{"id":"W2939201034","doi":"10.1002/ecs2.2701","title":"Long‐term population dynamics of dreissenid mussels (<i>Dreissena polymorpha</i> and <i>D. rostriformis</i>): a cross‐system analysis","year":2019,"lang":"en","type":"article","venue":"Ecosphere","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Museum of Nature","funders":"U.S. Army Corps of Engineers; Deutsche Forschungsgemeinschaft; U.S. Geological Survey; Belarusian Republican Foundation for Fundamental Research; Minnesota Department of Natural Resources; New York State Department of Environmental Conservation; U.S. Army; U.S. Environmental Protection Agency; National Science Foundation","keywords":"Dreissena; Zebra mussel; Population; Ecology; Biology; Invasive species; Range (aeronautics); Population decline; Bivalvia; Fishery; Mussel; Mollusca; Habitat; 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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002270583,0.0001852354,0.0003709759,0.00003106859,0.0001159762,0.00003344446,0.0001881422,0.000180343,0.0156446],"category_scores_gemma":[0.000009149181,0.0001684081,0.0001280004,0.0004566089,0.0001180868,0.0003158493,0.0001232733,0.0001201459,0.001459625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001848824,"about_ca_system_score_gemma":0.00001103796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001023268,"about_ca_topic_score_gemma":0.004007981,"domain_scores_codex":[0.9986631,0.00005132768,0.0004050563,0.0003806035,0.000213504,0.0002864142],"domain_scores_gemma":[0.9992244,0.00004096827,0.0002554427,0.0003650032,0.00001284195,0.0001013479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002461457,0.000058893,0.9960372,0.0000349584,0.0000703876,0.000008964005,0.00008128166,0.0006288365,0.0007734065,0.0001555992,0.0002852751,0.001840528],"study_design_scores_gemma":[0.0004331583,0.00007323812,0.9803908,0.00001322893,0.000248858,0.00001830292,0.0001056611,0.01751078,0.0009604741,0.0000386262,0.00001142967,0.0001954853],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890984,0.00003837868,0.0002654922,0.00003414213,0.0001498377,0.000305471,0.00003415499,0.00004294813,0.01003119],"genre_scores_gemma":[0.9949985,0.000005343842,0.0003622457,0.00005243123,0.00001652902,0.000008619767,0.0001085554,0.00001660774,0.004431227],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01688194,"threshold_uncertainty_score":0.9993178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003343479085658343,"score_gpt":0.2112050329652373,"score_spread":0.2078615538795789,"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."}}