{"id":"W4394441748","doi":"10.6084/m9.figshare.5141695","title":"Lake of the Woods phyto- and picoplankton: spatiotemporal patterns in blooms, community composition, and nutrient status","year":2017,"lang":"en","type":"dataset","venue":"Figshare","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Picoplankton; Nutrient; Environmental science; Geography; Eutrophication; Composition (language); Ecology; Oceanography; Physical geography; Geology; Phytoplankton; Biology","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":[0.0001406419,0.000151264,0.0001596683,0.0005536946,0.000680304,0.0007040301,0.0001681978,0.0001363921,0.0009530367],"category_scores_gemma":[0.0003334434,0.0001723072,0.0001287158,0.001145914,0.0002534041,0.0003109655,0.000441478,0.0001411792,0.0001347159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002438937,"about_ca_system_score_gemma":0.001550164,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7235362,"about_ca_topic_score_gemma":0.908879,"domain_scores_codex":[0.999918,0.000005230064,0.000004800127,0.00002449929,0.0000193006,0.00002817948],"domain_scores_gemma":[0.9997728,0.00001184355,0.00007290897,0.000009745507,0.00008055585,0.00005207047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006497798,0.000007297039,0.9897184,0.00002044492,0.00003851048,0.00003247284,0.0009616383,0.00004140789,0.004135475,0.00002842123,0.0005325336,0.004418382],"study_design_scores_gemma":[4.839655e-7,0.000002912049,0.9995528,0.000002749227,0.000004738371,0.000004886489,0.0001762424,0.00004114642,0.0000492859,0.000002523227,0.000161366,9.040648e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9983826,0.0001862582,0.00005410745,0.00004173594,0.000001478323,0.000003986292,0.0007765221,0.000004321532,0.0005490935],"genre_scores_gemma":[0.9981709,0.0001543008,0.0001238926,0.00002633216,0.000001970211,0.000006388801,0.0008918617,0.000003005411,0.0006213798],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.7235362,"threshold_uncertainty_score":0.5561839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01928681848471748,"score_gpt":0.250745222826926,"score_spread":0.2314584043422085,"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."}}