{"id":"W6901899048","doi":"10.6073/pasta/05ca288d7203107bddab618e95524c0a","title":"SBC LTER: OCEAN: Particulate Organic Matter Content and Composition of Stream, Estuarine, and Marine Sediments","year":2018,"lang":"en","type":"dataset","venue":"Environmental Data Initiative","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Organic matter; Particulates; Total organic carbon; Nitrate; Dissolved organic carbon; Isotopes of nitrogen; δ15N; Nitrogen","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002484831,0.0006638714,0.0007228961,0.0001617074,0.0001352906,0.00007127291,0.0005276887,0.0002202772,0.004683539],"category_scores_gemma":[0.00001903649,0.00064347,0.00003913247,0.00008389258,0.001136961,0.0007739837,0.004684221,0.0003736141,0.001927951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002018319,"about_ca_system_score_gemma":0.00001761781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004140779,"about_ca_topic_score_gemma":0.00007449561,"domain_scores_codex":[0.996981,0.0002585869,0.0006982726,0.001108277,0.0005496704,0.0004041873],"domain_scores_gemma":[0.9975922,0.0001156717,0.0007460657,0.001316801,0.00001421146,0.0002150332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002204642,0.0006601427,0.02250892,0.0001278131,0.0006692212,0.00005880383,0.0001181487,1.828394e-7,0.003706052,4.938166e-7,0.9718746,0.00005517735],"study_design_scores_gemma":[0.009725325,0.001850037,0.7154176,0.0008861779,0.003785093,0.0004077987,0.0008759224,0.0002352645,0.01408803,0.00008838504,0.2497667,0.002873685],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2256783,0.00007929089,0.000002681174,0.00002813198,0.00009438074,0.0006220613,0.7734551,0.00001490073,0.00002511823],"genre_scores_gemma":[0.08937825,0.000452656,0.0001799052,0.00029984,0.00009813343,0.00001436112,0.9094714,0.00009042567,0.00001502471],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7221079,"threshold_uncertainty_score":0.9996017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03592613353807422,"score_gpt":0.2503828111165617,"score_spread":0.2144566775784875,"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."}}