{"id":"W4206596493","doi":"10.4095/329204","title":"Regional lake sediment geochemical data from north-central Saskatchewan (NTS 074-A, B, G, and H): reanalysis data and QA/QC evaluation","year":2021,"lang":"en","type":"report","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Sediment; Aqua regia; Environmental science; Quality assurance; Hydrology (agriculture); Geology; Geochemistry; Geomorphology; Chemistry; Engineering; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002160124,0.0007262646,0.0003697964,0.004298206,0.001012021,0.001060056,0.0008745864,0.0003031207,0.002351795],"category_scores_gemma":[0.002419331,0.0003300234,0.000480548,0.007504324,0.0004234334,0.0003422853,0.0006671034,0.0004046504,0.001201634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008875616,"about_ca_system_score_gemma":0.01463191,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8642905,"about_ca_topic_score_gemma":0.9379982,"domain_scores_codex":[0.9976687,0.0002192698,0.0001900427,0.0002121105,0.001549049,0.0001607583],"domain_scores_gemma":[0.9923692,0.0002846442,0.0003386719,0.0004238153,0.006448145,0.0001354776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006631326,0.0002835246,0.8019443,0.0004095776,0.0007240103,0.0005978097,0.0009855079,0.01566608,0.04645202,0.0004380469,0.01611822,0.1157177],"study_design_scores_gemma":[0.00006750952,0.0001042136,0.9508267,0.0000418807,0.0001634165,0.00009515395,0.0009431838,0.003794634,0.02492405,0.00007891828,0.01889541,0.00006491956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.8811445,0.000445577,0.004756861,0.0002562595,0.00003088998,0.0008336462,0.09546679,0.0006144545,0.01645107],"genre_scores_gemma":[0.8485683,0.0007345416,0.02146745,0.0002793395,0.00001121578,0.0007930496,0.1060919,0.0002560883,0.02179806],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.1357095,"threshold_uncertainty_score":0.2730175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1251597523816531,"score_gpt":0.3178696778723568,"score_spread":0.1927099254907037,"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."}}