{"id":"W7056190397","doi":"","title":"The effect of latitude on recruitment variability and first year growth of yellow perch (Perca flavescens) in Ontario","year":2000,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Laser Design and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Perch; Latitude; Population; Seasonality","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003995072,0.0001303301,0.0002696125,0.0005720835,0.001307859,0.000605174,0.0005255523,0.0002621566,0.001311464],"category_scores_gemma":[0.001502212,0.0002596635,0.0002084959,0.000695145,0.0007238542,0.0002579712,0.0005218566,0.0002568646,0.0002488426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007995608,"about_ca_system_score_gemma":0.00495231,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9253501,"about_ca_topic_score_gemma":0.9870808,"domain_scores_codex":[0.9997203,0.0000368232,0.00001384334,0.00007744011,0.00008237067,0.00006931228],"domain_scores_gemma":[0.998068,0.0003805423,0.0003804511,0.00007641906,0.0006505961,0.0004439617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002954808,0.00001929272,0.9882203,0.00002645087,0.00004279575,0.00009014647,0.002101114,0.000272244,0.004351546,0.0001064823,0.0007512794,0.003722814],"study_design_scores_gemma":[0.000001749308,0.000005446374,0.9994092,0.000001579901,0.000002833489,0.0000082248,0.0002756143,0.00005772243,0.00004177826,0.000006210193,0.0001882741,0.000001506056],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997565,0.0001584715,0.00009827867,0.00008883524,0.000005416525,0.000004570733,0.0006798317,0.000006400115,0.001393139],"genre_scores_gemma":[0.9979882,0.00007310591,0.00007464455,0.00002641804,0.000002554118,0.000005814091,0.0003803727,0.000005518711,0.001443303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07464987,"threshold_uncertainty_score":0.150179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004108822563652213,"score_gpt":0.1432560699719655,"score_spread":0.1391472474083133,"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."}}