{"id":"W2002012954","doi":"10.1039/c1cc11501d","title":"Seebeck coefficients in ionic liquids –prospects for thermo-electrochemical cells","year":2011,"lang":"en","type":"article","venue":"Chemical Communications","topic":"Ionic liquids properties and applications","field":"Chemical Engineering","cited_by":186,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Seebeck coefficient; Ionic liquid; Thermoelectric effect; Electrochemistry; Materials science; Electrolyte; Ionic bonding; Thermoelectric materials; Range (aeronautics); Atmospheric temperature range; Electric potential energy; Engineering physics; Thermodynamics; Ion; Chemistry; Physical chemistry; Electrode; Power (physics); Composite material; Physics; Organic chemistry; Catalysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001487477,0.0002034138,0.0002411775,0.00005810227,0.0001310479,0.00001838558,0.001348325,0.0001916712,0.00009091182],"category_scores_gemma":[0.0001187872,0.0001954428,0.0001348841,0.0003636863,0.0001966393,0.00007718631,0.0003761163,0.0004411421,0.00008077537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001994848,"about_ca_system_score_gemma":0.00005863175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004006838,"about_ca_topic_score_gemma":0.000006834982,"domain_scores_codex":[0.9986051,0.00002143083,0.0004478064,0.0003282944,0.0001260873,0.0004712374],"domain_scores_gemma":[0.9980583,0.000202488,0.0000691028,0.00143387,0.0001055068,0.0001307525],"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":[0.00004278259,0.0004711168,0.00002614506,0.00002782446,0.0000179262,1.80263e-7,0.0005528544,0.000008596703,0.9632375,0.03493141,0.0002988444,0.0003848566],"study_design_scores_gemma":[0.0006447358,0.00003739818,0.00001735519,0.00004581149,0.00002244487,0.000002781392,0.00008458324,0.01627227,0.973192,0.002108025,0.00728447,0.0002880784],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9123874,0.001904377,0.0335192,0.002105564,0.000185809,0.002472412,0.00006543028,0.0008940084,0.04646577],"genre_scores_gemma":[0.9864714,0.00007695029,0.01179495,0.0001958929,0.00005395178,0.0007809179,0.00009685255,0.00005073199,0.0004783657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07408395,"threshold_uncertainty_score":0.7969925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04431151833889805,"score_gpt":0.2580035927771043,"score_spread":0.2136920744382062,"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."}}