{"id":"W3203116761","doi":"10.1007/s10661-021-09463-7","title":"Distinctive patterns and signals at major environmental events and collapse zone boundaries","year":2021,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; University of Toronto; Magyar Agrár- és Élettudományi Egyetem","keywords":"Relative species abundance; Abundance (ecology); Species richness; Ecology; Climate change; Environmental change; Scale (ratio); Cluster (spacecraft); Environmental science; Physical geography; Geography; Biology; Cartography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007487276,0.0002250092,0.0002825285,0.002824382,0.0002663123,0.0004126657,0.0002379148,0.0002532433,0.0009020314],"category_scores_gemma":[0.003234103,0.0001240624,0.0002485387,0.001810855,0.0005509179,0.0006405999,0.0007919514,0.0003424234,0.0001308053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002501725,"about_ca_system_score_gemma":0.0001737877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003567136,"about_ca_topic_score_gemma":0.004989257,"domain_scores_codex":[0.9996268,0.00008170362,0.00003982205,0.0001023239,0.00008758884,0.0000617808],"domain_scores_gemma":[0.997861,0.0006791137,0.0006867618,0.000132696,0.0004074124,0.0002331354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001688834,0.00004636413,0.9756781,0.00004073597,0.000063739,0.0001366106,0.0008085782,0.002141442,0.008110432,0.000542041,0.0001595713,0.01210356],"study_design_scores_gemma":[0.000002116591,0.00002690112,0.9952814,0.000004920873,0.000009641367,0.00004827755,0.000256311,0.003272644,0.0006294214,0.0002130148,0.0002454136,0.00001000397],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985381,0.00004743654,0.000841969,0.00001217786,0.00000163985,0.000005463092,0.0001950043,0.00001377292,0.0003445316],"genre_scores_gemma":[0.9989831,0.00001746413,0.0005030032,0.000002373382,0.00000296894,0.000005619324,0.0004143975,0.000003516262,0.00006755544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003567136,"threshold_uncertainty_score":0.007092714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004873498339530734,"score_gpt":0.2253302080011911,"score_spread":0.2204567096616603,"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."}}