{"id":"W6931996348","doi":"10.5683/sp2/f4f1a5","title":"Replication Data for: Model input and Output files associated with Teeter et al. (2018) Global Biogeochemical Cycles","year":2018,"lang":"en","type":"dataset","venue":"Borealis","topic":"Plant Reproductive Biology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of Victoria","funders":"","keywords":"Replicate; Replication (statistics); Biogeochemical cycle; Raw data; Process (computing); Data modeling","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":[],"consensus_categories":[],"category_scores_codex":[0.001612324,0.002094569,0.001236199,0.001359815,0.0008163163,0.001831375,0.003445357,0.002223782,0.08964062],"category_scores_gemma":[0.008479244,0.000824228,0.001809538,0.002092395,0.0003969597,0.001689029,0.001298192,0.002416991,0.0786327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001366826,"about_ca_system_score_gemma":0.00196389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01646709,"about_ca_topic_score_gemma":0.02268911,"domain_scores_codex":[0.9990838,0.0001454313,0.00009864621,0.0003731653,0.0002076827,0.0000913515],"domain_scores_gemma":[0.9963539,0.001153521,0.0002627201,0.001309558,0.0006917101,0.000228544],"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":[0.000135182,0.00006706027,0.002410504,0.0004428184,0.00007403701,0.00002614715,0.00002049679,0.002728012,0.0003277973,0.0007796437,0.9902725,0.002715865],"study_design_scores_gemma":[0.001129104,0.00005178831,0.008386607,0.0002192172,0.0001000808,0.00009273394,0.00007315612,0.007812839,0.001992372,0.006261398,0.9737844,0.00009628487],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003508495,0.00003250975,0.0003530361,0.0001038584,0.0000504989,0.00001752355,0.996903,0.001554821,0.0006339251],"genre_scores_gemma":[0.001529223,0.00002344185,0.0009417581,0.00006935478,0.00001170981,0.00009042851,0.9963241,0.0004213428,0.0005888054],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08964062,"threshold_uncertainty_score":0.2998778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03518237420092776,"score_gpt":0.3030106400283638,"score_spread":0.267828265827436,"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."}}