{"id":"W4399547424","doi":"10.32614/cran.package.flowscreen","title":"FlowScreen: Daily Streamflow Trend and Change Point Screening","year":2016,"lang":"en","type":"dataset","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Streamflow; Environmental science; Point (geometry); Geography; Mathematics; Cartography; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002218704,0.001971443,0.001421187,0.003500435,0.0005155253,0.00198805,0.002878266,0.0009758803,0.07116425],"category_scores_gemma":[0.008374107,0.0009373748,0.001406828,0.004686596,0.000301651,0.001608375,0.001958794,0.001671406,0.05271499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009273279,"about_ca_system_score_gemma":0.002095206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01260091,"about_ca_topic_score_gemma":0.02487148,"domain_scores_codex":[0.9987954,0.0002106857,0.0002170448,0.0003924799,0.0002354016,0.0001490123],"domain_scores_gemma":[0.9971743,0.0007731884,0.0003673715,0.0006838572,0.0008421307,0.0001592731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006717435,0.00002174913,0.002933275,0.0005248602,0.00006020041,0.00002246301,0.00004387858,0.0004901681,0.0001710674,0.0005877662,0.9888958,0.0061816],"study_design_scores_gemma":[0.0004312053,0.00002942499,0.01603668,0.0003993089,0.0000674449,0.00008008288,0.00009964289,0.002393264,0.00149994,0.003445217,0.9754153,0.0001024983],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003337264,0.00002538993,0.0007656855,0.00004258998,0.00002498262,0.00004307555,0.9960957,0.002142169,0.0005266743],"genre_scores_gemma":[0.001050133,0.00003671965,0.002515835,0.0000503508,0.000009030613,0.0003947271,0.994443,0.000697492,0.0008027575],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07116425,"threshold_uncertainty_score":0.2380682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2083243509409565,"score_gpt":0.3827075972648118,"score_spread":0.1743832463238554,"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."}}