{"id":"W4413054501","doi":"10.1038/s41597-025-05750-x","title":"Correction: Global Impacts Dataset of Invasive Alien Species (GIDIAS)","year":2025,"lang":"en","type":"erratum","venue":"Scientific Data","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Armed Forces","funders":"","keywords":"Alien; Ecology; Alien species; Invasive species; Geography; Data science; Biology; Computer science; Political science","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":[0.0008236357,0.0003328863,0.0004144683,0.00008145393,0.0003531768,0.0004072189,0.003744977,0.0002709736,0.124196],"category_scores_gemma":[0.0009623383,0.0003109801,0.00008741565,0.001477845,0.001347026,0.0005971063,0.005869132,0.000337527,0.00365123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009444748,"about_ca_system_score_gemma":0.0003647401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000867829,"about_ca_topic_score_gemma":0.01489185,"domain_scores_codex":[0.996377,0.0000780653,0.0005259415,0.001410618,0.001085969,0.0005224432],"domain_scores_gemma":[0.9952582,0.00006917838,0.0004198847,0.003999343,0.00005043472,0.0002030206],"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":[0.000009397503,0.00009852338,0.0006165862,0.00007074959,0.00002659418,0.000008965627,0.00003091734,0.000001337251,0.00009698685,0.00005793149,0.9984409,0.000541113],"study_design_scores_gemma":[0.0001447551,0.00002155717,0.009704911,0.000138391,0.00007769113,0.000008889268,0.0006971058,0.00004956073,0.0002544009,0.00004031236,0.9885877,0.0002746898],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001500363,0.0003248095,0.0000200709,0.0002849778,0.07665555,0.0002474607,0.567903,0.00004042186,0.3543736],"genre_scores_gemma":[0.0002645506,0.0003908761,0.00002867641,0.0001806106,0.0002065969,0.000006577603,0.6044522,0.000009401388,0.3944605],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1205448,"threshold_uncertainty_score":0.9999343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05863488910597562,"score_gpt":0.3023484650543872,"score_spread":0.2437135759484116,"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."}}