{"id":"W4390227150","doi":"10.5751/es-14403-280430","title":"Geographic scale dependency and the structure of climate adaptation policy networks in San Francisco Bay","year":2023,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Collective action; Social capital; Corporate governance; Context (archaeology); Network governance; Scale (ratio); Collaborative governance; Stakeholder; Social network analysis; Environmental governance; Economic geography; Environmental resource management; Regional science; Geography; Business; Political science; Economics; Public relations; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001171064,0.0001195487,0.0001556282,0.001656904,0.001219771,0.001654103,0.0004491461,0.0002990775,0.00365308],"category_scores_gemma":[0.008499175,0.0001651881,0.0001266241,0.001398139,0.001543281,0.001530434,0.001548641,0.0004085911,0.0001299208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004263788,"about_ca_system_score_gemma":0.00163482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1538506,"about_ca_topic_score_gemma":0.1854773,"domain_scores_codex":[0.9994699,0.0001780777,0.00003127104,0.0001423318,0.00006879705,0.0001097354],"domain_scores_gemma":[0.9934,0.002281657,0.002446184,0.0003443432,0.0008225232,0.000705396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001934836,0.0001232549,0.8980613,0.00016079,0.0001107565,0.0003940144,0.01834874,0.01047749,0.001143958,0.02801566,0.003060664,0.03990988],"study_design_scores_gemma":[0.00001823076,0.00004830525,0.9674666,0.00008483562,0.00004847448,0.00006845659,0.0126636,0.007451281,0.0001995784,0.00444324,0.007486411,0.00002101323],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901764,0.0001349431,0.0007865351,0.0006801504,0.00000446139,0.00002415661,0.0001617568,0.00001485089,0.008016661],"genre_scores_gemma":[0.9990651,0.00007539388,0.0003002045,0.00001631741,0.000002263278,0.00001257331,0.00008605819,0.000001887469,0.0004403119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1538506,"threshold_uncertainty_score":0.3059102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003176709352642302,"score_gpt":0.1970167514815627,"score_spread":0.1938400421289204,"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."}}