{"id":"W3171386442","doi":"10.48550/arxiv.2106.06923","title":"How fast do microdroplets generated during liquid-liquid phase separation move in a confined 2D space?","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Ternary operation; Oil droplet; Phase (matter); Solvent; Confined space; Work (physics); Chemistry; Ternary numeral system; Dissolution; Materials science; Chromatography; Analytical Chemistry (journal); Chemical physics; Thermodynamics","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":[0.000298925,0.0002450842,0.0003758006,0.0003134933,0.000313447,0.00088548,0.0003254731,0.0005213043,0.001025606],"category_scores_gemma":[0.001120979,0.0003408432,0.0002177135,0.000260026,0.0004386904,0.001727352,0.0003075392,0.0004427615,0.0005577169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004917992,"about_ca_system_score_gemma":0.0002417663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008495896,"about_ca_topic_score_gemma":0.0007006885,"domain_scores_codex":[0.9998293,0.00001901549,0.000007663246,0.00005839888,0.00004109105,0.0000445685],"domain_scores_gemma":[0.9994124,0.0002238999,0.0001908659,0.00003372896,0.00009026405,0.00004880864],"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":[0.0001376782,0.00004645631,0.004646038,0.0003143033,0.00004134731,0.0002066751,0.0002006192,0.002861326,0.970618,0.00161401,0.0003407678,0.0189727],"study_design_scores_gemma":[0.0000406471,0.000522249,0.03558224,0.00004553189,0.00007334028,0.0004701203,0.0008327322,0.0454878,0.9042284,0.002252091,0.01036044,0.0001043292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9692245,0.004567343,0.02318079,0.000390101,0.0001048879,0.00004743589,0.0002548228,0.000148032,0.002082076],"genre_scores_gemma":[0.9869668,0.003274837,0.008097051,0.0001148986,0.00003437158,0.00006150956,0.0002323683,0.00004327449,0.001174959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001025606,"threshold_uncertainty_score":0.003568232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03106840271006305,"score_gpt":0.2034234547839873,"score_spread":0.1723550520739242,"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."}}