{"id":"W4394420165","doi":"10.6084/m9.figshare.3846702","title":"Abundance and Variety of Plant Species in Grassland","year":2016,"lang":"en","type":"dataset","venue":"Figshare","topic":"Botany and Plant Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grassland; Abundance (ecology); Variety (cybernetics); Ecology; Plant species; Environmental science; Geography; Biology; Mathematics; Statistics","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":[0.0004849979,0.0008954027,0.0008098164,0.002250476,0.0003689055,0.0009423587,0.000878645,0.0006601608,0.02520485],"category_scores_gemma":[0.002978817,0.0002688807,0.0006168616,0.003771138,0.0001890729,0.0006566851,0.001073699,0.0005582572,0.01921958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008814705,"about_ca_system_score_gemma":0.0006844961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02908117,"about_ca_topic_score_gemma":0.06493079,"domain_scores_codex":[0.9995286,0.0000642925,0.00007103565,0.0001606297,0.0001062278,0.00006915296],"domain_scores_gemma":[0.9989145,0.0002101814,0.0002128988,0.0001993946,0.0003225642,0.0001404303],"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":[0.0003289002,0.00007566085,0.06059859,0.002018767,0.0001815839,0.00009356136,0.0002072432,0.001093829,0.0005373933,0.0006568281,0.9245742,0.009633566],"study_design_scores_gemma":[0.0002592732,0.00004926775,0.2909837,0.0006560318,0.00007822154,0.0001898804,0.0006112257,0.000906096,0.0005543642,0.0006356532,0.705017,0.00005917646],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002809517,0.00008406123,0.00003883944,0.00002947516,0.00001548813,0.000007422159,0.996344,0.0000678825,0.0006032145],"genre_scores_gemma":[0.004700906,0.0000659769,0.0002047052,0.00002429204,0.000007748328,0.00005917257,0.9941148,0.00002559856,0.0007968541],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02908117,"threshold_uncertainty_score":0.08431858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03231069867659103,"score_gpt":0.1993597776708954,"score_spread":0.1670490789943044,"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."}}