{"id":"W2914782699","doi":"10.1016/j.bpj.2018.11.893","title":"Phase Separation: Prediction and Role in Biological Regulation","year":2019,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"Solvation; Phase (matter); Chemistry; Chemical physics; Nucleic acid; Separation method; Separation (statistics); Function (biology); Protein–protein interaction; Biophysics; Chromatography; Biology; Molecule; Biochemistry; Computer science; Cell biology","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":[0.0007560203,0.0005209745,0.000520119,0.00128687,0.000658593,0.001422446,0.0007774816,0.0008562233,0.002461704],"category_scores_gemma":[0.004323218,0.000310569,0.0006239862,0.000911227,0.0009564027,0.00187758,0.0005960546,0.001278834,0.001086652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006281314,"about_ca_system_score_gemma":0.0005871724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004562607,"about_ca_topic_score_gemma":0.0002633468,"domain_scores_codex":[0.9997498,0.00005682392,0.00001616917,0.00007074179,0.00007538572,0.00003096132],"domain_scores_gemma":[0.9966918,0.001982625,0.0004682767,0.0002955486,0.0003897967,0.0001719395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003693747,0.0008601813,0.03795365,0.001040407,0.0001479014,0.0007907595,0.0002937645,0.06727538,0.4987594,0.1652613,0.006725579,0.2171978],"study_design_scores_gemma":[0.0001324766,0.0003244521,0.007289791,0.00004435862,0.00007809221,0.0004897927,0.00009985374,0.6336108,0.2065628,0.1467401,0.004554281,0.00007315732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4814708,0.001715883,0.5017943,0.00123973,0.0003875957,0.0001583862,0.0007514352,0.003538043,0.008943757],"genre_scores_gemma":[0.9630149,0.0005265236,0.03428598,0.0001212353,0.0001135308,0.00008627124,0.0007330503,0.0001667586,0.0009516395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002461704,"threshold_uncertainty_score":0.008235216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01299071969867095,"score_gpt":0.3043693664194517,"score_spread":0.2913786467207808,"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."}}