{"id":"W6943619921","doi":"10.16904/envidat.169","title":"Restoring grassland multifunctionality","year":2020,"lang":"en","type":"dataset","venue":"Socio-Environmental Systems Modeling","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Grassland; Species richness; Topsoil; Ecosystem; Restoration ecology; Hectare; Vegetation (pathology); Range (aeronautics); Grassland ecosystem","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":[],"consensus_categories":[],"category_scores_codex":[0.0006048385,0.0003655959,0.0003607743,0.0006077943,0.0006144942,0.0006953799,0.000480132,0.0003362316,0.003718861],"category_scores_gemma":[0.0005755583,0.0001146494,0.0003061336,0.0003936373,0.000426441,0.0005698606,0.0009976969,0.000436588,0.0004388196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007183604,"about_ca_system_score_gemma":0.0008270181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001689509,"about_ca_topic_score_gemma":0.007898914,"domain_scores_codex":[0.9997242,0.00005504287,0.00001411335,0.00008314088,0.00005803311,0.00006553887],"domain_scores_gemma":[0.9995962,0.00002462286,0.00008228069,0.00008242755,0.00006389816,0.0001506941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00191275,0.00265979,0.05750305,0.001668653,0.0005557481,0.0008685026,0.002738248,0.007953196,0.3851166,0.008161637,0.01093315,0.5199286],"study_design_scores_gemma":[0.0002780797,0.0118244,0.7641996,0.00037685,0.0006586928,0.001523785,0.003792253,0.01558961,0.03507367,0.007790171,0.1587965,0.00009650128],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9847387,0.0005819035,0.003741157,0.0002217304,0.00007608235,0.0002526341,0.0003438526,0.0002123567,0.009831574],"genre_scores_gemma":[0.9911335,0.0002350692,0.005156212,0.0001346252,0.00002617311,0.0001617329,0.0005958597,0.00003388073,0.00252284],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.003718861,"threshold_uncertainty_score":0.0124408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04702797281290426,"score_gpt":0.2524272100967801,"score_spread":0.2053992372838758,"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."}}