{"id":"W7140424382","doi":"10.1333/s00897172743a","title":"Autotitrator Titration Equivalence Point Detection Kinetics","year":2017,"lang":"en","type":"article","venue":"The Chemical Educator","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Equivalence point; Titration; Expediting; Equivalence (formal languages); Conductance; Kinetics; Base (topology)","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":[0.004486719,0.001654639,0.001447756,0.0008205301,0.0006575822,0.001517518,0.003577952,0.001929626,0.01051969],"category_scores_gemma":[0.006532435,0.0008872818,0.0007385834,0.001337325,0.000675983,0.001906706,0.001360403,0.005532837,0.009102353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001125698,"about_ca_system_score_gemma":0.001233562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001898,"about_ca_topic_score_gemma":0.002101219,"domain_scores_codex":[0.992153,0.001365456,0.0003048198,0.001472544,0.004077794,0.000626311],"domain_scores_gemma":[0.9941508,0.002119171,0.0002867992,0.001019352,0.002155763,0.0002680538],"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":[0.0003613554,0.0003499031,0.0004504165,0.0002198059,0.00002419868,0.00004790531,0.0004300432,0.0002778249,0.9680334,0.002282948,0.002411182,0.02511097],"study_design_scores_gemma":[0.00001831178,0.0003392682,0.0004992189,0.00001790292,0.00001044363,0.00005860877,0.00004208311,0.005613697,0.9818701,0.0003483862,0.01115586,0.00002615403],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3600544,0.008015971,0.5638556,0.001428514,0.001750722,0.002351068,0.005173153,0.01309579,0.04427488],"genre_scores_gemma":[0.5073406,0.01130193,0.2817275,0.001772627,0.0003243688,0.003624029,0.008749893,0.002482497,0.1826765],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01051969,"threshold_uncertainty_score":0.03519183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0205229477452863,"score_gpt":0.2729921646321442,"score_spread":0.2524692168868579,"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."}}