{"id":"W2912335688","doi":"10.1002/eap.1866","title":"A new baseline for countrywide α‐diversity and species distributions: illustration using >6,000 plant species in Panama","year":2019,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biodiversity; Geography; Panama; Ecology; Global biodiversity; Ecosystem services; Biodiversity hotspot; IUCN Red List; Species diversity; Survey data collection; Ecosystem; Statistics; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001870489,0.000105592,0.000138593,0.00002171125,0.0004104327,0.00003418665,0.0001363019,0.00008742027,0.0295947],"category_scores_gemma":[0.00004702872,0.00009448913,0.00003773621,0.0002333662,0.0001241238,0.0001169645,0.0002911361,0.00007480881,0.0002178824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005104364,"about_ca_system_score_gemma":0.00001007093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001347643,"about_ca_topic_score_gemma":0.001010839,"domain_scores_codex":[0.9991347,0.0000213632,0.0001882142,0.0002953488,0.0001365297,0.0002238223],"domain_scores_gemma":[0.9995446,0.0001322358,0.00006943686,0.0001451527,0.00001365909,0.00009489492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008877925,0.0006101357,0.7550659,0.00003225553,0.00001685142,0.000002794319,0.0002648214,0.0003489562,0.01286701,0.2069388,0.02252921,0.001234545],"study_design_scores_gemma":[0.0004334829,0.00004423705,0.7823383,0.000003440143,0.00001251041,0.000003627712,0.0005356899,0.0016895,0.0001801437,0.001341157,0.2132749,0.0001429492],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9566999,0.00002973798,0.03466773,0.0009951089,0.00004939266,0.001148865,0.001353284,0.00005004707,0.00500592],"genre_scores_gemma":[0.9961479,0.00007216552,0.001377909,0.000208729,0.00005130133,0.0001016159,0.000607534,0.000004152021,0.001428697],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2055976,"threshold_uncertainty_score":0.9712924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05341359315779627,"score_gpt":0.2444759925151135,"score_spread":0.1910623993573172,"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."}}