{"id":"W4309584828","doi":"10.48550/arxiv.2211.10021","title":"Energetics of Cytoskeletal Gel Contraction","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polymer; Molecular motor; Solvent; Chemical physics; Contraction (grammar); Cytoskeleton; Materials science; Isotropy; Chemistry; Nanotechnology; Physics; Composite material; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002575431,0.0002079331,0.0002237954,0.0004892451,0.0005394428,0.0005219223,0.0004039586,0.000430988,0.002978743],"category_scores_gemma":[0.001210252,0.000254967,0.0001570812,0.0002296302,0.0006596335,0.0006716365,0.0003945476,0.0003378171,0.0002388688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009463474,"about_ca_system_score_gemma":0.0002442593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001056106,"about_ca_topic_score_gemma":0.001255938,"domain_scores_codex":[0.9999003,0.00001352131,0.000005100173,0.00002089622,0.00002566624,0.00003453395],"domain_scores_gemma":[0.9997591,0.0001355651,0.00003061461,0.00002218501,0.00002195982,0.0000306013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004290086,0.0001888381,0.007629951,0.0002606185,0.0000362028,0.0006583545,0.0002595927,0.5134535,0.319227,0.1364394,0.002718284,0.0186995],"study_design_scores_gemma":[0.00005196728,0.0001102033,0.00914101,0.00002003318,0.0000137046,0.0001362286,0.00009697958,0.9086425,0.05836272,0.02216482,0.001209028,0.00005090124],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9686085,0.0002931464,0.01662579,0.0003973169,0.00002432452,0.00001776646,0.0002331288,0.0001352736,0.01366476],"genre_scores_gemma":[0.9970105,0.0001124208,0.001744339,0.00002612745,0.000004067826,0.00004419154,0.0001239098,0.00002540981,0.000909112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002978743,"threshold_uncertainty_score":0.009964883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03927674661078615,"score_gpt":0.1942499037801945,"score_spread":0.1549731571694083,"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."}}