{"id":"W2267238139","doi":"10.1149/ma2015-01/2/309","title":"Synthesis and Characterization of Li<sub>2</sub>FeSiO<sub>4</sub> As Candidate High-Capacity Li-Ion Battery Cathode Material","year":2015,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Hydro-Québec; Canadian Light Source (Canada); McGill University","funders":"","keywords":"Materials science; Electrochemistry; Orthorhombic crystal system; Cathode; X-ray photoelectron spectroscopy; Raman spectroscopy; Chemical engineering; Annealing (glass); Lithium-ion battery; Hydrothermal synthesis; Hydrothermal circulation; Nanotechnology; Battery (electricity); Chemistry; Crystallography; Crystal structure; Metallurgy; Physical chemistry; Electrode","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001285146,0.0001923632,0.0001812984,0.000282498,0.0001666669,0.0002040684,0.0001908879,0.0003071671,0.0009785487],"category_scores_gemma":[0.0001508123,0.0001005223,0.00009824919,0.000201912,0.0001635955,0.0001924083,0.00008625098,0.0001193528,0.0004848726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001842141,"about_ca_system_score_gemma":0.0001822069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006616514,"about_ca_topic_score_gemma":0.002125192,"domain_scores_codex":[0.9999342,0.000005603847,0.000005909389,0.00001130311,0.00003542669,0.00000753696],"domain_scores_gemma":[0.9999295,0.000009956838,0.00001646944,0.000005537509,0.00003034248,0.000008115173],"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":[0.00002406979,0.000007110546,0.0001550917,0.00003565368,0.000001448541,0.00004592112,0.00001278064,0.00009909213,0.9979669,0.00003249473,0.00005744576,0.001561973],"study_design_scores_gemma":[0.000004558761,0.0001055818,0.002860967,0.000004085341,0.000005983728,0.0001458284,0.00003075851,0.0009521335,0.9924143,0.00003451334,0.003436257,0.000004892512],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832297,0.001275632,0.01031961,0.0001341369,0.00002350842,0.00007821128,0.0008676982,0.0001412554,0.003930144],"genre_scores_gemma":[0.9630876,0.00104395,0.02453973,0.00007228976,0.00001221436,0.0000690797,0.001053259,0.0000679619,0.01005396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009785487,"threshold_uncertainty_score":0.003273606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526242871579595,"score_gpt":0.214347212269772,"score_spread":0.1990847835539761,"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."}}