{"id":"W2798550304","doi":"10.1007/978-1-4614-5491-5_1534","title":"Temperature Gradient Generation and Control","year":2015,"lang":"en","type":"book-chapter","venue":"","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Control (management); Materials science; Computer science; Artificial intelligence","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":[0.0002639347,0.0009574704,0.0005839412,0.0005667188,0.0003819857,0.00121051,0.001274154,0.0006740305,0.008718948],"category_scores_gemma":[0.0002715448,0.0005931224,0.0003738706,0.0006400559,0.0005772262,0.001375324,0.0008554217,0.001328697,0.007871473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006478816,"about_ca_system_score_gemma":0.0004761819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004578849,"about_ca_topic_score_gemma":0.0006233366,"domain_scores_codex":[0.9996644,0.00001502297,0.00001062972,0.0001057677,0.0001775637,0.0000265861],"domain_scores_gemma":[0.9999305,0.00001493956,0.000006231906,0.00001665686,0.00002583509,0.000005829308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009237428,0.00008348258,0.0001213176,0.0005931527,0.0000221211,0.0001183379,0.0002017186,0.00368087,0.2722427,0.08941327,0.03625421,0.5971766],"study_design_scores_gemma":[0.00001438984,0.00007842659,0.000427966,0.0001121792,0.00002345501,0.0004343874,0.00003425609,0.01452908,0.3635173,0.02125821,0.5995094,0.00006099743],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009639545,0.02442054,0.6985162,0.0009805036,0.002002181,0.0003128308,0.0006399783,0.00461292,0.2588752],"genre_scores_gemma":[0.1247553,0.03136589,0.2534151,0.00143553,0.00104809,0.0006741376,0.001424033,0.001713329,0.5841687],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008718948,"threshold_uncertainty_score":0.02916777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01146903234846671,"score_gpt":0.1844454987003291,"score_spread":0.1729764663518624,"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."}}