{"id":"W4399175963","doi":"10.1186/s13321-024-00853-w","title":"Identifying uncertainty in physical–chemical property estimation with IFSQSAR","year":2024,"lang":"en","type":"article","venue":"Journal of Cheminformatics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; The Scarborough Hospital; ARC Resources (Canada)","funders":"","keywords":"Property (philosophy); Computer science; Estimation; Data mining; Data science; Systems engineering; Engineering","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":[0.01343316,0.001468093,0.001329788,0.002275041,0.0003756117,0.00168065,0.001714321,0.0007689668,0.001306455],"category_scores_gemma":[0.01928418,0.000542163,0.002285246,0.001205716,0.0009158759,0.001768669,0.001795712,0.001456648,0.0005595834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001075316,"about_ca_system_score_gemma":0.001376965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006172399,"about_ca_topic_score_gemma":0.003113457,"domain_scores_codex":[0.9963117,0.001360098,0.0002137663,0.0006559122,0.001280014,0.0001785087],"domain_scores_gemma":[0.9812362,0.0141034,0.001421176,0.001642681,0.001469603,0.0001269014],"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":[0.0003339593,0.0001626129,0.01953222,0.0002424,0.0003794346,0.0001065151,0.0001011944,0.9207675,0.004619936,0.002386958,0.001087075,0.05028022],"study_design_scores_gemma":[0.00001003876,0.0000785308,0.001691795,0.00001195279,0.00002455284,0.0000342122,0.00001601811,0.9930881,0.002974283,0.001586162,0.0004695386,0.00001481317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2196634,0.0009513799,0.7670004,0.0003328734,0.00004050532,0.0001803196,0.002328523,0.006965063,0.002537586],"genre_scores_gemma":[0.8749078,0.000254259,0.1191663,0.0001955103,0.00003438607,0.0001687445,0.004521817,0.0002738044,0.0004773307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01343316,"threshold_uncertainty_score":0.07104218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009905848516422483,"score_gpt":0.2654185823120778,"score_spread":0.2555127337956553,"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."}}