{"id":"W2104590144","doi":"10.1890/13-0499.1","title":"Combining demographic and genetic factors to assess population vulnerability in stream species","year":2014,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metapopulation; Tributary; Ecology; Population; Climate change; Resistance (ecology); Environmental science; Environmental change; Geography; Biology; Biological dispersal","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":[0.001127321,0.0003516863,0.0002226253,0.001103836,0.000316528,0.0004893533,0.0003675976,0.0004151982,0.000525793],"category_scores_gemma":[0.003237549,0.0002007184,0.0004757711,0.0006212347,0.0003387078,0.0007127669,0.0007455479,0.0002856473,0.00003688741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008050105,"about_ca_system_score_gemma":0.00041304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01476771,"about_ca_topic_score_gemma":0.02912361,"domain_scores_codex":[0.9997482,0.0001277721,0.0000172621,0.0000560704,0.00003103206,0.00001971149],"domain_scores_gemma":[0.9989625,0.0005234146,0.0002637244,0.00007874547,0.00008617081,0.00008537914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003850317,0.00004199052,0.5442281,0.00001488812,0.0001929961,0.00005523626,0.0001411424,0.4461468,0.0009075408,0.001494611,0.00008963583,0.006648509],"study_design_scores_gemma":[0.000007611056,0.00009616666,0.1388563,0.000008575411,0.00005303019,0.00007304255,0.0001596263,0.8570348,0.0004171195,0.002966072,0.0003038984,0.00002369929],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811374,0.00004729205,0.01795695,0.00007680043,0.00000261201,0.00002081403,0.0002152542,0.00003816151,0.0005048446],"genre_scores_gemma":[0.9941104,0.00002665734,0.005614977,0.00001274171,0.000002113963,0.00001323705,0.0001059368,0.000003354968,0.000110517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01476771,"threshold_uncertainty_score":0.02936351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02642852059545401,"score_gpt":0.2552278052788391,"score_spread":0.2287992846833851,"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."}}