{"id":"W4411068910","doi":"10.1021/acs.jcim.5c00197","title":"Machine Learning Based Quantitative Structure–Dissolution Profile Relationship","year":2025,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"PCL Construction (Canada); University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Dissolution; Computer science; Chemistry; Artificial intelligence; Physical chemistry","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":[0.0001521363,0.00005845009,0.00009218758,0.000153495,0.00005366461,0.00004871777,0.00003360798,0.00005424544,0.000006768905],"category_scores_gemma":[0.0001887121,0.00005010743,0.00002572886,0.0001085039,0.000008629689,0.0005619101,0.000006376659,0.0002905391,7.667639e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003579713,"about_ca_system_score_gemma":0.00002266932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001405001,"about_ca_topic_score_gemma":1.531159e-7,"domain_scores_codex":[0.9994795,0.000008074276,0.000333438,0.00002337225,0.00008629943,0.00006929447],"domain_scores_gemma":[0.9997193,0.00004188393,0.00007975791,0.00002236715,0.0001038693,0.00003277866],"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":[0.00002137961,0.000002095672,0.0002128151,0.000127899,0.000009735707,1.07166e-7,0.0002886711,0.9886069,0.007128789,0.000830145,0.00007526502,0.002696204],"study_design_scores_gemma":[0.0002843339,0.000008965113,0.00001741846,0.0001267098,0.00001160218,0.000004112927,0.00009203687,0.9942197,0.004117826,0.0007571688,0.0003098558,0.00005026839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5925124,0.0003777449,0.4057372,0.0001043353,0.00008257697,0.00002663344,0.00000220636,0.00003239231,0.001124514],"genre_scores_gemma":[0.9916556,0.00001294362,0.008238301,0.0000461964,0.00001690769,4.985645e-7,0.00001596227,0.000002828708,0.00001073654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3991432,"threshold_uncertainty_score":0.2043322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212802193877281,"score_gpt":0.2675076540056386,"score_spread":0.2453796320668658,"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."}}