{"id":"W2961098799","doi":"10.1002/celc.201900829","title":"Correlating Structure and Properties of Super‐Concentrated Electrolyte Solutions: <sup>17</sup>O NMR and Electrochemical Characterization","year":2019,"lang":"en","type":"article","venue":"ChemElectroChem","topic":"Advanced Battery Materials and Technologies","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Institut National de la Recherche Scientifique","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; Deutscher Akademischer Austauschdienst","keywords":"Electrolyte; Lithium (medication); Electrochemistry; Chemistry; Differential scanning calorimetry; Solvent; Sulfonyl; Solvation; Inorganic chemistry; Physical chemistry; Organic chemistry; Alkyl; Thermodynamics","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":[],"consensus_categories":[],"category_scores_codex":[0.0000398461,0.0002230199,0.000300223,0.00005848542,0.00005322061,0.00003404092,0.00009252221,0.0001813478,0.00003269401],"category_scores_gemma":[0.00003039443,0.0002056071,0.00002193394,0.0001663407,0.00007767663,0.0002178092,0.00004680776,0.0002285368,0.000001786196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004645115,"about_ca_system_score_gemma":0.00001744234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001010359,"about_ca_topic_score_gemma":4.931877e-7,"domain_scores_codex":[0.9989763,0.000008807701,0.0002537576,0.0002461371,0.00009332712,0.0004216972],"domain_scores_gemma":[0.9996827,0.00001630708,0.00005582276,0.0001562468,0.00005088859,0.0000380029],"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":[0.00002843615,0.000006677488,0.0005272411,0.0001823934,0.00003706996,2.756003e-7,0.0001401211,0.0001990543,0.9977144,0.0002543805,0.000007231456,0.0009027462],"study_design_scores_gemma":[0.0003409396,0.0000739936,0.0002685429,0.00006307635,0.00001822514,0.00002537353,0.00005180941,0.03375182,0.9648048,0.0002914962,0.00009289804,0.0002170693],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961292,0.00201524,0.001196065,0.00003936833,0.00001268679,0.0002347509,0.000007508909,0.0003168562,0.00004834132],"genre_scores_gemma":[0.9989386,0.0005529297,0.000296781,0.00002470113,0.00003887568,0.00001543908,0.00006694478,0.00003485166,0.00003086087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03355277,"threshold_uncertainty_score":0.8384413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005580394974533969,"score_gpt":0.1661610546716688,"score_spread":0.1605806596971348,"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."}}