{"id":"W4413159746","doi":"10.1016/j.jcis.2025.138706","title":"Multiforce synergistic assembly-engineered chitosan-sodium carboxymethyl cellulose/LiFePO₄ composite thick electrodes toward high volumetric energy density lithium-ion batteries","year":2025,"lang":"en","type":"article","venue":"Journal of Colloid and Interface Science","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Key Research and Development Projects of Shaanxi Province; National Natural Science Foundation of China","keywords":"Carboxymethyl cellulose; Composite number; Lithium (medication); Electrode; Chemical engineering; Chitosan; Cellulose; Materials science; Energy density; Ion; Sodium; Chemistry; Composite material; Organic chemistry; Metallurgy; Physical chemistry","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"],"consensus_categories":[],"category_scores_codex":[0.0006002017,0.0002904452,0.000523322,0.0006905429,0.0001901613,0.0003238692,0.0005874322,0.00009266829,0.00001532841],"category_scores_gemma":[0.0002759538,0.0002582498,0.0000567253,0.001068999,0.0003001511,0.0007318864,0.0001781302,0.0003119241,0.000002427125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002107777,"about_ca_system_score_gemma":0.0001220158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003789273,"about_ca_topic_score_gemma":0.000003955462,"domain_scores_codex":[0.9979929,0.0000693159,0.0006990888,0.000284383,0.0004938482,0.0004604482],"domain_scores_gemma":[0.9989803,0.0001749153,0.000225004,0.0002277048,0.0002460601,0.0001459737],"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":[0.00006750265,0.000027002,0.0002018984,0.00009721526,0.00004795787,0.000003570199,0.0001559362,0.008140635,0.9900525,0.0003857184,0.0004467314,0.0003733994],"study_design_scores_gemma":[0.0004162413,0.0001885631,0.002134165,0.0002143037,0.00004869048,0.00003834574,0.00007901651,0.005996333,0.9898342,0.0002016562,0.0006057224,0.0002427646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8476077,0.001206293,0.1474805,0.000179486,0.003016034,0.00008445024,0.000006120394,0.00005913451,0.0003601927],"genre_scores_gemma":[0.9955791,0.0003247785,0.003328968,0.0001316958,0.0001525552,0.000004092035,9.636542e-7,0.00002111599,0.0004566801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1479714,"threshold_uncertainty_score":0.9999869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006922973219424983,"score_gpt":0.235567815702503,"score_spread":0.2286448424830781,"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."}}