{"id":"W3010123800","doi":"10.1038/s41597-020-0420-z","title":"Author Correction: A global database for metacommunity ecology, integrating species, traits, environment and space","year":2020,"lang":"en","type":"erratum","venue":"Scientific Data","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Université de Montréal","funders":"","keywords":"Metacommunity; Ecology; Space (punctuation); Geography; Computer science; Biology; Sociology; Demography","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":[0.005734165,0.002025507,0.001827043,0.005375003,0.003731768,0.006403821,0.003946198,0.004379805,0.1537523],"category_scores_gemma":[0.0702921,0.001232067,0.00166119,0.005073866,0.001709372,0.003345,0.003435168,0.008438027,0.1121083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003704035,"about_ca_system_score_gemma":0.009338379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03700019,"about_ca_topic_score_gemma":0.04591661,"domain_scores_codex":[0.9936565,0.000673305,0.001139233,0.0007483435,0.003318744,0.0004638729],"domain_scores_gemma":[0.9453334,0.01070256,0.002269386,0.004270187,0.03519716,0.002227291],"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":[0.00001295509,0.000002870472,0.00004010394,0.00004158542,0.000003414877,0.00003296473,0.000009660976,0.00001913371,0.00001676897,0.0003924404,0.9970527,0.002375503],"study_design_scores_gemma":[0.0000233902,0.00000711525,0.0004002414,0.0001818056,0.0000149795,0.0001134227,0.0000471097,0.0001189405,0.0001457775,0.001022453,0.9979055,0.00001927835],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001986145,0.0004776373,0.001715005,0.04452363,0.925294,0.0000447497,0.01648354,0.001523178,0.009739681],"genre_scores_gemma":[0.0116434,0.004509936,0.01698671,0.07532138,0.1752019,0.0005521184,0.05319466,0.007582162,0.6550077],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1537523,"threshold_uncertainty_score":0.5143527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09680895019397591,"score_gpt":0.3021538073879225,"score_spread":0.2053448571939466,"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."}}