{"id":"W2950060573","doi":"10.48550/arxiv.1407.2001","title":"Approach to universal self-similar attractor for the levelling of thin liquid films","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Fluid Dynamics and Thin Films","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Brockhouse Institute for Materials Research","funders":"","keywords":"Attractor; Levelling; Perturbation (astronomy); Capillary action; Self-similarity; Thin film; Volume of fluid method; Statistical physics; Classical mechanics; Physics; Materials science; Mathematics; Mathematical analysis; Mechanics; Nanotechnology; Geometry; Thermodynamics; Quantum mechanics; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003327348,0.0003637877,0.000422935,0.000189162,0.000117236,0.00003453206,0.001037386,0.0003752137,0.00001847605],"category_scores_gemma":[0.00002599324,0.0003547577,0.0003153316,0.0002593937,0.0000579198,0.00008257214,0.000395618,0.0005482621,0.00001508318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001401642,"about_ca_system_score_gemma":0.00006229344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007782834,"about_ca_topic_score_gemma":0.00001419105,"domain_scores_codex":[0.9987299,0.00003892535,0.0002414074,0.0005421615,0.00009146715,0.0003560904],"domain_scores_gemma":[0.9985384,0.0002408696,0.000109368,0.0008339671,0.000137718,0.0001396546],"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":[0.00006417376,0.00004677821,0.00003414939,0.0003430856,0.0002887693,0.000004417119,0.0005741246,0.9591619,0.0001966968,0.0385962,0.0006678566,0.00002186986],"study_design_scores_gemma":[0.0003282909,0.00006752093,0.00006800902,0.00006607849,0.0002032436,9.409047e-7,0.0002243809,0.993725,0.0003057289,0.0006400479,0.003973878,0.0003968588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2779998,0.0001001325,0.7140571,0.00002589156,0.0009330708,0.0007887483,0.0001837367,0.0003125722,0.005598964],"genre_scores_gemma":[0.9921716,0.000212557,0.006688912,0.00003867977,0.0001019347,0.000003238123,0.00005212403,0.00007655002,0.0006543535],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7141719,"threshold_uncertainty_score":0.9998904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04979642194767039,"score_gpt":0.1669217136334967,"score_spread":0.1171252916858263,"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."}}