{"id":"W3115229030","doi":"10.1016/j.physa.2020.125681","title":"Using fitting functions to estimate the diffusion coefficient of drug molecules in diffusion-controlled release systems","year":2020,"lang":"en","type":"article","venue":"Physica A Statistical Mechanics and its Applications","topic":"Drug Transport and Resistance Mechanisms","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Institut de Mathématiques de Toulouse","keywords":"Weibull distribution; Diffusion; Function (biology); Curve fitting; Applied mathematics; Diffusion equation; Mathematics; Statistical physics; Statistics; Thermodynamics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001259977,0.0001467881,0.0004188867,0.00004959038,0.0001852085,0.00002100714,0.00008574476,0.00003323888,0.00001279007],"category_scores_gemma":[0.0001122353,0.00009937763,0.00005698672,0.0003923358,0.00002036244,0.00002012661,0.00004954684,0.0001497756,0.000008928548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002312665,"about_ca_system_score_gemma":0.00005714555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003632786,"about_ca_topic_score_gemma":0.000009107698,"domain_scores_codex":[0.9987904,0.00003653977,0.0004143284,0.0003053128,0.0002536921,0.0001997506],"domain_scores_gemma":[0.9991471,0.0002225814,0.0001089061,0.000179964,0.0001126124,0.0002288384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004986435,0.0007017999,0.00003383479,0.0004390804,0.00005113163,0.000008860158,0.0009137509,0.004477608,0.1938836,0.7965249,0.00009358265,0.002373139],"study_design_scores_gemma":[0.001681546,0.000106935,0.0003022561,0.0001290776,0.0002222187,0.000002634319,0.0006942885,0.9938949,0.0006865864,0.001491172,0.000660387,0.0001279521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1169578,0.0001873126,0.8785527,0.002027685,0.00003724467,0.001896374,0.0002131569,0.00003139148,0.00009639464],"genre_scores_gemma":[0.9945189,0.00003151886,0.004781242,0.0001960974,0.00005823862,0.0003157201,0.00004346396,0.00002122608,0.00003357696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9894173,"threshold_uncertainty_score":0.4052503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01753610661975476,"score_gpt":0.2938706545943788,"score_spread":0.2763345479746241,"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."}}