{"id":"W2052450988","doi":"10.6000/1929-5995.2013.02.03.1","title":"Formulation, Characterization, Study of Swelling Kinetics and Network Parameters of Poly (MA-co-VA-co-AA) Terpolymeric Hydrogels with Various Concentrations of Acrylic Acid","year":2013,"lang":"en","type":"article","venue":"Journal of Research Updates in Polymer Science","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Swelling; Self-healing hydrogels; Acrylic acid; Gravimetric analysis; Kinetics; Materials science; Polymer chemistry; Nuclear chemistry; Chemical engineering; Thermogravimetric analysis; Diffusion; Chemistry; Polymer; Composite material; Organic chemistry; Copolymer; Thermodynamics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0001664211,0.0003244436,0.0001489799,0.0002128366,0.00008657573,0.0001702385,0.00009812232,0.000166139,0.0004851923],"category_scores_gemma":[0.0002189244,0.0001210689,0.0001813823,0.0001945119,0.0001051991,0.0002761405,0.00007830658,0.0003499368,0.0001531576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001485226,"about_ca_system_score_gemma":0.0001197916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003751191,"about_ca_topic_score_gemma":0.0005681555,"domain_scores_codex":[0.9999127,0.000008956215,0.00001034443,0.00002240347,0.00002978157,0.00001571758],"domain_scores_gemma":[0.9998109,0.00003581342,0.00009069429,0.0000089439,0.00003040347,0.00002330608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000110855,0.000007248098,0.00003549756,0.00002129449,9.427574e-7,0.000008995156,0.000006592555,0.00008412372,0.9994248,0.000009493061,0.00000250118,0.0003874872],"study_design_scores_gemma":[0.000002163099,0.0001526353,0.001177969,0.000004157102,0.000008967924,0.00004050686,0.000006872242,0.0007268499,0.9973917,0.00001251393,0.0004717195,0.000003916918],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887481,0.001992529,0.008050236,0.0000436265,0.00002355516,0.00005137453,0.0002119364,0.00004680283,0.0008318278],"genre_scores_gemma":[0.9885151,0.001724159,0.007539959,0.00002442715,0.00001419372,0.000101857,0.0002169385,0.0000229019,0.00184049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004851923,"threshold_uncertainty_score":0.001623094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0235137126966401,"score_gpt":0.3087675441431823,"score_spread":0.2852538314465422,"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."}}