{"id":"W2588339041","doi":"10.1139/cjfas-2016-0254","title":"Quantifying the spatial scale of common carp (<i>Cyprinus carpio</i>) recruitment synchrony","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Animal Ecology and Behavior Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Common carp; Latitude; Cyprinus; Spatial ecology; Environmental science; Biology; Temporal scales; Precipitation; Ecology; Geography; Fishery; Fish <Actinopterygii>; Meteorology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003771643,0.0001021014,0.0001838035,0.0007289919,0.0002972823,0.0003311372,0.0001523232,0.0001082555,0.0005531334],"category_scores_gemma":[0.001235349,0.000124769,0.0001193476,0.0005240651,0.000332589,0.0003207325,0.0004857099,0.000133907,0.00008940568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003225438,"about_ca_system_score_gemma":0.0002550037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01565589,"about_ca_topic_score_gemma":0.04200074,"domain_scores_codex":[0.9998041,0.00003263499,0.00001600202,0.0000942957,0.00002882556,0.00002418395],"domain_scores_gemma":[0.9988462,0.0002485003,0.0005871445,0.00006743967,0.0001501304,0.0001006068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004670078,0.00001071545,0.9817555,0.00001927705,0.00003579228,0.00003195315,0.0003402909,0.0004370997,0.01248378,0.00003233252,0.00006828416,0.004738286],"study_design_scores_gemma":[5.640089e-7,0.00000898962,0.9994863,0.000001448584,0.000003991895,0.00001614037,0.0001034509,0.0001528811,0.0001635125,0.00001232812,0.00004896387,0.000001391857],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993982,0.00005199475,0.0001926489,0.000007369629,7.210865e-7,0.000002560577,0.00007644913,0.000003922733,0.0002660496],"genre_scores_gemma":[0.9995667,0.00003845599,0.0001963547,0.000004905191,0.000002041565,0.000005600558,0.0001112786,0.00000195745,0.00007265693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01565589,"threshold_uncertainty_score":0.03112948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08310473051600306,"score_gpt":0.2947088286669681,"score_spread":0.211604098150965,"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."}}