{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007526998,0.0002324253,0.0004279083,0.0000496943,0.001020507,0.000268343,0.0002298488,0.0001096932,0.0004440749],"category_scores_gemma":[0.000103256,0.0002011659,0.00003259268,0.0001012977,0.0001439847,0.0004574548,0.001965487,0.0001658984,0.00004047335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009394107,"about_ca_system_score_gemma":0.000009024628,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06967076,"about_ca_topic_score_gemma":0.7876919,"domain_scores_codex":[0.9982149,0.0001596846,0.0004838272,0.0004737731,0.000227916,0.0004399053],"domain_scores_gemma":[0.9993997,0.0001061617,0.0001247666,0.00022096,0.00001802774,0.0001303413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009478655,0.00004524679,0.9851914,0.00003757096,0.00001903751,0.00001976854,0.0008991816,0.000004293837,0.0001765176,0.0003022722,0.002536125,0.0106738],"study_design_scores_gemma":[0.0007252234,0.0003662283,0.9322526,0.00002498562,0.00002259872,0.000009147926,0.0005445326,0.05762638,0.000008162995,0.001738075,0.006372648,0.0003094616],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928854,0.000007753311,0.00002549829,0.003783053,0.0002101416,0.000419049,0.000004904394,0.00003933405,0.002624844],"genre_scores_gemma":[0.9983327,0.00001243002,0.0002790298,0.000260496,0.0003232805,0.0001057483,0.00002967244,0.00001651174,0.0006400645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7180212,"threshold_uncertainty_score":0.9365244,"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."}}