{"id":"W4393459317","doi":"10.5281/zenodo.4018173","title":"Indicative distribution maps for Ecological Functional Groups - Level 3 of IUCN Global Ecosystem Typology","year":2020,"lang":"en","type":"dataset","venue":"UEF eRepo (University of Eastern Finland)","topic":"Botany and Plant Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia; University of Calgary; University of British Columbia","funders":"","keywords":"Typology; IUCN Red List; Geography; Distribution (mathematics); Ecology; Ecosystem; Environmental resource management; Environmental science; Biology; Archaeology; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001587966,0.0002002675,0.0005758606,0.00001180277,0.0002459922,0.00000597323,0.0003806562,0.0004978827,0.0006065483],"category_scores_gemma":[0.0001115495,0.000110469,0.0002227698,0.0001620515,0.0002520635,0.00005449626,0.0002627081,0.0001770802,0.0001263403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005698669,"about_ca_system_score_gemma":0.00003147345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002742178,"about_ca_topic_score_gemma":0.01108678,"domain_scores_codex":[0.9988567,0.0001347757,0.0002347027,0.0003947445,0.0001493158,0.0002297562],"domain_scores_gemma":[0.9985465,0.000432973,0.0007390027,0.00006899463,0.0001311901,0.00008131762],"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":[0.000496557,0.0001527481,0.01504927,0.0000938113,0.0002359772,0.00002190381,0.000017717,9.876717e-7,0.00002689272,0.0002508255,0.9832128,0.0004404857],"study_design_scores_gemma":[0.0004588256,0.0008615775,0.2899307,0.00003412276,0.0002008473,0.00002349371,0.0008158493,0.00001540411,0.000003082649,0.0004616267,0.7069881,0.000206331],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0657195,0.00004768771,0.0001039299,0.0006643534,0.0002951369,0.0002873355,0.932803,0.0000113671,0.00006766742],"genre_scores_gemma":[0.1096564,0.00007246839,0.00004075543,0.00004952396,0.0001443103,0.000001888107,0.8898726,4.75909e-7,0.0001616085],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2762247,"threshold_uncertainty_score":0.6641279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0748645331806128,"score_gpt":0.215065273981388,"score_spread":0.1402007408007752,"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."}}