{"id":"W6977354055","doi":"10.6084/m9.figshare.3552849.v1","title":"Supplement 1. Richness response, ANPP, and climate data for all studies included in the meta-analysis.","year":2016,"lang":"en","type":"dataset","venue":"Figshare","topic":"Spreadsheets and End-User Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Species richness; Body size and species richness; Biodiversity; Wildlife; Species diversity; Type (biology); Plant community","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005580034,0.001717216,0.002973513,0.005538145,0.0009356158,0.003709011,0.003524431,0.00218697,0.7134066],"category_scores_gemma":[0.07342817,0.001473047,0.003893691,0.007694282,0.0003775139,0.003291383,0.002281592,0.001882425,0.05803907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002306107,"about_ca_system_score_gemma":0.006616935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02064943,"about_ca_topic_score_gemma":0.04110168,"domain_scores_codex":[0.9975379,0.0007776941,0.0005598559,0.0003676141,0.0005535202,0.0002034053],"domain_scores_gemma":[0.9236713,0.06090882,0.006276709,0.002512697,0.005818553,0.0008119098],"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":[0.0003108882,0.0000466013,0.001325799,0.06310179,0.001454837,0.00006119507,0.0001290237,0.0006523544,0.0001709505,0.001632633,0.9245109,0.006602932],"study_design_scores_gemma":[0.006725094,0.0002482589,0.02483695,0.03892351,0.003820111,0.0004955336,0.0004714681,0.001585756,0.0003903568,0.0111573,0.911184,0.0001616504],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002030245,0.0003745105,0.0003791254,0.0003116909,0.0001676067,0.0002551759,0.9972783,0.000212651,0.0008179388],"genre_scores_gemma":[0.01047123,0.001470043,0.01302456,0.002648597,0.0006177156,0.01286954,0.9422989,0.0009950728,0.01560429],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7134066,"threshold_uncertainty_score":0.4087907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3686033953458031,"score_gpt":0.4214251410660014,"score_spread":0.05282174572019827,"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."}}