{"id":"W6901629586","doi":"10.60692/ab56y-f1r29","title":"RAINBIO: a mega-database of tropical African vascular plants distributions","year":2016,"lang":"en","type":"article","venue":"Socio-Environmental Systems Modeling","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bibliothèque et Archives nationales du Québec","funders":"","keywords":"Tropics; Georeference; Flora (microbiology); Vascular plant; Vegetation (pathology); Distribution (mathematics); Biodiversity; Tropical climate; Tropical forest","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005977343,0.0008891005,0.000876481,0.004986751,0.0003865961,0.001052146,0.001576827,0.0008241593,0.008028417],"category_scores_gemma":[0.004280495,0.0005254638,0.0005876031,0.01119457,0.0002223375,0.001394463,0.00153024,0.0007026792,0.00505834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004591956,"about_ca_system_score_gemma":0.001086067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006476986,"about_ca_topic_score_gemma":0.009863432,"domain_scores_codex":[0.9995522,0.00007123421,0.00009198491,0.0001377933,0.00009071865,0.0000561516],"domain_scores_gemma":[0.99863,0.0003714881,0.0003457295,0.0002714086,0.0002316956,0.0001496949],"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":[0.001643447,0.0002431622,0.09424567,0.01477383,0.001175241,0.001898354,0.003770995,0.0146849,0.02030338,0.01103495,0.6518195,0.1844065],"study_design_scores_gemma":[0.0002472236,0.00006076651,0.10943,0.000686368,0.0002466841,0.0006619323,0.0009184789,0.007421039,0.004915865,0.003457582,0.8718559,0.00009824006],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01842668,0.0008874689,0.002977625,0.0001183626,0.00002705012,0.00007072948,0.9730381,0.002228198,0.002225877],"genre_scores_gemma":[0.03185448,0.0007491449,0.01333068,0.00004453739,0.00001481654,0.0003567041,0.9528199,0.0003322003,0.0004975625],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008028417,"threshold_uncertainty_score":0.02685773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02498853335602596,"score_gpt":0.2248994023802036,"score_spread":0.1999108690241777,"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."}}