{"id":"W2004569980","doi":"10.1021/bm800594f","title":"Kinetic Controlled Synthesis of pH-Responsive Network Alginate","year":2008,"lang":"en","type":"article","venue":"Biomacromolecules","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Swelling; Polymer; Reagent; Kinetics; Activation energy; Chemistry; Reaction rate constant; Chemical engineering; Reaction rate; Drug delivery; Michaelis–Menten kinetics; Polymer chemistry; Organic chemistry; Catalysis; Enzyme","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001284168,0.0002403109,0.0001368093,0.0001026362,0.00007234611,0.000210302,0.0002060998,0.0001626723,0.0004908663],"category_scores_gemma":[0.0002683342,0.0001064588,0.0001594044,0.0001029968,0.0001147109,0.0002990008,0.0001533296,0.000281789,0.0001551517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002985539,"about_ca_system_score_gemma":0.0001651626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004083116,"about_ca_topic_score_gemma":0.0009473134,"domain_scores_codex":[0.9999141,0.000009922985,0.000009740202,0.00002437938,0.00002859506,0.00001330113],"domain_scores_gemma":[0.9998899,0.00002855382,0.00004377264,0.000009148665,0.00001745072,0.00001127615],"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":[0.00001729384,0.000006252187,0.00004610524,0.00003162117,0.000002296242,0.00000925705,0.000008754909,0.0004772573,0.9972772,0.0001965284,0.0000217351,0.001905826],"study_design_scores_gemma":[0.000003349749,0.00004284306,0.0002434096,0.000002542791,0.000004054666,0.00002192233,0.000002614403,0.002912641,0.9958122,0.00004784333,0.0009026336,0.000003975119],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9460061,0.002119791,0.04782392,0.00009043145,0.00006197979,0.00007863193,0.0004354728,0.0003054403,0.003078102],"genre_scores_gemma":[0.9795094,0.0008284966,0.01764157,0.00002546222,0.000005756675,0.0000363541,0.0001310763,0.00004035519,0.001781484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004908663,"threshold_uncertainty_score":0.002166212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01283690890085329,"score_gpt":0.2321922171360819,"score_spread":0.2193553082352286,"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."}}