{"id":"W1980767707","doi":"10.1021/jp001187j","title":"Test of Reaction Kinetics Using Both Differential Scanning and Accelerating Rate Calorimetries As Applied to the Reaction of Li<i><sub>x</sub></i>CoO<sub>2</sub> in Non-aqueous Electrolyte","year":2001,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry A","topic":"Thermal and Kinetic Analysis","field":"Materials Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Chemistry; Activation energy; Differential scanning calorimetry; Reaction rate; Order of reaction; Kinetics; Chemical kinetics; Electrolyte; Thermodynamics; Kinetic energy; Calorimeter (particle physics); Reaction rate constant; Analytical Chemistry (journal); Physical chemistry; Electrode; Organic chemistry; Catalysis","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":[0.0004611405,0.0001659344,0.0003934547,0.00004932967,0.0001061081,0.00003865389,0.0002203738,0.00005624343,0.000004581542],"category_scores_gemma":[0.0001991255,0.0001059421,0.00008452309,0.0004687915,0.0001311359,0.0001033138,0.00006311069,0.000297735,0.000001427343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005998615,"about_ca_system_score_gemma":0.00004925045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006724848,"about_ca_topic_score_gemma":0.000007296637,"domain_scores_codex":[0.9987419,0.00006990664,0.0004930765,0.0001417154,0.0003282607,0.0002251976],"domain_scores_gemma":[0.9986065,0.000322182,0.000675111,0.0001742517,0.0001478496,0.00007412542],"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":[0.0004525589,0.0001476775,0.00002665584,0.00003341744,0.00002644693,0.000003103408,0.0005269268,0.003267388,0.9937592,0.000002716993,0.000003903903,0.001750049],"study_design_scores_gemma":[0.0003598012,0.0001827376,0.001812385,0.0001020786,0.0001871518,0.00006303334,0.0002675192,0.003155624,0.9936463,0.0001138137,0.000002854801,0.0001066698],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986719,0.00003578952,0.0009762341,0.00008433599,0.00002386538,0.00008247098,0.000003362393,0.000005554155,0.0001164792],"genre_scores_gemma":[0.9994185,0.00004802537,0.00002915701,0.00002268004,0.0004597935,0.000001833301,0.000001158272,0.00001441445,0.000004444205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001785729,"threshold_uncertainty_score":0.4320195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049946123530933,"score_gpt":0.2332203581005456,"score_spread":0.2227208968652363,"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."}}