"about_ca_system_score_gemma":0.00001172888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003465089,"about_ca_topic_score_gemma":0.000006635737,"domain_scores_codex":[0.9983349,0.00004845943,0.0005131615,0.0003718884,0.0001872618,0.0005443731],"domain_scores_gemma":[0.9994555,0.00003543653,0.00006098545,0.0003905681,0.00001655264,0.00004100503],"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":[0.0001083384,0.00002276193,0.0001670119,0.0002226372,0.00004238509,0.000005103368,0.0001027134,0.01197566,0.9850755,0.001852386,0.00008516423,0.0003403958],"study_design_scores_gemma":[0.0005408259,0.0000344895,0.001359194,0.00006567064,0.00001149864,0.000002546389,0.00002284062,0.000008841296,0.9945883,0.001310078,0.001652454,0.0004032378],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926016,0.00007091142,0.0006919945,0.00001852161,0.001130463,0.0005017414,0.00002593573,0.0003368874,0.004621943],"genre_scores_gemma":[0.9979624,0.00006663309,0.0002645822,0.0002162074,0.0002005736,0.0007606412,0.00006150994,0.0001194195,0.0003480451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01196681,"threshold_uncertainty_score":0.9999097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004921691878874435,"score_gpt":0.1804150281588944,"score_spread":0.17549333628002,"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."}}