{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001444897,0.0004243295,0.0004599381,0.00004095745,0.001113415,0.0006606493,0.00225563,0.0002935483,0.03998498],"category_scores_gemma":[0.0007495449,0.0004005561,0.00009548197,0.0004802011,0.001410703,0.0005054598,0.005629086,0.0007411514,0.0009997898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001053791,"about_ca_system_score_gemma":0.0001059561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003578841,"about_ca_topic_score_gemma":0.008032908,"domain_scores_codex":[0.9965091,0.0001675343,0.0004198493,0.00168739,0.0006378841,0.0005782881],"domain_scores_gemma":[0.9971685,0.0001069078,0.0003051444,0.002035824,0.00001778735,0.0003658277],"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":[0.00001353484,0.0001020269,0.0002449874,0.00005020217,0.00003074385,0.000004350522,0.00009395222,8.007014e-7,0.0001386807,0.0003255093,0.9962395,0.002755661],"study_design_scores_gemma":[0.0002562527,0.00006504684,0.008071772,0.0000343351,0.0001452911,0.00001918271,0.002230766,0.002238872,0.00001584373,0.0000643261,0.9864681,0.0003901597],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0008293369,0.002290985,0.00685396,0.01945201,0.1599444,0.003779867,0.6054987,0.0004457852,0.200905],"genre_scores_gemma":[0.0008174335,0.0004790034,0.004482979,0.0006625323,0.0008500766,0.0001454287,0.3688866,0.00006324457,0.6236127],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.4227078,"threshold_uncertainty_score":0.9998446,"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."}}