{"id":"W2624613947","doi":"10.1021/acs.analchem.7b00693","title":"Measuring Rapid Time-Scale Reaction Kinetics Using Isothermal Titration Calorimetry","year":2017,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"thermodynamics and calorimetric analyses","field":"Chemistry","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Chemistry; Isothermal titration calorimetry; Kinetics; Calorimetry; Isothermal process; Titration; Reaction calorimeter; Scale (ratio); Thermodynamics; Physical chemistry","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000150678,0.0002498267,0.000313995,0.00003733939,0.0003917615,0.0002015201,0.0004502004,0.0003043354,0.001816805],"category_scores_gemma":[0.000241559,0.0002541278,0.0002275388,0.0001098871,0.0001921297,0.0001837399,0.00008874492,0.0003456392,0.00008362125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002081144,"about_ca_system_score_gemma":0.00005400742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001489768,"about_ca_topic_score_gemma":0.000002840779,"domain_scores_codex":[0.9984393,0.00000873552,0.0003508939,0.0004300124,0.0004082275,0.0003628684],"domain_scores_gemma":[0.9984801,0.00005186818,0.0002639617,0.000894525,0.000122713,0.0001868655],"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":[0.00003156091,0.0001080854,0.001190909,0.00006794458,0.0001039643,0.00001254232,0.000009536353,0.00003342018,0.9957762,0.00002398617,0.00007725285,0.002564534],"study_design_scores_gemma":[0.0005298205,0.00001500008,0.001131564,0.00006678409,0.0003687922,0.00002956476,0.00006067567,0.1414567,0.8542551,0.000174681,0.001409822,0.0005015237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8084055,0.0001012657,0.0009358512,0.00006197494,0.00005224271,0.00002344051,0.00001811034,0.00007593904,0.1903257],"genre_scores_gemma":[0.9933738,0.00002255575,0.0002773699,0.00002183503,0.0007053863,0.000002209243,0.00004166442,0.00004300032,0.005512168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1849683,"threshold_uncertainty_score":0.9999911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04337482688180511,"score_gpt":0.2710100175124015,"score_spread":0.2276351906305964,"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."}}