{"id":"W6926829821","doi":"10.25585/1487967","title":"Pacific Northwest bog forest metagenomes","year":2014,"lang":"en","type":"dataset","venue":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","topic":"Diatoms and Algae Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bog; Vegetation (pathology); Taiga; Forest cover","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001028915,0.002119634,0.001532493,0.004271086,0.001212813,0.001750303,0.002515193,0.00159812,0.0210947],"category_scores_gemma":[0.003426711,0.0007857838,0.001460394,0.008311859,0.0004464218,0.001078655,0.002084322,0.002050492,0.01824041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001468825,"about_ca_system_score_gemma":0.003946544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05523793,"about_ca_topic_score_gemma":0.09930924,"domain_scores_codex":[0.9992074,0.0001024267,0.00006441395,0.000291219,0.0002141786,0.000120391],"domain_scores_gemma":[0.9990764,0.000195873,0.0001130393,0.0002161601,0.0002651337,0.0001334322],"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":[0.0003934535,0.00008854731,0.004787446,0.003015427,0.0003262558,0.0001013206,0.0001052281,0.001609032,0.001834894,0.001329096,0.9753145,0.01109481],"study_design_scores_gemma":[0.0005365382,0.0000336064,0.02065001,0.0005209531,0.0002187873,0.0001111676,0.0001334528,0.001093609,0.001345393,0.001690712,0.9736095,0.00005627676],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007482003,0.0002207884,0.0001095877,0.00003246265,0.00001356017,0.00001300909,0.9977799,0.0003842182,0.0006982795],"genre_scores_gemma":[0.0005202372,0.00009922255,0.0003350384,0.00001527523,0.000002481416,0.00004508647,0.9987165,0.00005181044,0.0002143005],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9789053,"threshold_uncertainty_score":0.1098328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01342136406632953,"score_gpt":0.2497059182275412,"score_spread":0.2362845541612117,"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."}}