{"id":"W2289758672","doi":"10.1098/rsif.2015.0435","title":"Connectivity, passability and heterogeneity interact to determine fish population persistence in river networks","year":2015,"lang":"en","type":"article","venue":"Journal of The Royal Society Interface","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Population; Population growth; Population dynamics of fisheries; Persistence (discontinuity); Extinction (optical mineralogy); Obstacle; Spatial heterogeneity; Population decline; Ecology; Watershed; Index (typography); Vital rates; Biology; Geography; Fish <Actinopterygii>; Habitat; Demography; Fishery; Computer science; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000681843,0.0001836169,0.0002318466,0.00101141,0.0003402811,0.0008807955,0.0003067855,0.000346265,0.001039681],"category_scores_gemma":[0.00685703,0.0001867455,0.0003158603,0.0005699584,0.0008521171,0.00128135,0.0006066279,0.000297489,0.00009103926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003445108,"about_ca_system_score_gemma":0.0001947721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004393298,"about_ca_topic_score_gemma":0.00786324,"domain_scores_codex":[0.9997904,0.00009044436,0.00001747085,0.00003994566,0.00002639871,0.00003539684],"domain_scores_gemma":[0.9946043,0.003417521,0.001271875,0.0002313607,0.0001986184,0.0002763804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006611311,0.00002623628,0.9665795,0.00002808965,0.0001834105,0.0001451983,0.0003286386,0.02203088,0.002005069,0.00231863,0.00009782445,0.00619036],"study_design_scores_gemma":[0.000009345867,0.0001106847,0.910629,0.00001616117,0.0001376553,0.0003529582,0.000656638,0.07880978,0.0004985214,0.008484579,0.0002659326,0.00002873269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983366,0.00003813645,0.001199473,0.00004400942,7.949258e-7,0.000001939819,0.00002249634,0.000006947766,0.0003495065],"genre_scores_gemma":[0.9996878,0.0000159709,0.0001955277,0.00000281472,0.000001778107,0.00000161206,0.00002214004,0.000002313571,0.0000701178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004393298,"threshold_uncertainty_score":0.008735478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02415111775011024,"score_gpt":0.2532234433188184,"score_spread":0.2290723255687081,"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."}}