{"id":"W4210535526","doi":"10.3897/neobiota.71.75711","title":"Predatory ability and abundance forecast the ecological impacts of two aquatic invasive species","year":2022,"lang":"en","type":"article","venue":"NeoBiota","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of Windsor","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; University of Windsor","keywords":"Brown trout; Salmo; Biology; Predation; Ecology; Carcinus maenas; Predator; Abundance (ecology); Interspecific competition; Apex predator; Intraguild predation; Trophic level; Invasive species; Introduced species; Fishery; Vital rates; Catch per unit effort; Benthic zone; Population; Crustacean; Decapoda; Population growth; Fish <Actinopterygii>","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000342312,0.0003356266,0.0001616025,0.0005680827,0.0001128143,0.0003600258,0.0001777265,0.000252449,0.0006325051],"category_scores_gemma":[0.001076891,0.0001541871,0.0002945059,0.0002417598,0.0001501419,0.0003984109,0.0004268206,0.0001913557,0.0001458181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000317199,"about_ca_system_score_gemma":0.0001492176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006235364,"about_ca_topic_score_gemma":0.01415617,"domain_scores_codex":[0.9999192,0.00001295462,0.000006753886,0.00003059508,0.00001560862,0.00001481968],"domain_scores_gemma":[0.9994723,0.0001164945,0.0002351139,0.00003174915,0.00008683142,0.00005752352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005305415,0.00002453886,0.9773876,0.00001581985,0.00005007818,0.00005516896,0.0000768509,0.01140366,0.00732999,0.00005426001,0.00005592259,0.00349297],"study_design_scores_gemma":[0.000001673936,0.0000671563,0.9620431,0.000004072693,0.00002386671,0.00006865444,0.0001368184,0.03665846,0.0008080712,0.00007281798,0.0001081995,0.000007137248],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992254,0.00002011805,0.0004124836,0.000008309088,5.582653e-7,0.000002199316,0.00007846958,0.00001006945,0.0002423304],"genre_scores_gemma":[0.9994135,0.00001378556,0.0003672997,0.000003041428,7.735648e-7,0.00000205653,0.0001217615,0.000001637332,0.00007629626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006235364,"threshold_uncertainty_score":0.01239812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01403792730318411,"score_gpt":0.2196293499532866,"score_spread":0.2055914226501024,"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."}}