{"id":"W4313037001","doi":"10.5751/es-13536-270406","title":"How the qualities of actor-issue interdependencies influence collaboration patterns","year":2022,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Interdependence; Environmental governance; Corporate governance; Collaborative governance; Similarity (geometry); Interdependent networks; Exponential random graph models; Social network analysis; Computer science; Knowledge management; Business; Sociology; Graph; Random graph; Artificial intelligence","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":[0.02617403,0.0007061438,0.001040136,0.006427225,0.001422798,0.005242247,0.00157668,0.0009629055,0.003873782],"category_scores_gemma":[0.1091073,0.0006835903,0.003605033,0.006449071,0.003159669,0.006994218,0.004554362,0.001536633,0.0003567186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003279912,"about_ca_system_score_gemma":0.003297739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01103862,"about_ca_topic_score_gemma":0.0112458,"domain_scores_codex":[0.9610932,0.02842759,0.002194128,0.004411958,0.002918165,0.000954942],"domain_scores_gemma":[0.8044205,0.1678989,0.01266987,0.008199412,0.00505848,0.001752804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004406596,0.0001584593,0.8001044,0.00609022,0.01943938,0.0005574929,0.02716518,0.01431652,0.001485619,0.03401506,0.001792562,0.09443438],"study_design_scores_gemma":[0.0002520541,0.0006705239,0.7332342,0.00556819,0.02026426,0.000793864,0.03624548,0.02924355,0.002597751,0.1397905,0.03098589,0.0003537246],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8829679,0.0210603,0.06847427,0.00417574,0.0001979721,0.0004944015,0.002109911,0.0001621261,0.02035736],"genre_scores_gemma":[0.990787,0.001889196,0.006212517,0.0001167488,0.00001877659,0.0001228869,0.0004432877,0.00003954601,0.0003700722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02617403,"threshold_uncertainty_score":0.1384231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00986969605017012,"score_gpt":0.203744771479643,"score_spread":0.1938750754294729,"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."}}