{"id":"W6958184568","doi":"10.6073/pasta/aa53fcd2e642d16554333c41ba7ec5c5","title":"Eddy Flux Measurements, Pleistocene Park, Cherskii, Russia - 2016","year":2019,"lang":"en","type":"dataset","venue":"Environmental Data Initiative","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arctic; Pleistocene; Atmosphere (unit); The arctic; Water vapor; Flux (metallurgy); Climate change","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":[0.0005683801,0.0009089724,0.000579239,0.001255163,0.0004336472,0.0009355029,0.0007920892,0.0005960905,0.004488847],"category_scores_gemma":[0.0009175407,0.0003459944,0.0005519891,0.001885819,0.0001941365,0.0004739733,0.0006279578,0.0005849102,0.007283962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005878712,"about_ca_system_score_gemma":0.001339957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06379178,"about_ca_topic_score_gemma":0.09480523,"domain_scores_codex":[0.999681,0.00003543799,0.00003787311,0.00009955707,0.00009074236,0.0000554147],"domain_scores_gemma":[0.9994804,0.00003709093,0.00007116364,0.0001291846,0.0002190757,0.00006309104],"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":[0.0007056644,0.0002102944,0.1073759,0.001333709,0.0003925425,0.0002825077,0.0002170427,0.003898185,0.003199106,0.001467304,0.8560772,0.02484046],"study_design_scores_gemma":[0.0004556162,0.00006324799,0.3879515,0.000374056,0.0001109996,0.0001608469,0.000382101,0.004769942,0.003421135,0.0007124341,0.6015216,0.00007645493],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007495616,0.0001226469,0.0001896144,0.00004605354,0.00003592778,0.00001672846,0.9906413,0.000438668,0.0010134],"genre_scores_gemma":[0.006469691,0.00005936203,0.0005062949,0.00001183052,0.000008567078,0.00003311982,0.9921893,0.00004189614,0.0006798829],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06379178,"threshold_uncertainty_score":0.1268409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1565844143793167,"score_gpt":0.3076557092248737,"score_spread":0.151071294845557,"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."}}