{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001080798,0.0001606276,0.0001499102,0.00001031974,0.0002159309,0.00009832311,0.0005487818,0.0001380615,0.0005096407],"category_scores_gemma":[0.001370574,0.0001183916,0.0001079004,0.00004814852,0.0001746879,0.0001154033,0.00009109463,0.0003567637,0.0002683841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000904771,"about_ca_system_score_gemma":0.00002975992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001798381,"about_ca_topic_score_gemma":9.699986e-7,"domain_scores_codex":[0.9990551,0.000009288307,0.0002148806,0.0002388721,0.0001966988,0.0002851767],"domain_scores_gemma":[0.9988374,0.0001202003,0.00009797803,0.000717896,0.00005341222,0.0001731645],"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":[0.00001624138,0.00005150518,0.00002477543,0.00002841336,0.00001515491,0.000001278647,0.00007309783,0.000008898774,0.9979162,0.0006347779,0.0004094182,0.0008201925],"study_design_scores_gemma":[0.0001145282,0.00001081325,0.0001292806,0.00002235626,0.00003483316,0.00001079781,0.0000615322,0.004712674,0.9925146,0.0005722778,0.001647259,0.0001690741],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985266,0.00004369802,0.001687822,0.002552548,0.0003405272,0.00009927648,0.000007657443,0.0001386174,0.00986388],"genre_scores_gemma":[0.9977018,0.000006685344,0.0002094741,0.000153797,0.0007627262,0.00001302211,0.000005912969,0.00002091424,0.001125625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01243587,"threshold_uncertainty_score":0.5580208,"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."}}