{"id":"W2624311282","doi":"10.1002/aqc.2775","title":"Examining horizontal and vertical social ties to achieve social–ecological fit in an emerging marine reserve network","year":2017,"lang":"en","type":"article","venue":"Aquatic Conservation Marine and Freshwater Ecosystems","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Context (archaeology); Interpersonal ties; Social network (sociolinguistics); Marine reserve; Social network analysis; Marine protected area; Multilevel model; Ecology; Marine conservation; Environmental resource management; Business; Economic geography; Geography; Sociology; Political science; Computer science; Economics; Social capital; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002056591,0.0002053356,0.0001503539,0.002402831,0.002493077,0.002881894,0.0005509429,0.0006243858,0.004633706],"category_scores_gemma":[0.0119699,0.0001170104,0.000197853,0.002022946,0.001607117,0.0026012,0.003258616,0.0006376869,0.0002073692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002875239,"about_ca_system_score_gemma":0.001207495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01008021,"about_ca_topic_score_gemma":0.02316364,"domain_scores_codex":[0.9986482,0.0006645877,0.00007261363,0.0001662622,0.0002162959,0.0002319969],"domain_scores_gemma":[0.9875436,0.005097166,0.003987754,0.0003850312,0.00102857,0.001957822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008949126,0.0003377764,0.9387124,0.00009296961,0.00008331103,0.0004160236,0.02381045,0.001816468,0.0007212476,0.01346019,0.0004692715,0.01999043],"study_design_scores_gemma":[0.00001179389,0.000171667,0.8959252,0.00009341822,0.00005769761,0.0001990083,0.08035614,0.01300659,0.000335382,0.006851428,0.002971585,0.00002015572],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915176,0.000037822,0.0008695656,0.0001748265,0.00000255549,0.00003166445,0.00004136335,0.000003203283,0.007321327],"genre_scores_gemma":[0.9994395,0.00001500413,0.0003053286,0.000006429476,0.000001221794,0.00001640214,0.00002244465,5.824721e-7,0.0001931779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01008021,"threshold_uncertainty_score":0.02086139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06907435790652364,"score_gpt":0.2802690596354589,"score_spread":0.2111947017289353,"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."}}