{"id":"W1786054599","doi":"10.1007/s10822-015-9868-x","title":"Presenting data in such a fashion that they can be used by other scientists","year":2015,"lang":"en","type":"article","venue":"Journal of Computer-Aided Molecular Design","topic":"Chemical Thermodynamics and Molecular Structure","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Extrapolation; Covariance; Value (mathematics); Statistics; Least-squares function approximation; Measure (data warehouse); Error bar; Applied mathematics; Mathematics; Propagation of uncertainty; Simple (philosophy); Econometrics; Computer science; Statistical physics; Physics; Data mining; Epistemology","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":[0.0008525434,0.0002595212,0.0004069875,0.0001264685,0.00003851909,0.0001933812,0.001279383,0.0001751647,0.00002145684],"category_scores_gemma":[0.0001228926,0.0002319718,0.000134888,0.0001688802,0.00005505783,0.000167006,0.000375182,0.000468006,9.762618e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001463002,"about_ca_system_score_gemma":0.0002174087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004924058,"about_ca_topic_score_gemma":0.00001744277,"domain_scores_codex":[0.997716,0.0001525565,0.0005147208,0.0003869402,0.0008477485,0.0003820424],"domain_scores_gemma":[0.9982162,0.00008742441,0.0004722721,0.0007871824,0.0001504252,0.0002864854],"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":[0.00008607392,0.0001409225,0.0005844763,0.00004219803,0.0001433591,0.0006719282,0.0005170524,0.002249798,0.9914857,0.0001675333,0.002147634,0.001763388],"study_design_scores_gemma":[0.009094737,0.0002084653,0.0001109521,0.0005757715,0.0002119367,0.001212059,0.0002944561,0.186849,0.7849607,0.007360767,0.007886906,0.001234272],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6912462,0.0002780118,0.3075052,0.000283735,0.0001832999,0.00009676924,0.00003054008,0.0000175555,0.0003586894],"genre_scores_gemma":[0.9863573,0.000008923474,0.0131136,0.0002331853,0.0001309214,0.000001578021,0.00004280618,0.00005374296,0.00005797618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2951111,"threshold_uncertainty_score":0.9459534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05610103033108719,"score_gpt":0.2825540931976696,"score_spread":0.2264530628665824,"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."}}