{"id":"W2921671982","doi":"10.1111/cobi.13311","title":"Global mismatches in aboveground and belowground biodiversity","year":2019,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":156,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"Natural Sciences and Engineering Research Council of Canada; Vetenskapsrådet; Academy of Finland; H2020 European Research Council; Deutsche Forschungsgemeinschaft","keywords":"Biodiversity; Biome; Measurement of biodiversity; Soil biodiversity; Ecosystem; Global biodiversity; Environmental science; Species richness; Agroforestry; Ecology; Geography; Biology; Soil water; Soil organic matter; Biodiversity conservation","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001096821,0.00007152429,0.0001235388,0.000008717413,0.0001111467,0.0000116253,0.00008710992,0.0001281202,0.0001857088],"category_scores_gemma":[0.00002380981,0.00003200736,0.00002082861,0.0001685423,0.0001469638,0.00007446681,0.00009948197,0.00004241302,0.0001337339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002576575,"about_ca_system_score_gemma":0.000004617576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001577837,"about_ca_topic_score_gemma":0.007387432,"domain_scores_codex":[0.9994935,0.00004752566,0.00008681396,0.0001991386,0.00002665158,0.00014633],"domain_scores_gemma":[0.999759,0.0001240891,0.00003950813,0.0000240977,0.00002910457,0.00002417022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002898479,0.00001920784,0.9950425,0.000002717546,0.000007697974,0.000001252121,0.00002962457,1.163794e-7,0.001039079,0.001686041,0.0007872271,0.001355521],"study_design_scores_gemma":[0.0001980784,0.0001208314,0.9821798,0.000002324555,0.000003295158,0.000002843808,0.0003341998,0.000009748917,0.0000150176,0.001437408,0.01561893,0.00007754408],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918656,0.0001526131,5.145383e-7,0.00703099,0.000134521,0.0001137386,0.00006168622,0.00002272007,0.0006176532],"genre_scores_gemma":[0.9980428,0.00006264145,0.0000237457,0.001681454,0.00001455212,0.000001512426,0.00006894796,7.091547e-8,0.0001042372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0148317,"threshold_uncertainty_score":0.412236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02014396014370657,"score_gpt":0.2077335817891127,"score_spread":0.1875896216454061,"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."}}