{"id":"W2062532975","doi":"10.3109/10837450.2010.502900","title":"Comparison between nuclear magnetic resonance profiling and the source/sink approach for characterizing drug diffusion in hydrogel matrices","year":2010,"lang":"en","type":"article","venue":"Pharmaceutical Development and Technology","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Chemistry; Effective diffusion coefficient; Drug delivery; Materials science; Analytical Chemistry (journal); Nuclear magnetic resonance; Chromatography; Nanotechnology; Magnetic resonance imaging; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004079545,0.0001616087,0.0002340889,0.0000997998,0.0002285364,0.00003128445,0.0002342747,0.0002061423,0.000003189809],"category_scores_gemma":[0.00008401752,0.0001222615,0.00002167194,0.0001485487,0.0004495213,0.000005817107,0.0003015925,0.000306116,0.000002398391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000830979,"about_ca_system_score_gemma":0.00002778836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000039288,"about_ca_topic_score_gemma":0.000004999381,"domain_scores_codex":[0.9988939,0.00002785505,0.0003038883,0.0004002449,0.00007790844,0.0002962392],"domain_scores_gemma":[0.9996166,0.00004540722,0.00006570407,0.0001828702,0.00002930215,0.00006007485],"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":[0.0001508857,0.0001019115,0.06950253,0.00007714986,0.00002307019,3.623614e-7,0.0003032893,2.512591e-7,0.6320971,0.001730447,0.00002537749,0.2959877],"study_design_scores_gemma":[0.002151204,0.0000395411,0.005830554,0.00001959792,0.00004600795,0.00001713027,0.0002349343,0.008395779,0.6729376,0.0003806335,0.3096003,0.0003467839],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935943,0.003267842,0.0006535085,0.00159316,0.00002261785,0.0007133353,0.00000371938,0.00004644235,0.0001050281],"genre_scores_gemma":[0.982919,0.0003309154,0.01614598,0.0001230452,0.00005460563,0.0003097104,0.00002776137,0.00002460708,0.00006440019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3095749,"threshold_uncertainty_score":0.4985678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0245062386958702,"score_gpt":0.2822685495343808,"score_spread":0.2577623108385106,"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."}}