{"id":"W3016420205","doi":"10.1002/elps.202000005","title":"Empirical predictor of conditions that support ideal‐filter capillary electrophoresis","year":2020,"lang":"en","type":"article","venue":"Electrophoresis","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ionic strength; Oligonucleotide; Function (biology); Range (aeronautics); Rational design; Filter (signal processing); Capillary electrophoresis; Chemistry; Biological system; Chromatography; Analytical Chemistry (journal); Computer science; Materials science; Nanotechnology; DNA; Biochemistry; Physical chemistry; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002726062,0.0009822376,0.001188662,0.001157199,0.0003862797,0.001204149,0.0007229828,0.001225578,0.001043501],"category_scores_gemma":[0.02188913,0.0003538216,0.000397885,0.0004514839,0.001000382,0.001755376,0.0006235366,0.001192247,0.0005945301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007428805,"about_ca_system_score_gemma":0.001324752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001759631,"about_ca_topic_score_gemma":0.0009648955,"domain_scores_codex":[0.9988077,0.000269187,0.00007185432,0.0003159279,0.0002932681,0.000242179],"domain_scores_gemma":[0.9888074,0.007546859,0.001461342,0.0005908373,0.001298227,0.0002953635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001791083,0.0005465584,0.06206018,0.0007990747,0.0001623098,0.0008764717,0.0004995372,0.5696003,0.2492057,0.02648755,0.004956155,0.08301503],"study_design_scores_gemma":[0.00003977518,0.0002458925,0.009134091,0.00005266301,0.00002491086,0.0002295341,0.00008244414,0.8837666,0.09869505,0.006026453,0.001607861,0.00009470585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5612428,0.00102956,0.4276559,0.0006985877,0.00007512018,0.0001934344,0.0009651231,0.002785248,0.005354164],"genre_scores_gemma":[0.9623677,0.0004372921,0.03525743,0.0001576074,0.00002904038,0.0001927059,0.0008818166,0.0001308241,0.0005455153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002726062,"threshold_uncertainty_score":0.01441699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01647325161782982,"score_gpt":0.2316006279044706,"score_spread":0.2151273762866408,"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."}}