{"id":"W2169821086","doi":"10.5539/ijc.v4n5p1","title":"A Laborsaving, Timesaving, and More Reliable Strategy for Separation of Low-Molecular-Mass Phosphoproteins in Phos-tag Affinity Electrophoresis","year":2012,"lang":"en","type":"article","venue":"International Journal of Chemistry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Science and Technology Agency; Japan Society for the Promotion of Science; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Chemistry; Tris; Tricine; Phos; Polyacrylamide gel electrophoresis; Gel electrophoresis; TCEP; Chromatography; Electrophoresis; Sodium dodecyl sulfate; Affinity electrophoresis; Phosphate; Biochemistry; Affinity chromatography; Enzyme","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001876392,0.000127053,0.0001939237,0.00004401512,0.00002409051,0.00002419768,0.0002865218,0.0001263799,0.000164317],"category_scores_gemma":[0.0001174962,0.0001317217,0.00008862141,0.00007760151,0.00005087927,0.0001882828,0.00003656367,0.0002418199,3.512902e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001394615,"about_ca_system_score_gemma":0.0001088436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000186966,"about_ca_topic_score_gemma":9.272637e-7,"domain_scores_codex":[0.9989789,0.000004144109,0.0004709145,0.0001217612,0.0002457621,0.0001784837],"domain_scores_gemma":[0.9987835,0.00004849804,0.0005503434,0.0001357648,0.0004013053,0.00008060579],"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":[0.000158991,0.0001522216,0.003058612,0.00009258431,0.00005028692,0.000004047303,0.00007187282,0.0002452567,0.9951721,0.0003147537,0.0001344031,0.0005449021],"study_design_scores_gemma":[0.000577551,0.00001884547,0.0001567185,0.0001607324,0.00001708637,0.00003768823,0.00007419322,0.000247968,0.9949503,0.00255096,0.001090152,0.0001178116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898002,0.0007675817,0.007617281,0.0001776399,0.00002525966,0.00009050144,0.00005264984,0.00001221096,0.001456749],"genre_scores_gemma":[0.9828538,0.0002148462,0.01644798,0.00002868105,0.0001503372,0.00004073242,0.00002638703,0.00001901972,0.0002182032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008830702,"threshold_uncertainty_score":0.5371455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007569787904232115,"score_gpt":0.3073064953752159,"score_spread":0.2997367074709838,"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."}}