{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004540867,0.0004810026,0.0003688615,0.001291077,0.0006231575,0.001511907,0.0007984229,0.0005807683,0.001246854],"category_scores_gemma":[0.009485113,0.00022096,0.0005950604,0.002238951,0.0005893728,0.001578482,0.001170385,0.0008334225,0.0001982621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00101989,"about_ca_system_score_gemma":0.0004485236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05454878,"about_ca_topic_score_gemma":0.03894351,"domain_scores_codex":[0.9988915,0.0005712964,0.00004824328,0.0003602479,0.00006207098,0.00006670144],"domain_scores_gemma":[0.995935,0.002012847,0.0005211069,0.0006629691,0.0007181906,0.0001499256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001540495,0.0001415052,0.8939084,0.0000611809,0.000195038,0.0001807693,0.000597744,0.07259105,0.00127998,0.002093543,0.001317815,0.027479],"study_design_scores_gemma":[0.00002686037,0.0001565771,0.5449956,0.00006072887,0.0000872434,0.0001664657,0.001227113,0.4434385,0.001173482,0.00503324,0.003573656,0.00006050665],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843876,0.0001498709,0.01265181,0.0002239329,0.000008210158,0.00002410965,0.001486527,0.0001769904,0.0008909273],"genre_scores_gemma":[0.9920716,0.00002790846,0.006532497,0.00002175786,0.000003700662,0.00002004032,0.001244294,0.00001108783,0.00006720544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05454878,"threshold_uncertainty_score":0.1084625,"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."}}