{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001158102,0.0004813111,0.0006611449,0.0002030802,0.0001680967,0.0000413505,0.0005778651,0.0002607917,0.002185001],"category_scores_gemma":[0.00004715806,0.0004889679,0.000332637,0.0010015,0.0001731636,0.0001293888,0.00006754836,0.0004718115,0.0002282362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001564756,"about_ca_system_score_gemma":0.0001851873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001843663,"about_ca_topic_score_gemma":0.000004348938,"domain_scores_codex":[0.9972295,0.00008617005,0.0006708597,0.0005658233,0.0005407655,0.0009068802],"domain_scores_gemma":[0.9986003,0.0001134783,0.0001185544,0.0005866939,0.0001260694,0.0004549002],"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":[0.00004913471,0.0000367304,0.0009158511,0.0000640984,0.0001653312,0.00001353747,0.0001899145,0.00001629574,0.5434538,0.0003995768,0.4545913,0.0001044984],"study_design_scores_gemma":[0.0005412878,0.0005258466,0.006667299,0.00001416276,0.0001885085,0.00004065645,0.00006034675,0.0004513802,0.8183483,0.0005887221,0.1719945,0.0005789038],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9412537,0.04372239,0.004051347,0.002191279,0.0001459869,0.00085602,0.000335217,0.0009875789,0.006456501],"genre_scores_gemma":[0.9404213,0.05748741,0.0001552964,0.0009805497,0.0002738467,0.000162386,0.0002502817,0.0001415955,0.0001273466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2825967,"threshold_uncertainty_score":0.9997562,"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."}}