{"id":"W4410419580","doi":"10.1016/j.isci.2025.112691","title":"Advanced lithium-ion battery process manufacturing equipment for gigafactories: Past, present, and future perspectives","year":2025,"lang":"en","type":"review","venue":"iScience","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Electrification; Battery (electricity); Process (computing); Manufacturing engineering; Resource (disambiguation); Scalability; Resource efficiency; Computer science; Process engineering; Engineering; Electricity; Electrical engineering","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":[0.0009604526,0.0008588859,0.0009143954,0.001973964,0.000294764,0.001371097,0.0009263318,0.00114676,0.005103279],"category_scores_gemma":[0.000689578,0.0003614608,0.0007525105,0.0028148,0.0003697158,0.002488864,0.0006468916,0.001647801,0.002020472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005918792,"about_ca_system_score_gemma":0.001371232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001232217,"about_ca_topic_score_gemma":0.002725174,"domain_scores_codex":[0.9997508,0.00003082868,0.00002920479,0.00004498346,0.0001049017,0.00003936022],"domain_scores_gemma":[0.9995035,0.0001833357,0.00007550232,0.00001671826,0.0001873783,0.00003345549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007912275,0.0001043282,0.0002797782,0.0302222,0.00007872106,0.0002613469,0.00009410721,0.0009820721,0.007578708,0.01297706,0.01776086,0.9295818],"study_design_scores_gemma":[0.0000104512,0.0001493594,0.0006323294,0.003338029,0.00009860723,0.0006500992,0.00008352158,0.0002873836,0.001887664,0.003871083,0.9889703,0.00002119189],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004139213,0.9963987,0.0003634033,0.0004012867,0.0001699853,0.000005959088,0.00002393435,0.00001124995,0.002211532],"genre_scores_gemma":[0.002082079,0.9961566,0.000432081,0.0002028902,0.00008601436,0.000007917787,0.00003857513,0.000002479335,0.0009913123],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005103279,"threshold_uncertainty_score":0.0170722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02541860728137574,"score_gpt":0.3414763744982112,"score_spread":0.3160577672168355,"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."}}