{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.001324084,0.001799507,0.001477995,0.0004093359,0.0003582057,0.0002012717,0.005433255,0.0008886916,0.03804362],"category_scores_gemma":[0.0002902089,0.001801868,0.0002484779,0.0002762301,0.0009151931,0.00212741,0.005385393,0.001831835,0.2862377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002536183,"about_ca_system_score_gemma":0.0003720828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003889202,"about_ca_topic_score_gemma":0.0001559875,"domain_scores_codex":[0.9906712,0.0008855963,0.001272925,0.00306495,0.002687243,0.001418137],"domain_scores_gemma":[0.9896926,0.0002738089,0.001576608,0.007926905,0.00001769595,0.0005123859],"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":[0.000296828,0.001136497,0.0001591151,0.00009296294,0.001246232,0.000100702,0.00007984709,0.00001139362,0.0007160966,9.180009e-7,0.9959387,0.000220767],"study_design_scores_gemma":[0.002338651,0.0003376486,0.004486769,0.00034224,0.0009284877,0.00002595194,0.0002739106,0.00002121333,0.000465853,0.00001611599,0.9888113,0.001951894],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000898428,0.001369788,0.00001821314,0.00004557177,0.001241799,0.002316623,0.9930002,0.0001016668,0.001816311],"genre_scores_gemma":[0.0004193778,0.000690348,0.0004575024,0.001090546,0.0007484763,0.0002264718,0.9949813,0.0004165328,0.0009694672],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2481941,"threshold_uncertainty_score":0.9999478,"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."}}