{"id":"W3103778592","doi":"10.5751/es-11895-250415","title":"Collaborative research to inform adaptive comanagement: a framework for the Heʻeia National Estuarine Research Reserve","year":2020,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Ocean Service; University of Hawai'i at Mānoa; Hawaiʻi Institute of Marine Biology; Office for Coastal Management; National Oceanic and Atmospheric Administration; National Estuarine Research Reserve System","keywords":"Estuary; Library science; Geography; Ecology; Computer science; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002817637,0.00009973911,0.0001235939,0.00002627457,0.001404364,0.00006865009,0.0003756929,0.00009248175,0.0009093343],"category_scores_gemma":[0.0007808154,0.00007553837,0.00005440119,0.001157684,0.0006271622,0.000113206,0.005069403,0.0005014217,0.0002801227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001985312,"about_ca_system_score_gemma":0.00004284178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003057846,"about_ca_topic_score_gemma":0.002445562,"domain_scores_codex":[0.9982486,0.0001596496,0.0001556156,0.0003646631,0.0006145987,0.0004568967],"domain_scores_gemma":[0.9979275,0.001580091,0.0000302953,0.0001572686,0.0001651232,0.0001397368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002645012,0.0000972827,0.005088348,0.00002771208,0.0001560602,0.000001958501,0.01390348,0.0006220695,0.00002246545,0.1781089,0.7948908,0.006816509],"study_design_scores_gemma":[0.0004437642,0.0007284197,0.08941819,0.000005695237,0.00001140728,3.734816e-7,0.01027809,0.002966748,0.00001133599,0.09781687,0.7981913,0.0001277822],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1202562,0.0001658714,0.02655,0.5824649,0.0004269593,0.01051986,0.000171358,0.0001373349,0.2593075],"genre_scores_gemma":[0.9587118,0.0002116539,0.0189116,0.00872741,0.0002282326,0.001090082,0.00002529357,0.00001697791,0.01207693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8384556,"threshold_uncertainty_score":0.9998957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1135368650763938,"score_gpt":0.3857417118438907,"score_spread":0.2722048467674968,"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."}}