{"id":"W2165239045","doi":"10.1577/t05-280.1","title":"Importance and Predictability of Cannibalism in Rainbow Smelt","year":2007,"lang":"en","type":"article","venue":"Transactions of the American Fisheries Society","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"NOAA Sea Grant; National Oceanic and Atmospheric Administration; University of Vermont; U.S. Department of Commerce","keywords":"Cannibalism; Smelt; Predation; Biology; Population density; Population; Ecology; Fishery; Zoology; Fish <Actinopterygii>; Demography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003423558,0.0001619307,0.0001601816,0.0003952595,0.0002588086,0.0003996668,0.0001388142,0.0001585494,0.001108026],"category_scores_gemma":[0.001545405,0.0001237172,0.0001946703,0.0002539154,0.0002410983,0.0002030468,0.0004309515,0.0001955117,0.0001166575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006991313,"about_ca_system_score_gemma":0.0003198134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04613402,"about_ca_topic_score_gemma":0.1001947,"domain_scores_codex":[0.9998541,0.00002206875,0.00001088918,0.00004412772,0.00003916772,0.00002962482],"domain_scores_gemma":[0.9991061,0.000259111,0.0003075538,0.00004049651,0.0001602666,0.0001264012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003676339,0.000006953757,0.9965005,0.000003984606,0.00001771403,0.00002498801,0.00002983061,0.000826519,0.001345767,0.00001896739,0.00005566214,0.001132349],"study_design_scores_gemma":[5.370896e-7,0.000009851518,0.9981835,0.000001077828,0.000002507614,0.00001107489,0.00002903854,0.00164957,0.0000612445,0.00002114903,0.00002915692,0.00000128544],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99953,0.00001824692,0.0001263849,0.00001358151,0.000001211296,8.999625e-7,0.0000785681,0.000006493624,0.0002246914],"genre_scores_gemma":[0.9997652,0.000006100967,0.00005500556,0.000002755702,0.000001206313,7.535453e-7,0.00008194149,0.000001223085,0.00008581622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04613402,"threshold_uncertainty_score":0.09173101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006846459074478201,"score_gpt":0.2141469307135537,"score_spread":0.2073004716390755,"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."}}