{"id":"W4379185062","doi":"10.1007/s10980-023-01690-2","title":"Integrating seascape resistances and gene flow to produce area-based metrics of functional connectivity for marine conservation planning","year":2023,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada; Dalhousie University","funders":"","keywords":"Seascape; Biological dispersal; Landscape connectivity; Ecology; Context (archaeology); Landscape ecology; Genetic structure; Marine protected area; Population; Geography; Biology; Habitat; Genetic variation","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003210162,0.00009084743,0.000159182,0.00007859433,0.0001764097,0.000006886345,0.0000694846,0.00004883834,0.0002015219],"category_scores_gemma":[0.0004096393,0.00008560276,0.00002532539,0.0003317863,0.00009901277,0.00005830609,0.0002055446,0.00004781162,0.00002350142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006540964,"about_ca_system_score_gemma":0.000004650821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000033494,"about_ca_topic_score_gemma":0.0004648638,"domain_scores_codex":[0.9992564,0.00003357495,0.0001284088,0.0002824389,0.0001267096,0.0001724236],"domain_scores_gemma":[0.9992284,0.0005538108,0.00007439972,0.00009135692,0.00001145417,0.00004058003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001060696,0.00002857156,0.9772168,0.00001877192,0.00001708998,0.000001885401,0.0001266263,0.006028385,0.004768206,0.000008901447,0.01106225,0.0006164694],"study_design_scores_gemma":[0.0004116439,0.000191034,0.9804211,0.00000471369,0.00001739153,9.686665e-7,0.0002603291,0.0146799,0.002985991,0.0001088548,0.0008260756,0.00009202676],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969394,0.00001698693,0.001132205,0.0009740391,0.0001479392,0.0003126681,0.0000556568,0.00003448474,0.0003866248],"genre_scores_gemma":[0.9843218,0.000007718083,0.01501814,0.0002894599,0.00002341108,0.00005403818,0.00008156583,0.000005898659,0.0001979172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01388593,"threshold_uncertainty_score":0.3490779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02820125980207905,"score_gpt":0.2307813314768164,"score_spread":0.2025800716747373,"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."}}