{"id":"W2244023758","doi":"10.1007/s40553-015-0058-5","title":"Microstructural Characterization of Nanocrystalline Sn-Coated Carbon Fibre Electrodes Cycled in Li-Ion Cells","year":2015,"lang":"en","type":"article","venue":"Metallurgical and Materials Transactions E","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Novelis (Canada); University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanocrystalline material; Materials science; Electrolyte; Anode; Electrochemistry; Transmission electron microscopy; Chemical engineering; Scanning electron microscope; Carbon fibers; Coating; Substrate (aquarium); Electrode; Composite number; Analytical Chemistry (journal); Composite material; Nanotechnology; Chemistry; Chromatography","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":[],"consensus_categories":[],"category_scores_codex":[0.000149828,0.0001764867,0.0003847886,0.00009124246,0.00002298604,0.00004572086,0.0000691098,0.0001022574,0.0002798986],"category_scores_gemma":[0.000003483305,0.0001696571,0.00002215458,0.0001338595,0.0000498441,0.0001962016,0.000007554825,0.0000574522,0.000003165361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003761383,"about_ca_system_score_gemma":0.000009451181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005574416,"about_ca_topic_score_gemma":0.00001293509,"domain_scores_codex":[0.9989447,0.00006711527,0.0004823033,0.0001782748,0.0001118797,0.000215715],"domain_scores_gemma":[0.9997151,0.00001200031,0.00006190204,0.0001111171,0.00003480826,0.00006502911],"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":[0.00009166753,0.00002879284,0.000001907909,0.00009792869,0.00002191673,0.000004469733,0.00009021629,0.002295567,0.9971948,0.0000105244,0.000001137003,0.0001611292],"study_design_scores_gemma":[0.0007514373,0.00005484324,0.0005005316,0.00003688389,0.00003128767,0.00002095117,0.00001450209,0.0008822487,0.9970289,0.0001112614,0.0003884264,0.0001786822],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851716,0.00004466377,0.01356671,0.00002636073,0.0007094213,0.0002383702,0.0001046537,0.0001001851,0.0000380817],"genre_scores_gemma":[0.9989715,0.0001579993,0.0005275081,0.00001066554,0.00005067152,0.00002867251,0.0001156319,0.00002916038,0.0001081727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01379997,"threshold_uncertainty_score":0.6918417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00996319613538676,"score_gpt":0.2073702827903665,"score_spread":0.1974070866549797,"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."}}