{"id":"W6901928046","doi":"10.6073/pasta/b7b5ce28877a8335dcda39fa196e2e5a","title":"Soil percent carbon and nitrogen:Dimensions of Biodiversity - Genetic, Phylogenetic, Functional, and Remotely Sensed Diversity","year":2018,"lang":"en","type":"dataset","venue":"Environmental Data Initiative","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biodiversity; Biomass (ecology); Ecosystem; Trophic level; Sampling (signal processing); Phylogenetic diversity; Species diversity; Ecosystem diversity; Canopy; Diversity index","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","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0002751591,0.0007194993,0.000722861,0.0002853031,0.000715524,0.00003411366,0.0007100407,0.0004196448,0.0005943269],"category_scores_gemma":[0.00008803637,0.0007137255,0.00007908478,0.0001273262,0.002724582,0.0002371312,0.01216625,0.0004862078,0.0004575982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002966837,"about_ca_system_score_gemma":0.00006905823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001852315,"about_ca_topic_score_gemma":0.0003791739,"domain_scores_codex":[0.996119,0.0004731596,0.0004646828,0.001577936,0.0009095354,0.0004557332],"domain_scores_gemma":[0.9970224,0.0002035661,0.0006230708,0.00177569,0.00003157732,0.0003437109],"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":[0.0003192233,0.0004097263,0.02183782,0.00006945667,0.0006219955,0.00009547222,0.0002811298,0.000002972711,0.003186304,1.317065e-7,0.9731299,0.00004588017],"study_design_scores_gemma":[0.005143521,0.001375808,0.63618,0.0001996902,0.0047815,0.000259411,0.003041385,0.0003206731,0.003078775,0.0001213391,0.3428803,0.002617513],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3901119,0.0005722938,0.000001105202,0.00001131694,0.0001164972,0.0003923367,0.6087676,0.00001529883,0.00001166268],"genre_scores_gemma":[0.04400613,0.003680191,0.000406584,0.0001903639,0.0001151065,0.000003420749,0.9515536,0.00003976483,0.000004803353],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6302496,"threshold_uncertainty_score":0.9999894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05272328970432545,"score_gpt":0.2305382504211321,"score_spread":0.1778149607168066,"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."}}