{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001136718,0.0001271558,0.0003020324,0.000356492,0.0001374519,0.00005376134,0.0005990851,0.00006502788,0.00001475719],"category_scores_gemma":[0.0001802742,0.0001004556,0.00003706529,0.001057941,0.001085857,0.00008773336,0.0001048821,0.000173054,6.873606e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000258686,"about_ca_system_score_gemma":0.0003613321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001475646,"about_ca_topic_score_gemma":0.0000150583,"domain_scores_codex":[0.9976875,0.0001702067,0.0007748866,0.0002583617,0.0007356064,0.0003734595],"domain_scores_gemma":[0.9980789,0.0000793705,0.0005980365,0.0004001136,0.000702228,0.0001413003],"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":[0.00005404705,0.000292832,0.05916085,0.00001862163,0.00004373875,7.944624e-7,0.0006464453,0.000131285,0.9352708,0.00003452088,0.00001034207,0.00433572],"study_design_scores_gemma":[0.0004415842,0.001161727,0.02514239,0.00006795427,0.00001644573,0.00002216927,0.0004928235,0.0009081146,0.971559,0.00004495661,0.00004544823,0.00009741397],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945515,0.002235702,0.002563821,0.0001372173,0.00002341374,0.0004167348,0.00001129482,0.000002093547,0.00005819176],"genre_scores_gemma":[0.9979811,0.0003055208,0.001588527,0.00002347428,0.00003699575,0.00002438823,0.000008042628,0.00001372982,0.00001825586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03628818,"threshold_uncertainty_score":0.409646,"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."}}