{"id":"W4415261409","doi":"10.1093/jrsssc/qlaf052","title":"Gaussian process with dissolution spline kernel for in vitro dissolution testing","year":2025,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series C (Applied Statistics)","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"European Regional Development Fund","keywords":"Dissolution; Kernel (algebra); Piecewise; Spline (mechanical); Gaussian process; Kernel principal component analysis; Parametric statistics; Gaussian","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":[0.00465059,0.0009637393,0.00130853,0.001234941,0.0004427193,0.001093582,0.001861453,0.002456802,0.001696265],"category_scores_gemma":[0.01227022,0.0004960182,0.002000474,0.001416776,0.001303398,0.001287147,0.001181467,0.002794428,0.0006687011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001344292,"about_ca_system_score_gemma":0.001409468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01490037,"about_ca_topic_score_gemma":0.006535007,"domain_scores_codex":[0.9982815,0.0006896619,0.00008497939,0.0003096248,0.000471362,0.0001629227],"domain_scores_gemma":[0.995033,0.003254375,0.0005097982,0.0002921982,0.0008060239,0.0001045478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001343024,0.00007241353,0.002428995,0.00009586558,0.00005335245,0.000174511,0.00007563369,0.9492637,0.002671932,0.02151626,0.0008189284,0.02269418],"study_design_scores_gemma":[0.000004150575,0.00001450509,0.0001622786,0.000003120348,0.000004873067,0.00001130147,0.000002734179,0.9977059,0.0002388153,0.001662368,0.0001841464,0.000005797361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02637172,0.0003366891,0.9716339,0.0002930889,0.00004961105,0.00007099722,0.0001777525,0.0003669818,0.0006993034],"genre_scores_gemma":[0.8186496,0.0007681422,0.1731968,0.0002475904,0.00009382865,0.00042016,0.0006522633,0.0001818291,0.005789719],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01490037,"threshold_uncertainty_score":0.02962726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01030492194827679,"score_gpt":0.2762404070129939,"score_spread":0.2659354850647171,"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."}}