{"id":"W2120488249","doi":"10.1039/c4sm01483a","title":"Approach to universal self-similar attractor for the levelling of thin liquid films","year":2014,"lang":"en","type":"article","venue":"Soft Matter","topic":"Fluid Dynamics and Thin Films","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Brockhouse Institute for Materials Research","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Attractor; Levelling; Perturbation (astronomy); Capillary action; Thin film; Materials science; Self-similarity; Physics; Statistical physics; Classical mechanics; Mathematics; Mathematical analysis; Nanotechnology; Geometry; Composite material; Quantum mechanics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001815386,0.0001099256,0.0001269274,0.0000374564,0.00004469046,0.00001925662,0.0002128327,0.00006200418,0.00005674692],"category_scores_gemma":[0.00001040283,0.00008363534,0.00006890994,0.00006376096,0.00001392654,0.00005027909,0.00002997052,0.00009875913,0.00006455822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001467427,"about_ca_system_score_gemma":0.000005223737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001045961,"about_ca_topic_score_gemma":0.000001670174,"domain_scores_codex":[0.9994623,0.000009157224,0.000136542,0.0001184476,0.00009153517,0.000182028],"domain_scores_gemma":[0.9995477,0.0001295926,0.00001859211,0.0002341638,0.00002878722,0.00004120703],"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":[0.0001199495,0.000167531,0.0009226585,0.001091741,0.0004719538,0.000001099778,0.01029856,0.8156237,0.04084837,0.01860505,0.1107836,0.001065769],"study_design_scores_gemma":[0.0001947843,0.00004450603,0.0004803397,0.00001612329,0.00002717118,0.000001355175,0.00008381519,0.9599027,0.002490082,0.0001022957,0.03649456,0.000162242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1705667,0.00008413335,0.814428,0.0005876994,0.0007851105,0.0005170657,0.00005967492,0.0002386896,0.01273288],"genre_scores_gemma":[0.9744025,0.000004889876,0.02411735,0.0006630255,0.0001072164,0.00002235092,0.00001114105,0.00005523285,0.000616238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8038358,"threshold_uncertainty_score":0.341055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009168140325445051,"score_gpt":0.1867649934087897,"score_spread":0.1775968530833447,"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."}}